Improving assessment of prostate cancer bone metastases using advanced diffusion imaging

使用先进的扩散成像改进前列腺癌骨转移的评估

• 批准号: 10183247
• 负责人: Tyler Michael Seibert
• 金额: $ 20.13万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10183247
• 关键词: Address; Affect; Aftercare; Agreement; Anatomy; Biomedical Engineering; Caliber; Cancer Control; Cancer Etiology; Cessation of life; Classification; Clinical; Clinical Trials; Custom; Development; Diffusion; Diffusion Magnetic Resonance Imaging; Disease; Engineering; Environment; Epithelial; Evaluation; Goals; Guidelines; Human Resources; Hybrids; Image; Individual; Individual Adjustment; Institution; International; Lesion; Location; Magnetic Resonance Imaging; Malignant Neoplasms; Malignant neoplasm of prostate; Measurement; Measures; Medicine; Mentors; Metastatic Neoplasm to the Bone; Metastatic Prostate Cancer; Modeling; Multimodal Imaging; Neoplasm Metastasis; Outcome; PET/CT scan; Pain; Participant; Patient Care; Patients; Phase; Physicians; Principal Investigator; Process; Prostate Cancer therapy; Protocols documentation; Quality of life; Radiation; Radiation Oncologist; Radiation Oncology; Radiation therapy; Reader; Research; Research Personnel; Research Priority; Resolution; Resources; Restriction Spectrum Imaging; Scientist; Screening for Prostate Cancer; Signal Transduction; Structure; System; Techniques; Testing; Tissues; Veterans; Work; anatomic imaging; bioimaging; bone; bone imaging; cancer imaging; career; career development; clinical care; clinical pain; clinical practice; clinical predictors; design; experience; image guided radiation therapy; imaging biomarker; imaging detection; imaging genetics; improved; indexing; individual patient; innovation; interest; men; multi-scale modeling; novel therapeutics; outcome prediction; palliation; personalized medicine; predict clinical outcome; professor; prognostic; prognostic value; prostate cancer metastasis; quantitative imaging; reduce symptoms; response; therapeutically effective; tool; treatment planning; treatment response; tumor

Project Summary Metastatic prostate cancer (PCa) is a debilitating and often deadly disease affecting tens of thousands of men in the U.S. and worldwide. Effective therapeutic options exist for symptom relief and control of the cancer, with others in the pipeline for testing. It is even thought that some patients might be cured if we could detect metastatic disease when it is limited to only a small number of locations. However, both treatment and testing of novel therapies require accurate imaging of the metastases. Unfortunately, most PCa metastases are in bones, where imaging quality is poor, and metastases are considered unmeasurable with conventional techniques. The broad goal of this project is to optimize and test innovative approaches to quantitative imaging, radiation targeting, and response assessment of PCa. The proposal centers on distortion correction and advanced diffusion MRI models, which are effective for detection of PCa lesions and have shown promising association with clinical outcomes. The first specific aim of the proposal is to implement distortion-corrected diffusion MRI into a radiotherapy treatment planning system and measure the impact of distortion correction on precise and accurate tumor delineation in bone metastases. The second aim is to evaluate the prognostic value of diffusion MRI metrics as predictors of clinical outcomes after radiotherapy for bone metastases, a treatment with evidence of a survival benefit in some oligometastatic patients and important for quality of life in patients with painful bone lesions. The third aim is to evaluate the reliability of diffusion MRI for quantitative treatment response assessment of individual bone metastases, an unmet need for clinical practice and clinical trials. Dr. Seibert, assistant professor of Radiation Medicine and Bioengineering, seeks to advance patient care with this proposal and to improve the ability of other investigators to more efficiently test experimental treatments for PCa. Simultaneously, Dr. Seibert will gain mentored experience as a principal investigator and build on his engineering, clinical, and imaging backgrounds with specific expertise in the development of quantitative tools for PCa assessment. UC San Diego and the Center for Multimodal Imaging and Genetics— directed by K08 proposal mentor, Dr. Dale—provide the ideal environment for this project and career development, with a veteran team of mentors and an abundance of resources and skilled personnel to facilitate successful completion of the specific aims and to launch Dr. Seibert’s career as a physician-scientist in radiation oncology and biomedical imaging.

项目概要 转移性前列腺癌 (PCa) 是一种使人衰弱且往往致命的疾病，影响着数以万计的人 美国和世界各地的男性。存在缓解症状和控制病情的有效治疗选择 癌症，其他药物正在准备进行测试。人们甚至认为，如果我们能够做到的话，一些患者可能会被治愈。 当转移性疾病仅限于少数位置时检测。然而，无论是治疗还是 新疗法的测试需要对转移灶进行准确的成像。不幸的是，大多数 PCa 转移 位于骨骼中，成像质量较差，并且传统方法无法测量转移灶 技术。该项目的总体目标是优化和测试定量的创新方法 PCa 的成像、放射靶向和反应评估。该提案的重点是畸变校正 和先进的扩散 MRI 模型，可有效检测 PCa 病变，并已表明 与临床结果有希望的关联。 该提案的第一个具体目标是将畸变校正扩散 MRI 实施到 放射治疗治疗计划系统并测量畸变校正对精确和准确的影响 骨转移中准确的肿瘤勾画。第二个目的是评估扩散的预后价值 MRI 指标作为骨转移放疗后临床结果的预测因子，骨转移是一种治疗方法 一些寡转移患者的生存获益的证据，对于寡转移患者的生活质量很重要 疼痛的骨损伤。第三个目的是评估扩散MRI用于定量治疗的可靠性 对个体骨转移的反应评估，是临床实践和临床试验中未满足的需求。 放射医学和生物工程助理教授 Seibert 博士致力于提高患者的治疗水平 关心这个建议并提高其他研究人员更有效地测试实验的能力 PCa 的治疗。同时，Seibert 博士将获得作为首席研究员的指导经验，并 以他的工程、临床和成像背景为基础，在开发方面具有特定的专业知识 PCa 评估的定量工具。加州大学圣地亚哥分校和多模态成像和遗传学中心 - 由K08提案导师Dale博士指导——为该项目和职业生涯提供理想的环境 发展，拥有经验丰富的导师团队以及丰富的资源和技术人员来促进 成功完成具体目标并开启 Seibert 博士作为医师科学家的职业生涯 放射肿瘤学和生物医学成像。