Paper 13293-13
Paper 13293-13
Artificial intelligence in urology: combining imaging and clinical data for improved prostate diagnostics
25 January 2025 • 2:50 PM - 3:10 PM PST | Moscone Center, Room 301 (Level 3 South)
Abstract
This study investigates the integration of 3D MRI and clinical data to enhance prostate disease diagnosis. By combining biparametric MR studies with patient demographics and clinical findings, including longitudinal PSA levels, we developed fusion models that significantly improve diagnostic accuracy. Our best-performing model achieved higher ROC-AUC and quadratic weighted Kappa scores compared to image-only or tabular data-only approaches. These results highlight the potential of comprehensive data fusion in computer-aided diagnosis systems for urological applications, offering more precise and personalized diagnostic processes.
Presenter
Lucas Engelage
Laser-Forschungslabor, Klinikum der Univ. München, Ludwig-Maximilians-Univ. München (Germany), ALTA Klinik GmbH (Germany)
Lucas Engelage is a dedicated researcher with 4 years of experience in the field of urological diagnostics and treatment. His work focuses on advancing prostate cancer detection and management through innovative technologies. Engelage has been at the forefront of developing an artificial intelligence system capable of detecting prostate cancer in MRI images, significantly improving diagnostic accuracy and efficiency. In parallel, he has been instrumental in the development of a novel PSA test that utilizes dry capillary blood, potentially revolutionizing the ease and accessibility of prostate cancer screening. His research also extends to therapeutic innovations, including work on the TULSA PRO therapy, a minimally invasive treatment for prostate cancer. Engelage's multifaceted approach to urological research demonstrates his commitment to improving patient outcomes through the integration of cutting-edge technologies in diagnostics and treatment.