Initial evaluation of automated treatment planning software.
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ABSTRACT:
SUBMITTER: Gintz D
PROVIDER: S-EPMC5690942 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:PurposeOur purpose was to assess the clinical outcomes and target positioning accuracy of frameless linear accelerator single-isocenter multiple-target (SIMT) dynamic conformal arc (DCA) stereotactic radiosurgery (SRS) for multiple brain metastases (BM).Methods and materialsBetween October 2016 and September 2018, 31 consecutive patients ≥18 years old with 204 BM <3 cm in maximum size receiving SIMT DCA SRS were retrospectively evaluated. All plans were created using a dedicated automated treatment planning software (Brainlab, Munich, Germany), and treatments were performed with a Truebeam STx or a Novalis Tx (Brainlab and Varian Medical Systems, CA). The accuracy of setup and interfraction patient repositioning was assessed by Brainlab ExacTrac radiograph 6-dimensional image system and the risk of compromised target dose coverage evaluated. Brain control and overall survival were estimated by Kaplan-Meier method calculated from the time of SRS.ResultsFourteen patients were treated for 4 to 6 and 17 patients for 7 to 10 BM. The mean gross tumor volume (GTV) was 0.65 cm3 and the mean planning target volume (PTV) was 0.89 cm3. Mean V95 (the volume of the PTV covered by 95% of the prescription dose) and D95 (the prescription dose covering 95% of the PTV) were 99.5% and 21.1 Gy, respectively. With a median clinical follow-up of 11 months (range, 4-26 months), the 1-year survival was 68% and local control was 89%. As a consequence of plan isocenter residual errors, a loss of target coverage, defined as V95 < 95%, occurred in 28 PTVs (10 patients); using a 1 mm GTV-to-PTV margin, adequate dose coverage was maintained for all lesions.ConclusionsSIMT DCA SRS represents a fast and effective approach for patients with up to 10 BM. The dosimetric effects of residual set-up and intrafraction positioning errors are modest, although a GTV-to-PTV margin of 1 mm is recommended.
| S-EPMC7557192 | biostudies-literature
Project description:Precise procedural planning is crucial to achieve excellent results in patients undergoing Transcatheter aortic valve implantation (TAVI). The aim of this study was to compare the semi-automated 3mensio (3 m) software to the fully-automated HeartNavigator3 (HN) software. We randomly selected 100 patients from our in-house TAVI-registry and compared aortic annulus and perimeter as well as coronary distances between 3m-measurements and post-hoc HN-measurements. Finally, we retrospectively simulated prosthesis choice based on HN-measurements and analyzed the differences compared to routinely used 3 m based strategy. We observed significant differences between the two software packages regarding area (3 m 464 ± 88 mm², HN 482 ± 96 mm², p < 0.001), perimeter (3 m 77 ± 7 mm, HN 79 ± 8 mm, p < 0.001) and coronary distances (LCA: 3 m 13 ± 3 mm, HN 12 ± 3 mm, p < 0.001; RCA: 3 m 16 ± 3 mm, HN 15 ± 3 mm, p < 0.001). Prosthesis choice simulation based on newly obtained HN-measurements would have led to a decision change in 18% of patients, with a further reduction to 4% following manual adjustment of HN-measurements. The fully-automatic HN-software provides higher values for annular metrics and lower annulus-to-coronary-ostia distances compared to 3m-software. Measurement differences did not influence clinical outcome. Both, the HN-software and the 3m-software are sophisticated, reliable and easy to use for the clinician. Manual adjustment of HN-measurements may increase precision in complex aortic annulus anatomy.
