High speed automated intraoperative microscopy of the prostate circumference to ensure tumor-free margins in radical prostatectomy

项目摘要：在前列腺癌(PCa)中，肿瘤表面残留肿瘤的存在和数量 与其他因素相比，切除的前列腺是唯一受手术技术影响的预后因素，这些因素包括 固定且不可修改。然而，阳性手术切缘(PSM)，定义为肿瘤细胞存在于 去除标本表面的油墨，是常见的，特别是在晚期癌症中，并且是一种强烈的 临床进展和二次治疗的独立危险因素。此外，术后抬高 PSA被认为与遗留在患者体内的肿瘤有关，也与高风险 进展和二次治疗。因此，彻底切除肿瘤是重要的，以实现改善 患者预后和减少过度治疗，但在根治性和根治性之间存在微妙的平衡 最大限度地减少对神经血管束的损伤，以保护术后功能。NeuroSAFE试验 演示了通过全面的前列腺组织学实时检测和纠正PSMS 周长可以改善患者的预后，但目前还没有广泛采用的方法来实现这一点。 为了解决这一技术差距，我们开发了视频率结构照明显微镜。 (VR-SIM)，并证明它能够在活组织检查环境中准确诊断PCA，并且它可以 快速提供整个前列腺表面的十亿像素显微图像，以检测PSM。VR-SIM交付 探测PSM所需的表面积覆盖和分辨率，但它也是快速和相对简单的 价格低廉，为广泛采用提供了可能性。在这个项目中，我们的跨学科团队 拥有丰富前列腺专业知识的工程师和临床医生将进一步推动这项技术走向临床 翻译，通过完成关键的技术开发步骤并前瞻性地在大范围内进行验证 病人系列。具体地说，我们将提高设备的机械自动化速度，并将开发一种 用于处理摘除的前列腺的全自动系统，使千兆像素全景能够 切除后10分钟内交付前列腺周面，并进行最小的组织处理 和用户干预。然后我们将利用我们最近开发的复制的双色荧光染料 具有高度特异性的标准H&E，使用活组织检查和 身体标本以增强VR-SIM前列腺全景图的图像解释。这些改进将 结合在一项250名患者的前瞻性临床研究中测试该系统，以确定 一种术中PSM检测及术后PSA预测装置 PSM范围。最后，我们将使用一种新的支持Web的可视化工具来测量专家审阅者的行为并对其进行建模 观察者跟踪方法，可以在未来的计算机辅助搜索算法中使用，以加快 术中影像回顾。成功完成将为多中心临床试验奠定基础，以验证 VR-SIM在实时检测和纠正PSM以及改善患者预后方面的临床应用。

Project Summary: In prostate cancer (PCa), the presence and amount of residual tumor at the surface of the excised prostate is the only prognostic factor that is affected by surgical technique, vs. other factors, which are fixed and non-modifiable. Yet, positive surgical margins (PSM), defined as the presence of tumor cells at the inked surface of the removed specimen, are common, especially in advanced stage cancers, and are a strong independent risk factor for clinical progression and secondary treatment. In addition, elevated post-operative PSA, which is understood to be related to tumor left behind in the patient, is also associated with high risk of progression and secondary treatment. Thus, complete tumor removal is important to achieve to improve patient outcomes and reduce overtreatment, yet there is a delicate balance between resection radicality and minimizing damage to the neurovascular bundles to preserve post-operative function. The NeuroSAFE trial demonstrated that real-time detection and correction of PSMs by comprehensive histology of the prostate circumference results in improved patient outcomes, yet there are no widely adoptable methods to achieve this. In an effort to address this technical gap, we have developed video-rate structured illumination microscopy (VR-SIM) and demonstrated that it enables accurate diagnosis of PCa in the biopsy setting, and that it can rapidly deliver gigapixel microscopic images of the entire prostate surface for detection of PSMs. VR-SIM delivers the surface area coverage and resolution needed to detect PSMs, yet it is also fast and relatively simple and inexpensive, opening the possibility for widespread adoption. In this project, our interdisciplinary team of engineers and clinicians with significant prostate expertise will further advance this technology towards clinical translation, by completing critical technology development steps and by prospectively validating it in a large patient series. Specifically, we will increase the mechanical automation speed of the device, and will develop a fully automated system for handling of the removed prostate, to enable gigapixel panoramas of the entire prostate circumferential surface to be delivered within 10 minutes of removal and with minimal tissue processing and user intervention. We will then leverage our recently developed dual-color fluorescent stain that replicates standard H&E with high specificity, to develop expert-validated clinical image atlases using biopsies and cadaveric specimens to enhance image interpretation of VR-SIM prostate panoramas. These improvements will be combined to test the system in a prospective 250-patient clinical study, to determine the accuracy of the device for intra-operative detection of PSMs and prediction of post-operative PSA based on measurement of PSM extent. Finally, we will measure and model expert reviewer behavior using a novel web-enabled visual observer tracking method, which could be used in future computer-assisted search algorithms to expedite intra-operative image review. Successful completion will set the stage for multi-center clinical trials to validate the clinical utility of VR-SIM for real-time detection and correction of PSMs, and improvement of patient outcomes.