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

描述（由申请方提供）：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）的临床成像是人类癌症检测和分期的标准治疗。然而，临床成像是一个宏观过程，每1 mm3体素填充多达106个恶性细胞。目前，将临床影像学结果与导致该结果的细胞基因型和/或表型相关联是极其困难的。因此，"生物标志物"，例如MRI上的动态对比增强（DCE），或在注射靶向放射性示踪剂后看到的PET上的"热"体素，难以验证，因为宏观临床成像发现与微观组织学发现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（同一载玻片）免疫染色和苏木精/伊红（H & E）染色的任何病理标本。因此，消除了在细胞水平上共同配准组织切片的长期问题，同时保留了H & E组织学的“金标准”。该技术为集成平台奠定了基础，该平台允许来自个体患者癌症的宏观和微观数据集的高精度共配准。我们还开发了一种自动化显微镜，可同时采集H & E和NIR荧光，最多可扫描28个2 "x3"的整装载玻片（或56个1 "x3"的载玻片），无需人工干预。使用该技术以及申请中描述的其他几项创新，现在可以生成显微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公司研究（SCR）成像部门建立了学术-工业合作伙伴关系。SCR在经历非线性变形的3-D体积的配准、图像分割和模式识别方面是专家。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志物验证平台。我们的研究还利用了Beth Israel Deaconess医疗中心的独特临床资源，Hershey前列腺癌组织库。通过Hershey组织库，接受前列腺癌根治性直肠切除术的男性接受术前直肠内线圈3T MRI（Gd DCE前后），在直肠切除术中，整个腺体可用于整装准备。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志物验证平台提供原理证明，也将用于确定细胞水平的DCE-MRI机制。通过具有互补技能的学术和工业团队完成特定目标，几乎可以快速有效地验证任何类型癌症的任何拟议生物标志物。公共卫生相关性：用于癌症成像的生物标志物极其难以验证，因为临床成像是在宏观尺度上进行的，而切除组织的组织学评价是在微观尺度上进行的。我们已经在马萨诸塞州波士顿Beth Israel Deaconess Medical Center的Frangioni实验室和新泽西州普林斯顿的Siemens Corporate Research之间建立了学术-工业合作伙伴关系，旨在使用新的近红外荧光和图像融合技术开发生物标志物验证的集成平台。这项研究还利用了一个独特的前列腺癌组织库，该组织库提供了来自个体前列腺癌患者的配对DCE-MRI和组织学整体标本。

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.