| S-EPMC7329903 | biostudies-literature
Project description:A dose calculation verification system (VS) was acquired and commissioned as a second check on the treatment planning system (TPS). This system reads DICOM CT datasets, RT plans, RT structures, and RT dose from the TPS and automatically, using its own collapsed cone superposition/convolution algorithm, computes dose on the same CT dataset. The system was commissioned by extracting basic beam parameters for simple field geometries and dose verification for complex treatments. Percent depth doses (PDD) and profiles were extracted for field sizes using jaw settings 3 × 3 cm2 - 40 × 40 cm2 and compared to measured data, as well as our TPS model. Smaller fields of 1 × 1 cm2 and 2 × 2 cm2 generated using the multileaf collimator (MLC) were analyzed in the same fashion as the open fields. In addition, 40 patient plans consisting of both IMRT and VMAT were computed and the following comparisons were made: 1) TPS to the VS, 2) VS to measured data, and 3) TPS to measured data where measured data is both ion chamber (IC) and film measurements. Our results indicated for all field sizes using jaw settings PDD errors for the VS on average were less than 0.87%, 1.38%, and 1.07% for 6x, 15x, and 18x, respectively, relative to measured data. PDD errors for MLC field sizes were less than 2.28%, 1.02%, and 2.23% for 6x, 15x, and 18x, respectively. The infield profile analysis yielded results less than 0.58% for 6x, 0.61% for 15x, and 0.77% for 18x for the VS relative to measured data. Analysis of the penumbra region yields results ranging from 66.5% points, meeting the DTA criteria to 100% of the points for smaller field sizes for all energies. Analysis of profile data for field sizes generated using the MLC saw agreement with infield DTA analysis ranging from 68.8%-100% points passing the 1.5%/1.5 mm criteria. Results from the dose verification for IMRT and VMAT beams indicated that, on average, the ratio of TPS to IC and VS to IC measurements was 100.5 ± 1.9% and 100.4 ± 1.3%, respectively, while our TPS to VS was 100.1 ± 1.0%. When comparing the TPS and VS to film measurements, the average percentage pixels passing a 3%/3mm criteria based gamma analysis were 96.6 ± 4.2% and 97 ± 5.6%, respectively. When the VS was compared to the TPS, on average 98.1 ± 5.3% of pixels passed the gamma analysis. Based upon these preliminary results, the VS system should be able to calculate dose adequately as a verification tool of our TPS.
| S-EPMC5711088 | 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:PurposeKnowledge-based planning (KBP) offers the ability to predict dose-volume metrics based on information extracted from previous plans, reducing plan variability and improving plan quality. As clinical integration of KBP is increasing there is a growing need for quantitative evaluation of KBP models. A .NET-based application, RapidCompare, was created for automated plan creation and analysis of Varian RapidPlan models.MethodsRapidCompare was designed to read calculation parameters and a list of reference plans. The tool copies the reference plan field geometry and structure set, applies the RapidPlan model, optimizes the KBP plan, and generates data for quantitative evaluation of dose-volume metrics. A cohort of 85 patients, divided into training (50), testing (10), and validation (25) groups, was used to demonstrate the utility of RapidCompare. After training and tuning, the KBP model was paired with three different optimization templates to compare various planning strategies in the validation cohort. All templates used the same set of constraints for the planning target volume (PTV). For organs-at-risk, the optimization template provided constraints using the whole dose-volume histogram (DVH), fixed-dose/volume points, or generalized equivalent uniform dose (gEUD). The resulting plans from each optimization approach were compared using DVH metrics.ResultsRapidCompare allowed for the automated generation of 75 total plans for comparison with limited manual intervention. In comparing optimization techniques, the Dose/Volume and Lines optimization templates generated plans with similar DVH metrics, with a slight preference for the Lines technique with reductions in heart V30Gy and spinal cord max dose. The gEUD model produced high target heterogeneity.ConclusionAutomated evaluation allowed for the exploration of multiple optimization templates in a larger validation cohort than would have been feasible using a manual approach. A final KBP model using line optimization objectives produced the highest quality plans without human intervention.
