Chest CT measures of muscle and adipose tissue in COPD: gender-based differences in content and in relationships with blood biomarkers

Proteomics and machine learning in the prediction and explanation of low pectoralis muscle area

Low muscle mass is associated with numerous adverse outcomes independent of other associated comorbid diseases. We aimed to predict and understand an individual's risk for developing low muscle mass using proteomics and machine learning. We identified eight biomarkers associated with low pectoralis muscle area (PMA). We built three random forest classification models that used either clinical measures, feature selected biomarkers, or both to predict development of low PMA. The area under the receiver operating characteristic curve for each model was: clinical-only = 0.646, biomarker-only = 0.740, and combined = 0.744. We displayed the heterogenetic nature of an individual's risk for developing low PMA and identified two distinct subtypes of participants who developed low PMA. While additional validation is required, our methods for identifying and understanding individual and group risk for low muscle mass could be used to enable developments in the personalized prevention of low muscle mass.

New Perspectives for Estimating Body Composition From Computed Tomography: Clothing Associated Artifacts

As the value of clinical imaging is expanded through retrospective analyses, it is imperative that all efforts are made to optimize validity. Such considerations for retrospective designs should prioritize factors like naturalistic conditions for observations and measurement replicability, while avoiding sample biases and reliance on strict clinical timelines. Valid methodological approaches are immanent for successful translation from retrospective observational designs into prospective pragmatic research with actionable potential. In particular, thousands of studies have sought to associate clinical outcomes to measures of body composition across diverse patient groups. Post-hoc use of computed tomography (CT) to quantify adiposity and lean tissue characteristics has most frequently involved just a single slice at the level of the third lumbar vertebrae (L3). Abundant in statistical significance and inconsistencies alike, such methods have yet to be implemented or deemed valuable for making real-world clinical decisions. We present herein a concerning perspective, for both magnitude and prevalence, of a widely overlooked source of data variability for this methodology: the hinderance of pants and other tightly fit clothing.

Association between computed tomography-quantified respiratory muscles and chronic obstructive pulmonary disease: a retrospective study

BACKGROUND

This study examined the association between chest muscles and chronic obstructive pulmonary disease (COPD) and the relationship between chest muscle areas and acute exacerbations of COPD (AECOPD).

METHODS

There were 168 subjects in the non-COPD group and 101 patients in the COPD group. The respiratory and accessory respiratory muscle areas were obtained using 3D Slicer software to analysis the imaging of  computed tomography (CT). Univariate and multivariate Poisson regressions were used to analyze the number of AECOPD cases during the preceding year. The cutoff value was obtained using a receiver operating characteristic (ROC) curve.

RESULTS

We scanned 6342 subjects records, 269 of which were included in this study. We then measured the following muscle areas (non-COPD group vs. COPD group): pectoralis major (19.06 ± 5.36 cm2 vs. 13.25 ± 3.71 cm2, P < 0.001), pectoralis minor (6.81 ± 2.03 cm2 vs. 5.95 ± 1.81 cm2, P = 0.001), diaphragmatic dome (1.39 ± 0.97 cm2 vs. 0.85 ± 0.72 cm2, P = 0.011), musculus serratus anterior (28.03 ± 14.95 cm2 vs.16.76 ± 12.69 cm2, P < 0.001), intercostal muscle (12.36 ± 6.64 cm2 vs. 7.15 ± 5.6 cm2, P < 0.001), pectoralis subcutaneous fat (25.91 ± 13.23 cm2 vs. 18.79 ± 10.81 cm2, P < 0.001), paravertebral muscle (14.8 ± 4.35 cm2 vs. 13.33 ± 4.27 cm2, P = 0.007), and paravertebral subcutaneous fat (12.57 ± 5.09 cm2 vs. 10.14 ± 6.94 cm2, P = 0.001). The areas under the ROC curve for the pectoralis major, intercostal, and the musculus serratus anterior muscle areas were 81.56%, 73.28%, and 71.56%, respectively. Pectoralis major area was negatively associated with the number of AECOPD during the preceding year after adjustment (relative risk, 0.936; 95% confidence interval, 0.879-0.996; P = 0.037).

CONCLUSION

The pectoralis major muscle area was negative associated with COPD. Moreover, there was a negative correlation between the number of AECOPD during the preceding year and the pectoralis major area.

Pectoralis Muscle Area as a Predictor of Mortality in Patients Hospitalized with Bronchiectasis Exacerbation

INTRODUCTION

Data on factors related to mortality in patients with bronchiectasis exacerbation are insufficient. Computed tomography (CT) can measure the pectoralis muscle area (PMA) and is a useful tool to diagnose sarcopenia. This study aimed to evaluate whether PMA can predict mortality in patients with bronchiectasis exacerbation.

METHODS

Patients hospitalized due to bronchiectasis exacerbation at a single center were retrospectively divided into survivors and non-survivors based on 1-year mortality. Thereafter, a comparison of the clinical and radiologic characteristics was conducted between the two groups.

RESULTS

A total of 66 (14%) patients died at 1 year. In the multivariate analysis, age, BMI <18.4 kg/m2, sex-specific PMA quartile, ≥3 exacerbations in the previous year, serum albumin <3.5 g/dL, cystic bronchiectasis, tuberculosis-destroyed lung, and diabetes mellitus were independent predictors for the 1-year mortality in patients hospitalized with bronchiectasis exacerbation. A lower PMA was associated with a lower overall survival rate in the survival analysis according to sex-specific quartiles of PMA. PMA had the highest area under the curve during assessment of prognostic performance in predicting the 1-year mortality. The lowest sex-specific PMA quartile group exhibited higher disease severity than the highest quartile group.

CONCLUSIONS

CT-derived PMA was an independent predictor of 1-year mortality in patients hospitalized with bronchiectasis exacerbation. Patients with lower PMA exhibited higher disease severity. These findings suggest that PMA might be a useful marker for providing additional information regarding prognosis of patients with bronchiectasis exacerbation.

Proteomics and Machine Learning in the Prediction and Explanation of Low Pectoralis Muscle Area

Low muscle mass is associated with numerous adverse outcomes independent of other associated comorbid diseases. We aimed to predict and understand an individual's risk for developing low muscle mass using proteomics and machine learning. We identified 8 biomarkers associated with low pectoralis muscle area (PMA). We built 3 random forest classification models that used either clinical measures, feature selected biomarkers, or both to predict development of low PMA. The area under the receiver operating characteristic curve for each model was: clinical-only = 0.646, biomarker-only = 0.740, and combined = 0.744. We displayed the heterogenetic nature of an individual's risk for developing low PMA and identified 2 distinct subtypes of participants who developed low PMA. While additional validation is required, our methods for identifying and understanding individual and group risk for low muscle mass could be used to enable developments in the personalized prevention of low muscle mass.

Reduced Bik expression drives low-grade airway inflammation and increased risk for COPD in females

Chronic low-grade inflammation is increasingly recognized as a subtle yet potent risk factor for a multitude of age-related disorders, including respiratory diseases, cardiovascular conditions, metabolic syndromes, autoimmunity, and cancer. In this issue of the JCI, Mebratu, Jones, and colleagues shed new light on the mechanisms that promote low-grade airway inflammation and how this contributes to the development of chronic obstructive pulmonary disease (COPD). Their finding that Bik deficiency leads to spontaneous emphysema in female mice, but not in males, marks a notable advancement in our understanding of how inflammatory processes can diverge based on biological sex. This finding is of clinical relevance, given the vulnerability of women to developing COPD.

A fully automated pipeline for the extraction of pectoralis muscle area from chest computed tomography scans

Background

Computed tomography (CT)-derived pectoralis muscle area (PMA) measurements are prognostic in people with or at-risk of COPD, but fully automated PMA extraction has yet to be developed. Our objective was to develop and validate a PMA extraction pipeline that can automatically: 1) identify the aortic arch slice; and 2) perform pectoralis segmentation at that slice.

Methods

CT images from the Canadian Cohort of Obstructive Lung Disease (CanCOLD) study were used for pipeline development. Aorta atlases were used to automatically identify the slice containing the aortic arch by group-based registration. A deep learning model was trained to segment the PMA. The pipeline was evaluated in comparison to manual segmentation. An external dataset was used to evaluate generalisability. Model performance was assessed using the Dice-Sorensen coefficient (DSC) and PMA error.

