Image-Guided Molecular Optical Spectroscopy for Tumor-Targeted Prostate Cancer Interventions

由于前列腺癌的结构和表型的异质性，为了诊断和治疗的目的，确定前列腺癌的位置、范围和分级仍然具有挑战性。在**系统超声引导下盲目活检的情况下，这会导致超过30%的假阴性率，而对于肿瘤靶向(局部)治疗，如近距离治疗，其**成功取决于精确绘制MRI癌症靶点以提供大体肿瘤位置，**但缺乏治疗位置的分子信息，没有对肿瘤**进行准确分级**，并可能导致不良反应的较差平衡。因此，目前还没有解决在治疗过程中及时确认肿瘤位置/分级的医学**技术。我们的目标是开发一种图像引导系统，将实时分子组织**表征与光学拉曼光谱(RS)仪器相结合，用于肿瘤靶向**前列腺癌干预，改进肿瘤定位和表征。具体地说，**我们将利用实时导航平台开发和进行第一次人体研究**技术，允许在活检过程中高精度和肿瘤特异性地采集样本**。将完成四项研究目标，以确保在3年内将**技术在人体内转化为前列腺癌，并将其提交给我们的合作伙伴Elekta和飞利浦加拿大公司：(1)开发用于组织定征的光纤RS针设备，以指导前列腺介入治疗；(2)培训**有监督的机器学习算法，从光谱RS信号中推断生物**特性；(3)实施集成的图像引导平台，包括实时RS组织**分类和针跟踪，以确定具有前列腺运动补偿的MRI靶点；**(4)对MRI上可见的局部PCA且将**接受HDR近距离治疗的患者进行试点临床研究。最终，我们将有一项高端技术在**前列腺癌介入治疗中进行临床测试，用于实际的分子识别和癌症检测。

Confirming the location, extent, and grade of prostate cancer for diagnostic and therapeutic**purposes remains challenging due to the architectural and phenotypic heterogeneity. In the**case of blind systematic ultrasound-guided biopsies, this leads to more than 30% of false**negative rates, while for tumor-targeted (focal) therapies such as brachytherapy, their**success hinge on precise mapping of MRI cancer targets to provide the gross tumor location,**but lack molecular information at the treatment location, without accurate grading of the tumor**and can lead to a poor balance of toxicities. Therefore, there is no existing medical**technologies addressing the timely confirmation of tumor location/grade during therapy. Our**objective is to develop an image-guidance system integrating real-time molecular tissue**characterization with an optical Raman spectroscopy (RS) instrument for tumor-targeted**prostate cancer interventions, improving tumor localization and characterization. Specifically,**we will develop and conduct first in-human studies using a real-time navigation platform**technology allowing for high-precision and tumor-specific harvesting of samples during biopsy**procedures. Four research aims will be completed to insure in-human translation of the**technology into to our partners Elekta and Philips Canada within 3 years: (1) Develop a fiber**optics RS needle device for tissue characterization to guide prostate interventions; (2) Train**supervised machine-learning algorithms from spectral RS signatures to infer biological**properties; (3) Implement an integrated image-guidance platform with real-time RS tissue**classification and needle tracking to identified MRI targets with prostate motion compensation;**(4) Conduct a pilot clinical study patients with localized PCa visible on MRI and who will**undergo HDR brachytherapy. Ultimately, we will have a high-end technique clinically tested in**prostate interventions for practical molecular identification and cancer detection.