OBJECT: To compare the consistency of the agreement between the Convolution and TMR10 algorithms using a homogeneous phantom and to identify target characteristics that lead to large changes in target isodose coverage when the Convolution algorithm is used in GammaPlan as opposed to the TMR10 algorithm. METHODS: The IROC phantom end-to-end test was performed and RTDose for both the TMR10 and Convolution algorithm were submitted for comparison to the measurement. Treatment plans for 16 patients and 26 different targets were retrospectively re-calculated with the Convolution algorithm when originally planned with the TMR10 algorithm. Multivariate regression was used to find statistically significant predictors of loss in target prescription isodose coverage. RESULTS: Both algorithms agreed well with the IROC TLD measurement (within 1 %) and slightly better agreement was seen in the film analysis for the Convolution algorithm. After multivariate regression, small target volumes, < 1cm from air cavity, and minimum dose to target were potential predictors of large percentage loss of prescription isodose coverage (p = 0.049, 0.026, and 0.002, respectively). CONCLUSION: Convolution and TMR10 appear to be equivalent in homogeneous situations. Some target characteristics have been identified that might be indications for use of the Convolution algorithm in clinical practice.
OBJECT: To compare the consistency of the agreement between the Convolution and TMR10 algorithms using a homogeneous phantom and to identify target characteristics that lead to large changes in target isodose coverage when the Convolution algorithm is used in GammaPlan as opposed to the TMR10 algorithm. METHODS: The IROC phantom end-to-end test was performed and RTDose for both the TMR10 and Convolution algorithm were submitted for comparison to the measurement. Treatment plans for 16 patients and 26 different targets were retrospectively re-calculated with the Convolution algorithm when originally planned with the TMR10 algorithm. Multivariate regression was used to find statistically significant predictors of loss in target prescription isodose coverage. RESULTS: Both algorithms agreed well with the IROC TLD measurement (within 1 %) and slightly better agreement was seen in the film analysis for the Convolution algorithm. After multivariate regression, small target volumes, < 1cm from air cavity, and minimum dose to target were potential predictors of large percentage loss of prescription isodose coverage (p = 0.049, 0.026, and 0.002, respectively). CONCLUSION: Convolution and TMR10 appear to be equivalent in homogeneous situations. Some target characteristics have been identified that might be indications for use of the Convolution algorithm in clinical practice.
Authors: M Pearson; P Atherton; R McMenemin; F McDonald; G Mazdai; P Mulvenna; G Lambert Journal: Clin Oncol (R Coll Radiol) Date: 2009-01-22 Impact factor: 4.126