Association of pectoralis muscle area on computed tomography with airflow limitation severity and respiratory outcomes in COPD: A population-based prospective cohort study

Increased plasma interleukin-1β is associated with accelerated lung function decline in non-smokers

Interleukin-1β is one of the major cytokines involved in the initiation and persistence of airway inflammation in chronic obstructive pulmonary disease (COPD). However, the association between plasma interleukin-1β and lung function decline remains unclear. We aimed to explore the association between plasma interleukin-1β and lung function decline. This longitudinal evaluation of data from the Early COPD study analysed the association between the plasma interleukin-1β concentration, lung function decline, and COPD exacerbation. Overall, 1,328 participants were included in the baseline analysis, and 1,135 (85%) completed the 1-year follow-up. Increased plasma interleukin-1β was associated with accelerated lung function decline in non-smokers (forced expiratory volume in 1 s: per unit natural log-transformed increase, adjusted unstandardised β [95% confidence interval] 101.46 [16.73-186.18] mL/year, p=0.019; forced vital capacity: per unit natural log-transformed increase, adjusted unstandardised β [95% confidence interval] 146.20 [93.65-198.75] mL/year, p<0.001), but not in smokers. In non-smokers, participants with an interleukin-1β concentration in the top 30% (>5.02 pg/mL) had more respiratory symptoms, more severe emphysema and air trapping, and higher levels of inflammation-related biomarkers. In this study, a subgroup with increased plasma interleukin-1β was identified among non-smokers, and increased plasma interleukin-1β was associated with lung function accelerated decline.

Association of Exercise Tolerance with Respiratory Health Outcomes in Mild-to-Moderate Chronic Obstructive Pulmonary Disease

Rationale: Previous studies have identified exercise intolerance in patients with mild-to-moderate chronic obstructive pulmonary disease (COPD). The association of exercise tolerance with lung function decline and acute exacerbation risk in mild-to-moderate COPD is unclear, especially in the community population. Objectives: We evaluated exercise tolerance in patients with mild-to-moderate COPD and analyzed its associations with respiratory health outcomes. Methods: We analyzed data from the community-based ECOPD (Early Chronic Obstructive Pulmonary Disease) study of patients with mild-to-moderate COPD (postbronchodilator forced expiratory volume in 1 second (FEV1):forced vital capacity < 0.70 and FEV1 ≥ 50% predicted). Patients who completed questionnaires, spirometry, and cardiopulmonary exercise testing at baseline were included. Annual exacerbation assessment and spirometry were conducted for 2 years consecutively. Exercise tolerance was defined as the percentage of predicted peak oxygen uptake ([Formula: see text]o2peak% predicted). We analyzed the association between exercise tolerance, annual lung function decline, and acute exacerbation risk. Results: Overall, 338 patients were included in the baseline analysis, and 319 completed the 2-year follow up. The mean ± standard deviation of [Formula: see text]o2peak% predicted was 79.8 ± 13.7%. Low [Formula: see text]o2peak% predicted was associated with more chronic respiratory symptoms, worse lung function, severer emphysema, and air trapping at baseline. During the 2-year follow up, a decrease of 13.7% (1 standard deviation) in [Formula: see text]o2peak% predicted was associated with a decline in prebronchodilator FEV1:forced vital capacity (difference, 0.4% [95% confidence interval, 0.1-0.7%]; P = 0.003) and higher total exacerbation risk (relative risk, 1.25 [95% confidence interval, 1.08-1.46]; P = 0.004) after adjustment. Conclusions: Patients with mild-to-moderate COPD and exercise intolerance have worse respiratory health outcomes, for which low exercise tolerance is a prognostic marker. Clinical trial registered with www.chictr.org.cn (ChiCTR1900024643).

Application of Artificial Intelligence in Thoracic Radiology: A Narrative Review

Thoracic radiology has emerged as a primary field in which artificial intelligence (AI) is extensively researched. Recent advancements highlight the potential to enhance radiologists' performance through AI. AI aids in detecting and classifying abnormalities, and in quantifying both normal and abnormal anatomical structures. Additionally, it facilitates prognostication by leveraging these quantitative values. This review article will discuss the recent achievements of AI in thoracic radiology, focusing primarily on deep learning, and explore the current limitations and future directions of this cutting-edge technique.

