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A computer aided treatment event recognition system in radiation therapy.
Xia, Junyi; Mart, Christopher; Bayouth, John.
Afiliación
  • Xia J; Department of Radiation Oncology, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, Iowa City, Iowa 52242.
  • Mart C; Department of Radiation Oncology, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, Iowa City, Iowa 52242.
  • Bayouth J; Department of Radiation Oncology, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, Iowa City, Iowa 52242 and Department of Human Oncology, University of Wisconsin - Madison, 600 Highland Avenue, K4∕B55, Madison, Wisconsin 53792-0600.
Med Phys ; 41(1): 011713, 2014 Jan.
Article en En | MEDLINE | ID: mdl-24387505
PURPOSE: To develop an automated system to safeguard radiation therapy treatments by analyzing electronic treatment records and reporting treatment events. METHODS: CATERS (Computer Aided Treatment Event Recognition System) was developed to detect treatment events by retrieving and analyzing electronic treatment records. CATERS is designed to make the treatment monitoring process more efficient by automating the search of the electronic record for possible deviations from physician's intention, such as logical inconsistencies as well as aberrant treatment parameters (e.g., beam energy, dose, table position, prescription change, treatment overrides, etc). Over a 5 month period (July 2012-November 2012), physicists were assisted by the CATERS software in conducting normal weekly chart checks with the aims of (a) determining the relative frequency of particular events in the authors' clinic and (b) incorporating these checks into the CATERS. During this study period, 491 patients were treated at the University of Iowa Hospitals and Clinics for a total of 7692 fractions. RESULTS: All treatment records from the 5 month analysis period were evaluated using all the checks incorporated into CATERS after the training period. About 553 events were detected as being exceptions, although none of them had significant dosimetric impact on patient treatments. These events included every known event type that was discovered during the trial period. A frequency analysis of the events showed that the top three types of detected events were couch position override (3.2%), extra cone beam imaging (1.85%), and significant couch position deviation (1.31%). The significant couch deviation is defined as the number of treatments where couch vertical exceeded two times standard deviation of all couch verticals, or couch lateral/longitudinal exceeded three times standard deviation of all couch laterals and longitudinals. On average, the application takes about 1 s per patient when executed on either a desktop computer or a mobile device. CONCLUSIONS: CATERS offers an effective tool to detect and report treatment events. Automation and rapid processing enables electronic record interrogation daily, alerting the medical physicist of deviations potentially days prior to performing weekly check. The output of CATERS could also be utilized as an important input to failure mode and effects analysis.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Planificación de la Radioterapia Asistida por Computador Límite: Humans Idioma: En Revista: Med Phys Año: 2014 Tipo del documento: Article Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Planificación de la Radioterapia Asistida por Computador Límite: Humans Idioma: En Revista: Med Phys Año: 2014 Tipo del documento: Article Pais de publicación: Estados Unidos