Development of a Model including MRI Features for Predicting Advanced-stage Recurrence of Hepatocellular Carcinoma
Hanyu Jiang1, Chongtu Yang1, Yidi Chen1
1From the Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China (H.J., C.Y., Y.C., Y. Wang, W.C., B.S.); JD.com, Beijing, China (Y. Wu); Université Paris Cité, UMR 1149, CRI, Paris, France (M.R.); Department of Radiology, Hôpital Beaujon, APHP.Nord, Clichy, France (M.R.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, University of California San Diego, San Diego, Calif (K.J.F.); Department of Radiology, Center for Advanced Magnetic Resonance in Medicine, and Division of Gastroenterology, Department of Medicine, Duke University Medical Center, Durham, NC (M.R.B.); and Department of Radiology, Sanya People's Hospital, Sanya, China (B.S.).
Abstract:
Background Identifying patients at high risk for advanced-stage hepatocellular carcinoma (HCC) recurrence after liver resection may improve patient survival. Purpose To develop a model including MRI features for predicting postoperative advanced-stage HCC recurrence. Materials and Methods This single-center, retrospective study includes consecutive adult patients who underwent preoperative contrast-enhanced MRI and curative-intent resection for early- to intermediate-stage HCC (from December 2011 to April 2021). Three radiologists evaluated 52 qualitative features on MRI scans. In the training set, Fine-Gray proportional subdistribution hazard analysis was performed to identify clinical, laboratory, imaging, pathologic, and surgical variables to include in the predictive model. In the test set, the concordance index (C-index) was computed to compare the developed model with current staging systems. The Kaplan-Meier survival curves were compared using the log-rank test. Results The study included 532 patients (median age, 54 years; IQR, 46-62 years; 465 male patients), 302 patients from the training set (median age, 54 years; IQR, 46-63 years; 265 male patients), and 128 patients from the test set (median age, 53 years; IQR, 46-63 years; 108 male patients). Advanced-stage recurrence was observed in 38 of 302 (12.6%) and 15 of 128 (11.7%) of patients from the training and test sets, respectively. Serum neutrophil count (109/L), tumor size (in centimeters), and arterial phase hyperenhancement proportion on MRI scans were associated with advanced-stage recurrence (subdistribution hazard ratio range, 1.16-3.83; 95% CI: 1.02, 7.52; P value range, <.001 to .02) and included in the predictive model. The model showed better test set prediction for advanced-stage recurrence than four staging systems (2-year C-indexes, 0.82 [95% CI: 0.74, 0.91] vs 0.63-0.68 [95% CI: 0.52, 0.82]; P value range, .001-.03). Patients at high risk for HCC recurrence (model score, ≥15 points) showed increased advanced-stage recurrence and worse all-stage recurrence-free survival (RFS), advanced-stage RFS, and overall survival than patients at low risk for HCC recurrence (P value range, <.001 to .02). Conclusion A model combining serum neutrophil count, tumor size, and arterial phase hyperenhancement proportion predicted advanced-stage HCC recurrence better than current staging systems and may identify patients at high risk. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Tsai and Mellnick in this issue.
