Javier Garcia Lopez, Paula Benedetti, Luis Puente Maest and Javier de Miguel Diez.

The Volume reduction in COPD (COPD) ‘Effective in all variants’. However, it does require a comprehensive study of patients who can benefit from these treatments, as explained by pulmonologists in Gregorio Maranon Hospital Who participated in the new Interhospital conference on pulmonology in Madridorganized by medical writing.

During the meeting, sponsored by Neumomadrid Foundation In cooperation with GSK s Oxymsa Nippon gasesA review of treatment options for patients with severe COPD, whose daily habits are limited, was conducted. He explained that “the patient expresses this great feeling of lack of air and the need to breathe very superficially.” Paola BenedettiDr., a medical specialist in the Respiratory Service of the Gregorio Marañone Hospital, has focused on the basics and indications for these alternatives.

Discussion table on volume reduction in severe COPD.

The main goal, as explained by the expert, is “a little more help” to the patient, that is, Reduce hyperinflation Improve respiratory mechanics and diaphragm muscle function. Also, improving the elastic contraction of the lung, favoring the gas exchange capacity of the remaining lung tissue or reversing the chronic decrease in the supply of tissues with oxygen.

Like all treatment, Benedetti warned, Size reduction has indications and contraindications. The first is that he is a patient with severe emphysema, with “severe” shortness of breath or who meets certain functional criteria. Among the contraindications, on the other hand, we find the presence of bronchiectasis or cancer as well Continuation of the tobacco habit or treatment with prednisone, among others.

The specialist explained that the types of lung volume reduction Valves for acute emphysema with intact incisionsAnd steam in acute emphysema with attached fissures.

One of the primary advantages of valves, the pulmonologist emphasized, is that they are reversible, while steam is “not a reversible option.” At this point, the expert indicated the speed with which this technique is being applied, not the exception to it Possible complications such as shortness of breath, fever or severe pneumonia.

“An essential thing is Careful selection of patientsthe main candidate to refer to these treatments, “notes the specialist, who emphasized that it is necessary”Offer benefit over risk. Another important aspect, he added, “is that there is no age limit and does not interfere with lung transplantation.”

Javier García-López, Paola Benedetti during the Inter-Hospital Conference on Pulmonology.


The experience of cashew nuts in reducing volume in chronic obstructive pulmonary disease

On the table, runs it Luis Puente MaestoHead of the Department of Pulmonology; s Javier de Miguel DiezHead of the Respiratory Service Division. I also intervened Javier Garcia Lopezwho is also the center’s chief of pulmonology services, which chronicled the hospital’s experience with this technology through a clinical case that demonstrated how the specialists worked.

In this case a 71-year-old woman, a former smoker, with a Long-term chronic obstructive pulmonary disease And that he has had two incomes in the past three years. With her, and with any patient, “the potential causes of exclusion must be carefully evaluated,” Garcia explained, emphasizing that “The patient must know the risks before deciding whether to seek treatment“.

After evaluating a file Emphysema via computed tomographyAn echocardiogram, which cannot be evaluated, is performed Pulmonary arterial hypertension Very concretely, the specialist recalls. At this point, he highlights that one of the contraindications, pulmonary hypertension, is the only one available to the patient, so “you have to go further and have a catheterization”, as pulmonologists assure it is neither severe nor moderate, so you can continue with treatment .

“Knowing that it’s a filter, we have to choose how we handle it: whether with valves or steam,” says the specialist. “We always prefer valves because they are reversible in case of complications,” he adds. The patient, remember, was laid Three valves four millimeters. All this just three months after he went to counseling. He remembers that after four days without immediate complications, he was discharged from the hospital. However, ten days after discharge, the patient went to the emergency department referring to a Source That after conducting a study, it was confirmed that it was LSD . atelectasisAlthough his shortness of breath improved.

Since 2015, the specialist noted, The hospital treated 21 patients through coils, valves and steam; With subjective improvement in 80 percent of patients, even after 5 years. However, these procedures “are not free,” Garcia emphasized, so they are associated with risks. In the hospital experience, there was a case of pneumothorax, a massive hemoptysis patient And three patients with serious infections. However, the pulmonologist stressed that “volume reduction is effective in all of its variants,” noting the need for a “comprehensive study” of each case because they are very fragile patients.

Javier de Miguel Diez, Luis Puente Maisto, Paula Benedetti and Javier Garcia Lopez.

Although it may contain statements, statements, or notes from health institutions or professionals, the information in medical writing is edited and prepared by journalists. We recommend the reader to consult a health professional for any health-related questions.

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Introduction

Chronic obstructive pulmonary disease (COPD) is a clinical syndrome that features chronic respiratory symptoms and structural pulmonary abnormalities leading to lung function impairment with persistent airflow limitation.1 A recent study indicated that the overall prevalence of spirometry defined for COPD was 8.6% of adults in China, including 11.9% of men aged 40 years or older. The acute exacerbation of COPD (AECOPD) is a key factor that affects the disease prognosis and leads to hospitalization. Thus, AECOPD-related morbidity and mortality should be given more attention.2,3 Pulmonary hypertension (PH) is a common and severe comorbidity of COPD that results in an increased risk of hospitalization, reduced exercise capacity, and shorter survival. Right-heart catheterization (RHC) is the “gold standard” for the diagnosis of PH. However, RHC related significant risks and its difficulty of placement limits this procedure in patients with PH. Echocardiography is a noninvasive method that is widely used to assess PH in patients with AECOPD.4 A tricuspid regurgitant jet ≥3 m/s tested by echocardiography is diagnosed as PH, which may lead to underdetermined diagnoses of PH.5 Moreover, pulmonary artery systolic pressure detected by echocardiography is poorly correlated with the mean pulmonary artery pressure (mPAP) in severe COPD. A main pulmonary artery to ascending aorta diameter ratio (PA/A) of greater than one has been reported to be a promising indicator for revealing PH.6,7 Furthermore, an increased ratio of PA/A was closely associated with the poor survival of patients with COPD, particularly in individuals with moderate-to-severe cases.8 Nevertheless, the impact of the PA/A ratio in AECOPD remains to be elucidated. In this present study, we aim to disclose the associations between the PA/A ratio and clinical outcomes in hospitalized patients with AECOPD.

Patients and Methods

Study Population

This retrospective observational study was conducted at the Yijishan Hospital affiliated with the Wannan Medical College and was approved by the Research Ethics Committee of Yijishan Hospital. The clinical data of patients was maintained with confidentiality and in compliance with the Declaration of Helsinki. Written informed consent from patients was waived due to the retrospective nature of this study. Consecutive AECOPD patients admitted to the Department of Respiratory Medicine and Respiratory Intensive Care Units (RICU) were reviewed from September 2017 to July 2021. Patients with advanced lung cancer, pneumothorax, stroke, pneumonia, diffuse interstitial lung disease, hemodialysis, or left-heart failure, as well as those who only accepted palliative therapy, or had a lack of chest computed tomography (CT) images, were excluded from the final analysis.

AECOPD is defined as COPD with an acute worsening of respiratory symptoms (typically cough, dyspnea, increased sputum volume, and/or sputum purulence) requiring additional treatments.9 Indications for RICU admission were made according to the expert consensus released in 2014 on AECOPD in China.10 In brief, these consisted of a significant increase in symptom intensity (severe dyspnea, changes in mental status, moderate or severe hypoxemia with or without hypercapnia), failure of an exacerbation to respond to initial medical management, hemodynamic instability, and a patient requiring mechanical ventilation (MV). The treatment success of AECOPD patients was defined as improvement in the clinical condition when discharged from the hospital. Conversely, treatment failure was thought to occur as an event of in-hospital death or deterioration of the clinical condition prior to discharge.

Demographic characteristics, including gender, age, the age-adjusted Charlson Comorbidity Index (aCCI), length of stay, body mass index (BMI) and in-hospital death, were collected. Laboratory tests, including an arterial blood gas analysis (pH value, oxygenation index, the ratio of arterial partial pressure of oxygen to the fraction of inspired oxygen), PaCO2, and the blood lactate level), hemoglobin, blood red cell distribution width (RDW), D-dimer, brain natriuretic peptide (BNP), fibrinogen (Fib), and blood platelet (PLT), were initially recorded after admission. The percentage of ICU admissions requiring invasive MV (IMV) was also calculated. A chest CT was performed when the patient was admitted to the hospital. The procedure for measuring the pulmonary artery (PA) diameter and PA/A ratio determined by the chest CT conformed to a previous study.6 Briefly, the PA diameter and ascending aorta diameter were averaged from two perpendicular measurements at the PA bifurcation level collected from the same chest CT images, as shown in Figure 1.

Figure 1 Diameters of the PA and A were determined by CT scan at the PA bifurcation. (A) PA/A ratio < 1; (B) PA/A ratio > 1.

Abbreviations: A, aorta; PA, pulmonary artery.

Statistical Analysis

Continuous data were analyzed using a normal distribution test prior to further analysis. Continuous data are indicated as the mean (standard deviation [SD]) or median (inter-quartile range [25,75]). Categorical variables are presented as the number (n) or percentage. Continuous variables were analyzed using the independent t-test or the Mann-Whitney U-test, and categorical variables were analyzed using a Chi-square test. The logistic regression model was used as a multivariate analysis to reveal the independent risk factors of in-hospital worst outcomes in patients with AECOPD. The Kaplan–Meier survival method was used to analyze the effect of the PA/A ratio on outcomes of AECOPD patients. A Log rank test was applied to appraise the statistical differences between the two survival curves. A receiver operating characteristic (ROC) curve analysis was conducted to evaluate factors predicting an in-hospital worst outcome. A P value less than 0.05 was considered statistically significant. The statistical analyses were performed using SPSS for Windows (release 22.0, IBM Corporation, USA).

Results

As indicated in Figure 2, a total of 229 patients with AECOPD were reviewed. According to the inclusion criteria and exclusion criteria, 111 patients were excluded due to the condition being combined with advanced lung cancer (n = 10), pneumothorax (n = 4) stroke (n = 5), pneumonia (n = 29), diffuse interstitial lung disease (n = 7), hemodialysis (n = 6), left-heart failure (n = 19), palliative therapy (n = 23), and a lack of CT images (n = 10). Ultimately, 118 eligible individuals were reviewed in this study: 74 individuals with a PA/A ratio <1 and 44 individuals with PA/A ratio ≥1. The outcomes of 21 patients were treatment failures, and 97 patients were treatment successes when discharged from the hospital.

Figure 2 A flowchart of this study.

Characteristics of the AECOPD Patients with a PA/A Ratio <1 or a PA/A Ratio ≥1

The pH value in the PA/A ratio ≥1 group was significantly lower than that in the PA/A ratio <1 group (p = 0.026). Remarkably, the PA/A ratio ≥1 group had a significantly higher value of PaCO2, RDW, BNP, PA diameter, and RICU admissions, as well as worse outcomes than the PA/A ratio <1 group (P < 0.05). However, there were no significant statistical differences for the other indicators between the two groups (Table 1).

Table 1 Characteristics of AECOPD Patients with Different PA/A Ratio

Clinical Features of the AECOPD Patients with Treatment Failure

As indicated in Table 2, compared to the treatment success group, the treatment failure group had a much lower pH value (7.34 ± 0.11 vs 7.28 ± 0.13, respectively, p = 0.040) and less count of PLT (median 167 × 109/L vs 130 × 109/L, respectively, p = 0.018). The treatment failure group had higher levels of D-dimer and BNP compared with the improved group (P < 0.05). In addition, the percentage of RDW, rate of RICU admissions, and the proportion of IMV in the treatment failure group were significantly higher than that in the improved group (P < 0.05). Notably, the PA diameter and PA/A ratio were significantly increased in the treatment failure group than in the improved group (mean PA diameter: 3.71 vs 3.22, p = 0.001; mean PA/A ratio: 1.09 vs 0.89, p < 0.001).

