Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition • 09-14 May 2026

Digital Poster

Classification in Diffusion MRI II

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Classification in Diffusion MRI II
Digital Poster
Analysis Methods
Monday, 11 May 2026
Digital Posters Row E
17:05 - 18:00
Session Number: 364-06
No CME/CE Credit
Similar Sessions
Advanced classification methods based on diffusion MRI
  Figure 364-06-001.  DTI with 3D high-resolution MRI of lumbosacral nerve roots in LDH with radiculopathy & clinical correlations
wei Zeng, Yang Haitao, Lisha Nie
The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
Impact: By pinpointing the most damaged nerve-root segment and controlling cerebrospinal fluid bias, this standardized index supports accurate decompression-level selection, quantifies injury severity, and tracks post-treatment recovery, while providing a consistent endpoint for multicenter trials and therapy development.
  Figure 364-06-002.  Time-dependent diffusion MRI for Microstructural Mapping and Glioma Grading Prediction
Mingjun Lu, Yongzhou Xu, Shilong Lu, Zhibo Wen
Zhujiang Hospital, Southern Medical University, Guangzhou, China
Impact: By leveraging time-dependent diffusion MRI, this study provides novel microstructural biomarkers for glioma characterization, enabling precise noninvasive grading and offering translational potential for individualized therapeutic strategies.
  Figure 364-06-003.  Time-dependent diffusion MRI for assessing microstructure and prognostic risk factors in cervical cancer
Tianhui Zhang, Weixiong Fan, Kuiyuan Liu, Haoan Xu, Wenbiao Zhu, Yingsi Yang, Wenhui Xie, Dan Wu, Zhihan Yan, Jiaqi Wang, Jing Yang, Meihao Wang, Xue Wang
Meizhou People's Hospital, Guangdong,Meizhou, China
Impact: Time-dependent diffusion MRI enables microstructural mapping of cervical cancer, offering a novel imaging biomarker for predicting tumor aggressiveness and lymphovascular invasion, thus supporting individualized treatment decisions.
  Figure 364-06-004.  Differentiating Cervical Cancer Subtypes Using Diffusion MRI: More b Values or More Diffusion Times?
Zhilin Yuan, Diwei Shi, Chen Wang, Fan Liu, Jing Chen, Xinyu Liu, Yilan Ji, Baiyan Su, Jinxia ZHU, Thorsten Feiweier, Zhengyu Jing, Junzhong Xu, Hua Guo, Yuan Li, Yonglan He, Huadan Xue
Peking Union Medical College Hospital, Beijing, China
Impact: Incorporating multiple diffusion times into signal acquisitions can improve clinical performance of dMRI measurements in cervical cancer diagnosis, rather than solely expanding b-value ranges. This study provides useful guidance for optimizing cervical cancer imaging protocols and data analysis.
  Figure 364-06-005.  Diagnostic Value of Time-Dependent Diffusion MRI in Grading and Subtyping Meningiomas
Yuxi Xie, Yiping Lu, Bo Yin
Huashan Hospital, Fudan University, China
Impact: Td-dMRI-derived microstructural parameters represent promising noninvasive biomarkers for distinguishing the grades, subtypes, and proliferative activity of meningiomas. By offering quantitative, biologically validated parameters, td-dMRI may help to enhance noninvasive grading, guide surgical planning, and improve prognostic assessment in meningioma patients.
  Figure 364-06-006.  T2 mapping and advanced diffusion models for the differentiation of thyroid nodules
Kunyao Li, Junhao Huang, Huanhuan Ren, Daihong Liu, Xinying Ren, Wenqin Yang, Hongyu Chen, Wang Lv, 菁 张, Hong Yu, Fei Han, Ting Yin, Jiuquan Zhang
Chongqing University Cancer Hospital, Chongqing, China
Impact: T2 mapping and advanced diffusion models offer a valuable diagnostic reference for differentiating benign from malignant thyroid nodules and identifying specific pathological subtypes in clinical practice.
  Figure 364-06-007.  A Study on the Predictive Value of DTI and ASL Histogram Features for MGMT Status and Prognosis in Glioblastoma
Fengwei Yu, Hailong Jiang, Pinzhen Chen, Jing Yang, Ruishan Liu, Jianping Yang, Jiafei Chen, Wei Chen
Army Medical University (Third Military Medical University), Chongqing, China
