- 著者
- Yoshitaka Masutani
- 出版者
- Japanese Society for Magnetic Resonance in Medicine
- 雑誌
- Magnetic Resonance in Medical Sciences (ISSN:13473182)
- 巻号頁・発行日
- pp.rev.2021-0005, (Released:2021-05-21)
- 参考文献数
- 92
- 被引用文献数
- 1
In this paper, fundamentals and recent progress for obtaining biological features quantitatively by using diffusion MRI are reviewed. First, a brief description of diffusion MRI history, application, and development was presented. Then, well-known parametric models including diffusion tensor imaging (DTI), diffusional kurtosis imaging (DKI), and neurite orientation dispersion diffusion imaging (NODDI) are introduced with several classifications in various viewpoints with other modeling schemes. In addition, this review covers mathematical generalization and examples of methodologies for the model parameter inference from conventional fitting to recent machine learning approaches, which is called Q-space learning (QSL). Finally, future perspectives on diffusion MRI parameter inference are discussed with the aspects of imaging modeling and simulation.
- 著者
- Masami Goto Osamu Abe Akifumi Hagiwara Shohei Fujita Koji Kamagata Masaaki Hori Shigeki Aoki Takahiro Osada Seiki Konishi Yoshitaka Masutani Hajime Sakamoto Yasuaki Sakano Shinsuke Kyogoku Hiroyuki Daida
- 出版者
- Japanese Society for Magnetic Resonance in Medicine
- 雑誌
- Magnetic Resonance in Medical Sciences (ISSN:13473182)
- 巻号頁・発行日
- pp.rev.2021-0096, (Released:2022-02-18)
- 参考文献数
- 106
- 被引用文献数
- 31
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).