Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition

Image Analysis for Cancer

Digital Poster

Analysis Methods

Tuesday, 12 May 2026

Digital Posters Row D

16:55 - 17:50

Session Number: 463-06

No CME/CE Credit

Similar Sessions

This session will cover the development and validation of image analysis approaches applied to applications in cancer.

		463-06-001. The Value of Gadoxetate Disodium-Enhanced MRI Habitat Imaging in Preoperative Prediction of Proliferative HCC Zhimin Yu, Chengyu Ding, Xueqin Zhang Nantong University, Nantong, China Impact: The nomogram model based on gadoxetate disodium-enhanced MRI habitat imaging demonstrates potential for predicting proliferative hepatocellular carcinoma and exhibits favorable capability for prognostic risk stratification.
		463-06-002. DCE-MRI Morphometric Assessment Predicts Chemotherapy Response in Colorectal Liver Metastasis HUAN ZHANG, Tong Tong Fudan University Shanghai Cancer Center, Shanghai, China Impact: This study reveals the potential role of morphometric features in predicting chemotherapy response in CRLM, providing a practical and effective tool for clinical decision-making.
		463-06-003. Multiparametric 18F-FDG PET/MRI Reveals Intratumoral Heterogeneity for Differentiating Benign and Malignant Solitary Pulmonar Nan Meng, Qianqian Chen, Xinyu Wang, Yue Liu, Xuan Yu, Qiuyu Ji, Zhe Wang, Yang Yang, Meiyun Wang Henan Provincial People's Hospital, Zhengzhou, China Impact: Multiparametric ¹⁸F-FDG PET/MRI habitat imaging enables non-invasive differentiation of benign and malignant solitary pulmonary lesions by quantifying intratumoral spatial heterogeneity. This approach reveals distinct subregional patterns and provides novel imaging biomarkers with potential clinical utility for precision diagnosis and management.
		463-06-004. Habitat analysis and peritumoral radiomics for predicting castration resistance in prostate cancer patients hongyan Gao, Wenjia Wang, hui Wu Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China Impact: Habitat analysis can predict the likelihood of CRPC development in PCa patients by resolving intratumoral heterogeneity. The peritumoral radiomics model holds independent predictive value for CRPC, and integrating peritumoral radiomic features can further enhance model performance.
		463-06-005. The value of foundation model-driven multiomics for predicting platinum resistance in HGSOC patients Qiu Bi, Li Wu, Yunzhu Wu, Meining Chen The First People’s Hospital of Yunnan Province. The Affiliated Hospital of Kunming University of Science and Technology, kunming, China Impact: This study carries the potential to equip clinicians with treatment strategies aimed at enhancing the efficacy of individualized therapy.
		463-06-006. Multiparametric MRI in the Discrimination of Progression from Atypical Endometrial Hyperplasia to Stage IA Endometrial Cancer Qingwen Xiao, Lingtao Zhang, wei cui, Dong Zhang, Liangping Luo, Changzheng Shi The First Affiliated Hospital of Jinan University, Guangzhou, China Impact: This study confirms the critical role of multiparametric MRI in differentiating AH from Stage IA EC, paving the way for a reliable, non-invasive approach to clinical diagnosis.
		463-06-007. Noninvasive Assessment of Bladder Cancer Staging and Grading Using Continuous-Time Random Walk-Based Habitat Analysis Ding Li, Xiaochun Wang First Hospital of Shanxi Medical University, Taiyuan, China Impact: Our results show that CTRW-derived parameters, particularly in Habitat 2, effectively distinguish staging and grading subgroups. A combined model incorporating imaging and clinical factors achieved strong predictive performance, highlighting its potential as a noninvasive diagnostic tool.
		463-06-008. Automated Lesion Detection of Deep Learning-based Phase Corrected Single-Shot rFOV Diffusion Images of the Prostate Eugene Milshteyn, Xinzeng Wang, Patricia Lan, Arnaud Guidon, Adele Courot, Nicolas Gogin, Nabih Nakrour, Ranjodh Dhami, William Bradley, Mukesh Harisinghani, Rory Cochran GE HealthCare, San Ramon, United States of America Impact: DL Phase Correction improves the signal-to-noise ratio and IQ of prostate DWI over current commercial DL reconstructions, while showing compatibility with an investigational automated prostate lesion detection tool.
		463-06-009. Radiomic feature analyses reveal imaging biomarkers correlated with PI-RADS lesion classification in prostate cancer MRI. Savannah Duenweg, Michael Barrett, Samuel Bobholz, Allison Lowman, Biprojit Nath, Aleksandra Winiarz, Hope Reecher, Fitzgerald Kyereme, Stephanie Vincent-Sheldon, Kathleen Bhatt, Katherine Troy, Michael Kim, Eric Fair, William Hall, Peter LaViolette Medical College of Wisconsin, Milwaukee, United States of America Impact: Radiomic features calculated on clinical multiparametric MRI strongly correlate with PI-RADS classifications. These features may provide quantitative biomarkers to aid diagnostic confidence for indeterminate PI-RADS lesions and reduce inter-rater variability.
		463-06-010. A Biparametric MRI-based Deep Transfer Learning and Radiomics Model for Diagnosing Clinically Significant Prostate Cancer Xuelian Zhao, NING ZHANG, fei jia, Guang Liu, Yanli Jiang, Jing Zhang, Kai AI The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, China Impact: This study provides a critical foundation for optimizing prostate biopsy decisions. It can potentially reduce unnecessary procedures and improve patient management, demonstrating significant promise for clinical translation.
		463-06-011. MRI in Diagnosing Lumbar Spine Chordoma: Insights from a Low-Resource Environment Chikumbutso Khomba, Osward Bwanga, Lloyd Likato Affidea Diagnostic, Dublin, Ireland Impact: This case demonstrates how MRI can act as a surrogate diagnostic adjunct in settings with limited access to histopathology. By guiding early surgical planning and multidisciplinary care for spinal chordoma, MRI enhances clinical decision-making and promotes equitable cancer management.