Plan Quality Metrics Research Articles

Feasibility Study of Beam Angle Optimization Based on Scripts in Automated-planning for Liver Cancer

To study the feasibility and potential benefits of beam angle optimization (BAO) to automated planning in liver cancer. An approach of beam angle sampling is proposed to implement BAO along with the module Auto-planning in treatment planning system (TPS) Pinnacle. An in-house developed plan quality metric (PQM) is taken as the preferred evaluating method during the sampling. The process is driven automatically by in-house made Pinnacle scripts both in sampling and scoring. In addition, dosimetry analysis and physician's opinion are also performed as the supplementary and compared with the result of PQM. It is revealed by the numerical analysis of PQM scores that only 15% patients whose superior trials evaluated by PQM are also the initial trials. Gantry optimization can bring benefit to plan quality along with auto-planning in liver cancer. Similar results are provided by both dose comparison and physician's opinion. It is possible to introduce a full automated approach of beam angle optimization to automated planning process. The advantages of this procedure can be observed both in numerical analysis and physician's opinion.

A study on inter-planner plan quality variability using a manual planning- or Lightning dose optimizer-approach for single brain lesions treated with the Gamma Knife® Icon™.

The purpose of this study is to investigate inter-planner plan quality variability using a manual forward planning (MFP)- or fast inverse planning (FIP, Lightning)-approach for single brain lesions treated with the Gamma Knife® (GK) Icon™. Thirty patients who were previously treated with GK stereotactic radiosurgery or radiotherapy were selected and divided into three groups (post-operative resection cavity, intact brain metastasis, and vestibular schwannoma [10 patients per group]). Clinical plans for the 30 patients were generated by multiple planners using FIP only (1), a combination of FIP and MFP (12), and MFP only (17). Three planners (Senior, Junior, and Novice) with varying experience levels re-planned the 30 patients using MFP and FIP (two plans per patient) with planning time limit of 60min. Statistical analysis was performed to compare plan quality metrics (Paddick conformity index, gradient index, number of shots, prescription isodose line, target coverage, beam-on-time (BOT), and organs-at-risk doses) of MFP or FIP plans among three planners and to compare plan quality metrics between each planner's MFP/FIP plans and clinical plans. Variability in FIP parameter settings (BOT, low dose, and target max dose) and in planning time among the planners was also evaluated. Variations in plan quality metrics of FIP plans among three planners were smaller than those of MFP plans for all three groups. Junior's MFP plans were the most comparable to the clinical plans, whereas Senior's and Novice's MFP plans were superior and inferior, respectively. All three planners' FIP plans were comparable or superior to the clinical plans. Differences in FIP parameter settings among the planners were observed. Planning time was shorter and variations in planning time among the planners were smaller for FIP plans in all three groups. The FIP approach is less planner dependent and more time-honored than the MFP approach.

Quantitative evaluation of radiotherapy plan in precise external beam radiotherapy process management for cervical cancer

To identify the problems in clinical radiotherapy planning for cervical cancer through quantitative evaluation of the radiotherapy plans to improve the quality of the plans and the radiotherapy process. We selected the clinically approved and administered radiotherapy plans for 227 cervical cancer patients undergoing external radiotherapy at Sun Yat-sen University Cancer Center from May, 2019 to January, 2022. These plans were transferred from the treatment planning system to the Plan IQTM workstation. The plan quality metrics were determined based on the guidelines of ICRU83 report, the GEC-ESTRO Working Group, and the clinical requirements of our center and were approved by a senior clinician. The problems in the radiotherapy plans were summarized and documented, and those with low scores were re-planned and the differences were analyzed. We identified several problems in the 277 plans by quantitative evaluation. Inappropriate target volume selection (with scores < 60) in terms of GTV, PGTV (CI) and PGTV (V66 Gy) was found in 10.6%, 65.2%, and 1% of the plans, respectively; and the PGTV (CI), GTV, and PCTV (D98%, HI) had a score of 0 in 0.4%, 10.1%, 0.4%, 0.4% of the plans, respectively. The problems in the organs at risk (OARs) involved mainly the intestines (the rectum, small intestine, and colon), found in 20.7% of the plans, and in occasional cases, the rectum, small intestine, colon, kidney, and the femoral head had a score of 0. Senior planners showed significantly better performance than junior planners in PGTV (V60 Gy, D98%), PCTV (CI), and CTV (D98%) (P≤0.046) especially in terms of spinal cord and small intestine protection (P≤0.034). The bowel (the rectum, small intestine and colon) dose was significantly lower in the prone plans than supine plans (P < 0.05), and targets coverage all met clinical requirements. Twenty radiotherapy plans with low scores were selected for re-planning. The re-planned plans had significantly higher GTV (Dmin) and PTV (V45 Gy, D98%) (P < 0.05) with significantly reduced doses of the small intestines (V40 Gy vs V30 Gy), the colon (V40 Gy vs V30 Gy), and the bladder (D35%) (P < 0.05). Quantitative evaluation of the radiotherapy plans can not only improve the quality of radiotherapy plan, but also facilitate risk management of the radiotherapy process.

