Enhancing Radiotherapy for Locally Advanced Non-Small Cell Lung Cancer Patients with iCE, a Novel System for Automated Multi-Criterial Treatment Planning Including Beam Angle Optimization.
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ABSTRACT:
SUBMITTER: Fjellanger K
PROVIDER: S-EPMC8616198 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundWith the large-scale introduction of volumetric modulated arc therapy (VMAT), selection of optimal beam angles for coplanar static-beam IMRT has increasingly become obsolete. Due to unavailability of VMAT in current MR-linacs, the problem has re-gained importance. An application for automated IMRT treatment planning with integrated, patient-specific computer-optimization of beam angles (BAO) was used to systematically investigate computer-aided generation of beam angle class solutions (CS) for replacement of computationally expensive patient-specific BAO. Rectal cancer was used as a model case.Materials and methods23 patients treated at a Unity MR-linac were included. BAOx plans (x=7-12 beams) were generated for all patients. Analyses of BAO12 plans resulted in CSx class solutions. BAOx plans, CSx plans, and plans with equi-angular setups (EQUIx, x=9-56) were mutually compared.ResultsFor x>7, plan quality for CSx and BAOx was highly similar, while both were superior to EQUIx. E.g. with CS9, bowel/bladder Dmean reduced by 22% [11%, 38%] compared to EQUI9 (p<0.001). For equal plan quality, the number of EQUI beams had to be doubled compared to BAO and CS.ConclusionsComputer-generated beam angle CS could replace individualized BAO without loss in plan quality, while reducing planning complexity and calculation times, and resulting in a simpler clinical workflow. CS and BAO largely outperformed equi-angular treatment. With the developed CS, time consuming beam angle re-optimization in daily adaptive MR-linac treatment could be avoided. Further systematic research on computerized development of beam angle class solutions for MR-linac treatment planning is warranted.
| S-EPMC8518312 | biostudies-literature
Project description:Background and purposeLiterature is non-conclusive regarding selection of beam configurations in radiotherapy for mediastinal lymphoma (ML) radiotherapy, and published studies are based on manual planning with its inherent limitations. In this study, coplanar and non-coplanar beam configurations were systematically compared, using a large number of automatically generated plans.Material and methodsAn autoplanning workflow, including beam configuration optimization, was configured for young female ML patients. For each of 25 patients, 24 plans with different beam configurations were generated with autoplanning: 11 coplanar CP_x plans and 11 non-coplanar NCP_x plans with x = 5 to 15 IMRT beams with computer-optimized, patient-specific configurations, and the coplanar VMAT and non-coplanar Butterfly VMAT (B-VMAT) beam angle class solutions (600 plans in total).ResultsAutoplans compared favorably with manually generated, clinically delivered plans, ensuring that beam configuration comparisons were performed with high quality plans. There was no beam configuration approach that was best for all patients and all plan parameters. Overall there was a clear tendency towards higher plan quality with non-coplanar configurations (NCP_x≥12 and B-VMAT). NCP_x≥12 produced highly conformal plans with on average reduced high doses in lungs and patient and also a reduced heart Dmean, while B-VMAT resulted in reduced low-dose spread in lungs and left breast.ConclusionsNon-coplanar beam configurations were favorable for young female mediastinal lymphoma patients, with patient-specific and plan-parameter-dependent dosimetric advantages of NCP_x≥12 and B-VMAT. Individualization of beam configuration approach, considering also the faster delivery of B-VMAT vs. NCP_x≥12, can importantly improve the treatments.
| S-EPMC8082440 | biostudies-literature
Project description:Beam angle configuration is a major planning decision in intensity modulated radiation treatment (IMRT) that has a significant impact on dose distributions and thus quality of treatment, especially in complex planning cases such as those for lung cancer treatment. We propose a novel method to automatically determine beam configurations that incorporates noncoplanar beams. We then present a completely automated IMRT planning algorithm that combines the proposed method with a previously reported OAR DVH prediction model. Finally, we validate this completely automatic planning algorithm using a set of challenging lung IMRT cases. A beam efficiency index map is constructed to guide the selection of beam angles. This index takes into account both the dose contributions from individual beams and the combined effect of multiple beams by introducing a beam-spread term. The effect of the beam-spread term on plan quality was studied systematically and the weight of the term to balance PTV dose conformity against OAR avoidance was determined. For validation, complex lung cases with clinical IMRT plans that required the use of one or more noncoplanar beams were re-planned with the proposed automatic planning algorithm. Important dose metrics for the PTV and OARs in the automatic plans were compared with those of the clinical plans. The results are very encouraging. The PTV dose conformity and homogeneity in the automatic plans improved significantly. And all the dose metrics of the automatic plans, except the lung V5 Gy, were statistically better than or comparable with those of the clinical plans. In conclusion, the automatic planning algorithm can incorporate non-coplanar beam configurations in challenging lung cases and can generate plans efficiently with quality closely approximating that of clinical plans.
