Microstructure & Connectivity Lab
Publications (Review, Commentary, Consensus)
Publications (Review, Commentary, Consensus)
Edited by: Kurt G. Schilling, Irvin Teh, Julien Cohen-Adad, Richard Dortch, Ibrahim Ibrahim, Nian Wang, Bruce Damon, Rory L. Cochran, Alexander Leemans
Journal: Brain Structure and Function (2026)
Keywords: Extracranial Tractography, Cardiac DTI, Spinal Cord MRI, Peripheral Nerves, Skeletal Muscle Architecture, Body MRI.
Summary: While diffusion tractography is widely recognized as a cornerstone of brain mapping, its application to anatomical structures outside the brain remains a rapidly evolving frontier. This comprehensive review surveys the adaptation of tractography for mapping the microarchitecture of the heart, spinal cord, peripheral nerves, brachial plexus, kidneys, skeletal muscle, and prostate. We detail the unique methodological challenges associated with extracranial imaging - such as managing physiological motion and lower tissue anisotropy - and explore the powerful structural, diagnostic, and clinical insights these techniques unlock across the body.
Edited by: Kurt G. Schilling, Matthew Cieslak, Maxime Descoteaux, Bennett A. Landman, Franco Pestilli, Ariel Rokem, Stamatios N. Sotiropoulos, Jacques-Donald Tournier, Jelle Veraart
Journal: Brain Structure and Function (2026)
Keywords: Diffusion MRI (dMRI), Tractography, Preprocessing Pipelines, Artifact Correction, Reproducibility, Denoising, EPI Distortion.
Summary: Diffusion MRI fiber tractography is highly sensitive to imaging noise and artifacts, which can cascade into severe anatomical inaccuracies. This consensus-driven commentary outlines how implementing state-of-the-art preprocessing techniques - including denoising, Gibbs ringing removal, and corrections for motion, eddy currents, and EPI distortions - drastically improves the anatomical fidelity and test-retest reproducibility of tractography. The paper serves as a practical guide to best practices, highlighting integrated, publicly available neuroinformatics pipelines and data-handling strategies that maximize the reliability of brain mapping.
Edited by: J.C. Gore, M. Li, K.G. Schilling, L. Xu, Y. Li, Z. Zu, A.W. Anderson, Z. Ding, Y. Gao
Journal: Magnetic Resonance Imaging (2026)
Keywords: White Matter fMRI, BOLD Signal, Resting State, Functional Connectivity, Neurovascular Coupling, Microstructure
Summary: Historically, blood oxygenation level-dependent (BOLD) signals in white matter have been largely ignored or treated as noise in fMRI analyses. This review synthesizes emerging evidence demonstrating that white matter BOLD signals are robust, detectable, and intimately linked to tissue microstructure, composition, and vascular properties. By detailing the relationships between white matter BOLD, local metabolism, and synchronized gray matter networks, this paper advocates for incorporating white matter functional signals into a more complete, holistic model of brain functional organization.
Edited by: Bramsh Qamar Chandio, Kurt G. Schilling and Julio E. Villalon-Reina
Journal: Frontiers in Neuroscience (2025)
Summary: Explore our new Research Topic, 'Methods and applications of diffusion MRI tractometry,' which highlights the transformation of tractometry into a powerful framework for quantifying white matter microstructure with high anatomical specificity. This collection of sixteen articles spans cutting-edge methodological innovations - including reproducible software and validation tools - and diverse clinical applications ranging from autism and multiple sclerosis to lifespan development. By advancing beyond traditional voxel-based metrics to precise along-tract profiling, these contributions offer critical new insights into the human connectome and disease mechanisms. Read the full e-book to discover how these emerging techniques and open-source resources are reshaping the future of neuroimaging research.
Authors: Kurt G. Schilling, Fan Zhang, J-Donald Tournier, Francesco Vergani, Stamatios N. Sotiropoulos, Ariel Rokem, and Lauren J. O'Donnell.
Journal: Brain Structure & Function (2025)
Summary: Originating from the inaugural International Society of Tractography (IST) debate, this article tackles a fundamental controversy in neuroimaging: 'Can tractography give us anything we can't get from an atlas template?'. We critically compare the standardized efficiency of population-based white matter atlases against the personalized precision of subject-specific tractography across four key domains: microstructure, macrostructure, pathway localization, and connectomics. Ultimately, we argue that while atlases drive reproducibility, individualized virtual dissection is indispensable for capturing patient-specific anatomical variability and mapping unique structural connectivity in both health and disease.
Authors: Kurt Schilling, Fan Zhang, Claudio Román, Lauren O’Donnell, Pamela Guevara
Journal: Brain Structure and Function (2025)
Summary: This correspondence outlines key insights into the tractography of short association fibers (SAFs), using a “Did You Know” format to highlight current challenges, progress, and future directions. (1) Did you know SAFs form a dense mesh of superficial white matter and differ from long-range tracts in structure, development, and vulnerability? (2) Did you know reconstructing SAFs is difficult due to their short length, high curvature, and proximity to cortex? (3) Did you know recent advances in acquisition, modeling, and segmentation - like deep learning and high-resolution MRI - have made SAF tractography feasible? (4) Did you know there is no standard classification for SAFs, with atlases and clustering strategies still evolving? (5) Did you know SAFs are sensitive to developmental and pathological changes and are implicated in Alzheimer’s, schizophrenia, autism, and MS?
