Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition - From Theory to Clinic: Advances in Diffusion MRI Modeling and Analysis

From Theory to Clinic: Advances in Diffusion MRI Modeling and Analysis

Oral

Diffusion

Monday, 11 May 2026

Auditorium 2

13:50 - 15:40

Moderators: Milena Capiglioni & Marco Pizzolato

Session Number: 306-02

CME/CE Credit Available

Similar Sessions

This session brings together work on diffusion MRI analysis and modelling, from theoretical frameworks and uncertainty quantification to clinical implementation.

Skill Level: Advanced

13:50		306-02-001. Validity of the Gaussian phase approximation (GPA): Analytical results for the constant gradient spin echo in one dimension Teddy Cai, Nathan Williamson, Peter Basser Eunice Kennedy Shriver - National Institute of Child Health and Human Development (NICHD), Bethesda, United States of America Impact: We find that the GPA is more fragile than commonly assumed. The introduction of exchange-like dynamics, in particular, can lead to significant positive excess phase kurtosis. This undermines the validity of models that assume the GPA in permeable microstructure.
14:01		306-02-002. A dSPECIAL acquisition: Modeling metabolic diffusion in the rat brain at a wide range of b-values and diffusion times Malte Brammerloh , Tan Toi Phan, Rita Oliveira, Thanh Phong Lê, Quentin Uhl, Eloise Mougel, Jessie Mosso, Cristina Cudalbu, Ileana Jelescu Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland Impact: We extend time-dependent dMRS analysis beyond typical metabolites and to higher b-values at long diffusion times, expanding the potential of dMRS as a non-invasive histology technique. Neuronal vs glial features are corroborated by histology literature.
14:12		306-02-003. Propagating uncertainty from diffusion MRI signal to fiber orientations, model parameters and tractography Jiezhang Cao, William Consagra, Lipeng Ning, Lauren O’Donnell, Yogesh Rathi Brigham and Women's Hospital and Harvard Medical School, Boston, United States of America Impact: Without multiple dMRI scans, our approach can quantify and propagate the uncertainty of fiber orientations, standard model parameters and tractography, reducing scan time, and improving reproducibility with statistically robust estimation.
14:23		306-02-004. A Robust Iterative Reconstruction Framework for Phase-Based Diffusion MRI with Quantitative Noise and Precision Analysis Daiki Tamada, Ali Pirasteh, David Jarrard, Diego Hernando, Scott Reeder University of Wisconsin - Madison, Madison, United States of America Impact: Our reconstruction framework and analysis advance PBD from a promising concept to a quantitatively characterized method. The finding that median PBD estimates are unbiased at low-SNR offers a key advantage over conventional DWI, providing a pathway for protocol optimization.
14:34		306-02-005. HARP: HARmonizing in-vivo diffusion MRI using Phantom-only training Hwihun Jeong, Qiang Liu, Kathryn Keenan, Elisabeth Wilde, Walter Schneider, Sudhir Pathak, Anthony Zuccolotto, Lauren O’Donnell, Lipeng Ning, Yogesh Rathi Brigham and Women's Hospital and Harvard Medical School, Boston, United States of America Impact: HARP enables inter-scanner dMRI harmonization trained only with phantom data, eliminating the complex need for matched in-vivo multi-site cohorts. This robust, phantom-only strategy significantly enhances the feasibility and scalability of quantitative dMRI for large-scale clinical studies.
14:45		306-02-006. A Cleaner Cortical Grey Matter Diffusion Signal: CSF Partial Volume Correction Using Surface and PSF Estimation Hossein Rafipoor, Saad Jbabdi, Wenchuan Wu, William Clarke, Michiel Cottaar FMRIB Centre, Oxford Centre for Integrative Neuroimaging (OXCIN), University of Oxford, Oxford, United Kingdom Impact: This framework enables more accurate cortical diffusion MRI by removing CSF contamination bias without requiring CSF-suppressed acquisitions or additional modelling, improving the reliability of grey-matter microstructure mapping and enabling more detailed modelling of diffusion within the cortex.
14:56		306-02-007. GAIA – Green Artificial Intelligence for Accelerated medical imaging: Sustainable and Efficient Diffusion MRI Analysis Maëliss Jallais, Matteo Mancini, Marco Palombo Cardiff University, Cardiff, United Kingdom Impact: MRI and AI models have a significant carbon footprint. Exploiting knowledge distillation, GAIA enables accurate, lightweight, and energy-efficient networks, reducing environmental impact and supporting sustainable, accessible deployment of advanced imaging tools across diverse clinical and low-resource settings.
15:07		306-02-008. Axon- and glia-specific fiber orientation distributions in human white matter probed with diffusion MR spectroscopy Jessie Mosso, Santiago Coelho, Ricardo Coronado-Leija, Valentin Stepanov, Andrè Döring, Roland Kreis, Dmitry Novikov, Els Fieremans New York University Grossman School of Medicine, New York, United States of America Impact: We report unique metabolite fiber orientation distribution functions measured in human white matter with diffusion MR spectroscopy. The agreement between water and neuronal but not glial metabolites orientations opens new avenues for elucidating brain meso-structure in a cell type-specific manner.
15:18		306-02-009. Clinical Soma and Neurite Density Imaging (SANDI): Translational microstructural mapping for standard 3T MRI scanners Hansol Lee, Kwok-Shing Chan, Yixin Ma, Eva Krijnen, Laleh Eskandarian, Aneri Bhatt, Julianna Gerold, Susie Huang, Hong Hsi Lee Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, United States of America Impact: The proposed clinical SANDI model enables reliable, noninvasive microstructural mapping of gray matter on widely available clinical 3T scanners within feasible scan times, facilitating broader translation of advanced diffusion MRI models for studying neurodegeneration, aging, and other microstructural brain alterations.
15:29		306-02-010. Non-parametric In-vivo Diffusion Tensor Distribution (DTD) MRI of the Human Brain Kulam Najmudeen Magdoom, Joelle Sarlls, Peter Basser The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, United States of America Impact: We have developed a method which has identified various mesoscopic water pools inside each voxel not observed previously. This has the potential to detect subtle changes in tissue microstructure in disease such as traumatic brain injury (TBI), development, etc.