| S-EPMC6691500 | biostudies-literature
Project description:Beam angle optimization (BAO) by far remains an important and challenging problem in external beam radiation therapy treatment planning. Conventional BAO algorithms discussed in previous studies all focused on photon-based therapies. Impact of BAO on proton therapy is important while proton therapy increasingly receives great interests. This study focuses on potential benefits of BAO on intensity-modulated proton therapy (IMPT) that recently began available to clinical cancer treatment.The authors have developed a novel uncertainty incorporated BAO algorithm for IMPT treatment planning in that IMPT plan quality is highly sensitive to uncertainties such as proton range and setup errors. A linear programming was used to optimize robust intensity maps to scenario-based uncertainties for an incident beam angle configuration. Unlike conventional intensity-modulated radiation therapy with photons (IMXT), the search space for IMPT treatment beam angles may be relatively small but optimizing an IMPT plan may require higher computational costs due to larger data size. Therefore, a deterministic local neighborhood search algorithm that only needs a very limited number of plan objective evaluations was used to optimize beam angles in IMPT treatment planning.Three prostate cancer cases and two skull base chordoma cases were studied to demonstrate the dosimetric advantages and robustness of optimized beam angles from the proposed BAO algorithm. Two- to four-beam plans were optimized for prostate cases, and two- and three-beam plans were optimized for skull base cases. By comparing plans with conventional two parallel-opposed angles, all plans with optimized angles consistently improved sparing at organs at risks, i.e., rectum and femoral heads for prostate, brainstem for skull base, in either nominal dose distribution or uncertainty-based dose distributions. The efficiency of the BAO algorithm was demonstrated by comparing it with alternative methods including simulated annealing and genetic algorithm. The numbers of IMPT plan objective evaluations required were reduced by up to a factor of 5 while the same optimal angle plans were converged in selected comparisons.Uncertainty incorporated BAO may introduce pronounced improvement of IMPT plan quality including dosimetric benefits and robustness over uncertainties, based on the five clinical studies in this paper. In addition, local search algorithms may be more efficient in finding optimal beam angles than global optimization approaches for IMPT BAO.
| S-EPMC3422361 | biostudies-other
Project description:Time-consuming manual methods have been required to register cone-beam computed tomography (CBCT) images with plans in the Pinnacle(3) treatment planning system in order to replicate delivered treatments for adaptive radiotherapy. These methods rely on fiducial marker (FM) placement during CBCT acquisition or the image mid-point to localise the image isocentre. A quality assurance study was conducted to validate an automated CBCT-plan registration method utilising the Digital Imaging and Communications in Medicine (DICOM) Structure Set (RS) and Spatial Registration (RE) files created during online image-guided radiotherapy (IGRT).CBCTs of a phantom were acquired with FMs and predetermined setup errors using various online IGRT workflows. The CBCTs, DICOM RS and RE files were imported into Pinnacle(3) plans of the phantom and the resulting automated CBCT-plan registrations were compared to existing manual methods. A clinical protocol for the automated method was subsequently developed and tested retrospectively using CBCTs and plans for six bladder patients.The automated CBCT-plan registration method was successfully applied to thirty-four phantom CBCT images acquired with an online 0 mm action level workflow. Ten CBCTs acquired with other IGRT workflows required manual workarounds. This was addressed during the development and testing of the clinical protocol using twenty-eight patient CBCTs. The automated CBCT-plan registrations were instantaneous, replicating delivered treatments in Pinnacle(3) with errors of ±0.5 mm. These errors were comparable to mid-point-dependant manual registrations but superior to FM-dependant manual registrations.The automated CBCT-plan registration method quickly and reliably replicates delivered treatments in Pinnacle(3) for adaptive radiotherapy.
