Minjie Liang1, Xiangyi Cai1, Yi Tang2, Xiao-Ling Yang1, Jin Fang1, Jie Li1,3, ShuiHua Zhang1, Quan Zhou1,4. 1. Medical Imaging Center, First Affiliated Hospital, Jinan University, Guangzhou, Guangdong, China. 2. Department of Medical technology, The Second Traditional Chinese Medicine Hospital of Guangdong Province, Guangzhou, Guangdong, China. 3. Medical Imaging Center, Affiliated hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China. 4. Medical Imaging Center, Third Affiliated Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Abstract
BACKGROUND: Prediabetes is an intermediate state in which blood glucose is higher than normal but does not meet the diagnostic criteria for diabetes. Diffusion tensor imaging (DTI) is an MRI method that can sensitively detect microscopic lesions in the white matter of the brain, but most previous DTI studies only focused on patients with diabetes, and little is known about prediabetes. PURPOSE: To investigate the changes in the microstructure of brain white matter in prediabetes patients using DTI and trace-based spatial statistics (TBSS). STUDY TYPE: Prospective. POPULATION: Sixty subjects (30 patients with prediabetes and 30 healthy volunteers) were enrolled. FIELD STRENGTH/SEQUENCE: 3.0T/DTI-MRI sequence with single-shot echo-planar imaging sequence (SE-EPI). ASSESSMENT: DTI data were collected and analyzed using the TBSS method in the FMRIB software library. STATISTICAL TESTS: DTI using a two-sample t-test. Pearson correlation analysis was performed on DTI values and neuropsychology scale results (mini-mental state examination [MMSE], Montreal cognitive assessment [MoCA], self-rating anxiety scale [SAS], and self-rating depression scale [SDS]) RESULTS: Compared with the control group, the fractional anisotropy (FA) values in the right part of the corpus callosum body (bCC) (P = 0.035), the right superior longitudinal fasciculus (SLF.R) (P = 0.047), and the left superior longitudinal fasciculus (SLF.L) in the prediabetic group were reduced (P = 0.040). DATA CONCLUSION: DTI as a noninvasive technique can assess early changes in the white matter microarchitecture of patients with prediabetes. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1105-1112.
BACKGROUND:Prediabetes is an intermediate state in which blood glucose is higher than normal but does not meet the diagnostic criteria for diabetes. Diffusion tensor imaging (DTI) is an MRI method that can sensitively detect microscopic lesions in the white matter of the brain, but most previous DTI studies only focused on patients with diabetes, and little is known about prediabetes. PURPOSE: To investigate the changes in the microstructure of brain white matter in prediabetespatients using DTI and trace-based spatial statistics (TBSS). STUDY TYPE: Prospective. POPULATION: Sixty subjects (30 patients with prediabetes and 30 healthy volunteers) were enrolled. FIELD STRENGTH/SEQUENCE: 3.0T/DTI-MRI sequence with single-shot echo-planar imaging sequence (SE-EPI). ASSESSMENT: DTI data were collected and analyzed using the TBSS method in the FMRIB software library. STATISTICAL TESTS: DTI using a two-sample t-test. Pearson correlation analysis was performed on DTI values and neuropsychology scale results (mini-mental state examination [MMSE], Montreal cognitive assessment [MoCA], self-rating anxiety scale [SAS], and self-rating depression scale [SDS]) RESULTS: Compared with the control group, the fractional anisotropy (FA) values in the right part of the corpus callosum body (bCC) (P = 0.035), the right superior longitudinal fasciculus (SLF.R) (P = 0.047), and the left superior longitudinal fasciculus (SLF.L) in the prediabetic group were reduced (P = 0.040). DATA CONCLUSION: DTI as a noninvasive technique can assess early changes in the white matter microarchitecture of patients with prediabetes. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1105-1112.
Authors: Sunny X Tang; Lindsay D Oliver; Katrin Hänsel; Pamela DeRosse; Majnu John; Ammar Khairullah; James M Gold; Robert W Buchanan; Aristotle Voineskos; Anil K Malhotra Journal: Transl Psychiatry Date: 2022-06-06 Impact factor: 7.989
Authors: Abigail E Salinero; Lisa S Robison; Olivia J Gannon; David Riccio; Febronia Mansour; Charly Abi-Ghanem; Kristen L Zuloaga Journal: FASEB J Date: 2020-09-16 Impact factor: 5.191