Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Institute of Pathology, Technical University of Munich, Munich, Germany.
J Am Med Inform Assoc. 2021 Aug 13;28(9):1874-1884. doi: 10.1093/jamia/ocab085.
Broad adoption of digital pathology (DP) is still lacking, and examples for DP connecting diagnostic, research, and educational use cases are missing. We blueprint a holistic DP solution at a large academic medical center ubiquitously integrated into clinical workflows; researchapplications including molecular, genetic, and tissue databases; and educational processes.
We built a vendor-agnostic, integrated viewer for reviewing, annotating, sharing, and quality assurance of digital slides in a clinical or research context. It is the first homegrown viewer cleared by New York State provisional approval in 2020 for primary diagnosis and remote sign-out during the COVID-19 (coronavirus disease 2019) pandemic. We further introduce an interconnected Honest Broker for BioInformatics Technology (HoBBIT) to systematically compile and share large-scale DP research datasets including anonymized images, redacted pathology reports, and clinical data of patients with consent.
The solution has been operationally used over 3 years by 926 pathologists and researchers evaluating 288 903 digital slides. A total of 51% of these were reviewed within 1 month after scanning. Seamless integration of the viewer into 4 hospital systems clearly increases the adoption of DP. HoBBIT directly impacts the translation of knowledge in pathology into effective new health measures, including artificial intelligence-driven detection models for prostate cancer, basal cell carcinoma, and breast cancer metastases, developed and validated on thousands of cases.
We highlight major challenges and lessons learned when going digital to provide orientation for other pathologists. Building interconnected solutions will not only increase adoption of DP, but also facilitate next-generation computational pathology at scale for enhanced cancer research.
数字病理学（DP）的广泛采用仍然缺乏，缺乏将 DP 连接诊断、研究和教育用例的示例。我们在大型学术医疗中心蓝图规划了一个整体的 DP 解决方案，该方案普遍集成到临床工作流程中；研究应用包括分子、遗传和组织数据库；以及教育过程。
我们构建了一个与供应商无关的集成查看器，用于在临床或研究环境中查看、注释、共享和质量保证数字幻灯片。它是 2020 年纽约州临时批准的第一个国产查看器，用于在 COVID-19（2019 年冠状病毒病）大流行期间进行主要诊断和远程签名。我们进一步引入了一个互联的生物信息学技术诚实经纪人（HoBBIT），以系统地编译和共享包括匿名图像、编辑后的病理报告和同意患者的临床数据在内的大规模 DP 研究数据集。
该解决方案已在 3 年内由 926 名病理学家和研究人员操作使用，评估了 288903 个数字幻灯片。其中 51%的幻灯片在扫描后 1 个月内进行了审查。查看器无缝集成到 4 个医院系统中，明显提高了 DP 的采用率。HoBBIT 直接将病理学知识转化为有效的新健康措施，包括基于人工智能的前列腺癌、基底细胞癌和乳腺癌转移的检测模型，这些模型在数千个病例中得到了开发和验证。
我们强调了数字化过程中的主要挑战和经验教训，为其他病理学家提供指导。构建互联解决方案不仅将增加 DP 的采用率，还将促进下一代计算病理学的规模化应用，以增强癌症研究。
