Bayesian bioluminescence image reconstruction for therapy monitoring of hormone-r

贝叶斯生物发光图像重建用于激素-r 治疗监测

• 批准号: 7991507
• 负责人: Alexander D. Klose
• 金额: $ 17.11万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-30 至 2012-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7991507
• 关键词: Algorithms; Androgens; Animal Model; Animals; Beds; Bioluminescence; Clinic; Development; Diffusion; Disease; Dorsal; Equation; Evolution; Hormones; Human; Image; Imaging Device; Imaging technology; Intervention; Light; Location; Longitudinal Studies; Magnetic Resonance Imaging; Malignant neoplasm of prostate; Maps; Measures; Methods; Mitogen-Activated Protein Kinases; Modeling; Molecular; Monitor; Neoplasm Metastasis; Optics; Pathway interactions; Patients; Performance; Pharmacotherapy; Phosphotransferases; Probability; Process; Property; Prostate Cancer therapy; Prostatic Neoplasms; Quality of life; Recovery; Refractory; Research; Sampling; Side; Signal Pathway; Signal Transduction; Solutions; Source; Structure; Surface; Survival Rate; Technology; Testing; Therapy Evaluation; Time; Tissue Model; Tissues; Translations; Tumor Volume; Validation; Weight; base; design; effective therapy; hormone refractory prostate cancer; human FRAP1 protein; image reconstruction; imaging modality; improved; in vivo; insight; light intensity; male; mouse model; novel; preclinical study; public health relevance; reconstruction; response; therapy development; tissue phantom; tomography; tumor; tumor growth

DESCRIPTION (provided by applicant): Hormone-refractory tumors are the most deadly form of prostate cancer. There is currently no cure for patients with these very aggressive and highly metastatic tumors. Thus, the design of effective therapies for patients with such advanced prostate cancer is very essential for increasing patient survival and quality of life. It also is absolutely critical for therapy development to understand how different cell signaling pathways give rise to this deadly disease. In fact, sensitive imaging technology could give insight into these molecular mechanisms in a small animal model of hormone-refractory prostate cancer. Moreover, in vivo monitoring of tumor development could also assess immediate responses to prostate cancer therapy. Hence, bioluminescence imaging has already become a powerful tool for imaging tumor development in animals, but quantitative imaging has not been possible yet. Animals still need to be sacrificed at the endpoint of therapy in order to determine the actual tumor mass for therapy evaluation. Therefore, the development of a novel tomographic bioluminescence imaging method, where tumor volume can directly be determined in vivo and at all time points during studies, is of utmost significance for developing such highly effective therapies. The main hypothesis of this application is that a bioluminescence image reconstruction method will provide detailed volume information about tumor growth/regression at all intermediate time points during therapy in a small animal model of hormone-refractory prostate cancer. Our technology will help testing what specific drugs and therapies could block hormone-refractory prostate cancer in vivo and, thus, would significantly aid therapy development and facilitate its translation into the clinic. We will focus on two specific aims to support the hypothesis. First, we will develop a multi-spectral and multiple-view Bayesian image reconstruction method with an entropic prior and an evolution strategy for sampling the global search space of the unknown bioluminescent source distributions inside tissue. Our method will employ a high-order radiative transfer model based on the SPN equations and an adaptive grid refinement method for curved geometries. We will also implement a MRI and CT co-registration method with an animal bed for including anatomical tissue structure into the image reconstruction process. Second, we will reconstruct changes in tumor volume during therapy in a Nkx3.1/Pten mouse model of hormone-refractory prostate cancer. We will study the pharmacological manipulation of the Akt/mTOR and B-Ref/Erk Map kinase signaling pathways by determining small changes in tumor volume at various time points during therapy. PUBLIC HEALTH RELEVANCE: A Bayesian bioluminescence image reconstruction method will help testing what specific drugs and therapies can block hormone-refractory prostate cancer in small animal models. It will not only significantly aid therapy development in pre-clinical studies but will also facilitate its translation into the clinic. Therefore, the proposed imaging method will have a high probability of directly impacting the treatment of male patients with the deadliest form of prostate cancer and would increase survival rate.

描述（由申请人提供）：激素难治性肿瘤是前列腺癌的最致命形式。目前还没有治愈这些非常侵袭性和高转移性肿瘤的患者。因此，为患有这种晚期前列腺癌的患者设计有效的治疗方法对于提高患者的生存率和生活质量是非常重要的。了解不同的细胞信号通路如何引起这种致命疾病对于治疗开发也是至关重要的。事实上，灵敏的成像技术可以在难治性前列腺癌的小动物模型中深入了解这些分子机制。此外，体内监测肿瘤发展也可以评估对前列腺癌治疗的即时反应。因此，生物发光成像已经成为动物肿瘤发展成像的有力工具，但定量成像还不可能。在治疗结束时仍需要处死动物，以确定实际肿瘤质量用于治疗评价。因此，开发一种新的断层生物发光成像方法，其中肿瘤体积可以直接在体内和在研究期间的所有时间点确定，对于开发这种高效疗法具有极其重要的意义。 本申请的主要假设是，生物发光图像重建方法将在治疗期间的所有中间时间点在难治性前列腺癌的小动物模型中提供关于肿瘤生长/消退的详细体积信息。我们的技术将有助于测试哪些特定的药物和疗法可以在体内阻断难治性前列腺癌，因此，将大大有助于治疗开发，并促进其转化为临床。我们将集中在两个具体的目标来支持这一假设。首先，我们将开发一个多光谱和多视角贝叶斯图像重建方法与熵先验和进化策略采样的未知生物发光源分布的组织内的全局搜索空间。我们的方法将采用高阶辐射传输模型的基础上的SPN方程和自适应网格加密方法的弯曲的几何形状。我们还将实现MRI和CT配准方法与动物床，包括解剖组织结构到图像重建过程中。第二，我们将重建治疗期间肿瘤体积的变化在Nkx3.1/Pten小鼠模型的肿瘤难治性前列腺癌。我们将通过测定治疗期间不同时间点肿瘤体积的微小变化来研究Akt/mTOR和B-Ref/Erk Map激酶信号通路的药理学操作。 公共卫生相关性：贝叶斯生物发光图像重建方法将有助于测试哪些特定的药物和疗法可以在小动物模型中阻断难治性前列腺癌。它不仅将大大有助于临床前研究中的治疗开发，而且还将促进其转化为临床。因此，所提出的成像方法将具有直接影响患有最致命形式的前列腺癌的男性患者的治疗的高概率，并且将提高存活率。