Analysis of pulmonary sounds for the diagnosis of interstitial lung diseases secondary to rheumatoid arthritis. (1st May 2018)

• Record Type: Journal Article
• Authors: Pancaldi, Fabrizio; Sebastiani, Marco; Cassone, Giulia; Luppi, Fabrizio; Cerri, Stefania; Della Casa, Giovanni; Manfredi, Andreina
• Is Part Of: Computers in biology and medicine. Volume 96(2018)
• Page Start: 91
• Page End: 97
• Publication Date: 2018-05-01
• Subjects: Rheumatoid arthritis -- Interstitial lung disease -- Early diagnosis -- Lung sounds -- Velcro crackle -- Estimation -- Detection; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2018.03.006
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: The diagnosis of interstitial lung diseases in patients affected by rheumatoid arthritis is fundamental to improving their survival rate. In particular, the average survival time of patients affected by rheumatoid arthritis with pulmonary implications is approximately 3 years. The gold standard for confirming the diagnosis of this disease is computer tomography. However, it is very difficult to raise diagnosis suspicion because the symptoms of the disease are extremely common in elderly people. The detection of the so-called velcro crackle in lung sounds can effectively raise the suspicion of an interstitial disease and speed up diagnosis. However, this task largely relies on the experience of physicians and has not yet been standardized in clinical practice. The diagnosis of interstitial lung diseases based on thorax auscultation still represents an underexplored field in the study of rheumatoid arthritis. In this study, we investigate the problem of the automatic detection of velcro crackle in lung sounds. In practice, the patient is auscultated using a digital stethoscope and the lung sounds are saved to a file. The acquired digital data are then analysed using a suitably developed algorithm. In particular, the proposed solution relies on the empirical observation that the audio bandwidth associated with velcro crackle is larger than that associated with healthy breath sounds. Experimental results from a database of 70 patients affected by rheumatoid arthritis demonstrate that the developed tool can outperform specialized physicians in terms of diagnosing pulmonary disorders. The overall accuracy of the proposed solution is 90.0 %, with negative and positive predictive values of 95.0 % and 83.3 %, respectively, whereas the reliability of physician diagnosis is in the range of 60 − 70 % . The devised algorithm represents an enabling technology for a novel approach to the diagnosis of interstitial lung diseases in patients affected by rheumatoid arthritis. Highlights: The survival time of patients affected by rheumatoid arthritis with pulmonary implications is on the order of 3–8 years. The history and overall clinical condition of the patient remain the only indicators for considering further medical tests. The suspicion of pulmonary implications can be assessed through the algorithmic analysis of lung sounds. The developed tool can be exploited by rheumatologists to identify the patients with possible pulmonary disorders. The developed technology can turn the investigation of pulmonary disorders into aquantitative andobjective process.