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

核医学中令人兴奋的治疗学领域（即治疗+诊断）涉及在放射药物治疗（RPT）之前，期间或之后同时使用放射性药物成像。成像是通过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发射放射性同位素。与常规的外束放射治疗（EBRT）相反，RPT目前还没有根据患者的个体特征进行计划。RPT中的剂量测定被认为是困难和耗时的，因此，传递到肿瘤/健康器官的辐射剂量通常不能量化。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），允许在RPT中进行个性化剂量评估。我的短期目标是：1)开发PET和SPECT成像方案，使用治疗对测量放射性药物生物分布，即使是不能直接成像的放射性同位素。2)开发稳健的图像分割算法，从SPECT/CT和PET/CT图像中精确量化肿瘤/器官的放射性和质量（剂量学中都需要），并使用AI实现自动分割。3)定量图像生成和剂量测定方法（如器官水平与体素化方法）对剂量估计不确定性的研究贡献。4)结合诊断性PET、治疗性SPECT和剂量图像的定量、纹理、形状和强度图像特征（放射组学），改进/简化剂量估计，并建立剂量/反应的预测模型。我的课程在培养高素质人才（HQP）方面具有很强的组成部分。HQP被指导成为专家/领导者，无论他们是在工业、学术界还是医疗保健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产学研合作。HQP将在科学会议上建立网络并传播我们的工作，并鼓励我们加入本领域的学会委员会。在一个多学科、多元文化、多样化和包容性的团队环境中，追求和推动科学卓越。我们在定量成像、剂量学、人工智能方面的经验，以及BC癌症和英属哥伦比亚大学的支持，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的前沿。该项目将为简化剂量测定方案、建立自动分割工具、实现个性化RPT计划、培训HQP以及扩大与工业界和学术界合作伙伴的合作做出重要贡献。

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.