A cine-EPID based method for jaw detection and quality assurance for tracking jaw in IMRT/VMAT treatments

T. Fuangrod, Pejman Rowshanfarzad, P.B. Greer, R.H. Middleton

    Research output: Contribution to journalArticlepeer-review

    16 Citations (Scopus)

    Abstract

    © 2014 Associazione Italiana di Fisica Medica. A new tool with the potential to verify and track jaw position during delivery has been developed. The method should be suitable for independent quality assurance for jaw position during jaw tracking dynamic IMRT and VMAT treatments. The jaw detection and tracking algorithm developed consists of five main steps. Firstly, the image is enhanced by removing a normalised predicted EPID image (that does not include the collimator transmission) from each cine EPID image. Then, using a histogram clustering technique a global intensity threshold level was determined. This threshold level was used to classify each pixel of the image as either under the jaws or under the MLC. Additionally, the collimator angle was automatically detected and used to rotate the image to vertical direction. Finally, this rotation allows the jaw positions to be determined using vertical and horizontal projection profiles. Nine IMRT fields (with static jaws) and a single VMAT clinical field (with dynamic jaws) were tested by determining the root mean square difference between planned and detected jaw positions. The test results give a detection accuracy of ±1mm RMS error for static jaw IMRT treatments and ±1.5mm RMS error for the dynamic jaw VMAT treatment. This method is designed for quality assurance and verification in modern radiation therapy; to detect the position of static jaws or verify the position of tracking jaws in more complex treatments. This method uses only information extracted from EPID images and it is therefore independent from the linear accelerator.
    Original languageEnglish
    Pages (from-to)16-24
    JournalPhysica Medica
    Volume31
    Issue number1
    DOIs
    Publication statusPublished - 2015

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