Intratumor and peritumor MRI radiomics features of rectal cancer can predict overall survival after neoadjuvant therapy

Motivation: Use MR radiomics features as a potential factor for predicting overall survival (OS) after neoadjuvant therap in rectal cancer. Goal(s): To explore the ability of the intratumoral and peritumoral radiomics features to predict the OS. Approach: A nomogram that combines clinical features, intratumor and peritumor radiomics features from T2WI using Machine Learning to predict OS was developed, validated using the Kaplan-Meier survival curve. Results: There was a significant statistical difference in the label scores between the high-risk and low-risk groups divided by median survival time as the cutoff value. The C-index of the training and test cohort was 0.798, 0.772 respectively. Impact: The radiomics model of peritumor radiomics features as the intratumor model can predict the OS in rectal cancer with neoadjuvant therapy. Combined with clinical features and the radiomics model of intratumor radiomics features, high accuracy can be obtained.

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
2024-11-26
DOI
https://doi.org/10.58530/2024/3095
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
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article

Intratumor and peritumor MRI radiomics features of rectal cancer can predict overall survival after neoadjuvant therapy

Haibo Xu, Yaoyao He, Zilong Yuan, Xiaofang Guo 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
Radiomics and Machine Learning in Medical Imaging
article

Intratumor and peritumor MRI radiomics features of rectal cancer can predict overall survival after neoadjuvant therapy

Haibo Xu, Yaoyao He, Zilong Yuan, Xiaofang Guo, Yulin Liu, Tingting Nie
article en

Abstract

Motivation: Use MR radiomics features as a potential factor for predicting overall survival (OS) after neoadjuvant therap in rectal cancer. Goal(s): To explore the ability of the intratumoral and peritumoral radiomics features to predict the OS. Approach: A nomogram that combines clinical features, intratumor and peritumor radiomics features from T2WI using Machine Learning to predict OS was developed, validated using the Kaplan-Meier survival curve. Results: There was a significant statistical difference in the label scores between the high-risk and low-risk groups divided by median survival time as the cutoff value. The C-index of the training and test cohort was 0.798, 0.772 respectively. Impact: The radiomics model of peritumor radiomics features as the intratumor model can predict the OS in rectal cancer with neoadjuvant therapy. Combined with clinical features and the radiomics model of intratumor radiomics features, high accuracy can be obtained.

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
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Openalex Percentile: Top 63%
Radiomics and Machine Learning in Medical Imaging
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Intratumor and peritumor MRI radiomics features of rectal cancer can predict overall survival after neoadjuvant therapy — Haibo Xu, Yaoyao He, 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 (2024) | TGRS Research Map | TGRS