Diagnostic potential of automated subcortical volume segmentation in atypical parkinsonism
Diagnostic potential of automated subcortical volume segmentation in atypical parkinsonism
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DOI：
10.1212/wnl.0000000000002518
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发表时间：
2016-03-29
期刊：
影响因子：
9.9
通讯作者：
Seppi, Klaus
中科院分区：
文献类型：
--
作者：
Scherfler, Christoph;Goebel, Georg;Seppi, Klaus
目的：确定自动和观察者独立的体积MRI分析是否能够区分帕金森病（PD）、多系统萎缩（MSA）和进行性核上性麻痹（PSP）的早期至中晚期患者。方法：对临床可能患有PD （n = 40）、MSA （n = 40）和PSP （n = 30）的患者进行t1加权体积MRI检查，平均病程为2.8 +/- 1.7 y，使用22个皮质下区域的自动体积测量。临床随访期为2.5 +/- 1.2年。数据被分成训练集（n = 72）和测试集（n = 38）。利用训练集构建C4.5决策树模型，将患者分为MSA、PSP或PD。以最后随访的最终临床诊断为诊断金标准，通过测试集对分类算法进行检验。结果：中脑和壳层体积以及小脑灰质室是最重要的脑区，可以构建预测模型。PD与MSA或PSP的诊断准确率为97.4%。相比之下，在MRI采集时，基于有效的临床共识标准的诊断准确率为62.9%。结论：皮质下脑区体积分割可将PD与MSA和PSP区分开来，提高了早期至中晚期帕金森患者的诊断准确性。证据分类：本研究提供了III类证据，自动MRI分析可以准确区分早期PD、MSA和PSP。
Objective:To determine whether automated and observer-independent volumetric MRI analysis is able to discriminate among patients with Parkinson disease (PD), multiple system atrophy (MSA), and progressive supranuclear palsy (PSP) in early to moderately advanced stages of disease.Methods:T1-weighted volumetric MRI from patients with clinically probable PD (n = 40), MSA (n = 40), and PSP (n = 30) and a mean disease duration of 2.8 +/- 1.7 y were examined using automated volume measures of 22 subcortical regions. The clinical follow-up period was 2.5 +/- 1.2 years. The data were split into a training (n = 72) and a test set (n = 38). The training set was used to build a C4.5 decision tree model in order to classify patients as MSA, PSP, or PD. The classification algorithm was examined by the test set using the final clinical diagnosis at last follow-up as diagnostic gold standard.Results:The midbrain and putaminal volume as well as the cerebellar gray matter compartment were identified as the most significant brain regions to construct a prediction model. The diagnostic accuracy for PD vs MSA or PSP was 97.4%. In contrast, diagnostic accuracy based on validated clinical consensus criteria at the time of MRI acquisition was 62.9%.Conclusions:Volume segmentation of subcortical brain areas differentiates PD from MSA and PSP and improves diagnostic accuracy in patients presenting with early to moderately advanced stage parkinsonism.Classification of evidence:This study provides Class III evidence that automated MRI analysis accurately discriminates among early-stage PD, MSA, and PSP.