Evaluation of a cycle-generative adversarial network-based cone-beam CT to synthetic CT conversion algorithm for adaptive radiation therapy

PurposeImage-guided radiation therapy could benefit from implementing adaptive radiation therapy (ART) techniques. A cycle-generative adversarial network (cycle-GAN)-based cone-beam computed tomography (CBCT)-to-synthetic CT (sCT) conversion algorithm was evaluated regarding image quality, image segmentation and dosimetric accuracy for head and neck (H&N), thoracic and pelvic body regions.MethodsUsing a cycle-GAN, three body site-specific models were priorly trained with independent paired CT and CBCT datasets of a kV imaging system (XVI, Elekta). sCT were generated based on first-fraction CBCT for 15 patients of each body region. Mean errors (ME) and mean absolute errors (MAE) were analyzed for the sCT. On the sCT, manually delineated structures were compared to deformed structures from the planning CT (pCT) and evaluated with standard segmentation metrics. Treatment plans were recalculated on sCT. A comparison of clinically relevant dose-volume parameters (D₉₈, D₅₀ and D₂ of the target volume) and 3D-gamma (3%/3mm) analysis were performed.ResultsThe mean ME and MAE were 1.4, 29.6, 5.4 Hounsfield units (HU) and 77.2, 94.2, 41.8 HU for H&N, thoracic and pelvic region, respectively. Dice similarity coefficients varied between 66.7 ± 8.3% (seminal vesicles) and 94.9 ± 2.0% (lungs). Maximum mean surface distances were 6.3 mm (heart), followed by 3.5 mm (brainstem). The mean dosimetric differences of the target volumes did not exceed 1.7%. Mean 3D gamma pass rates greater than 97.8% were achieved in all cases.ConclusionsThe presented method generates sCT images with a quality close to pCT and yielded clinically acceptable dosimetric deviations. Thus, an important prerequisite towards clinical implementation of CBCT-based ART is fulfilled.     

A practical methodology to improve the dosimetric accuracy of MR-based radiotherapy simulation for brain tumors

PurposeTo investigate the dosimetric accuracy of synthetic computed tomography (sCT) images generated by a clinically-ready voxel-based MRI simulation package, and to develop a simple and feasible method to improve the accuracy.Methods20 patients with brain tumor were selected to undergo CT and MRI simulation. sCT images were generated by a clinical MRI simulation package. The discrepancy between planning CT and sCT in CT number and body contour were evaluated. To resolve the discrepancies, an sCT specific CT-relative electron density (RED) calibration curve was used, and a layer of pseudo-skin was created on the sCT. The dosimetric impact of these discrepancies, and the improvement brought about by the modifications, were evaluated by a planning study. Volumetric modulated arc therapy (VMAT) treatment plans for each patient were created and optimized on the planning CT, which were then transferred to the original sCT and the modified-sCT for dose re-calculation. Dosimetric comparisons and gamma analysis between the calculated doses in different images were performed.ResultsThe average gamma passing rate with 1%/1 mm criteria was only 70.8% for the comparison of dose distribution between planning CT and original sCT. The mean dose difference between the planning CT and the original sCT were −1.2% for PTV D₉₅ and −1.7% for PTV D_max, while the mean dose difference was within 0.7 Gy for all relevant OARs. After applying the modifications on the sCT, the average gamma passing rate was increased to 92.2%. Mean dose difference in PTV D₉₅ and D_max were reduced to −0.1% and −0.3% respectively. The mean dose difference was within 0.2 Gy for all OAR structures and no statistically significant difference were found.ConclusionsThe modified-sCT demonstrated improved dosimetric agreement with the planning CT. These results indicated the overall dosimetric accuracy and practicality of this improved MR-based treatment planning method.     

Multi-Atlas Based Adaptive Active Contour Model with Application to Organs at Risk Segmentation in Brain MR Images

BackgroundAccurate delineation of organs at risk (OARs) is critical in radiotherapy. Manual delineation is tedious and suffers from both interobserver and intraobserver variability. Automatic segmentation of brain MR images has a wide range of applications in brain tumor radiotherapy. In this paper, we propose a multi-atlas based adaptive active contour model for OAR automatic segmentation in brain MR images.MethodsThe proposed method consists of two parts: multi-atlas based OAR contour initiation and an adaptive edge and local region based active contour evolution. In the adaptive active contour model, we define an energy functional with an adaptive edge intensity fitting force which is responsible for evaluating contour inwards or outwards, and a local region intensity fitting force which guides the evolution of the contour.ResultsExperimental results show that the proposed method achieved more accurate segmentation results in brainstem, eyes and lens automatic segmentation with the Dice Similar Coefficient (DSC) value of 87.19%, 91.96%, 77.11% respectively. Besides, the dosimetric parameters also demonstrate the high consistency of the manual OAR delineations and the auto segmentation results of the proposed method in brain tumor radiotherapy.ConclusionsThe geometric and dosimetric evaluations show the desirable performance of the proposed method on the application of OARs segmentations in brain tumor radiotherapy.     

