Dosimetric accuracy of the Convolution algorithm for Leksell Gamma Plan radiosurgery treatment planning: Evaluation in the presence of clinically relevant inhomogeneities.

PURPOSE: The Leksell Gamma Plan Convolution algorithm (LGP-Convolution) has not been widely adopted. This mainly stems from the higher calculated beam-on times relative to the standard ray tracing-based LGP-TMR10 dose calculation algorithm. This study aims to evaluate the accuracy of the LGP-Convolution in scenarios where the treated lesions are in the vicinity of or encompassed by bone and/or air inhomogeneities. METHODS: The solid water dosimetry phantom provided by the vendor was modified to include bone and air inhomogeneities. Two treatment planning scenarios were investigated involving a single shot and multiple shots, respectively. Treatment planning and dose prescription were performed using the LGP-Convolution algorithm. Triple channel film dosimetry was performed using GafChromic EBT3 films calibrated in terms of absorbed dose to water in a 60 Co beam. Monte Carlo (MC) simulation dosimetry was also performed in the inhomogeneous experimental geometry using the EGSnrc MC platform and a previously validated sector-based phase-space source model. MC simulations were also employed to determine correction factors required for converting EBT3 measurements at points within the bone and air inhomogeneities from dose-to-water values to the corresponding dose to medium values. RESULTS AND CONCLUSIONS: EBT3 dose to medium correction factors ranged with field size (4, 8, or 16 mm) within 0.941-0.946 for bone and 0.745-0.749 for air inhomogeneities. An excellent agreement was found between the LGP-Convolution calculations with corresponding EBT3 and MC dose to medium results at all measurement points, except those located inside the air inhomogeneity. The latter is of no clinical importance and excluding them yielded gamma index passing rates of nearly 100% for 3% local dose difference and 1 mm distance-to-agreement criteria. The excellent agreement observed between LGP-Convolution calculations and film as well as MC results of dose to medium indicates that the latter is the quantity reported by the LGP-Convolution.

Breast Cancer Classification on Multiparametric MRI - Increased Performance of Boosting Ensemble Methods.

Introduction: This study aims to assess the utility of Boosting ensemble classification methods for increasing the diagnostic performance of multiparametric Magnetic Resonance Imaging (mpMRI) radiomic models, in differentiating benign and malignant breast lesions. Methods: The dataset includes mpMR images of 140 female patients with mass-like breast lesions (70 benign and 70 malignant), consisting of Dynamic Contrast Enhanced (DCE) and T2-weighted sequences, and the Apparent Diffusion Coefficient (ADC) calculated from the Diffusion Weighted Imaging (DWI) sequence. Tumor masks were manually defined in all consecutive slices of the respective MRI volumes and 3D radiomic features were extracted with the Pyradiomics package. Feature dimensionality reduction was based on statistical tests and the Boruta wrapper. Hierarchical Clustering on Spearman's rank correlation coefficients between features and Random Forest classification for obtaining feature importance, were implemented for selecting the final feature subset. Adaptive Boosting (AdaBoost), Gradient Boosting (GB), Extreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM) classifiers, were trained and tested with bootstrap validation in differentiating breast lesions. A Support Vector Machine (SVM) classifier was also exploited for comparison. The Receiver Operator Characteristic (ROC) curves and DeLong's test were utilized to evaluate the classification performances. Results: The final feature subset consisted of 5 features derived from the lesion shape and the first order histogram of DCE and ADC images volumes. XGboost and LGBM achieved statistically significantly higher average classification performances [AUC = 0.95 and 0.94 respectively], followed by Adaboost [AUC = 0.90], GB [AUC = 0.89] and SVM [AUC = 0.88]. Conclusion: Overall, the integration of Ensemble Learning methods within mpMRI radiomic analysis can improve the performance of computer-assisted diagnosis of breast cancer lesions.

Dosimetric impact of rotational errors on the quality of VMAT-SRS for multiple brain metastases: Comparison between single- and two-isocenter treatment planning techniques.

PURPOSE: In the absence of a 6D couch and/or assuming considerable intrafractional patient motion, rotational errors could affect target coverage and OAR-sparing especially in multiple metastases VMAT-SRS cranial cases, which often involve the concurrent irradiation of off-axis targets. This work aims to study the dosimetric impact of rotational errors in such applications, under a comparative perspective between the single- and two-isocenter treatment techniques. METHODS: Ten patients (36 metastases) were included in this study. Challenging cases were only considered, with several targets lying in close proximity to OARs. Two multiarc VMAT plans per patient were prepared, involving one and two isocenters, serving as the reference plans. Different degrees of angular offsets at various orientations were introduced, simulating rotational errors. Resulting dose distributions were evaluated and compared using commonly employed dose-volume and plan quality indices. RESULTS: For single-isocenter plans and 1° rotations, plan quality indices, such as coverage, conformity index and D95% , deteriorated significantly (>5%) for distant targets from the isocenter (at> 4-6 cm). Contrarily, for two-isocenter plans, target distances to nearest isocenter were always shorter (≤4 cm), and, consequently, 1° errors were well-tolerated. In the most extreme case considered (2° around all axes) conformity index deteriorated by on-average 7.2%/cm of distance to isocenter, if one isocenter is used, and 2.6%/cm, for plans involving two isocenters. The effect is, however, strongly associated with target volume. Regarding OARs, for single-isocenter plans, significant increase (up to 63%) in Dmax and D0.02cc values was observed for any angle of rotation. Plans that could be considered clinically unacceptable were obtained even for the smallest angle considered, although rarer for the two-isocenter planning approach. CONCLUSION: Limiting the lesion-to-isocenter distance to ≤4 cm by introducing additional isocenter(s) appears to partly mitigate severe target underdosage, especially for smaller target sizes. If OAR-sparing is also a concern, more stringent rotational error tolerances apply.