Table 2 Characteristics of Treatment Success Group and Treatment Failure Group in Severe AECOPD

A PA/A Ratio ≥1 Was an Independent Risk Factor for Treatment Failure in AECOPD

The multivariate analysis indicated that the PA/A ratio ≥1 (OR value = 6.129, 95% CI: 1.665–22.565, p = 0.006) and IMV (OR value = 10.798, 95% CI: 2.072–56.261, p = 0.005) were two independent risk factors for treatment failure in patients with AECOPD. Although the RDW, D-dimer, PLT, and RICU admissions had observed significant differences between the two groups according to the univariate analysis, they did not reach significant statistical differences according to the multivariate analysis (Table 3). Additionally, the Kaplan–Meier survival analysis indicated that patients with a PA/A ratio ≥1 had worse outcomes than patients with a PA/A ratio <1 during hospitalization (HR = 5.277, 95% CI: 2.178–12.78, p < 0.001) (Figure 3).

Table 3 Multivariate Analysis for Risk Factors of Treatment Failure in AECOPD

Figure 3 Effect of the PA/A ratio on the outcomes of AECOPD patients.

Abbreviation: PA/A ratio: main pulmonary artery to ascending aorta diameter ratio.

Note: A Kaplan–Meier survival curve analysis was performed, and a Log rank test was used, and a P < 0.05 was considered statistically significant.

Predictors of Treatment Failure in Hospitalized Patients with AECOPD

Figure 4 displays the diverse ROC curve of the PA/A ratio, the PA value, the BNP, and the RDW for predicting treatment failure in hospitalized patients with AECOPD. Even though there were no significant statistical differences observed, the area under the curve (AUC) value of the PA/A ratio was numerically larger than that of the other indicators. The best cut-off value of the PA/A ratio for predicting treatment failure was 0.925. The sensitivity was 81.82%, and the specificity was 66.67% (Table 4).

Table 4 ROC Curve Analysis for Factors Predicting Treatment Failure

Figure 4 PA/A ratio, PA value, BNP, and RDW for predicting treatment failure in hospitalized patients with AECOPD.

Abbreviations: PA/A ratio, main pulmonary artery to ascending aorta diameter ratio; PA, main pulmonary artery; RDW, blood red cell distribution width; BNP, brain natriuretic peptide.

Note: The receiver operating characteristic (ROC) curve analysis was conducted to evaluate factors predicting in-hospital worst outcomes.

Discussion

The strengths of this study were its primary findings. First, patients with a PA/A ratio ≥1 had significantly higher PaCO2, RDW, BNP, PA diameters, RICU admission rates, and proportions of treatment failure. Second, the PA diameter and PA/A ratio were significantly increased in the treatment failure group compared with the treatment success group. Third, a PA/A ratio ≥1 was an independent risk factor for treatment failure in patients with AECOPD. The Kaplan–Meier survival analysis indicated that patients with a PA/A ratio ≥1 had worse outcomes than patients with a PA/A ratio <1 during hospitalization. Finally, the PA/A ratio may be a promising factor for predicting treatment failure in hospitalized AECOPD patients.

A previous study indicated that the relative pulmonary arterial enlargement (PA/A ratio >1 on CT scanning) predicted hospitalization for AECOPD, and a PA/A ratio >1 with increased blood troponin levels shared close associations with increased respiratory failure, ICU admission, and in-hospital mortality.11 Iliaz et al reported that the PA/A ratio was related to the frequency of hospitalizations and exacerbations due to COPD in one year after hospital discharge.12 However, the relationships between a PA/A ratio >1 alone and ICU admission or in-hospital mortality are still unclear. In the present study, we found that AECOPD patients with a PA/A ratio ≥1 had a decreased pH value and increased PaCO2 compared with patients with a PA/A ratio <1, implicating increased type II respiratory failure in patients with a PA/A ratio ≥1. A decreased pH value and increased PaCO2 may contribute directly to pulmonary vasoconstriction leading to a rise in pulmonary vascular resistance and pulmonary arterial pressure.13 In addition, we also disclosed a higher percentage of RICU admissions and a markedly increased rate of treatment failure in hospitalized AECOPD patients with a PA/A ratio ≥1. Thus, an increased PA/A ratio was associated with severity and worse outcomes in inpatients with AECOPD. Many studies have revealed that the RDW is a valuable biomarker for predicting pulmonary hypertension and its associated prognosis.14–16 In a previous study performed by our group, we indicated that the RDW shared positive relationships with the PA/A ratio in patients with pH secondary to COPD.17 Similar to previous studies, we found an increase in the RDW in AECOPD patients with a PA/A ratio ≥1. Likewise, the serum level of BNP was drastically elevated. BNP is an important indicator for identifying risk categories in PH. Increased BNP is related to a worse outcome of PH.18

In this study, we demonstrated that there was a decreased pH value, lower number of PLTs, and increases in the RDW, D-dimer, BNP, PA diameter, and PA/A ratio in AECOPD patients with treatment failure compared with the improved group. Patients with treatment failure also required more IMV supports and intensive care. It was reported that lower pH values were associated with short or long mortality in hospitalized AECOPD patients.19,20 RDW is an indicator that reflects the heterogeneity of red blood cell volume. Recently, RDW was found to be an independent negative prognostic factor closely associated with adverse outcomes in hospitalized AECOPD patients.21,22 Dysregulation of erythrocyte homeostasis and metabolic imbalance may account for significant changes in the RDW in AECOPD patients. However, the underlying pathophysiological mechanisms remain unknown.23 A hypercoagulable state is a feature of hospitalized AECOPD patients. An increased D-dimer level is not only an important independent risk factor for pulmonary embolism in inpatients with AECOPD but also a predictor of higher mortality in stable COPD patients.24,25 Cardiac failure is a frequent complication of AECOPD, deeply affecting exercise tolerance and life span in patients with COPD. BNP is widely used to evaluate heart function. BNP can be used to risk-stratify, and an elevated BNP is associated with a higher MV use and worse outcomes in AECOPD patients.26 An increased PA/A ratio is positively correlated with COPD severity. Previous studies have reported that pulmonary artery enlargement detected by CT is a risk predictor for a severe exacerbation of COPD.27,28 Intriguingly, the PA/A ratio is an important determinant of mortality in moderate-to-severe COPD.8 In our present study, we found that a PA/A ratio ≥1 was a strong independent risk-factor of in-hospital treatment failure in patients with AECOPD. In addition, the PA/A ratio might be a better predictor of in-hospital treatment failure compared with other indicators including the PA value, BNP, and RDW. Taken together, the results of the present study provide additional evidence for a close association between the PA/A ratio and the outcome of AECOPD.

In this study, AECOPD patients with a PA/A ratio ≥1 had markedly higher values of PaCO2, RDW, BNP, the PA diameter, ICU admission rates, and proportions of treatment failure and had worse outcomes during hospitalization. A PA/A ratio ≥1 was an independent risk factor for treatment failure in patients with AECOPD. The PA/A ratio may be a promising predictor for treatment failure. It is worth noting that there are several limitations in this study. First, the sample size was small, and this might lead to an interpretation bias in the final analysis. Further work is required to validate the initial conclusion for a larger sample size. Second, the PA/A ratio partially reflects a change in the pulmonary artery pressure. However, the association between the PA/A ratio and the pulmonary artery pressure was not assessed in this study. Finally, to reduce the chance of radioactive exposure, a dynamic change in the PA/A ratio during hospitalization was unclear.

Acknowledgments

We thank LetPub for its linguistic assistance during the preparation of this manuscript.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

The design of the study and collection, analysis, and interpretation of data were supported by the Anhui Provincial Key projects of the Natural Science Foundation for Colleges and Universities (KJ2021A0834).

Disclosure

The authors report no conflicts of interest in this work.

References

1. Celli BR, Wedzicha JA. Update on clinical aspects of chronic obstructive pulmonary disease. N Engl J Med. 2019;381:1257–1266. doi:10.1056/NEJMra1900500

2. Wang C, Xu J, Yang L, et al. Prevalence and risk factors of chronic obstructive pulmonary disease in China (the China Pulmonary Health [CPH] study): a national cross-sectional study. Lancet. 2018;391:1706–1717. doi:10.1016/S0140-6736(18)30841-9

3. Garcia-Sanz MT, Canive-Gomez JC, Senin-Rial L, et al. One-year and long-term mortality in patients hospitalized for chronic obstructive pulmonary disease. J Thorac Dis. 2017;9:636–645. doi:10.21037/jtd.2017.03.34

4. Nakayama S, Chubachi S, Sakurai K, et al. Characteristics of chronic obstructive pulmonary disease patients with pulmonary hypertension assessed by echocardiography in a three-year observational cohort study. Int J Chron Obstruct Pulmon Dis. 2020;15:487–499. doi:10.2147/COPD.S230952

5. Carpio AM, Goertz A, Kelly C, et al. Unrecognized pulmonary arterial hypertension in hospitalized patients. Int J Cardiovasc Imaging. 2021;37:1237–1243. doi:10.1007/s10554-020-02108-9

6. Iyer AS, Wells JM, Vishin S, et al. CT scan-measured pulmonary artery to aorta ratio and echocardiography for detecting pulmonary hypertension in severe COPD. Chest. 2014;145:824–832. doi:10.1378/chest.13-1422

7. Schneider M, Ran H, Pistritto AM, et al. Pulmonary artery to ascending aorta ratio by echocardiography: a strong predictor for presence and severity of pulmonary hypertension. PLoS One. 2020;15(7):e235716. doi:10.1371/journal.pone.0235716

8. Terzikhan N, Bos D, Lahousse L, et al. Pulmonary artery to aorta ratio and risk of all-cause mortality in the general population: the Rotterdam Study. Eur Respir J. 2017;49:1602168. doi:10.1183/13993003.02168-2016

9. Zeng Y, Cai S, Chen Y, et al. Current status of the treatment of COPD in China: a multicenter prospective observational study. Int J Chron Obstruct Pulmon Dis. 2020;15:3227–3237. doi:10.2147/COPD.S274024

10. Cai BQ, Cai SX, Chen RC, et al. Expert consensus on acute exacerbation of chronic obstructive pulmonary disease in the People’s Republic of China. Int J Chron Obstruct Pulmon Dis. 2014;9:381–395. doi:10.2147/COPD.S58454

11. Wells JM, Morrison JB, Bhatt SP, et al. Pulmonary artery enlargement is associated with cardiac injury during severe exacerbations of COPD. Chest. 2016;149:1197–1204. doi:10.1378/chest.15-1504

12. Iliaz S, Tanriverdio E, Chousein E, et al. Importance of pulmonary artery to ascending aorta ratio in chronic obstructive pulmonary disease. Clin Respir J. 2018;12:961–965. doi:10.1111/crj.12612

13. Morray JP, Lynn AM, Mansfield PB. Effect of pH and PCO2 on pulmonary and systemic hemodynamics after surgery in children with congenital heart disease and pulmonary hypertension. J Pediatr. 1988;113:474–479. doi:10.1016/S0022-3476(88)80631-0

14. Zuk M, Migdal A, Dominczak J, et al. Usefulness of Red Cell Width Distribution (RDW) in the assessment of children with Pulmonary Arterial Hypertension (PAH). Pediatr Cardiol. 2019;40:820–826. doi:10.1007/s00246-019-02077-4

15. Ulrich A, Wharton J, Thayer TE, et al. Mendelian randomisation analysis of red cell distribution width in pulmonary arterial hypertension. Eur Respir J. 2020;55:1901486.

