Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Jalan Lagoon Selatan, 47500, Bandar Sunway, Selangor, Malaysia.
BMC Med Educ. 2022 Jul 30;22(1):587. doi: 10.1186/s12909-022-03545-x.
Literature review demonstrated a surprising lack of publications on digital e-learning pathology resources for senior medical undergraduates and interns. An interactive Digital Pathology Repository (iDPR) integrating two- and three-dimensional (2D, 3D) high-resolution anatomical pathology images with correlated digital histopathology was developed. The novel iDPR was rigorously evaluated using mixed methods to assess pathology knowledge gains (pre- and post-tests), quality impact analysis (questionnaire), user feedback (focus group discussions) and user visual behaviour (eye gaze tracking analysis of 2D/ 3D images).Exposure to iDPR appeared to improve user pathology knowledge, as observed by significantly increased test scores on topic-related quizzes (n = 69, p < 0.001). In addition, most users were highly satisfied with the key design elements of the iDPR tool. Focus group discussion revealed the iDPR was regarded as a relevant online learning resource, although some minor technical issues were also noted. Interestingly, visual behaviour trends indicated that specific diagnostic pathological lesions could be correctly identified faster in 3D images, when compared to 2D images.The iDPR offers promise and potential in pathology education for senior clinical students and interns, gauging from both qualitative and quantitative positive user feedback. With incorporation of image annotations and interactive functionality, and with further technology development, this would prove a useful tool for diagnostic pathology and telepathology. As images with added visual-spatial dimension can provide enhanced detail and aid more rapid diagnosis, future applications of the iDPR could include virtual reality or holographic images of anatomical pathology specimens.
文献回顾表明，针对高年级医学生和实习医生的数字电子学习病理学资源的出版物非常少。我们开发了一个集成了二维（2D）和三维（3D）高分辨率解剖病理学图像与相关数字组织病理学的交互式数字病理学存储库（iDPR）。使用混合方法对新颖的 iDPR 进行了严格评估，以评估病理学知识的获取（前后测试）、质量影响分析（问卷调查）、用户反馈（焦点小组讨论）和用户视觉行为（对 2D/3D 图像的眼动追踪分析）。接触 iDPR 似乎可以提高用户的病理学知识，因为与主题相关的测验分数明显提高（n=69，p<0.001）。此外，大多数用户对 iDPR 工具的关键设计元素非常满意。焦点小组讨论表明，尽管也注意到了一些小的技术问题，但 iDPR 被认为是一个相关的在线学习资源。有趣的是，视觉行为趋势表明，与 2D 图像相比，在 3D 图像中可以更快地正确识别特定的诊断性病理病变。从定性和定量的积极用户反馈来看，iDPR 为高年级临床学生和实习医生的病理学教育带来了希望和潜力。随着图像注释和交互功能的加入以及进一步的技术发展，这将成为诊断病理学和远程病理学的有用工具。由于具有附加视觉空间维度的图像可以提供更详细的信息并有助于更快地诊断，因此 iDPR 的未来应用可能包括解剖病理学标本的虚拟现实或全息图像。
