Radiation hematologic toxicity prediction in rectal cancer: a comparative radiomics-based study on CT image and dose map

Our study can confirm that the HT occurrence in locally advanced rectal cancer (LARC) patients was multifactorial, and combining effective features together can classify the high-risk patients with HT, thus timely preventing or detecting HT to improve the subsequent outcome.

Authors

Yingpeng Liu
Qingtao Xu
Yi Wang (ORCID: https://orcid.org/0009-0008-0443-2480)
Xianyun Meng
Jingfeng Zhang (ORCID: https://orcid.org/0009-0009-5817-8067)
Liping Guo

Institutions

Ningbo University (CN)
Ningbo No. 2 Hospital (CN)

Publication Details

Journal: Frontiers in Oncology
Published: 2025-03-04
DOI: https://doi.org/10.3389/fonc.2025.1516855
Primary Topic: Radiomics and Machine Learning in Medical Imaging
Type: article
Field-Weighted Citation Impact: 0.00

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article

Radiation hematologic toxicity prediction in rectal cancer: a comparative radiomics-based study on CT image and dose map

Yingpeng Liu, Qingtao Xu, Yi Wang, Xianyun Meng et al.

Mar 4, 2025

Frontiers in Oncology

Radiomics and Machine Learning in Medical Imaging

article

Radiation hematologic toxicity prediction in rectal cancer: a comparative radiomics-based study on CT image and dose map

Yingpeng Liu, Qingtao Xu, Yi Wang, Xianyun Meng, Jingfeng Zhang, Liping Guo

March 4, 2025article en

Abstract

Our study can confirm that the HT occurrence in locally advanced rectal cancer (LARC) patients was multifactorial, and combining effective features together can classify the high-risk patients with HT, thus timely preventing or detecting HT to improve the subsequent outcome.

Frontiers in OncologyVol. 15

Ningbo University (CN), Ningbo No. 2 Hospital (CN)

Good health and well-being

Openalex Percentile: Top 94%

Radiomics and Machine Learning in Medical Imaging

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