A dosimetric evaluation of IGART strategies for cervix cancer treatment

PurposeImage guided adaptive radiotherapy (IGART) strategies can be used to include the temporal aspects of radiotherapy treatment. A dosimetric evaluation of on- and off-line adaptive strategies are done in this study.MethodsA library of equivalent uniform dose (EUD)-based Intensity Modulated Radiotherapy Treatment plans with incrementally increasing clinical target volume (CTV)-to-planning target volume (PTV) margins were developed for 10 patients. Utilizing daily computed tomography (CT) images an on-line strategy using a margin-of-the-day (MOD) concept that selects the best plan from the library was employed. This was compared to an off-line strategy with full analysis of accumulated dose between fractions where dosimetric deviations from the treatment intent triggered plan adaptation. A fixed margin treatment approach was used as benchmark.ResultsUsing fixed margins of <15 mm lead to under-dosages of more than 5 Gy in total delivered dose. The average CTV EUD for the off-line and on-line strategy was 50.0 ± 5.0 Gy and 50.4 ± 2.0 Gy respectively and OAR doses were comparable.ConclusionA fixed margin treatment approach yields a significant probability of CTV under-dosage. Using EUD dose metrics CTV coverage can be restored in both the off-line and on-line adaptive strategies at acceptable OAR dose levels. Considering the workload and time on the treatment machine, the off-line strategy proves to be sufficient and more practical.     

Evaluation of patient organ doses from kilovoltage cone-beam CT imaging in radiation therapy

BackgroundCurrently, CBCT system is an indispensable component of radiation therapy units. Because of that, it is important in treatment planning and diagnosis. CBCT is also an crucial tool for patient positioning and verification in image-guided radiation therapy (IGRT). Therefore, it is critical to investigate the patient organ doses arising from CBCT imaging. The purpose of this study is to evaluate patient organ doses and effective dose to patients from three different protocols of Elekta Synergy XVI system for kV CBCT imaging examinations in image guided radiation therapy.Materials and methodsOrgan dose measurements were done with thermoluminescent dosimeters in Alderson RA NDO male phantom for head & neck (H&N), chest and pelvis protocols of the Elekta Synergy XVI kV CBCT system. From the measured organ dose, effective dose to patients were calculated according to the International Commission on Radiological Protection 103 report recommendations.ResultsFor H&N, chest and pelvis scans, the organ doses were in the range of 0.03–3.43 mGy, 6.04–22.94 mGy and 2.5–25.28 mGy, respectively. The calculated effective doses were 0.25 mSv, 5.56 mSv and 4.72 mSv, respectively.ConclusionThe obtained results were consistent with the most published studies in the literature. Although the doses to patient organs from the kV CBCT system were relatively low when compared with the prescribed treatment dose, the amount of delivered dose should be monitored and recorded carefully in order to avoid secondary cancer risk, especially in pediatric examinations.     

An Automated Treatment Plan Quality Control Tool for Intensity-Modulated Radiation Therapy Using a Voxel-Weighting Factor-Based Re-Optimization Algorithm

Intensity-modulated radiation therapy (IMRT) currently plays an important role in radiotherapy, but its treatment plan quality can vary significantly among institutions and planners. Treatment plan quality control (QC) is a necessary component for individual clinics to ensure that patients receive treatments with high therapeutic gain ratios. The voxel-weighting factor-based plan re-optimization mechanism has been proved able to explore a larger Pareto surface (solution domain) and therefore increase the possibility of finding an optimal treatment plan. In this study, we incorporated additional modules into an in-house developed voxel weighting factor-based re-optimization algorithm, which was enhanced as a highly automated and accurate IMRT plan QC tool (TPS-QC tool). After importing an under-assessment plan, the TPS-QC tool was able to generate a QC report within 2 minutes. This QC report contains the plan quality determination as well as information supporting the determination. Finally, the IMRT plan quality can be controlled by approving quality-passed plans and replacing quality-failed plans using the TPS-QC tool. The feasibility and accuracy of the proposed TPS-QC tool were evaluated using 25 clinically approved cervical cancer patient IMRT plans and 5 manually created poor-quality IMRT plans. The results showed high consistency between the QC report quality determinations and the actual plan quality. In the 25 clinically approved cases that the TPS-QC tool identified as passed, a greater difference could be observed for dosimetric endpoints for organs at risk (OAR) than for planning target volume (PTV), implying that better dose sparing could be achieved in OAR than in PTV. In addition, the dose-volume histogram (DVH) curves of the TPS-QC tool re-optimized plans satisfied the dosimetric criteria more frequently than did the under-assessment plans. In addition, the criteria for unsatisfied dosimetric endpoints in the 5 poor-quality plans could typically be satisfied when the TPS-QC tool generated re-optimized plans without sacrificing other dosimetric endpoints. In addition to its feasibility and accuracy, the proposed TPS-QC tool is also user-friendly and easy to operate, both of which are necessary characteristics for clinical use.     