16. Liu J, Yang J, Xu S, et al. Prognostic impact of red blood cell distribution width in pulmonary hypertension patients: a systematic review and meta-analysis. Medicine. 2020;99:e19089. doi:10.1097/MD.0000000000019089

17. Yang J, Liu C, Li L, et al. Red blood cell distribution width predicts pulmonary hypertension secondary to chronic obstructive pulmonary disease. Can Respir J. 2019;2019:3853454. doi:10.1155/2019/3853454

18. Hoeper MM, Pausch C, Olsson KM, et al. COMPERA 2.0: a refined 4-strata risk assessment model for pulmonary arterial hypertension. Eur Respir J. 2021;2102311. doi: 10.1183/13993003.02311-2021

19. Gayaf M, Karadeniz G, Guldaval F, et al. Which one is superior in predicting 30 and 90 days mortality after COPD exacerbation: DECAF, CURB-65, PSI, BAP-65, PLR, NLR. Expert Rev Respir Med. 2021;15:845–851. doi:10.1080/17476348.2021.1901584

20. Chen L, Chen L, Zheng H, et al. Emergency admission parameters for predicting in-hospital mortality in patients with acute exacerbations of chronic obstructive pulmonary disease with hypercapnic respiratory failure. BMC Pulm Med. 2021;21:258. doi:10.1186/s12890-021-01624-1

21. Hu GP, Zhou YM, Wu ZL, et al. Red blood cell distribution width is an independent predictor of mortality for an acute exacerbation of COPD. Int J Tuberc Lung Dis. 2019;23:817–823. doi:10.5588/ijtld.18.0429

22. Epstein D, Nasser R, Mashiach T, et al. Increased red cell distribution width: a novel predictor of adverse outcome in patients hospitalized due to acute exacerbation of chronic obstructive pulmonary disease. Respir Med. 2018;136:1–7. doi:10.1016/j.rmed.2018.01.011

23. Salvagno GL, Sanchis-Gomar F, Picanza A, et al. Red blood cell distribution width: a simple parameter with multiple clinical applications. Crit Rev Clin Lab Sci. 2015;52:86–105. doi:10.3109/10408363.2014.992064

24. Wang J, Ym D. Prevalence and risk factors of pulmonary embolism in acute exacerbation of chronic obstructive pulmonary disease and its impact on outcomes: a systematic review and meta-analysis. Eur Rev Med Pharmacol Sci. 2021;25:2604–2616. doi:10.26355/eurrev_202103_25424

25. Husebo GR, Gabazza EC, D’Alessandro GC, et al. Coagulation markers as predictors for clinical events in COPD. Respirology. 2021;26:342–351. doi:10.1111/resp.13971

26. Vallabhajosyula S, Haddad TM, Sundaragiri PR, et al. Role of B-type natriuretic peptide in predicting in-hospital outcomes in acute exacerbation of chronic obstructive pulmonary disease with preserved left ventricular function: a 5-year retrospective analysis. J Intensive Care Med. 2018;33:635–644. doi:10.1177/0885066616682232

27. Yang T, Chen C, Chen Z. The CT pulmonary vascular parameters and disease severity in COPD patients on acute exacerbation: a correlation analysis. BMC Pulm Med. 2021;21:34. doi:10.1186/s12890-020-01374-6

28. Wells JM, Washko GR, Han MK, et al. Pulmonary arterial enlargement and acute exacerbations of COPD. N Engl J Med. 2012;367:913–921. doi:10.1056/NEJMoa1203830

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Cuiqiong Dai,&ast; Zihui Wang,&ast; Zhishan Deng, Fan Wu, Huajing Yang, Shan Xiao, Xiang Wen, Youlan Zheng, Jianwu Xu, Lifei Lu, Ningning Zhao, Peiyu Huang, Yumin Zhou, Pixin Ran

State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, People’s Republic of China

Correspondence: Pixin Ran; Yumin Zhou, The State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, No. 195 Dongfeng Xi Road, Guangzhou, 510000, People’s Republic of China, Tel +86-020 83205187, Fax +86-020 81340482, Email [email protected]; [email protected]

Background: Serum total bilirubin has been reported to have antioxidant properties against chronic respiratory diseases. The objective of our study is to evaluate the association of total bilirubin (TB) with annual lung function decline in COPD patients with different GOLD stages.
Methods: This study used pooled data from two observational and prospective cohorts of 612 COPD patients whose TB levels were measured at baseline. The associations between TB and postbronchodilator FEV1, FEV1pred, FVC, FVCpred, FEV1/FVC, and the rate of their decline were all determined using linear regression models in the total population and strata of GOLD stages.
Results: Serum TB was positively related to FEV1 and FVC in the total group (β 0.02, 95% CI 0.001∼ 0.02, P = 0.025 and β 0.02, 95% CI 0.002∼ 0.03, P = 0.022, respectively). Additionally, TB was inversely associated with the annual decline in FEV1 and FEV1pred (β 4.91, 95% CI 1.68∼ 8.14, P = 0.025 and β 0.21, 95% CI 0.06∼ 0.36, P = 0.022, respectively) when adjusted for multivariables. After stratification, the significant associations merely persisted in COPD patients with GOLD 2 and GOLD 3– 4.
Conclusion: Increased TB level was related to less annual decline in FEV1 as well as FEV1pred in moderate-to-severe COPD but not mild COPD, which indicated the different status of TB in different COPD severity and the possible role as potential biomarker merely in moderate-to-severe COPD. Future researches to determine whether TB could be served as biomarker for COPD and the mechanisms should be focused on some target patients with a certain disease severity.

Introduction

Serum total bilirubin (TB), an end product of heme degradation, is demonstrated to scavenge oxidation free radicals and thus suppress oxidative stress.1 Experimental evidence from animal models indicated that TB could protect respiratory tissues against environmental stressors by cytoprotective properties.2,3 Additionally, accumulating clinical studies supported that mild higher bilirubin levels could decrease the risk of cardiovascular disease (CVD) and CVD-related diseases.4–6 An increased total bilirubin level is also associated with a lower risk of chronic respiratory diseases, including lung cancer and chronic obstructive pulmonary disease (COPD), as well as all-cause mortality.7–9 Furthermore, Kirstin E. et al found that elevated bilirubin concentrations would decrease the acute exacerbation of COPD.10

A few longitudinal cohort studies have explored the relationship between total bilirubin and the rate of lung function decline. For example, Ah YL et al11 showed that serum bilirubin concentration was significantly related to the annual changes in FEV1, FVC, and FEV1 /FVC in general Koreans adjusted for sex, age, body mass index (BMI), and baseline lung function. Similarly, only in mild COPD, serum bilirubin is inversely related to the rate of FEV1 decline over 3 to 9 years.12 In a Swiss general population sample, per interquartile range increase of bilirubin exposure is concomitant with 1.1% increase in FEV1/FVC and 116.2 mL in FEF25-75% in smokers with high BMI.13 Also, David M. et al demonstrated that TB is significantly associated with higher FEV1 and FVC in baseline lung function in AIDS individuals.14 However, all these studies focused on the general or specific target population. And the data between bilirubin concentrations and the annual decline in lung function in all different GOLD stages of COPD have not been reported before. To fill this evidence gap, we hypothesized that higher TB level is associated with less annual lung function decline in COPD patients with different GOLD stages. To test the hypothesis, we pooled data from two observational and prospective cohort studies to assess the relationship between serum TB and lung function decline in the total COPD population and then further in different GOLD stage subgroups.

Methods

Study Subjects

The data were pooled from two population-based, multi-center, and prospective cohort studies, including the National Key Technology Research and Development Program of the 12th National 5-year Development Plan (2012–2015 Program; Trial registration number ChiCTR-OO-14004264) and the Early COPD (ECOPD; Trial registration number ChiCTR1900024643). The details of these two cohorts have been reported previously.15,16 Briefly, two cohorts recruited participants aged 20 years or older and completed bilirubin measurement, questionnaires, and lung function tests at baseline. Subjects included in this study completed spirometric measurements again for an interval of 7 to 9 years follow-up duration in 2012–2015 Program as well as 1 to 2 years in ECOPD. Only participants defined as COPD (postbronchodilator FEV1/FVC <0.7)17 with reliable data were included in our analysis. Participants were excluded if they had any comorbidity that might significantly influence bilirubin, such as hemolytic disorders, hepatobiliary diseases, or renal insufficiency by self-report. Additionally, TB concentrations >1.75 mg/dL for women and >2.34 mg/dL for men were also excluded for suspicious Gilbert syndrome, a benign hereditary disease caused by UGT1A1 genotypes.18 The original two studies were performed in line with the principles of the Declaration of Helsinki. Besides, the two studies were approved by the Ethics Committee of Scientific research project review of the First Hospital of Guangzhou Medical University (No.2013–37 for 2012–2015 Program and N0.2018–53 for ECOPD) and written informed consent was also attained from all the participants.

Bilirubin Measurement

At baseline, venous blood samples were collected from eligible participants required to fast for more than 8 hours by trained and professional staff. The samples will be stored at room temperature for at least 30 min and then quantified by biochemical assays performed by the clinical laboratory to test total bilirubin. Bilirubin concentrations were measured or transformed to the nearest 0.06 mg/dL (1 μmol/L).

Lung Function Measurement

Spirometry was performed by well-trained staff using a portable spirometer (CareFusion™ MasterScreen Pneumo, Germany) on the same day of bilirubin detection. Only at least three acceptable curves and two reproducible tests can be considered as acceptable for our study. We also performed postbronchodilator Spirometry (salbutamol sulfate aerosol, 400 μg 20min later) and then recorded and retrieved postbronchodilator FEV1, FVC, FEV1pred, FVCpred, and FEV1/FVC. Annual Lung function decline was calculated as the parameters at follow-up minus corresponding baseline values divided by the number of years for follow-up duration. All spirometric maneuvers and quality control were performed following European Respiratory Society/American Thoracic Society standards.19 The definition of GOLD stages in our study was in line with GOLD criteria for COPD, and we considered GOLD 3–4 COPD as severe COPD.17

Questionnaire

A questionnaire interview was carried out using a standardized questionnaire recommended by Zhong N et al.20 We abstracted information about demographic characteristics, risk factors (smoke, occupational exposure, comorbidities, and family history of respiratory diseases), and respiratory symptoms, including any one of wheeze, cough, sputum production, and dyspnea. We classified smoking status as never smoker, former smoker, and current smoker. Subjects who have smoked less than 100 cigarettes in the past are identified as never smokers. Current smokers are referred to someone who were smoking at baseline, and the others are regarded as former smokers. The definition of the smoking index is multiplying the number of packs of cigarettes smoked per day by the number of years the person smoked. We took subjects whose parents, siblings, or children had any of the listed respiratory diseases (chronic bronchitis, emphysema, asthma, COPD, cor pulmonale, bronchiectasis, lung cancer, interstitial lung disease, obstructive sleep apnea hypopnea syndrome) as having a family history of respiratory diseases.

Statistical Analysis

All variables are expressed as mean ± SD or number (%). Characteristics of participants among GOLD 1, GOLD 2, and GOLD 3–4 compared using One-Way analysis of variance (ANOVA) test for continuous variables and the χ2 or Fisher's exact test for categorical variables. The associations of TB with pulmonary function parameters at baseline or annual lung function decline were assessed using univariable and multivariable regression models. All linear regression models were adjusted for age, sex, BMI, smoking status, smoke index, passive smoker, occupational exposure, comorbidities, and family history of respiratory diseases. To ensure the authenticity of the data, there was no imputation for missing values of interest in our analysis. Data analysis was performed using IBM SPSS Version 25.0 and the statistical software R version 4.0.3. Two-sided p < 0.05 were considered statistically significant.

Results

Baseline Characteristics

Of the 1053 patients with COPD, 442 were excluded for various reasons (Figure 1). The remaining 612 subjects were divided into three subgroups by GOLD stages. Characteristics of the total group and three subgroups are presented in Table 1. Compared with patients with mild COPD (GOLD 1), patients with moderate-to-severe COPD (GOLD 2, 3 and 4) were more likely to be old, female, breathless and have lower BMI, heavier smoking exposure, more comorbidities, more family history of respiratory diseases as well as worse lung function. There was no significant difference in TB levels among the three subgroups (P = 0.486). The mean follow-up duration for our patients was about two years.

Table 1 Baseline Characteristics of the Study Subjects

Figure 1 Flow chart of participant selection.

Abbreviation: COPD, chronic obstructive pulmonary disease.

Note: COPD was diagnosed by postbronchodilator FEV1/FVC <0.7.

Associations of Total Bilirubin with Baseline Lung Function Parameters

Univariable and multivariable linear regressions of baseline pulmonary function parameters such as FEV1, FEV1pred, FVC, FVCpred, and FEV1/FVC on TB concentrations are shown in Table 2. After adjustment for age, sex, BMI, smoking status, smoke index, passive smoker, occupational exposure, comorbidities, and family history of respiratory diseases, TB level (μmol/L) was significantly related to FEV1 and FVC in the total COPD patients (β 0.02, 95% CI 0.001~0.02, P = 0.025 and β 0.02, 95% CI 0.002~0.03, P = 0.022, respectively). Stratified by GOLD stages, the relationship between TB and FEV1 was only present in GOLD 1 stage (β 0.01, 95% CI 0.001~0.02, P = 0.032), whereas FVC became tending to be slightly associated with bilirubin (P = 0.054).

