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Advantages of Using Both Voxel- and Surface-based Morphometry in Cortical Morphology Analysis: A Review of Various Applications.
Goto, Masami; Abe, Osamu; Hagiwara, Akifumi; Fujita, Shohei; Kamagata, Koji; Hori, Masaaki; Aoki, Shigeki; Osada, Takahiro; Konishi, Seiki; Masutani, Yoshitaka; Sakamoto, Hajime; Sakano, Yasuaki; Kyogoku, Shinsuke; Daida, Hiroyuki.
Afiliación
  • Goto M; Department of Radiological Technology, Faculty of Health Science, Juntendo University.
  • Abe O; Department of Radiology, Graduate School of Medicine, The University of Tokyo.
  • Hagiwara A; Department of Radiology, Juntendo University School of Medicine.
  • Fujita S; Department of Radiology, Graduate School of Medicine, The University of Tokyo.
  • Kamagata K; Department of Radiology, Juntendo University School of Medicine.
  • Hori M; Department of Radiology, Juntendo University School of Medicine.
  • Aoki S; Department of Radiology, Juntendo University School of Medicine.
  • Osada T; Department of Radiology, Toho University Omori Medical Center.
  • Konishi S; Department of Radiology, Juntendo University School of Medicine.
  • Masutani Y; Department of Neurophysiology, Juntendo University School of Medicine.
  • Sakamoto H; Department of Neurophysiology, Juntendo University School of Medicine.
  • Sakano Y; Graduate School of Information Sciences, Hiroshima City University.
  • Kyogoku S; Department of Radiological Technology, Faculty of Health Science, Juntendo University.
  • Daida H; Department of Radiological Technology, Faculty of Health Science, Juntendo University.
Magn Reson Med Sci ; 21(1): 41-57, 2022 Mar 01.
Article en En | MEDLINE | ID: mdl-35185061
Surface-based morphometry (SBM) is extremely useful for estimating the indices of cortical morphology, such as volume, thickness, area, and gyrification, whereas voxel-based morphometry (VBM) is a typical method of gray matter (GM) volumetry that includes cortex measurement. In cases where SBM is used to estimate cortical morphology, it remains controversial as to whether VBM should be used in addition to estimate GM volume. Therefore, this review has two main goals. First, we summarize the differences between the two methods regarding preprocessing, statistical analysis, and reliability. Second, we review studies that estimate cortical morphological changes using VBM and/or SBM and discuss whether using VBM in conjunction with SBM produces additional values. We found cases in which detection of morphological change in either VBM or SBM was superior, and others that showed equivalent performance between the two methods. Therefore, we concluded that using VBM and SBM together can help researchers and clinicians obtain a better understanding of normal neurobiological processes of the brain. Moreover, the use of both methods may improve the accuracy of the detection of morphological changes when comparing the data of patients and controls.In addition, we introduce two other recent methods as future directions for estimating cortical morphological changes: a multi-modal parcellation method using structural and functional images, and a synthetic segmentation method using multi-contrast images (such as T1- and proton density-weighted images).
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Imagen por Resonancia Magnética / Sustancia Gris Límite: Humans Idioma: En Revista: Magn Reson Med Sci Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2022 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Imagen por Resonancia Magnética / Sustancia Gris Límite: Humans Idioma: En Revista: Magn Reson Med Sci Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2022 Tipo del documento: Article