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Background and purpose: This study aimed to investigate the feasibility of safe-dose escalation to dominant intraprostatic lesions (DILs) and assess the clinical impact using dose-volume (DV) and biological metrics in photon and proton therapy. Biological parameters defined as late grade ≥ 2 gastrointestinal (GI) and genitourinary (GU) derived from planned (DP) and accumulated dose (DA) were utilized. Materials and methods: In total, 10 patients with high-risk prostate cancer with multiparametric MRI-defined DILs were investigated. Each patient had two plans with a focal boost to the DILs using intensity-modulated proton therapy (IMPT) and volumetric-modulated arc therapy (VMAT). Plans were optimized to obtain DIL coverage while respecting the mandatory organ-at-risk constraints. For the planning evaluation, DV metrics, tumor control probability (TCP) for the DILs and whole prostate excluding the DILs (prostate-DILs), and normal tissue complication probability (NTCP) for the rectum and bladder were calculated. Wilcoxon signed-rank test was used for analyzing TCP and NTCP data. Results: IMPT achieved a higher Dmean for the DILs compared to VMAT (IMPT: 68.1 GyRBE vs. VMAT: 66.6 Gy, p < 0.05). Intermediate-high rectal and bladder doses were lower for IMPT (p < 0.05), while the high-dose region (V60 Gy) remained comparable. IMPT-TCP for prostate-DIL were higher compared to VMAT (IMPT: 86%; α/β = 3, 94.3%; α/β = 1.5 vs. VMAT: 84.7%; α/β = 3, 93.9%; α/β = 1.5, p < 0.05). Likewise, IMPT obtained a moderately higher DIL TCP (IMPT: 97%; α/β = 3, 99.3%; α/β = 1.5 vs. VMAT: 95.9%; α/β = 3, 98.9%; α/β = 1.5, p < 0.05). Rectal DA-NTCP displayed the highest GI toxicity risk at 5.6%, and IMPT has a lower GI toxicity risk compared to VMAT-predicted Quantec-NTCP (p < 0.05). Bladder DP-NTCP projected a higher GU toxicity than DA-NTCP, with VMAT having the highest risk (p < 0.05). Conclusion: Dose escalation using IMPT is able to achieve a high TCP for the DILs, with the lowest rectal and bladder DV doses at the intermediate-high-dose range. The reduction in physical dose was translated into a lower NTCP (p < 0.05) for the bladder, although rectal toxicity remained equivalent. [ABSTRACT FROM AUTHOR]

Objective: This work aims to use machine learning models to predict gamma passing rate of portal dosimetry quality assurance with log file derived features. This allows daily treatment monitoring for patients and reduce wear and tear on EPID detectors to save cost and prevent downtime. Methods: 578 VMAT trajectory log files selected from prostate, lung and spine SBRT were used in this work. Four machine learning models were explored to identify the best performing regression model for predicting gamma passing rate within each sub-site and the entire unstratified data. Predictors used in these models comprised of hand-crafted log file-derived features as well as modulation complexity score. Cross validation was used to evaluate the model performance in terms of R² and RMSE. Result: Using gamma passing rate of 1%/1mm criteria and entire dataset, LASSO regression has a R² of 0.121 ± 0.005 and RMSE of 4.794 ± 0.013%, SVM regression has a R² of 0.605 ± 0.036 and RMSE of 3.210 ± 0.145%, Random Forest regression has a R² of 0.940 ± 0.019 and RMSE of 1.233 ± 0.197%. XGBoost regression has the best performance with a R² and RMSE value of 0.981 ± 0.015 and 0.652 ± 0.276%, respectively. Conclusion: Log file-derived features can predict gamma passing rate of portal dosimetry with an average error of less than 2% using the 1%/1mm criteria. This model can potentially be applied to predict the patient specific QA results for every treatment fraction. [ABSTRACT FROM AUTHOR]