Table 2 Univariable and Multivariable Linear Regression Analysis for TB and Baseline Lung Function Parameters in the Total Group and Subgroups by GOLD Stages

Total Bilirubin and Annual Lung Function Decline

Totally, higher bilirubin concentrations were associated with a reduced rate of decline in lung function, which is consistent in the univariable and multivariable regression analysis approximately (Figure 2). In the total COPD group, we found that per 1 μmol/L increase in TB will reduce 4.91 mL/L decline in FEV1 (P = 0.003), 0.21% decline in FEV1pred (P = 0.005), 6.26 mL/L decline in FVC (P = 0.039), and 0.23% in FVCpred (P = 0.023). However, following stratification according to GOLD stages and multi-adjustments, the similar associations of FEV1 and FEV1pred with TB merely existed in GOLD 2 and GOLD 3–4 patients. Besides, bilirubin only showed a protective effect on the rate of decline in airflow limitation (FEV1/FVC) in severe COPD (GOLD 3–4).

Figure 2 Linear regression analysis for the relationship between bilirubin and annual lung function decline, by overall COPD population and stratified by GOLD stages.

Notes: Annual Lung function decline was calculated as the parameters at follow-up minus corresponding baseline values divided by the number of years for follow-up duration. Multivariable linear regression analysis models were adjusted for age, sex, BMI, smoking status, smoke index, passive smoker, occupational exposure, comorbidities and family history of respiratory diseases. Per unit increase of TB in all these models is 1 μmol/L. Crude β means the unstandardized β estimate from univariable analysis, Crude P values mean the P values from univariable analysis, adj.β means the unstandardized β estimate from the multivariable analysis, adj.P values mean the P values from multivariable analysis. Abbreviations see abbreviation section in Table 1.

Discussion

In the pooled data from two prospective and longitudinal cohort studies, we found that TB was positively associated with FEV1 in the total COPD population at baseline. Besides, TB also significantly reduced the rate of FEV1 and FEV1pred decline in the total COPD group at follow-up duration after adjustment for age, sex, BMI, smoking status, smoke index, passive smoker, occupational exposure, comorbidities, as well as family history of respiratory diseases. Surprisingly, when stratifying by disease severity according to GOLD stages, relationships significantly persisted only in patients with moderate-to-severe COPD. To our best knowledge, our study was the first to explore TB and lung function in the target COPD population with different GOLD stages.

What we found between TB and FEV1 were in line with those of Ah YL et al11 who found that higher TB concentration was associated with higher FEV1 and less annual FEV1 decline in the general Koreans and those of Apperley S et al12 who also showed that consistent associations in mild-to-moderate COPD after adjusting for age, sex, race, BMI and baseline measures of lung function. All these demonstrations indicated the potential protective role of TB played on lung function. We could reasonably speculate about the mechanisms of mild higher TB level protecting lung function. Summarily, the most important heme oxygenase that influences the biochemical production of bilirubin is heme oxygenase-1 (HO-1),21 which would be up-regulated by oxidative stress22 and hypoxia.23,24 HO-1 is expressed in pulmonary cells including type II pneumocytes and alveolar macrophages.25 COPD is a chronic pathological process accompanied by endogenously or exogenously produced oxidative stress and inflammation.26,27 Higher HO-1 levels expressed in COPD would increase TB concentrations. Furthermore, bilirubin has been reported to be an endogenous bioactive substance possessing substantial antioxidant activities by several experiments.28–30 Thus, TB may improve the lung function in COPD in this way.

Another extended finding was that the significant protection effects merely persisted in moderate-to-severe COPD. It may be implied that only when oxidative stress increased to a certain degree can bilirubin perform a function against oxidation. We can get some evidence from the current studies. A Mendelian Randomization analysis using UK Biobank showed that smokers with genetically raised serum bilirubin levels have lower rates of lung cancer and these relationships are strongest in current heavy smokers (20 or more cigarettes per day),31 whereas Hyun et al found that high serum TB was not significantly associated with the presence of COPD in never-smokers.32 Likewise, our data showed that patients in GOLD 2 and GOLD 3–4 had more smoking exposure (more smoking index, pack-yrs). As we know, heavy cigarettes exposure aggravated inflammation and oxidative damage of COPD, which would be suppressed by bilirubin reduction to attenuate pulmonary injury.33 Differently from previous studies,11,13 we found no significant association between TB and airflow limitation (FEV1/FVC) in the total group. The conflicting results may be attributed to the differences of adjusted covariates in the proportion of sex, distribution of age, BMI, smoking status and index, comorbidities, as well as family history of respiratory diseases.

Our study also has a few limitations. First, the sample size in moderate-to-severe COPD was small, so we could not respectively evaluate the relationship of TB and GOLD 3 COPD or GOLD 4 COPD, given that the participants were community-based. However, GOLD 3 and GOLD 4 were usually incorporated as severe COPD in clinical epidemiology. Second, we only collected one blood sample, which did not allow for continuous evaluation of intraindividual variability, although bilirubin levels are demonstrated to keep stable after adolescence.34 Besides, we could not exclude the influence of alcohol intake on TB for lacking the related information. However, we have excluded other factors affecting bilirubin as we can by incorporating hepatic disease into comorbidities, which may be caused by heavy alcohol consumption.

Conclusions

In conclusion, we confirmed again that TB is inversely associated with annual lung function decline in FEV1 and FEV1pred in COPD. And that association persists only in moderate-to-severe COPD adjusted for multi-covariates, which implicated the different functional status of TB being in different degrees of COPD severity. It is also suggested that TB may be a biomarker for only moderate-to-severe COPD but not mild COPD. We should focus more on the specific COPD patients with a certain disease severity when validating bilirubin as a biomarker of COPD potentially in future studies, given the protective effects of TB. Besides, further researches are also needed to investigate the mechanisms of TB action on different severity levels of COPD to explain the different influences on lung function decline.

Abbreviations

TB, total bilirubin; COPD, chronic obstructive pulmonary disease; GOLD, the Global Initiative for Chronic Lung Disease; mMRC, Modified Medical Research Council dyspnea; BMI, body mass index; FVC, forced vital capacity; FVC, %predicted, the ratio of FVC to its predicted value; FEV1, forced expiratory volume in the first second; FEV1,%predicted, the ratio of FEV1 to its predicted value; FEV1/FVC, the ratio of FEV1 to FVC; ANOVA, analysis of variance; SD, standard deviation; CI, confidence interval; CVD, cardiovascular disease; ECOPD, the early COPD; HO-1, oxygenase-1.

Data Sharing Statement

The datasets used and analyzed in this study are available from the corresponding author on reasonable request.

Ethics Approval and Consent to Participate

The original two studies were performed in line with the principles of the Declaration of Helsinki. All the participants from two studies gave written informed consent and two studies were approved by the Ethics Committee of the First Affiliated Hospital of Guangzhou Medical University (No.2013-37 and No. 2018-53 respectively).

Acknowledgments

The authors thank for the contributions of all the subjects who agreed to donate their information for analysis. Besides, the authors thank Bijia Lin, Shaodan Wei and Xiaopeng Ling (State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Nanshan Medicine Innovation Institute of Guangdong Province) for their help in collecting the data.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

The study was funded by The Nature Key Research and Development Program (2016YFC1304101), the Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program (2017BT01s155), the independent project of the State Key Laboratory of Respiratory Diseases (SKLRD-QN-201913), the National Science Foundation of China (81970045), and Zhong Nanshan Medical Development Foundation of Guangdong Province (ZNSA-202003, ZNSA-2020012, ZNSA-2020013).

Disclosure

All the authors declare they have no real or potential competing interests in this work.

References

1. Stocker R, Yamamoto Y, Mcdonagh A, Glazer A, Ames B. Bilirubin Is an Antioxidant of Possible Physiological Importance. Science. 1987;235:43.

2. Wang H-D, Yamaya M, Okinaga S, et al. Bilirubin Ameliorates Bleomycin-Induced Pulmonary Fibrosis in Rats. Am J Respir Crit Care Med. 2002;165(2):406–411.

3. Ryter SW, Morse D, Choi AM. Carbon monoxide and bilirubin: potential therapies for pulmonary/vascular injury and disease. Am J Respir Cell Mol Biol. 2007;36(2):175–182.

4. McCarty MF. “Iatrogenic Gilbert syndrome”–a strategy for reducing vascular and cancer risk by increasing plasma unconjugated bilirubin. Med Hypotheses. 2007;69(5):974–994.

5. Vitek L, Jirsa M, Brodanova M, et al. Gilbert syndrome and ischemic heart disease a protective effect of elevated bilirubin levels. Atherosclerosis. 2008;198:1–11.

6. Schwertner HA, Vitek L, Schwertner HA. Gilbert syndrome, UGT1A1*28 allele, and cardiovascular disease risk: possible protective effects and therapeutic applications of bilirubin. Atherosclerosis. 2008;198(1):1–11.

7. Horsfall LJ, Rait G, Walters K, et al. Serum Bilirubin and Risk of Respiratory Disease and Death. JAMA. 2011;305:691–697.

8. Monroy-Iglesias MJ, Moss C, Beckmann K, et al. Serum Total Bilirubin and Risk of Cancer: a Swedish Cohort Study and Meta-Analysis. Cancers. 2021;13:21.

9. Lim JE, Kimm H, Jee SH. Combined effects of smoking and bilirubin levels on the risk of lung cancer in Korea: the severance cohort study. PLoS One. 2014;9(8):e103972.

10. Brown KE, Sin DD, Voelker H, et al. Serum bilirubin and the risk of chronic obstructive pulmonary disease exacerbations. Respir Res. 2017;18(1):179.

11. Leem AY, Kim HY, Kim YS, Park MS, Chang J, Jung JY. Association of serum bilirubin level with lung function decline: a Korean community-based cohort study. Respir Res. 2018;19(1):99.

12. Apperley S, Park HY, Holmes DT, et al. Serum Bilirubin and Disease Progression in Mild COPD. Chest. 2015;148(1):169–175.

13. Curjuric I, Imboden M, Adam M, et al. Serum bilirubin is associated with lung function in a Swiss general population sample. Eur Respir J. 2014;43(5):1278–1288.

14. MacDonald DM, Zanotto AD, Collins G, et al. Associations between baseline biomarkers and lung function in HIV-positive individuals. AIDS. 2019;33(4):655–664.

15. Liu S, Zhou Y, Liu S, et al. Association between exposure to ambient particulate matter and chronic obstructive pulmonary disease: results from a cross-sectional study in China. Thorax. 2017;72(9):788–795.

16. Wu F, Zhou YM, Peng JQ, et al. Rationale and design of the Early Chronic Obstructive Pulmonary Disease (ECOPD) study in Guangdong, China: a prospective observational cohort study. J Thorac Dis. 2021;12:87.

17. Agusti A, Vogelmeier C, Papi A, et al. Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Lung Disease: 2021 report. Available from: goldcopd.org/2021-gold-reports/. Accessed July 1, 2021.

18. Duzenli T, Maden O, Tanoglu A, Kaplan M, Yazgan Y. Associations between Gilbert’s syndrome and personality characteristics. Trends Psychiatry Psychother. 2021;43(2):151–158.

19. Miller MR, Hankinson J, Brusasco V, et al. Standardisation of spirometry. Eur Respir J. 2005;26(2):319–338.

20. Zhong N, Wang C, Yao W, et al. Prevalence of chronic obstructive pulmonary disease in China: a large, population-based survey. Am J Respir Crit Care Med. 2007;176(8):753–760.

21. Tenhunen R, Marver HS, Schmid R. Microsomal Heme Oxygenase. Biol Chem. 1969;244(23):6388–6394.

22. Carter EP, Garat C, Imamura M. Continual emerging roles of HO-1: protection against airway inflammation. Am J Physiol Lung Cell Mol Physiol. 2004;287:L24–L25.

23. Christou H, Morita T, Hsieh C-M, et al. Prevention of Hypoxia-Induced Pulmonary Hypertension by Enhancement of Endogenous Heme Oxygenase-1 in the Rat. Circ Res. 2000;86:1224–1229.

24. Minamino T, Christou H, Hsieh C-M, et al. Targeted expression of heme oxygenase-1 prevents the pulmonary inflammatory and vascular responses to hypoxia. PNAS. 2001;98(15):8798–8803.

25. Fredenburgh LE, Perrella MA, Mitsialis SA. The role of heme oxygenase-1 in pulmonary disease. Am J Respir Cell Mol Biol. 2007;36(2):158–165.