| S-EPMC4775828 | biostudies-other
Project description:PurposeTo propose and validate a fully automated multicriterial treatment planning solution for a CyberKnife® equipped with an InCiseTM 2 multileaf collimator.MethodsThe AUTO BAO plans are generated using fully automated prioritized multicriterial optimization (AUTO MCO) of pencil-beam fluence maps with integrated noncoplanar beam angle optimization (BAO), followed by MLC segment generation. Both the AUTO MCO and segmentation algorithms have been developed in-house. AUTO MCO generates for each patient a single, high-quality Pareto-optimal IMRT plan. The segmentation algorithm then accurately mimics the AUTO MCO 3D dose distribution, while considering all candidate beams simultaneously, rather than replicating the fluence maps. Pencil-beams, segment dose depositions, and final dose calculations are performed with a stand-alone version of the clinical dose calculation engine. For validation, AUTO BAO plans were generated for 33 prostate SBRT patients and compared to reference plans (REF) that were manually generated with the commercial treatment planning system (TPS), in absence of time pressure. REF plans were also compared to AUTO RB plans, for which fluence map optimization was performed for the beam angle configuration used in the REF plan, and the segmentation could use all these beams or only a subset, depending on the dosimetry.ResultsAUTO BAO plans were clinically acceptable and dosimetrically similar to REF plans, but had on average reduced numbers of beams ((beams in AUTO BAO)/(beams in REF) (relative improvement): 24.7/48.3 (-49%)), segments (59.5/98.9 (-40%)), and delivery times (17.1/22.3 min. (-23%)). Dosimetry of AUTO RB and REF were also similar, but AUTO RB used on average fewer beams (38.0/48.3 (-21%)) and had on average shorter delivery times (18.6/22.3 min. (-17%)). Delivered Monitor Units (MU) were similar for all three planning approaches.ConclusionsA new, vendor-independent optimization workflow for fully automated generation of deliverable high-quality CyberKnife® plans was proposed, including BAO. Compared to manual planning with the commercial TPS, fraction delivery times were reduced by 5.3 min. (-23%) due to large reductions in beam and segment numbers.
| S-EPMC8457110 | biostudies-literature
Project description:The geometric accuracy of CT images is essential when they are used for planning radiation therapy. In this study, a method of quantitative testing of image rotation in CT is presented, based on the automated analysis of an image of a phantom half-filled with water. A plug-in was written for ImageJ software for automated detection of a water surface in an image and measurement of its angle relative to a horizontal line. A water phantom can be used for the evaluation of image rotation for axial mode. In helical mode the movement of the table would cause movement of the water. The difference between image rotation for axial and helical scans can be evaluated by measuring and comparing the angles of the tabletop surface for both modes. Preliminary results of measurements for three CT scanners show that image rotation does not exceed 0.5°, and is less than 0.1° for the dedicated CT simulator. It was observed that, for one CT scanner image, the rotation angle depended on tube rotation time.
| S-EPMC5690054 | biostudies-literature
Project description:Background and purposeTreatment planning of radiotherapy for locally advanced breast cancer patients can be a time consuming process. Artificial intelligence based treatment planning could be used as a tool to speed up this process and maintain plan quality consistency. The purpose of this study was to create treatment plans for locally advanced breast cancer patients using a Convolutional Neural Network (CNN).Materials and methodsData of 60 patients treated for left-sided breast cancer was used with a training, validation and test split of 36/12/12, respectively. The in-house built CNN model was a hierarchically densely connected U-net (HD U-net). The inputs for the HD U-net were 2D distance maps of the relevant regions of interest. Dose predictions, generated by the HD U-net, were used for a mimicking algorithm in order to create clinically deliverable plans.ResultsDose predictions were generated by the HD U-net and mimicked using a commercial treatment planning system. The predicted plans fulfilling all clinical goals while showing small (≤0.5 Gy) statistically significant differences (p < 0.05) in the doses compared to the manual plans. The mimicked plans show statistically significant differences in the average doses for the heart and lung of ≤0.5 Gy and a reduced D2% of all PTVs. In total, ten of the twelve mimicked plans were clinically acceptable.ConclusionsWe created a CNN model which can generate clinically acceptable plans for left-sided locally advanced breast cancer patients. This model shows great potential to speed up the treatment planning process while maintaining consistent plan quality.
