Dynamic chest radiography effective for diagnosing COPD

Will Morton, Associate Editor, AuntMinnie.com. Headshot

Dynamic chest radiography (DCR) can serve as a simpler alternative to pulmonary function tests for diagnosing chronic obstructive pulmonary disease (COPD), according to a study published December 16 in Radiology.

The finding is from a prospective trial in 553 patients with and without COPD, with DCR showing strong correlations with standard spirometry measurements, noted first author Dong Yu, MD, of Southern Medical University in Guangzhou, China, and colleagues.

“DCR represents an efficacious alternative approach to standard pulmonary function tests (PFTs) for COPD screening that simultaneously captures lung function and chest imaging,” the group wrote.

Current diagnostic methods for COPD mainly rely on PFTs such as spirometers. These devices require a high degree of cooperation between physicians and patients, which limits their widespread use, according to the authors. They also carry a risk of aerosol transmission, which was reflected by their limited use during the COVID-19 pandemic, Yu and colleagues added.

Conversely, diaphragmatic motion captured by DCR has been shown previously to correlate with spirometry’s ratio of forced expiratory volume in 1 second (FEV1) to forced vital capacity (FVC) (FEV1/FVC). Projected lung area (PLA) acquired by DCR and the rate of change in PLA (ΔPLA) has also shown a good correlation with FEV1. However, these results have not yet been systematically verified in prospective studies, the authors noted.

To that end, the researchers recruited 553 participants (median age, 60) for a trial conducted at their hospital between November 2022 and July 2024: 191 participants had COPD and 362 served as healthy controls. Participants underwent PFT tests and DCR within one week of enrollment. The researchers then analyzed correlations between DCR parameters and evaluated DCR’s diagnostic performance with an area under the receiver operating curve (AUC) analysis.

Tracking and quantitative analysis of diaphragmatic motion and projected lung area (PLA) at dynamic chest radiography (DCR) in a 55-year-old healthy man during deep breathing. (A) Posteroanterior radiograph with purple and green lines indicating the right and left lateral diaphragm apices, respectively. (B) Graph of diaphragmatic motion (in millimeters; y-axis) over time (i.e., frame number; x-axis). The software tracked the position of the diaphragm apex at DCR to obtain these amplitude-time plots of diaphragmatic motion (right lung, purple; left lung, green). The dark blue line corresponds to the frame representing the end of inspiration; the light blue line corresponds to the frame representing the end of expiration. (C) Posteroanterior radiograph shows the PLA (outline), which is the area surrounded by the medial edge of the ribs, the diaphragm, and the edge of the mediastinum. (D) Graph of PLA (in millimeters squared; y-axis) over time (i.e., frame number; x-axis). The software automatically tracked the boundaries of the lung fields and obtained the time-varying curves of the bilateral lung field areas. The blue line corresponds to the frame representing the end of inspiration.Tracking and quantitative analysis of diaphragmatic motion and projected lung area (PLA) at dynamic chest radiography (DCR) in a 55-year-old healthy man during deep breathing. (A) Posteroanterior radiograph with purple and green lines indicating the right and left lateral diaphragm apices, respectively. (B) Graph of diaphragmatic motion (in millimeters; y-axis) over time (i.e., frame number; x-axis). The software tracked the position of the diaphragm apex at DCR to obtain these amplitude-time plots of diaphragmatic motion (right lung, purple; left lung, green). The dark blue line corresponds to the frame representing the end of inspiration; the light blue line corresponds to the frame representing the end of expiration. (C) Posteroanterior radiograph shows the PLA (outline), which is the area surrounded by the medial edge of the ribs, the diaphragm, and the edge of the mediastinum. (D) Graph of PLA (in millimeters squared; y-axis) over time (i.e., frame number; x-axis). The software automatically tracked the boundaries of the lung fields and obtained the time-varying curves of the bilateral lung field areas. The blue line corresponds to the frame representing the end of inspiration.RSNAAccording to the analysis, bilateral (right and left lung) ΔPLA during deep breathing on DCR correlated well with FEV1 percent predicted (r = 0.65; p < 0.001) and FEV1/FVC (r = 0.638; P < 0.001). In addition, the researchers developed a machine learning nomogram based on three DCR features, which performed well on an internal test set from 57 participants with COPD and 108 controls (AUC, 0.82), the researchers reported.

“A DCR-based nomogram demonstrated robust diagnostic performance in identifying COPD, suggesting that DCR represents an efficacious alternative approach to standard PFTs for COPD screening,” the group wrote.

Ultimately, as DCR technology becomes more feasible, it may prove to be particularly valuable in scenarios where standard PFTs are unavailable or contraindicated, such as in primary care, during pandemics, or in patients who are bedridden, the researchers concluded.

In an accompanying editorial, Hiroto Hatabu, MD, PhD, of the University of Pennsylvania; Shoji Kudoh, MD, PhD, of Nippon Medical School in Tokyo; and Gyorgy Frendl, MD, PhD, of Harvard Medical School in Cambridge, MA, wrote that the clinical use of DCR over standard PFTs would represent a major advancement in screening for and diagnosis and management of pulmonary diseases.

“To our knowledge, no major breakthroughs in point-of-care chest imaging have been reported in the past quarter century,” they wrote.

However, the authors’ conclusion is derived from a single-center trial, and "external validation using independent multicenter cohorts is necessary to confirm the findings in broader populations,” they noted.

“Furthermore, the subclassification of COPD (mild, moderate, and severe categories) is of great interest to clinicians for decision-making and management of COPD," Hatabu, Kudoh, and Frendl concluded. "Assessing whether DCR is also valuable for such subclassification would have been useful and will have to be studied in the future."

The full study is available here.

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