Feasibility and Preliminary Performance of an AI Prototype for Digital ROSE During EBUS-TBNA and Peripheral TBNA: a Prospective Pilot Study (AI-ROSE-FEAS)

AI (Artificial Intelligence), Bronchoscopy, EBUS Guided Transbronchial Needle Aspiration, Lung Cancer (Diagnosis), Lung Neoplasms, Mediastinal ( Chest) Masses, Mediastinal Lymphadenopathy

bronchoscopy, artificial intelligence

Rapid On-Site Evaluation (ROSE) of cytological slides obtained during EBUS-TBNA improves diagnostic yield by providing real-time adequacy assessment and preliminary diagnostic orientation after each needle pass. In centers without a dedicated cytopathologist, ROSE is performed by a second interventional pulmonologist acting as a dedicated ROSE operator (interventional pulmonologist-performed ROSE, IP-ROSE), a model associated with good but variable diagnostic performance compared to cytopathologist-performed ROSE. This study evaluates the feasibility and preliminary diagnostic performance of an investigational artificial intelligence prototype for digital ROSE. The prototype, developed in-house by the Principal Investigator, analyzes microscopic images of Diff-Quik stained cytological slides acquired through a dedicated digital microscope, together with basic clinical data, via API calls to a multimodal AI model. It produces two outputs: sample adequacy (appropriate/not appropriate) and malignancy suspicion (benign/malignant), each with a confidence score. The AI output is recorded in the study database for research purposes only and is not shown to the operator in real time; it does not influence clinical decisions during the procedure. The study is a prospective, monocentric, observational pilot study enrolling 65 adult patients undergoing EBUS-TBNA or peripheral TBNA with IP-ROSE at a single interventional pulmonology unit. The primary statistical unit is the individual ROSE slide, with an expected 130 to 160 evaluable slides. Co-primary endpoints are: (1) technical feasibility of the AI prototype, defined as the proportion of slides with valid AI output within 90 seconds; and (2) AI accuracy for sample adequacy assessment compared to the definitive cytopathological diagnosis, with an expected 95% confidence interval precision of ±5.5%. Secondary endpoints include AI accuracy for malignancy suspicion, agreement between the AI prototype and the IP-ROSE operator, and AI output latency. The AI prototype is not a commercially approved or CE-marked medical device. It was developed internally by the Principal Investigator for research purposes and is evaluated exclusively within this study. Data from this pilot study will inform the design of a subsequent confirmatory non-inferiority trial, which will be the subject of separate registration and ethical approval.

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