Towards personalized medicine with theranostics: quantitative molecular imaging and artificial intelligence

通过治疗诊断学实现个性化医疗：定量分子成像和人工智能

• 批准号: RGPIN-2021-02965
• 负责人: Uribe, Carlos
• 金额: $ 1.75万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=742305
• 关键词: Towards; personalized; medicine; theranostics; quantitative

The exciting field of theranostics (i.e. therapy + diagnostics) in nuclear medicine involves usage of radiopharmaceutical imaging in tandem with (before, during or after) radiopharmaceutical therapy (RPT). Imaging is done with single photon computed emission tomography/computed tomography (SPECT/CT) or positron emission tomography (PET), while RPT uses alpha- or beta-emitting radioisotopes. Contrary to what is routine for external beam radiation therapy (EBRT), RPT is presently not planned based on individual patient characteristics. Dosimetry in RPT is believed to be difficult and time-consuming, and thus, radiation doses delivered to tumors/healthy organs are commonly not quantified. Basic science research involving physics, applied math, engineering, and computer science, while working closely with physicians and technologists, are essential in closing the gap between RPT and EBRT. My proposed program aims at bringing RPT on par with EBRT, utilizing quantitative imaging and artificial intelligence (AI), to allow for personalized dose assessments in RPT. My short-term objectives are: 1)Develop PET and SPECT imaging protocols to measure radiopharmaceutical biodistribution using theranostic pairs even for radioisotopes that cannot be directly imaged. 2)Develop robust image segmentation algorithms to accurately quantify tumor/organ radioactivity and mass (both required in dosimetry) from SPECT/CT and PET/CT images, and enable automated segmentation using AI. 3)Study contributions to uncertainties in the dose estimates from quantitative image generation and dosimetry method (e.g. organ level vs. voxelized methods). 4)Combine quantitative, texture, shape, and intensity image features (radiomics) from diagnostic PET, therapy SPECT, and dose images to improve/simplify dose estimates and build predictive models for doses/responses. My program is designed with a strong component in training of highly qualified personnel (HQP). HQP are mentored to become experts/leaders, whether they pursue a career in industry, academia, or healthcare practice. HQP will develop their own thinking and decision-making, while actively mentored and supported. They participate in and enhance our industry-academic collaborations. HQP will network and disseminate our work at scientific conferences and are encouraged to join committees of societies in our field. Scientific excellence will be pursued and propelled in the context of a multidisciplinary, multicultural, diverse, and inclusive team environment. Our experience with quantitative imaging, dosimetry, AI, and the support from both BC Cancer and the University of British Columbia make this program a great venue and opportunity to put Canada at the forefront of personalized RPT. The program will make critical contributions to enable simplified dosimetry protocols, establish tools for automatic segmentation, enable personalized RPT planning, train HQP, and expand collaborations with industry and academic partners.

核医学中治疗诊断学（即治疗+诊断）的令人兴奋的领域涉及放射性药物成像与放射性药物治疗（RPT）（之前，期间或之后）的结合使用。成像是用单光子计算机发射断层扫描/计算机断层扫描（SPECT/CT）或正电子发射断层扫描（PET）完成的，而RPT使用α或β放射性同位素。与常规的外照射放射治疗（EBRT）相反，RPT目前没有基于个体患者特征进行规划。RPT中的剂量测定被认为是困难和耗时的，因此，递送到肿瘤/健康器官的辐射剂量通常不被量化。基础科学研究涉及物理学、应用数学、工程学和计算机科学，同时与医生和技术人员密切合作，对于缩小RPT和EBRT之间的差距至关重要。我提出的计划旨在使RPT与EBRT相提并论，利用定量成像和人工智能（AI），以实现RPT的个性化剂量评估。我的短期目标是：1）开发PET和SPECT成像协议，以使用治疗诊断对测量放射性药物的生物分布，即使是不能直接成像的放射性同位素。2)开发强大的图像分割算法，从SPECT/CT和PET/CT图像中准确量化肿瘤/器官放射性和质量（均为剂量测定所需），并使用AI实现自动分割。3)研究对定量图像生成和剂量测定方法（例如，器官水平与体素化方法）剂量估计不确定性的贡献。4)结合来自诊断PET、治疗SPECT和剂量图像的联合收割机定量、纹理、形状和强度图像特征（放射组学），以改善/简化剂量估计并构建剂量/反应的预测模型。我的计划是设计与高素质人才（HQP）的培训强有力的组成部分。HQP被指导成为专家/领导者，无论他们是在行业，学术界还是医疗实践中追求职业生涯。HQP将发展自己的思维和决策，同时积极指导和支持。他们参与并加强我们的行业-学术合作。HQP将在科学会议上建立网络并传播我们的工作，并鼓励加入我们领域的协会委员会。卓越的科学将在多学科，多元文化，多样化和包容性的团队环境中追求和推进。我们在定量成像、剂量测定、人工智能方面的经验，以及BC Cancer和不列颠哥伦比亚省大学的支持，使这个项目成为一个很好的场所和机会，使加拿大处于个性化RPT的最前沿。该计划将为简化剂量测定方案、建立自动分割工具、实现个性化RPT规划、培训HQP以及扩大与行业和学术合作伙伴的合作做出重要贡献。