Abstract

Facilitating accurate diagnosis and ensuring appropriate treatment of dementia subtypes, including Alzheimer's disease (AD), Parkinson's disease dementia (PDD), and Lewy body dementia (DLB), is clinically important. However, the differences in glucose metabolic distribution among these three dementia subtypes are minor, which can result in difficulties in diagnosis by visual assessment or traditional quantification methods. Here, we explored this issue using novel approaches, including brain network and abnormal hemispheric asymmetry analyses. We generated 18F-labeled fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) images from patients with AD, PDD, and DLB, and healthy control (HC) subjects (n = 22, 18, 22, and 22, respectively) from Huashan hospital, Shanghai, China. Brain network properties were measured and between-group differences evaluated using graph theory. We also calculated and explored asymmetry indices for the cerebral hemispheres in the four groups, to explore whether differences between the two hemispheres were characteristic of each group. Our study revealed significant differences in the network properties of the HC and AD groups (small-world coefficient, 1.36 vs. 1.28; clustering coefficient, 1.48 vs. 1.59; characteristic path length, 1.57 vs. 1.64). In addition, differing hub regions were identified in the different dementias. We also identified rightward asymmetry in the hemispheric brain networks of patients with AD and DLB, and leftward asymmetry in the hemispheric brain networks of patients with PDD, which were attributable to aberrant topological properties in the corresponding hemispheres.

Highlights

  • Dementia is progressive cognitive deterioration caused by brain injury or disease

  • This study employed the novel approach of combining brain network and asymmetry analyses to explore the marginal differences in glucose metabolic distributions in brains from patients with three dementia subtypes

  • We found that network alterations in the DLB group were broader than those in the Alzheimer’s disease (AD) and Parkinson’s disease dementia (PDD) group

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Summary

Introduction

Dementia is progressive cognitive deterioration caused by brain injury or disease. The technique, 18F-labeled fluorodeoxyglucose (18F-FDG) positron emission tomography (PET), which reveals glucose metabolic distribution across the whole brain, is the most commonly used, accurate and effective, gold-standard method for diagnosis of early-stage dementia. Based on quantitative analysis of FDG-PET scans, scholars have explored the clinically significant differences between healthy controls and patients with different dementia subtypes, including AD [3], PDD [4], and DLB [5]; differences in the glucose metabolic distributions underlying the various dementia subtypes in their early stages are usually slight, representing a challenge for clinicians in distinguishing among dementia subtypes by visual assessment or traditional quantification methods [4, 6, 7]. Novel methods are required to facilitate accurate diagnosis and ensure appropriate treatment for patients with dementia

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