Results

In total 90 participants were used for training (age 67.0±9.9 years; forced expiratory volume in 1 s (FEV1) 93±21% predicted; FEV1/forced vital capacity (FVC) 0.69±0.10; 47 men), and 32 for external testing (age 68.6±7.4 years; FEV1 65±17% predicted; FEV1/FVC 0.50±0.09; 16 men). Compared with manual segmentation, the deep learning model achieved a DSC of 0.94±0.02, 0.94±0.01 and 0.90±0.04 on the true aortic arch slice in the train, validation and external test sets, respectively. Automated aortic arch slice detection obtained distance errors of 1.2±1.3 mm and 1.6±1.5 mm on the train and test data, respectively. Fully automated PMA measurements were not different from manual segmentation (p>0.05). PMA measurements were different between people with and without COPD (p=0.01) and correlated with FEV1 % predicted (p<0.05).

Conclusion

A fully automated CT PMA extraction pipeline was developed and validated for use in research and clinical practice.

Muscle mass cross-sectional area is associated with survival outcomes in malignant pleural disease related to lung cancer

INTRODUCTION

Malignant pleural effusions are common in advanced malignancy and associated with overall poor survival. The presence of sarcopenia (decreased muscle mass) is associated with poor outcomes in numerous disease states, however, its relationship to malignant pleural disease has not been defined. We sought to understand if there was an association between decreased survival and decreased muscle mass in patients with malignant pleural effusion.

METHODS

Patients with malignant pleural disease undergoing indwelling tunneled pleural catheter placement were retrospectively reviewed. Computed tomography was reviewed and cross-sectional area of pectoralis and paraspinous muscle areas were calculated. Overall survival and associations with muscle mass were calculated.

RESULTS

A total of 309 patients were available for analysis, with a median age of 67 years and the majority female (58%). The median survival was 129 days from initial pleural drainage to death. Regression analysis and Kaplan-Meier survival analysis did not reveal an association with survival and muscle mass for the entire population. However, Kaplan-Meier survival analysis of the lung cancer subgroup revealed the presence of decreased muscle mass and decreased survival time.

CONCLUSION

The presence of decreased muscle mass within a lung cancer population that has malignant pleural effusions are associated with decreased survival. However, the presence of decreased muscle mass within a heterogenous population of malignant pleural disease was not associated with decreased overall survival time. Further study of the role that sarcopenia may play in malignant pleural disease is warranted.

Deep learning-based pectoralis muscle volume segmentation method from chest computed tomography image using sagittal range detection and axial slice-based segmentation

The pectoralis muscle is an important indicator of respiratory muscle function and has been linked to various parenchymal biomarkers, such as airflow limitation severity and diffusing capacity for carbon monoxide, which are widely used in diagnosing parenchymal diseases, including asthma and chronic obstructive pulmonary disease. Pectoralis muscle segmentation is a method for measuring muscle volume and mass for various applications. The segmentation method is based on deep-learning techniques that combine a muscle area detection model and a segmentation model. The training dataset for the detection model comprised multichannel images of patients, whereas the segmentation model was trained on 7,796 cases of the computed tomography (CT) image dataset of 1,841 patients. The dataset was expanded incrementally through an active learning process. The performance of the model was evaluated by comparing the segmentation results with manual annotations by radiologists and the volumetric differences between the CT image datasets of the same patients. The results indicated that the machine learning model is promising in segmenting the pectoralis major muscle, with good agreement between the automatic segmentation and manual annotations by radiologists. The training accuracy and loss values of the validation set were 0.9954 and 0.0725, respectively, and for segmentation, the loss value was 0.0579. This study shows the potential clinical usefulness of the machine learning model for pectoralis major muscle segmentation as a quantitative biomarker for various parenchymal and muscular diseases.

CT-Derived Deep Learning-Based Quantification of Body Composition Associated with Disease Severity in Chronic Obstructive Pulmonary Disease

Purpose

Our study aimed to evaluate the association between automated quantified body composition on CT and pulmonary function or quantitative lung features in patients with chronic obstructive pulmonary disease (COPD).

Materials and Methods

A total of 290 patients with COPD were enrolled in this study. The volume of muscle and subcutaneous fat, area of muscle and subcutaneous fat at T12, and bone attenuation at T12 were obtained from chest CT using a deep learning-based body segmentation algorithm. Parametric response mapping-derived emphysema (PRMemph), PRM-derived functional small airway disease (PRMfSAD), and airway wall thickness (AWT)-Pi10 were quantitatively assessed. The association between body composition and outcomes was evaluated using Pearson's correlation analysis.

Results

The volume and area of muscle and subcutaneous fat were negatively associated with PRMemph and PRMfSAD (p < 0.05). Bone density at T12 was negatively associated with PRMemph (r = -0.1828, p = 0.002). The volume and area of subcutaneous fat and bone density at T12 were positively correlated with AWT-Pi10 (r = 0.1287, p = 0.030; r = 0.1668, p = 0.005; r = 0.1279, p = 0.031). However, muscle volume was negatively correlated with the AWT-Pi10 (r = -0.1966, p = 0.001). Muscle volume was significantly associated with pulmonary function (p < 0.001).

Conclusion

Body composition, automatically assessed using chest CT, is associated with the phenotype and severity of COPD.

Deep Learning-based Approach to Predict Pulmonary Function at Chest CT

Background Low-dose chest CT screening is recommended for smokers with the potential for lung function abnormality, but its role in predicting lung function remains unclear. Purpose To develop a deep learning algorithm to predict pulmonary function with low-dose CT images in participants using health screening services. Materials and Methods In this retrospective study, participants underwent health screening with same-day low-dose CT and pulmonary function testing with spirometry at a university affiliated tertiary referral general hospital between January 2015 and December 2018. The data set was split into a development set (model training, validation, and internal test sets) and temporally independent test set according to first visit year. A convolutional neural network was trained to predict the forced expiratory volume in the first second of expiration (FEV₁) and forced vital capacity (FVC) from low-dose CT. The mean absolute error and concordance correlation coefficient (CCC) were used to evaluate agreement between spirometry as the reference standard and deep-learning prediction as the index test. FVC and FEV₁ percent predicted (hereafter, FVC% and FEV₁%) values less than 80% and percent of FVC exhaled in first second (hereafter, FEV₁/FVC) less than 70% were used to classify participants at high risk. Results A total of 16 148 participants were included (mean age, 55 years ± 10 [SD]; 10 981 men) and divided into a development set (n = 13 428) and temporally independent test set (n = 2720). In the temporally independent test set, the mean absolute error and CCC were 0.22 L and 0.94, respectively, for FVC and 0.22 L and 0.91 for FEV₁. For the prediction of the respiratory high-risk group, FVC%, FEV₁%, and FEV₁/FVC had respective accuracies of 89.6% (2436 of 2720 participants; 95% CI: 88.4, 90.7), 85.9% (2337 of 2720 participants; 95% CI: 84.6, 87.2), and 90.2% (2453 of 2720 participants; 95% CI: 89.1, 91.3) in the same testing data set. The sensitivities were 61.6% (242 of 393 participants; 95% CI: 59.7, 63.4), 46.9% (226 of 482 participants; 95% CI: 45.0, 48.8), and 36.1% (91 of 252 participants; 95% CI: 34.3, 37.9), respectively. Conclusion A deep learning model applied to volumetric chest CT predicted pulmonary function with relatively good performance. © RSNA, 2023 Supplemental material is available for this article.

Increased chest CT derived bone and muscle measures capture markers of improved morbidity and mortality in COPD

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a disease of accelerated aging and is associated with comorbid conditions including osteoporosis and sarcopenia. These extrapulmonary conditions are highly prevalent yet frequently underdiagnosed and overlooked by pulmonologists in COPD treatment and management. There is evidence supporting a role for bone-muscle crosstalk which may compound osteoporosis and sarcopenia risk in COPD. Chest CT is commonly utilized in COPD management, and we evaluated its utility to identify low bone mineral density (BMD) and reduced pectoralis muscle area (PMA) as surrogates for osteoporosis and sarcopenia. We then tested whether BMD and PMA were associated with morbidity and mortality in COPD.

