The aim of this study was to study focal cerebellar pathology in early stages of multiple sclerosis (MS) using ultra-high-field magnetization-prepared 2 inversion-contrast rapid gradient-echo (7T MP2RAGE).
Twenty early-stage relapsing-remitting MS patients underwent an MP2RAGE acquisition at 7 T magnetic resonance imaging (MRI) (images acquired at 2 different resolutions: 0.58 × 0.58 × 0.58 mm3, 7T_0.58, and 0.75 × 0.75 × 0.90 mm3, 7T_0.75) and 3 T MRI (1.0 × 1.0 × 1.2 mm3, 3T_1.0). Total cerebellar lesion load and volume and mean cerebellar lesion volume were compared across images using a Wilcoxon signed-rank test. Mean T1 relaxation times in lesions and normal-appearing tissue as well as contrast-to-noise ratio (CNR) measurements were also compared using a Wilcoxon signed-rank test. A multivariate analysis was applied to assess the contribution of MRI metrics to clinical performance in MS patients.
Both 7T_0.58 and 7T_0.75 MP2RAGE showed significantly higher lesion load compared with 3T_1.0 MP2RAGE (P < 0.001). Plaques that were judged as leukocortical in 7T_0.75 and 3T_1.0 MP2RAGEs were instead identified as WM lesions in 7T_0.58 MP2RAGE. Cortical lesion CNR was significantly higher in MP2RAGEs at 7 T than at 3 T. Total lesion load as well as total and mean lesion volume obtained at both 7 T and 3 T MP2RAGE significantly predicted attention (P < 0.05, adjusted R 2 = 0.5), verbal fluency (P < 0.01, adjusted R 2 = 0.6), and motor performance (P = 0.01, adjusted R 2 = 0.7).
This study demonstrates the value of 7 T MP2RAGE to study the cerebellum in early MS patients. 7T_0.58 MP2RAGE provides a more accurate anatomical description of white and gray matter pathology compared with 7T_0.75 and 3T_1.0 MP2RAGE, likely due to the improved spatial resolution, lower partial volume effects, and higher CNR.
From the *Advanced Clinical Imaging Technology, Siemens Healthcare AG; †Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland; ‡Centre for Advanced Imaging, University of Queensland; §Siemens Healthcare Pty Ltd, Brisbane, Queensland, Australia; ∥Department of Radiology, Valais Hospital, Sion, Switzerland; ¶Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA; #Signal Processing Laboratory, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; **Siemens Medical Solutions USA, Inc, Malvem, PA; ††Medical Image Analysis Laboratory, Centre d'Imagerie BioMédicale; and ‡‡Neuroimmunology Unit, Neurology, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland.
Received for publication August 12, 2016; and accepted for publication, after revision, October 11, 2016.
Conflicts of interest and sources of funding: Supported by the Swiss National Science Foundation under grant PZ00P3_131914/11, The Swiss Government: Federal Commission for Scholarships for Foreign Students, The Swiss MS Society and the Societé Académique Vaudoise, the Centre d'Imagerie BioMédicale (CIBM) of the University of Lausanne (UNIL), the Swiss Federal Institute of Technology Lausanne (EPFL), the University of Geneva (UniGe), the Centre Hospitalier Universitaire Vaudois (CHUV), the Hôpitaux Universitaires de Genève (HUG), and the Leenaards and the Jeantet Foundations. The funding sources had no role in study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the article for publication.
M.J.F., K.O., G.K. and T.K. are Siemens employees. For the remaining authors, none were declared.
Correspondence to: Mário João Fartaria, MSc, Advanced Clinical Imaging Technology, Siemens Healthcare AG, EPFL Innovation Park, Bâtiment E 1015, Lausanne, Switzerland. E-mail: email@example.com.