TOPIC 389 - INTELLIGENT SOFTWARE FOR RADIATION THERAPY PLANNING

主题 389 - 用于放射治疗计划的智能软件

• 批准号: 10196876
• 负责人: JONATHAN EDELEN
• 金额: $ 5.5万
• 依托单位: RADIASOFT, LLC
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-16 至 2020-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10196876
• 关键词: Address; Algorithms; Archives; Artificial Intelligence; Cancer Patient; Complex; Computer software; Data; Data Set; Development; Elements; Generations; Goals; Human; Intelligence; Intervention; Machine Learning; Malignant neoplasm of prostate; Manuals; Medical Imaging; Methodology; Modality; Normal tissue morphology; Operative Surgical Procedures; Patient Care; Patients; Phase; Process; Prostate Cancer therapy; Pythons; Radiation Dose Unit; Radiation Oncology; Radiation therapy; Risk; Supervision; System; Technology; Therapeutic; Training; Work; automated algorithm; automated segmentation; base; cancer therapy; data reduction; effective therapy; high risk; intelligent algorithm; machine learning algorithm; meetings; operation; prediction algorithm; prototype; response; stem; success; treatment planning; tumor; web interface

INTELLIGENT SOFTWARE FOR RADIATION THERAPY PLANNING Besides surgery, radiotherapy is the most effective treatment modality for localized prostate cancer. The success of radiotherapy stems from the exploit of a therapeutic window in tumor response and normal tissue tolerance which maximizes the chance of sterilizing the tumor while sparing the surrounding normal tissue from severe damage. This requires an accurate and individualized radiation dose distribution generated from the examination of the patient’s medical images. Radiation therapy is technically complex and labor intensive. Intensive human supervision and intervention are needed throughout the path of patient care. Artificial intelligence and machine learning technologies are adept at automating workflows and tasks—in this case the development of cancer treatment plans. We believe that this machine learning has incredible potential to address inherent problems in the existing treatment planning workflow. Our approach will mitigate the current issues with treatment planning, integrate seamlessly with day-to-day operations, and will serve as a treatment solution that benefits patients in a way that limits their risk and extends their lives. The goal of this project is to develop a start-to-end prostate cancer treatment planning system. We will work with three expert radiation oncology teams to archive existing patient data for use in training of artificial intelligence algorithms. These algorithms will enable high quality plans to be generated with ease. At the completion of Phase I, we will have a prototype interface that will allow users to create treatment plans and segmentation using artificial intelligence algorithms. Additionally, users will be able to evaluate these plans against other expert plans and against the training data.

放射治疗计划的智能软件