METHODS

BMD and PMA were analyzed from chest CT scans of 8468 COPDGene participants with COPD and controls (smoking and non-smoking). Multivariable regression models tested the relationship of BMD and PMA with measures of function (6-min walk distance (6MWD), handgrip strength) and disease severity (percent emphysema and lung function). Multivariable Cox proportional hazards models were used to evaluate the relationship between sex-specific quartiles of BMD and/or PMA derived from non-smoking controls with all-cause mortality.

RESULTS

COPD subjects had significantly lower BMD and PMA compared with controls. Higher BMD and PMA were associated with increased physical function and less disease severity. Participants with the highest BMD and PMA quartiles had a significantly reduced mortality risk (36% and 46%) compared to the lowest quartiles.

CONCLUSIONS

These findings highlight the potential for CT-derived BMD and PMA to characterize osteoporosis and sarcopenia using equipment available in the pulmonary setting.

Computed tomography-based body composition measures in COPD and their association with clinical outcomes: A systematic review

Background

Computed tomography (CT) is commonly utilized in chronic obstructive pulmonary disease (COPD) for lung cancer screening and emphysema characterization. Computed tomography-morphometric analysis of body composition (muscle mass and adiposity) has gained increased recognition as a marker of disease severity and prognosis. This systematic review aimed to describe the CT-methodology used to assess body composition and identify the association of body composition measures and disease severity, health-related quality of life (HRQL), cardiometabolic risk factors, respiratory exacerbations, and survival in patients with COPD.

Methods

Six databases were searched (inception-September 2021) for studies evaluating adult COPD patients using thoracic or abdominal CT-muscle or adiposity body composition measures. The systematic review was conducted in accordance with the PRISMA guidelines.

Results

Twenty eight articles were included with 15,431 COPD patients, across all GOLD stages with 77% males, age range (mean/median 59–78 years), and BMI range 19.8–29.3 kg/m². There was heterogeneity in assessment of muscle mass and adiposity using thoracic (n = 22) and abdominal (n = 8) CT-scans, capturing different muscle groups, anatomic locations, and adiposity compartments (visceral, subcutaneous, and epicardial). Low muscle mass and increased adiposity were associated with increased COPD severity measures (lung function, exercise capacity, dyspnea) and lower HRQL, but were not consistent across studies. Increased visceral adiposity (n = 6) was associated with cardiovascular disease or risk factors (hypertension, hyperlipidemia, and diabetes). Low muscle CSA was prognostic of respiratory exacerbations or mortality in three of six studies, whereas the relationship with increased intermuscular adiposity and greater mortality was only observed in one of three studies.

Conclusion

There was significant variability in CT-body composition measures. In several studies, low muscle mass was associated with increased disease severity and lower HRQL, whereas adiposity with cardiovascular disease/risk factors. Given the heterogeneity in body composition measures and clinical outcomes, the prognostic utility of CT-body composition in COPD requires further study.

Physical Activity, Exercise Capacity, and Body Composition in U.S. Veterans with Chronic Obstructive Pulmonary Disease (COPD)

RATIONALE

Differences in body composition may contribute to variability in exercise capacity (EC) and physical activity (PA) in chronic obstructive pulmonary disease (COPD). Most studies have employed bioimpedance-based surrogates of muscle (lean) mass; relatively few studies have included consideration of fat mass and limited studies have been performed using dual X-ray absorptiometry (DXA)-assessed body composition.

OBJECTIVE

To determine whether DXA-assessed muscle (lean) and fat mass exhibit differential correlations with EC and PA in COPD Methods: US Veterans with COPD (defined as FEV1/FVC<0.7 or emphysema on clinical chest computed tomography) had DXA-assessed body composition, EC (6-minute walk distance; 6MWD), objective PA (average daily step counts), and self-reported PA measured at enrollment. Associations between EC, PA, and body composition were examined using Spearman correlations and multivariable models adjusted a priori for age, sex, race, and lung function.

RESULTS

Subjects (n=98) were predominantly white (88%), obese (mean BMI 30.2±6.2), and male, (94%) with a mean age (±SD) of 69.9±7.9 years and moderate airflow obstruction (mean FEV1% 68±20). Modest inverse correlations between EC and PA with fat mass were observed (Spearman's rho range [-0.20]-[-0.34]) while measures of muscle (lean) mass were not significantly associated with EC or PA. The appendicular skeletal muscle (ASM)-to-weight ratio, which considers both muscle (lean) and fat mass, was consistently associated with EC (8.4 [95%CI=2.9-13.8] meter increase on 6MWD per 1% increase in ASM-to-weight ratio), objective PA (194.8 [95%CI=15.2-374.4] steps per day per 1% increase in ASM-to-weight ratio), and self-reported PA in multivariable-adjusted models.

CONCLUSION

DXA-assessed body composition measures which include consideration of both lean and fat mass are associated with cross-sectional EC and PA in COPD populations. Clinical trial registered at ClinicalTrials.gov (NCT02099799).

Associations of pulmonary and extrapulmonary computed tomographic manifestations with impaired physical activity in symptomatic patients with chronic obstructive pulmonary disease

In patients with chronic obstructive pulmonary disease (COPD), emphysema, airway disease, and extrapulmonary comorbidities may cause various symptoms and impair physical activity. To investigate the relative associations of pulmonary and extrapulmonary manifestations with physical activity in symptomatic patients, this study enrolled 193 patients with COPD who underwent chest inspiratory/expiratory CT and completed COPD assessment test (CAT) and the Life-Space Assessment (LSA) questionnaires to evaluate symptom and physical activity. In symptomatic patients (CAT ≥ 10, n = 100), emphysema on inspiratory CT and air-trapping on expiratory CT were more severe and height-adjusted cross-sectional areas of pectoralis muscles (PM index) and adjacent subcutaneous adipose tissue (SAT index) on inspiratory CT were smaller in those with impaired physical activity (LSA < 60) than those without. In contrast, these findings were not observed in less symptomatic patients (CAT < 10). In multivariable analyses of the symptomatic patients, severe air-trapping and lower PM index and SAT index, but not CT-measured thoracic vertebrae bone density and coronary artery calcification, were associated with impaired physical activity. These suggest that increased air-trapping and decreased skeletal muscle and subcutaneous adipose tissue quantity are independently associated with impaired physical activity in symptomatic patients with COPD.

Adipose tissue provides a cushioning effect in low-energy isolated blunt thoracic trauma: a prospective observational study

INTRODUCTION

This study aimed to investigate the specific effects of subcutaneous adipose tissue thickness (SATT) on trauma-related injury (TRI) development in patients with low-energy isolated blunt thoracic trauma.

PATIENTS AND METHODS

This prospective observational study was performed between March 2018-March 2019. Patients admitted to our hospital because of blunt thoracic trauma were enrolled. SATT in axial CT images of the thorax was measured using the four anatomically designated localizations. Patients were analyzed in terms of demographic data, BMI, comorbid diseases, causes of injury, vital parameters, visual analog scale, trauma score, injury type, treatment, and hospitalization. A poor clinical outcome was defined as the development of a TRI.

RESULTS

The study group consisted of 152 patients (43 female, 109 male). The mean age was 49 ± 19.1 years. There was a positive linear association between the BMI and SATT for all the patients in the study. TRI frequency was higher in the low-SATT subgroup than in the high-SATT group (p < 0.001). BMI and mean SATT values were related to a poor logistic regression analysis outcome (p < 0.01). Being in the low-BMI subgroup was a risk factor for TRI development (p < 0.01; OR:0.23;95% CI:0.08-0.61).

CONCLUSION

We found that a low SATT and BMI were related to a poor clinical outcome in our study group. It is essential to carefully examine these patients in detail, even in low-energy trauma. Subcutaneous tissue over the thorax serves as a protective shield for other thoracic structures in patients with LEBTT.

Cardiopulmonary exercise testing has greater prognostic value than sarcopenia in oesophago-gastric cancer patients undergoing neoadjuvant therapy and surgical resection

BACKGROUND

Sarcopenia (low skeletal muscle mass), myosteatosis (low skeletal muscle radiation-attenuation) and fitness are independently associated with postoperative outcomes in oesophago-gastric cancer. This study aimed to investigate (1) the effect of neoadjuvant therapy (NAT) on sarcopenia, myosteatosis and cardiopulmonary exercise testing (CPET), (2) the relationship between these parameters, and (3) their association with postoperative morbidity and survival.

