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Yamashita K, Kuwashiro T, Ishikawa K, Furuya K, Harada S, Shin S, Wada N, Hirakawa C, Okada Y, Noguchi T. Identification of predictors for mini-mental state examination and revised Hasegawa's Dementia Scale scores using MR-based brain morphometry. Eur J Radiol Open 2021; 8:100359. [PMID: 34095357 PMCID: PMC8167144 DOI: 10.1016/j.ejro.2021.100359] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Accepted: 05/21/2021] [Indexed: 11/16/2022] Open
Abstract
Purpose The early detection of cognitive function decline is crucial to help manage or slow the progression of symptoms. The Mini-Mental State Examination (MMSE) and revised Hasegawa's Dementia Scale (HDS-R) are widely used in screening for cognitive impairment. The purpose of this study was to explore common predictors of the two different cognitive testing systems using MR-based brain morphometry. Materials and Methods This retrospective study included 200 subjects with clinical suspicion of cognitive impairment who underwent 3D T1-weighted MRI at our institution between February 2019 and August 2020. Variables related to the volume of deep gray matter and 70 cortical thicknesses were obtained from the MR images using voxel-based specific regional analysis system for Alzheimer's disease (VSRAD) and FreeSurfer software. The correlation between each variable including age and MMSE/HDS-R scores was evaluated using uni- and multi-variate logistic regression analyses. Results In univariate analysis, parameters include hippocampal volume and bilateral entorhinal cortex (ERC) thickness showed moderate correlation coefficients with both MMSE and HDS-R scores. Multivariate analysis demonstrated the right ERC thickness was the common parameter which significantly correlates with both MMSE and HDS-R scores (p < 0.05). Conclusion Right ERC thickness appears to offer a useful predictive biomarker for both MMSE and HDS-R scores.
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Key Words
- 3D, 3-dimensional
- AD, Alzheimer’s disease
- ApoE, apolipoprotein E
- Cerebral cortex
- ERC, entorhinal cortex
- GM, gray matter
- HDS-R, revised Hasegawa's Dementia Scale
- MMSE, Mini-Mental State Examination
- MPRAGE, magnetization-prepared rapid gradient-echo
- Magnetic resonance imaging
- Mini-Mental State examination
- VOI, voxel of interest
- VSRAD, Voxel-based specific regional analysis system for Alzheimer’s disease
- WM, white matter
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Affiliation(s)
- Koji Yamashita
- Department of Radiology, Clinical Research Institute, National Hospital Organization Kyushu Medical Center, 1-8-1 Jigyohama, Chuo-ku, Fukuoka, 810-0065, Japan
| | - Takahiro Kuwashiro
- Department of Cerebrovascular Medicine and Neurology, Clinical Research Institute, National Hospital Organization Kyushu Medical Center, 1-8-1 Jigyohama, Chuo-ku, Fukuoka, 810-0065, Japan
| | - Kensuke Ishikawa
- Department of Psychiatry, Clinical Research Institute, National Hospital Organization Kyushu Medical Center, 1-8-1 Jigyohama, Chuo-ku, Fukuoka, 810-0065, Japan
| | - Kiyomi Furuya
- Department of Radiology, Clinical Research Institute, National Hospital Organization Kyushu Medical Center, 1-8-1 Jigyohama, Chuo-ku, Fukuoka, 810-0065, Japan
| | - Shino Harada
- Department of Radiology, Clinical Research Institute, National Hospital Organization Kyushu Medical Center, 1-8-1 Jigyohama, Chuo-ku, Fukuoka, 810-0065, Japan
| | - Seitaro Shin
- Department of Radiology, Clinical Research Institute, National Hospital Organization Kyushu Medical Center, 1-8-1 Jigyohama, Chuo-ku, Fukuoka, 810-0065, Japan
| | - Noriaki Wada
- Department of Radiology, Clinical Research Institute, National Hospital Organization Kyushu Medical Center, 1-8-1 Jigyohama, Chuo-ku, Fukuoka, 810-0065, Japan
| | - Chika Hirakawa
- Department of Medical Technology, Division of Radiology, National Hospital Organization Kyushu Medical Center, 1-8-1 Jigyohama, Chuo-ku, Fukuoka, 810-0065, Japan
| | - Yasushi Okada
- Department of Cerebrovascular Medicine and Neurology, Clinical Research Institute, National Hospital Organization Kyushu Medical Center, 1-8-1 Jigyohama, Chuo-ku, Fukuoka, 810-0065, Japan
