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Abstract #2167

Differentiating Histological grade in breast cancer by time-dependent diffusion MRI: A Preliminary Study

Shunan Che1, Kun Ma1, Yueluan Jiang2, Feiweier Thorsten3, Jing Li1, Xinming Zhao1, and Chunwu Zhou1
1Diagnostic Radiology, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China, 2Diagnostic Radiology, MR Research Collaboration, Siemens Healthineers, Beijing, China, 3MR Research Collaboration, Siemens Healthineers, Erlangen, Germany

Synopsis

Keywords: Diffusion Modeling, Diffusion Modeling

Motivation: Accurate histological grading is crucial for assessing tumor behavior and prognosis in invasive breast carcinoma. Traditional grading is susceptible to sample variability.

Goal(s): This study aims to evaluate the diagnostic value of td-dMRI parameters for pathological grading of breast cancer.

Approach: 55 breast cancer patients underwent td-dMRI, and data were analyzed using an IMPULSED scheme to derive microstructural parameters. Statistical tests and ROC curves were used to evaluate microstructural parameters for diagnostic accuracy.

Results: Dex demonstrated the best predictive efficacy (AUC 0.774), improving to 0.812 when combined with other parameters, highlighting td-dMRI technique’s potential for non-invasive tumor grading.

Impact: This study highlights time-dependent diffusion MRI's potential for accurate, non-invasive breast cancer grading, enhancing clinical decision-making and treatment planning, and paving the way for further research into microstructural changes and applications in other cancer types.

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Keywords