An EPID response calculation algorithm using spatial beam characteristics of primary, head scattered and MLC transmitted radiation
- North Shore Cancer Center, 17 Centennial Drive, Peabody, Massachusetts 01960 (United States)
We have developed an independent algorithm for the prediction of electronic portal imaging device (EPID) response. The algorithm uses a set of images [open beam, closed multileaf collimator (MLC), various fence and modified sweeping gap patterns] to separately characterize the primary and head-scatter contributions to EPID response. It also characterizes the relevant dosimetric properties of the MLC: Transmission, dosimetric gap, MLC scatter [P. Zygmansky et al., J. Appl. Clin. Med. Phys. 8(4) (2007)], inter-leaf leakage, and tongue and groove [F. Lorenz et al., Phys. Med. Biol. 52, 5985-5999 (2007)]. The primary radiation is modeled with a single Gaussian distribution defined at the target position, while the head-scatter radiation is modeled with a triple Gaussian distribution defined downstream of the target. The distances between the target and the head-scatter source, jaws, and MLC are model parameters. The scatter associated with the EPID is implicit in the model. Open beam images are predicted to within 1% of the maximum value across the image. Other MLC test patterns and intensity-modulated radiation therapy fluences are predicted to within 1.5% of the maximum value. The presented method was applied to the Varian aS500 EPID but is designed to work with any planar detector with sufficient spatial resolution.
- OSTI ID:
- 21120740
- Journal Information:
- Medical Physics, Vol. 35, Issue 6; Other Information: DOI: 10.1118/1.2911870; (c) 2008 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); ISSN 0094-2405
- Country of Publication:
- United States
- Language:
- English
Similar Records
The impact of MLC transmitted radiation on EPID dosimetry for dynamic MLC beams
2D lag and signal nonlinearity correction in an amorphous silicon EPID and their impact on pretreatment dosimetric verification