1234 - fp - cit SPECT图像在帕金森综合征诊断中的视觉和半定量分析观察者间的一致性

M. Suárez-Piñera , M.L. Prat , A. Mestre-Fusco , J. Fuertes , S. Mojal , E. Balaguer
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引用次数: 0

摘要

目的利用123I-FP-CIT SPECT图像,通过研究多巴胺转运体(DAT)来识别突触前多巴胺能通路的退化。SPECT图像的正确分析有助于运动障碍的充分解释和诊断。目的:1。比较运动障碍患者123I-FP-CIT SPECT图像的视觉和半定量分析。2. 评估观察者之间在视觉和半定量分析中的一致性。3.方法对32例提示原发性帕金森综合征(PS)的运动障碍患者行123I-FP-CIT SPECT检查,由2名核医学医师独立进行视觉和半定量图像分析。目视分析以目视解释为基础。半定量分析计算为特异性摄取(尾状核、壳核和纹状体)与非特异性摄取(枕状)。计算敏感性、特异性、PPV和NPV。数据比较采用方差分析和Bonferroni事后检验。分别用类内相关系数和Kappa统计量评估视觉和半定量分析的观察者间一致性。采用半定量数据生成ROC曲线。结果视觉分析显示,原发性PS与非原发性PS鉴别诊断的敏感性为86%,特异性为100-88%。半定量分析显示,视觉分析得出的疾病严重程度逐渐降低。半定量分析没有提供任何额外的信息,以视觉分析。类内相关系数和Kappa统计量分别为0.92和0.80。壳核指数区分原发性PS与非原发性PS的临界值为1.9。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interobserver agreement in the visual and semi-quantitative analysis of the 123I-FP-CIT SPECT images in the diagnosis of Parkinsonian syndrome

Aims

Using 123I-FP-CIT SPECT images makes it possible to identify presynaptic deterioration of the dopaminergic pathway by studying the dopamine transporter (DAT). A correct analysis of the SPECT images contributes to an adequate interpretation and diagnosis of movement disorders. Aims: 1. To compare visual and semiquantitative analysis of 123I-FP-CIT SPECT images in patients with movement disorders. 2. To evaluate interobserver agreement in visual and semiquantitative analysis. 3. To obtain a cut-off in the semiquantitative analysis to discriminate primary Parkinsonism Syndrome (PS) from non-primary PS.

Methods

A 123I-FP-CIT SPECT was performed in 32 patients with movement disorders suggestive of primary PS. Visual and semiquantitative images analyses were performed independently by two nuclear medicine physicians. Visual analysis was based on the visual interpretation. Semiquantitative analysis was calculated as specific uptake (caudate, putamen and striatum) versus non-specific uptake (occipital). Sensitivity, specificity, PPV, and NPV were calculated. Data were compared using ANOVA test followed by Bonferroni post hoc test. Interobserver agreement of the visual and semiquantitative analysis was assessed by intraclass correlation coefficient and Kappa statistics, respectively. ROC curve was generated with semiquantitative data.

Results

Visual analysis showed 86% sensitivity and 100–88% specificity for the differential diagnosis of primary PS from non-primary PS. Semiquantitative analysis showed a gradual hypouptake proportional to the disease severity obtained in the visual analysis. Semiquantitative analysis did not provide any additional information to the visual analysis. Intraclass correlation coefficient and Kappa statistics showed 0.92 and 0.80 values, respectively. The cut-off value to differentiate primary PS from non-primary PS was 1.9 on the putamen index.

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