METHODS

Body composition analysis used single slice computed tomography (CT) images from chest (superior to aortic arch) and abdominal CT scans (third lumbar vertebrae). Oxygen uptake at anaerobic threshold (VO2 at AT) and at peak exercise (VO2 Peak) were measured using CPET. Measurements were performed before and after NAT and an adjusted regression model assessed their association.

RESULTS

Of the 184 patients recruited, 100 underwent surgical resection. Following NAT skeletal muscle mass, radiation-attenuation and fitness reduced significantly (p < 0.001). When adjusted for age, sex, and body mass index, only pectoralis muscle mass was associated with VO2 Peak (p = 0.001). VO2 at AT and Peak were associated with 1-year survival, while neither sarcopenia nor myosteatosis were associated with morbidity or survival.

CONCLUSION

Skeletal muscle and CPET variables reduced following NAT and were positively associated with each other. Cardiorespiratory function significantly contributes to short-term survival after oesophago-gastric cancer surgery.

Low thoracic muscle mass index on computed tomography predicts adverse outcomes following lobectomy via thoracotomy for lung cancer

OBJECTIVES

The aim of this study was to determine whether the preoperative thoracic muscle mass is associated with postoperative outcomes in patients undergoing lobectomy via thoracotomy for lung cancer.

METHODS

Consecutive patients undergoing lobectomy were retrospectively reviewed. The thoracic muscle mass index (TMMI) was obtained at the level of the fifth thoracic vertebra on preoperative thoracic computed tomography (CT). Patients were analysed comparatively by being dividing into low and high muscle index groups by the median of sex-specific TMMI. The primary outcomes were the incidence of any or postoperative pulmonary complications. The secondary outcomes were postoperative intensive care unit (ICU) admission, length of stay (LOS) in the ICU, total hospital LOS, readmission and mortality.

RESULTS

The study population consisted of 120 patients (63.6 ± 9.8 years; 74% male). Each groups included 60 patients. Major complications occurred in 28.3% (34/120) and readmission in 18.3% (22/120) of patients. The adjusted multivariable analysis showed that each unit increase in TMMI (cm2/m2) was independently associated with the rates of less any complications [odds ratio (OR) 0.92, P = 0.014], pulmonary complications (OR 0.27, P = 0.019), ICU admission (OR 0.76, P = 0.031), hospitalization for >6 days (OR 0.90, P = 0.008) and readmission (OR 0.93, P = 0.029).

CONCLUSIONS

Low TMMI obtained from the preoperative thoracic CT is an independent predictor of postoperative adverse outcomes in patients following lobectomy via thoracotomy for lung cancer. TMMI measurements may contribute to the development of preoperative risk stratification studies in the future.

Pectoralis muscle area and its association with indices of disease severity in interstitial lung disease

RATIONALE

The pathophysiology of interstitial lung disease (ILD) impacts body composition, whereby ILD severity is linked to lower lean mass.

OBJECTIVES

To determine i) if pectoralis muscle area (PMA) is a surrogate for whole-body lean mass in ILD, ii) whether PMA is associated with ILD severity, and iii) if the longitudinal change in PMA is associated with pulmonary function and mortality in ILD.

METHODS

Patients with ILD (n = 164) were analyzed retrospectively. PMA was quantified from a chest computed tomography scan. Peripheral oxygen saturation (SpO₂), 6-min walk distance (6MWD), and pulmonary function were obtained as part of routine clinical care. Dyspnea and quality of life were assessed using the UCSD Shortness of Breath Questionnaire and European Quality of Life 5 Dimensions questionnaire, respectively.

RESULTS

PMA was associated with whole-body lean mass (p < 0.001). After adjusting for age, sex, height, body mass, and prednisone status, PMA was associated with %-predicted forced vital capacity (FVC), %-predicted diffusion capacity (DL_CO), resting and exertional SpO₂, and dyspnea (all p < 0.05), but not forced expiratory volume in 1 s (FEV₁), FEV₁/FVC, 6MWD, or quality of life (all p > 0.05). The annual negative PMA slope was associated with annual negative slopes in FVC, FEV₁, and DL_CO (all p < 0.05), but not FEV₁/FVC (p = 0.46). Annual slope in PMA was associated with all-cause mortality (hazard ratio = -0.80, 95% CI:0.889-0.959; p < 0.001).

CONCLUSION

In patients with ILD, PMA is a suitable surrogate for whole-body lean mass. A lower PMA is associated with indices of ILD severity, which supports the notion that ILD progression may involve sarcopenia.

Sex and Gender Omic Biomarkers in Men and Women With COPD: Considerations for Precision Medicine

Sex and gender differences in lung health and disease are imperative to consider and study if precision pulmonary medicine is to be achieved. The development of reliable COPD biomarkers has been elusive, and the translation of biomarkers to clinical care has been limited. Useful and effective biomarkers must be developed with attention to clinical heterogeneity of COPD; inherent heterogeneity exists related to grouping women and men together in the studies of COPD. Considering sex and gender differences and influences related to -omics may represent progress in susceptibility, diagnostic, prognostic, and therapeutic biomarker development and clinical innovation to improve the lung health of men and women.

Novel Nutrition-Based Nomograms to Assess the Outcomes of Lung Cancer Patients Treated With Anlotinib or Apatinib

Background

Previous studies have indicated that the changes in body composition during treatment are prognostic in lung cancer. The question which follows is it may be too late to identify vulnerable patients after treatment and to improve outcomes for these patients. In our study, we sought to explore the alterations of body composition and weight before the outset of the antiangiogenic treatment and its role in predicting clinical response and outcomes.

Methods

In this retrospective study, 122 patients with advanced lung cancer treated with anlotinib or apatinib were analyzed. The changes in weight and body composition including skeletal muscle index (SMI), subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT) for 3 months before the outset of antiangiogenic treatment and other clinical characteristics were evaluated with LASSO Cox regression and multivariate Cox regression analysis, which were applied to construct nomograms. The performance of the nomograms was validated internally by using bootstrap method with 1,000 resamples models and was assessed by the concordance index (C-index), calibration plots, decision curve analysis (DCA).

Results

The median progression-free survival (PFS) and overall survival (OS) were 128 (95% CI 103.2–152.8) days and 292 (95% CI 270.9–313.1) days. Eastern Cooperative Oncology Group performance status (ECOG PS), brain metastases, the Glasgow Prognostic Score (GPS), clinical response, therapeutic regimen, and ΔL1SMI per 90 days were significantly associated with PFS, while ECOG PS, GPS, clinical response, therapeutic regimen, ΔL1SMI per 90 days were identified for OS. The C-index for the nomograms of PFS and OS were 0.763 and 0.748, respectively. The calibration curves indicated excellent agreement between the predicted and actual survival outcomes of 3- and 4-month PFS and 7- and 8-month OS. DCA showed the considerable value of the model.

Conclusion

Nomograms were developed from clinical features and nutritional indicators to predict the probability of achieving 3-month and 4-month PFS and 7-month and 8-month OS with antiangiogenic therapy for advanced lung cancer. Dynamic changes in body composition before the initiation of treatment contributed to early detection of poor outcome.

Distinguishing Smoking-Related Lung Disease Phenotypes Via Imaging and Molecular Features

BACKGROUND

Chronic tobacco smoke exposure results in a broad range of lung pathologies including emphysema, airway disease and parenchymal fibrosis as well as a multitude of extra-pulmonary comorbidities. Prior work using CT imaging has identified several clinically relevant subgroups of smoking related lung disease, but these investigations have generally lacked organ specific molecular correlates.

RESEARCH QUESTION

Can CT imaging be used to identify clinical phenotypes of smoking related lung disease that have specific bronchial epithelial gene expression patterns to better understand disease pathogenesis?

STUDY DESIGN AND METHODS

Using K-means clustering, we clustered participants from the COPDGene study (n = 5,273) based on CT imaging characteristics and then evaluated their clinical phenotypes. These clusters were replicated in the Detection of Early Lung Cancer Among Military Personnel (DECAMP) cohort (n = 360), and were further characterized using bronchial epithelial gene expression.

