Fei Xiang1, Xiaoyuan Liang1, Lili Yang2, Xingyu Liu1, Sheng Yan3. 1. Department of Hepatobiliary Pancreatic Surgery, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China. 2. Department of Radiology, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China. 3. Department of Hepatobiliary Pancreatic Surgery, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China. shengyan@zju.edu.cn.
Abstract
OBJECTIVES: Gallbladder carcinoma (GBC) is the most common and aggressive biliary tract malignancy with high postoperative recurrence rates. This single-center study aimed to develop and validate a radiomics signature to estimate GBC recurrence-free survival (RFS). METHODS: This study retrospectively included 204 consecutive patients with pathologically diagnosed GBC and were randomly divided into development (n = 142) and validation (n = 62) cohorts (7:3). The radiomics features of tumor were extracted from preoperative contrast-enhanced CT imaging for each patient. In the development cohort, the least absolute shrinkage and selection operator (LASSO) Cox regression was employed to develop a radiomics signature for RFS prediction. The patients were stratified into high-score or low-score groups according to their median value of radiomics score. A nomogram was established using multivariable Cox regression by incorporating significant pathological predictors and radiomics signatures. RESULTS: The radiomics signature based on 12 features could discriminate high-risk patients with poor RFS. Multivariate Cox analysis revealed that pT3/4 stage (hazard ratio, [HR] = 2.691), pN2 stage (HR = 3.60), poor differentiation grade (HR = 2.651), and high radiomics score (HR = 1.482) were independent risk variables associated with worse RFS and were incorporated to construct a nomogram. The nomogram displayed good prediction performance in estimating RFS with AUC values of 0.895, 0.935, and 0.907 at 1, 3, and 5 years, respectively. CONCLUSIONS: The radiomics signature and combined nomogram may assist in predicting RFS in GBC patients. KEY POINTS: • A radiomics signature extracted from preoperative contrast-enhanced CT can be a useful tool to preoperatively predict RFS of GBC. • T3/T4 stage, N2, poor tumor differentiation, and high radiomics score were positively associated with postoperative recurrence.
OBJECTIVES: Gallbladder carcinoma (GBC) is the most common and aggressive biliary tract malignancy with high postoperative recurrence rates. This single-center study aimed to develop and validate a radiomics signature to estimate GBC recurrence-free survival (RFS). METHODS: This study retrospectively included 204 consecutive patients with pathologically diagnosed GBC and were randomly divided into development (n = 142) and validation (n = 62) cohorts (7:3). The radiomics features of tumor were extracted from preoperative contrast-enhanced CT imaging for each patient. In the development cohort, the least absolute shrinkage and selection operator (LASSO) Cox regression was employed to develop a radiomics signature for RFS prediction. The patients were stratified into high-score or low-score groups according to their median value of radiomics score. A nomogram was established using multivariable Cox regression by incorporating significant pathological predictors and radiomics signatures. RESULTS: The radiomics signature based on 12 features could discriminate high-risk patients with poor RFS. Multivariate Cox analysis revealed that pT3/4 stage (hazard ratio, [HR] = 2.691), pN2 stage (HR = 3.60), poor differentiation grade (HR = 2.651), and high radiomics score (HR = 1.482) were independent risk variables associated with worse RFS and were incorporated to construct a nomogram. The nomogram displayed good prediction performance in estimating RFS with AUC values of 0.895, 0.935, and 0.907 at 1, 3, and 5 years, respectively. CONCLUSIONS: The radiomics signature and combined nomogram may assist in predicting RFS in GBC patients. KEY POINTS: • A radiomics signature extracted from preoperative contrast-enhanced CT can be a useful tool to preoperatively predict RFS of GBC. • T3/T4 stage, N2, poor tumor differentiation, and high radiomics score were positively associated with postoperative recurrence.
Authors: Jennifer Xiao; Habib Rahbar; Daniel S Hippe; Mara H Rendi; Elizabeth U Parker; Neal Shekar; Michael Hirano; Kevin J Cheung; Savannah C Partridge Journal: NPJ Breast Cancer Date: 2021-04-16
Authors: Patrick Grossmann; Olya Stringfield; Nehme El-Hachem; Marilyn M Bui; Emmanuel Rios Velazquez; Chintan Parmar; Ralph Th Leijenaar; Benjamin Haibe-Kains; Philippe Lambin; Robert J Gillies; Hugo Jwl Aerts Journal: Elife Date: 2017-07-21 Impact factor: 8.140