Clinical implementation of deep learning-based automated left breast simultaneous integrated boost radiotherapy treatment planning
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ABSTRACT:
SUBMITTER: Zeverino M
PROVIDER: S-EPMC10534254 | biostudies-literature | 2023 Sep
REPOSITORIES: biostudies-literature
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Project description:The delivery of a simultaneous integrated boost to the intra-prostatic tumour nodule may improve local control. The ability to deliver such treatments with hypofractionated SBRT was attempted using RapidArc (Varian Medical systems, Palo Alto, CA) and Multiplan (Accuray inc, Sunnyvale, CA).15 patients with dominant prostate nodules had RapidArc and Multiplan plans created using a 5 mm isotropic margin, except 3 mm posteriorly, aiming to deliver 47.5 Gy in 5 fractions to the boost whilst treating the whole prostate to 36.25 Gy in 5 fractions. An additional RapidArc plan was created using an 8 mm isotropic margin, except 5 mm posteriorly, to account for lack of intrafraction tracking.Both RapidArc and Multiplan can produce clinically acceptable boost plans to a dose of 47.5 Gy in 5 fractions. The mean rectal doses were lower for RapidArc plans (D50 13.2 Gy vs 15.5 Gy) but the number of missed constraints was the same for both planning methods (11/75). When the margin was increased to 8 mm/5 mm for the RapidArc plans to account for intrafraction motion, 37/75 constraints were missed.RapidArc and Multiplan can produce clinically acceptable simultaneous integrated boost plans, but the mean rectal D50 and D20 with RapidArc are lower. If the margins are increased to account for intrafraction motion, the RapidArc plans exceed at least one dose constraint in 13/15 cases. Delivering a simultaneous boost with hypofractionation appears feasible, but requires small margins needing intrafraction motion tracking.
| S-EPMC3853231 | biostudies-other
Project description:The investigators propose a randomized non-inferiority trial that compares preoperative Fluoro Uracil (FU)-based chemoradiotherapy to radiotherapy with a simultaneous integrated boost. In patients with T3-4 rectal cancer, the latter approach is considered preferential with regard to toxicity and cost. The metabolic response of the tumor, as assessed by 18F-2-Fluoro-2-Deoxyglucose-Positron Emission tomography (18F-FDG PET) or PET-CT, will be used as a surrogate marker of cause specific outcome
| 2096816 | ecrin-mdr-crc
Project description:Since the clinical implementation of novel rotational forms of intensity-modulated radiotherapy, a variety of planning studies have been published that reinforce the major selling points of the technique. Namely, comparable or even improved dose distributions with a reduction in both monitor units and treatment times, when compared with static gantry intensity-modulated radiotherapy. Although the data are promising, a rigorous approach to produce these plans has yet to be established. As a result, this study outlines a robust and streamlined planning strategy with a concentration on RapidArc class solutions for prostate with a simultaneous integrated boost. This planning strategy outlines the field setup, recommended starting objectives, required user interactions to be made throughout optimization and post-optimization adjustments. A comparative planning study, with static gantry IMRT, is then presented as justification for the planning strategy itself. A variety of parameters are evaluated relating to both the planning itself (optimization and calculation time) and the plans that result. Results of this comparative study are in line with previously published data, and the planning process is streamlined to a point where the RapidArc optimization time takes 15 ± 1.3 minutes. Application of this planning strategy reduces the dependence of the produced plan on the experience of the planner, and has the potential to streamline the planning process within radiotherapy departments.
| S-EPMC5718576 | biostudies-literature
Project description:Dominant intraprostatic lesion (DIL) has been known as the most common local recurrence site of prostate cancer. We evaluated the feasibility of simultaneous integrated boost (SIB) to DIL with CyberKnife stereotactic body radiotherapy (CK-SBRT). We selected 15 patients with prostate cancer and visible DIL and compared 3 plans for each patient: 1) No boost plan of 35 Gy to prostate, 2) DIL_40 plan of SIB 40 Gy to DIL and 35 Gy to prostate, and 3) DIL_45 plan with 45 Gy to DIL and 35 Gy to the prostate in 5 fractions. All targets satisfied with the prescription coverage per protocol. However, some patients failed to meet the Dmax of the rectum in DIL_40 plans (n = 4), and DIL_45 plans (n = 6). Violations of bladder constraints occurred in four DIL_45 plans. Consequently, the DIL boost with SBRT was possible in 73% of patients with DIL_40 plans, and 60% of patients with DIL_45 plans without any violation of normal organ constraints. All patients who experienced constraint violations had DILs in posterior segments. DIL boost using CK-SBRT could be an option for localized prostate cancer patients. For patients who had DIL in posterior segments, a moderate dose escalation of 40 Gy seemed appropriate.