| S-EPMC10562024 | biostudies-literature
Project description:BackgroundHypofractionated whole-breast irradiation is a standard adjuvant therapy for early-stage breast cancer. This study evaluates the plan quality and efficacy of an in-house-developed automated radiotherapy treatment planning algorithm for hypofractionated whole-breast radiotherapy.MethodsA cohort of 99 node-negative left-sided breast cancer patients completed hypofractionated whole-breast irradiation with six-field IMRT for 42.56 Gy in 16 daily fractions from year 2016 to 2018 at a tertiary center were re-planned with an in-house-developed algorithm. The automated plan-generating C#-based program is developed in a Varian ESAPI research mode. The dose-volume histogram (DVH) and other dosimetric parameters of the automated and manual plans were directly compared.ResultsThe average time for generating an autoplan was 5 to 6 min, while the manual planning time ranged from 1 to 1.5 h. There was only a small difference in both the gantry angles and the collimator angles between the autoplans and the manual plans (ranging from 2.2 to 5.3 degrees). Autoplans and manual plans performed similarly well in hotspot volume and PTV coverage, with the autoplans performing slightly better in the ipsilateral-lung-sparing dose parameters but were inferior in contralateral-breast-sparing. The autoplan dosimetric quality did not vary with different breast sizes, but for manual plans, there was worse ipsilateral-lung-sparing (V4Gy) in larger or medium-sized breasts than in smaller breasts. Autoplans were generally superior than manual plans in CI (1.24 ± 0.06 vs. 1.30 ± 0.09, p < 0.01) and MU (1010 ± 46 vs. 1205 ± 187, p < 0.01).ConclusionsOur study presents a well-designed standardized fully automated planning algorithm for optimized whole-breast radiotherapy treatment plan generation. A large cohort of 99 patients were re-planned and retrospectively analyzed. The automated plans demonstrated similar or even better dosimetric quality and efficacy in comparison with the manual plans. Our result suggested that the autoplanning algorithm has great clinical applicability potential.
| S-EPMC7077022 | biostudies-literature
Project description:Computer-assisted synthetic planning has seen major advancements that stem from the availability of large reaction databases and artificial intelligence methodologies. SynRoute is a new retrosynthetic planning software tool that uses a relatively small number of general reaction templates, currently 263, along with a literature-based reaction database to find short, practical synthetic routes for target compounds. For each reaction template, a machine learning classifier is trained using data from the Pistachio reaction database to predict whether new computer-generated reactions based on the template are likely to work experimentally in the laboratory. This reaction generation methodology is used together with a vectorized Dijkstra-like search of top-scoring routes organized by synthetic strategies for easy browsing by a synthetic chemist. SynRoute was able to find routes for an average of 83% of compounds based on selection of random subsets of drug-like compounds from the ChEMBL database. Laboratory evaluation of 12 routes produced by SynRoute, to synthesize compounds not from the previous random subsets, demonstrated the ability to produce feasible overall synthetic strategies for all compounds evaluated.
| S-EPMC10498441 | biostudies-literature
Project description:Over the past two decades a significant number of OCT segmentation approaches have been proposed in the literature. Each methodology has been conceived for and/or evaluated using specific datasets that do not reflect the complexities of the majority of widely available retinal features observed in clinical settings. In addition, there does not exist an appropriate OCT dataset with ground truth that reflects the realities of everyday retinal features observed in clinical settings. While the need for unbiased performance evaluation of automated segmentation algorithms is obvious, the validation process of segmentation algorithms have been usually performed by comparing with manual labelings from each study and there has been a lack of common ground truth. Therefore, a performance comparison of different algorithms using the same ground truth has never been performed. This paper reviews research-oriented tools for automated segmentation of the retinal tissue on OCT images. It also evaluates and compares the performance of these software tools with a common ground truth.
