基于分子成像的脑糖代谢在多系统萎缩中的时空动态进展。

IF 7.6 1区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Xiaofeng Dou, Jing Wang, Daoyan Hu, Haotian Wang, Congcong Yu, Rui Zhou, Xiaohui Zhang, Qiong Yao, Mei Tian, Hong Zhang, Yan Zhong, Chentao Jin
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引用次数: 0

摘要

目的:多系统萎缩(Multiple system atrophy, MSA)是一种临床表现复杂的进行性神经退行性疾病,对其治疗及发病机制的认识至关重要。在这项研究中,我们旨在利用疾病进展模型(SuStaIn模型)来阐明MSA患者脑糖代谢的体内时空进展模式,并研究确定的进展相关亚型之间临床特征和多巴胺能功能的差异。方法:共192名参与者(117名MSA患者[70名MSA- p, 47名MSA- c]和75名健康对照)接受了[18F]FDG PET扫描,其中82名MSA患者另外接受了[18F]FP-CIT PET成像。[18F]建立了基于FDG pet的SuStaIn模型,利用横断面数据说明脑糖代谢的时空演化模式,并确定了不同的代谢亚型。代谢亚型和分期与运动功能(UPDRS-III)、认知功能(MMSE、MoCA)、自主神经症状和多巴胺转运蛋白(DAT)活性相关。结果:[18F]基于FDG pet的SuStaIn模型确定了两种强大的时空代谢进展亚型,其中亚型1富集于MSA-C(52.0%, 39/75),亚型2富集于MSA-P(78.8%, 26/33)。亚型1的特征是最初在小脑发生低代谢,随后进展到脑干、纹状体和皮层区域。亚型2表现为纹状体发病模式,依次向脑干、小脑和额叶进展。尽管病程相当,但亚型1患者表现出明显较差的认知能力(MMSE, FDR q = 0.013; MoCA, FDR q = 0.032)和降低的壳核前后DAT比率(FDR q)。结论:本研究首次使用[18F]FDG pet为基础的SuStaIn模型来阐明MSA的时空动态进展,并鉴定出新的代谢亚型。这些发现为MSA的生物学异质性提供了代谢证据,可能有助于患者的管理和机制的理解。临床试验号:不适用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Molecular imaging based spatiotemporal dynamics progression of brain glucose metabolism in multiple system atrophy.

Objective: Multiple system atrophy (MSA) is a progressive neurodegenerative disorder with complex clinical manifestations, which is essential for patient management and mechanistic understanding of MSA. In this study, we aimed to use disease progression modeling (SuStaIn model) to elucidate the in vivo spatiotemporal progression patterns of brain glucose metabolism in MSA patients, and investigate the differential profiles of clinical characteristics and dopaminergic function among the identified progression-related subtypes.

Methods: A total of 192 participants (117 MSA patients [70 MSA-P, 47 MSA-C] and 75 healthy controls) who underwent [18F]FDG PET scans, with 82 MSA patients additionally receiving [18F]FP-CIT PET imaging were retrospectively enrolled. [18F]FDG PET-based SuStaIn model was established to illustrate spatiotemporal evolutionary patterns of brain glucose metabolism using the cross-sectional data, and identified distinct metabolic subtypes. Metabolic subtypes and stages were correlated with motor function (UPDRS-III), cognitive function (MMSE, MoCA), autonomic symptoms, and dopamine transporter (DAT) activity.

Results: The [18F]FDG PET-based SuStaIn model identified two robust spatiotemporal metabolic progression subtypes, with Subtype 1 enriched in MSA-C (52.0%, 39/75) and Subtype 2 in MSA-P (78.8%, 26/33). Subtype 1 was characterized by initial hypometabolism in the cerebellum, sequentially progressing to brainstem, striatum, and cortical regions. Subtype 2 demostrated a striatal-onset pattern, progressing sequentially to the brainstem, cerebellum, and frontal lobe. Despite comparable disease duration, subtype 1 patients exhibited significantly poorer cognitive performance (MMSE, FDR q = 0.013; MoCA, FDR q = 0.032) and reduced anterior-to-posterior putamen DAT ratios (FDR q < 0.001) compared to subtype 2. Conversely, subtype 2 patients showed more obvious motor deficits (UPDRS-III, FDR q = 0.042). Significant correlations were observed between SuStaIn progression stages and clinical features across all patients, including UPDRS-III (r = 0.322, p = 0.001), MMSE (r = -0.263, p = 0.009), and MoCA scores (r = -0.292, p = 0.004). These results were confirmed in an independent validation cohort.

Conclusion: This study for the first time used [18F]FDG PET-based SuStaIn model to elucidate spatiotemporal dynamic progression of MSA, and identified novel metabolic subtypes. These findings provided metabolic evidence of the biological heterogeneity in MSA, which maybe helpful for patients managment and the understanding of mechanisms.

Clinical trial number: Not applicable.

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来源期刊
CiteScore
15.60
自引率
9.90%
发文量
392
审稿时长
3 months
期刊介绍: The European Journal of Nuclear Medicine and Molecular Imaging serves as a platform for the exchange of clinical and scientific information within nuclear medicine and related professions. It welcomes international submissions from professionals involved in the functional, metabolic, and molecular investigation of diseases. The journal's coverage spans physics, dosimetry, radiation biology, radiochemistry, and pharmacy, providing high-quality peer review by experts in the field. Known for highly cited and downloaded articles, it ensures global visibility for research work and is part of the EJNMMI journal family.
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