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Characterization of thalamic lesions and their correlates in multiple sclerosis by ultra-high-field MRI.
Mehndiratta, Ambica; Treaba, Constantina A; Barletta, Valeria; Herranz, Elena; Ouellette, Russell; Sloane, Jacob A; Klawiter, Eric C; Kinkel, Revere P; Mainero, Caterina.
Afiliación
  • Mehndiratta A; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.
  • Treaba CA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Barletta V; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Herranz E; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Ouellette R; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.
  • Sloane JA; Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
  • Klawiter EC; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Kinkel RP; Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.
  • Mainero C; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Mult Scler ; 27(5): 674-683, 2021 04.
Article en En | MEDLINE | ID: mdl-32584159
BACKGROUND: Thalamic pathology is a marker for neurodegeneration and multiple sclerosis (MS) disease progression. OBJECTIVE: To characterize (1) the morphology of thalamic lesions, (2) their relation to cortical and white matter (WM) lesions, and (3) clinical measures, and to assess (4) the imaging correlates of thalamic atrophy. METHODS: A total of 90 MS patients and 44 healthy controls underwent acquisition of 7 Tesla images for lesion segmentation and 3 Tesla scans for atrophy evaluation. Thalamic lesions were classified according to the shape and the presence of a central venule. Regression analysis identified the predictors of (1) thalamic atrophy, (2) neurological disability, and (3) information processing speed. RESULTS: Thalamic lesions were mostly ovoid than periventricular, and for the great majority (78%) displayed a central venule. Lesion volume in the thalamus, cortex, and WM did not correlate with each other. Thalamic atrophy was only associated with WM lesion volume (p = 0.002); subpial and WM lesion volumes were associated with neurological disability (p = 0.016; p < 0.001); and WM and thalamic lesion volumes were related with cognitive impairment (p < 0.001; p = 0.03). CONCLUSION: Thalamic lesions are unrelated to those in the cortex and WM, suggesting that they may not share common pathogenic mechanisms and do not contribute to thalamic atrophy. Combined WM, subpial, and thalamic lesion volumes at 7 Tesla contribute to the disease severity.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Disfunción Cognitiva / Esclerosis Múltiple Límite: Humans Idioma: En Revista: Mult Scler Asunto de la revista: NEUROLOGIA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Disfunción Cognitiva / Esclerosis Múltiple Límite: Humans Idioma: En Revista: Mult Scler Asunto de la revista: NEUROLOGIA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido