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Correcting Dose Calculation Errors in Radiation Oncology

纠正放射肿瘤学中的剂量计算错误

基本信息

批准号：
9923448
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
项目类别：
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/9923448
关键词：
Affect Agreement Characteristics Clinic Clinical Clinical Trials Computer Models Computer Systems Computers Credentialing Data Dependence Dose Ensure Goals Head and Neck Cancer Head and neck structure Hospitals Image Individual Infrastructure Institution Intervention Linear Accelerator Radiotherapy Systems Malignant Neoplasms Manufacturer Name Measurement Measures Modeling Normal tissue morphology Patients Process Radiation Radiation Dose Unit Radiation Oncology Radiation therapy Recurrence 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 comparison treatment planning tumor

项目摘要

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.

放射肿瘤学中剂量误差的识别与解决放射治疗是许多癌症治疗的标准治疗方法。以避免不必要的复发或毒性，正确的剂量必须在±5%的范围内给予肿瘤开了处方。通过治疗计划计算机来确定对患者的辐射剂量计算，其准确性在很大程度上取决于个别诊所描述他们的辐射场。对国家参与中心的审计放射治疗临床试验发现，美国18%的审计病例确实如此辐射剂量未达到预期剂量的±7%。造成这些问题的一个可能原因误差是机构计算中对辐射场的不准确描述模特。该项目将开发工具，可以确定何时这一重要原因的剂量误差是相关的，确定哪些参数对于准确计算辐射最重要剂量，然后直接与发现问题的医院互动，以解决这些问题错误。这推进了我们提高存活率和减少正常组织的长期目标通过确保准确的剂量传递，确保放射肿瘤学中的毒性。我们的假设是一个线性的加速器型号特定的计算系统可以识别和解决50%的治疗错误在放射肿瘤学方面(误差为5%)，这将是迈向提高了质量。具体目标1将开发基础设施，以识别计算错误利用参考辐射束特性计算放射治疗剂量。然后它将测试数百家机构在计算放射治疗剂量方面的表现。特定目标2将确定哪些基本放射治疗参数对于准确的剂量计算最为重要在临床条件下。具体目标3将发展与机构互动的基础设施其中识别出了计算误差。我们将与该机构合作，改善他们的剂量计算模型，并验证了他们的新模型在计算剂量方面更准确。由于计算模型用于确定所有患者的剂量，因此这一改进将使在该机构接受治疗的所有患者受益。