| S-EPMC7477222 | biostudies-literature
Project description:PurposeTo assess the feasibility of accelerated hypofractionated radiotherapy with simultaneous integrated boost (SIB) in patients with breast cancer.Materials and methodsA total of 27 patients after breast-conserving surgery were included in this study. Patients were planned on a four-dimensional computerized tomogram, and contouring was done using RTOG guidelines. The dose was 34 Gy/10#/2 week to the breast and 40 Gy/10#/2 week to the tumor bed as SIB with volumetric modulated arc technique. The primary endpoint was grade 2 acute skin toxicity. Doses to the organs-at-risk were calculated. Toxicities and cosmesis were assessed using RTOG/LENT/SOMA and HARVARD/NSABP/RTOG grading scales, respectively. Disease-free survival (DFS) and overall survival (OS) were calculated with Kaplan-Meier curves.ResultsThe mean age of the patients was 42 years. Left and right breast cancers were seen in 17 (63%) and 10 (37%) patients, respectively. The mean values of ipsilateral lung V16 and contralateral lung V5 were 16.01% and 3.74%, respectively. The mean heart doses from the left and right breast were 7.25 Gy and 4.37 Gy, respectively. The mean doses to the contralateral breast, oesophagus, and Dmax to brachial plexus were 2.64 Gy, 3.69 Gy, and 26.95 Gy, respectively. The mean value of thyroid V25 was 19.69%. Grade 1 and 2 acute skin toxicities were observed in 9 (33%) and 5 (18.5%) patients, respectively. Grade 2 hyperpigmentation, edema, and induration were observed in 1 (3.7%), 2 (7.4%), and 4 (14.8%) patients, respectively. Mild breast pain and arm/shoulder discomfort were reported by 1 (3.4%) patient. The median follow-up was 51 months (range, 12 to 61 months). At four years, breast induration, edema, and fibrosis were observed in 1 (3.7%) patient. Cosmesis was excellent and good in 21 (78%) and 6 (22%) patients, respectively. Local recurrence and distant metastases occurred in 1 (3.7%) and 2 (7.4%) patients, respectively. DFS and OS at four years were 88% and 92%, respectively.ConclusionWith this radiotherapy schedule, acute and late toxicity rates were acceptable with no adverse cosmesis. Local control, DFS, and OS were good.
| S-EPMC9262700 | biostudies-literature
Project description:PurposeTreatment planning for pancreas stereotactic body radiation therapy (SBRT) is a challenging task, especially with simultaneous integrated boost treatment approaches. We propose a deep learning (DL) framework to accurately predict fluence maps from patient anatomy and directly generate intensity modulated radiation therapy plans.Methods and materialsThe framework employs 2 convolutional neural networks (CNNs) to sequentially generate beam dose prediction and fluence map prediction, creating a deliverable 9-beam intensity modulated radiation therapy plan. Within the beam dose prediction CNN, axial slices of combined structure contour masks are used to predict 3-dimensional (3D) beam doses for each beam. Each 3D beam dose is projected along its beam's-eye-view to form a 2D beam dose map, which is subsequently used by the fluence map prediction CNN to predict its fluence map. Finally, the 9 predicted fluence maps are imported into the treatment planning system to finalize the plan by leaf sequencing and dose calculation. One hundred patients receiving pancreas SBRT were retrospectively collected for this study. Benchmark plans with unified simultaneous integrated boost prescription (25/33 Gy) were manually optimized for each case. The data set was split into 80/20 cases for training and testing. We evaluated the proposed DL framework by assessing both the fluence maps and the final predicted plans. Further, clinical acceptability of the plans was evaluated by a physician specializing in gastrointestinal cancer.ResultsThe DL-based planning was, on average, completed in under 2 minutes. In testing, the predicted plans achieved similar dose distribution compared with the benchmark plans (-1.5% deviation for planning target volume 33 V33Gy), with slightly higher planning target volume maximum (+1.03 Gy) and organ at risk maximum (+0.95 Gy) doses. After renormalization, the physician rated 19 cases clinically acceptable and 1 case requiring minor improvement.ConclusionsThe DL framework can effectively plan pancreas SBRT cases within 2 minutes. The predicted plans are clinically deliverable, with plan quality approaching that of manual planning.
| S-EPMC8099762 | 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:PurposeWe evaluate the feasibility of the elective nodal irradiation strategy in stereotactic body radiotherapy (SBRT) for pancreatic cancer.MethodsThree simultaneous integrated boost (SIB)-SBRT plans (Boost1, Boost2, and Boost3) were retrospectively generated for each of 20 different patients. Boost1 delivered 33 and 25 Gy to PTV1 and PTV2, respectively. Boost2 delivered 40, 33, and 25 Gy to boostCTV, PTV1, and PTV2, respectively. Boost3 delivered 33 and 25 Gy to PTV1 and PTV3, respectively. PTV1 covered the initial standard SBRT plan (InitPlan) gross tumor volume (GTV). PTV2 covered CTVgeom which was created by a 10-mm expansion (15 mm posterior) of GTV. PTV3 covered CTVprop which included elective nodal regions. The boostCTV included GTV as well as involved vasculature. The planning feasibility in each scenario and dose-volume histograms (DVHs) were analyzed and compared with the InitPlan (delivered 33 Gy only to PTV1) by paired t-test. Next, a novel DVH prediction model was developed and its performance was evaluated according to the prediction accuracy (AC) of planning violations. Then, the model was used to simulate the impacts of GTV-to-organs at risk (OAR) distance and gastrointestinal (GI) OAR volume variations on planning feasibility.ResultsSignificant dose increases were observed in GI-OARs in SIB-SBRT plans when compared with InitPlan. All dose constraints were met in 63% of cases in InitPlan, Boost1, and Boost2, whereas Boost3 developed DVH violations in all cases. Utilizing previous patient anatomy, the novel DVH prediction model achieved a high AC in the prediction of violations for GI-OARs; the positive predictive value, negative predictive value, and AC were 66%, 90%, and 84%, respectively. Experiments with the model demonstrated that the larger proximity volume of GI-OAR at the shorter distance substantially impacted on planning violations.ConclusionsSIB-SBRT plan with geometrically defined prophylactic areas can be dosimetrically feasible, but including all nodal areas with 25 Gy in five fractions appears to be unrealistic.
