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

SBIR TOPIC 417 多发性脑转移瘤立体定向放射外科管理平台 - 检测、规划和随访

• 批准号: 10579810
• 负责人: HAO JIANG
• 金额: $ 5.5万
• 依托单位: NEURALRAD LLC
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-15 至 2022-06-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10579810
• 关键词: Artificial Intelligence; Brain; Clinical; Community Practice; Diagnosis; Environment; Institutes; Institution; Learning; Manuals; Metastatic malignant neoplasm to brain; Patient Care; Patients; Performance; Population; Privatization; Radiation therapy; Radiosurgery; Site; Small Business Innovation Research Grant; Toxic effect; Translating; United States; base; clinical practice; design; detection platform; follow-up; performance site; success

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.

据估计，美国每年约有17万名被诊断为脑转移瘤的患者，其中大多数患者临床表现为多发性脑转移瘤（mBMs）。立体定向放射外科（SRS）已被广泛用于治疗脑脊髓瘤，并证明毒性远低于传统的全脑放疗。目前的SRS平台是针对有限靶点的单组分治疗设计的，因此使用现有平台进行mBMs SRS的临床工作流程繁琐：1)人工对mBMs进行识别和分割；2)繁琐的手工规划mBMs到不同的治疗阶段；3)治疗随访中mBMs变化的繁琐跟踪。我们的团队一直在积极开发（r01支持）基于人工智能（AI）的mBMs管理平台，即AimBMs，以优化SRS mBMs患者护理。该SBIR提案的目标是翻译、验证和商业化AimBMs平台。该方案包括三个目标：1)开发私有云，将AimBMs平台集成到临床实践环境中；2)利用现场增量学习，细化和优化AimBMs平台的具体实践性能；3)在5个合作机构中验证AimBMs平台的性能。这个项目的成功将导致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。