Optimizing MRI Cytometry: Preliminary Applications and Standard Procedure Enhancements in Cervical Cancer Diagnosis
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.
Authors
- Diwei Shi (ORCID: https://orcid.org/0000-0001-8261-4943)
- Yonglan He (ORCID: https://orcid.org/0000-0003-2567-9710)
- Xin Gao (ORCID: https://orcid.org/0000-0001-8622-1522)
- Fan Liu (ORCID: https://orcid.org/0000-0001-9647-6705)
- Zhengyu Jin
- Jing Ren (ORCID: https://orcid.org/0000-0002-2116-4659)
- Jing Chen (ORCID: https://orcid.org/0000-0001-7974-3090)
- Yuan Li (ORCID: https://orcid.org/0000-0001-9845-215X)
- Zhiyong Wang (ORCID: https://orcid.org/0000-0002-8379-1607)
- Xinyu Liu (ORCID: https://orcid.org/0000-0002-0564-7167)
- Zhilin Yuan
- Hua Guo (ORCID: https://orcid.org/0000-0003-4474-8507)
- Huadan Xue
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/10.58530/2025/2176
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00