Abstract
A new Pinnacle 3D treatment‐planning system software release has recently become available (v7.4, Philips Radiation Oncology Systems, Milpitas, CA), which supports modeling of rounded multileaf collimator (MLC) leaf ends; it also includes a number of other software enhancements intended to improve the overall dose calculation accuracy. In this report, we provide a general discussion of the dose calculation algorithm and new beam‐modeling parameters. The accuracy of a diode dosimeter was established for measurement of MLC‐shaped beam profiles required by the new software version by comparison with film and ion chamber measurements in various regions of the field. The results suggest that a suitable diode or other small volume dosimeter with appropriate energy sensitivity should be used to obtain profiles for commissioning the planning system. Film should be used with caution, especially for larger field profile measurements. The dose calculation algorithm and modeling parameters chosen were validated through various test field measurements including a bar pattern, a strip pattern, and a clinical head and neck IMRT field. For the bar and strip patterns, the agreement between Pinnacle calculations and diode measurements was generally very good. These tests were helpful in establishing the new model parameter values, especially tongue‐and‐groove width, additional interleaf leakage, rounded leaf tip radius, and MLC transmission. For the clinical head and neck field, the comparison between Pinnacle and film measurements showed regions of approximately 2 cGy under‐ or overdose. However, the Pinnacle calculations agreed with diode measurements at all points to within 1 cGy or 1% of the maximum dose for the field (67 cGy). The greatest discrepancy between film and diode measurements for the clinical field (maximum of 2.8%) occurred in low‐dose regions in the central part of the field. The disagreement may be due to the overresponse of film to scattered radiation in the low‐dose regions, which have significant shielding by the MLCs.PACS numbers: 87.53.Bn, 87.53.Dq
Highlights
In a previous publication,(1) validation of sequential intensity-modulated radiation therapy (IMRT) with a commercial treatment-planning system was reported (Pinnacle, Philips Radiation Oncology Systems, Milpitas, CA)
Dose calculation algorithm and physics enhancements The convolution superposition dose algorithm consists of three parts: creation of an incident energy fluence map for a beam, the computation of a 3D TERMA grid by projecting the incident energy fluence through the patient representation, and superposition of the TERMA with a dose deposition kernel to compute the dose in the patient.[2,3,4,5,6] For IMRT, particular consideration is required for the modeling of the multileaf collimator (MLC) characteristics and the scatter and output effects of small MLC fields in larger jaw settings
We have provided a general discussion of the dose calculation algorithm and new beam-modeling parameters
Summary
In a previous publication,(1) validation of sequential intensity-modulated radiation therapy (IMRT) with a commercial treatment-planning system was reported (Pinnacle, Philips Radiation Oncology Systems, Milpitas, CA). The version of Pinnacle tested at that time, v6.2b, did not provide accurate modeling of the rounded leaf ends on the multileaf collimator (MLC) system tested (Millennium MLC, Varian Medical Systems, Palo Alto, CA). Dosimetric inaccuracies were reported and analyzed for calculations performed for sequential (step-and-shoot) IMRT that were directly attributable to the MLC leaf-modeling strategy implemented by Pinnacle at that time. A new software release has recently become available (v7.4) that supports modeling of rounded MLC leaf ends; the version includes a number of other software enhancements intended to improve the overall accuracy of dose calculation. We provide a general discussion of the dose calculation algorithm and new beam-modeling parameters. We validate the dose calculation algorithm and modeling parameters chosen, by performing various validation measurements
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