Ibrahim, Mohamed I.

Abstract Interstitial lung disease (ILD) is a chronic, irreversible condition that is challenging to diagnose due to subtle symptoms and limitations of conventional tools. Noninvasive lung sound analysis using phonopulmography offers a promising alternative. This study evaluated the feasibility of a deep learning model for distinguishing normal and pathological lung sounds in ILD. Lung sound recordings were collected from 12 subjects (6 healthy, 6 ILD) and segmented beat-to-beat using simultaneously acquired ECG and phonopulmography, yielding 2,280 segments. Mel-frequency cepstral coefficients (MFCCs; 13 per segment) were extracted, and a one-dimensional CNN-based You Only Listen Once (YOLO) model was trained for segment classification. Evaluation used Leave-One-Out Cross-Validation, with patient-level classification by aggregating segment predictions via majority vote. On the test set (190 segments per class), the model achieved an average segment-level accuracy of 0.738 ± 0.087 and mean AUC of 0.850 ± 0.062. Precision, recall, and F1-score were 0.775 ± 0.148, 0.755 ± 0.183, and 0.738 ± 0.089, respectively. These preliminary results suggest that beat-level MFCCs with a 1D CNN-based YOLO model enable accurate segment- and patient-level classification. This feasibility study highlights the potential of AI-assisted auscultation for noninvasive monitoring and clinical decision support in ILD management, pending further validation in larger cohorts.

Microplastics may pose health risks, particularly for chronic lung diseases. Clarifying the link between circulating microplastics and pulmonary disease is vital for shaping research and interventions. The objective of this study was to evaluate whether microplastics in peripheral blood are associated with COPD or IPF vs. no lung disease. In this pilot prospective case-control study, participants were grouped as control (n = 10), COPD (n = 9), or IPF (n = 10). Relevant comorbidities and exposures were obtained from records and questionnaires. All underwent standardized blood collection (PlasticTox©). Samples were analyzed for total microplastic concentration, stratified by size (<10 µm, 10–30 µm, 30–70 µm). The primary outcome was to show a difference in total microplastic burden between lung disease and controls. Secondary measures were to determine size-specific concentrations and associations with demographic variables and smoking history. Among 29 participants (median age 70 (IQR 64–80); 14 women (48.3%)), COPD/IPF groups had significantly higher total microplastic concentrations vs. controls (median 26.0 vs. 3.5 particles/100 µL; p < 0.01). Particle burdens <10 µm and 10–30 µm were particularly elevated (both p < 0.01). After adjusting for smoking, only the <10 µm fraction remained independently associated with lung disease (adjusted odds ratio 1.94 (95% CI, 1.23–7.04)). In this pilot exploratory study, individuals with COPD or IPF showed greater circulating microplastic levels than controls. These findings should be interpreted as hypothesis-generating, and larger analytically validated studies are needed to clarify directionality, causal mechanisms, contamination control, and the clinical relevance of circulating microplastic burden.

ABSTRACTRobotic‐assisted bronchoscopy (RAB) has improved lung nodule evaluation, but its feasibility to biopsy aortopulmonary lymph nodes remains underexplored. This study explored the safety and effectiveness of RAB for sampling aortopulmonary lymph nodes suspected of malignancy. We conducted a literature review on RAB for aortopulmonary lymph node biopsy and present a case of a patient with a history of malignancy. Using the Ion Endoluminal System, we navigated to the anterior segment of the left upper lobe to access a subaortic lymph node in a patient with a history of mantle cell lymphoma. Biopsy confirmed disease recurrence. Our literature review identified seven patients who underwent RAB to assess aortopulmonary lymph nodes, with most findings showing small‐cell lung cancer. Our study reports an 88% diagnostic yield, and no complications associated with the procedure. RAB is a safe and effective approach for biopsying aortopulmonary lymph nodes.