A Novel Proton Pencil Beam Scanning FLASH RT Delivery Method Enables Optimal OAR Sparing and Ultra-High Dose Rate Delivery: A Comprehensive Dosimetry Study for Lung Tumors

Purpose: While transmission proton beams have been demonstrated to achieve ultra-high dose rate FLASH therapy delivery, they are unable to spare normal tissues distal to the target. This study aims to compare FLASH treatment planning using single energy Bragg peak proton beams versus transmission proton beams in lung tumors and to evaluate Bragg peak plan optimization, characterize plan quality, and quantify organ-at-risk (OAR) sparing. Materials and Methods: Both Bragg peak and transmission plans were optimized using an in-house platform for 10 consecutive lung patients previously treated with proton stereotactic body radiation therapy (SBRT). To bring the dose rate up to the FLASH-RT threshold, Bragg peak plans with a minimum MU/spot of 1200 and transmission plans with a minimum MU/spot of 400 were developed. Two common prescriptions, 34 Gy in 1 fraction and 54 Gy in 3 fractions, were studied with the same beam arrangement for both Bragg peak and transmission plans (n = 40 plans). RTOG 0915 dosimetry metrics and dose rate metrics based on different dose rate calculations, including average dose rate (ADR), dose-averaged dose rate (DADR), and dose threshold dose rate (DTDR), were investigated. We then evaluated the effect of beam angular optimization on the Bragg peak plans to explore the potential for superior OAR sparing. Results: Bragg peak plans significantly reduced doses to several OAR dose parameters, including lung V7.4Gy and V7Gy by 32.0% (p < 0.01) and 30.4% (p < 0.01) for 34Gy/fx plans, respectively; and by 40.8% (p < 0.01) and 41.2% (p < 0.01) for 18Gy/fx plans, respectively, compared with transmission plans. Bragg peak plans have ~3% less in DADR and ~10% differences in mean OARs in DTDR and DADR relative to transmission plans due to the larger portion of lower dose regions of Bragg peak plans. With angular optimization, optimized Bragg peak plans can further reduce the lung V7Gy by 20.7% (p < 0.01) and V7.4Gy by 19.7% (p < 0.01) compared with Bragg peak plans without angular optimization while achieving a similar 3D dose rate distribution. Conclusion: The single-energy Bragg peak plans achieve superior dosimetry performances in OARs to transmission plans with comparable dose rate performances for lung cancer FLASH therapy. Beam angle optimization can further improve the OAR dosimetry parameters with similar 3D FLASH dose rate coverage.

Dose Prediction Models Based on Geometric and Plan Optimization Parameter for Adjuvant Radiotherapy Planning Design in Cervical Cancer Radiotherapy

The prediction of an additional space for the dose sparing of organs at risk (OAR) in radiotherapy is still difficult. In this pursuit, the present study was envisaged to find out the factors affecting the bladder and rectum dosimetry of cervical cancer. Additionally, the relationship between the dose-volume histogram (DVH) parameters and the geometry and plan dose-volume optimization parameters of the bladder/rectum was established to develop the dose prediction models and guide the planning design for lower OARs dose coverage directly. Thirty volume modulated radiation therapy (VMAT) plans from cervical cancer patients were randomly chosen to build the dose prediction models. The target dose coverage was evaluated. Dose prediction models were established by univariate and multiple linear regression among the dosimetric parameters of the bladder/rectum, the geometry parameters (planning target volume (PTV), volume of bladder/rectum, overlap volume of bladder/rectum (OV), and overlapped volume as a percentage of bladder/rectum volume (OP)), and corresponding plan dose-volume optimization parameters of the nonoverlapping structures (the structure of bladder/rectum outside the PTV (NOS)). Finally, the accuracy of the prediction models was evaluated by tracking d = (predicted dose-actual dose)/actual in additional ten VMAT plans. V30, V35, and V40 of the bladder and rectum were found to be multiple linearly correlated with the relevant OP and corresponding dose-volume optimization parameters of NOS (regression R2 > 0.99, P < 0.001 ). The variations of these models were less than 0.5% for bladder and rectum. Percentage of bladder and rectum within the PTV and the dose-volume optimization parameters of NOS could be used to predict the dose quantitatively. The parameters of NOS as a limited condition could be used in the plan optimization instead of limiting the dose and volume of the entire OAR traditionally, which made the plan optimization more unified and convenient and strengthened the plan quality and consistency.

Optimization of Stop Plan for Skip-Stop Operation on Suburban Railway Line

A combination of express and local trains (E/L mode) is generally used to operate a suburban rail service, it can meet the rapid and direct service needs of long-distance travelers as well the needs of short-distance travelers. Generally, a stop plan is the core of the E/L mode. A stop plan optimization model in E/L mode, which aims to minimize the total passenger travel time and the number of operating trains during the peak period with the safe headway and departure frequency constraints, is proposed in this study. Meanwhile, an algorithm based on a genetic algorithm is designed to solve the proposed model. A case study of the Jiangjin Line, a suburban railway in Chongqing, China, is carried out. The results show the efficiency and feasibility of the proposed method. The calculation results also show that the total passenger travel time under E/L mode with the overtaking condition is significantly reduced compared with the all-stops (AS) mode and E/L mode without overtaking condition. The superiority of the E/L mode can be enhanced by reducing the dwell time at stations and adopting the overtaking condition.

