Machine learning-based radiomics analysis of PET imaging for early prediction of concurrent chemoradiotherapy response in stage II–III cervical squamous cell carcinoma

D Pang; Hong Yang; Shilai Zhang; Wenming Qiu; Weiwei Pu; Ziya Liu; Zhi Yang; Ning Li; Hai Liao; Guoyou Xiao

doi:10.1186/s12885-026-15882-x

April 9, 2026BMC CancerOpen Access

Machine learning-based radiomics analysis of PET imaging for early prediction of concurrent chemoradiotherapy response in stage II–III cervical squamous cell carcinoma

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Key Points

To evaluate the effectiveness of a pre-treatment radiomics model using machine learning for predicting treatment response in cervical cancer.
Single-center retrospective cohort study
Developed radiomics model based on pre-treatment PET imaging
Used random forest algorithm for analysis
Compared performance of five machine learning algorithms
The random forest model showed the highest performance for predicting early response (AUC = 0.783)
External validation is necessary before clinical use

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Implication

Retrospective cohort study demonstrates predictive modeling efficacy in cervical cancer, highlighting the potential for early treatment response assessment.

Abstract

In this single-center retrospective cohort study, a pre-treatment ¹⁸F-FDG PET radiomics model using random forest showed the best performance among the five evaluated ML algorithms for predicting early CCRT response (test-set AUC = 0.783). External validation is required before clinical implementation.

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Cite This Study

Pang et al. (2026) studied this question.

synapsesocial.com/papers/69d9e4d578050d08c1b7522a https://doi.org/10.1186/s12885-026-15882-x

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Machine learning-based radiomics analysis of PET imaging for early prediction of concurrent chemoradiotherapy response in stage II–III cervical squamous cell carcinoma

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

Machine learning-based radiomics analysis of PET imaging for early prediction of concurrent chemoradiotherapy response in stage II–III cervical squamous cell carcinoma

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

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