Background and purpose: Normal tissue complication probability (NTCP) parameters derived from traditional 3D plans may not be ideal in defining toxicity outcomes for modern radiotherapy techniques. This study aimed to derive parameters of the Lyman-Kutcher-Burman (LKB) NTCP model using prospectively scored clinical data for late gastrointestinal (GI) and genitourinary (GU) toxicities for high-risk prostate cancer patients treated using volumetricmodulated-arc-therapy (VMAT). Dose-volume-histograms (DVH) extracted from planned (DP) and accumulated dose (DA) were used. Material and methods: DP and DA obtained from the DVH of 150 prostate cancer patients with pelvic-lymph-nodes irradiation treated using VMAT were used to generate LKB-NTCP parameters using maximum likelihood estimations. Defined GI and GU toxicities were recorded up to 3-years post RT follow-up. Model performance was measured using Hosmer-Lemeshow goodness of fit test and the mean area under the receiver operating characteristics curve (AUC). Bootstrapping method was used for internal validation. Results: For mild-severe (Grade =1) GI toxicity, the model generated similar parameters based on DA and DP DVH data (DA-D50:71.6 Gy vs DP-D50:73.4; DAm: 0.17 vs DP-m:0.19 and DA/P-n 0.04). The 95% CI for DA-D50 was narrower and achieved an AUC of >0.6. For moderate-severe (Grade =2) GI toxicity, DAD50 parameter was higher and had a narrower 95% CI (DA-D50:77.9 Gy, 95% CI:76.4-79.6 Gy vs DP-D50:74.6, 95% CI:69.1-85.4 Gy) with good model performance (AUC>0.7). For Grade =1 late GU toxicity, D50 and n parameters for DA and DP were similar (DA-D50: 58.8 Gy vs DP-D50: 59.5 Gy; DA-n: 0.21 vs DP-n: 0.19) with a low AUC of<0.6. For Grade =2 late GU toxicity, similar NTCP parameters were attained from DA and DP DVH Data (DA-D50:81.7 Gy vs DPD50: 81.9 Gy; DA-n:0.12 vs DP-n:0.14) with an acceptable AUCs of >0.6. Conclusions: The achieved NTCP parameters using modern RT techniques and accounting for organmotion differs from QUANTEC reported parameters. DA-D50 of 77.9 Gy for GI and DA/DP-D50 of 81.7-81.9 Gy for GU demonstrated good predictability in determining the risk of Grade =2 toxicities especially for GI derived D50 and are recommended to incorporate as part of the DV planning constraints to guide dose escalation strategies while minimising the risk of toxicity. [ABSTRACT FROM AUTHOR]

Background: This study aims to explore the role of four-dimensional (4D) transperineal ultrasound (TPUS) in the contouring of prostate gland with planning computed tomography (CT) images, in the absence of magnetic resonance imaging (MRI). Materials and methods: Five radiation oncologists (ROs) performed two rounds of prostate gland contouring (single-blinded) on CT-alone and CT/TPUS datasets obtained from 10 patients who underwent TPUS-guided external beam radiotherapy. Parameters include prostate volume, DICE similarity coefficient (DSC) and centroid position. Wilcoxon signed-rank test assessed the significance of inter-modality differences, and the intraclass correlation coefficient (ICC) reflected inter- and intra-observer reliability of parameters. Results: Inter-modality analysis revealed high agreement (based on DSC and centroid position) of prostate gland contours between CT-alone and CT/TPUS. Statistical significant difference was observed in the superior-inferior direction of the prostate centroid position (p = 0.011). All modalities yielded excellent inter-observer reliability of delineated prostate volume with ICC > 0.9, mean DSC > 0.8 and centroid position: CT-alone (ICC = 1.000) and CT/TPUS (ICC = 0.999) left-right (L/R); CT-alone (ICC = 0.999) and CT/TPUS (ICC = 0.998) anterior-posterior (A/P); CT-alone (ICC = 0.999) and CT/TPUS (ICC = 1.000) superior-inferior (S/I). Similarly, all modalities yielded excellent intra-observer reliability of delineated prostate volume, ICC > 0.9 and mean DSC > 0.8. Lastly, intra-observer reliability was excellent on both imaging modalities for the prostate centroid position, ICC > 0.9. Conclusion: TPUS does not add significantly to the amount of anatomical information provided by CT images. However, TPUS can supplement planning CT to achieve a higher positional accuracy in the S/I direction if access to CT/MRI fusion is limited. [ABSTRACT FROM AUTHOR]

Biological uncertainty remains one of the main sources of uncertainties in proton therapy, and is encapsulated in a scalar quantity known as relative biological effective (RBE). It is currently recognised that a constant RBE of 1.1 is not consistent with radiobiological experiment and may lead to sub-optimal exploitation of the benefits of proton therapy. To overcome this problem, several RBE models have been developed, and in most of these models, there is a dependence of RBE on dose-averaged linear energy transfer (LET), . In this work, we show that the estimation in these models during the data-fitting (or parameter estimation) phase could be subjected to a huge uncertainty due to not taking into account cellular materials during simulation, and this uncertainty can propagate down to the resulting RBE models. The dosimetric impact of this uncertainty is then evaluated on a simple clinical spread out Bragg peak (SOBP) and a prostate example. Our simulation shows that uncertainty due to the use of water as cellular material is non-negligible under low and low dose (2 Gy), and can be neglected otherwise. Thus, this study indicates that further dose and range margins may be required for low target under low dose. This is due to greater uncertainties in RBE model associated with incomplete knowledge of cellular composition for computation. [ABSTRACT FROM AUTHOR]