Muscles and Central Neural Networks Involved in Breathing: State of the Art

Breathing is a systemic act, which involves not only the lungs, but the entire body system. To have a comprehensive clinical picture, it is necessary to have all the patient's data; from this assumption, we can affirm that it is necessary to know all the muscles involved in breathing to understand how to obtain a comprehensive approach for the care and treatment of the patient to improve respiratory capacity. The text reviews the efferent connections of the respiratory centers and cites all the muscles that are involved in the mechanism of breathing and that are controlled and managed by the respiratory centers, starting from the muscular description of the cranial area, the bucco-cervical area, the cervicothoracic area, and the thoracic area. Knowing the function of the respiratory accessory muscles allows us to obtain, in some clinical cases, valuable data that can prove predictive of the diagnostic path of the pathology. This is the first article in the literature, to the authors' knowledge, that attempts to list and include in a single text all the muscles directly or indirectly involved in breathing. The goal of this narrative review article is to remind clinicians and researchers involved in the study of different muscular respiratory responses that we need to analyze and work all the skeletal musculature involved in breathing to better understand what happens in the pathological or physiological phases during breathing. This step will allow us to better individualize the therapeutic and training approach for healthy subjects.

Association of computed tomography-derived pectoralis muscle area and density with disease severity and respiratory symptoms in patients with chronic obstructive pulmonary disease: A case-control study

RATIONALE AND OBJECTIVES

Computed tomography (CT) is commonly used and offers an additional viewpoint for evaluating extrapulmonary symptoms, disease severity, and muscle atrophy. This study assessed whether the pectoralis muscle area (PMA) and pectoralis muscle density (PMD) are lower in patients with chronic obstructive pulmonary disease (COPD) than in healthy controls and elucidated their relationships with these variables.

MATERIALS AND METHODS

The participants were enrolled in the hospital outpatient clinic between October 2023 and May 2024. Information was obtained from questionnaires, lung function, and CT imaging findings. On full-inspiratory CT, the PMA and PMD were measured at the aortic arch level using predetermined attenuation ranges of -29 and 150 Hounsfield units. We observed lower PMA and PMD and evaluated their associations with lung function, respiratory symptoms, and CT imaging findings in patients with COPD.

RESULTS

Overall, 120 participants were enrolled at baseline (60 healthy controls and 60 patients with COPD). PMA and PMD were lower with progressive airflow limitation severity in those with COPD. The degree of emphysema and air trapping, as well as lung function, were correlated with PMA and PMD (P < 0.05), although not with the COPD Assessment Test or modified Medical Research Council scores (P > 0.05).

CONCLUSION

Participants with COPD had smaller PMA and PMD. These measurements were correlated with the severity of airflow limitation, lung function, emphysema, and air trapping, suggesting that these features of the pectoralis muscle obtained from CT are helpful in assessments of patients with COPD.

Definition, diagnosis, and treatment of respiratory sarcopenia

PURPOSE OF REVIEW

Skeletal muscle weakness and wasting also occurs in the respiratory muscles, called respiratory sarcopenia. Respiratory sarcopenia may lead to worse clinical indicators and outcomes. We present a novel definition and diagnostic criteria for respiratory sarcopenia, summarize recent reports on the association between respiratory sarcopenia, physical and nutritional status, and clinical outcomes, and provide suggestions for the prevention and treatment of respiratory sarcopenia.

RECENT FINDINGS

Recently, a novel definition and diagnostic criteria for respiratory sarcopenia have been prepared. Respiratory sarcopenia is defined as a condition in which there is both low respiratory muscle strength and low respiratory muscle mass. Respiratory muscle strength, respiratory muscle mass, and appendicular skeletal muscle mass are used to diagnose respiratory sarcopenia. Currently, it is challenging to definitively diagnose respiratory sarcopenia due to the difficulty in accurately determining low respiratory muscle mass. Decreased respiratory muscle strength and respiratory muscle mass are associated with lower physical and nutritional status and poorer clinical outcomes. Exercise interventions, especially respiratory muscle training, nutritional interventions, and their combinations may effectively treat respiratory sarcopenia. Preventive interventions for respiratory sarcopenia are unclear.

SUMMARY

The novel definition and diagnostic criteria will contribute to promoting the assessment and intervention of respiratory sarcopenia.

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.