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A quantitative evaluation of the performances of the deformable image registration (DIR) algorithm implemented in MIM-Maestro was performed using multiple similarity indices. Two phantoms, capable of mimicking different anatomical bending and tumor shrinking were built and computed tomography (CT) studies were acquired after applying different deformations. Three different contrast levels between internal structures were artificially created modifying the original CT values of one dataset. DIR algorithm was applied between datasets with increasing deformations and different contrast levels and manually refined with the Reg Refine tool. DIR algorithm ability in reproducing positions, volumes, and shapes of deformed structures was evaluated using similarity indices such as: landmark distances, Dice coefficients, Hausdorff distances, and maximum diameter differences between segmented structures. Similarity indices values worsen with increasing bending and volume difference between reference and target image sets. Registrations between images with low contrast (40 HU) obtain scores lower than those between images with high contrast (970 HU). The use of Reg Refine tool leads generally to an improvement of similarity parameters values, but the advantage is generally less evident for images with low contrast or when structures with large volume differences are involved. The dependence of DIR algorithm on image deformation extent and different contrast levels is well characterized through the combined use of multiple similarity indices., (© 2019 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.)

Purpose: Patient‐specific quality assurance (QA) is very important in radiotherapy, especially for patients with highly conformed treatment plans like VMAT plans. Traditional QA protocols for these plans are time‐consuming reducing considerably the time available for patient treatments. In this work, a new MC‐based secondary dose check software (SciMoCa) is evaluated and benchmarked against well‐established TPS (Monaco and Pinnacle3) by means of treatment plans and dose measurements. Methods: Fifty VMAT plans have been computed using same calculation parameters with SciMoCa and the two primary TPSs. Plans were validated with measurements performed with a 3D diode detector (ArcCHECK) by translating patient plans to phantom geometry. Calculation accuracy was assessed by measuring point dose differences and gamma passing rates (GPR) from a 3D gamma analysis with 3%–2 mm criteria. Comparison between SciMoCa and primary TPS calculations was made using the same estimators and using both patient and phantom geometry plans. Results: TPS and SciMoCa calculations were found to be in very good agreement with validation measurements with average point dose differences of 0.7 ± 1.7% and −0.2 ± 1.6% for SciMoCa and two TPSs, respectively. Comparison between SciMoCa calculations and the two primary TPS plans did not show any statistically significant difference with average point dose differences compatible with zero within error for both patient and phantom geometry plans and GPR (98.0 ± 3.0% and 99.0 ± 3.0% respectively) well in excess of the typical 95%clinical tolerance threshold. Conclusion: This work presents results obtained with a significantly larger sample than other similar analyses and, to the authors' knowledge, compares SciMoCa with a MC‐based TPS for the first time. Results show that a MC‐based secondary patient‐specific QA is a clinically viable, reliable, and promising technique, that potentially allows significant time saving that can be used for patient treatment and a per‐plan basis QA that effectively complements traditional commissioning and calibration protocols. [ABSTRACT FROM AUTHOR]

Background and Purpose: In our institute, breast cancer patients undergoing adjuvant treatment are included in a protocol aimed to reduce cardiovascular morbidity (SAFE-2014, NCT2236806), assessing preclinical heart damage with heart speckle-tracking ultrasound. To develop a dose constraint related to subclinical heart damage, a reliable delineation of heart substructures based on a pre-existing guideline was made.Patients and Methods: Heart substructures of 16 left-sided breast cancer patients included in the SAFE protocol were delineated by five operators. For each substructure, a multi-contour delineation based on a majority vote algorithm (MCD) was created. A consensus-based delineation (CBD) was developed by an independent team of two blinded operators. Dice similarity coefficients (DSC) between volumes delineated by different operators and the MCD were collected and reported, as well as DSC between CBD and MCD.Results: Mean DSCs between heart chambers delineated by each operator and the corresponding MCDs ranged between 0.78 and 0.96. Mean DSC between substructures delineated by all single operators and the corresponding MCD ranged between 0.84 and 0.94. Mean DSC between CBD and the corresponding MCD ranged from 0.89 to 0.97.Conclusion: Results showed low inter-observer variability of heart substructure delineation. This constitutes an external validation of the contouring atlas used, allowing a reliable dosimetric assessment of these volumes within the SAFE-2014 trial. [ABSTRACT FROM AUTHOR]