Digital Lung Auscultation: Will Early Diagnosis of Fibrotic Interstitial Lung Disease Become a Reality?

Reliability of crackles in fibrotic interstitial lung disease: a prospective, longitudinal study

BACKGROUND

Although crackles on chest auscultation represent a fundamental component of the diagnostic suspect for fibrotic interstitial lung disease (ILD), their reliability has not been properly studied. We assessed the agreement among respiratory physicians on the presence and changes over time of audible crackles collected in a prospective longitudinal cohort of patients with fibrotic ILD.

METHODS

Lung sounds were digitally recorded at baseline and after 12 months at eight anatomical sites. Nine respiratory physicians blindly assessed randomized couples of recordings obtained from the same anatomical site at different timepoints. The physicians indicated the presence of crackles in individual recordings and which recording from each couple eventually had more intense crackles. Fleiss' kappa coefficient was used to measure inter- and intra-rater agreement.

RESULTS

Fifty-two patients, mostly with a diagnosis of IPF (n = 40, 76.9%) were prospectively enrolled between October 2019 and May 2021. The final acoustic dataset included 702 single recordings, corresponding to 351 couples of recordings from baseline and 12-months timepoints. Kappa coefficient was 0.57 (95% CI 0.55-0.58) for the presence of crackles and 0.42 (95% CI 0.41-0.43) for acoustic change. Intra-rater agreement, measured for three respiratory physicians on three repeated assessments, ranged from good to excellent for the presence of crackles (κ = 0.87, κ = 0.86, κ = 0.79), and from moderate to good for acoustic change (κ = 0.75, κ = 0.76, κ = 0.57).

CONCLUSIONS

Agreement between respiratory physicians for the presence of crackles and acoustic change was acceptable, suggesting that crackles represent a reliable acoustic finding in patients with fibrotic ILD. Their role as a lung-derived indicator of disease progression merits further studies.

AI co-pilot bronchoscope robot

The unequal distribution of medical resources and scarcity of experienced practitioners confine access to bronchoscopy primarily to well-equipped hospitals in developed regions, contributing to the unavailability of bronchoscopic services in underdeveloped areas. Here, we present an artificial intelligence (AI) co-pilot bronchoscope robot that empowers novice doctors to conduct lung examinations as safely and adeptly as experienced colleagues. The system features a user-friendly, plug-and-play catheter, devised for robot-assisted steering, facilitating access to bronchi beyond the fifth generation in average adult patients. Drawing upon historical bronchoscopic videos and expert imitation, our AI-human shared control algorithm enables novice doctors to achieve safe steering in the lung, mitigating misoperations. Both in vitro and in vivo results underscore that our system equips novice doctors with the skills to perform lung examinations as expertly as seasoned practitioners. This study offers innovative strategies to address the pressing issue of medical resource disparities through AI assistance.

Machine Learning for Automated Classification of Abnormal Lung Sounds Obtained from Public Databases: A Systematic Review

Pulmonary auscultation is essential for detecting abnormal lung sounds during physical assessments, but its reliability depends on the operator. Machine learning (ML) models offer an alternative by automatically classifying lung sounds. ML models require substantial data, and public databases aim to address this limitation. This systematic review compares characteristics, diagnostic accuracy, concerns, and data sources of existing models in the literature. Papers published from five major databases between 1990 and 2022 were assessed. Quality assessment was accomplished with a modified QUADAS-2 tool. The review encompassed 62 studies utilizing ML models and public-access databases for lung sound classification. Artificial neural networks (ANN) and support vector machines (SVM) were frequently employed in the ML classifiers. The accuracy ranged from 49.43% to 100% for discriminating abnormal sound types and 69.40% to 99.62% for disease class classification. Seventeen public databases were identified, with the ICBHI 2017 database being the most used (66%). The majority of studies exhibited a high risk of bias and concerns related to patient selection and reference standards. Summarizing, ML models can effectively classify abnormal lung sounds using publicly available data sources. Nevertheless, inconsistent reporting and methodologies pose limitations to advancing the field, and therefore, public databases should adhere to standardized recording and labeling procedures.

Early Detection and Staging of Lung Fibrosis Enabled by Collagen-Targeted MRI Protein Contrast Agent

Chronic lung diseases, such as idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD), are major leading causes of death worldwide and are generally associated with poor prognoses. The heterogeneous distribution of collagen, mainly type I collagen associated with excessive collagen deposition, plays a pivotal role in the progressive remodeling of the lung parenchyma to chronic exertional dyspnea for both IPF and COPD. To address the pressing need for noninvasive early diagnosis and drug treatment monitoring of pulmonary fibrosis, we report the development of human collagen-targeted protein MRI contrast agent (hProCA32.collagen) to specifically bind to collagen I overexpressed in multiple lung diseases. When compared to clinically approved Gd3+ contrast agents, hProCA32.collagen exhibits significantly better r1 and r2 relaxivity values, strong metal binding affinity and selectivity, and transmetalation resistance. Here, we report the robust detection of early and late-stage lung fibrosis with stage-dependent MRI signal-to-noise ratio (SNR) increase, with good sensitivity and specificity, using a progressive bleomycin-induced IPF mouse model. Spatial heterogeneous mapping of usual interstitial pneumonia (UIP) patterns with key features closely mimicking human IPF, including cystic clustering, honeycombing, and traction bronchiectasis, were noninvasively detected by multiple MR imaging techniques and verified by histological correlation. We further report the detection of fibrosis in the lung airway of an electronic cigarette-induced COPD mouse model, using hProCA32.collagen-enabled precision MRI (pMRI), and validated by histological analysis. The developed hProCA32.collagen is expected to have strong translational potential for the noninvasive detection and staging of lung diseases, and facilitating effective treatment to halt further chronic lung disease progression.

