Predicting the recurrence risk of liver metastasis from colorectal cancer: a study based on preoperative CT intratumoral and peritumoral radiomics features.

Dongying Zhang, Peiheng Li, Yong Wei, Mingmei Xue, Fangfang Guo, Chenguang Li

Abstract read

In one paragraph

Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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5 · Who and what money

Authors and funding

6 authors.

Dongying ZhangDepartment of Radiology, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China.

Peiheng LiDepartment of Radiology, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China.

Yong WeiDepartment of Radiology, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China.

Mingmei XueDepartment of Radiology, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China.

Fangfang GuoDepartment of Radiology, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China.

Chenguang LiDepartment of Radiology, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to explore the value of predicting the recurrence risk of colorectal cancer liver metastasis (CRLM) based on preoperative CT intratumoral and peritumoral radiomics features. Methods: This study utilized retrospectively collected preoperative CT data of 201 CRLM patients, comprising 145 cases from the hospital one and 56 cases from an external hospital two. Liver metastases were precisely segmented via manual annotation. Subsequently, the intratumoral region of interest (ROI Results: Compared with SVM and RF, MLP demonstrated superior predictive performance for estimating the recurrence risk of CRLM patients. The best radiomics signatures for predicting the recurrence risk of CRLM were ROI Conclusion: Preoperative CT-based radiomics features extracted from intra-tumoral (ROI

Indexed as

colorectal neoplasmscomputed tomographyliverneoplasm metastasisradiomics

Identifiers

PMID41064090

DOI10.3389/fonc.2025.1662354

PMCPMC12500699

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.