Abstract #2176

Optimizing MRI Cytometry: Preliminary Applications and Standard Procedure Enhancements in Cervical Cancer Diagnosis

Zhilin Yuan¹, Diwei Shi², Fan Liu³, Zongshu Wang⁴, Yonglan He¹, Xin Gao⁵, Yuan Li⁶, Jing Chen⁵, Xinyu Liu¹, Jing Ren¹, Hua Guo⁷, Zhengyu Jin¹, and Huadan Xue¹

¹Radiology Department, Peking Union Medical College Hospital, Beijing, China, ²Center for Nano and Micro Mechanics, Department of Engineering Mechanics, Tsinghua University, beijing, China, ³Center for Biomedical Imaging Research, School of Biomedical Engineering, Tsinghua University, beijing, China, ⁴Tsinghua University, beijing, China, ⁵Radiology Department, Peking Union Medical College Hospital, beijing, China, ⁶Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, PR China, Beijing, China, ⁷Center for Biomedical Imaging Research, School of Biomedical Engineering, Tsinghua University, Beijing, China

Synopsis

Keywords: Microstructure, Tumors

Motivation: Cervical cancer arises from abnormal cell proliferation, and MRI-cytometry techniques have introduced a novel non-invasive approach to directly evaluate tissue microenvironment, previously unexplored in cervical cancer.

Goal(s): To explore the clinical value of MRI cytometry-based parameters in the identification of cervical cancer and further optimize the standard process to obtain better diagnostic efficiency.

Approach: MRI cytometry-based parameters are obtained by fitting the IMPULSE and JOINT models from the oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE) sequences.

Results: MRI cytometry parameters can accurately differentiate cervical cancer from normal cervix, with improved diagnostic performance achieved through full layer mapping and JOINT model fitting.

Impact: The MRI cytometry parameters can distinguish cervical cancer from normal cervix by directly capturing the changes in the tissue microstructure. It may further assist in preoperative risk stratification and treatment efficacy evaluation in cervical cancer in the future.

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