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Updated: Oct 31, 2025

Using Retinal Imaging to Study Dementia
Published on: November 6, 2017
Voxel-based specific regional analysis system for Alzheimer's disease utility as a screening tool for unrecognized
Yoko Ueba1, Takaaki Murakami1, Taizo Yamamoto2
1Department of Diabetes, Endocrinology, and Nutrition, Kyoto University Hospital, Kyoto, Japan.
Aims/Introduction:
An efficient screening strategy for identification of cognitive dysfunction remains a clinical issue in the management of elderly adults with diabetes. A magnetic resonance imaging voxel-based specific regional analysis system for Alzheimer's disease (VSRAD) has been developed as an automated brain morphometry system that includes the hippocampus. We carried out a multicenter retrospective study to evaluate the utility of VSRAD for screening cognitive dysfunction in diabetes outpatient clinics.
Materials And Methods:
We enrolled patients with diabetes aged >65 years who underwent brain magnetic resonance imaging scans for the purpose of a medical checkup between November 2018 and May 2019. Patients who were already suspected or diagnosed with mild cognitive impairment and/or dementia as well as those with a history of cerebrovascular disease were excluded.
Results:
A total of 67 patients were enrolled. Five patients were diagnosed with mild cognitive impairment or dementia (clinical cognitive dysfunction). Patients with clinical cognitive dysfunction showed a significantly higher z-score in VSRAD analysis (2.57 ± 0.47 vs 1.15 ± 0.55, P < 0.01). The sensitivities and specificities for diagnosis of clinical cognitive dysfunction were 80 and 48% for the Mini-Mental State Examination, 100 and 89% for the z-score, and 100 and 90% for the combination of the Mini-Mental State Examination score and z-score, respectively.
Conclusions:
VSRAD analysis can distinguish patients with clinical cognitive dysfunction in the elderly with diabetes, and also shows reasonable sensitivity and specificity compared with the Mini-Mental State Examination alone. Thus, VSRAD analysis can be useful for early identification of clinical cognitive dysfunction in the elderly with diabetes.
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