RESULTS

Three clusters (preserved, interstitial predominant and emphysema predominant) were identified. Compared to the preserved cluster, the interstitial and emphysema clusters had worse lung function, exercise capacity and quality of life. In longitudinal follow-up, individuals from the emphysema group had greater declines in exercise capacity and lung function, more emphysema, more exacerbations, and higher mortality. Similarly, genes involved in inflammatory pathways (tumor necrosis factor-α, interferon-β) are more highly expressed in bronchial epithelial cells from individuals in the emphysema cluster, while genes associated with T-cell related biology are decreased in these samples. Samples from individuals in the interstitial cluster generally had intermediate levels of expression of these genes.

INTERPRETATION

Using quantitative CT imaging, we identified three groups of individuals in older ever-smokers that replicate in two cohorts. Airway gene expression differences between the three groups suggests increased levels of inflammation in the most severe clinical phenotype, possibly mediated by the tumor necrosis factor-α and interferon-β pathways.

CLINICAL TRIAL REGISTRATION

COPDGene (NCT00608764), DECAMP-1 (NCT01785342), DECAMP-2 (NCT02504697).

Advances in Chronic Obstructive Pulmonary Disease Imaging

Chest computed tomography (CT) imaging is a useful tool that provides in vivo information regarding lung structure. Imaging has contributed to a better understanding of COPD, allowing for the detection of early structural changes and the quantification of extra-pulmonary structures. Novel CT imaging techniques have provided insight into the progression of the main COPD subtypes, such as emphysema and small airway disease. This article serves as a review of new information relevant to COPD imaging. CT abnormalities, such as emphysema and loss of airways, are present even in smokers who do not meet the criteria for COPD and in those with mild-to-moderate disease. Subjects with mild-to-moderate COPD, with the highest loss of airways, also experience the highest decline in lung function. Extra-pulmonary manifestations of COPD, such as right ventricle enlargement and low muscle mass measured on CT, are associated with increased risk for all-cause mortality. CT longitudinal data has also given insight into the progression of COPD. Mechanically affected areas of lung parenchyma adjacent to emphysematous areas are associated with a greater decline in FEV₁. Subjects with the greatest percentage of small airway disease, as measured on matched inspiratory-expiratory CT scan, also present with the greatest decline in lung function.

Chest computed tomography is a valid measure of body composition in individuals with advanced lung disease

There is growing interest in evaluating body composition using routine clinical computed tomography (CT) scans; however, the validity of this technique in lung transplant patients has not been described. The study objectives were to determine the reliability of measuring fat compartments from thoracic CT and evaluate the validity of muscle and fat cross-sectional area (CSA) from thoracic CT by comparing to bioelectrical impedance analysis (BIA). Thoracic CT scans from lung transplant assessments were obtained for analysis. Total thoracic muscle CSA, pectoral muscle CSA, subcutaneous adipose tissue (SAT), and mediastinal adipose tissue (MAT) were manually segmented by two independent raters. Reliability was analysed using intra-class correlation coefficient (ICC). Correlations were determined between CT measures with fat-free mass index (FFMI), body fat mass index (BFMI) and per cent body fat (%BF) from BIA; and anthropometrics [body mass index (BMI) and waist circumference (WC)]. High inter- and intra-rater reliability were found for SAT and MAT (ICCs = 0.99). Pectoral and total muscle CSA were correlated with FFMI (r = .41, p = .003 and r = .57, p < .001, respectively). SAT was associated with whole-body fat from BIA and with BMI and WC (r = .61 to .80, p < .001). MAT was associated with BMI (r = .58, p < .001) and WC (r = .61, p < .001). This study supports the reliability and validity of using thoracic CT to measure muscle and fat. Future studies are needed to investigate whether these CT-based measures are predictive of clinical and post-transplant outcomes in advanced lung disease.

Smaller Left Ventricle Size at Noncontrast CT Is Associated with Lower Mortality in COPDGene Participants

Background Smokers with chronic obstructive pulmonary disease (COPD) have smaller left ventricles (LVs) due to reduced preload. Skeletal muscle wasting is also common in COPD, but less is known about its contribution to LV size. Purpose To explore the relationships between CT metrics of emphysema, venous vascular volume, and sarcopenia with the LV epicardial volume (LV_EV) (myocardium and chamber) estimated from chest CT images in participants with COPD and then to determine the clinical relevance of the LV_EV in multivariable models, including sex and anthropomorphic metrics. Materials and Methods The COPDGene study (ClinicalTrials.gov identifier: NCT00608764) is an ongoing prospective longitudinal observational investigation that began in 2006. LV_EV, distal pulmonary venous blood volume for vessels smaller than 5 mm² in cross section (BV5), CT emphysema, and pectoralis muscle area were retrospectively extracted from 3318 nongated, unenhanced COPDGene CT scans. Multivariable linear and Cox regression models were used to explore the association between emphysema, venous BV5, pectoralis muscle area, and LV_EV as well as the association of LV_EV with health status using the St George's Respiratory Questionnaire, 6-minute walk distance, and all-cause mortality. Results The median age of the cohort was 64 years (interquartile range, 57-70 years). Of the 2423 participants, 1806 were men and 617 were African American. The median LV_EV between Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1 and GOLD 4 COPD was reduced by 13.9% in women and 17.7% in men (P < .001 for both). In fully adjusted models, higher emphysema percentage (β = -4.2; 95% confidence interval [CI]: -5.0, -3.4; P < .001), venous BV5 (β = 7.0; 95% CI: 5.7, 8.2; P < .001), and pectoralis muscle area (β = 2.7; 95% CI: 1.2, 4.1; P < .001) were independently associated with reduced LV_EV. Reductions in LV_EV were associated with improved health status (β = 0.3; 95% CI: 0.1, 0.4) and 6-minute walk distance (β = -12.2; 95% CI: -15.2, -9.3). These effects were greater in women than in men. The effect of reduced LV_EV on mortality (hazard ratio: 1.07; 95% CI: 1.05, 1.09) did not vary by sex. Conclusion In women more than men with chronic obstructive pulmonary disease, a reduction in the estimated left ventricle epicardial volume correlated with a loss of pulmonary venous vasculature, greater pectoralis muscle sarcopenia, and lower all-cause mortality. © RSNA, 2020 Online supplemental material is available for this article.

Chronic Obstructive Pulmonary Disease in Women: A Biologically Focused Review with a Systematic Search Strategy

Purpose

Evidence suggests that chronic obstructive pulmonary disease (COPD) symptoms and progression may differ between men and women. However, limited information is currently available on the pathophysiological and biological factors that may underlie these sex-related differences. The objective of this review is to systematically evaluate reports of potential sex-related differences, including genetic, pathophysiological, structural, and other biological factors, that may influence COPD development, manifestation, and progression in women.

Patients and Methods

A PubMed literature search was conducted from inception until January 2020. Original reports of genetic, hormonal, and physiological differences, and biological influences that could contribute to COPD development, manifestation, and progression in women were included.

Results

Overall, 491 articles were screened; 29 articles met the inclusion criteria. Results from this analysis demonstrated between-sex differences in inflammatory, immune, genetic, structural, and physiological factors in patients with COPD.

Conclusion

Various biological differences are observed between men and women with COPD including differences in inflammatory and metabolic pathways related to obesity and fat distribution, immune cell function and autophagy, extent and distribution of emphysema and airway wall remodeling. An enhanced understanding of these differences has the potential to broaden our understanding of how COPD develops and progresses, thereby providing an opportunity to ultimately improve diagnosis, treatment, and monitoring of COPD in both men and women.

Association between thoracic fat measured using computed tomography and lung function in a population without respiratory diseases

Background

Local fat distribution patterns and their local or systemic effects have recently attracted significant attention. The aim of this study was to assess the impact of thoracic adiposity on lung function in a population without respiratory diseases according to sex.

Methods

A total of 455 subjects (282 males and 173 females), who had undergone spirometry, and chest and abdominal computed tomography between June 2012 and June 2016 at medical healthcare center, were included. Pericardial fat, intrathoracic fat, subcutaneous thoracic fat, and both visceral and subcutaneous abdominal fat were measured by directly assessing tissue volume using computed tomography. Multiple linear regression analyses adjusted for pack-years of smoking, high-density lipoprotein, and high-sensitivity C-reactive protein were performed to evaluate the association between fat volumes and lung function.

