解读 99mTc-巯基乙酰三甘氨酸利尿扫描的关键变量：预测模型的建立和验证。
Key variables for interpreting 99mTc-mercaptoacetyltriglycine diuretic scans: development and validation of a predictive model.
机构信息
Department of Biostatistics and Bioinformatics, Emory University School of Public Health, Atlanta, GA, USA.
出版信息
AJR Am J Roentgenol. 2011 Aug;197(2):325-33. doi: 10.2214/AJR.10.5909.
OBJECTIVE
The purpose of this study was to facilitate interpretation of (99m)Tc-mercaptoacetyltriglycine (MAG3) diuretic scans by identifying key interpretative variables and developing a predictive model for computer-assisted diagnosis.
MATERIALS AND METHODS
Ninety-seven studies were randomly selected from an archived database of MAG3 baseline and furosemide acquisitions and scan interpretations (obstruction, equivocal finding, or no obstruction) derived from a consensus of three experts. Sixty-one studies (120 kidneys) were randomly chosen to build a predictive model for diagnosing or excluding obstruction. The other 36 studies (71 kidneys) composed the validation group. The probability of normal drainage (no obstruction) at the baseline acquisition and the probability of no obstruction, equivocal finding, or obstruction after furosemide administration were determined by logistic regression analysis and proportional odds modeling of MAG3 renographic data.
RESULTS
The single most important baseline variable for excluding obstruction was the ratio of postvoid counts to maximum counts. Renal counts in the last minute of furosemide acquisition divided by the maximum baseline acquisition renal counts and time to half-maximum counts after furosemide administration in a pelvic region of interest were the critical variables for determining obstruction. The area under the receiver operating characteristic curve (AUC) for predicting normal drainage in the validation sample was 0.93 (standard error, 0.02); sensitivity, 85%; specificity, 93%. The AUC for the diagnosis of obstruction after furosemide administration was 0.84 (standard error, 0.06); sensitivity, 82%; specificity, 83%.
CONCLUSION
A predictive system has been developed that provides a promising computer-assisted diagnosis approach to the interpretation of MAG3 diuretic renal scans; this system has also identified the key variables required for scan interpretation.
目的
本研究旨在通过确定关键解释变量并开发预测模型以辅助计算机诊断，从而促进（99m）Tc-巯基乙酰三甘氨酸（MAG3）利尿扫描的解读。
材料和方法
从 MAG3 基线和速尿采集以及三位专家共识得出的扫描解读（梗阻、不确定发现或无梗阻）的存档数据库中随机选择了 97 项研究。随机选择了 61 项研究（120 个肾脏）来建立预测模型以诊断或排除梗阻。其余 36 项研究（71 个肾脏）组成验证组。通过逻辑回归分析和 MAG3 肾图数据的比例优势建模确定基线采集时正常引流（无梗阻）的概率以及速尿给药后无梗阻、不确定发现或梗阻的概率。
结果
排除梗阻的单一最重要的基线变量是排空后计数与最大计数之比。速尿采集最后 1 分钟的肾计数除以最大基线采集肾计数以及速尿给药后盆腔感兴趣区的半最大值时间是确定梗阻的关键变量。在验证样本中预测正常引流的受试者工作特征曲线（AUC）下面积为 0.93（标准误差，0.02）；敏感性为 85%；特异性为 93%。速尿给药后诊断梗阻的 AUC 为 0.84（标准误差，0.06）；敏感性为 82%；特异性为 83%。
结论
已经开发出一种预测系统，为 MAG3 利尿剂肾扫描的解读提供了一种有前途的计算机辅助诊断方法；该系统还确定了扫描解释所需的关键变量。
Zotero 插件