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A Novel Optical Bioimaging Method for Direct Assessment of Ovarian Cancer Chemotherapy Response at Laparoscopy

机译:腹腔镜下直接评估卵巢癌化疗反应的新型光学生物成像方法

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摘要

In patients with advanced ovarian cancer (AOC), additional imaging of disseminated disease at laparoscopy could complement conventional imaging for estimation of chemotherapy response. We developed an image segmentation method and evaluated its use in making accurate and objective measurements of peritoneal metastases in comparison to Response Evaluation Criteria In Solid Tumors (RECIST) criteria. A software tool using a custom ImageJ macro-based approach was employed to estimate lesion size by converting image pixels into unit length. The software tool was tested as a proof-of-principle in an AOC patient with two isolated peritoneal deposits. Image analysis of representative laparoscopic snapshots before and after three cycles of neoadjuvant chemotherapy (NACT) revealed an average tumor nodule response ratio (TNRR) of 40% (partial response), which was in concordance with RECIST evaluation by computed tomography (CT). We demonstrated the feasibility of using this novel anatomical analysis for direct assessment of chemotherapy response in an AOC patient as an adjunct to RECIST criteria.
机译:对于晚期卵巢癌(AOC)患者,腹腔镜检查对弥漫性疾病的其他影像学检查可补充常规影像学检查,以评估化疗反应。我们开发了一种图像分割方法,并与实体肿瘤反应评估标准(RECIST)标准相比,评估了其在进行腹膜转移准确,客观测量中的用途。通过使用基于ImageJ宏的定制方法的软件工具,通过将图像像素转换为单位长度来估计病变大小。该软件工具已作为具有两个孤立腹膜沉积物的AOC患者的原则证明进行了测试。在新辅助化疗(NACT)的三个周期之前和之后的代表性腹腔镜快照的图像分析显示,平均肿瘤结节应答率(TNRR)为40%(部分应答),这与通过计算机断层扫描(CT)进行的RECIST评价一致。我们证明了使用这种新颖的解剖学分析直接评估AOC患者作为RECIST标准的化疗反应的可行性。

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