Results

In males, intrathoracic fat and visceral abdominal fat were inversely associated with forced expiratory volume in 1 s (FEV₁) % predicted (P=0.025, P=0.010, respectively), and subcutaneous thoracic fat volumes showed a negative correlation with both FEV₁% and forced vital capacity (FVC) % predicted (P=0.019, P=0.045, respectively). In females, subcutaneous thoracic fat demonstrated a negative correlation with both FEV₁% and FVC % predicted (P=0.031 and P=0.008, respectively).

Conclusions

The influence of local thoracic fat distribution on lung function differed according to sex. Visceral fat and subcutaneous thoracic fat in males and subcutaneous fat in females were significantly associated with decreased lung function.

Computed tomography-derived area and density of pectoralis muscle associated disease severity and longitudinal changes in chronic obstructive pulmonary disease: a case control study

BACKGROUND

Muscle wasting is associated with prognosis in patients with chronic obstructive pulmonary disease (COPD). The cross-sectional area of skeletal muscles on computed tomography (CT) could serve as a method to evaluate body composition. The present study aimed to determine the ability of CT-derived pectoralis muscle area (PMA) and pectoralis muscle density (PMD) to determine the severity of COPD and change in longitudinal pulmonary function in patients with COPD.

METHODS

A total of 293 participants were enrolled in this study, a whom 222 had undergone at least two spirometry measurements within 3 years after baseline data acquisition. PMA and PMD were measured from a single axial slice of chest CT above the aortic arch at baseline. The emphysema index and bronchial wall thickness were quantitatively assessed in all scans. The generalized linear model was used to determine the correlation between PMA and PMD measurements and pulmonary function.

RESULTS

PMA and PMD were significantly associated with baseline lung function and the severity of emphysema (P < 0.05). Patients with the lowest PMA and PMD exhibited significantly more severe airflow obstruction (β = - 0.06; 95% confidence interval: - 0.09 to - 0.03]. PMA was statistically associated with COPD assessment test (CAT) score (P = 0.033). However, PMD did not exhibit statistically significant correlation with either CAT scores or modified Medical Research Council scores (P > 0.05). Furthermore, neither PMA nor PMD were associated with changes in forced expiratory volume in 1 s over a 3-year periods.

CONCLUSIONS

CT-derived features of the pectoralis muscle may be helpful in predicting disease severity in patients with COPD, but are not necessarily associated with longitudinal changes in lung function.

Cross-sectional and longitudinal assessment of muscle from regular chest computed tomography scans: L1 and pectoralis muscle compared to L3 as reference in non-small cell lung cancer

Background

Computed tomography (CT) is increasingly used in clinical research for single-slice assessment of muscle mass to correlate with clinical outcome and evaluate treatment efficacy. The third lumbar level (L3) is considered as reference for muscle, but chest scans generally do not reach beyond the first lumbar level (L1). This study investigates if pectoralis muscle and L1 are appropriate alternatives for L3.

Methods

CT scans of 115 stage IV non-small cell lung cancer patients were analyzed before and during tumor therapy. Skeletal muscle assessed at pectoralis and L1 muscle was compared to L3 at baseline. Furthermore, the prognostic significance of changes in muscle mass determined at different locations was investigated.

Results

Pearson’s correlation coefficient between skeletal muscle at L3 and L1 was stronger (r=0.90, P<0.001) than between L3 and pectoralis muscle (r=0.71, P<0.001). Cox regression analysis revealed that L3 (HR 0.943, 95% CI: 0.92–0.97, P<0.001) and L1 muscle loss (HR 0.954, 95% CI: 0.93–0.98, P<0.001) predicted overall survival, whereas pectoralis muscle loss did not.

Conclusion

L1 is a better alternative than pectoralis muscle to substitute L3 for analysis of muscle mass from regular chest CT scans.

Quantification of body-torso-wide tissue composition on low-dose CT images via automatic anatomy recognition

PURPOSE

Quantification of body composition plays an important role in many clinical and research applications. Radiologic imaging techniques such as Dual-energy X-ray absorptiometry (DXA), magnetic resonance imaging (MRI), and computed tomography (CT) imaging make accurate quantification of the body composition possible. However, most current imaging-based methods need human interaction to quantify multiple tissues. When dealing with whole-body images of many subjects, interactive methods become impractical. This paper presents an automated, efficient, accurate, and practical body composition quantification method for low-dose CT images.

METHOD

Our method, named automatic anatomy recognition body composition analysis (AAR-BCA), aims to quantify four tissue components in body torso (BT) - subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), bone tissue, and muscle tissue - from CT images of given whole-body positron emission tomography/computed tomography (PET/CT) acquisitions. AAR-BCA consists of three key steps - modeling BT with its ensemble of key objects from a population of patient images, recognition or localization of these objects in a given patient image I, and delineation and quantification of the four tissue components in I guided by the recognized objects. In the first step, from a given set of patient images and the associated delineated objects, a fuzzy anatomy model of the key object ensemble, including anatomic organs, tissue regions, and tissue interfaces, is built where the objects are organized in a hierarchical order. The second step involves recognizing, or finding roughly the location of, each object in any given whole-body image I of a patient following the object hierarchy and guided by the built model. The third step makes use of this fuzzy localization information of the objects and the intensity distributions of the four tissue components, already learned and encoded in the model, to optimally delineate in a fuzzy manner and quantify these components. All parameters in our method are determined from training datasets.

RESULTS

Thirty-eight low-dose CT images from different subjects are tested in a fivefold cross-validation strategy for evaluating AAR-BCA with a 23-15 train-test dataset division. For BT, over all objects, AAR-BCA achieves a false-positive volume fraction (FPVF) of 3.7% and false-negative volume fraction (FNVF) of 3.8%. Notably, SAT achieves both a FPVF and FNVF under 3%. For bone tissue, it achieves a FPVF and a FNVF both under 3.5%. For VAT tissue, the FNVF of 4.8% is higher than for other objects and so also for muscle (4.7%). The level of accuracy for the four tissue components in individual body subregions mostly remains at the same level as for BT. The processing time required per patient image is under a minute.

CONCLUSIONS

Motivated by applications in cancer and systemic diseases, our goal in this paper was to seek a practical method for body composition quantification which is automated, accurate, and efficient, and works on BT in low-dose CT. The proposed AAR-BCA method toward this goal can quantify four tissue components including SAT, VAT, bone tissue, and muscle tissue in the body torso with under 5% overall error. All needed parameters can be automatically estimated from the training datasets.

Imaging Advances in Chronic Obstructive Pulmonary Disease. Insights from the Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) Study

The Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study, which began in 2007, is an ongoing multicenter observational cohort study of more than 10,000 current and former smokers. The study is aimed at understanding the etiology, progression, and heterogeneity of chronic obstructive pulmonary disease (COPD). In addition to genetic analysis, the participants have been extensively characterized by clinical questionnaires, spirometry, volumetric inspiratory and expiratory computed tomography, and longitudinal follow-up, including follow-up computed tomography at 5 years after enrollment. The purpose of this state-of-the-art review is to summarize the major advances in our understanding of COPD resulting from the imaging findings in the COPDGene study. Imaging features that are associated with adverse clinical outcomes include early interstitial lung abnormalities, visual presence and pattern of emphysema, the ratio of pulmonary artery to ascending aortic diameter, quantitative evaluation of emphysema, airway wall thickness, and expiratory gas trapping. COPD is characterized by the early involvement of the small conducting airways, and the addition of expiratory scans has enabled measurement of small airway disease. Computational advances have enabled indirect measurement of nonemphysematous gas trapping. These metrics have provided insights into the pathogenesis and prognosis of COPD and have aided early identification of disease. Important quantifiable extrapulmonary findings include coronary artery calcification, cardiac morphology, intrathoracic and extrathoracic fat, and osteoporosis. Current active research includes identification of novel quantitative measures for emphysema and airway disease, evaluation of dose reduction techniques, and use of deep learning for phenotyping COPD.

