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蛋白SPECT试剂，可以开发自动化软件处理包，其将客观地产生纹状体定量摄取值，用于评价帕金森病（PD）诊断和进展。这种全自动和客观的纹状体分析（OSA）包将能够评估受试者转介SPECT神经受体成像研究的灵敏度和特异性高于目前可能通过目视检查或手动图像处理方法。OSA将执行（不需要用户交互）以下处理步骤：a）沿眦-耳道线沿着重新定向重建的脑体积，B）识别具有纹状体活动的轴向切片并将指定数目的切片相加，c）按照区域移动的设定规则将区域模板放置在左右尾状核和壳核以及枕骨背景区域上，d）提取计数密度数据，用于确定区域纹状体V3”，如公式中所示：V3”=（区域纹状体计数密度-枕部计数密度）/（枕部计数密度）。所需的算法将编码到软件包（OSA）中，并将应用于患者和健康志愿者组的OSA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者组获得的结果进行比较。 我们建议开发一个完全自动化的软件包，用于分析帕金森氏症患者的突触前多巴胺能功能，该软件包可以很容易地用于临床环境中，用于神经受体SPECT脑图像的高质量定量成像评估。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规范数据集获得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.