我们的目标是确定教育游戏 SonoQz 是否可以提高卵巢肿瘤超声评估的诊断性能。SonoQz 移动应用程序是作为一种教育工具开发的，供医生根据卵巢肿瘤的静态图像进行超声评估。该游戏包含来自 324 个卵巢肿瘤的图像，并由超声专家在手术前进行检查。在训练阶段，参与者在 SonoQz 应用程序中评估至少 200 个案例，之前进行训练前测试，然后进行训练后测试。两个相等的测试（A 和 B），每个包含 20 个案例，用作训练前和训练后测试。一半的用户首先进行测试 A，然后进行 B，剩下的用户按照相反的顺序进行测试。用户被要求对肿瘤进行分类（1）根据国际卵巢肿瘤分析（IOTA）简单规则，（2）良性或恶性，以及（3）提出具体的组织学诊断。使用对训练前和训练后测试具有固定效应的 Logistic 混合模型以及对参与者和病例的交叉随机效应来确定测试分数、敏感性和特异性的任何改善。来自 19 个医疗中心的 58 名医生参与了研究。比较训练前和训练后测试，简单规则评估中正确分类案例的中位数从 72% 增加到 83%，p<0.001；将病变分类为良性或恶性肿瘤的比例为 86% 至 95%，p < 0.001；在做出具体诊断时，从 43% 到 63%，p < 0.001。当将肿瘤分类为良性或恶性时，在敏感性水平不变的情况下（98% vs. 97%，p = 0.157），特异性从 70% 增加到 89%，p < 0.001。我们的结果表明，教育游戏 SonoQz 是一种有效的工具，可以提高评估卵巢肿瘤的诊断性能，特别是通过减少假阳性的数量，同时保持高灵敏度。© 2024 作者。斯堪的纳维亚产科与妇科学报，约翰·威利 (John Wiley) 出版

Our objective was to determine whether the educational game SonoQz can improve diagnostic performance in ultrasound assessment of ovarian tumors.The SonoQz mobile application was developed as an educational tool for medical doctors to practice ultrasound assessment, based on still images of ovarian tumors. The game comprises images from 324 ovarian tumors, examined by an ultrasound expert prior to surgery. A training phase, where the participants assessed at least 200 cases in the SonoQz app, was preceded by a pretraining test, and followed by a posttraining test. Two equal tests (A and B), each consisting of 20 cases, were used as pre- and posttraining tests. Half the users took test A first, B second, and the remaining took the tests in the opposite order. Users were asked to classify the tumors (1) according to International Ovarian Tumor Analysis (IOTA) Simple Rules, (2) as benign or malignant, and (3) suggest a specific histological diagnosis. Logistic mixed models with fixed effects for pre- and posttraining tests, and crossed random effects for participants and cases, were used to determine any improvement in test scores, sensitivity, and specificity.Fifty-eight doctors from 19 medical centers participated. Comparing the pre- and posttraining test, the median of correctly classified cases, in Simple Rules assessment increased from 72% to 83%, p < 0.001; in classifying the lesion as benign or malignant tumors from 86% to 95%, p < 0.001; and in making a specific diagnosis from 43% to 63%, p < 0.001. When classifying tumors as benign or malignant, at an unchanged level of sensitivity (98% vs. 97%, p = 0.157), the specificity increased from 70% to 89%, p < 0.001.Our results indicate that the educational game SonoQz is an effective tool that may improve diagnostic performance in assessing ovarian tumors, specifically by reducing the number of false positives while maintaining high sensitivity.© 2024 The Author(s). Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).