Advancing Lung Cancer Diagnosis with eyonis® LCS

摘要

The integration of AI/ML technologies into medical imaging is revolutionizing radiology, offering transformative benefits in clinical workflows. AI-powered Software as a Medical Device (SaMD) solutions not only reduce workload and optimize image interpretation but also unlock critical insights previously undetectable by human eyes-catching the unseen and enabling earlier, more accurate diagnoses. Lung cancer, the leading cause of cancer-related mortality worldwide, is often diagnosed at a late stage, when curative treatment is no longer viable. Early detection is paramount. Traditional screening methods rely heavily on nodule size and growth as indicators of malignancy. However, these criteria alone are insufficient for identifying cancer at its earliest, most treatable stage. eyonis® LCS, the flagship clinical development program of Median Technologies, represents a next-generation AI/ML-based SaMD designed specifically for lung cancer screening [1][2]. It combines Computer-Aided Detection (CADe) and Computer-Aided Diagnosis (CADx) [3][4] capabilities to support clinicians in identifying malignant nodules with greater precision. By leveraging specific architectural choices and deep learning models, eyonis® LCS enhances diagnostic accuracy beyond the current standard of care [5], offering a paradigm shift in early lung cancer detection [6]. This presentation will delve into some of the architectural foundations of eyonis® LCS, highlight its clinical impact, and demonstrate how it empowers radiologists to diagnose lung cancer when patients can still be cured. Through this pioneering technology, Median Technologies is redefining the future of cancer screening and patient outcomes.