Impact: This study establishes DTI-derived histogram features as non-invasive biomarkers for O⁶-methylguanine-DNA methyltransferase （MGMT） status, revealing their mediating role in survival, which may guide personalized treatment strategies in glioblastoma.
  Figure 364-06-008.  Quantitative Time-Dependent Diffusion MRI for Diagnosis of Endometrial Lesions：A Preliminary Study
Le Fu, Jiejun Cheng, Yichen Wang, Jianli Yu
Shanghai first maternity and infant hospital, Shanghai, China
Impact: td-dMRI enables noninvasive quantification of endometrial microstructure, offering superior diagnostic specificity over ADC.
It shows promise as a biomarker for preoperative risk stratification and personalized management of endometrial lesions.
  Figure 364-06-009.  Investigating White-Matter Pathways of Cognitive Decline in Parkinson's Disease
Rishitha Praveen, Ivan Campbell, Narayan Chaurasiya, Jessica K. Caldwell, Aaron Ritter, Zoltan Mari, Virendra Mishra
University of Alabama at Birmingham, Birmingham, United States of America
Impact: The hidden white-matter fingerprints of cognitive impairment in Parkinson's illness are revealed by fixel-based MRI. PD-nMCI has early compensatory wiring while PD-MCI exhibit structural deterioration.
  Figure 364-06-010.  Discriminating Orbital Lymphoma from Inflammation Using Microstructure-Based Time-Dependent Diffusion MRI
Hangzhi Liu, Yingzhu Zhao, Chen Zhang, Xiaoxia Qu, Thorsten Feiweier, Xinyan Wang, Junfang Xian
Department of Radiology, Beijing, China
Impact: 
  • Td-dMRI enhances the pre-operative differentiation of orbital lymphoma from inflammatory lesions.
  • The derived microstructural parameters (e.g., cellular diameter and cellularity) demonstrate a strong correlation with histopathological findings.
  • Cellularity exhibits the highest diagnostic accuracy (AUC = 0.87) for identifying lymphoma.
  Figure 364-06-011.  The Application of Time-Dependent Diffusion MRI in Clinical Staging and Pathological Differentiation of Cervical Carcinoma
Junjun Li, Yi Xiao, Yi Zhu, Kai AI, Jianxin Guo
The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
Impact: TDD-MRI parameters, particularly cell diameter, demonstrate superior accuracy to ADC in differentiating pathological grades and stages in CSC, supporting their use for non-invasive cervical cancer assessment.
  Figure 364-06-012.  Single-shell AMURA and MiSFIT diffusion metrics improve brain-age prediction beyond conventional DTI
Raquel Santiesteban, Rafael Navarro, Alessandra Gallo, Álvaro Planchuelo-Gómez, Antonio Tristán-Vega, Santiago Aja-Fernández, Rodrigo de Luis García
UNIVERSIDAD DE VALLADOLID, Valladolid, Spain
Impact: Advanced AMURA/MiSFIT metrics from single-shell dMRI improve brain-age accuracy over conventional DTI while avoiding multi-shell acquisitions and heavy computation. This enables immediate integration into standard clinical protocols and multi-centre studies using existing data and routine scanners.
  Figure 364-06-013.  Application of IVIM-DWI Parameters and Peritumoral Vessels in Predicting pCR in Luminal Breast Cancer
Xinyue Yin, Moyun Zhang, Shuo Wang, Zhitian Guo, Haonan Guan, Lina Zhang
The First Affiliated Hospital of Dalian Medical University, Dalian, China
Impact: A multi-parameter MRI strategy integrating diffusion (ADC, D) and vascularity (AVS) enhances pCR prediction in Luminal breast cancer, enabling more precise NAC response assessment and informing individualized treatment decisions.
  Figure 364-06-014.  Conditional Diffusion Model for Synthetic Breast Implant Images: Impact on Classification Performance
Vanika Singhal, Harsh Suthar, Sandeep Kaushik, Sajith Rajamani, Uday Patil, Pavan Annangi, Chitresh Bhushan, Dattesh Dayanand Shanbhag
GE HealthCare, Bengaluru, India
Impact: This study demonstrates that diffusion-based synthetic data generation can address breast implant case scarcity, improving MRI classification accuracy and generalizability. It enables broader adoption of synthetic augmentation for underrepresented clinical scenarios, fostering efficient workflows and improving model robustness.

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