26. Kirkham PA, Barnes PJ. Oxidative stress in COPD. Chest. 2013;144(1):266–273.

27. Harijith A, Natarajan V, Fu P. The Role of Nicotinamide Adenine Dinucleotide Phosphate Oxidases in Lung Architecture Remodeling. Antioxidants(Basel). 2017;6(4):87.

28. Huang H, Guo M, Liu N, et al. Bilirubin neurotoxicity is associated with proteasome inhibition. Cell Death Dis. 2017;8(6):e2877.

29. Vitek L. Bilirubin as a signaling molecule. Med Res Rev. 2020;40(4):1335–1351.

30. Stocker R, Glazert AN, Ames BN. Antioxidant activity of albumin-bound bilirubin. Medical Sciences. 1987;84(2):5918–5922.

31. Horsfall LJ, Burgess S, Hall I, Nazareth I. Genetically raised serum bilirubin levels and lung cancer: a cohort study and Mendelian randomisation using UK Biobank. Thorax. 2020;75(11):955–964.

32. Lee H, Hong Y, Lim MN, et al. Inflammatory biomarkers and radiologic measurements in never-smokers with COPD: a cross-sectional study from the CODA cohort. Chron Respir Dis. 2018;15(2):138–145.

33. Wei J, Zhao H, Fan G, Li J. Bilirubin treatment suppresses pulmonary inflammation in a rat model of smoke-induced emphysema. Biochem Biophys Res Commun. 2015;465(2):180–187.

34. Wilding P, Rollasox JG, Robinson D. Patterns of change for various biochemical constituents detected in well population screening. Clin chim Acta. 1972;1:375–387.

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COPD patient on a Nebuliser breathing apparatus

COPD patient on a Nebuliser breathing apparatus (Representative image)

Photo : iStock

KEY HIGHLIGHTS

  • Breath is the basis of our existence and healthy lungs are primary to breathing activity.
  • Yet, Chronic obstructive pulmonary disease can creep in stealthily and steal that basic ability.
  • COPD brings with it an increased chance of heart failure and early death.

We often tend to believe that with old age one's lungs become diseased and do not perform as efficiently as they did when one was young. Or that continuous wheezing or breathlessness is okay and will go away when one eats nutritious foods or rests enough. But that is not ALWAYS true. If we pay attention to the factors that determine pulmonary health and strength, we may be able to stall impending damage - unless, of course, some conditions make it a progressive and incurable disease.

What is Chronic Obstructive Pulmonary Disease (COPD)?

Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory lung disease that causes obstructed airflow from the lungs. According to the Mayo Clinic experts, symptoms include:
  1. Breathing difficulty,
  2. Cough,
  3. Mucous (sputum) production and
  4. Wheezing.

What causes COPD?

Those persons who have suffered long-term exposure to irritating gases or particulate matter, most often from cigarette smoke etc. In countries where smoke-free cooking setups are not the norm, COPD often occurs in people exposed to fumes from burning fuel for cooking and heating in poorly ventilated homes. The more worrisome part is that the damage does not stop there and since the heart and lung are part of the same setup, people with COPD are at increased risk of developing heart disease, lung cancer and a variety of other conditions.

Risk factors for COPD include:

  1. Exposure to tobacco smoke: The more years one has been smoking (the more packs you smoke), the greater your risk. Pipe smokers, cigar smokers and marijuana smokers as well as those exposed to large amounts of secondhand smoke also cannot hope to be spared either.
  2. People with asthma: Asthma, a chronic inflammatory airway disease, may be a risk factor for developing COPD. Smoking coupled with asthmatic conditions is a deadly combination that allows COPD to take root.
  3. Occupational exposure to specks of dust and chemicals: Working in factory environs where suspended particulate matter in form of cement dust, asbestos, cloth fibres, chemical fumes, vapours and specks of dust etc irritate and inflame your lungs, COPD is not too far away. In the developing world, people exposed to fumes from burning fuel for cooking and heating in poorly ventilated homes are at higher risk of developing COPD.
  4. Exposure to air pollution in the home or at work: This is another hazardous trigger for COPD.
  5. Respiratory infections: Diseases involving the breathing tract such as pneumonia, and now SARS-CoV-2 (COVID-19) can also increase your risk.
  6. Genetics: The uncommon genetic disorder alpha-1-antitrypsin deficiency is the cause of some cases of COPD. Therefore, stay aware of your family's medical history. Other genetic factors likely make certain smokers more susceptible to the disease.

Is COPD treatable?

While it is a fact that COPD is a progressive disease that gets worse over time, with modern research enabling better management protocol, it is treatable. With proper management, most people with COPD can achieve good symptom control and quality of life, as well as reduced risk of other associated conditions, says Mayo Clinic.
According to the US Centers for Disease Control and Prevention (CDC), your doctor may also consider the following treatment options:
  1. Medicine: This may be to treat symptoms such as coughing or wheezing.
  2. Pulmonary rehabilitation: A personalised treatment program that teaches you how to manage your COPD symptoms to improve your quality of life. Customised breathing exercises, tips and hacks on how to conserve your energy, and what types of food and exercise are right for you are imparted.
  3. Prevention and treatment of lung infections: Lung infections can cause serious problems in people with COPD. Stay up-to-date on certain types of crucial vaccines such as flu, COVID-19, and pneumonia vaccines. Respiratory infections should be treated with antibiotics, if appropriate.
  4. Supplemental oxygen: A portable oxygen tank may be needed if blood oxygen levels are low. All these will, of course, be decided by your treating doctor.

What happens when COPD advances?

When COPD is unmanaged, it can develop into more complicated health conditions like:

  1. Respiratory infections
  2. Heart problems
  3. Lung cancer
  4. High blood pressure in lung arteries (pulmonary hypertension)
  5. Depression

Signs and symptoms of COPD:

COPD is diagnosed using a simple breathing test called spirometry. Here's a key to managing COPD better. Catch its signs early and see a doctor soon. According to the American Lung Association experts, many people don't recognise the symptoms of COPD until the later stages of the disease. Sometimes people think they are short of breath or less able to go about their normal activities because they are "just getting older."

Remember, shortness of breath can be an important symptom of lung disease - which when left untreated can damage the heart and the vascular system. Be very careful as vital organs are involved. If you experience any of these symptoms or think you might be at risk for COPD, it is important to discuss this with your doctor.

  1. Chronic cough
  2. Shortness of breath while doing everyday activities (dyspnea)
  3. Frequent respiratory infections
  4. The blueness of the lips or fingernail beds (cyanosis)
  5. Fatigue
  6. Producing a lot of mucus (also called phlegm or sputum)
  7. Wheezing

The Bottom Line:

Don't wait for symptoms to become severe because valuable treatment time could be lost. Early detection of COPD is key to successful treatment. According to the UK health body NHS, while there's currently no cure for COPD, the sooner treatment begins, the less chance there is of severe lung damage. Learn Pranayam - the yoga of breathing right. It will give you better control over your breath and mind too.

Disclaimer: Tips and suggestions mentioned in the article are for general information purposes only and should not be construed as professional medical advice. Always consult your doctor or a dietician before starting any fitness programme or making any changes to your diet.

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Introduction

Despite advances in symptomatic management of chronic obstructive pulmonary disease (COPD) with new combination inhalers and in therapeutic options for patients with severe emphysema such as endobronchial valves, patients with COPD still have significant morbidity and mortality.1 Patients newly diagnosed with early COPD tend to have variable disease courses that remain difficult to predict even with readily available in-office spirometry.2 The healthcare burden of COPD in the US is significant and exacerbations account for $18 billion in direct costs annually.3 Thus, there is a pressing need to define clinically meaningful subtypes in COPD that better categorize patients with vastly different disease trajectories to identify those at risk for accelerated lung function decline and, ultimately, improve disease outcomes with targeted therapies.

The Fleischner Society published a statement in 2015 detailing computed tomography (CT) subtypes based on visual and quantitative evaluation of images to classify emphysema as well as other important features such as airway wall thickening, inflammatory small airways disease, interstitial abnormalities, and bronchiectasis.4 The combination of visual assessment and quantitative metrics can further help identify COPD phenotypes and provide information on disease progression and mortality.5 Commercially available software using novel radiographic features has become increasingly available to further aid in COPD subtyping. The use of quantitative CT (QCT) imaging has been harnessed by several companies discussed in detail in this review. These software packages can assess changes in airway architecture, vascular morphology, and parenchymal density on inspiratory and expiratory scans to measure the extent of emphysema, air trapping, and functional small airways disease (fSAD).

Search Strategy and Selection Criteria

The intention of this review is to present an overview of commercial platforms that provide quantitative CT applications for improving COPD subtyping. While there are many software platforms that offer this capability, those described here were selected based on our experience and communications with members of the COPDGene and SPIROMICS studies as well as with clinicians from other institutions. We searched published articles reported on the websites of VIDA, Imbio, Thirona, FLUIDDA, 4D Medical, and CoreLine, the companies that produce the platforms we review. We also searched terms such as “COPD” and “computed tomography,” company names (“VIDA,” “Imbio,” “Thirona,” “FLUIDDA,” “4D Medical,” “CoreLine”), and different combinations of these terms for all fields on PubMed and Web of Science before December 4, 2021. Only clinical studies using non-contrast QCT were included in this review; as such, the terms “preclinical” and “contrast enhanced” were used for exclusion criteria. All articles were published in English and related to COPD, QCT, and clinical studies. We excluded some articles whose resources were not available. We evaluated reviews and original research in this area, then cited relevant articles.

Quantitative Analysis of Computed Tomography

X-ray CT, with its high spatial resolution and air-soft tissue contrast, is used extensively in the clinical management of COPD patients. For radiographic assessments, thoracic radiologists routinely use the extensive array of analytical techniques that have been developed to improve the diagnostic and prognostic value of QCT.6,7 Measurements of low attenuation areas are by far the most extensively used readouts for quantifying obstructive regions of the lungs. When applying a threshold of <950 Hounsfield Units (HU) to CT scans acquired at inspiration (ie, full inflation), this quantitative index, presented as the relative volume of the lung parenchyma, has been pathologically validated as a measure of emphysema.8,9 Similar strategies have been applied to expiratory CT scans to assess the extent of air trapping, a hallmark of small airways disease (SAD).10 Spatially aligned paired CT scans acquired at different inflation levels have provided readouts of ventilation, ventilation heterogeneity, and quantification of SAD when emphysema is present.11–13 The high air-tissue contrast on the inspiration CT scan has also been exploited to develop methods for airway and vessel measurements, as well as fissure completeness.14–17 Combined, these analytical techniques provide detailed quantitative information on airway and vessel remodeling and alterations in local parenchyma.

Commercial Platforms

FLUIDDA

FLUIDDA, founded in 2005 and based primarily in Belgium, has harnessed the power of functional respiratory imaging (FRI) through the Broncholab platform. Using high-resolution CT (HRCT), FRI can create 3-dimensional airway models for computational fluid dynamics simulations.18 In addition to FRI, Broncholab provides additional QCT-based metrics that include lobe volumes and densities, emphysema scores, and pulmonary airway and vascular measurements (Figure 1).

Figure 1 Representative clinical report of blood vessel density with coronal image and summary statistics from a COPD patient,courtesy of FLUIDDA.

Researchers have demonstrated how FRI can be used to understand the heterogeneity of COPD. Among studies of exacerbations, van Geffen et al19 and Hajian et al20 used FRI to assess regional heterogeneity by looking at hyperinflation, airway diameter, and resistance, both during a COPD exacerbation and after resolution. Improvements in hyperinflation and airway resistance correlated to improved quality-of-life and pulmonary function testing (PFT) metrics, suggesting that therapy should focus on decreasing airway resistance, mostly distally, during exacerbations. FRI could further visualize variability in ventilation and airway resistance among subjects during exacerbations. In addition, FRI revealed changes in airway structure and volume in different regions of the lungs, including both central and distal airways,21 after inhaling a combination of a long-acting beta agonist (LABA) and inhaled corticosteroid (ICS).22 De Backer et al23 later demonstrated that administration of inhaled extra fine beclomethasone/formoterol with a lower ICS dose improved lung function and hyperinflation. Furthermore, FRI identified regional changes in medication deposition not detected by spirometry. More recently, this group found the combination long-acting muscarinic antagonist (LAMA) glycopyrrolate and LABA formoterol improved airway volumes and resistance, as measured by FRI, as well as forced expiratory volume in 1 second (FEV1), inspiratory capacity (IC), and hyperinflation. These findings support the use of dual bronchodilator therapy in patients with moderate-to-severe COPD.24,25 Orally administered roflumilast further reduced areas of hyperinflation, suggesting its ability to redistribute ventilation, which could enhance concomitant inhaler use.26 FRI parameters also predicted COPD exacerbations using machine learning algorithms in a cohort of 62 patients.27 Eleven baseline FRI parameters, specifically further decreases in airway volumes leading to higher airway resistances in chronically narrowed airways, could predict an impending exacerbation. No other clinical data, notably PFTs, had this predictive power.27 Most recently, Cahn et al28 showed that the phosphoinositide 3-kinase δ (PI3Kδ) inhibitor nemiralisib, combined with standard of care, helped patients recover from exacerbations and led to improved respiratory parameters, including FEV1 and distal-specific imaging airway volume, over a 28-day period and was well tolerated.

