Resolving bundle-specific intra-axonal T2 values within a voxel using diffusion-relaxation tract-based estimation
Muhamed Barakovic,
Chantal M.W. Tax,
Umesh Rudrapatna,
Maxime Chamberland,
Jonathan Rafael-Patino,
Cristina Granziera,
Jean-Philippe Thiran,
Alessandro Daducci,
Erick J. Canales-Rodríguez,
Derek K. Jones
Affiliations
Muhamed Barakovic
Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, Wales, UK; Signal Processing Laboratory 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
Chantal M.W. Tax
Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, Wales, UK
Umesh Rudrapatna
Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, Wales, UK
Maxime Chamberland
Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, Wales, UK
Jonathan Rafael-Patino
Signal Processing Laboratory 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
Cristina Granziera
Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland; Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
Jean-Philippe Thiran
Signal Processing Laboratory 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Radiology Department, Centre Hospitalier Universitaire Vaudois and University of Lausanne, 1005 Lausanne, Switzerland
Alessandro Daducci
Department of Computer Science, University of Verona, Verona, Italy
Erick J. Canales-Rodríguez
Signal Processing Laboratory 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; FIDMAG Germanes Hospitalàries Research Foundation, CIBERSAM, Barcelona, Spain; Corresponding author at: Signal Processing Laboratory 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Derek K. Jones
Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, Wales, UK; Mary MacKillop Institute for Health Research, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
At the typical spatial resolution of MRI in the human brain, approximately 60–90% of voxels contain multiple fiber populations. Quantifying microstructural properties of distinct fiber populations within a voxel is therefore challenging but necessary. While progress has been made for diffusion and T1-relaxation properties, how to resolve intra-voxel T2 heterogeneity remains an open question. Here a novel framework, named COMMIT-T2, is proposed that uses tractography-based spatial regularization with diffusion-relaxometry data to estimate multiple intra-axonal T2 values within a voxel. Unlike previously-proposed voxel-based T2 estimation methods, which (when applied in white matter) implicitly assume just one fiber bundle in the voxel or the same T2 for all bundles in the voxel, COMMIT-T2 can recover specific T2 values for each unique fiber population passing through the voxel. In this approach, the number of recovered unique T2 values is not determined by a number of model parameters set a priori, but rather by the number of tractography-reconstructed streamlines passing through the voxel. Proof-of-concept is provided in silico and in vivo, including a demonstration that distinct tract-specific T2 profiles can be recovered even in the three-way crossing of the corpus callosum, arcuate fasciculus, and corticospinal tract. We demonstrate the favourable performance of COMMIT-T2 compared to that of voxelwise approaches for mapping intra-axonal T2 exploiting diffusion, including a direction-averaged method and AMICO-T2, a new extension to the previously-proposed Accelerated Microstructure Imaging via Convex Optimization (AMICO) framework.