| S-EPMC5025289 | biostudies-literature
Project description:BackgroundReal-time automated analysis of videos of the microvasculature is an essential step in the development of research protocols and clinical algorithms that incorporate point-of-care microvascular analysis. In response to the call for validation studies of available automated analysis software by the European Society of Intensive Care Medicine, and building on a previous validation study in sheep, we report the first human validation study of AVA 4.MethodsTwo retrospective perioperative datasets of human microcirculation videos (P1 and P2) and one prospective healthy volunteer dataset (V1) were used in this validation study. Video quality was assessed using the modified Microcirculation Image Quality Selection (MIQS) score. Videos were initially analyzed with (1) AVA software 3.2 by two experienced investigators using the gold standard semi-automated method, followed by an analysis with (2) AVA automated software 4.1. Microvascular variables measured were perfused vessel density (PVD), total vessel density (TVD), and proportion of perfused vessels (PPV). Bland-Altman analysis and intraclass correlation coefficients (ICC) were used to measure agreement between the two methods. Each method's ability to discriminate between microcirculatory states before and after induction of general anesthesia was assessed using paired t-tests.ResultsFifty-two videos from P1, 128 videos from P2 and 26 videos from V1 met inclusion criteria for analysis. Correlational analysis and Bland-Altman analysis revealed poor agreement and no correlation between AVA 4.1 and AVA 3.2. Following the induction of general anesthesia, TVD and PVD measured using AVA 3.2 increased significantly for P1 (p < 0.05) and P2 (p < 0.05). However, these changes could not be replicated with the data generated by AVA 4.1.ConclusionsAVA 4.1 is not a suitable tool for research or clinical purposes at this time. Future validation studies of automated microvascular flow analysis software should aim to measure the new software's agreement with the gold standard, its ability to discriminate between clinical states and the quality thresholds at which its performance becomes unacceptable.
| S-EPMC8017044 | biostudies-literature
Project description:Postoperative/adjuvant radiotherapy of advanced gastric cancer involves a large planning target volume (PTV) with multi-concave shapes which presents a challenge for volumetric modulated arc therapy (VMAT) planning. This study investigates the advantages of automated VMAT planning for this site compared to manual VMAT planning by expert planners.For 20 gastric cancer patients in the postoperative/adjuvant setting, dual-arc VMAT plans were generated using fully automated multi-criterial treatment planning (autoVMAT), and compared to manually generated VMAT plans (manVMAT). Both automated and manual plans were created to deliver a median dose of 45 Gy to the PTV using identical planning and segmentation parameters. Plans were evaluated by two expert radiation oncologists for clinical acceptability. AutoVMAT and manVMAT plans were also compared based on dose-volume histogram (DVH) and predicted normal tissue complication probability (NTCP) analysis.Both manVMAT and autoVMAT plans were considered clinically acceptable. Target coverage was similar (manVMAT: 96.6?±?1.6%, autoVMAT: 97.4?±?1.0%, p?=?0.085). With autoVMAT, median kidney dose was reduced on average by >?25%; (for left kidney from 11.3?±?2.1 Gy to 8.9?±?3.5 Gy (p?=?0.002); for right kidney from 9.2?±?2.2 Gy to 6.1?±?1.3 Gy (p?<? 0.001)). Median dose to the liver was lower as well (18.8?±?2.3 Gy vs. 17.1?±?3.6 Gy, p?=?0.048). In addition, Dmax of the spinal cord was significantly reduced (38.3?±?3.7 Gy vs. 31.6?±?2.6 Gy, p?<? 0.001). Substantial improvements in dose conformity and integral dose were achieved with autoVMAT plans (4.2% and 9.1%, respectively; p?<? 0.001). Due to the better OAR sparing in the autoVMAT plans compared to manVMAT plans, the predicted NTCPs for the left and right kidney and the liver-PTV were significantly reduced by 11.3%, 12.8%, 7%, respectively (p???0.001). Delivery time and total number of monitor units were increased in autoVMAT plans (from 168?±?19 s to 207?±?26 s, p?=?0.006) and (from 781?±?168 MU to 1001?±?134 MU, p?=?0.003), respectively.For postoperative/adjuvant radiotherapy of advanced gastric cancer, involving a complex target shape, automated VMAT planning is feasible and can substantially reduce the dose to the kidneys and the liver, without compromising the target dose delivery.
| S-EPMC5913894 | biostudies-other