Apart from studies of COPD exacerbations, FRI is also being used to assess whether non-invasive ventilation (NIV) has the long-term benefit of improving oxygenation and/or chronic hypercarbia in patients with severe COPD.29 In patients treated with at least 6 months of NIV, mass flow was redistributed to areas of the lung with better perfusion and less emphysema to improve ventilation-perfusion matching and recruit previously occluded small airways. Patients had improved gas exchange, 6-minute walk distance (6MWD), and anxiety.30 These results suggest that patients with SAD may benefit from long-term NIV use. In patients with severe COPD with secondary pulmonary hypertension, inhaled nitric oxide caused pulmonary vasodilation as measured by increases in vessel volume through FRI. While subjective improvements in dyspnea were seen, long-term data is not yet available.31

VIDA Diagnostics

VIDA Diagnostics Inc., founded in 2004 and headquartered in Coralville, IA, has developed the Apollo Pulmonary Evaluation Software, their flagship QCT application. VIDA provides advanced algorithms for airway wall measurements, ventilation maps, and disease probability maps (DPM) obtained from the spatial alignment of paired CT scans at varying inflation levels, and Topographic Multi-Planar Reformat (tMPR) that displays an optimized view of non-overlapping airways in context with surrounding tissue (Figure 2). VIDA, using Apollo, serves as the image analysis core for COPDGene (Genetic Epidemiology of COPD), ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints), SPIROMICS (SubPopulations and InteRmediate Outcome Measures in COPD Study), SARP (Severe Asthma Research Group), and the MESA (Multi-Ethnic Study of Atherosclerosis) Lung Study.

Figure 2 Representative clinical report (left) and tMPR (Topographic Multi-Planar Reformat; right) with air trapping map, courtesy of VIDA Diagnostics, Inc.

In a study of current or former smokers with preserved spirometry who were symptomatic as measured by the COPD Assessment Test (CAT), VIDA software detected submillimeter increases in airway wall thickening compared to asymptomatic current and former smokers.32 Differences in airway anatomy on CT scans from the MESA Lung Study and SPIROMICS were associated with COPD development and subjects with the accessory sub-superior airway, the most common airway branch variant, were at higher risk.33 Those with the second most common variant, absence of the right medial-basal airway, had a familial FGF10 gene inheritance pattern, and were at increased risk of developing COPD, dyspnea, and smaller airway lumens. Central airways collapse greater than 50% of the airway lumen during exhalation, ie, expiratory central airway collapse (ECAC), was associated with worse St. George’s Respiratory Questionnaire (SGRQ) and Medical Research Council Scale (mMRC) scores in smokers with and without COPD in the COPDGene Study.34 Emphysema affects subsegmental airway anatomy and airflow obstruction, likely related to loss of airway tethering,35 and these changes in wall area correlated to the chronic bronchitis phenotype.36 Kirby et al37 quantified degree of fSAD using DPM in the longitudinal Canadian Chronic Obstructive Lung Disease (CanCOLD) study by registering full inspiration and expiration CT images to classify each voxel as emphysematous, gas trapping, or normal. DPM measurements were associated with PFTs, bronchodilator response, and symptoms, particularly dyspnea, as measured by the mMRC.

Kirby’s team has also used VIDA’s airway segmentation tool to evaluate total airway count (TAC), airway inner diameter, and wall area in CT scans from the CanCOLD Study.38 GOLD I and GOLD II subjects had reduced TAC and thinner airway walls with narrower lumens than never smokers and at-risk individuals. Since airway remodeling can be associated with declining lung function, such changes may serve as biomarkers to predict individuals at risk for accelerated disease progression. In two other cohorts –one from SARP and another from SPIROMICS– differences in airway structures of asthma and COPD subjects with post-bronchodilator FEV1 <80% were assessed.39 COPD patients had more severe emphysema, SAD, and reduced tissue fraction and regional lung deformation compared to asthmatics, with greatest differences in upper and middle lobes.

For patients with advanced emphysema undergoing interventional procedures, Apollo was used to evaluate fissure completeness in subjects undergoing bronchoscopic thermal vapor ablation, an alternative to valve placement due to collateral ventilation.40 Apollo showed that a target lobe volume reduction (TLVR) of about 50% would give patients improved quality of life and lung function following endoscopic valve therapy.41 Apollo software revealed QCT characteristics, such as low attenuation cluster (LAC) that reflect the size of the “emphysematous holes,” predictive of subjects who would respond positively to lung volume reduction with coils42 and valves.43 Beyond airway analysis, Apollo was used for vessel segmentation in the MESA study to demonstrate that peripheral total pulmonary vascular volume was greater after long-term black carbon exposure, suggesting air pollution could affect vascular remodeling, and, ultimately, gas exchange.44

Thirona

Thirona, headquartered in Nijmegen, Netherlands, and founded in 2014, develops artificial intelligence software products focusing on thoracic CT imaging. Thirona’s commercial software LungQ is capable of quantifying anatomical volumes, disease distribution, airway and vascular morphology, and fissure completeness.

Early studies using Thirona’s technology included work by Boueiz et al45 that evaluated lobar distribution of emphysema in the COPDGene cohort. They found that subgroups of smokers with upper-lobe predominant emphysema had greater disease progression over a 5-year period, gas trapping, and dyspnea. Thirona’s LungQ segmentation protocol was used in a separate study of COPDGene subjects to approximate the total lung capacity-adjusted lung density at the 15th percentile of predicted (TLC-PD15) as a means of monitoring disease progression.46 In smokers at risk for developing COPD, LungQ showed that lung tissue density increased over 5 years, suggesting ongoing inflammation and airway remodeling. In contrast, end-stage COPD patients (GOLD III or IV) had loss of TLC-PD15 over time, thus displaying a more classic picture of progressive emphysema and tissue destruction. Over the same 5-year period, smokers with and without COPD had increased evidence of emphysema and air trapping, but these radiographic findings accounted for less than half the decline in FEV1 in GOLD stages II–IV.47 The role of inflammation in airway wall thickening was validated by Charbonnier et al,48 who found that, in the COPDGene cohort, higher airway wall thickness (Pi10) was associated with worse lung function, 6MWD, and SGRQ scores in all GOLD stages. Further, subjects who quit smoking had lower Pi10 between their first visit and at 5-year follow-up; in contrast, Pi10 increased in subjects who started smoking, suggesting a reversible component of smoking-related inflammation. Most recently, Bodduluri et al49 confirmed that progressive airway narrowing and remodeling in COPD could be quantified by the CT imaging-derived ratio of airway luminal surface area to volume (SA/V) using Thirona’s airway quantification software. SA/V increased with airway narrowing and decreased with airway loss. Overall, subjects with predominantly airway loss had worse survival, although both changes were associated with increased respiratory morbidity.

In the therapeutic sphere, Thirona’s LungQ software for evaluating fissure completeness was used to identify the TLVR for bronchoscopic lung volume reduction with endobronchial valves, similar to VIDA’s technology. This study found that a minimal difference of –563 mL in a patient provided a clinical benefit.50 Measurements of lobar oxygen uptake also helped identify the least functional, and therefore target lobe for valve placement.51 Patients from the Lung Volume Reduction Coil Treatment in Patients with Emphysema (RENEW) Trial with significant hyperinflation (residual volume >200% predicted) had the best clinical outcomes when QCT analysis was used to identify lobar treatment location and adequate emphysema (>20%) for endobronchial coil treatment.52

Imbio

Imbio, a Minneapolis, US-based medical imaging software company founded in 2012, uses imaging biomarkers to enhance personalized medicine. Imbio’s Lung Density Analysis (LDA) software identifies key functional information from CT scans in COPD patients. The functional LDA image analysis tool maps regions of functionally healthy lung, air trapping, and emphysema. LDA uses parametric response mapping (PRM) to produce a voxel-wise map to pair inspiratory and expiratory CT scans to quantify fSAD (Figure 3). In addition to PRM, LDA includes other QCT metrics such as emphysema scores and lobe volume and density measurements.

Figure 3 Representative clinical report that contains PRM images in all orientations and summary statistics from a COPD patient, courtesy of Imbio.

Various studies have evaluated the efficacy of PRM as an accurate readout of SAD. These radiographic regions of fSAD pathologically correspond to areas of lung tissue with loss of terminal bronchioles, airway lumen narrowing, and obstruction identified by microscopic examination of resected lung. PRM is the only technique that has been histologically validated to date.13 An early study using PRM (2012), which analyzed data from 194 COPD subjects from COPDGene, showed that this technology can provide regional information on disease activity and, notably, that fSAD often preceded the development of emphysema.11 This association was more evident in subjects in the COPDGene cohort with mild- to moderate-stage COPD, where worsening PRM-derived fSAD (PRMfSAD) was also associated with declining FEV1 and diffusing capacity for carbon monoxide (DLCO).53,54 PRM metrics have been proven to be strongly associated with both the development and severity of COPD when compared to other biomarkers of emphysema, including expiratory-to-inspiratory ratio of mean lung density (MLD), an indirect measure of air trapping, and Perc15 (the Hounsfield Units [HU] where less than 15% of the voxels on an inspiratory CT are found).55

PRM, as part of the LDA platform, was used to analyze CT scans from the SPIROMICS study. In a 3-year follow-up of 1,105 COPD subjects from SPIROMICS, those who suffered from exacerbations during this time had greater small airways abnormalities as defined by PRMfSAD.56 As subjects progressed in their disease courses, emphysema increased as expected; however, this change was associated with a decrease in mean PRMfSAD values, suggesting that fSAD may be a transitional period between normal lung parenchyma and development of irreversible emphysema. fSAD may, therefore, offer a promising indicator for early, directed treatment.57 Of note, aging in and of itself, in both smokers and ever-smokers without airflow obstruction, was found to increase PRMfSAD in an analysis of 580 SPIROMICS subjects.58 This PRM approach was also successfully used in smokers without COPD, where it showed that these metrics can identify unique patterns of progression, and that both PRMfSAD and PRMEMPH, ie, PRM-derived emphysema, can independently predict future development of emphysema.59,60 Bronchiectasis was also found to be associated with increased emphysema in smokers and those with both bronchiectasis and emphysema had lower FEV1 and 6MWD.17 In current or former smokers, the low attenuation area on low-dose CT imaging ordered as part of routine lung cancer screening may be able to detect quantitative emphysema and diagnose subjects with early COPD, allowing clinicians to monitor patients closely and perhaps initiate appropriate treatment when needed.61 These findings suggest that PRM could allow clinicians to further understand the variable disease progression of COPD, resulting in better-tailored treatments.

Coreline

Coreline, based in Seoul, Korea and founded in 2012, has developed the AI-based technology AVIEW COPD. This commercial platform includes quantitative analyses and visualization software that performs automated segmentation to evaluate emphysema, SAD, pulmonary vasculature and airways, and fissure integrity.