| S-EPMC6370996 | biostudies-literature
Project description:Background and purposeReducing trismus in radiotherapy for head and neck cancer (HNC) is important. Automated deep learning (DL) segmentation and automated planning was used to introduce new and rarely segmented masticatory structures to study if trismus risk could be decreased.Materials and methodsAuto-segmentation was based on purpose-built DL, and automated planning used our in-house system, ECHO. Treatment plans for ten HNC patients, treated with 2 Gy × 35 fractions, were optimized (ECHO0). Six manually segmented OARs were replaced with DL auto-segmentations and the plans re-optimized (ECHO1). In a third set of plans, mean doses for auto-segmented ipsilateral masseter and medial pterygoid (MIMean, MPIMean), derived from a trismus risk model, were implemented as dose-volume objectives (ECHO2). Clinical dose-volume criteria were compared between the two scenarios (ECHO0 vs. ECHO1; ECHO1 vs. ECHO2; Wilcoxon signed-rank test; significance: p < 0.01).ResultsSmall systematic differences were observed between the doses to the six auto-segmented OARs and their manual counterparts (median: ECHO1 = 6.2 (range: 0.4, 21) Gy vs. ECHO0 = 6.6 (range: 0.3, 22) Gy; p = 0.007), and the ECHO1 plans provided improved normal tissue sparing across a larger dose-volume range. Only in the ECHO2 plans, all patients fulfilled both MIMean and MPIMean criteria. The population median MIMean and MPIMean were considerably lower than those suggested by the trismus model (ECHO0: MIMean = 13 Gy vs. ≤42 Gy; MPIMean = 29 Gy vs. ≤68 Gy).ConclusionsAutomated treatment planning can efficiently incorporate new structures from DL auto-segmentation, which results in trismus risk sparing without deteriorating treatment plan quality. Auto-planning and deep learning auto-segmentation together provide a powerful platform to further improve treatment planning.
| S-EPMC8552336 | biostudies-literature
Project description:PurposeThe aim was to assess the feasibility of online adaptive radiotherapy (oART) for bladder cancer using a focal boost by focusing on the quality of the online treatment plan and automatic target delineation, duration of the workflow and performance in the presence of fiducial markers for tumor bed localization.MethodsFifteen patients with muscle invasive bladder cancer received daily oART with Cone Beam CT (CBCT), artificial intelligence (AI)-assisted automatic delineation of the daily anatomy and online plan reoptimization. The bladder and pelvic lymph nodes received a total dose of 40 Gy in 20 fractions, the tumor received an additional simultaneously integrated boost (SIB) of 15 Gy. The dose distribution of the reference plan was calculated for the daily anatomy, i.e. the scheduled plan. Simultaneously, a reoptimization of the plan was performed i.e. the adaptive plan. The target coverage and V95% outside the target were evaluated for both plans. The need for manual adjustments of the GTV delineation, the duration of the workflow and the influence of fiducial markers were assessed.ResultsAll 300 adaptive plans met the requirement of the CTV-coverage V95%≥98% for both the boost (55 Gy) and elective volume (40 Gy). For the scheduled plans the CTV-coverage was 53.5% and 98.5%, respectively. Significantly less tissue outside the targets received 55 Gy in case of the adaptive plans as compared to the scheduled plans. Manual corrections of the GTV were performed in 67% of the sessions. In 96% of these corrections the GTV was enlarged and resulted in a median improvement of 1% for the target coverage. The median on-couch time was 22 min. A third of the session time consisted of reoptimization of the treatment plan. Fiducial markers were visible on the CBCTs and aided the tumor localization.ConclusionsAI-driven CBCT-guided oART aided by fiducial markers is feasible for bladder cancer radiotherapy treatment including a SIB. The quality of the adaptive plans met the clinical requirements and fiducial markers were visible enabling consistent daily tumor localization. Improved automatic delineation to lower the need for manual corrections and faster reoptimization would result in shorter session time.
| S-EPMC10557331 | biostudies-literature