| | - Tomoyuki Noguchi
- Department of Radiology, Clinical Research Institute, National Hospital Organization Kyushu Medical Center, 1-8-1 Jigyohama, Chuo-ku, Fukuoka, 810-0065, Japan
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Younes L, Albert M, Miller MI; BIOCARD Research Team. Inferring changepoint times of medial temporal lobe morphometric change in preclinical Alzheimer's disease. Neuroimage Clin 2014; 5:178-87. [PMID: 25101236 DOI: 10.1016/j.nicl.2014.04.009] [Citation(s) in RCA: 75] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/07/2014] [Revised: 04/17/2014] [Accepted: 04/17/2014] [Indexed: 11/21/2022]
Abstract
This paper uses diffeomorphometry methods to quantify the order in which statistically significant morphometric change occurs in three medial temporal lobe regions, the amygdala, entorhinal cortex (ERC), and hippocampus among subjects with symptomatic and preclinical Alzheimer's disease (AD). Magnetic resonance imaging scans were examined in subjects who were cognitively normal at baseline, some of whom subsequently developed clinical symptoms of AD. The images were mapped to a common template, using shape-based diffeomorphometry. The multidimensional shape markers indexed through the temporal lobe structures were modeled using a changepoint model with explicit parameters, specifying the number of years preceding clinical symptom onset. Our model assumes that the atrophy rate of a considered brain structure increases years before detectable symptoms. The results demonstrate that the atrophy changepoint in the ERC occurs first, indicating significant change 8–10 years prior to onset, followed by the hippocampus, 2–4 years prior to onset, followed by the amygdala, 3 years prior to onset. The ERC is significant bilaterally, in both our local and global measures, with estimates of ERC surface area loss of 2.4% (left side) and 1.6% (right side) annually. The same changepoint model for ERC volume gives 3.0% and 2.7% on the left and right sides, respectively. Understanding the order in which changes in the brain occur during preclinical AD may assist in the design of intervention trials aimed at slowing the evolution of the disease. We use diffeomorphometry to quantify the order in which statistically significant morphometric change occurs in three medial temporal lobe regions, the amygdala, entorhinal cortex (ERC), and hippocampus among subjects with symptomatic and preclinical Alzheimer's disease (AD). We introduce a model on anatomical shape change in which changepoint is inferred, taking place some period of time before cognitive onset of AD. The analysis uses a dataset arising from the BIOCARD study, in which all subjects were cognitively normal at baseline, some of whom subsequently developed clinical symptoms of AD. The results demonstrate that the atrophy changepoint in the ERC occurs first, indicating significant change 8-10 years prior to onset, followed by hippocampus, 2-4 years prior to onset, followed by amygdala, 3 years prior to onset. The ERC is significant bilaterally, in both our local and global measures, with estimates of ERC surface area loss of 2.4% (left side) and 1.6% (right side) annually. Understanding the order in which changes in the brain occur during preclinical AD may assist in the design of intervention trials aimed at slowing the evolution of the disease.
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Key Words
- AD, Alzheimer's disease
- CDR, clinical dementia rating
- ERC, entorhinal cortex
- FWER, family-wise error rate
- GPB, Geriatric Psychiatry Branch
- MCI, mild cognitive impairment
- MMSE, mini-mental state exam
- NIA, National Institute on Aging
- NIH, Clinical Center of the National Institutes of Health
- NIMH, National Institute for Mental Health
- ROI-LDDMM, region-of-interest large deformation diffeomorphic metric mapping
- RSS, residual sum of squares
- SPGR, spoiled gradient echo
- diffeomorphometry, study of shape using a metric on the diffeomorphic connections between structures
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