Fully automated segmentally boosted VMAT.

Treatment planning for volumetric modulated arc therapy (VMAT) typically involves the use of multiple arcs to achieve sufficient intensity modulation. Alternatively, we can perform segment boosting to achieve similar intensity modulation while also reducing the number of control points used. Here, we propose the MetaPlanner Boosted VMAT (MPBV) approach, which generates boosted VMAT plans through a fully automated framework. The proposed MPBV approach is an open-source framework that consists of three main stages: meta-optimization of treatment plan hyperparameters, fast beam angle optimization on a coarse dose grid to select desirable segments for boosting, and final plan generation (i.e., constructing the boosted VMAT arc and performing optimization). Performance for the MPBV approach is evaluated on 21 prostate cases and 6 head and neck cases using clinically relevant plan quality metrics (i.e., target coverage, dose conformity, dose homogeneity, and OAR sparing). As compared to two baseline methods with multiple arcs, MPBV maintains or improves dosimetric performance for the evaluated metrics while substantially reducing average estimated delivery times (from 2.6 to 2.1 min). Our proposed MPBV approach provides an automated framework for producing high-quality VMAT plans that uses fewer control points and reduces delivery time as compared to traditional approaches with multiple arcs. MPBV applies automated treatment planning to segmentally boosted VMAT to address the beam utilization inefficiencies of traditional VMAT approaches that use multiple full arcs.

OptImal Gamma kNife lIghTnIng sOlutioN (IGNITION) score to characterize the solution space of the Gamma Knife FIP optimizer for stereotactic radiosurgery.

The objective of this study is to evaluate the user-defined optimization settings in the Fast Inverse Planning (FIP) optimizer in Leksell GammaPlan® and determine the parameters that result in the best stereotactic radiosurgery (SRS) plan quality for brain metastases, benign tumors, and arteriovenous malformations (AVMs). Thirty patients with metastases and 30 with benign lesions-vestibular schwannoma, AVMs, pituitary adenoma, and meningioma-treated with SRS were evaluated. Each target was planned by varying the low dose (LD) and beam-on-time (BOT) penalties in increments of 0.1, from 0 to 1. The following plan quality metrics were recorded for each plan: Paddick conformity index (PCI), gradient index (GI), BOT, and maximum organ-at-risk (OAR) doses. A novel objective score matrix was calculated for each target using a linearly weighted combination of the aforementioned metrics. A histogram of optimal solutions containing the five best scores was extracted. A total of 7260 plans were analyzed with 121 plans per patient for the range of LD/BOT penalties. The ranges of PCI, GI, and BOT across all metastatic lesions were 0.58-0.97, 2.1-3.8, and 8.8-238 min, respectively, and were 0.13-0.97, 2.1-3.8, and 8.8-238 min, respectively, for benign lesions. The objective score matrix showed unique optimal solutions for metastatic lesions and benign lesions. Additionally, the plan metrics of the optimal solutions were significantly improved compared to the clinical plans for metastatic lesions with equivalent metrics for all other cases. In this study, FIP optimizer was evaluated to determine the optimal solution space to maximize PCI and minimize GI, BOT and OAR doses simultaneously for single metastatic/benign/non-neoplastic targets. The optimal solution chart was determined using a novel objective score which provides novice and expert planners a roadmap to generate the most optimal plans efficiently using FIP.

Computational Analysis of Tumor Treating Fields for Non-Small Cell Lung Cancer in Full Thoracic Models

Tumor Treating Fields (TTFields) are alternating electric fields at 150 to 200 kHz that exert their anticancer effect by destroying tumor cells when they undergo mitosis. TTFields are currently being tested in patients with non-small cell lung cancer with advanced disease (NCT02973789) and those with brain metastasis (NCT02831959). However, the distribution of these fields within the thoracic compartment remains poorly understood. Using positron emission tomography-computed tomography image data sets obtained from a series of 4 patients with poorly differentiated adenocarcinoma, the positron emission tomography-positive gross tumor volume (GTV), clinical target volume (CTV), and structures from the chest surface to the intrathoracic compartment were manually segmented, followed by 3-dimensional physics simulation and computational modeling using finite element analysis. Electric field-volume histograms, specific absorption rate-volume histograms, and current density-volume histograms were generated to produce plan quality metrics (95%, 50%, and 5% volumes) for quantitative comparisons between models. Unlike other organs in the body, the lungs have a large volume of air, which has a very low electric conductivity value. Our comprehensive and individualized models demonstrated heterogeneity in electric field penetration to the GTVs with differences upwards of 200% and yielded a diverse range of TTFields distributions. Target contact with the conductive pleura intensified TTFields at the GTV and CTV. Furthermore, in a sensitivity analysis, varying electric conductivity and mass density of the CTV altered TTFields coverage to both the CTV and GTV. Personalized modeling is important to accurately estimate target coverage at the tumor volumes and surrounding normal tissue structures in the thorax.

