Melissa B Pergakis, Afrah A Ali, WanTsu Wendy Chang, Benjamin Neustein, Casey Albin, Aimee Aysenne, Samuel A Tisherman, Nicholas A Morris
Smartphone Use in the Management of Neurological Emergencies: A Simulation-Based Study
Neurocritical care
background accurate characterization suspicious small renal masses crucial optimized management deep learning dl algorithms may assist effort purpose develop validate dl algorithm identifying benign small renal masses contrastenhanced multiphase ct materials methods surgically resected renal masses measuring 3 cm less diameter contrastenhanced ct included dl algorithm developed using retrospective data one hospital 2009 2021 patients randomly allocated training internal test set ratio 82 2013 2021 external testing performed data five independent hospitals prospective test set obtained 2021 2022 one hospital algorithm performance evaluated using area receiver operating characteristic curve auc compared results seven clinicians using delong test results total 1703 patients mean age 56 years 12 sd 619 female single renal mass per patient evaluated retrospective data set included 1063 lesions 874 training set 189 internal test set multicenter external test set included 537 lesions 123 66 benign 89 subcentimeter 1 cm lesions 166 prospective test set included 103 lesions 136 14 benign 20 194 subcentimeter lesions dl algorithm performance comparable urological radiologists external test set auc 080 95 ci 075 085 versus 084 95 ci 078 088 p 61 prospective test set auc 087 95 ci 079 093 versus 092 95 ci 086 096 p 70 subcentimeter lesions external test set algorithm urological radiologists similar auc 074 95 ci 063 083 081 95 ci 068 092 p 78 respectively conclusion multiphase ctbased dl algorithm showed comparable performance radiologists identifying benign small renal masses including lesions 1 cm less published cc 40 license supplemental material available article