SBIR TOPIC 417 Multiple Brain Metastases Stereotactic Radiosurgery Management Platform - Detection, Planning and Follow-up

据估计，美国每年约有170，000例患者诊断为脑转移瘤（BM），大多数患者具有多种BM（mBM）的临床表现。 立体定向放射外科（SRS）已被频繁用于治疗mBM，并表现出比传统的全脑放疗毒性小得多。目前的SRS平台设计用于对有限数量的靶点进行单次治疗，因此使用现有平台的mBM SRS的临床工作流程繁琐：1）劳动密集型手动mBM识别和分割; 2）繁琐的手动计划mBM进入不同的治疗疗程;以及3）治疗随访中繁琐的跟踪mBM变化。我们的团队一直在积极开发（R 01支持）基于人工智能（AI）的mBM管理平台，即AimBM，以优化SRS mBM患者护理。该SBIR提案旨在翻译、验证和商业化AimBM平台。该提案包括三个目标：1）开发一个私有云，将AimBMs平台集成到临床实践环境中; 2）使用现场增量学习改进和优化AimBMs平台性能，以实现特定于站点的实践; 3）在5个合作机构中验证AimBMs平台性能。该项目的成功将使AimBMs平台从单一的学术机构使用到广泛的SRS社区实践，使大量的mBMs人群受益。

It was estimated that ~170,000 patients diagnosed with Brain metastases (BMs) in United States each year and most patients have clinical manifestation of multiple BMs (mBMs). Stereotactic radiosurgery (SRS) has been used frequently for treating mBMs and demonstrated much less toxicity than conventional whole brain radiotherapy. Current SRS platform was designed for single-fraction treatment on limited number of targets, thus clinical workflow of mBMs SRS using extant platform is cumbersome: 1) labor-intensive manual mBMs identification and segmentation; 2) cumbersome manual planning mBMs into different treatment sessions; and 3) tedious tracking mBMs changes in treatment follow-up. Our team have been actively developing (R01-supported) an Artificial intelligence (AI)-based mBMs management platform, namely AimBMs, to optimize SRS mBMs patient care. This SBIR proposal targets to translate, validate and commercialize the AimBMs platform. The proposal consists of three aims: 1) develop a private cloud to integrate AimBMs platform into clinical practice environment; 2) refine and optimize AimBMs platform performance for site-specific practice using on-site incremental learning; and 3) validate AimBMs platform performance in 5 collaborating institutes. The success of this project will lead to bringing the AimBMs platform from a single academic institution use to a broad SRS community practice, benefitting a large mBMs population.