Automated Parkinson's Disease Dopamine Transporter Scan Analysis Fast Track

描述(由申请人提供)：我们假设对于一类多巴胺转运体SPECT试剂，可以开发一个自动化的软件处理包，它将客观地产生纹状体定量摄取值，用于评估帕金森病(PD)的诊断和进展。这一全自动化和客观的纹状体分析(OSA)包将能够评估SPECT神经受体成像研究的受试者，其灵敏度和特异度高于目前通过肉眼检查或手动图像处理方法所可能达到的水平。OSA将执行以下处理步骤(无需用户交互)：a)沿冠鼻线重新定位重建的脑体积，b)识别具有纹状体活动的轴向切片并对指定数量的切片求和，c)按照区域移动的既定规则将区域模板放置在左右尾状核、壳核和枕背景区，d)提取计数密度数据以确定区域纹状体V3“，如公式中所示：V3”=(区域纹状体计数密度-枕区计数密度)/(枕区计数密度)。所需的算法将被编码到一个软件包(OSA)中，并将OSA应用于多组患者和健康志愿者的结果与由训练有素的图像处理技术人员手动分析相同受试组获得的结果进行比较。 我们建议开发一个用于帕金森病患者突触前多巴胺能功能分析的全自动程序包，该程序包可以方便地用于临床环境中对神经受体SPECT脑图像进行高质量的定量成像评估。这种自动化分析将消除确定成像结果测量(疾病进展)的主观性，并允许临床成像中心参考标准数据集获得对患者的准确诊断和监测评估。

DESCRIPTION (provided by applicant): We hypothesize that for a class of dopamine transporter SPECT agents, an automated software processing package can be developed, which will objectively yield striatal quantitative uptake values for evaluating Parkinson's disease (PD) diagnosis and progression. This fully automated and Objective Striatal Analysis (OSA) package will be able to evaluate subjects referred for SPECT neuroreceptor imaging studies with a sensitivity and specificity higher than currently possible by visual inspection or manual image processing methods. OSA will carry out (with no user interaction required) the following processing steps: a) reorientation of the reconstructed brain volume along the cantho-meatal line, b) identification of axial slices with striatal activity and summation of specified number of slices, c) placement of regional template on left and right caudate and putamen and occipital background region following set rules for movement of regions, d) extraction of count density data for determination of regional striatal V3" as indicated in the equation: V3"= (regional striatal count density - occipital count density)/(occipital count density). The required algorithms will be coded into a software package (OSA), and the results of OSA applied to groups of patients and healthy volunteers will be compared to the results obtained by manually analyzing the same subject groups by a highly-trained image processing technologist. We propose to develop a completely automated package for analysis of presynaptic dopaminergic function in Parkinson's patients which can be easily used in a clinical setting for high quality quantitative imaging assessments of neuroreceptor SPECT brain images. This automated analysis will remove subjectivity in the determination of the imaging outcome measure (progression of disease), and permit a clinical imaging center to obtain accurate diagnostic and monitoring assessments of the patient with reference to a normative dataset.