The effect of integrating knowledge-based planning with multicriteria optimization in treatment planning for prostate SBRT.

Knowledge-based planning (KBP) and multicriteria optimization (MCO) are two powerful tools to assist treatment planners in achieving optimal target coverage and organ-at-risk (OAR) sparing. The purpose of this work is to investigate if integrating MCO with conventional KBP can further improve treatment plan quality for prostate cancer stereotactic body radiation therapy (SBRT). A two-phase study was designed to investigate the impact of MCO and KBP in prostate SBRT treatment planning. The first phase involved the creation of a KBP model based on thirty clinical SBRT plans, generated by manual optimization (KBP_M). A ten-patient validation cohort was used to compare manual, MCO, and KBP_M optimization techniques. The next phase involved replanning the original model cohort with additional tradeoff optimization via MCO to create a second model, KBP_MCO. Plans were then generated using linear integration (KBP_M+MCO), non-linear integration (KBP_MCO), and a combination of integration methods (KBP_MCO+MCO). All plans were analyzed for planning target volume (PTV) coverage, OAR constraints, and plan quality metrics. Comparisons were generated to evaluate plan and model quality. Phase 1 highlighted the necessity of KBP and MCO in treatment planning, as both optimization methods improved plan quality metrics (Conformity and Heterogeneity Indices) and reduced mean rectal dose by 2Gy, as compared to manual planning. Integrating MCO with KBP did not further improve plan quality, as little significance was seen over KBP or MCO alone. Principal component score (PCS) fitting showed KBP_MCO improved bladder and rectum estimated and modeled dose correlation by 5% and 22%, respectively; however, model improvements did not significantly impact plan quality. KBP and MCO have shown to reduce OAR dose while maintaining desired PTV coverage in this study. Further integration of KBP and MCO did not show marked improvements in treatment plan quality while requiring increased time in model generation and optimization time.

Updating a clinical Knowledge-Based Planning prediction model for prostate radiotherapy

Background and purposeClinical knowledge-based planning (KBP) models dedicated to prostate radiotherapy treatment may require periodical updates to remain relevant and to adapt to possible changes in the clinic. This study proposes a paired comparison of two different update approaches through a longitudinal analysis. Materials and methodsA clinically validated KBP model for moderately hypofractionated prostate therapy was periodically updated using two approaches: one was targeted at achieving the biggest library size (Mt), while the other one at achieving the highest mean sample quality (Rt). Four subsequent updates were accomplished. The goodness, robustness and quality of the outcomes were measured and compared to those of the common ancestor. Plan quality was assessed through the Plan Quality Metric (PQM) and plan complexity was monitored. ResultsBoth update procedures allowed for an increase in the OARs sparing between +3.9 % and +19.2 % compared to plans generated by a human planner. Target coverage and homogeneity slightly reduced [−0.2 %;−14.7 %] while plan complexity showed only minor changes.Increasing the sample size resulted in more reliable predictions and improved goodness-of-fit, while increasing the mean sample quality improved the outcomes but slightly reduced the models reliability. ConclusionsRepeated updates of clinical KBP models can enhance their robustness, reliability and the overall quality of automatically generated plans. The periodical expansion of the model sample accompanied by the removal of the unacceptable low quality plans should maximize the benefits of the updates while limiting the associated workload.

Impact of Plan Quality and Complexity Metrics on Gamma Passing Rate SIMT SRS Technique

