September 4, 2015 -- Tracking liver metastases on follow-up CT scans is a critical task for clinicians, but the process is time-consuming and often inefficient. A new automated method for detecting and segmenting liver metastases may help, according to an article published online in the Journal of Medical Imaging.
Designed to operate as a radiologist would, the algorithm identifies, tracks, and segments lesions to assess changes between baseline CT exams and follow-up studies. In testing, the technique yielded high sensitivity for detecting metastatic liver lesions, in addition to a 90% accuracy rate for tracking tumors on a set of follow-up cases, according to biomedical engineering doctoral student Avi Ben-Cohen and colleagues from Tel Aviv University and Sheba Medical Center in Israel.
"The initial results presented here look promising," they wrote. "We achieved high sensitivity and high Dice segmentation results as well as a high matching rate. ... Using the [Response Evaluation Criteria in Solid Tumors (RECIST)] diagnosis criteria, we obtained a success rate of 88%. Additionally, expert ratings of the automated system segmentation results were in strong agreement."