Quantification of Parkinson's disease-related network expression with ECD SPECT
Quantification of Parkinson's disease-related network expression with ECD SPECT
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DOI：
10.1007/s00259-006-0261-9
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发表时间：
2007-04-01
影响因子：
9.1
通讯作者：
Eidelberg, David
中科院分区：
文献类型：
--
作者：
Eckert, Thomas;Van Laere, Koen;Eidelberg, David
目的应用空间协方差分析结合FDG PET研究帕金森病（PD）的代谢网络。在目前的研究中，我们利用一种新的，完全自动化的基于体素的方法来量化网络表达的ECD SPECT图像从患者与经典PD，患者与多系统萎缩（MSA），和健康对照subjects.Methods我们应用了一个先前验证的基于体素的PD相关的协方差模式（PDRP），以量化网络表达的ECD SPECT扫描的35例PD患者，15名年龄和疾病严重程度匹配的MSA患者和35名年龄匹配的健康对照受试者。使用方差分析比较各组的PDRP评分。结果PD组PDRP评分明显高于MSA组和对照组（P < 0.001），而MSA组和对照组PDRP评分明显高于MSA组和对照组（P < 0.001）。ROC分析表明，PDRP测量的总体诊断准确性为0.91（AUC）。最佳的截止值是一致的灵敏度为0.97和特异性为0.80和0.71区分PD患者从MSA和正常controls.Conclusion我们的研究结果表明，完全自动化的基于体素的网络评估技术，可用于量化网络表达的ECD SPECT扫描帕金森病患者。
Purpose Spatial covariance analysis has been used with FDG PET to identify a specific metabolic network associated with Parkinson's disease (PD). In the current study, we utilized a new, fully automated voxel-based method to quantify network expression in ECD SPECT images from patients with classical PD, patients with multiple system atrophy (MSA), and healthy control subjects.Methods We applied a previously validated voxel-based PD-related covariance pattern (PDRP) to quantify network expression in the ECD SPECT scans of 35 PD patients, 15 age- and disease severity-matched MSA patients, and 35 age-matched healthy control subjects. PDRP scores were compared across groups using analysis of variance. The sensitivity and specificity of the prospectively computed PDRP scores in the differential diagnosis of individual subjects were assessed by receiver operating characteristic (ROC) analysis.Results PDRP scores were significantly increased (p < 0.001) in the PD group relative to the MSA and control groups. ROC analysis indicated that the overall diagnostic accuracy of the PDRP measures was 0.91 (AUC). The optimal cutoff value was consistent with a sensitivity of 0.97 and a specificity of 0.80 and 0.71 for discriminating PD patients from MSA and normal controls, respectively.Conclusion Our findings suggest that fully automated voxel-based network assessment techniques can be used to quantify network expression in the ECD SPECT scans of parkinsonian patients.