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      Evolving treatment plan quality criteria from institution-specific experience.

      Medical physics
      Humans, Neoplasms, radiotherapy, Quality Control, Radiotherapy Planning, Computer-Assisted, standards

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          Abstract

          The dosimetric aspects of radiation therapy treatment plan quality are usually evaluated and reported with dose volume histogram (DVH) endpoints. For clinical practicality, a small number of representative quantities derived from the DVH are often used as dose endpoints to summarize the plan quality. National guidelines on reference values for such quantities for some standard treatment approaches are often used as acceptance criteria to trigger treatment plan review. On the other hand, treatment prescription and planning approaches specific to each institution warrants the need to report plan quality in terms of practice consistency and with respect to institution-specific experience. The purpose of this study is to investigate and develop a systematic approach to record and characterize the institution-specific plan experience and use such information to guide the design of plan quality criteria. In the clinical setting, this approach will assist in (1) improving overall plan quality and consistency and (2) detecting abnormal plan behavior for retrospective analysis. The authors propose a self-evolving methodology and have developed an in-house prototype software suite that (1) extracts the dose endpoints from a treatment plan and evaluates them against both national standard and institution-specific criteria and (2) evolves the statistics for the dose endpoints and updates institution-specific criteria. The validity of the proposed methodology was demonstrated with a database of prostate stereotactic body radiotherapy cases. As more data sets are accumulated, the evolving institution-specific criteria can serve as a reliable and stable consistency measure for plan quality and reveals the potential use of the "tighter" criteria than national standards or projected criteria, leading to practice that may push to shrink the gap between plans deemed acceptable and the underlying unknown optimality. The authors have developed a rationale to improve plan quality and consistency, by evolving the plan quality criteria from institution-specific experience, complementary to national standards. The validity of the proposed method was demonstrated with a prototype system on prostate stereotactic body radiotherapy (SBRT) cases. The current study uses direct and indirect DVH endpoints for plan quality evaluation, but the infrastructure proposed here applies to general outcome data as well. The authors expect forward evaluation together with intelligent update based on evidence-based learning, which will evolve the clinical practice for improved efficiency, consistency, and ultimately better treatment outcome.

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          Author and article information

          Journal
          22559641
          10.1118/1.4704497

          Chemistry
          Humans,Neoplasms,radiotherapy,Quality Control,Radiotherapy Planning, Computer-Assisted,standards

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