Multiphase CT with Deep Learning Accurately Differentiates Small Renal Masses

Small solid kidney masses can be adequately differentiated for diagnosis on dynamic CT images by using a deep learning method with a convolutional neural network (CNN), according to new research. Currently, diagnosis with dynamic CT has depended largely on radiologist experience. This study shows automated image analysis of these masses with deep learning can discern between benign and malignant tumors without requiring a radiologist to have significant experience. The findings were published in an ahead-of-print issue of American Journal of Roentgenology. Researchers from Okayama University in Japan studied 168 pathologically diagnosed small solid masses (less than 4cm) from 159 patients between 2012 and 2016.