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Kato S, Kurokawa R, Suzuki F, Amemiya S, Shinozaki T, Takanezawa D, Kohashi R, Abe O. White and Gray Matter Abnormality in Burning Mouth Syndrome Evaluated with Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging. Magn Reson Med Sci 2024; 23:204-213. [PMID: 36990741 PMCID: PMC11024709 DOI: 10.2463/mrms.mp.2022-0099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 03/02/2023] [Indexed: 03/30/2023] Open
Abstract
PURPOSE Burning mouth syndrome (BMS) is defined by a burning sensation or pain in the tongue or other oral sites despite the presence of normal mucosa on inspection. Both psychiatric and neuroimaging investigations have examined BMS; however, there have been no analyses using the neurite orientation dispersion and density imaging (NODDI) model, which provides detailed information of intra- and extracellular microstructures. Therefore, we performed voxel-wise analyses using both NODDI and diffusion tensor imaging (DTI) models and compared the results to better comprehend the pathology of BMS. METHODS Fourteen patients with BMS and 11 age- and sex-matched healthy control subjects were prospectively scanned using a 3T-MRI machine using 2-shell diffusion imaging. Diffusion tensor metrics (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity [AD], and radial diffusivity [RD]) and neurite orientation and dispersion index metrics (intracellular volume fraction [ICVF], isotropic volume fraction [ISO], and orientation dispersion index [ODI]) were retrieved from diffusion MRI data. These data were analyzed using tract-based spatial statistics (TBSS) and gray matter-based spatial statistics (GBSS). RESULTS TBSS analysis showed that patients with BMS had significantly higher FA and ICVF and lower MD and RD than the healthy control subjects (family-wise error [FWE] corrected P < 0.05). Changes in ICVF, MD, and RD were observed in widespread white matter areas. Fairly small areas with different FA were included. GBSS analysis showed that patients with BMS had significantly higher ISO and lower MD and RD than the healthy control subjects (FWE-corrected P < 0.05), mainly limited to the amygdala. CONCLUSION The increased ICVF in the BMS group may represent myelination and/or astrocytic hypertrophy, and microstructural changes in the amygdala in GBSS analysis indicate the emotional-affective profile of BMS.
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Affiliation(s)
- Shimpei Kato
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Ryo Kurokawa
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, MI, USA
| | - Fumio Suzuki
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Shiori Amemiya
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Takahiro Shinozaki
- Department of Oral Diagnostic Sciences, Nihon University School of Dentistry, Tokyo, Japan
| | - Daiki Takanezawa
- Department of Oral Diagnostic Sciences, Nihon University School of Dentistry, Tokyo, Japan
| | - Ryutaro Kohashi
- Department of Oral and Maxillofacial Radiology, Nihon University School of Dentistry, Tokyo, Japan
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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Huang H, Ma X, Yue X, Kang S, Rao Y, Long W, Liang Y, Li Y, Chen Y, Lyu W, Wu J, Tan X, Qiu S. Cortical gray matter microstructural alterations in patients with type 2 diabetes mellitus. Brain Behav 2022; 12:e2746. [PMID: 36059152 PMCID: PMC9575596 DOI: 10.1002/brb3.2746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 08/02/2022] [Indexed: 11/08/2022] Open
Abstract
BACKGROUND AND PURPOSE Neurodegenerative processes are widespread in the brains of type 2 diabetes mellitus (T2DM) patients; gaps remain to exist in the current knowledge of the associated gray matter (GM) microstructural alterations. METHODS A cross-sectional study was conducted to investigate alterations in GM microarchitecture in T2DM patients by diffusion tensor imaging and neurite orientation dispersion and density imaging (NODDI). Seventy-eight T2DM patients and seventy-four age-, sex-, and education level-matched healthy controls (HCs) without cognitive impairment were recruited. Cortical macrostructure and GM microstructure were assessed by surface-based analysis and GM-based spatial statistics (GBSS), respectively. Machine learning models were trained to evaluate the diagnostic values of cortical intracellular volume fraction (ICVF) for the classification of T2DM versus HCs. RESULTS There were no differences in cortical thickness or area between the groups. GBSS analysis revealed similar GM microstructural patterns of significantly decreased fractional anisotropy, increased mean diffusivity and radial diffusivity in T2DM patients involving the frontal and parietal lobes, and significantly lower ICVF values were observed in nearly all brain regions of T2DM patients. A support vector machine model with a linear kernel was trained to realize the T2DM versus HC classification and exhibited the highest performance among the trained models, achieving an accuracy of 74% and an area under the curve of 83%. CONCLUSIONS NODDI may help to probe the widespread GM neuritic density loss in T2DM patients occurs before measurable macrostructural alterations. The cortical ICVF values may provide valuable diagnostic information regarding the early GM microstructural alterations in T2DM.
