Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition - Imaging Stroke Recovery: From Microstructure to Personalized Therapy

Imaging Stroke Recovery: From Microstructure to Personalized Therapy

Digital Poster

Neuro A

Tuesday, 12 May 2026

Digital Posters Row D

09:15 - 10:10

Session Number: 463-02

No CME/CE Credit

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This digital poster session highlights advanced neuroimaging approaches to characterize brain injury, plasticity, and recovery following stroke, with applications ranging from acute assessment to rehabilitation and regenerative therapies. The studies integrate diffusion, vascular, functional, metabolic, and machine learning–based MRI methods to better understand stroke heterogeneity and guide personalized interventions.

		463-02-001. Can DKI and EPT analysis reflecting voxel-wise heterogeneity capture subtle tissue changes after stroke stem cell therapy? Maho Kitagawa, Masahito Kawabori, Xinnan Li, Ulrich Katscher, Khin Khin Tha Hokkaido University, Sappro, Japan Impact: This study demonstrates that histogram- and texture-based MRI indices can sensitively detect microstructural changes after stem cell transplantation and may serve as early imaging biomarkers for predicting functional recovery, providing a new framework for monitoring regenerative therapies in cerebral infarction.
		463-02-002. Heightened Impairments of Neurovascular Coupling and White Matter Microstructure in Bilateral Asymptomatic Moyamoya Disease Rui Hu, Jinhao Lyu, Qi Duan, Chaobang Xie, Xin Lou The First Medical Center, Chinese PLA General Hospital, Beijing, China Impact: Individuals with bilateral asymptomatic MMD present with more pronounced impairments in NVC, which may exacerbate microstructural damage and potentially contribute to cognitive decline. The observed functional and structural abnormalities offer an imaging-based framework for the development of targeted clinical interventions.
		463-02-003. Cardiac-induced volumetric brain tissue pulsations measured using DENSE MRI in patients undergoing carotid endarterectomy Ellen van Hulst, Carolijn J.M. de Bresser, Geert Biessels, Gert Borst, Jaco Zwanenburg University Medical Center Utrecht, Utrecht, Netherlands Impact: Volumetric strain measured with DENSE captures subtle hemispheric and pre- versus postoperative pulsatility differences in a small group of patients with carotid artery occlusive disease, highlighting its potential as a sensitive, noninvasive biomarker of cerebral vascular function for cerebrovascular research.
		463-02-004. Alterations of brain network topology and structural-functional coupling in post-stroke aphasia Guihua Xu, Yongsheng Wu, Rui Zhu, Junyu Qu, Wenwen Xu, Yunqi Ju, Jiaxiang xin, Dawei Wang Qilu Hospital of Shandong University, Qilu Medical Imaging Institute of Shandong University, Jinan,China, China Impact: This study identifies S-F decoupling as a potential biomarker for aphasia severity, informing targeted neuromodulation therapies for language recovery.
		463-02-005. DTI-Based Lesion Subtypes and Penumbra Zones in Ischemic Stroke Treated with Intranasal Stem Cell Therapy Yunlin Peng, Danhong Dong, 方仪王, Qiyang Chen, Liyan Tang, Diyuan Deng, Zhehao Wu, Qinglei Shi, Renzhi Wang, Xiang Wan, Hsien-Da Huang, Xinjie Bao The Chinese University of Hong Kong (Shenzhen), Shenzhen Research Institute of Big Data, China Impact: This study introduces a dual modal segmentation method based on DTI-derived FA and MD maps to segment lesion sub-regions and penumbra in ischemic stroke, providing noninvasive biomarkers for patient stratification that enables noninvasive monitoring of intranasal stem cell therapy.
		463-02-006. Replication of White Matter Disconnection Associated with Post-Stroke Depression Matthew Thurston, Jason Mattingley, Stephanie Forkel, Margaret Moore, Regis Bordet, Ranaud Lopes, Thibaut Dondaine, Florine Ruthman, Perminder Sachdev, Jessica Lo, Lena Oestreich The University of Queensland, Brisbane, Australia Impact: Our findings replicate and extend evidence that post-stroke depression is associated with widespread white matter disconnections. This reproducible network signature underscores the importance of connectivity-based biomarkers for identifying patients at risk and guiding targeted rehabilitation strategies.