At the 2018 annual meeting of the Radiological Society of North America, Coreline presented a voxel-by-voxel segmentation using a 2.5D convolutional neural net and compared it to their gold standard semi-automated algorithm, which uses the airway segmentation module of AVIEW and requires additional processing by research assistants. This AI technology, AVIEW Metric, was found to be practical and reliable when tested on inspiratory CT scans of both healthy subjects and subjects with COPD from the Korean Obstructive Lung Disease (KOLD) study.62 By fully automating various image analysis algorithms, AVIEW Metric segmented all airways in a few minutes and allowed for inspiratory and expiratory lung registration. Researchers have also shown the potential of AVIEW technology for classifying COPD phenotypes. Kwon et al63 assessed how ambient air pollution may predispose subjects to different phenotypes in a study of a Korean cohort of 457 subjects with and without COPD. Using AVIEW software to measure spirometry (FEV1, FVC [forced vital capacity]), degree of emphysema, airway wall thickness, and fSAD, this group evaluated the association of these measurements to the average concentration of environmental particulate matter less than or equal to 10 µm (PM10) in diameter and nitrogen dioxide (NO2). While imaging phenotypes were not associated with NO2, increased exposure to PM10 was associated with lower FVC, increased emphysema, and airway wall thickness. AVIEW software revealed no associations between fSAD and air pollutants. Elsewhere, use of QCT emphysema air-trapping composite (EAtC) maps from AVIEW segmentation software correlated to GOLD staging and lung function, which researchers are studying as a potential biomarker of disease progression.64 Most recently, AVIEW has been used to analyze longitudinal changes over a 6-year period in pulmonary vascular parameters obtained from CT images in 288 COPD patients.65 Degrees of emphysema were classified as five subtypes based on Hounsfield Units and used to assess severity on inspiratory and expiratory scans. Total and small vessel numbers per lung surface area (LSA) were obtained and shown to decrease as COPD progressed. However, these markers had weaker correlations to PFTs. COPD can be distinguished by the emphysema versus bronchitis phenotypes, and these vascular parameters demonstrated that total and small vessel numbers per LSA were higher in the SAD/bronchitis phenotype, confirming that changes in the pulmonary vasculature were more prominent for subjects with predominantly emphysema.

4DMedical

4DMedical, founded in 2012 and based both in Melbourne, Australia and Los Angeles, CA, uses X-ray Velocimetry (XV) Technology to capture simultaneous X-ray images from different acquisition angles to measure the motion of lung tissue at multiple locations during various breath stages. XV then creates colored heat maps of ventilation measurements.66,67 The limited angles from which images are acquired by XV allows for much lower radiation doses than are used for conventional CT scans. XV Lung Ventilation Analysis Software (XV LVAS) is an FDA-approved software that generates reports of areas of high and low ventilation in all phases of breathing.

Reports consist of coronal and axial images rendered in 4-dimensional animation, where red depicts regions of low ventilation, green depicts average ventilation regions, and blue depicts regions of high ventilation (Figure 4). Once the report is generated, it is saved directly onto a hospital’s Picture Archiving and Communication System (PACS). New versions of these reports are actively being developed, and include contrast-free pulmonary angiography, ventilation-perfusion reports, and airway flow and expiratory quantification. Researchers at Johns Hopkins School of Medicine are actively studying XV Technology to validate the clinical benefit of XV LVAS, with the goal of detecting earlier changes in airway function, ventilation defects, and disease progression than clinically available spirometry data and CT images can provide.68 At Vanderbilt University, researchers are comparing the degree of hyperinflation in COPD subjects, as measured by XV image analysis software, to traditional PFTs. This study will also compare lobar expiratory time constraints with fissure completeness measured by StratX software (pulmonx.com/stratx/) with the goal of improving the ability to evaluate patient outcomes after endobronchial valve placement (4D Medical X-ray Velocimetry for Bronchoscopic Lung Volume Reduction Targeting, ClinicalTrials.gov ID NCT04786171).

Figure 4 Representative clinical report of lung ventilation with coronal map, histogram showing specific ventilation and quantitation of ventilation heterogeneity, courtesy of 4D Medical.

Discussion

The commercial platforms reviewed here provide regional functional and anatomic information that enhances our understanding of the heterogeneity of COPD and aids clinicians and researchers in assessing which patients are more likely to experience disease progression and respond to tailored treatments. These novel markers can be harnessed to individualize patient care, moving beyond the widely accepted global metrics obtained from PFTs and patient-reported symptoms. FLUIDDA’s FRI technology highlights key alterations in both airway structure and resistance during COPD exacerbations and with medication use. VIDA’s QCT software Apollo provides similar information by looking at airway remodeling with its airway segmentation tool. Both FLUIDDA and VIDA also explore vessel segmentation. Thirona’s LungQ software has been used to quantify lung volumes and disease distribution, and, more recently, to evaluate fissure completeness, similar to VIDA’s technology. Imbio’s unique capability lies in its PRM maps that can quantify the area of SAD in the lungs to show how these regions evolve with disease progression. Recently, Coreline’s AI-based technology AVIEW COPD has used automated segmentation software to evaluate many of the same key structures, including pulmonary vasculature, fissures, and regions of emphysema and SAD. Lastly, 4DMedical’s XV Technology relies instead on composite X-ray images to create ventilation maps and thereby requires lower radiation doses than the conventional CT scans used by other companies. Of note, this review is based on published literature and online resources, and a full description of each platform and its capabilities would only be attainable through direct contact with the vendor.

Conclusion

The companies discussed in this review have developed a wide array of novel imaging modalities that have already moved the QCT field forward and will allow researchers and clinicians additional insight into the complex disease process of COPD. These imaging biomarkers have demonstrated the ability to predict disease progression earlier and inform the contributions of airway remodeling, air trapping, and emphysema to airflow obstruction and altered pulmonary biomechanics. The geographic distribution of these changes as visualized by automated software has also been validated and could signal accelerated lung function decline not yet captured by global PFT metrics. Such tools also hold the promise of assisting clinicians in advanced bronchoscopic procedures, such as lung volume reduction via coil treatments and endobronchial valves in the appropriate patient population. More importantly, many of the metrics have been correlated to patient symptoms and clinically meaningful outcomes. Even in subjects without airflow obstruction as measured on PFTs, these imaging markers were sensitive to abnormalities that could predict which subgroups were more likely to progress and become symptomatic. This leaves ample opportunity for research focused on key populations, where early intervention and monitoring could change the course of a potentially irreversible disease process with significant life-limiting morbidity and mortality.

Abbreviations

COPD, chronic obstructive pulmonary disease; FRI, functional respiratory imaging; fSAD, functional small airways disease; PFT, pulmonary function testing; PRM, parametric response mapping; QCT, quantitative computed tomography.

Acknowledgments

The authors thank Lee Olsen for assisting with manuscript preparation and editing.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

The research for this review was funded by the National Heart, Lung, and Blood Institute/NIH (grants R01HL139690 and R01HL150023).

Disclosure

Dr. Galbán is co-inventor and patent holder of Parametric Response Mapping, which the University of Michigan has licensed to Imbio, LLC, and has a financial interest in Imbio, LLC. Dr. Labaki reports personal fees from Konica Minolta and Continuing Education Alliance. Dr. Han reports personal fees from GlaxoSmithKline, AstraZeneca, Boehringer Ingelheim, Cipla, Chiesi, Novartis, Pulmonx, Teva, Verona, Merck, Mylan, Sanofi, DevPro, Aerogen, Polarian, Regeneron, United Therapeutics, UpToDate, Medscape, and Integrity. She has received either in kind research support or funds paid to the institution from the National Institutes of Health (NIH), Novartis, Sunovion, Nuvaira, Sanofi, AstraZeneca, Boehringer Ingelheim, Gala Therapeutics, Biodesix, the COPD Foundation, and the American Lung Association. She has participated in Data Safety Monitoring Boards for Novartis and Medtronic with funds paid to the institution. She has received stock options from Meissa Vaccines. The authors report no other conflicts of interest in this work.

References

1. Quaderi SA, Hurst JR. The unmet global burden of COPD. Glob Health Epidemiol Genom. 2018;3:e4. doi:10.1017/gheg.2018.1

2. Agusti A, Calverley PM, Celli B, et al. Characterisation of COPD heterogeneity in the ECLIPSE cohort. Respir Res. 2010;11:122. doi:10.1186/1465-9921-11-122

3. Lopez-Campos JL, Tan W, Soriano JB. Global burden of COPD. Respirology. 2016;21(1):14–23. doi:10.1111/resp.12660

4. Lynch DA, Austin JH, Hogg JC, et al. CT-definable subtypes of chronic obstructive pulmonary disease: a statement of the Fleischner Society. Radiology. 2015;277(1):192–205. doi:10.1148/radiol.2015141579

5. Park J, Hobbs BD, Crapo JD, et al. Subtyping COPD by using visual and quantitative CT imaging features. Chest. 2020;157(1):47–60. doi:10.1016/j.chest.2019.06.015

6. Herth FJF, Kirby M, Sieren J, et al. The modern art of reading computed tomography images of the lungs: quantitative CT. Respiration. 2018;95(1):8–17. doi:10.1159/000480435

7. Lynch DA, Newell JD. Quantitative imaging of COPD. J Thorac Imaging. 2009;24(3):189–194. doi:10.1097/RTI.0b013e3181b31cf0

8. Coxson HO, Rogers RM, Whittall KP, et al. A quantification of the lung surface area in emphysema using computed tomography. Am J Respir Crit Care Med. 1999;159(3):851–856. doi:10.1164/ajrccm.159.3.9805067

9. Gevenois PA, De Vuyst P, de Maertelaer V, et al. Comparison of computed density and microscopic morphometry in pulmonary emphysema. Am J Respir Crit Care Med. 1996;154(1):187–192. doi:10.1164/ajrccm.154.1.8680679

10. Matsuoka S, Kurihara Y, Yagihashi K, Hoshino M, Watanabe N, Nakajima Y. Quantitative assessment of air trapping in chronic obstructive pulmonary disease using inspiratory and expiratory volumetric MDCT. AJR Am J Roentgenol. 2008;190(3):762–769. doi:10.2214/AJR.07.2820

11. Galban CJ, Han MK, Boes JL, et al. Computed tomography-based biomarker provides unique signature for diagnosis of COPD phenotypes and disease progression. Nat Med. 2012;18(11):1711–1715. doi:10.1038/nm.2971

12. Bhatt SP, Bodduluri S, Newell JD, et al. CT-derived biomechanical metrics improve agreement between spirometry and emphysema. Acad Radiol. 2016;23(10):1255–1263. doi:10.1016/j.acra.2016.02.002

13. Vasilescu DM, Martinez FJ, Marchetti N, et al. Noninvasive imaging biomarker identifies small airway damage in severe chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2019;200(5):575–581. doi:10.1164/rccm.201811-2083OC

14. Hammond E, Sloan C, Newell JD Jr, et al. Comparison of low- and ultralow-dose computed tomography protocols for quantitative lung and airway assessment. Med Phys. 2017;44(9):4747–4757. doi:10.1002/mp.12436

15. Gerard SE, Patton TJ, Christensen GE, Bayouth JE, Reinhardt JM. FissureNet: a deep learning approach for pulmonary fissure detection in CT images. IEEE Trans Med Imaging. 2019;38(1):156–166. doi:10.1109/TMI.2018.2858202

16. Estépar RS, Kinney GL, Black-Shinn JL, et al. Computed tomographic measures of pulmonary vascular morphology in smokers and their clinical implications. Am J Respir Crit Care Med. 2013;188(2):231–239. doi:10.1164/rccm.201301-0162OC

17. Martinez CH, Okajima Y, Yen A, et al. Paired CT measures of emphysema and small airways disease and lung function and exercise capacity in smokers with radiographic bronchiectasis. Acad Radiol. 2021;28(3):370–378. doi:10.1016/j.acra.2020.02.013

18. De Backer JW, Vos WG, Vinchurkar SC, et al. Validation of computational fluid dynamics in CT-based airway models with SPECT/CT. Radiology. 2010;257(3):854–862. doi:10.1148/radiol.10100322

19. van Geffen WH, Hajian B, Vos W, et al. Functional respiratory imaging: heterogeneity of acute exacerbations of COPD. Int J Chron Obstruct Pulmon Dis. 2018;13:1783–1792. doi:10.2147/COPD.S152463

20. Hajian B, De Backer J, Vos W, et al. Changes in ventilation-perfusion during and after an COPD exacerbation: an assessment using fluid dynamic modeling. Int J Chron Obstruct Pulmon Dis. 2018;13:833–842. doi:10.2147/COPD.S153295

21. De Backer LA, Vos WG, Salgado R, et al. Functional imaging using computer methods to compare the effect of salbutamol and ipratropium bromide in patient-specific airway models of COPD. Int J Chron Obstruct Pulmon Dis. 2011;6:637–646. doi:10.2147/COPD.S21917

