Preoperative CT-based morphological heterogeneity for predicting survival in patients with colorectal cancer liver metastases after surgical resection: a retrospective study.

IF 2.9 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING BMC Medical Imaging Pub Date : 2024-12-18 DOI:10.1186/s12880-024-01524-w
Qian Xing, Yong Cui, Ming Liu, Xiao-Lei Gu, Xiao-Ting Li, Bao-Cai Xing, Ying-Shi Sun
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引用次数: 0

Abstract

Objective: To explore the value of preoperative CT-based morphological heterogeneity (MH) for predicting local tumor disease-free survival (LTDFS) and progression-free survival (PFS) in patients with colorectal cancer liver metastases (CRLM).

Methods: The latest CT data of 102 CRLM patients were retrospectively analyzed. The morphological score of each liver metastasis was obtained, and the morphological heterogeneity difference (MHD) was calculated. The receiver operating characteristic (ROC) curve was drawn, and the cutoff value was found. The Kaplan-Meier method was used to draw survival curves of patients with or without MH. The Cox regression analysis was used to build the model with MH and clinical characteristics for predicting PFS.

Results: In 78 patients without MH, median PFS was 9.0 months (95% CI:6.5-11.5), while in 24 patients with MH, median PFS was 6.0 months (95% CI:4.0-8.1), indicating that MH significantly affected PFS (p = 0.001). MH affected PFS in both the chemotherapy group and the chemotherapy combined with targeted therapy group (p = 0.005, p = 0.043). MH, preoperative carcinoembryonic antigen (CEA) and chemotherapy after surgery were independent predictors for postoperative PFS in patients with CRLM.

Conclusion: Preoperative CT-based MH had good efficacy for predicting LTDFS and PFS of CRLM patients after surgical resection, regardless of preoperative treatment. MH is one of the independent predictors of PFS.

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来源期刊
BMC Medical Imaging
BMC Medical Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
4.60
自引率
3.70%
发文量
198
审稿时长
27 weeks
期刊介绍: BMC Medical Imaging is an open access journal publishing original peer-reviewed research articles in the development, evaluation, and use of imaging techniques and image processing tools to diagnose and manage disease.
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