		463-02-007. Automated Prediction of Domain-Specific NIHSS from MRI Using Machine Learning for Acute Stroke Assessment Wen Zhang, Shun Liu, Andreia Faria Johns Hopkins University School of Medicine, Baltimore, United States of America Impact: Automated NIHSS prediction accelerates stroke evaluation, improves consistency, and enables precision prognosis. By linking lesion patterns to functional outcomes and sharing open resources, this work advances reproducible neuroscience and supports personalized, data-driven decision-making in stroke care and research.
		463-02-008. CATCH-220: A Modular and Ultrafast Deep Learning–Enhanced Whole-Brain MRI Protocol at 1.5 T Eduardo Gragnano, Giovanni Pannella, Alessia Carboni, Alessandro Lanaro, Josef Pfeuffer, Davide Piccini, Maria Camilla Rossi-Espagnet, Fabio Tortora, Francesco Briganti, DOMENICO ZACA', Sirio Cocozza University Hospital "Federico II", Naples, Italy Impact: CATCH-220 demonstrates that clinically deployable, deep learning–enhanced whole-brain MRI can be achieved on standard 1.5 T scanners in under four minutes, supporting broader clinical use of ultrafast, multiparametric MRI in acute and routine neuroimaging workflows.
		463-02-009. In vivo Tracking of Transplanted Neural Stem Cells Using Oatp1a1-Enhanced Magnetic Resonance Imaging in Stroke Wanning Zhu, Qin Wen, Qinyuan Zhang, Zhe Wang, Jun Peng, Liejing Lu Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University,, Guangzhou, China Impact: This study establishes an organic anion-transporting polypeptide 1a1 (Oatp1a1)-based MRI platform that addresses the nonspecific signals and potential toxicity of iron-based tracking methods by providing specific, safe longitudinal monitoring of transplanted stem cells in stroke, thereby advancing regenerative therapy development.
		463-02-010. MR-Elastography characterizes changes in cerebral biomechanics after ischemic stroke Hannah Mies, Roland Zerelles, Laura Körner, Sara Amin, Artur Ashalyan, Sabine Heiland, Omar Darwish, Sibu Mundiyanapurath, Peter Ringleb, Matthias Gawlitza, Wolfgang Wick, Martin Bendszus, Ralph Sinkus, Katharina Schregel Heidelberg University Hospital, Heidelberg, Germany Impact: By revealing biomechanical brain tissue changes after stroke and CSVD, our study highlights the potential of MRE to monitor tissue remodeling and recovery. These insights may inform the development of new imaging biomarkers and treatment approaches.
		463-02-011. The Role of Early Post-Stroke Structural Brain Networks in Motor Recovery Xin Wen, Wentao Zeng, Wei Sheng, Yue Qin, Yanqiang Qiao, Junya Mu, Ming Zhang The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China Impact: This study provides insights into how early post-stroke structural brain network changes predict motor function recovery, offering potential biomarkers for clinicians to improve rehabilitation strategies and prompting further research on personalized recovery interventions.
		463-02-012. Enhancing Post-Stroke Motor Recovery with Ventrolateral Thalamus DBS via Neuroplastic Remodeling Revealed by DTI in PTI Model Cheng-Ru Yang, Yao-Wen Liang, Ssu-Ju Li, Ting-Chieh Chen, Ching-Wen Chang, Yu-Qian Ke, Yi-Duan Chen, Yi-Ren Lin, Zhi-Shin Cheng, Sheng-Huang Lin, You-Yin Chen National Yang Ming Chiao Tung University, Taipei, Taiwan Impact: Our findings identify the VL as a superior DBS target for stroke recovery. This work using DTI to show how VL-DBS structurally reorganizes motor pathways, offering a new therapeutic strategy.
		463-02-013. Functional Imaging Enriches Lesion Connectome Models by Integrating Graph Theory and Disconnectome for Stroke Recovery Himanshu Singh, Sparsh Singh, Vishnu V. Y., S Senthil Kumaran, Leve Joseph Devarajan Sebastian, Ajay Garg All India Institute of Medical Sciences, New Delhi, India Impact: Integrating structural, functional network measures and graph theory metrics at 1, 3 and 6 months to connectome modelling in stroke improves longitudinal prediction of stroke recovery. This reveals reorganisation progression from local to distributed networks.
		463-02-014. Multiparametric MRI with MRS Alters Clinical Pathway in a Case of Presumed Hypertensive Hemorrhage. Itoro Utitufon , ABDUL RASHID KARIM, Monsurah Omowunmi Ahmad., Chinedum Sampson, John Bright Adomako, Raphael Duodu Osei, Lorisgreat Ananyelom Anafo, Michael Uje Victor, Falmata Lawan Gajerima NNPC Multispecialty Hospital, Abuja, Nigeria Impact: MRI with spectroscopy provided metabolic evidence of tumor growth within a hemorrhagic lesion initially suspected as stroke on CT. The combination of structural and metabolic imaging changed the clinical diagnosis and management plan, illustrating MRI’s critical impact on patient care.