Lam Hansen, Kwan Ricky, Tuthill Mark, Haghighi Mehrvash
Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Department of Pathology, Henry Ford Health System, Detroit, MI, USA.
J Pathol Inform. 2020 Oct 5;11:31. doi: 10.4103/jpi.jpi_42_20. eCollection 2020.
Gross imaging of surgical specimens is paramount for the accurate gross examination and diagnosis of disease. Optimized imaging workflow can facilitate consistently high-quality gross photographs, especially in high-volume, metropolitan hospitals such as ours. Most commercial medical gross imaging technology provides ergonomically well-designed hardware, remotely operated cameras, intuitive software interfaces, and automation of workflow. However, these solutions are usually cost-prohibitive and require a large sum of capital budget.
We applied lean techniques such as value stream mapping (VSM) to design a streamlined and error-free workflow for gross imaging process. We implemented a cost-effective technology, UniTwain, combined with high-resolution webcam to achieve the ideal results.
We reduced the mean process time from 600 min to 4.0 min (99.3% decrease in duration); the median process time was reduced from 580 min to 3.0 min. The process efficiency increased from 20% to 100%. The implemented solution has a comparable durability, scalability, and archiving feasibility to commercial medical imaging systems and costs four times less. The only limitations are manual operation of the webcam and lower resolution. The webcam sensors have 8.2 megapixel (MP) resolution, approximately 12 MP less than medical imaging devices. However, we believe that this difference is not visually significant and the effect on gross diagnosis with the naked eye is minimal.
To our knowledge, this is the first study that utilized UniTwain as a viable, low-cost solution to streamline the gross imaging workflow. The UniTwain combined with high-resolution webcam could be a suitable alternative for our institution that does not plan to heavily invest in medical imaging.
手术标本的大体成像对于疾病的准确大体检查和诊断至关重要。优化的成像工作流程有助于持续获得高质量的大体照片,尤其是在像我们这样的高流量大城市医院。大多数商业医学大体成像技术提供了符合人体工程学设计的硬件、遥控相机、直观的软件界面以及工作流程自动化。然而,这些解决方案通常成本过高,需要大量的资本预算。
我们应用了诸如价值流映射(VSM)等精益技术来设计一个简化且无差错的大体成像流程工作流。我们采用了一种经济高效的技术——UniTwain,并结合高分辨率网络摄像头以实现理想效果。
我们将平均流程时间从600分钟缩短至4.0分钟(时长减少了99.3%);中位数流程时间从580分钟降至3.0分钟。流程效率从20%提高到了100%。所实施的解决方案在耐用性、可扩展性和存档可行性方面与商业医学成像系统相当,成本却低四倍。唯一的局限是网络摄像头的手动操作以及较低的分辨率。网络摄像头传感器具有820万像素(MP)分辨率,比医学成像设备少约1200万像素。然而,我们认为这种差异在视觉上并不显著,对肉眼大体诊断的影响微乎其微。
据我们所知,这是第一项将UniTwain作为一种可行的低成本解决方案来简化大体成像工作流程的研究。UniTwain与高分辨率网络摄像头相结合,对于我们不打算在医学成像方面进行大量投资的机构而言可能是一个合适的替代方案。