22. De Backer LA, Vos W, De Backer J, Van Holsbeke C, Vinchurkar S, De Backer W. The acute effect of budesonide/formoterol in COPD: a multi-slice computed tomography and lung function study. Eur Respir J. 2012;40(2):298–305. doi:10.1183/09031936.00072511

23. De Backer J, Vos W, Vinchurkar S, et al. The effects of extrafine beclometasone/formoterol (BDP/F) on lung function, dyspnea, hyperinflation, and airway geometry in COPD patients: novel insight using functional respiratory imaging. J Aerosol Med Pulm Drug Deliv. 2015;28(2):88–99. doi:10.1089/jamp.2013.1064

24. De Backer W, De Backer J, Verlinden I, et al. Functional respiratory imaging assessment of glycopyrrolate and formoterol fumarate metered dose inhalers formulated using co-suspension delivery technology in patients with COPD. Ther Adv Respir Dis. 2020;14:1753466620916990. doi:10.1177/1753466620916990

25. De Backer W, De Backer J, Vos W, et al. A randomized study using functional respiratory imaging to characterize bronchodilator effects of glycopyrrolate/formoterol fumarate delivered by a metered dose inhaler using co-suspension delivery technology in patients with COPD. Int J Chron Obstruct Pulmon Dis. 2018;13:2673–2684. doi:10.2147/COPD.S171707

26. Vos W, Hajian B, De Backer J, et al. Functional respiratory imaging to assess the interaction between systemic roflumilast and inhaled ICS/LABA/LAMA. Int J Chron Obstruct Pulmon Dis. 2016;11:263–271. doi:10.2147/COPD.S93830

27. Lanclus M, Clukers J, Van Holsbeke C, et al. Machine learning algorithms utilizing functional respiratory imaging may predict COPD exacerbations. Acad Radiol. 2019;26(9):1191–1199. doi:10.1016/j.acra.2018.10.022

28. Cahn A, Hamblin JN, Robertson J, et al. An inhaled PI3Kdelta inhibitor improves recovery in acutely exacerbating COPD patients: a randomized trial. Int J Chron Obstruct Pulmon Dis. 2021;16:1607–1619. doi:10.2147/COPD.S309129

29. De Backer L, Vos W, Dieriks B, et al. The effects of long-term noninvasive ventilation in hypercapnic COPD patients: a randomized controlled pilot study. Int J Chron Obstruct Pulmon Dis. 2011;6:615–624. doi:10.2147/COPD.S22823

30. Hajian B, De Backer J, Sneyers C, et al. Pathophysiological mechanism of long-term noninvasive ventilation in stable hypercapnic patients with COPD using functional respiratory imaging. Int J Chron Obstruct Pulmon Dis. 2017;12:2197–2205. doi:10.2147/COPD.S136412

31. Hajian B, De Backer J, Vos W, et al. Pulmonary vascular effects of pulsed inhaled nitric oxide in COPD patients with pulmonary hypertension. Int J Chron Obstruct Pulmon Dis. 2016;11:1533–1541. doi:10.2147/COPD.S106480

32. Woodruff PG, Barr RG, Bleecker E, et al. Clinical significance of symptoms in smokers with preserved pulmonary function. N Engl J Med. 2016;374(19):1811–1821. doi:10.1056/NEJMoa1505971

33. Smith BM, Traboulsi H, Austin JHM, et al. Human airway branch variation and chronic obstructive pulmonary disease. Proc Natl Acad Sci USA. 2018;115(5):E974–E981. doi:10.1073/pnas.1715564115

34. Bhatt SP, Terry NL, Nath H, et al. Association between expiratory central airway collapse and respiratory outcomes among smokers. JAMA. 2016;315(5):498–505. doi:10.1001/jama.2015.19431

35. Diaz AA, Han MK, Come CE, et al. Effect of emphysema on CT scan measures of airway dimensions in smokers. Chest. 2013;143(3):687–693. doi:10.1378/chest.12-0039

36. Kim V, Davey A, Comellas AP, et al. Clinical and computed tomographic predictors of chronic bronchitis in COPD: a cross sectional analysis of the COPDGene study. Respir Res. 2014;15:52. doi:10.1186/1465-9921-15-52

37. Kirby M, Yin Y, Tschirren J, et al. A novel method of estimating small airway disease using inspiratory-to-expiratory computed tomography. Respiration. 2017;94(4):336–345. doi:10.1159/000478865

38. Kirby M, Tanabe N, Tan WC, et al. Total airway count on computed tomography and the risk of chronic obstructive pulmonary disease progression. Findings from a population-based study. Am J Respir Crit Care Med. 2018;197(1):56–65. doi:10.1164/rccm.201704-0692OC

39. Choi S, Haghighi B, Choi J, et al. Differentiation of quantitative CT imaging phenotypes in asthma versus COPD. BMJ Open Respir Res. 2017;4(1):e000252. doi:10.1136/bmjresp-2017-000252

40. Gompelmann D, Eberhardt R, Schuhmann M, et al. Lung volume reduction with vapor ablation in the presence of incomplete fissures: 12-month results from the STEP-UP Randomized Controlled Study. Respiration. 2016;92(6):397–403. doi:10.1159/000452424

41. Gompelmann D, Kontogianni K, Schuhmann M, Eberhardt R, Heussel CP, Herth FJ. The minimal important difference for target lobe volume reduction after endoscopic valve therapy. Int J Chron Obstruct Pulmon Dis. 2018;13:465–472. doi:10.2147/COPD.S152029

42. Kontogianni K, Russell K, Eberhardt R, et al. Clinical and quantitative computed tomography predictors of response to endobronchial lung volume reduction therapy using coils. Int J Chronic Obstr. 2018;13:2215–2223. doi:10.2147/Copd.S159355

43. Schuhmann M, Raffy P, Yin Y, et al. Computed tomography predictors of response to endobronchial valve lung reduction treatment. Comparison with chartis. Am J Respir Crit Care Med. 2015;191(7):767–774. doi:10.1164/rccm.201407-1205OC

44. Aaron CP, Hoffman EA, Kawut SM, et al. Ambient air pollution and pulmonary vascular volume on computed tomography: the MESA air pollution and lung cohort studies. Eur Respir J. 2019;53(6):1802116. doi:10.1183/13993003.02116-2018

45. Boueiz A, Chang Y, Cho MH, et al. Lobar emphysema distribution is associated with 5-year radiological disease progression. Chest. 2018;153(1):65–76. doi:10.1016/j.chest.2017.09.022

46. Diaz AA, Strand M, Coxson HO, et al. Disease severity dependence of the longitudinal association between CT lung density and lung function in smokers. Chest. 2018;153(3):638–645. doi:10.1016/j.chest.2017.10.012

47. Pompe E, Strand M, van Rikxoort EM, et al. Five-year progression of emphysema and air trapping at CT in smokers with and those without chronic obstructive pulmonary disease: results from the COPDGene Study. Radiology. 2020;295(1):218–226. doi:10.1148/radiol.2020191429

48. Charbonnier JP, Pompe E, Moore C, et al. Airway wall thickening on CT: relation to smoking status and severity of COPD. Respir Med. 2019;146:36–41. doi:10.1016/j.rmed.2018.11.014

49. Bodduluri S, Kizhakke Puliyakote A, Nakhmani A, Charbonnier JP, Reinhardt JM, Bhatt SP. Computed tomography-based airway surface area-to-volume ratio for phenotyping airway remodeling in chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2021;203(2):185–191. doi:10.1164/rccm.202004-0951OC

50. Welling JBA, Hartman JE, van Rikxoort EM, et al. Minimal important difference of target lobar volume reduction after endobronchial valve treatment for emphysema. Respirology. 2018;23(3):306–310. doi:10.1111/resp.13178

51. Welling JBA, Klooster K, Charbonnier JP, et al. A new oxygen uptake measurement supporting target selection for endobronchial valve treatment. Respiration. 2019;98(6):521–526. doi:10.1159/000502310

52. Slebos DJ, Cicenia J, Sciurba FC, et al. Predictors of response to endobronchial coil therapy in patients with advanced emphysema. Chest. 2019;155(5):928–937. doi:10.1016/j.chest.2019.02.012

53. Bhatt SP, Soler X, Wang X, et al. Association between functional small airway disease and FEV1 decline in chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2016;194(2):178–184. doi:10.1164/rccm.201511-2219OC

54. Criner RN, Hatt CR, Galban CJ, et al. Relationship between diffusion capacity and small airway abnormality in COPDGene. Respir Res. 2019;20(1):269. doi:10.1186/s12931-019-1237-1

55. Pompe E, Galban CJ, Ross BD, et al. Parametric response mapping on chest computed tomography associates with clinical and functional parameters in chronic obstructive pulmonary disease. Respir Med. 2017;123:48–55. doi:10.1016/j.rmed.2016.11.021

56. Han MK, Quibrera PM, Carretta EE, et al. Frequency of exacerbations in patients with chronic obstructive pulmonary disease: an analysis of the SPIROMICS cohort. Lancet Respir Med. 2017;5(8):619–626. doi:10.1016/S2213-2600(17)30207-2

57. Boes JL, Hoff BA, Bule M, et al. Parametric response mapping monitors temporal changes on lung CT scans in the subpopulations and intermediate outcome measures in COPD Study (SPIROMICS). Acad Radiol. 2015;22(2):186–194. doi:10.1016/j.acra.2014.08.015

58. Martinez CH, Diaz AA, Meldrum C, et al. Age and small airway imaging abnormalities in subjects with and without airflow obstruction in SPIROMICS. Am J Respir Crit Care Med. 2017;195(4):464–472. doi:10.1164/rccm.201604-0871OC

59. Labaki WW, Gu T, Murray S, et al. Reprint of: voxel-wise longitudinal parametric response mapping analysis of chest computed tomography in smokers. Acad Radiol. 2019;26(3):306–312. doi:10.1016/j.acra.2019.02.003

60. Pompe E, Moore CM, Mohamed Hoesein FAA, et al. Progression of emphysema and small airways disease in cigarette smokers. Chronic Obstr Pulm Dis. 2021;8(2):198–212. doi:10.15326/jcopdf.2020.0140

61. Labaki WW, Xia M, Murray S, et al. Quantitative emphysema on low-dose CT imaging of the chest and risk of lung cancer and airflow obstruction: an analysis of the national lung screening trial. Chest. 2021;159(5):1812–1820. doi:10.1016/j.chest.2020.12.004

62. Yun J, Park J, Yu D, et al. Improvement of fully automated airway segmentation on volumetric computed tomographic images using a 2.5 dimensional convolutional neural net. Med Image Anal. 2019;51:13–20. doi:10.1016/j.media.2018.10.006

63. Kwon SO, Hong SH, Han YJ, et al. Long-term exposure to PM10 and NO2 in relation to lung function and imaging phenotypes in a COPD cohort. Respir Res. 2020;21(1):247. doi:10.1186/s12931-020-01514-w

64. Hwang HJ, Seo JB, Lee SM, et al. New method for combined quantitative assessment of air-trapping and emphysema on chest computed tomography in chronic obstructive pulmonary disease: comparison with parametric response mapping. Korean J Radiol. 2021;22(10):1719–1729. doi:10.3348/kjr.2021.0033

65. Park SW, Lim M-N, Kim WJ, Bak SH. Quantitative assessment the longitudinal changes of pulmonary vascular counts in chronic obstructive pulmonary disease. Res Square. 2021;23:1.

66. Dubsky S, Hooper SB, Siu KK, Fouras A. Synchrotron-based dynamic computed tomography of tissue motion for regional lung function measurement. J R Soc Interface. 2012;9(74):2213–2224. doi:10.1098/rsif.2012.0116

67. Fouras A, Allison BJ, Kitchen MJ, et al. Altered lung motion is a sensitive indicator of regional lung disease. Ann Biomed Eng. 2012;40(5):1160–1169. doi:10.1007/s10439-011-0493-0

68. 4DMedical. 4DMedical commences clinical trial studying XV LVAS at Johns Hopkins school of medicine; [updated June 29, 2021]. Available from: company-announcements.afr.com/asx/4dx/5329e76d-d85f-11eb-8781-565d0a66e208.pdf. Accessed December 29, 2021.

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