Frailty and geriatric conditions in older patients with idiopathic pulmonary fibrosis

BACKGROUND

Functional status, an important predictor of health outcomes in older patients, has not been studied in an IPF population. This study aimed to determine the prevalence of frailty and geriatric conditions in older patients with IPF.

METHODS

IPF patients age ≥65 years were identified prospectively at the University of Michigan. Frailty was assessed using the Fried frailty phenotype. Questionnaires addressing functional status, geriatric conditions and symptoms were administered. Quantitative measurement of pectoralis muscle area was performed. Patient variables were compared among different frailty groups.

RESULTS

Of the 50 participants, 48% were found to be frail and 40% had ≥2 geriatric conditions. Frailty was associated with increased age, lower lung function, shorter 6-min walk distance, higher symptom scores and a greater number of comorbidities, geriatric conditions and functional limitations (p < 0.05). Pectoralis muscle area was nearly significant (p = 0.08). Self-reported fatigue score (odds ratio [OR] = 2.13, confidence interval [CI] 95% 1.23-3.70, p = 0.0068) and diffusion capacity (OR = 0.54 CI 95% 0.35-0.85, p = 0.0071) were independent predictors of frailty.

CONCLUSIONS

Frailty and geriatric conditions are common in older patients with IPF. The presence of frailty was associated with objective (diffusion capacity) and subjective (self-reported fatigue score) data. Longitudinal evaluation is necessary to determine impact of frailty on disease-related outcomes in IPF.

Pectoralis muscle area and mortality in smokers without airflow obstruction

Background

Low muscle mass is associated with increased mortality in the general population but its prognostic value in at-risk smokers, those without expiratory airflow obstruction, is unknown. We aimed to test the hypothesis that reduced muscle mass is associated with increased mortality in at-risk smokers.

Methods

Measures of both pectoralis and paravertebral erector spinae muscle cross-sectional area (PMA and PVMA, respectively) as well as emphysema on chest computed tomography (CT) scans were performed in 3705 current and former at-risk smokers (≥10 pack-years) aged 45–80 years enrolled into the COPDGene Study between 2008 and 2013. Vital status was ascertained through death certificate. The association between low muscle mass and mortality was assessed using Cox regression analysis.

Results

During a median of 6.5 years of follow-up, 212 (5.7%) at-risk smokers died. At-risk smokers in the lowest (vs. highest) sex-specific quartile of PMA but not PVMA had 84% higher risk of death in adjusted models for demographics, smoking, dyspnea, comorbidities, exercise capacity, lung function, emphysema on CT, and coronary artery calcium content (hazard ratio [HR] 1.85 95% Confidence interval [1.14–3.00] P = 0.01). Results were consistent when the PMA index (PMA/height²) was used instead of quartiles. The association between PMA and death was modified by smoking status (P = 0.04). Current smokers had a significantly increased risk of death (lowest vs. highest PMA quartile, HR 2.25 [1.25–4.03] P = 0.007) while former smokers did not.

Conclusions

Low muscle mass as measured on chest CT scans is associated with increased mortality in current smokers without airflow obstruction.

Trial registration

NCT00608764

Electronic supplementary material

The online version of this article (10.1186/s12931-018-0771-6) contains supplementary material, which is available to authorized users.

Lung, Fat and Bone: Increased Adiponectin Associates with the Combination of Smoking-Related Lung Disease and Osteoporosis

Background: Adiponectin has been proposed as a biomarker of disease severity and progression in chronic obstructive pulmonary disease (COPD) and associated with spirometry-defined COPD and with computed tomography (CT)-measured emphysema. Increased adiponectin plays a role in other diseases including diabetes/metabolic syndrome, cardiovascular disease and osteoporosis. Previous studies of adiponectin and COPD have not assessed the relationship of adiponectin to airway disease in smokers and have not evaluated the effect of other comorbid diseases on the relationship of adiponectin and lung disease. We postulated that adiponectin levels would associate with both airway disease and emphysema in smokers with and without COPD, and further postulated that body composition and the comorbid diseases of osteoporosis, cardiovascular disease and diabetes might influence adiponectin levels. Methods: Current and former smokers from the COPD Genetic Epidemiology study (COPDGene) (n= 424) were assigned to 4 groups based on CT lung characteristics and volumetric Bone Density (vBMD). Emphysema (% low attenuation area at -950) and airway disease (Wall area %) were used to assess smoking-related lung disease (SRLD). Group 1) Normal Lung with Normal vBMD; Group 2) Normal Lung and Osteoporosis; Group 3) SRLD with Normal vBMD; Group 4) SRLD with Osteoporosis. Cardiovascular disease (CVD), diabetes, C-reactive protein (CRP) and T-cadherin (soluble receptor for adiponectin) levels were defined for each group. Body composition was derived from chest CT. Multivariable regression assessed effects of emphysema, wall area %, bone density, comorbid diseases and other key factors on log adiponectin. Results: Group 4, SRLD with Osteoporosis, had significantly higher adiponectin levels compared to other groups and the effect persisted in adjusted models. Systemic inflammation (by CRP) was associated with SRLD in Groups 3 and 4 but not with osteoporosis alone. In regression models, lower bone density and worse emphysema were associated with higher adiponectin. Airway disease was associated with higher adiponectin levels when T-cadherin was added to the model. Male gender, greater muscle and fat were associated with lower adiponectin. Conclusions: Adiponectin is increased with both airway disease and emphysema in smokers. Bone density, and fat and muscle composition are all significant factors predicting adiponectin that should be considered when it is used as a biomarker of COPD. Increased adiponectin from chronic inflammation may play a role in the progression of bone loss in COPD and other lung diseases.

Thoracic Skeletal Muscle Is Associated With Adverse Outcomes After Lobectomy for Lung Cancer

BACKGROUND

Assessment of risk associated with lung cancer resection is primarily based on evaluation of cardiopulmonary function and remains imprecise. We investigated the relationship between thoracic muscle and early outcomes after lobectomy.

METHODS

Cross-sectional area of skeletal muscle was measured at the level of the fifth thoracic vertebra on computed tomography in 135 consecutive patients before lobectomy for lung cancer. Patients were stratified into low and high muscle groups using the sex-specific muscle median. Primary outcome was a composite of any postoperative complication as per The Society of Thoracic Surgeons General Thoracic Surgical Database. Secondary outcomes included postoperative respiratory complications, postoperative intensive care unit admission, hospital length of stay, and hospital readmission within 30 days of hospital discharge. The χ² test, adjusted multivariable regression analysis, and likelihood ratio test were performed.

RESULTS

Patients with low muscle were significantly more likely to have any postoperative complication and respiratory postoperative complications. Although postoperative intensive care unit admission was similar for low muscle and high muscle groups, low muscle patients had longer hospital length of stay and a higher rate of hospital readmission. Adjusted multivariable regression revealed the independent association of thoracic muscle with all outcomes. The likelihood ratio test suggested that thoracic muscle adds predictive capability to information captured by preoperative pulmonary function testing.

CONCLUSIONS

Low thoracic muscle is independently associated with increased postoperative complications and health care utilization among patients undergoing lobectomy for lung cancer. Evaluation of thoracic muscle may enhance risk prediction models.

Chest computed tomography-derived low fat-free mass index and mortality in COPD

Low fat-free mass index (FFMI) is an independent risk factor for mortality in chronic obstructive pulmonary disease (COPD) not typically measured during routine care. In the present study, we aimed to derive fat-free mass from the pectoralis muscle area (FFM_PMA) and assess whether low FFMI_PMA is associated with all-cause mortality in COPD cases. We used data from two independent COPD cohorts, ECLIPSE and COPDGene.Two equal sized groups of COPD cases (n=759) from the ECLIPSE study were used to derive and validate an equation to calculate the FFM_PMA measured using bioelectrical impedance from PMA. We then applied the equation in COPD cases (n=3121) from the COPDGene cohort, and assessed survival. Low FFMI_PMA was defined, using the Schols classification (FFMI <16 in men, FFMI <15 in women) and the fifth percentile normative values of FFMI from the UK Biobank.The final regression model included PMA, weight, sex and height, and had an adjusted R² of 0.92 with fat-free mass (FFM) as the outcome. In the test group, the correlation between FFM_PMA and FFM remained high (Pearson correlation=0.97). In COPDGene, COPD cases with a low FFMI_PMA had an increased risk of death (HR 1.6, p<0.001).We demonstrated COPD cases with a low FFMI_PMA have an increased risk of death.

