1 Department of Radiology, Unit 1473, University of Texas M.D. Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030.
2 Department of Biostatistics, University of Texas M.D. Anderson Cancer Center, Houston, TX.
AJR Am J Roentgenol. 2018 Apr;210(4):W156-W163. doi: 10.2214/AJR.17.18428. Epub 2018 Feb 7.
The purpose of this study is to identify imaging and patient parameters that affect the diagnostic performance of delayed contrast-enhanced CT for distinguishing malignant from benign adrenal lesions larger than 1 cm in adult patients and to derive predictive models.
This retrospective study assessed 97 pathologically proven adrenal lesions that had undergone unenhanced, portal venous, and 15-minute delayed CT. Quantitatively, single-parameter evaluations of lesion attenuation (in Hounsfield units) and absolute percentage enhancement washout (APEW) and relative percentage enhancement washout (RPEW) were performed. In addition, descriptive CT features (lesion size, margin definition, heterogeneity vs homogeneity, fat, and calcification) and patients' demographic characteristics and medical history of malignancy were evaluated for association with lesion status using multiple logistic regression with stepwise model selection. Areas under the ROC curve (A) were determined for univariate and multivariate analyses. Leave-one-lesion-out cross-validation was applied to ascertain the predictive performance of single-parameter and multivariate evaluations.
The A values for unenhanced attenuation, portal venous attenuation, delayed attenuation, APEW, and RPEW were 0.835, 0.534, 0.847, 0.792, and 0.871, respectively. Multivariate analyses revealed that portal venous attenuation, delayed attenuation, and APEW were significant features, with an A of 0.923 when combined. The addition of the descriptive CT features increased the A to 0.938; patient age and a history of malignancy were additional significant factors, increasing the A to 0.956 and 0.972, respectively. The combined predictive classifier yielded 89% accuracy under cross-validation, compared with the best commonly applied single-parameter evaluation (77% for RPEW < 40%).
Multivariate imaging evaluation applied to delayed contrast-enhanced CT alone, with or without patient characteristics, improves diagnostic performance for characterizing adrenal lesions beyond those of single-parameter evaluations. Predictive formulas assessing the probabilities of lesion benignity or malignancy are provided.
本研究旨在确定影响成人患者大于 1cm 良恶性肾上腺病变的延迟对比增强 CT 诊断性能的影像学和患者参数，并建立预测模型。
本回顾性研究评估了 97 例经病理证实的肾上腺病变，这些病变均进行了未增强、门静脉期和 15 分钟延迟 CT 检查。定量评估病变衰减值（HU）、绝对增强洗脱百分比（APEW）和相对增强洗脱百分比（RPEW）。此外，还评估了描述性 CT 特征（病变大小、边界定义、异质性与均匀性、脂肪和钙化）以及患者的恶性肿瘤病史和人口统计学特征，使用逐步模型选择的多变量逻辑回归分析与病变状态的相关性。绘制受试者工作特征曲线（ROC）下面积（A），进行单变量和多变量分析。采用留一病变交叉验证法确定单变量和多变量评价的预测性能。
未增强衰减值、门静脉期衰减值、延迟衰减值、APEW 和 RPEW 的 AUC 值分别为 0.835、0.534、0.847、0.792 和 0.871。多变量分析显示门静脉期衰减值、延迟衰减值和 APEW 是重要特征，联合后 AUC 值为 0.923。增加描述性 CT 特征后，AUC 值增加到 0.938；患者年龄和恶性肿瘤病史是另外两个重要因素，分别将 AUC 值提高到 0.956 和 0.972。交叉验证下，联合预测分类器的准确率为 89%，优于最佳常用单参数评估（RPEW<40%时为 77%）。
单独应用延迟对比增强 CT 的多变量成像评估，无论是否结合患者特征，均能提高良恶性肾上腺病变的诊断性能，优于单参数评估。还提供了评估病变良恶性概率的预测公式。