<h3>Purpose/Objective(s)</h3> Multiple studies have reported different outcomes regarding the effect of plan complexity and quality metrics on gamma passing rate. However, there is very little information in literature regarding a single isocenter multitarget (SIMT) SRS technique. This study aims to evaluate the effect of different plan complexity metrics and quality metrics on gamma passing rate (GPR). Moreover, we aim to analyze the impact of distance to isocenter (DIS) & target size on plan quality metrics for the SIMT SRS technique. <h3>Materials/Methods</h3> 40 previously treated patient scans with 4–11 targets, an average volume of 1.2 cc and DIS range of 1.45 to 8.75 cm were used to create SIMT SRS in a treatment planning system (TPS) for a Linac using 6MV-FFF beam energy. In-house programs were developed to compute complexity metrics such as Plan averaged beam Area (PA), Plan averaged beam Irregularity (PI), Total MU, Leaf Travel (LT), mean Dose Rate variation (DR), mean Gantry Speed (GS) variation. Also, target volume, DIS, Paddick Conformity (PCI), and RTOG Conformity (RTOG_CI) indices were calculated per target & per plan. Paddick Gradient index (PGI) only was computed per plan. Patient QAs were then performed on a 4-D detector phantom using SNC software for comparison between measurements and calculated dose with objectives of 3%2mm & 10% threshold as per AAPM TG-218 recommendation. Spearman correlation was used for correlation and T-test for determining whether there are any statistically significant differences between the means of calculation per target vs per plan for PCI and RTOG_CI. <h3>Results</h3> The following results were observed: no correlation between GPR and PGI/RTOG_CI/number of targets/ target size, a positive but weak correlation between PCI & GPR (0.322, p-value = 0.023) and a negative weak correlation between DIS & GPR (-0.38, p-value = 0.01). However, a strong correlation was observed between target size & PCI/RTOG_CI/PGI (0.793, 0.719 & 0.636 respectively (p-value<0.001)), but no correlation between plan quality metrics and DIS. There was a positive weak correlation between GPR & DR/PA and a negative weak correlation between PI & GPR (0.35, 0.302 & -0.33 respectively). A moderate correlation was observed between GS & GPR (0.46, p-value= 0.0025), while no correlation was found between GPR & LT/total MU. Moreover, there was significant difference in mean PCI, RTOG_CI between per target and per plan. <h3>Conclusion</h3> GPR of SRS/SRT using single-isocenter VMAT for multiple targets is not associated with DIS, LT, total MU, and plan quality metrics. Also, DIS does not have any impact on plan quality metrics. Instead, there is a strong correlation between tumor volume & plan quality metrics, indicating volume is an important predictor for plan quality metrics. Moreover, DIS has a moderate impact on GPR, showing that a larger distance between target location and isocenter can result in lower GPR. For plan quality evaluation, calculation of PCI & RTOG_CI should be done per tumor.

An Optimal Solution Study on a Non-Invasive Stereotactic Radiosurgery Instrument Optimizer for Stereotactic Radiosurgery of Single Brain Metastasis

<h3>Purpose/Objective(s)</h3> This study looks at a fast inverse planning (FIP) optimizer that enables more efficient and less planner dependent stereotactic radiosurgery (SRS) treatment planning. FIP generates a plan using multiple user-inputted variables that affect plan quality metrics, such as target coverage (TC), maximum dose to the target and organs-at-risk, low dose (LD), and beam-on time (BOT). The objective of this study is to systematically characterize each of these variables and determine which combination leads to the best SRS plan quality metrics. <h3>Materials/Methods</h3> Thirty patients with a single brain metastasis who were previously treated with SRS were evaluated. Each lesion was planned using FIP by varying the LD and BOT variables in 0.1 increments from 0.0 to 1.0 (i.e., plan #1 [0.0, 0.0], plan #2 [0.0, 0.1], ..., plan #120 [1.0, 0.9] and plan #121 [1.0, 1.0]). All plans were generated with the same prescription dose (24 Gy/1 fraction), TC (100%), maximum allowed dose (43.2 Gy), and Gamma angle (90°). The following metrics were recorded for each plan to evaluate plan quality: Paddick conformity index (PCI), gradient index (GI), and BOT. Heat maps for each of the above metrics as a function of LD and BOT penalties were analyzed. An objective score matrix was calculated for each plan using a linear weighted combination of scaled and normalized GI, PCI, and BOT. An optimal solution space containing the 5 lowest values of the score matrix per patient was extracted. A frequency histogram was subsequently created in the LD-BOT coordinate space. <h3>Results</h3> The target volumes in the study ranged from 1.0 cc to 2.5 cc. For every patient, 121 plans were generated across the range of LD and BOT penalties, resulting in 3630 plans included in this analysis. The range of PCI, GI, and BOT across all plans were 0.71 to 0.95, 2.5 to 2.9, and 17.2 to 221 minutes, respectively. The variation of the LD/BOT penalties had a much larger impact resulting in a higher deviation about the mean for BOT (169%), followed by PCI (28%). Heat map analysis revealed that the plans that maximized PCI and minimized GI values occupied the upper triangular matrix of the LD/BOT penalty space, while plans that minimized BOT occupied the lower triangular space. The optimal solutions frequently occupied the diagonal space in between these zones. Specifically, the histogram analysis showed that 4 highest frequencies occurred at the user-inputted settings (LD, BOT) of (0.6, 0.5), (0.8, 0.6), (0.7, 0.5), and (0.7, 0.6), in order of plan quality. <h3>Conclusion</h3> In this study, the user-inputted variables (LD and BOT) were systematically varied to determine the optimal solutions to simultaneously maximize PCI while minimizing GI and BOT. The results of this study may permit SRS planners to generate single brain metastasis plans more efficiently using the study-defined optimal settings of LD and BOT.

