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

用于肿瘤靶向前列腺癌干预的图像引导分子光谱

• 批准号: 523532-2018
• 负责人: Kadoury, Samuel
• 金额: $ 11.49万
• 依托单位: École Polytechnique de Montréal
• 依托单位国家: 加拿大
• 项目类别: Collaborative Health Research Projects
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=693895
• 关键词: Image; Guided; Molecular; Optical; Spectroscopy

Confirming the location, extent, and grade of prostate cancer for diagnostic and therapeuticpurposes remains challenging due to the architectural and phenotypic heterogeneity. In thecase of blind systematic ultrasound-guided biopsies, this leads to more than 30% of falsenegative rates, while for tumor-targeted (focal) therapies such as brachytherapy, theirsuccess 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 tumorand can lead to a poor balance of toxicities. Therefore, there is no existing medicaltechnologies addressing the timely confirmation of tumor location/grade during therapy. Ourobjective is to develop an image-guidance system integrating real-time molecular tissuecharacterization with an optical Raman spectroscopy (RS) instrument for tumor-targetedprostate cancer interventions, improving tumor localization and characterization. Specifically,we will develop and conduct first in-human studies using a real-time navigation platformtechnology allowing for high-precision and tumor-specific harvesting of samples during biopsyprocedures. Four research aims will be completed to insure in-human translation of thetechnology into to our partners Elekta and Philips Canada within 3 years: (1) Develop a fiberoptics RS needle device for tissue characterization to guide prostate interventions; (2) Trainsupervised machine-learning algorithms from spectral RS signatures to infer biologicalproperties; (3) Implement an integrated image-guidance platform with real-time RS tissueclassification 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 willundergo HDR brachytherapy. Ultimately, we will have a high-end technique clinically tested inprostate interventions for practical molecular identification and cancer detection.

由于建筑和表型异质性，确认前列腺癌的位置，程度和等级用于诊断和治疗性斑点仍然具有挑战性。在盲目系统性超声引导活检的情况下，这导致了30％以上的虚假率，而对于诸如肿瘤靶向的（焦点）疗法（例如近距离生日疗法），它们的成功铰链在MRI癌症的精确映射上取决于MRI癌症的精确映射，以使肿瘤位置缺乏良好的肿瘤范围，但可以在治疗方面提供较差的位置，从而可以逐渐毕业，从而逐渐毕业。因此，没有现有的医学技术来解决治疗过程中肿瘤位置/等级的及时确认。我们的原则是开发一个图像戒断系统，该系统将实时分子组织筛腔与光学拉曼光谱仪（RS）仪器整合起来，用于肿瘤 - 靶向刺激性癌症干预措施，从而改善肿瘤的定位和表征。具体而言，我们将使用实时导航平台技术进行首次进行人类研究，以便在活检过程中对样品进行高精度和肿瘤特异性收获。将完成四项研究目标，以确保将Thetechnology在3年内向我们的合作伙伴Elekta和Philips Canada转换为我们的合作伙伴：（1）开发一种用于指导前列腺干预的组织表征的Fiberoptics RS针头设备； （2）来自光谱RS特征的训练训练的机器学习算法，以推断生物培训； （3）实现具有实时RS组织分类和针头跟踪的集成图像辅助平台，以通过前列腺运动补偿确定的MRI靶标；（4）进行一项试验临床研究，在MRI上可见局部PCA和Willundergo HDR HDR Hyparachytherapy。最终，我们将采用一项高端技术，临床测试的攻击性干预措施，用于实践分子鉴定和癌症检测。