Clinical Evaluation of the V5-LU01 AI Software in Thoracic CT for V5med Inc.

STUDY DESIGN: This is a two-arm retrospective, multi-reader, multi-case, (MRMC) randomized reader study. OBJECTIVE: Primary: The primary objective of this clinical study is to prove that radiologist's performance aided with V5med Lung AI is superior to the unaided for detecting qualified lung nodules. Secondary: The secondary objective of this clinical study is to prove that the radiologist's reading time is not significantly increased when aided with V5med Lung AI. Addition Objectives: To prove that the agreement (e.g., in kappa correlation coefficient) between experts and radiologist's Lung-RADS score aided with V5med Lung AI is superior to the unaided. NUMBER OF SUBJECTS: Retrospective CT studies from approximately 350 patients will be included in the study with approximately 170 true positive cases and 180 normal cases. PRIMARY ENDPOINTS: Scores given by the radiologists with and without V5med Lung AI will be recorded and compared to the true status of the study-cases. The frequency of the scores for each method (Aided, Unaided) will be tabulated and LROC curves constructed along with sensitivity, specificity, PPV, NPV and clinical actions. Additionally, machine nodule detection rate and false positives per patient on normal cases will be measured. PATIENT POPULATION: The study will target approximately two hundred (200) patients whose CT lung nodules were shown to be cancer and one hundred and eighty (150) patients who have no lung nodule greater than 4mm. The patient population will be consistent with the national lung cancer screening protocols.