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Statistical estimation of T1 relaxation times using conventional magnetic resonance imaging.
Mejia, Amanda F; Sweeney, Elizabeth M; Dewey, Blake; Nair, Govind; Sati, Pascal; Shea, Colin; Reich, Daniel S; Shinohara, Russell T.
Afiliación
  • Mejia AF; Department of Biostatistics, The Johns Hopkins University, Baltimore, MD 21205, USA.
  • Sweeney EM; Department of Biostatistics, The Johns Hopkins University, Baltimore, MD 21205, USA; Translational Neuroradiology Unit, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
  • Dewey B; Translational Neuroradiology Unit, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
  • Nair G; Translational Neuroradiology Unit, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
  • Sati P; Translational Neuroradiology Unit, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
  • Shea C; Translational Neuroradiology Unit, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
  • Reich DS; Department of Biostatistics, The Johns Hopkins University, Baltimore, MD 21205, USA; Translational Neuroradiology Unit, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
  • Shinohara RT; Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA. Electronic address: rshi@upenn.edu.
Neuroimage ; 133: 176-188, 2016 06.
Article en En | MEDLINE | ID: mdl-26732403
Quantitative T1 maps estimate T1 relaxation times and can be used to assess diffuse tissue abnormalities within normal-appearing tissue. T1 maps are popular for studying the progression and treatment of multiple sclerosis (MS). However, their inclusion in standard imaging protocols remains limited due to the additional scanning time and expert calibration required and susceptibility to bias and noise. Here, we propose a new method of estimating T1 maps using four conventional MR images, which are intensity-normalized using cerebellar gray matter as a reference tissue and related to T1 using a smooth regression model. Using cross-validation, we generate statistical T1 maps for 61 subjects with MS. The statistical maps are less noisy than the acquired maps and show similar reproducibility. Tests of group differences in normal-appearing white matter across MS subtypes give similar results using both methods.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Encéfalo / Interpretación de Imagen Asistida por Computador / Modelos Estadísticos / Imagen de Difusión Tensora / Sustancia Blanca / Esclerosis Múltiple Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Neuroimage Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2016 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Encéfalo / Interpretación de Imagen Asistida por Computador / Modelos Estadísticos / Imagen de Difusión Tensora / Sustancia Blanca / Esclerosis Múltiple Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Neuroimage Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2016 Tipo del documento: Article País de afiliación: Estados Unidos