Non-invasive prediction of KRAS mutation in rectal cancer using hybrid intravoxel incoherent motion and diffusion kurtosis model

Motivation: KRAS mutation detection in rectal cancer is crucial but currently requires invasive biopsies. Non-invasive imaging biomarkers are needed. Goal(s): Evaluate the efficacy of a hybrid IVIM-DKI model in predicting KRAS mutation status in rectal cancer patients. Approach: 73 patients underwent IVIM-DKI MRI before surgery. IVIM-DKI parameters were compared between KRAS mutant and wild-type groups. Results: Significant differences in ADC, D, and K values between groups. K value showed highest diagnostic accuracy (AUC 0.779) for predicting KRAS mutation status. Impact: The hybrid IVIM-DKI model, especially the K value, demonstrates potential as a non-invasive imaging biomarker for KRAS mutation status in rectal cancer. This approach could guide treatment decisions and evaluate prognosis without invasive biopsies, potentially improving patient care and outcomes in rectal cancer management.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/2823
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Non-invasive prediction of KRAS mutation in rectal cancer using hybrid intravoxel incoherent motion and diffusion kurtosis model

Wenli Tan, Jie Yuan, Mengxiao Liu
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Radiomics and Machine Learning in Medical Imaging
article

Non-invasive prediction of KRAS mutation in rectal cancer using hybrid intravoxel incoherent motion and diffusion kurtosis model

Wenli Tan, Jie Yuan, Mengxiao Liu
article en

Abstract

Motivation: KRAS mutation detection in rectal cancer is crucial but currently requires invasive biopsies. Non-invasive imaging biomarkers are needed. Goal(s): Evaluate the efficacy of a hybrid IVIM-DKI model in predicting KRAS mutation status in rectal cancer patients. Approach: 73 patients underwent IVIM-DKI MRI before surgery. IVIM-DKI parameters were compared between KRAS mutant and wild-type groups. Results: Significant differences in ADC, D, and K values between groups. K value showed highest diagnostic accuracy (AUC 0.779) for predicting KRAS mutation status. Impact: The hybrid IVIM-DKI model, especially the K value, demonstrates potential as a non-invasive imaging biomarker for KRAS mutation status in rectal cancer. This approach could guide treatment decisions and evaluate prognosis without invasive biopsies, potentially improving patient care and outcomes in rectal cancer management.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 63%
Radiomics and Machine Learning in Medical Imaging
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Non-invasive prediction of KRAS mutation in rectal cancer using hybrid intravoxel incoherent motion and diffusion kurtosis model — Wenli Tan, Jie Yuan, et al. · Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition (2025) | TGRS Research Map | TGRS