Features found on MRI may predict liver cancer recurrence after surgery

An algorithm based on MRI features could help clinicians predict liver cancer recurrence after patients have undergone liver resection, researchers have found. The findings could translate into better patient outcomes, wrote a team led by Hanyu Jiang, PhD, of West China Hospital, Sichuan University, in Chengdu, China. The study results were published November 7 in Radiology. "Identifying patients at high risk for advanced-stage hepatocellular carcinoma recurrence after liver resection may improve patient survival," the group noted. Liver resection is a common treatment for hepatocellular carcinoma, but its long-term effect can be limited by the frequent recurrence of the disease, according to the researchers. That's why patients at high risk for advanced-stage recurrence could "benefit from adjuvant therapies and a more intensive postsurgical surveillance strategy for extrahepatic metastases," they wrote.Preoperative axial extracellular contrast agent-enhanced (A-E) MRI and (F-H) follow-up CT images in a 71-year-old male patient with chronic hepatitis B and a serum neutrophil count of 4.2 × 109/L. A 5.6-cm mass with a 1.9-cm satellite nodule was detected in segments V and VIII. (A) The mass (asterisks, A-E) shows mild-to-moderate hyperintensity on T2-weighted images, (B) hypointensity on T1-weighted noncontrast-enhanced images, (C) less than 50% hyperenhancement on late arterial phase images, (D) nonperipheral washout and incomplete enhancing capsule on portal venous phas...
Source: AuntMinnie.com Headlines - Category: Radiology Authors: Tags: Clinical News Imaging Informatics MRI Artificial Intelligence Genitourinary Radiology Source Type: news