Simulation-Free Online Adaption: An Accelerated Pathway to Palliative Radiotherapy

<h3>Purpose/Objective(s)</h3> Novel AI-assisted on-line adaptive radiotherapy, combined with a simulation-free planning approach, might provide rapid palliative radiotherapy treatment which will accommodate patient shape on day of treatment. This would eliminate the simulation appointment, reducing patient wait-time, as well as allow sophisticated treatment options (such as IMRT/VMAT, boost, dose escalation). This study reports on the feasibility of this novel pathway as well as early experience. We report on AI contouring accuracy, accuracy of synthetic CT, evaluation of auto-planning quality, and efficiency of this novel pathway. <h3>Materials/Methods</h3> A commercial on-line adaptive system that generates a plan of the day with AI contours and auto-planning was used for this work in combination with a test environment that replicated the system. Reference contours and planning was conducted on diagnostic CT, while on-couch adaptive sessions utilized the daily CBCT and generated synthetic CT. AI contouring accuracy was determined by comparing target and organ at risk (OAR) contours reviewed by a Clinician (supervised), to the AI-derived (unsupervised) contours using the Dice Similarity Co-efficient (DSC). The fidelity of the synthetic CT created for daily on-couch treatment planning was assessed by comparing AI contours (body and bones) to the CBCT structures as a surrogate for the underlying deformable registration using a Likert scale. Daily plan generation was evaluated against reference plan quality metrics for target and OAR structures. Efficiency of the adaptive treatment was measured for each human and system task in the treatment delivery pathway. <h3>Results</h3> Data is reported for 10 retrospective patients in our test system and 6 prospective patients treated at our Institution with an online adaptive system. These were abdominopelvic palliative lesions. Mean DSC for unsupervised targets and OAR (kidney, liver, bladder, rectum) were above 0.9, while duodenum and stomach contours required user intervention. The synthetic CT registration of diagnostic CT to CBCT was scored as locally aligned within 2mm for all prospective patients for body contour, however the bones did not replicate as well. This indicates for diagnostic CTs bones are not deformed well. The daily plans were generated were determined to have a conformity index and PTV V95% equivalent to reference plans. The adaptive process averaged 20 min (range 14 to 27 min). <h3>Conclusion</h3> Early results are encouraging and suggest that this novel AI-assisted online adaptive radiotherapy may be feasible for simulation-free dynamic palliative radiotherapy.

Evaluation of a hybrid automatic planning solution for rectal cancer

BackgroundScript-based planning and knowledge-based planning are two kinds of automatic planning solutions. Hybrid automatic planning may integrate the advantages of both solutions and provide a more robust automatic planning solution in the clinic. In this study, we evaluated and compared a commercially available hybrid planning solution with manual planning and script-based planning.MethodsIn total, 51 rectal cancer patients in our institution were enrolled in this study. Each patient generated 7 plans: one clinically accepted manual plan ({plan}_{manual}), three script-based plans and three hybrid plans generated with the volumetric-modulated arc therapy technique and 3 different clinical goal settings: easy, moderate and hard ({plan}_{hybrid}^{easy}, {plan}_{hybrid}^{moderate}, {plan}_{hybrid}^{hard}, {plan}_{script}^{easy}, {plan}_{script}^{moderate} and {plan}_{script}^{hard}). Planning goals included planning target volume (PTV) Dmax, bladder Dmean and femur head Dmean. The PTV prescription was the same (50.00 Gy) for the 3 goal settings. The hard setting required a lower PTV Dmax and stricter organ at risk (OAR) dose, while the easy setting was the opposite. Plans were compared using dose metrics and plan quality metric (PQM) scores, including bladder D15 and D50, left and right femur head D25 and D40, PTV D2, D98, CI (conformity index) and HI (homogeneity index).ResultsCompared to manual planning, hybrid planning with all settings significantly reduced the OAR dose (p < 0.05, paired t-test or Wilcoxon signed rank test) for all dose-volume indices, except D25 of the left femur head. For script-based planning, {plan}_{script}^{easy} significantly increased the OAR dose for the femur head and D2 and the PTV homogeneity index (p < 0.05, paired t-test or Wilcoxon signed rank test). Meanwhile, the maximum dose of the PTV was largely increased with hard script-based planning (D2 = 56.06 ± 7.57 Gy). For all three settings, the comparison of PQM between hybrid planning and script-based planning showed significant differences, except for D25 of the left femur head and PTV D2. The total PQM showed that hybrid planning could provide a better and more robust plan quality than script-based planning.ConclusionsThe hybrid planning solution was manual-planning comparable for rectal cancer. Hybrid planning can provide a better and more robust plan quality than script-based planning.

Comparison of anatomically informed class solution template trajectories with patient-specific trajectories for stereotactic radiosurgery and radiotherapy.

