Gian Franco Piredda1,2,3, Tom Hilbert1,2,3, Cristina Granziera4,5, Guillaume Bonnier6,7, Reto Meuli2, Filippo Molinari8, Jean-Philippe Thiran2,3, Tobias Kober1,2,3. 1. Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland. 2. Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland. 3. LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. 4. Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland. 5. Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland. 6. Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland. 7. Swiss Center for Electronics and Microtechnology, Neuchatel, Switzerland. 8. Biolab, Department of Electronics and Telecommunication, Polytechnic University of Turin, Turin, Italy.
Abstract
PURPOSE: To exploit the improved comparability and hardware independency of quantitative MRI, databases of MR physical parameters in healthy tissue are required, to which tissue properties of patients can be compared. In this work, normative values for longitudinal and transverse relaxation times in the brain were established and tested in single-subject comparisons for detection of abnormal relaxation times. METHODS: Relaxometry maps of the brain were acquired from 52 healthy volunteers. After spatially normalizing the volumes into a common space, T1 and T2 inter-subject variability within the healthy cohort was modeled voxel-wise. A method for a single-subject comparison against the atlases was developed by computing z-scores with respect to the established healthy norms. The comparison was applied to two multiple sclerosis and one clinically isolated syndrome cases for a proof of concept. RESULTS: The established atlases exhibit a low variation in white matter structures (median RMSE of models equal to 32 ms for T1 and 4 ms for T2 ), indicating that relaxation times are in a narrow range for normal tissues. The proposed method for single-subject comparison detected relaxation time deviations from healthy norms in the example patient data sets. Relaxation times were found to be increased in brain lesions (mean z-scores >5). Moreover, subtle and confluent differences (z-scores ~2-4) were observed in clinically plausible regions (between lesions, corpus callosum). CONCLUSIONS: Brain T1 and T2 quantitative norms were derived voxel-wise with low variability in healthy tissue. Example patient deviation maps demonstrated good sensitivity of the atlases for detecting relaxation time alterations.
PURPOSE: To exploit the improved comparability and hardware independency of quantitative MRI, databases of MR physical parameters in healthy tissue are required, to which tissue properties of patients can be compared. In this work, normative values for longitudinal and transverse relaxation times in the brain were established and tested in single-subject comparisons for detection of abnormal relaxation times. METHODS: Relaxometry maps of the brain were acquired from 52 healthy volunteers. After spatially normalizing the volumes into a common space, T1 and T2 inter-subject variability within the healthy cohort was modeled voxel-wise. A method for a single-subject comparison against the atlases was developed by computing z-scores with respect to the established healthy norms. The comparison was applied to two multiple sclerosis and one clinically isolated syndrome cases for a proof of concept. RESULTS: The established atlases exhibit a low variation in white matter structures (median RMSE of models equal to 32 ms for T1 and 4 ms for T2 ), indicating that relaxation times are in a narrow range for normal tissues. The proposed method for single-subject comparison detected relaxation time deviations from healthy norms in the example patient data sets. Relaxation times were found to be increased in brain lesions (mean z-scores >5). Moreover, subtle and confluent differences (z-scores ~2-4) were observed in clinically plausible regions (between lesions, corpus callosum). CONCLUSIONS: Brain T1 and T2 quantitative norms were derived voxel-wise with low variability in healthy tissue. Example patient deviation maps demonstrated good sensitivity of the atlases for detecting relaxation time alterations.
Authors: Cristina Granziera; Jens Wuerfel; Frederik Barkhof; Massimiliano Calabrese; Nicola De Stefano; Christian Enzinger; Nikos Evangelou; Massimo Filippi; Jeroen J G Geurts; Daniel S Reich; Maria A Rocca; Stefan Ropele; Àlex Rovira; Pascal Sati; Ahmed T Toosy; Hugo Vrenken; Claudia A M Gandini Wheeler-Kingshott; Ludwig Kappos Journal: Brain Date: 2021-06-22 Impact factor: 13.501
Authors: Marcus Raudner; Markus Schreiner; Tom Hilbert; Tobias Kober; Michael Weber; Reinhard Windhager; Siegfried Trattnig; Vladimir Juras Journal: Invest Radiol Date: 2020-11 Impact factor: 10.065
Authors: Adam V Dvorak; Taylor Swift-LaPointe; Irene M Vavasour; Lisa Eunyoung Lee; Shawna Abel; Bretta Russell-Schulz; Carina Graf; Anika Wurl; Hanwen Liu; Cornelia Laule; David K B Li; Anthony Traboulsee; Roger Tam; Lara A Boyd; Alex L MacKay; Shannon H Kolind Journal: Sci Rep Date: 2021-01-11 Impact factor: 4.379