Diffuse lung involvement in rheumatoid arthritis: a respiratory physician's perspective

ABSTRACT

The lungs are one of the most common extra-articular organs involved in rheumatoid arthritis (RA), which is reported to occur in up to 60% to 80% of RA patients. Respiratory complications are the second leading cause of death due to RA. Although there is a wide spectrum of RA-associated respiratory diseases, interstitial lung disease is the most common manifestation and it impacts the prognosis of RA. There has been progress in understanding the management and progression of rheumatoid arthritis-associated interstitial lung disease (RA-ILD) and RA-associated respiratory diseases recently, for example, opportunistic pulmonary infectious diseases and toxicity from RA therapies. From a chest physicians' perspective, we will update the diagnosis and treatment of RA-associated ILD, methotrexate-associated lung disease, and the complication of Pneumocystis jiroveci pneumonia in RA in this review.

Novel diagnostic techniques in interstitial lung disease

Research into novel diagnostic techniques and targeted therapeutics in interstitial lung disease (ILD) is moving the field toward increased precision and improved patient outcomes. An array of molecular techniques, machine learning approaches and other innovative methods including electronic nose technology and endobronchial optical coherence tomography are promising tools with potential to increase diagnostic accuracy. This review provides a comprehensive overview of the current evidence regarding evolving diagnostic methods in ILD and to consider their future role in routine clinical care.

The Current and Future Role of Technology in Respiratory Care

Over the past few decades, technology and improvements in artificial intelligence have dramatically changed major sectors of our day-to-day lives, including the field of healthcare. E-health includes a wide range of subdomains, such as wearables, smart-inhalers, portable electronic spirometers, digital stethoscopes, and clinical decision support systems. E-health has been consistently shown to enhance the quality of care, improve adherence to therapy, and allow early detection of worsening in chronic pulmonary diseases. The present review addresses the current and potential future role of major e-health tools and approaches in respiratory medicine, with the aim of providing readers with trustful and updated evidence to increase their awareness of the topic, and to allow them to optimally benefit from the latest innovation technology. Collected literature evidence shows that the potential of technology tools in respiratory medicine mainly relies on three fundamental interactions: between clinicians, between clinician and patient, and between patient and health technology. However, it would be desirable to establish widely agreed and adopted standards for conducting trials and reporting results in this area, as well as to take into proper consideration potentially relevant pitfalls related to privacy protection and compliance with regulatory procedures.

Structure dependence and species sensitivity of in vivo hepatobiliary toxicity with lysophosphatidic acid receptor 1 (LPA1) antagonists

BMS-986020, BMS-986234 and BMS-986278, are three lysophosphatidic acid receptor 1 (LPA₁) antagonists that were or are being investigated for treatment of idiopathic pulmonary fibrosis (IPF). Hepatobiliary toxicity (elevated serum AST, ALT, and ALP, plasma bile acids [BAs], and cholecystitis) was observed in a Phase 2 clinical trial with BMS-986020, and development was discontinued. In dogs and rats, the species used for the pivotal toxicology studies, there was no evidence of hepatobiliary toxicity in the dog while findings in the rat were limited to increased plasma BAs levels (6.1× control), ALT (2.9×) and bilirubin (3.4×) with no histopathologic correlates. Since neither rats nor dogs predicted clinical toxicity, follow-up studies in cynomolgus monkeys revealed hepatobiliary toxicity that included increased ALT (2.0× control) and GLDH (4.9×), bile duct hyperplasia, cholangitis, cholestasis, and cholecystitis at clinically relevant BMS-986020 exposures with no changes in plasma or liver BAs. This confirmed monkey as a relevant species for identifying hepatobiliary toxicity with BMS-986020. In order to assess whether the toxicity was compound-specific or related to LPA₁ antagonism, two structurally distinct LPA₁ antagonists (BMS-986234 and BMS-986278), were evaluated in rat and monkey. There were no clinical or anatomic pathology changes indicative of hepatobiliary toxicity. Mixed effects on plasma bile acids in both rat and monkey has made this biomarker not a useful predictor of the hepatobiliary toxicity. In conclusion, the nonclinical data indicate the hepatobiliary toxicity observed clinically and in monkeys administered BMS-986020 is compound specific and not mediated via antagonism of LPA₁.

Possible Role of Chest Ultrasonography for the Evaluation of Peripheral Fibrotic Pulmonary Changes in Patients Affected by Idiopathic Pulmonary Fibrosis—Pilot Case Series

Lung ultrasonography (LUS) provides an estimation of peripheral airspace (PAS) geometry of the lung. Altered PAS produces sonographic interstitial syndrome (SIS). Idiopathic pulmonary fibrosis (IPF) involves peripheral lung with altered PAS. The aim of the study is to correlate echographic patterns with peripheral fibrotic changes on high-resolution Chest CT scan (HRCT). Patients underwent LUS and HRCT on the same date. Four LUS patterns were described: (1) near normal; (2) SIS with predominance of reverberant artifacts; (3) SIS with vertical predominance; (4) white lung. Four HRCT grades of peripheral fibrotic infiltrates were reported: grade 1 mild; grade 2 moderate; grade 3 severe; grade 4 massive or honeycomb. LUS pattern 1 was indicative of mild to moderate fibrotic alterations in 100% of cases. LUS pattern 2 matched with HRCT grade 2 in 24 out of 30 cases (77%). Huge discordance in four cases because of large honeycomb cysts. LUS pattern 3 was indicative of severe to massive alterations in 100% of cases. LUS pattern 4 showed a heterogeneous distribution of HRCT grades, severe changes, and ground glass opacities (GGO). This preliminary work demonstrates some level of agreement between LUS patterns and HRCT grades. Limitations and methodological issues have been shown to support subsequent studies of agreement.