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Affiliation(s)
- Haoming Huang
- The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China.,Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Xiaomeng Ma
- The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China.,Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Xiaomei Yue
- The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China.,Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Shangyu Kang
- The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China.,Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Yawen Rao
- The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China.,Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Wenjie Long
- Department of Geriatrics, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Yi Liang
- Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Yifan Li
- The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China.,Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Yuna Chen
- The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China.,Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Wenjiao Lyu
- The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China.,Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Jinjian Wu
- The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China.,Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Xin Tan
- Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Shijun Qiu
- Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
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Andica C, Kamagata K, Hatano T, Saito A, Uchida W, Ogawa T, Takeshige-Amano H, Zalesky A, Wada A, Suzuki M, Hagiwara A, Irie R, Hori M, Kumamaru KK, Oyama G, Shimo Y, Umemura A, Pantelis C, Hattori N, Aoki S. Free-Water Imaging in White and Gray Matter in Parkinson's Disease. Cells 2019; 8:cells8080839. [PMID: 31387313 PMCID: PMC6721691 DOI: 10.3390/cells8080839] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Revised: 07/29/2019] [Accepted: 08/03/2019] [Indexed: 11/16/2022] Open
Abstract
This study aimed to discriminate between neuroinflammation and neuronal degeneration in the white matter (WM) and gray matter (GM) of patients with Parkinson’s disease (PD) using free-water (FW) imaging. Analysis using tract-based spatial statistics (TBSS) of 20 patients with PD and 20 healthy individuals revealed changes in FW imaging indices (i.e., reduced FW-corrected fractional anisotropy (FAT), increased FW-corrected mean, axial, and radial diffusivities (MDT, ADT, and RDT, respectively) and fractional volume of FW (FW) in somewhat more specific WM areas compared with the changes of DTI indices. The region-of-interest (ROI) analysis further supported these findings, whereby those with PD showed significantly lower FAT and higher MDT, ADT, and RDT (indices of neuronal degeneration) in anterior WM areas as well as higher FW (index of neuroinflammation) in posterior WM areas compared with the controls. Results of GM-based spatial statistics (GBSS) analysis revealed that patients with PD had significantly higher MDT, ADT, and FW than the controls, whereas ROI analysis showed significantly increased MDT and FW and a trend toward increased ADT in GM areas, corresponding to Braak stage IV. These findings support the hypothesis that neuroinflammation precedes neuronal degeneration in PD, whereas WM microstructural alterations precede changes in GM.
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Affiliation(s)
- Christina Andica
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan
| | - Koji Kamagata
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan.
| | - Taku Hatano
- Department of Neurology, Juntendo University School of Medicine, Tokyo 113-8421, Japan
| | - Asami Saito
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan
| | - Wataru Uchida
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan
- Department of Radiological Sciences, Tokyo Metropolitan University, Graduate School of Human Health Sciences, Tokyo 116-8551, Japan
| | - Takashi Ogawa
- Department of Neurology, Juntendo University School of Medicine, Tokyo 113-8421, Japan
| | | | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Parkville, VIC 3053, Australia
- Melbourne School of Engineering, The University of Melbourne, VIC 3010, Australia
| | - Akihiko Wada
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan
| | - Michimasa Suzuki
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan
| | - Ryusuke Irie
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan
- Department of Radiology, The University of Tokyo Graduate School of Medicine, Tokyo 113-0033, Japan
| | - Masaaki Hori
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan
- Department of Radiology, Toho University Omori Medical Center, Tokyo 143-8541, Japan
| | - Kanako K Kumamaru
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan
| | - Genko Oyama
- Department of Neurology, Juntendo University School of Medicine, Tokyo 113-8421, Japan
| | - Yashushi Shimo
- Department of Neurology, Juntendo University School of Medicine, Tokyo 113-8421, Japan
| | - Atsushi Umemura
- Department of Neurosurgery, Juntendo University School of Medicine, Tokyo 113-8421, Japan
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Parkville, VIC 3053, Australia
- Melbourne School of Engineering, The University of Melbourne, VIC 3010, Australia
- Florey Institute for Neuroscience and Mental Health, Parkville, VIC 3052, Australia
| | - Nobutaka Hattori
- Department of Neurology, Juntendo University School of Medicine, Tokyo 113-8421, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan
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