Class solution template trajectories are used clinically for efficiency, safety, and reproducibility. The aim was to develop class solutions for single cranial metastases radiotherapy/radiosurgery based on intracranial target positioning and compare to patient-specific trajectories in the context of 4π optimization. Template trajectories were constructed based on the open-source Montreal Neurological Institute (MNI) average brain. The MNI brain was populated with evenly spaced spherical target volumes (2 cm diameter, N = 243) and organs-at-risk (OARs) were identified. Template trajectories were generated for six anatomical regions (frontal, medial, and posterior, each with laterality dependence) based on previously published 4π optimization methods. Volumetric modulated arc therapy (VMAT) treatment plans generated using anatomically informed template 4π trajectories and patientspecific 4π trajectories were compared against VMAT plans from a standard four-arc template. Four-arc optimization techniques were compared to the standard VMAT template by placing three spherical targets in each of six anatomical regions of a test patient. This yielded 54 plans to compare various plan quality metrics. Increasing plan technique complexity, the total number of OAR maximum dose reductions compared to the standard arc template for the 6 anatomical classes was 4+/-2 (OFIXEDc) and 7+/-2 (OFIXEDi). In 65.6% of all cases, optimized fixed-couch positions outperformed the standard-arc template. Of the three comparisons, the most complex (OFIXEDi) showed the greatest statistical significance compared to the least complex (VMATi) across 12 plan quality metrics of maximum dose to each OAR, V12Gy, total plan Monitor Units, conformity index, and gradient index (p < 0.00417). In approximately 70% of all cases, 4π optimization methods outperformed the standard-arc template in terms of maximum dose reduction to OAR, by exclusively changing the arc geometry. We conclude that a tradeoff exists between complexity of a class solution methodology compared to patient-specific methods for arc selection, in the context of plan quality improvement.

Modulation of Tumor-Treating Fields by Cerebral Edema from Brain Tumors

PurposeCerebral edema is an important component of brain metastasis, and its presence may alter the distribution of tumor-treating fields (TTFields). We therefore performed a computational study to model the extent of this alteration according to various edema conditions associated with the metastasis. Methods and MaterialsPostacquisition magnetic resonance imaging data sets were obtained from 2 patients with solitary brain metastases from non-small cell lung cancer. After delineation of various anatomies, a 3-dimensional finite element mesh model was generated and then solved for the distribution of applied electric fields, rate of energy deposition, and current density at the gross tumor volume (GTV), edema, and other cranial structures. Electric field–volume histograms, specific absorption rate–volume histograms, and current density–volume histograms were generated, by which plan quality metrics were derived from and used to evaluate relative differences in field coverage between models under various conditions. ResultsChanges in the conductivity of cerebral edema altered the electric fields, rate of energy deposition, and current density at the GTV region. At the cerebral edema region, increasing electric conductivity of the edema only decreased the electric fields and rate of energy deposition while the current density increased. The ratio of edema-to-tumor is also important because the plan quality metrics increased linearly when the edema-to-GTV ratio decreased, and increased vice versa. Furthermore, a conductive necrotic core additionally altered the distribution of TTFields according to the plan quality metrics. ConclusionsOur modeling study demonstrated that cerebral edema alters the distribution of applied TTFields in patients. Personalized treatment planning will need to take into account the modulating effects of cerebral edema on TTFields as well as additional effects from a necrotic core inside the GTV.

Evaluation of a New Inverse, Globally Convex Treatment Planning System Algorithm for Gamma Knife Radiation Surgery Within a Prospective Trial: Advantages and Disadvantages in Practical Application

PurposeA new inverse planning software called IntuitivePlan (IP) based on a global convex optimization algorithm was adopted for the Gamma Knife radiation surgery. We investigated IP's suitability for daily clinical use and its applicability for different cerebral entities. Methods and MaterialsFor 230 target volumes, IP was tested in a prospective trial. The computed treatment plans were compared with conventional expert preplans, which included forward planning by the expert and local internal optimization. Based on the same dose constraints, we used the default settings for the inverse calculation of the treatment plans. Plan quality metrics such as the Paddick conformity index were compared for both planning techniques with additional subdivisions into the 3 selectable IP planning strategies and different entity groups. ResultsIP calculated treatment plans of quality similar to that of preplans created by expert planners. Some plan quality metrics, especially those related to conformity and dose gradient, attained statistically significantly higher scores combined with high coverage for the inversely generated plans except for the selectivity optimizing strategy. Normal brain volume receiving 10 Gy or 12 Gy or higher (V10Gy or V12Gy) did not show significant differences for the coverage optimizing strategies. The IP software demonstrated significantly shorter planning times versus manual planning as well as greater numbers of isocenters, often associated with longer treatment times. In terms of total time, these differences almost balanced out again. ConclusionsOur results suggest that IP is advantageous for complex tumors. We observed general clinical significance for conformity and superiority for the selectivity optimizing strategy. In addition, the high-quality calculation from IP enables novices in the profession to achieve pre-treatment plans of a quality similar to that of expert planners. IP allows for optimizing the sparing of surrounding tissue and conformity for benign tumors within a short time. Thus, IP forms a solid basis for further planning on the treatment day.