Handgrip Strength in Chronic Obstructive Pulmonary Disease. Associations with Acute Exacerbations and Body Composition

RATIONALE

Handgrip strength (HGS) predicts mortality in the elderly, but its determinants and clinical significance in chronic obstructive pulmonary disease (COPD) has not been defined.

OBJECTIVES

We tested associations of HGS with pectoralis muscle area (PMA), subcutaneous adipose tissue (SAT), imaging characteristics, and lung function in smokers with COPD, and evaluated the cross-sectional and longitudinal associations of HGS with acute respiratory events.

METHODS

We analyzed demographic, clinical, spirometry, HGS, and imaging data of 272 subjects with COPD, obtaining measures of airway thickness, emphysema, PMA, and SAT from chest computed tomography scans. We tested associations of lung function and imaging characteristics with HGS, using linear models. HGS association to acute respiratory events at enrollment and during follow-up (mean, 2.6 years) was analyzed using adjusted logistic models.

RESULTS

HGS correlated with PMA, SAT, forced expiratory volume, and airway thickness, but not with body mass index or emphysema severity. In adjusted regression models, HGS was directly (β, 1.5; 95% confidence interval [CI], 0.1-3.0) and inversely (β, -3.3; 95% CI, -5.1 to -0.9) associated with one standard deviation of PMA and SAT, respectively, independent of body mass index and emphysema. In regression models adjusted for age, sex, body mass index, race, pack-years smoked, current smoking, chronic bronchitis, FEV1% predicted, emphysema, and airway metrics, HGS was associated with exacerbation risk; in cross-sectional analyses, there was an increment of 5% in the risk of exacerbations for each 1-kg decrement in HGS (risk ratio, 1.05; 95% CI, 1.01-1.08), and there was a similar risk during follow-up (risk ratio, 1.04; 95% CI, 1.01-1,07).

CONCLUSIONS

In ever-smokers with COPD, HGS is associated with computed tomography markers of body composition and airway thickness, independent of body mass index and emphysema. Higher HGS is associated with lower exacerbation frequency.

Differences in Respiratory Symptoms and Lung Structure Between Hispanic and Non-Hispanic White Smokers: A Comparative Study

Background: Prior studies have demonstrated that U.S. Hispanic smokers have a lower risk of decline in lung function and chronic obstructive pulmonary disease (COPD) compared with non-Hispanic whites (NHW). This suggests there might be racial-ethnic differences in susceptibility in cigarette smoke-induced respiratory symptoms, lung parenchymal destruction, and airway and vascular disease, as well as in extra-pulmonary manifestations of COPD. Therefore, we aimed to explore respiratory symptoms, lung function, and pulmonary and extra-pulmonary structural changes in Hispanic and NHW smokers. Methods: We compared respiratory symptoms, lung function, and computed tomography (CT) measures of emphysema-like tissue, airway disease, the branching generation number (BGN) to reach a 2-mm-lumen-diameter airway, and vascular pruning as well as muscle and fat mass between 39 Hispanic and 39 sex-, age- and smoking exposure-matched NHW smokers. Results: Hispanic smokers had higher odds of dyspnea than NHW after adjustment for COPD and asthma statuses (odds ratio[OR] = 2.96; 95% confidence interval [CI] 1.09-8.04), but no significant differences were found in lung function and CT measurements. Conclusions: While lung function and CT measures of the lung structure were similar, dyspnea is reported more frequently by Hispanic than matched-NHW smokers. It seems to be an impossible puzzle but it's easy to solve a Rubik' Cube using a few algorithms.

Determinants of pre-transplantation pectoralis muscle area (PMA) and post-transplantation change in PMA in lung transplant recipients

BACKGROUND

This study aimed to determine predictors of pectoralis muscle area (PMA) and assess change in PMA following lung transplantation and its relationship to outcomes.

METHODS

A retrospective review of 88 lung transplant recipients at a single center was performed. PMA was determined on a single axial slice from chest computerized tomography. Pectoralis muscle index (PMI) was calculated from the PMA divided by the height squared.

RESULTS

PMI decreased post-transplantation (8.1±2.8 cm² /m² pre-transplantation, 7.5±2.9 cm² /m² at 6 months, and 7.6±2.7 cm² /m² at 12 months, P<.05). Chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD) were predictors of pre-transplant PMI (β=-2.3, P=.001 for COPD; β=2.1, P<.001 for ILD) and percent change in PMI at 12 months post-transplantation relative to baseline (β=19.2, P=.04 for COPD; β=-20.1, P=.01 for ILD). Patients in the highest quartile for PMI change at 12 months had fewer ventilator days compared with patients in the other quartiles (P=.03).

CONCLUSIONS

Underlying diagnosis was a significant predictor of both pre-transplantation PMI and change in PMI post-transplantation. Further studies of PMI are needed to determine its clinical utility in predicting outcomes following lung transplantation.

Lower Pectoralis Muscle Area Is Associated with a Worse Overall Survival in Non-Small Cell Lung Cancer

BACKGROUND

Muscle wasting is a component of the diagnosis of cancer cachexia and has been associated with poor prognosis. However, recommended tools to measure sarcopenia are limited by poor sensitivity or the need to perform additional scans. We hypothesized that pectoralis muscle area (PMA) measured objectively on chest CT scan may be associated with overall survival (OS) in non-small cell lung cancer (NSCLC).

METHODS

We evaluated 252 cases from a prospectively enrolling lung cancer cohort. Eligible cases had CT scans performed prior to the initiation of surgery, radiation, or chemotherapy. PMA was measured in a semi-automated fashion while blinded to characteristics of the tumor, lung, and patient outcomes.

RESULTS

Men had a significantly greater PMA than women (37.59 vs. 26.19 cm², P < 0.0001). In univariate analysis, PMA was associated with age and body mass index (BMI). A Cox proportional hazards model was constructed to account for confounders associated with survival. Lower pectoralis area (per cm²) at diagnosis was associated with an increased hazard of death of 2% (HR_adj, 0.98; confidence interval, 0.96-0.99; P = 0.044) while adjusting for age, sex, smoking, chronic bronchitis, emphysema, histology, stage, chemotherapy, radiation, surgery, BMI, and ECOG performance status.

CONCLUSIONS

Lower PMA measured from chest CT scans obtained at the time of diagnosis of NSCLC is associated with a worse OS.

IMPACT

PMA may be a valuable CT biomarker for sarcopenia-associated lung cancer survival. Cancer Epidemiol Biomarkers Prev; 26(1); 38-43. ©2016 AACR SEE ALL THE ARTICLES IN THIS CEBP FOCUS SECTION, "THE OBESITY PARADOX IN CANCER EVIDENCE AND NEW DIRECTIONS".

Cachexia in chronic obstructive pulmonary disease: new insights and therapeutic perspective

Cachexia and muscle wasting are well recognized as common and partly reversible features of chronic obstructive pulmonary disease (COPD), adversely affecting disease progression and prognosis. This argues for integration of weight and muscle maintenance in patient care. In this review, recent insights are presented in the diagnosis of muscle wasting in COPD, the pathophysiology of muscle wasting, and putative mechanisms involved in a disturbed energy balance as cachexia driver. We discuss the therapeutic implications of these new insights for optimizing and personalizing management of COPD-induced cachexia.

Challenges and Current Efforts in the Development of Biomarkers for Chronic Inflammatory and Remodeling Conditions of the Lungs

This review discusses biomarkers that are being researched for their usefulness to phenotype chronic inflammatory lung diseases that cause remodeling of the lung's architecture. The review focuses on asthma, chronic obstructive pulmonary disease (COPD), and pulmonary hypertension. Bio-markers of environmental exposure and specific classes of biomarkers (noncoding RNA, metabolism, vitamin, coagulation, and microbiome related) are also discussed. Examples of biomarkers that are in clinical use, biomarkers that are under development, and biomarkers that are still in the research phase are discussed. We chose to present examples of the research in biomarker development by diseases, because asthma, COPD, and pulmonary hypertension are distinct entities, although they clearly share processes of inflammation and remodeling.