Adjustment for the Age- and Gender-Related Metabolic Changes Improves the Differential Diagnosis of Parkinsonism.

IF 3.7 Q2 GENETICS & HEREDITY
Phenomics (Cham, Switzerland) Pub Date : 2022-10-25 eCollection Date: 2023-02-01 DOI:10.1007/s43657-022-00079-6
Jiaying Lu, Min Wang, Ping Wu, Igor Yakushev, Huiwei Zhang, Sibylle Ziegler, Jiehui Jiang, Stefan Förster, Jian Wang, Markus Schwaiger, Axel Rominger, Sung-Cheng Huang, Fengtao Liu, Chuantao Zuo, Kuangyu Shi
{"title":"Adjustment for the Age- and Gender-Related Metabolic Changes Improves the Differential Diagnosis of Parkinsonism.","authors":"Jiaying Lu, Min Wang, Ping Wu, Igor Yakushev, Huiwei Zhang, Sibylle Ziegler, Jiehui Jiang, Stefan Förster, Jian Wang, Markus Schwaiger, Axel Rominger, Sung-Cheng Huang, Fengtao Liu, Chuantao Zuo, Kuangyu Shi","doi":"10.1007/s43657-022-00079-6","DOIUrl":null,"url":null,"abstract":"<p><p>Age and gender are the important factors for brain metabolic declines in both normal aging and neurodegeneration, and the confounding effects may influence early and differential diagnosis of neurodegenerative diseases based on the [<sup>18</sup>F]fluorodeoxyglucose positron emission tomography ([<sup>18</sup>F]FDG PET). We aimed to explore the potential of the adjustment of age- and gender-related confounding factors on [<sup>18</sup>F]FDG PET images in differentiation of Parkinson's disease (PD), multiple system atrophy (MSA) and progressive supra-nuclear palsy (PSP). Eight hundred and seventy-seven clinically definitely diagnosed Parkinsonian patients from a benchmark Huashan Parkinsonian PET imaging database were included. An age- and gender-adjusted Z (AGAZ) score was established based on the gender-specific longitudinal metabolic changes on healthy subjects. AGAZ scores and standardized uptake value ratio (SUVR) values were quantified at regional-level and support vector machine-based error-correcting output codes method was applied for classification. Additional references of the classifications based on metabolic pattern scores were included. The feature-based AGAZ score showed the best performance in classification (accuracy for PD, MSA, PSP: 93.1%, 96.3%, 94.8%). In both genders, the AGAZ score consistently achieved the best efficiency, and the improvements compared to the conventional SUVR value for PD, MSA, and PSP mainly laid in specificity (Male: 5.7%; Female: 11.1%), sensitivity (Male: 7.2%; Female: 7.3%), and sensitivity (Male: 7.3%; Female: 17.2%). Female patients benefited more from the adjustment on [<sup>18</sup>F]FDG PET in MSA and PSP groups (absolute net reclassification index, <i>p</i> < 0.001). Collectively, the adjustment of age- and gender-related confounding factors may improve the differential diagnosis of Parkinsonism. Particularly, the diagnosis of female Parkinsonian population has the best improvement from this correction.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s43657-022-00079-6.</p>","PeriodicalId":74435,"journal":{"name":"Phenomics (Cham, Switzerland)","volume":"3 1","pages":"50-63"},"PeriodicalIF":3.7000,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883378/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Phenomics (Cham, Switzerland)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s43657-022-00079-6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/2/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0

Abstract

Age and gender are the important factors for brain metabolic declines in both normal aging and neurodegeneration, and the confounding effects may influence early and differential diagnosis of neurodegenerative diseases based on the [18F]fluorodeoxyglucose positron emission tomography ([18F]FDG PET). We aimed to explore the potential of the adjustment of age- and gender-related confounding factors on [18F]FDG PET images in differentiation of Parkinson's disease (PD), multiple system atrophy (MSA) and progressive supra-nuclear palsy (PSP). Eight hundred and seventy-seven clinically definitely diagnosed Parkinsonian patients from a benchmark Huashan Parkinsonian PET imaging database were included. An age- and gender-adjusted Z (AGAZ) score was established based on the gender-specific longitudinal metabolic changes on healthy subjects. AGAZ scores and standardized uptake value ratio (SUVR) values were quantified at regional-level and support vector machine-based error-correcting output codes method was applied for classification. Additional references of the classifications based on metabolic pattern scores were included. The feature-based AGAZ score showed the best performance in classification (accuracy for PD, MSA, PSP: 93.1%, 96.3%, 94.8%). In both genders, the AGAZ score consistently achieved the best efficiency, and the improvements compared to the conventional SUVR value for PD, MSA, and PSP mainly laid in specificity (Male: 5.7%; Female: 11.1%), sensitivity (Male: 7.2%; Female: 7.3%), and sensitivity (Male: 7.3%; Female: 17.2%). Female patients benefited more from the adjustment on [18F]FDG PET in MSA and PSP groups (absolute net reclassification index, p < 0.001). Collectively, the adjustment of age- and gender-related confounding factors may improve the differential diagnosis of Parkinsonism. Particularly, the diagnosis of female Parkinsonian population has the best improvement from this correction.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-022-00079-6.

调整与年龄和性别相关的代谢变化可改善帕金森病的鉴别诊断。
年龄和性别是正常衰老和神经退行性疾病脑代谢衰退的重要因素,其混杂效应可能会影响基于[18F]氟脱氧葡萄糖正电子发射断层扫描([18F]FDG PET)的神经退行性疾病的早期诊断和鉴别诊断。我们的目的是探讨调整年龄和性别相关混杂因素对[18F]FDG PET图像在帕金森病(PD)、多系统萎缩(MSA)和进行性核上麻痹(PSP)鉴别诊断中的潜在影响。研究对象包括华山帕金森病 PET 成像基准数据库中 87 名临床确诊的帕金森病患者。根据健康受试者的性别特异性纵向代谢变化建立了年龄和性别调整 Z(AGAZ)评分。AGAZ 分数和标准化摄取值比(SUVR)值在区域一级进行量化,并采用基于支持向量机的纠错输出编码方法进行分类。此外,还纳入了基于代谢模式评分的分类参考文献。基于特征的 AGAZ 评分显示出最佳的分类性能(PD、MSA、PSP 的准确率分别为 93.1%、96.3%、94.8%)。与传统的 SUVR 值相比,AGAZ 评分对 PD、MSA 和 PSP 的改善主要体现在特异性(男性:5.7%;女性:11.1%)、敏感性(男性:7.2%;女性:7.3%)和灵敏度(男性:7.3%;女性:17.2%)方面。在 MSA 和 PSP 组中,女性患者从[18F]FDG PET 的调整中获益更多(绝对净重新分类指数,p 补充信息:在线版本包含补充材料,可在 10.1007/s43657-022-00079-6上查阅。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信