Intra-arc binary collimation with dynamic axes trajectory optimization for the SRS treatment of multiple metastases with multiple prescriptions.

This work generates multi-metastases cranial stereotactic radiosurgery/radiotherapy (SRS/SRT) plans using a novel treatment planning technique in which dynamic couch, collimator, and gantry trajectories are used with periodic binary target collimation. The performance of this planning technique is evaluated against conventional volumetric arc therapy (VMAT) planning in terms of various dose and plan quality metrics. A 3D cost space (referred to herein as the combined optimization of dynamic axes or CODA cube) was calculated based on an overlap between targets and organs-at-risk (OARs) and uncollimated areas between targets (island blocking) for all combinations of couch, gantry, and collimator angles. Gradient descent through the cube was applied to determine dynamic trajectories. At each control point (CP), each target can either be conformally treated or blocked by the multi-leaf collimator (referred to as intra-arc binary collimation, iABC). Simulated annealing was used to optimize the collimation patterns throughout the arcs as well as the monitor units (MUs) delivered at each CP. Seven previously treated VMAT plans were selected for comparison against the CODA-iABC planning technique. Two CODA-iABC plans were developed: a single gantry arc plan and a plan with one gantry arc and two couch arcs. Plan quality comparison metrics included maximum and mean dose to OARs (brainstem, chiasm, optic nerves, eyes, and lenses), the volume of normal brain receiving 12Gy (V12Gy), total MUs, target conformity, and dose-gradient index. Treatment plans generated with 1-arc CODA-iABC plans delivered an average of 21% and 30% higher maximum and mean doses to brainstem, respectively, when compared to VMAT plans. Treatment plans generated with 3-arc CODA-iABC used an average of 24% fewer MUs and resulted in an average reduction of 48% maximum dose and 50% mean dose to the OARs, when compared to VMAT. Target conformity values were worse in both CODA-iABC plans than VMAT by an average of 35% and 15%, respectively. There are no significant differences in V12Gy for all three planning techniques; however, 3-arc CODA-iABC is more effective at reducing dose to normal brain in the low-dose region (<12Gy). CODA-iABC is a novel planning technique that has been developed to automatically generate patient-specific multi-axis trajectories for multiple metastases cranial SRS/SRT. This work has demonstrated the feasibility of planning with this novel method. The 1-arc CODA-iABC planning technique is slightly dosimetric inferior to VMAT. With an increased sampling of a three-dimensional CODA cube by using a 3-arc CODA-iABC technique, there was improved total dose sparing to all the OARs and increased MU efficiency, but with a cost in target conformity, when compared to VMAT.

Plan Quality Assessment of Fractionated Stereotactic Radiotherapy Treatment Plans in Patients With Brain Metastases.

Background and PurposeThe treatment options available in the management of brain metastases includes fractionated stereotactic radiotherapy (FSRT) and stereotactic radiosurgery (SRS) treatments. FSRT treatments have proved to be useful mainly in the treatment of larger volumes. This study aims to evaluate the FSRT treatment technique used in our department based on various plan quality indices.Methods and Materials24 treatment plans of 23 patients were analyzed. Volumetric modulated arc therapy (VMAT) plans were generated in line with the department protocol. The following parameters were extracted: Radiation Therapy Oncology Group conformity index (RTOG CI), Paddick conformity index (Paddick CI), gradient index (GI), quality index (Q), homogeneity index (HI), and V24.4 volume as a parallel index of V12 used at SRS plan evaluation.ResultsPlan conformity was acceptable, RTOG CI mean was 0.942; Paddick CI mean was 0.824. The mean GI value was 6.146. The mean of HI and Q indices were 1.263 and 0.94, respectively. V24.4 mean was 33.434 cm3. All plans achieved clinically acceptable organs-at-risk (OAR) constraints. PTV volumes were clustered into either 10 cm3 or 15 cm3 bins depending on the plan quality metric we used. The mean values show a balanced distribution of plan indices along the various PTV bins.DiscussionOur results based on the derived indices show that our FSRT approach can achieve clinically acceptable treatment plans. Furthermore, the clustering of PTV volumes show that these plan quality metrics remain acceptable for a wide spectrum of PTV volumes.

Ramifications of Setup Margin Use During Frameless Stereotactic Radiosurgery/Therapy With Gamma Knife Icon Cone-Beam Computed Tomography (CBCT): A Dosimetric Study.

