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 170,000 名患者被诊断为脑转移瘤 (BM)，大多数患者具有多发性 BM (mBM) 的临床表现。 立体定向放射外科 (SRS) 经常用于治疗 mBM，并且比传统的全脑放疗毒性小得多。目前的SRS平台是为有限数量的靶标进行单次治疗而设计的，因此使用现有平台进行mBM SRS的临床工作流程很麻烦：1）劳动密集型的手动mBM识别和分割； 2) 繁琐的手动规划 mBM 到不同的治疗疗程中； 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（R01 支持）基于人工智能 (AI) 的 mBM 管理平台，即 AimBMs，以优化 SRS mBM 患者护理。该 SBIR 提案旨在翻译、验证 AimBMs 平台并将其商业化。该提案包含三个目标：1）开发私有云，将 AimBMs 平台集成到临床实践环境中； 2) 使用现场增量学习针对特定地点的实践完善和优化 AimBMs 平台性能； 3) 在 5 个合作机构验证 AimBM 平台性能。该项目的成功将使 AimBMs 平台从单一学术机构的使用转向广泛的 SRS 社区实践，从而使大量 mBMs 人群受益。