| S-EPMC8645926 | biostudies-literature
Project description:BackgroundThere is no consensus regarding the clinical target volume (CTV) margins in radiotherapy for glioma. In this study, we aimed to perform a complete macropathologic analysis examining microscopic tumor extension (ME) to more accurately define the CTV in glioma.MethodsThirty-eight supra-total resection specimens of glioma patients were examined on histologic sections. The ME distance, defined as the maximum linear distance from the tumor border to the invasive tumor cells, was measured at each section. We defined the CTV based on the relationships between ME distance and clinicopathologic features.ResultsBetween February 2016 and July 2020, a total of 814 slides were examined, corresponding to 162 slides for low-grade glioma (LGG) and 652 slides for high-grade glioma (HGG). The ME value was 0.69 ± 0.43 cm for LGG and 1.29 ± 0.54 cm for HGG (P < 0.001). After multivariate analysis, tumor grade, O6-methylguanine-DNA-methyltransferase promoter methylated status (MGMTm), isocitrate dehydrogenase wild-type status (IDHwt), and 1p/19q non-co-deleted status (non-codel) were positively correlated with ME distance (all P < 0.05). We defined the CTV of glioma based on tumor grade. To take into account approximately 95% of the ME, a margin of 1.00 cm, 1.50 cm, and 2.00 cm were chosen for grade II, grade III, and grade IV glioma, respectively. Paired analysis of molecularly defined patients confirmed that tumors that had all three molecular alterations (i.e., MGMTm/IDHwt/non-codel) were the most aggressive subgroups (all P < 0.05). For these patients, the margin could be up to 1.50 cm, 2.00 cm, and 2.50 cm for grade II, grade III, and grade IV glioma, respectively, to cover the subclinical lesions in 95% of cases.ConclusionsThe ME was different between the grades of gliomas. It may be reasonable to recommend 1.00 cm, 1.50 cm, and 2.00 cm CTV margins for grade II, grade III, and grade IV glioma, respectively. Considering the highly aggressive nature of MGMTm/IDHwt/non-codel tumors, for these patients, the margin could be further expanded by 0.5 cm. These recommendations would encompass microscopic disease extension in 95% of cases.Trial registrationThe trial was registered with Chinese Clinical Trial Registry ( ChiCTR2100049376 ).
| S-EPMC8597244 | biostudies-literature
Project description:BackgroundFor several tumor entities, automated treatment planning has improved plan quality and planning efficiency, and may enable adaptive treatment approaches. Whole-pelvic prostate radiotherapy (WPRT) involves large concave target volumes, which present a challenge for volumetric arc therapy (VMAT) optimization. This study evaluates automated VMAT planning for WPRT-VMAT and compares the results with manual expert planning.MethodsA system for fully automated multi-criterial plan generation was configured for each step of sequential-boost WPRT-VMAT, with final "autoVMAT" plans being automatically calculated by the Monaco treatment planning system (TPS; Elekta AB, Stockholm, Sweden). Configuration was based on manually generated VMAT plans (manualVMAT) of 5 test patients, the planning protocol, and discussions with the treating physician on wishes for plan improvements. AutoVMAT plans were then generated for another 30 evaluation patients and compared to manualVMAT plans. For all 35 patients, manualVMAT plans were optimized by expert planners using the Monaco TPS.ResultsAutoVMAT plans exhibited strongly improved organ sparing and higher conformity compared to manualVMAT. On average, mean doses (Dmean) of bladder and rectum were reduced by 10.7 and 4.5 Gy, respectively, by autoVMAT. Prostate target coverage (V95%) was slightly higher (+0.6%) with manualVMAT. In a blinded scoring session, the radiation oncologist preferred autoVMAT plans to manualVMAT plans for 27/30 patients. All treatment plans were considered clinically acceptable. The workload per patient was reduced by > 70 min.ConclusionAutomated VMAT planning for complex WPRT dose distributions is feasible and creates treatment plans that are generally dosimetrically superior to manually optimized plans.
| S-EPMC5869893 | biostudies-literature