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Surrogate vascular input function measurements from the superior sagittal sinus are repeatable and provide tissue-validated kinetic parameters in brain DCE-MRI.
Lewis, Daniel; Zhu, Xiaoping; Coope, David J; Zhao, Sha; King, Andrew T; Cootes, Timothy; Jackson, Alan; Li, Ka-Loh.
Afiliación
  • Lewis D; Department of Neurosurgery, Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK. daniel.lewis-3@postgrad.manchester.ac.uk.
  • Zhu X; Geoffrey Jefferson Brain Research Centre, University of Manchester, Stott Lane, Salford, M6 8HD, Greater Manchester, UK. daniel.lewis-3@postgrad.manchester.ac.uk.
  • Coope DJ; Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, School of Biological Sciences, University of Manchester, Manchester, UK. daniel.lewis-3@postgrad.manchester.ac.uk.
  • Zhao S; Division of Informatics, Imaging and Data Sciences, Wolfson Molecular Imaging Centre (WMIC), University of Manchester, Manchester, UK.
  • King AT; Department of Neurosurgery, Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.
  • Cootes T; Geoffrey Jefferson Brain Research Centre, University of Manchester, Stott Lane, Salford, M6 8HD, Greater Manchester, UK.
  • Jackson A; Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, School of Biological Sciences, University of Manchester, Manchester, UK.
  • Li KL; Division of Informatics, Imaging and Data Sciences, Wolfson Molecular Imaging Centre (WMIC), University of Manchester, Manchester, UK.
Sci Rep ; 12(1): 8737, 2022 05 24.
Article en En | MEDLINE | ID: mdl-35610281
Accurate vascular input function (VIF) derivation is essential in brain dynamic contrast-enhanced (DCE) MRI. The optimum site for VIF estimation is, however, debated. This study sought to compare VIFs extracted from the internal carotid artery (ICA) and its branches with an arrival-corrected vascular output function (VOF) derived from the superior sagittal sinus (VOFSSS). DCE-MRI datasets from sixty-six patients with different brain tumours were retrospectively analysed and plasma gadolinium-based contrast agent (GBCA) concentration-time curves used to extract VOF/VIFs from the SSS, the ICA, and the middle cerebral artery. Semi-quantitative parameters across each first-pass VOF/VIF were compared and the relationship between these parameters and GBCA dose was evaluated. Through a test-retest study in 12 patients, the repeatability of each semiquantitative VOF/VIF parameter was evaluated; and through comparison with histopathological data the accuracy of kinetic parameter estimates derived using each VOF/VIF and the extended Tofts model was also assessed. VOFSSS provided a superior surrogate global input function compared to arteries, with greater contrast-to-noise (p < 0.001), higher peak (p < 0.001, repeated-measures ANOVA), and a greater sensitivity to interindividual plasma GBCA concentration. The repeatability of VOFSSS derived semi-quantitative parameters was good to excellent (ICC = 0.717-0.888) outperforming arterial based approaches. In contrast to arterial VIFs, kinetic parameters obtained using a SSS derived VOF permitted detection of intertumoural differences in both microvessel surface area and cell density within resected tissue specimens. These results support the usage of an arrival-corrected VOFSSS as a surrogate vascular input function for kinetic parameter mapping in brain DCE-MRI.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Imagen por Resonancia Magnética / Seno Sagital Superior Tipo de estudio: Observational_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Imagen por Resonancia Magnética / Seno Sagital Superior Tipo de estudio: Observational_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article
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