ObjectiveThe objective is to explore the possibility of optimal/rational application of setup margin during treatment planning for frameless stereotactic Gamma Knife radiosurgery/therapy.MethodsUncertainty measurements for frameless Gamma Knife Icon treatment were used to calculate the necessary setup margin via four different published recipes and these margins were subsequently applied to treatment plans of 30 previously treated patients and replans were generated meeting comparable plan quality metrics. All plans were then analyzed based on the ability to maintain normal tissue dose tolerances and the relative increase in target dose coverage probability using a pass/fail scoring system based on published normal tissue dose constraints and an in-house developed optimal scoring method.ResultsGross tumor volume/planning target volume (GTV/PTV) size strongly correlated with both meeting normal tissue tolerances and optimal scores for single fraction plans corroborating published clinical outcomes. The Van Herk Margin Formula (VHMF) and Parker margin formulae were indicated as good candidates for high probabilities of both meeting normal tissue goals and high optimal scores which generally translated to just over 1 mm in GTV to PTV margin.ConclusionFor single fraction treatment, GTV size is highly significant in predicting failure to meet normal tissue goals whereas whether setup margin was used was not a significant predictor. Setup margin can rationally be applied when fraction number is dictated by clinically indicated metrics regarding GTV size of greater or less than 4 cc. 1 mm is a reasonable practical application of margin added to GTV to ensure physical prescription dose target coverage for most cases when clinically desired based on disease type and intended outcome.

Integrated MRI‐guided proton therapy planning: Accounting for the full MRI field in a perpendicular system

To present a first study on the treatment planning feasibility in perpendicular field MRI-integrated proton therapy that considers the full transport of protons from the pencil beam scanning (PBS) assembly to the patient inside the MRIscanner. A generic proton PBS gantry was modeled as being integrated with a realistic split-bore MRI system in the perpendicular orientation. MRI field strengths were modeled as 0.5, 1, and 1.5T. The PBS beam delivery and dose calculation was modeled using the TOPAS Monte Carlo toolkit coupled with matRad as the optimizer engine. A water phantom, liver, and prostate plans were evaluated and optimized in the presence of the full MRI field distribution. A simple combination of gantry angle offset and small PBS nozzle skew was used to direct the proton beams along a path that closely follows the reference planning scenario, that is, without magneticfield. All planning metrics could be successfully achieved with the inclusion of gantry angle offsets in the range of 8 -29 when coupled with a PBS nozzle skew of 1.6 -4.4 . These two hardware-based corrections were selected to minimize the average Euclidean distance (AED) in the beam path enabling the proton beams to travel inside the patient in a path that is close to the original path (AED smaller than 3mm at 1.5T). Final dose optimization, performed through further changes in the PBS delivery, was then shown to be feasible for our selection of plans studied yielding comparable plan quality metrics to referenceconditions. For the first time, we have shown a robust method to account for the full proton beam deflection in a perpendicular orientation MRI-integrated proton therapy. These results support the ongoing development of the current prototypesystems.

Automatic Radiotherapy Planning for Glioblastoma Radiotherapy With Sparing of the Hippocampus and nTMS-Defined Motor Cortex.

BackgroundNavigated transcranial magnetic stimulation (nTMS) of the motor cortex has been successfully implemented into radiotherapy planning by a number of studies. Furthermore, the hippocampus has been identified as a radiation-sensitive structure meriting particular sparing in radiotherapy. This study assesses the joint protection of these two eloquent brain regions for the treatment of glioblastoma (GBM), with particular emphasis on the use of automatic planning.Patients and MethodsPatients with motor-eloquent brain glioblastoma who underwent surgical resection after nTMS mapping of the motor cortex and adjuvant radiotherapy were retrospectively evaluated. The radiotherapy treatment plans were retrieved, and the nTMS-defined motor cortex and hippocampus contours were added. Four additional treatment plans were created for each patient: two manual plans aimed to reduce the dose to the motor cortex and hippocampus by manual inverse planning. The second pair of re-optimized plans was created by the Auto-Planning algorithm. The optimized plans were compared with the “Original” plan regarding plan quality, planning target volume (PTV) coverage, and sparing of organs at risk (OAR).ResultsA total of 50 plans were analyzed. All plans were clinically acceptable with no differences in the PTV coverage and plan quality metrics. The OARs were preserved in all plans; however, overall the sparing was significantly improved by Auto-Planning. Motor cortex protection was feasible and significant, amounting to a reduction in the mean dose by >6 Gy. The dose to the motor cortex outside the PTV was reduced by >12 Gy (mean dose) and >5 Gy (maximum dose). The hippocampi were significantly improved (reduction in mean dose: ipsilateral >6 Gy, contralateral >4.6 Gy; reduction in maximum dose: ipsilateral >5 Gy, contralateral >5 Gy). While the dose reduction using Auto-Planning was generally better than by manual optimization, the radiated total monitor units were significantly increased.ConclusionConsiderable dose sparing of the nTMS-motor cortex and hippocampus could be achieved with no disadvantages in plan quality. Auto-Planning could further contribute to better protection of OAR. Whether the improved dosimetric protection of functional areas can translate into improved quality of life and motor or cognitive performance of the patients can only be decided by future studies.