Integrated approach to bronchoalveolar lavage cytology to distinguish interstitial lung diseases

Background: Broncho-alveolar lavage (BAL) is a safe diagnostic procedure, useful for differentiating fibrotic lung disorders and for excluding malignancy and infection. A recent multicenter study demonstrated a new, relatively sensitive, and specific index called Bronchoalveolar Cytology Threshold (BCT), useful for distinguishing healthy individuals from patients with lung diseases. Objectives: In our study, BCT was applied for the first time to the analysis of interstitial lung diseases (ILDs), investigating its potential for differential diagnosis. Combinations of BAL cells that improve diagnostic accuracy for ILDs were studied and are proposed. Methods: A retrospective analysis of BAL samples was performed. We considered more than 1000 BAL samples from patients investigated for ILD, performed at Siena University Hospital. The samples enrolled for the study included 468 patients: 413 with and 55 without ILD. BAL was performed for diagnostic purposes in line with international guidelines. BCT were calculated according to available literature. Results: Among ILDs, patients with fibrotic hypersensitivity pneumonitis, idiopathic pulmonary fibrosis (IPF) and sarcoidosis showed significantly lower BCTs than unclassified ILD. Asbestosis patients showed significantly lower BCTs than nonspecific interstitial pneumonia (NSIP), cryptogenic organizing pneumonia (COP), connective tissue disease related ILD (CTD-ILD), sarcoidosis and unclassified ILD patients. COP patients showed significantly higher BCT than IPF, f-HP and sarcoidosis. Moreover, COP patients were best distinguished by BCT. Conclusion: The analysis of BAL features is currently included in the diagnostic algorithm of ILDs. BAL cell patterns and BCT index can provide useful information for distinguishing ILDs, reducing the need for invasive procedures. Integrated approaches to BAL analysis can improve the interpretation of results without further cost or loss of time.