A PET-CT radiomics model for immunotherapy response and prognosis prediction in patients with metastatic colorectal cancer

In this study, a radiomic model based on PET/CT images was successfully constructed, which can effectively predict immunotherapy response and prognosis of mCRC patients. The model combines radiomic features, immune scores and clinical features, showing high prediction accuracy and clinical application value. In the future, the reliability and generalization ability of this model need to be further verified in larger prospective studies to promote its application in clinical practice.

Authors

Institutions

Publication Details

Journal
Frontiers in Oncology
Published
2025-05-23
DOI
https://doi.org/10.3389/fonc.2025.1568755
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A PET-CT radiomics model for immunotherapy response and prognosis prediction in patients with metastatic colorectal cancer

Yeda Chen, Wenbiao Chen, Peng Zhu, Guoping Sun
Frontiers in Oncology
Radiomics and Machine Learning in Medical Imaging
article

A PET-CT radiomics model for immunotherapy response and prognosis prediction in patients with metastatic colorectal cancer

Yeda Chen, Wenbiao Chen, Peng Zhu, Guoping Sun
article en

Abstract

In this study, a radiomic model based on PET/CT images was successfully constructed, which can effectively predict immunotherapy response and prognosis of mCRC patients. The model combines radiomic features, immune scores and clinical features, showing high prediction accuracy and clinical application value. In the future, the reliability and generalization ability of this model need to be further verified in larger prospective studies to promote its application in clinical practice.

Frontiers in OncologyVol. 15
Jinan University (CN), Southern University of Science and Technology (CN), Dongguan People’s Hospital (CN), Southern Medical University Shenzhen Hospital (CN)
National Natural Science Foundation of China
Good health and well-being
Openalex Percentile: Top 82%
Radiomics and Machine Learning in Medical Imaging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.