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  • 标题:Automated gigapixel circumferential surface microscopy of the prostate
  • 本地全文:下载
  • 作者:Samuel Luethy ; David B. Tulman ; J. Quincy Brown
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2020
  • 卷号:10
  • 期号:1
  • 页码:1-14
  • DOI:10.1038/s41598-019-56939-1
  • 出版社:Springer Nature
  • 摘要:Abstract Positive surgical margins, or cancer cells found at the boundary of an excised tumor mass, are a significant problem in the management of many cancers resulting in worsened patient outcomes. The problem is exacerbated in organ sites such as the prostate, where unnecessarily wide local excisions can result in significant deterioration of post-operative quality of life due to collateral damage to neighboring structures. Yet, at the same time, incomplete tumor removal results in worsened prognosis and need for additional interventions. Here, we report the design and development of a rapid and completely automated system for intraoperative gigapixel ex vivo microscopy of the circumferential surgical prostate margin within intra-operative timeframes, called the Automated Prostate Positioning System (APPS). The APPS leverages the rotational geometry of the prostate and high speed structured illumination microscopy (SIM) to generate continuous gigapixel panoramas of the fresh intact prostate circumference, including areas of the prostate adjacent to the neurovascular bundles, the rectum, and the bladder wall. Our previous work using SIM and a manual prostate handling method demonstrated the promise of the imaging technique for accurate detection of positive surgical margins. Our work here advances the technology toward clinical adoption, by demonstrating 10% greater tissue surface coverage fraction, 1.6× faster imaging throughput, and reduced number of required operator steps, compared to our prior approach. The APPS may be operated by a single person in the operating room suite within intraoperative time limits, while simultaneously delivering nearly two orders of magnitude higher tissue surface coverage than destructive and labor-intensive frozen section analysis techniques.
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