Search

Background: The requirement for precise and effective delivery of the actual dose to the patient grows along with the complexity of breast cancer radiotherapy. Dosimetry during treatment has become a crucial component of guaranteeing the efficacy and security. Purpose: To propose a dosimetry method during breast cancer radiotherapy based on body surface changes. Methods: A total of 29 left breast cancer radiotherapy cases were retroactively retrieved from an earlier database for analysis. Non‐rigid image registration and dose recalculation of the planning computed tomography (CT) referring to the Cone‐beam computed tomography were performed to obtain dose changes. The study used 3D point cloud feature extraction to characterize body surface changes. Based on the correlation proof, a mapping model is developed between body surface changes and dose changes using neural network framework. The MSE metrics, the Euclidean distances of feature points and the 3D gamma pass rate metric were used to assess the prediction accuracy. Results: A strong correlation exist between body surface changes and dose changes (first canonical correlation coefficient = 0.950). For the dose deformation field and dose amplitude difference in the test set, the MSE of the predicted and actual values were 0.136 pixels and 0.229 cGy, respectively. After deforming the planning dose into a deformed one, the feature points' Euclidean distance between it and the recalculated dose changes from 9.267 ± 1.879 mm to 0.456 ± 0.374 mm. The 3D gamma pass rate of 90% or higher for the 2 mm/2% criteria were achieved by 80.8% of all cases, with a minimum pass rate of 75.9% and a maximum pass rate of 99.6%. Pass rate for the 3 mm/2% criteria ranged from 87.8% to 99.8%, with 92.3% of the cases having a pass rate of 90% or higher. Conclusions: This study provides a dosimetry method that is non‐invasive, real‐time, and requires no additional dose for breast cancer radiotherapy. [ABSTRACT FROM AUTHOR]

Background: Retrospective studies indicate that radiation damage to left anterior descending coronary artery (LAD) may be critical for late‐stage radiation‐induced cardiac morbidity. Developing a method that accurately depicts LAD motion and perform dose assessment is crucial. Purpose: To construct a generalized cardiac surface motion model for LAD dose assessment in left breast cancer radiotherapy. Methods: Cine MRI of 25 cases were divided into training and testing sets for model construction, and five external cases were gathered for generalization validation. Motion prediction from average intensity projection images (AIP) surface point cloud to that of each phase was realized by mapping the relationship between datum points and corresponding points with statistical shape modeling (SSM). Root mean square error (RMSE) for predicted corresponding points and Euclidean distance (ED) for predicted surface point cloud were used to assess model's accuracy. LAD dose assessment for 10 left breast cancer radiotherapy cases was perform by model application. Results: The RMSE in testing cases and external cases were 0.209 ± 0.020 mm to 0.841 ± 0.074 mm and 0.895 ± 0.093 mm to 1.912 ± 0.138 mm, respectively; while the ED were 1.399 ± 0.029 mm to 1.658 ± 0.100 mm, 1.571 ± 0.080 mm to 1.779 ± 0.104 mm, respectively, proving the generalized model's high accuracy. The volume of LAD characterizing motion range (WPLAD) (2.392 ± 0.639 cm3) was approximately twice that of LAD from superimposed images (SPLAD) (0.927 ± 0.326 cm3) with p < 0.05, and the former's Dmax (3582.06 ± 575.92 cGy) was significantly larger than latter's (3222.71 ± 665.37 cGy) (p < 0.05). While WPLAD's Dmean (1408.06 ± 413.06 cGy) was slightly smaller than that of SPLAD (1504.15 ± 448.03 cGy), the difference did not reach statistical significance (p > 0.05). WPLAD's V20 (23.42% ± 16.62%) was less than SPLAD's (29.18% ± 21.07%) with p < 0.05, but their comparison in V30 and V40 did not yield statistically significant results. It implies the conventional LAD dose assessment ignores motion impact and may not be justified. Conclusions: The generalized cardiac surface motion model informs LAD dose accurate assessment in left breast cancer radiotherapy. [ABSTRACT FROM AUTHOR]