Diffusion tensor imaging of white matter in patients with prediabetes by trace‐based spatial statistics
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...
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Published in | Journal of magnetic resonance imaging Vol. 49; no. 4; pp. 1105 - 1112 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
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01.04.2019
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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. |
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AbstractList | BackgroundPrediabetes 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.PurposeTo investigate the changes in the microstructure of brain white matter in prediabetes patients using DTI and trace‐based spatial statistics (TBSS).Study TypeProspective.PopulationSixty subjects (30 patients with prediabetes and 30 healthy volunteers) were enrolled.Field Strength/Sequence3.0T/DTI‐MRI sequence with single‐shot echo‐planar imaging sequence (SE‐EPI).AssessmentDTI data were collected and analyzed using the TBSS method in the FMRIB software library.Statistical TestsDTI 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])ResultsCompared 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 ConclusionDTI as a noninvasive technique can assess early changes in the white matter microarchitecture of patients with prediabetes.Level of Evidence: 2Technical Efficacy: Stage 2J. Magn. Reson. Imaging 2019;49:1105–1112. 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. To investigate the changes in the microstructure of brain white matter in prediabetes patients using DTI and trace-based spatial statistics (TBSS). Prospective. Sixty subjects (30 patients with prediabetes and 30 healthy volunteers) were enrolled. 3.0T/DTI-MRI sequence with single-shot echo-planar imaging sequence (SE-EPI). DTI data were collected and analyzed using the TBSS method in the FMRIB software library. 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). DTI as a noninvasive technique can assess early changes in the white matter microarchitecture of patients with prediabetes. 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 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. 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.BACKGROUNDPrediabetes 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.To investigate the changes in the microstructure of brain white matter in prediabetes patients using DTI and trace-based spatial statistics (TBSS).PURPOSETo investigate the changes in the microstructure of brain white matter in prediabetes patients using DTI and trace-based spatial statistics (TBSS).Prospective.STUDY TYPEProspective.Sixty subjects (30 patients with prediabetes and 30 healthy volunteers) were enrolled.POPULATIONSixty subjects (30 patients with prediabetes and 30 healthy volunteers) were enrolled.3.0T/DTI-MRI sequence with single-shot echo-planar imaging sequence (SE-EPI).FIELD STRENGTH/SEQUENCE3.0T/DTI-MRI sequence with single-shot echo-planar imaging sequence (SE-EPI).DTI data were collected and analyzed using the TBSS method in the FMRIB software library.ASSESSMENTDTI data were collected and analyzed using the TBSS method in the FMRIB software library.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).STATISTICAL TESTSDTI 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).DTI as a noninvasive technique can assess early changes in the white matter microarchitecture of patients with prediabetes.DATA CONCLUSIONDTI as a noninvasive technique can assess early changes in the white matter microarchitecture of patients with prediabetes.2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1105-1112.LEVEL OF EVIDENCE2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1105-1112. |
Author | Zhang, ShuiHua Zhou, Quan Yang, Xiao‐ling Cai, Xiangyi Fang, Jin Li, Jie Liang, Minjie Tang, Yi |
Author_xml | – sequence: 1 givenname: Minjie surname: Liang fullname: Liang, Minjie organization: Jinan University – sequence: 2 givenname: Xiangyi surname: Cai fullname: Cai, Xiangyi organization: Jinan University – sequence: 3 givenname: Yi surname: Tang fullname: Tang, Yi organization: The Second Traditional Chinese Medicine Hospital of Guangdong Province – sequence: 4 givenname: Xiao‐ling surname: Yang fullname: Yang, Xiao‐ling organization: Jinan University – sequence: 5 givenname: Jin surname: Fang fullname: Fang, Jin organization: Jinan University – sequence: 6 givenname: Jie surname: Li fullname: Li, Jie organization: Affiliated hospital of Hangzhou Normal University – sequence: 7 givenname: ShuiHua surname: Zhang fullname: Zhang, ShuiHua organization: Jinan University – sequence: 8 givenname: Quan surname: Zhou fullname: Zhou, Quan email: tzq@jnu.edu.cn organization: Third Affiliated Hospital, Southern Medical University |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30302864$$D View this record in MEDLINE/PubMed |
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CitedBy_id | crossref_primary_10_1186_s11689_025_09592_x crossref_primary_10_1096_fj_202000085R crossref_primary_10_1177_02841851211056471 crossref_primary_10_1002_hbm_26235 crossref_primary_10_2147_JIR_S437156 crossref_primary_10_1016_j_neubiorev_2020_04_001 crossref_primary_10_1016_j_neuropharm_2021_108877 crossref_primary_10_1002_jnr_24830 crossref_primary_10_1016_j_diabres_2024_111731 crossref_primary_10_1111_dom_14958 crossref_primary_10_3389_fendo_2020_595962 crossref_primary_10_1016_j_cccb_2024_100369 crossref_primary_10_1038_s41398_022_02002_z crossref_primary_10_1016_j_ebiom_2022_104144 |
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Prediabetes is an intermediate state in which blood glucose is higher than normal but does not meet the diagnostic criteria for diabetes. Diffusion... Prediabetes is an intermediate state in which blood glucose is higher than normal but does not meet the diagnostic criteria for diabetes. Diffusion tensor... BackgroundPrediabetes is an intermediate state in which blood glucose is higher than normal but does not meet the diagnostic criteria for diabetes. Diffusion... |
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SubjectTerms | Anisotropy Anxiety Brain Cognitive ability Computer architecture Corpus callosum Correlation analysis Data processing Diabetes Diabetes mellitus Diagnostic systems Field strength Lesions Magnetic resonance imaging Mathematical analysis Medical imaging Mental depression Neuroimaging Patients Population (statistical) Population statistics Population studies Statistical analysis Statistical tests Substantia alba Tensors |
Title | Diffusion tensor imaging of white matter in patients with prediabetes by trace‐based spatial statistics |
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