Kurz Alexander, Krahl Dieter, Kutzner Heinz, Barnhill Raymond, Perasole Antonio, Figueras Maria Teresa Fernandez, Ferrara Gerardo, Braun Stephan A, Starz Hans, Llamas-Velasco Mar, Utikal Jochen Sven, Fröhling Stefan, von Kalle Christof, Kather Jakob Nikolas, Schneider Lucas, Brinker Titus J
Digital Biomarkers for Oncology Group, National Center for Tumor Diseases (NCT), German Cancer Research Center (DKFZ), Heidelberg, Germany.
Dres. Krahl Dermatopathology, Heidelberg, Germany.
Eur J Cancer. 2023 Nov;193:113294. doi: 10.1016/j.ejca.2023.113294. Epub 2023 Aug 18.
Historically, cancer diagnoses have been made by pathologists using two-dimensional histological slides. However, with the advent of digital pathology and artificial intelligence, slides are being digitised, providing new opportunities to integrate their information. Since nature is 3-dimensional (3D), it seems intuitive to digitally reassemble the 3D structure for diagnosis.
To develop the first human-3D-melanoma-histology-model with full data and code availability. Further, to evaluate the 3D-simulation together with experienced pathologists in the field and discuss the implications of digital 3D-models for the future of digital pathology.
A malignant melanoma of the skin was digitised via 3 µm cuts by a slide scanner; an open-source software was then leveraged to construct the 3D model. A total of nine pathologists from four different countries with at least 10 years of experience in the histologic diagnosis of melanoma tested the model and discussed their experiences as well as implications for future pathology.
We successfully constructed and tested the first 3D-model of human melanoma. Based on testing, 88.9% of pathologists believe that the technology is likely to enter routine pathology within the next 10 years; advantages include a better reflectance of anatomy, 3D assessment of symmetry and the opportunity to simultaneously evaluate different tissue levels at the same time; limitations include the high consumption of tissue and a yet inferior resolution due to computational limitations.
3D-histology-models are promising for digital pathology of cancer and melanoma specifically, however, there are yet limitations which need to be carefully addressed.
历史上，癌症诊断一直由病理学家通过二维组织学切片进行。然而，随着数字病理学和人工智能的出现，切片正在被数字化，为整合其信息提供了新的机会。由于自然界是三维（3D）的，通过数字方式重新组装3D结构进行诊断似乎是直观的。
开发第一个具有完整数据和代码可用性的人类3D黑色素瘤组织学模型。此外，与该领域经验丰富的病理学家一起评估3D模拟，并讨论数字3D模型对数字病理学未来的影响。
通过载玻片扫描仪对皮肤恶性黑色素瘤进行3微米切片数字化；然后利用开源软件构建3D模型。来自四个不同国家的九名病理学家，在黑色素瘤组织学诊断方面至少有10年经验，对该模型进行了测试，并讨论了他们的经验以及对未来病理学的影响。
我们成功构建并测试了第一个人类黑色素瘤3D模型。基于测试，88.9%的病理学家认为该技术可能在未来10年内进入常规病理学领域；优点包括更好地反映解剖结构、对对称性进行3D评估以及有机会同时评估不同组织层面；局限性包括组织消耗量大以及由于计算限制分辨率仍然较低。
3D组织学模型对癌症尤其是黑色素瘤的数字病理学很有前景，然而，仍有一些局限性需要仔细解决。
