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Distributed knowledge-based platform for radiotherapy plan quality control

Distributed knowledge-based platform for radiotherapy plan quality control
分布式放疗计划质量控制知识平台
批准号:
9900745
负责人:
Kevin Lawrence Moore
金额:
$37.46万
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-06-11 至 2023-03-31

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ABSTRACT Many recent studies focused on radiotherapy treatment plan quality have begun to quantify what clinicians have long understood: even “optimized” radiotherapy is no guarantee of a truly optimal treatment plan for every patient. Plan quality deficiencies have been shown to put a significant proportion of patients who should have been at low risk of radiation-induced complications at much higher risk for poor outcome. Available research clearly demonstrates a link between radiation provider volume and survival, which emphasizes the importance of quality radiation delivery. Radiation providers in rural or community practices by nature see a wide variety of cases, with lower provider volume for each individual disease site. Through no fault of their own, physician and non-physician practitioners at these rural and community centers could be inadvertently and systematically delivering low quality radiotherapy to their patients simply due to the fact that no platform currently exists that could benchmark their practice against a distributed, externally-validated plan quality control system. Our research team has developed, tested, and clinically-implemented an important tool to combat radiotherapy plan quality deficiencies known as knowledge-based planning (KBP). Knowledge-based planning relies on the use of statistical learning techniques that analyzed a plurality of prior treatments to discover patient-specific anatomical features can be precisely correlated to high quality radiation dose delivery. Unfortunately, the clinical use of KBP has been limited to a handful of high-volume academic centers and, without some external mechanism to increase utilization, its use is not likely to expand significantly to rural and community centers because of the lack of any billing code associated with its use. To provide just such an external mechanism, we intend to build ORBITeR (On-line Real-time Benchmarking Informatics Technology for Radiotherapy), a freely available, on-line knowledge-based radiotherapy plan quality control system. ORBITeR will allow clinicians to obtain automatic and immediate feedback on the quality of any individual treatment plan prior to treatment. We will develop a KBP-driven plan analysis system on a HIPAA-compliant web-based platform designed to give users real- time radiotherapy plan quality feedback. To provide real-time feedback to clinical users, we will develop reporting modules on the ORBITeR system that provide patient-specific feedback on the quality of the intended treatment plan using already-validated head-and-neck, brain, prostate, cervix, lung, pancreas, and liver cancer knowledge-based models. We then will disseminate and evaluate the effectiveness of the ORBITeR plan quality resource among the greater radiation oncology community. Finally, we will develop a quality analytics system to conduct widespread plan quality and patterns of care study across submitting sites on the ORBITeR system. .
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Distributed knowledge-based platform for radiotherapy plan quality control
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