Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
364-05-011 ISMRM Abstract

Time-Dependent Diffusion MRI-based Quantitative Multiparameters for Assessment of TP53 mutation status in Rectal Cancer

Accepted
Xiaohuan Mei 1, Yijing Luo1, Lan Zhou1, Aerzuguli Abudulimu1, 会婷 张2, Long Qian3, Thorsten Feiweier4, mengsi li1, wenzheng li1
1Xiangya Hospital of Central South University, Changsha, China
2MR Research Collaboration, Siemens Healthineers Ltd., Wuhan, China
3MR Research Collaboration Team, Siemens Healthineers Ltd., Guangzhou, Guang Zhou, China
4Research & Clinical Translation, Magnetic Resonance, Siemens Healthineers AG, Erlangen, Germany
Presenting Author: Xiaohuan Mei

Synopsis

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References

1. Dekker E, Tanis PJ, Vleugels JLA, Kasi PM, Wallace MB. Colorectal cancer. Lancet 2019; 394:1467-1480.
2. Hassin O, Nataraj NB, Shreberk-Shaked M, et al. Different hotspot p53 mutants exert distinct phenotypes and predict outcome of colorectal cancer patients. Nat Commun 2022; 13:2800.
3. Wang X, Ba R, Huang Y, et al. Time-Dependent Diffusion MRI Helps Predict Molecular Subtypes and Treatment Response to Neoadjuvant Chemotherapy in Breast Cancer. Radiology 2024; 313:e240288.
4. Wu D, Jiang K, Li H, et al. Time-Dependent Diffusion MRI for Quantitative Microstructural Mapping of Prostate Cancer. Radiology 2022; 303:578-587.
5. Zhang H, Liu K, Ba R, et al. Histological and molecular classifications of pediatric glioma with time-dependent diffusion MRI-based microstructural mapping. Neuro Oncol 2023; 25:1146-1156.
6. Zhong X, Peng J, Shu Z, Song Q, Li D. Prediction of p53 mutation status in rectal cancer patients based on magnetic resonance imaging-based nomogram: a study of machine learning. Cancer Imaging 2023; 23:88.

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