Comparison of Dosimetric Benefits of Three Precise Radiotherapy Techniques in Nasopharyngeal Carcinoma Patients Using a Priority-Classified Plan Optimization Model

IntroductionAlthough intensity-modulated radiotherapy (IMRT), volumetric-modulated arc therapy (VMAT) and tomotherapy (TOMO) are broadly applied for nasopharyngeal carcinoma (NPC), the best technique remains unclear. Therefore, this study was conducted to address this issue.MethodsThe priority-classified plan optimization model was applied to IMRT, VMAT and TOMO plans in forty NPC patients according to the latest international guidelines. And the dosimetric parameters of planning target volumes (PTVs) and organs at risk (OARs) were compared among these three techniques. The Friedman M test in SPSS software was applied to assess significant differences.ResultsThe median PGTVnx coverage of IMRT was the lowest (93.5%, P &lt; 0.001) for all T categories. VMAT was comparable to TOMO in OARs clarified as priority I and II, and both satisfied the prescribed requirement. IMRT resulted in a relatively high dose for V25 and V30. Interestingly, subgroup analysis showed that the median PTV coverage of the three techniques was no less than 95% in the early T stage. The heterogeneity index (HI) of PGTVnx in VMAT was better than that in IMRT (P = 0.028). Compared to TOMO, VMAT showed a strong ability to protect eyesight and decrease low-dose radiation volumes. In the advanced T stage subgroup, TOMO numerically achieved the highest median PGTVnx coverage volume compared with VMAT and IMRT (93.61%, 91% and 90%, respectively). The best CI and HI of PCTV-1 were observed in TOMO. Furthermore, TOMO was better than VMAT for sparing the brain stem, spinal cord and temporal lobes (all P &lt; 0.05). However, the median V5, V10, V15, V20 and V25 were significantly higher with TOMO than with VMAT (all P &lt; 0.05).ConclusionIn the early T stage, VMAT provides a similar dose coverage and protection of OARs to IMRT, and there are no obvious advantages to choosing TOMO for NPC patients in the early T stage. TOMO may be recommended for patients in the advanced T stage due as it provides the largest dose coverage of PGTVnx and the best protection of the brain stem, spinal cord and temporal lobes. Additionally, more randomized clinical trials are needed for further clarification.

Outcome-based multi-objective optimization of lymphoma radiation therapy plans

At its core, radiation therapy (RT) requires balancing therapeutic effects against risk of adverse events in cancer survivors. The radiation oncologist weighs numerous disease and patient-level factors when considering the expected risk-benefit ratio of combined treatment modalities. As part of this, RT plan optimization software is used to find a clinically acceptable RT plan delivering a prescribed dose to the target volume while respecting pre-defined radiation dose-volume constraints for selected organs at risk. The obvious limitation to the current approach is that it is virtually impossible to ensure the selected treatment plan could not be bettered by an alternative plan providing improved disease control and/or reduced risk of adverse events in this individual. Outcome-based optimization refers to a strategy where all planning objectives are defined by modeled estimates of a specific outcome’s probability. Noting that various adverse events and disease control are generally incommensurable, leads to the concept of a Pareto-optimal plan: a plan where no single objective can be improved without degrading one or more of the remaining objectives. Further benefits of outcome-based multi objective optimization are that quantitative estimates of risks and benefit are obtained as are the effects of choosing a different trade-off between competing objectives. Furthermore, patient-level risk factors and combined treatment modalities are integrated directly into plan optimization. Here, we present this approach in the clinical setting of multi modality therapy for malignant lymphoma, a malignancy with marked heterogeneity in biology, target localization, and patient characteristics. We discuss future research priorities including the potential of artificial intelligence.

Replacing Manual Planning of Whole Breast Irradiation With Knowledge-Based Automatic Optimization by Virtual Tangential-Fields Arc Therapy

PurposeTo implement Knowledge Based (KB) automatic planning for right and left-sided whole breast treatment through a new volumetric technique (ViTAT, Virtual Tangential-fields Arc Therapy) mimicking conventional tangential fields (TF) irradiation.Materials and MethodA total of 193 clinical plans delivering TF with wedged or field-in-field beams were selected to train two KB-models for right(R) and left(L) sided breast cancer patients using the RapidPlan (RP) tool implemented in the Varian Eclipse system. Then, a template for ViTAT optimization, incorporating individual KB-optimized constraints, was interactively fine-tuned. ViTAT plans consisted of four arcs (6 MV) with start/stop angles consistent with the TF geometry variability within our population; the delivery was completely blocked along the arcs, apart from the first and last 20° of rotation for each arc. Optimized fine-tuned KB templates for automatic plan optimization were generated. Validation tests were performed on 60 new patients equally divided in R and L breast treatment: KB automatic ViTAT-plans (KB-ViTAT) were compared against the original TF plans in terms of OARs/PTVs dose-volume parameters. Wilcoxon-tests were used to assess the statistically significant differences.ResultsKB models were successfully generated for both L and R sides. Overall, 1(3%) and 7(23%) out of 30 automatic KB-ViTAT plans were unacceptable compared to TF for R and L side, respectively. After the manual refinement of the start/stop angles, KB-ViTAT plans well fitted TF-performances for these patients as well. PTV coverage was comparable, while PTV D1% was improved with KB-ViTAT by R:0.4/L:0.2 Gy (p &lt; 0.05); ipsilateral OARs Dmean were similar with a slight (i.e., few % volume) improvement/worsening in the 15–35 Gy/2–15 Gy range, respectively. KB-ViTAT better spared contralateral OARs: Dmean of contralateral OARs was 0.1 Gy lower (p &lt; 0.05); integral dose was R:5%/L:8% lower (p &lt; 0.05) than TF. The overall time for the automatic plan optimization and final dose calculation was 12 ± 2 minutes.ConclusionsFully automatic KB-optimization of ViTAT can efficiently replace manually optimized TF planning for whole breast irradiation. This approach was clinically implemented in our institute and may be suggested as a large-scale strategy for efficiently replacing manual planning with large sparing of time, elimination of inter-planner variability and of, seldomly occurring, sub-optimal manual plans.