Correcting Dose Calculation Errors in Radiation Oncology

纠正放射肿瘤学中的剂量计算错误

• 批准号: 9282227
• 负责人: Stephen F Kry
• 金额: $ 14.96万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-05-01 至 2021-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9282227
• 关键词: Affect; Agreement; Characteristics; Clinic; Clinical; Clinical Trials; Computer Simulation; Computer Systems; Computers; Credentialing; Data; Dependence; Dose; Ensure; Goals; Head and Neck Cancer; Head and neck structure; Hospitals; Image; Individual; Institution; Intervention; Linear Accelerator Radiotherapy Systems; Malignant Neoplasms; Manufacturer Name; Measurement; Measures; Modeling; Normal tissue morphology; Patients; Process; Radiation; Radiation Oncology; Radiation therapy; Recurrence; Research Infrastructure; Roentgen Rays; Safety; Source; Standardization; System; Testing; Therapy Clinical Trials; Toxic effect; Treatment outcome; United States; Work; base; cancer care; clinical practice; dosimetry; experience; improved; improved outcome; individual patient; interactive tool; performance tests; quality assurance; standard care; standard of care; tool; treatment planning; tumor

Identifying and resolving dose errors in radiation oncology Radiation therapy is the standard of care for the treatment of many cancers. To avoid unnecessary recurrences or toxicity, the correct dose must be delivered to the tumor within ±5% of what is prescribed. The radiation dose to the patient is determined with a treatment planning computer calculation, the accuracy of which depends strongly on the input parameters used by the individual clinic to describe their radiation fields. Audits of centers participating in national radiation therapy clinical trials have found that that 18% of audited cases in the United States do not deliver the radiation dose within ±7% of the intended dose. One possible cause for these errors is the inaccurate characterization of the radiation field in the institution’s computational model. This project will develop tools that can identify when this important cause of dose errors is relevant, identify which parameters are most important for the accurate calculation of radiation dose, and then directly interact with those hospitals with identified problems to resolve those errors. This advances our long term goal of improving survival and decreasing normal tissue toxicity in radiation oncology by ensuring accurate dose delivery. Our hypothesis is that a linear accelerator model-specific computational system can identify and resolve 50% of treatment errors in radiation oncology (those showing >5% error), which would be a substantial step towards improved quality. Specific Aim 1 will develop the infrastructure to identify computational errors in radiation therapy dose calculations using reference radiation beam characteristics. It will then test the performance of hundreds of institutions in calculating radiotherapy doses. Specific Aim 2 will determine which basic radiotherapy parameters are most important for accurate dose calculation under clinical conditions. Specific Aim 3 will develop infrastructure to interact with institutions where computational errors have been identified. We will work with the institution to improve their dose calculation models, and verify that their new models are more accurate at calculating dose. Because the calculation model is used to determine the dose to all patients, this improvement will benefit all patients treated at that institution.

识别和解决放射肿瘤学中的剂量误差 放射疗法是许多癌症治疗的标准护理。避免不必要 复发或毒性，正确的剂量必须在±5%的范围内输送到肿瘤。 规定的。患者的辐射剂量由治疗计划计算机确定 计算，其精度在很大程度上取决于输入参数所使用的 个别诊所描述其辐射场。对参加国家 放射治疗临床试验发现，在美国，18%的审计病例 未输送预期剂量±7%范围内的辐射剂量。其中一个可能的原因是 错误是该机构计算中辐射场的不准确表征 模型该项目将开发工具，可以确定当这个重要的原因剂量误差 确定哪些参数对准确计算辐射最重要 剂量，然后直接与那些有确定问题的医院互动，以解决这些问题， 错误.这推进了我们提高生存率和减少正常组织的长期目标 通过确保准确的剂量输送，降低放射肿瘤学中的毒性。我们的假设是， 加速器模型专用计算系统可以识别和解决50%的治疗错误 在放射肿瘤学中（显示>5%误差的那些），这将是朝着 提高质量。具体目标1将开发基础设施，以识别计算错误， 使用参考辐射束特性的辐射治疗剂量计算。它将测试 数百家机构在计算放射治疗剂量方面的表现。具体目标2将 确定哪些基本放射治疗参数对精确剂量计算最重要 在临床条件下。具体目标3将发展与各机构互动的基础设施 其中计算错误已被识别。我们将与该机构合作， 剂量计算模型，并验证其新模型在计算剂量时更准确。 由于计算模型用于确定所有患者的剂量，因此这种改进将 使所有在该机构接受治疗的患者受益。