计算机辅助诊断系统对甲状腺结节的诊断价值研究

目的比较计算机辅助诊断（CAD）系统与多名超声医师对甲状腺结节的诊断效能,初步探讨CAD软件的诊断价值及分析甲状腺结节超声特征对CAD软件及超声医师诊断的影响。 方法选取2016年2月至2018年6月电子科技大学医学院附属四川省肿瘤医院医学影像信息（PACS）系统中甲状腺结节灰阶超声图像50张,采用CAD软件及111名超声医师同时对50张甲状腺结节图像进行诊断。以病理结果为"金标准"分别计算CAD软件,准确率最高的高年资医师、准确率最高的低年资医师鉴别诊断甲状腺结节的敏感度、特异度、阳性预测值、阴性预测值,并绘制受试者工作特征曲线（ROC曲线）;各组间准确率的比较采用McNemar检验,ROC曲线下面积的比较采用Z检验。 结果CAD软件、准确率最高的高年资医师、准确率最高的低年资医师诊断甲状腺结节良恶性的敏感度、特异度、阳性预测值、阴性预测值及准确性分别为76.9%、87.5%、86.9%、77.8%、82.0%;86.9%、77.8%、76.9%、87.5%、82.0%;82.6%、70.4%、70.4%、82.6%、76%;CAD软件与高年资医师诊断准确率相同且均高于低年资医师,差异有统计学意义;CAD软件与高年资医师ROC曲线下面积一致且均大于低年资医师,但差异均无统计学意义（P均>0.05）。医师误诊的病例主要为桥本甲状腺炎以及微小低回声病灶伴点状强回声的甲状腺结节,而分布位置以及结节内粗大钙化灶伴后方宽大声影造成了CAD软件的误诊。 结论CAD软件诊断甲状腺结节的准确率与高年资医师一致,高于低年资医师;甲状腺结节的分布位置以及结节内粗大钙化灶伴后方宽大声影可能是影响CAD软件诊断准确性的因素;而桥本甲状腺炎以及微小低回声病灶伴点状强回声可能会影响超声医师对甲状腺结节的正确诊断。

Performance of computer-aided diagnosis system versus radiologists in diagnosis of thyroid nodules

ObjectiveTo compare the diagnostic performance of computer-aided diagnosis (CAD) system versus 111 radiologists with different experiences (senior and junior radiologists) in identifying benign and malignant thyroid nodules. MethodsA total of 50 thyroid nodules and 111 radiologists were enrolled in this study. All the diagnostic results for the 50 nodules were estimated by radiologists and CAD system simultaneously. The diagnostic sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of senior and junior radiologists with maximum accuracy and CAD for differentiation between benign and malignant thyroid nodules were compared. The McNemar test was used to compare the accuracy between the two groups. Receiver operating characteristic curve (ROC) analysis was performed, and the Z test was used to compare the area under the ROC curve (AUC). ResultsThe sensitivity, specificity, PPV, NPV, and overall accuracy of CAD in differentiation between benign and malignant thyroid nodules were 76.9%, 87.5%, 86.9%, 77.8%, and 82.0%, respectively; the corresponding percentages were 86.9%, 77.8%, 76.9%, 87.5%, and 82.0% for the senior radiologist with maximum accuracy, and 82.6%, 70.4%, 70.4%, 82.6%, and 76% for the junior radiologist with maximum accuracy. In ROC curve analysis, the AUC values were 0.82, 0.82, and 0.76 for CAD, senior and junior radiologists with maximum accuracy, separately, and the CAD system achieved a diagnostic accuracy that was comparable to that of the senior radiologist but higher than that of the junior radiologist (P<0.05). Both CAD system and senior radiologist had a larger AUC in the differential diagnosis of thyroid nodules than the junior radiologist; however, the difference between CAD system and the senior radiologist was not statistically significant (0.82 vs 0.76, P=0.5). For radiologists, the nodules in Hashimoto's thyroiditis and small hypoechoic nodules with colloid inside the lesion tended to be misdiagnosed. For CAD system, the distribution of nodules and the presence of macrocalcification inside the lesion with wide acoustic shadow may also influence the analysis of the CAD system. ConclusionsIn thyroid nodule diagnosis, CAD system can achieve a diagnostic accuracy comparable to that of the senior radiologist with maximum accuracy, but higher than that of the junior radiologist with maximum accuracy. The distribution of thyroid nodules and the presence of macrocalcification inside the lesion may influence the performance the CAD system, while the nodules in Hashimoto's thyroiditis and small hypoechoic nodules with colloid inside the lesion are harder to distinguish for radiologists.