A Platform for Cancer Biomarker Validation: Image Fusion Using NIR Fluorescence

描述(申请人提供)：使用磁共振成像(MRI)、计算机断层扫描(CT)、正电子发射断层扫描(PET)和/或单光子发射计算机断层扫描(SPECT)的临床成像是检测和分期人类癌症的标准。然而，临床成像是一个宏观的过程，每1mm3体素有多达106个恶性细胞填充。目前，很难将临床影像表现与导致该发现的细胞基因和/或表型联系起来。因此，“生物标记物”，如MRI上的动态对比度增强(DCE)，或注射靶向放射性示踪剂后在PET上看到的“热”体素，很难验证，因为宏观临床成像结果与微观组织学结果的融合充满了技术挑战。为了解决这个问题，我们的实验室开发了新的近红外(NIR)荧光技术，允许同时对任何病理标本进行(同一张玻片)免疫染色和苏木素/伊红(H&E)染色。因此，消除了在细胞水平上共同登记组织切片的长期问题，同时保留了H&E组织学的“黄金标准”。这项技术为一个集成平台奠定了基础，该平台允许对单个患者癌症的宏观和微观数据集进行高精度的联合配准。我们还开发了一种自动显微镜，可以同时获取H&E和NIR荧光，并且允许在没有人工干预的情况下扫描多达28 2“x3”整装载玻片(或56 1“x3”载玻片)。使用这项技术和申请中描述的其他几项创新，现在可以生成微观分辨率的临床病理标本的3-D数据集。然而，为了弥合微观和宏观领域之间的差距，我们与新泽西州普林斯顿的西门子企业研究(SCR)成像部门建立了学术-产业合作伙伴关系。SCR擅长非线性变形的3-D体积的联合配准、图像分割和模式识别。使用SCR为这项研究开发的算法，我们提出了一个自动化和集成的癌症生物标记物验证平台。我们的研究还利用了贝丝以色列女执事医疗中心的独特临床资源--好时前列腺癌组织库。通过好时组织银行，接受前列腺癌根治术的男性患者在手术前接受直肠内线圈3T磁共振成像(Gd DCE前后)，在前列腺切除术时，整个腺体可用于整体准备。临床成像(DCE-MRI)和整体组织学的配对数据集将为我们的生物标记物验证平台提供原则证明，并将用于在细胞水平上确定DCE-MRI的机制。由具有互补技能的学术和工业团队完成特定目标，将允许任何类型的癌症的几乎任何拟议的生物标记物得到快速和有效的验证。公共卫生相关性：癌症成像的生物标志物极难验证，因为临床成像是在宏观范围内进行的，而切除组织的组织学评估是在微观尺度上进行的。我们在马萨诸塞州波士顿的贝斯以色列女执事医疗中心的Frangion实验室和新泽西州普林斯顿的西门子企业研究公司之间建立了学术-产业合作伙伴关系，旨在开发一个使用新的近红外荧光和图像融合技术的生物标记物验证的集成平台。这项研究还利用了一个独特的前列腺癌组织库，该库提供了来自个别前列腺癌患者的配对DCE-MRI和组织学整体。

DESCRIPTION (provided by applicant): Clinical imaging using magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and/or single-photon emission computed tomography (SPECT) is the standard of care for the detection and staging of human cancer. However, clinical imaging is a macroscopic process, with up to 106 malignant cells filling every 1 mm3 voxel. At present, it is extremely difficult to correlate clinical imaging findings with the cellular genotype and/or phenotype leading to the finding. Hence, "biomarkers," such as dynamic contrast enhancement (DCE) on MRI, or a "hot" voxel on PET seen after injection of a targeted radiotracer, are difficult to validate since the fusion of macroscopic clinical imaging findings with microscopic histological findings is fraught with technical challenges. To solve this problem, our laboratory has developed new near-infrared (NIR) fluorescence technology that permits simultaneous (same slide) immunostaining and hematoxylin/eosin (H&E) staining of any pathological specimen. Hence, the chronic problem of co-registering tissue slices at the cellular level is eliminated, while the "gold-standard" of H&E histology is preserved. This technology lays the foundation for an integrated platform that permits high accuracy co-registration of macroscopic and microscopic data sets from an individual patient's cancer. We have also developed an automated microscope that acquires H&E and NIR fluorescence simultaneously, and which permits up to 28 2"x3" whole-mount slides (or 56 1"x3" slides) to be scanned without human intervention. Using this technology, and several other innovations described in the application, 3-D data sets of clinical pathological specimens, at microscopic resolution, can now be generated. However, to bridge the gap between the microscopic and macroscopic domains, we have formed an academic-industrial partnership with the Imaging Department of Siemens Corporate Research (SCR) in Princeton, NJ. SCR is expert in the co-registration of 3-D volumes that have undergone non-linear deformations, in image segmentation, and in pattern recognition. Using algorithms developed by SCR for this study, we present an automated and integrated platform for cancer biomarker validation. Our study also leverages a unique clinical resource at the Beth Israel Deaconess Medical Center, the Hershey Prostate Cancer Tissue Bank. Through the Hershey Tissue Bank, men undergoing radical prostatectomy for prostate cancer receive a preoperative endorectal coil 3T MRI (pre- and post-Gd DCE), and at prostatectomy, the entire gland is available for whole-mount preparation. The paired data sets of clinical imaging (DCE-MRI) and whole mount histology will provide proof of principle for our biomarker validation platform, and will also be used to determine the mechanism of DCE-MRI at the cellular level. Completion of the specific aims by academic and industrial teams with complementary skill sets will permit virtually any proposed biomarker, for any type of cancer, to be validated rapidly and efficiently. PUBLIC HEALTH RELEVANCE: Biomarkers for cancer imaging are extremely difficult to validate, since clinical imaging is performed on a macroscopic scale and histological evaluation of resected tissue is performed on a microscopic scale. We have formed an academic-industrial partnership between the Frangioni Laboratory at the Beth Israel Deaconess Medical Center in Boston, MA and Siemens Corporate Research in Princeton, NJ aimed at developing an integrated platform for biomarker validation using new near-infrared fluorescence and image fusion technology. This study also leverages a unique prostate cancer tissue bank that provides paired DCE-MRI and histological whole mounts from individual prostate cancer patients.