Authors: Ileana O. Jelescu, Francesco Grussu, Andrada Ianus, Brian Hansen, Rachel L. C. Barrett, Manisha Aggarwal, Stijn Michielse, Fatima Nasrallah, Warda Syeda, Nian Wang, Jelle Veraart, Alard Roebroeck, Andrew F. Bagdasarian, Cornelius Eichner, Farshid Sepehrband, Jan Zimmermann, Lucas Soustelle, Christien Bowman, Benjamin C. Tendler, Andreea Hertanu, Ben Jeurissen, Marleen Verhoye, Lucio Frydman, Yohan van de Looij, David Hike, Jeff F. Dunn, Karla Miller, Bennett A. Landman, Noam Shemesh, Adam Anderson, Emilie McKinnon, Shawna Farquharson, Flavio Dell’Acqua, Carlo Pierpaoli, Ivana Drobnjak, Alexander Leemans, Kevin D. Harkins, Maxime Descoteaux, Duan Xu, Hao Huang, Mathieu D. Santin, Samuel C. Grant, Andre Obenaus, Gene S. Kim, Dan Wu, Denis Le Bihan, Stephen J. Blackband, Luisa Ciobanu, Els Fieremans, Ruiliang Bai, Trygve B. Leergaard, Jiangyang Zhang, Tim B. Dyrby, G. Allan Johnson, Julien Cohen-Adad, Matthew D. Budde, Kurt G. Schilling
Journal: Magnetic Resonance in Medicine (2025)
Summary: These three papers from the ISMRM Diffusion Study Group provide best practices and recommendations for preclinical diffusion MRI (dMRI). Part 1 focuses on in vivo small-animal imaging, detailing considerations for species selection, imaging protocols, and analysis to enhance rigor and reproducibility. Part 2 explores ex vivo imaging, highlighting its advantages—such as higher resolution, improved signal-to-noise ratio (SNR), and direct histological comparisons—while addressing challenges in tissue preparation and acquisition. Part 3 covers ex vivo data processing, discussing preprocessing steps, diffusion model fitting, and comparisons with microscopy and tractography, aiming to improve methodological validation and open science efforts. Together, these works provide a comprehensive guide to optimizing preclinical dMRI research.
Authors: Alard Roebroeck, Suzanne Haber, Elena Borra, Simona Schiavi, Stephanie J. Forkel, Kathleen Rockland, Tim B. Dyrby, Kurt Schilling
Journal: Brain Structure & Function (2025)
Summary: This correspondence article summarizes a debate from the 2024 Tract-Anat Retreat on the value of animal models in human diffusion tractography. We argue that, despite species differences and translational challenges, animal studies are invaluable for validating tractography against histology, acquiring extreme high-resolution datasets, probing disease mechanisms, and advancing comparative anatomy. The piece underscores the unique translational potential of preclinical models while emphasizing the need for ethical rigor, careful species selection, and methodological awareness.
Authors: Ileana O. Jelescu, Marco Palombo, Francesca Bagnato, Kurt G. Schilling
Journal: Journal of Neuroscience Methods (2020)
Keywords: Biophysical Modeling, Diffusion MRI (dMRI), Microstructure, Validation, Clinical Translation, Brain Tissue, Neuropathology.
Summary: Biophysical modeling in diffusion MRI has grown immensely over the past 25 years, promising non-invasive insights into cellular-level brain tissue properties. This review maps the journey of bringing a biophysical model from initial design to clinical implementation. We detail the steps of selecting estimable microstructural features, optimizing acquisition protocols, and rigorously validating models using numerical simulations, experimental data, and complementary techniques. By examining applications in tumors, ischemia, and demyelinating diseases, the paper highlights successes in pathology while outlining unresolved challenges holding back clinical translation - including the lack of ground-truth validation for certain microstructural parameters and the need for a generalized standard model.
Authors: Kurt G. Schilling, Alessandro Daducci, Klaus Maier-Hein, Cyril Poupon, Jean-Christophe Houde, Vishwesh Nath, Adam W. Anderson, Bennett A. Landman, Maxime Descoteaux
Journal: Magnetic Resonance Imaging (2019)
Keywords: Diffusion MRI (dMRI), Tractography, Algorithms, Validation, Benchmark Competitions, Structural Connectivity, Accuracy, False Positives.
Summary: Assessing the true anatomical accuracy of diffusion MRI tractography is "challenging". Over the past decade, the neuroimaging community has organized multiple international benchmark competitions ("challenges") to evaluate algorithm reliability using curated datasets and known ground truths. This review synthesizes the key lessons learned from these global initiatives, highlighting what tractography algorithms do well (such as following local orientations to reconstruct valid connections) alongside persistent limitations (like the sensitivity-specificity tradeoff and high false-positive rates in complex crossing-fiber regions). By reflecting on these outcomes, we provide a roadmap defining the past, present, and future challenges facing the field of diffusion tractography.