Clinical implications of different calculation algorithms in breast radiotherapy: A comparison between pencil beam and collapsed cone convolution |
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Affiliation: | 2. Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong;3. School of Medicine, University of Queensland, Australia |
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Abstract: | BackgroundThis investigation focused on the clinical implications of the use of the Collapsed Cone Convolution algorithm (CCC) in breast radiotherapy and investigated the dosimetric differences as respect to Pencil Beam Convolution algorithm (PBC).Material and methods15 breast treatment plans produced using the PBC algorithm were re-calculated using the CCC algorithm with the same MUs. In a second step, plans were re-optimized using CCC algorithm with modification of wedges and beam weightings to achieve optimal coverage (CCCr plans). For each patient, dosimetric comparison was performed using the standard tangential technique (SWT) and a forward-planned IMRT technique (f-IMRT).ResultsThe CCC algorithm showed significant increased dose inhomogeneity. Mean and minimum PTV doses decreased by 1.4% and 2.8% (both techniques). Mean V95% decreased to 83.7% and 90.3%, respectively for the SWT and f-IMRT. V95% was correlated to the ratio of PTV and lung volumes into the treatment field. The re-optimized CCCr plans achieved similar target coverage, but high-dose volume was significantly larger (V107%: 7.6% vs 2.3% (SWT), 7.1% vs 2.1% (f-IMRT). There was a significantly increase in the ipsilateral lung volume receiving low doses (V5 Gy: 31.3% vs 26.2% in SWT, 27.0% vs 23.0% in f-IMRT). MUs needed for PTV coverage in CCCr plans were higher by 3%.ConclusionsThe PBC algorithm overestimated PTV coverage in terms of all important dosimetric metrics. If previous clinical experience are based on the use of PBC model, especially needed is discussion between medical physicists and radiation oncologists to fully understand the dosimetric changes. |
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Keywords: | Collapsed cone Pencil beam Dose calculation algorithm Breast cancer |
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