HARDI-ZOOMit protocol improves specificity to microstructural changes in presymptomatic myelopathy

René Labounek, Jan Valošek, Tomáš Horák, Alena Svátková, Petr Bednařík, Lubomír Vojtíšek, Magda Horáková, Igor Nestrašil, Christophe Lenglet, Julien Cohen-Adad, Josef Bednařík, Petr Hluštík

Research output: Contribution to journalArticlepeer-review


Diffusion magnetic resonance imaging (dMRI) proved promising in patients with non-myelopathic degenerative cervical cord compression (NMDCCC), i.e., without clinically manifested myelopathy. Aim of the study is to present a fast multi-shell HARDI-ZOOMit dMRI protocol and validate its usability to detect microstructural myelopathy in NMDCCC patients. In 7 young healthy volunteers, 13 age-comparable healthy controls, 18 patients with mild NMDCCC and 15 patients with severe NMDCCC, the protocol provided higher signal-to-noise ratio, enhanced visualization of white/gray matter structures in microstructural maps, improved dMRI metric reproducibility, preserved sensitivity (SE = 87.88%) and increased specificity (SP = 92.31%) of control-patient group differences when compared to DTI-RESOLVE protocol (SE = 87.88%, SP = 76.92%). Of the 56 tested microstructural parameters, HARDI-ZOOMit yielded significant patient-control differences in 19 parameters, whereas in DTI-RESOLVE data, differences were observed in 10 parameters, with mostly lower robustness. Novel marker the white-gray matter diffusivity gradient demonstrated the highest separation. HARDI-ZOOMit protocol detected larger number of crossing fibers (5–15% of voxels) with physiologically plausible orientations than DTI-RESOLVE protocol (0–8% of voxels). Crossings were detected in areas of dorsal horns and anterior white commissure. HARDI-ZOOMit protocol proved to be a sensitive and practical tool for clinical quantitative spinal cord imaging.

Original languageEnglish (US)
Article number17529
JournalScientific reports
Issue number1
StatePublished - Dec 1 2020
Externally publishedYes

Bibliographical note

Funding Information:
The authors thank Dr. Pavel Hok from Department of Neurology, Palacký University and University Hospital Olomouc for help with an implementation of dMRI data preprocessing and solving of several co-registration issues, Ing. Petr Kudlička and Ing. Veronika Fabíková from CEITEC Brno for operating the research scanner, Dr. Jan Kočica, prof. Zdeněk Kadaňka, Dr. Zdeněk Kadaňka jr. and Ing. Dagmar Kratochvílová from Department of Neurology, University Hospital Brno for recruitment of healthy controls and patients, Ing. Jakub Zimolka and Ing. Zuzana Piskořová from Department of Biomedical Engineering, Brno University of Technology for help with implementation of pilot data processing algorithms on pilot experimental and testing dataset, Dr. Miloš Keřkovský, Dr. Tomáš Rohan and Dr. Marek Dostál from Department of Radiology, University Hospital Brno for compression level evaluations by all used participants and for well working discussion about used MRI protocol parameter settings. We acknowledge the core facility MAFIL of CEITEC supported by the Czech-BioImaging large RI project [LM2015062, LM2018129] for their support with obtaining scientific data presented in this paper. This research was supported and funded by the Czech Health Research Council [NV18-04-00159], and by the Ministry of Health of the Czech Republic project for conceptual development in research organizations [65269705-University Hospital, Brno, Czech Republic]. IN was supported by the Million Dollar Bike Ride grant from the Penn Medicine Orphan Disease Center at the University of Pennsylvania [MDBR-17-123-MPS]. CL was partly supported by National Institutes of Health [P41 EB015894, P41 EB027061, P30 NS076408]. JCA was funded by the Canada Research Chair in Quantitative Magnetic Resonance Imaging [950-230815], the Canadian Institute of Health Research [CIHR FDN-143263], the Fonds de Recherche du Québec-Santé [28826], the Fonds de Recherche du Québec-Nature et Technologies [2015-PR-182754], the Natural Sciences and Engineering Research Council of Canada [RGPIN-2019-07244], the Canada First Research Excellence Fund (IVADO and TransMedTech) and the Quebec BioImaging Network [5886, 35450]. Computational and storage resources were supplied by the project “e-Infrastruktura CZ” (e-INFRA LM2018140) provided within the program Projects of Large Research, Development and Innovations Infrastructures and by the fMRI laboratory, Department of Neurology, Palacky University Olomouc, Czech Republic.

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