Evaluation of plan quality improvements in PlanIQ-guided Autoplanning

AimPhilips recently integrated PlanIQ with Autoplan® in Pinnacle³ TPS (V16.2). The objective of the present work is to quantitatively demonstrate how this integration improves the plan quality.BackgroundPinnacle³ Autoplan® is the tool that generates the treatment plans with clinically acceptable plan quality with less manual intervention. In the recent past, a new tool called PlanIQ (Sun Nuclear Corp.) was introduced for a priori estimation of the best possible sparing of an organ at risk (OAR) for a given patient anatomy. Philips has recently integrated PlanIQ tool with Autoplan® for a seamless and efficient planning workflow.Materials and methodsWe have performed this evaluation in Pinnacle³ TPS (V.16.2) for the VMAT treatment technique. All plans were created using Varian True beam machine with the dual arc technique. Basically, we created two sets of VMAT plans using 6 MV photons. In the first set of VMAT plans (AP_RTOG), we used OAR goals from either RTOG guidelines to perform optimization using Autoplan®. Subsequently, we exported the same dataset to the PlanIQ system to perform feasibility analysis on the OAR goals. These newly obtained OAR goals from PlanIQ were used to generate the other set of plans (AP_PlanIQ plans). We compared the dosimetric results from these two sets of plans in five cases, such as brain, head & neck, lung, abdomen and prostate.ResultsWe compared the dosimetric results for AP_RTOG and AP_PlanIQ plans. We used RTOG guidelines to evaluate the plans and observed that while both sets of plans were meeting the RTOG guidelines in terms of OAR sparing, the AP_PlanIQ plans were significantly better in terms of OAR sparing as compared to AP_RTOG plans without any compromise in the target coverage.ConclusionThe results indicate that, although Autoplan helps achieve the user-defined goals without much manual intervention, the plan quality (OAR sparing) can be significantly improved without taking many iterative steps when PlanIQ suggested clinical goals are used in the Autoplan-based optimization.Advances in knowledgeAt present, there are no published material available about the efficacy of the integration of PlanIQ with Autoplanning®. In the present work, our objective is to evaluate the improvements in plan quality resulting from this integration.     

Prediction of multi-criteria optimization (MCO) parameter efficiency in volumetric modulated arc therapy (VMAT) treatment planning using machine learning (ML)

PurposeTo predict the impact of optimization parameter changes on dosimetric plan quality criteria in multi-criteria optimized volumetric-modulated-arc therapy (VMAT) planning prior to optimization using machine learning (ML).MethodsA data base comprising a total of 21,266 VMAT treatment plans for 44 cranial and 18 spinal patient geometries was generated. The underlying optimization algorithm is governed by three highly composite parameters which model a combination of important aspects of the solution. Patient geometries were parametrized via volume- and shape properties of the voxel objects and overlap-volume histograms (OVH) of the planning-target-volume (PTV) and a relevant organ-at-risk (OAR). The impact of changes in one of the three optimization parameters on the maximally achievable value range of five dosimetric properties of the resulting dose distributions was studied. To predict the extent of this impact based on patient geometry, treatment site, and current parameter settings prior to optimization, three different ML-models were trained and tested. Precision-recall curves, as well as the area-under-curve (AUC) of the resulting receiver-operator-characteristic (ROC) curves were analyzed for model assessment.ResultsSuccessful identification of parameter regions resulting in a high variability of dosimetric plan properties depended on the choice of geometry features, the treatment indication and the plan property under investigation. AUC values between 0.82 and 0.99 could be achieved. The best average-precision (AP) values obtained from the corresponding precision/recall curves ranged from 0.71 to 0.99.ConclusionsMachine learning models trained on a database of pre-optimized treatment plans can help finding relevant optimization parameter ranges prior to optimization.     

Techniques for adaptive prostate radiotherapy

Variations in the position and shape of the prostate make accurate setup and treatment challenging. Adaptive radiation therapy (ART) techniques seek to alter the treatment plan, at one or more points throughout the treatment course, in response to changes in patient anatomy observed between planning and pre-treatment images. This article reviews existing and developing ART techniques for prostate cancer along with an overview of supporting in-room imaging technologies. Challenges to the clinical implementation of adaptive radiotherapy are also discussed.     

Integral dose based inverse optimization objective function promises lower toxicity in head-and-neck

PurposeThe voxels in a CT data sets contain density information. Besides its use in dose calculation density has no other application in modern radiotherapy treatment planning. This work introduces the use of density information by integral dose minimization in radiotherapy treatment planning for head-and-neck squamous cell carcinoma (HNSCC).Materials and methodsEighteen HNSCC cases were studied. For each case two intensity modulated radiotherapy (IMRT) plans were created: one based on dose-volume (DV) optimization, and one based on integral dose minimization (Energy hereafter) inverse optimization. The target objective functions in both optimization schemes were specified in terms of minimum, maximum, and uniform doses, while the organs at risk (OAR) objectives were specified in terms of DV- and Energy-objectives respectively. Commonly used dosimetric measures were applied to assess the performance of Energy-based optimization. In addition, generalized equivalent uniform doses (gEUDs) were evaluated. Statistical analyses were performed to estimate the performance of this novel inverse optimization paradigm.ResultsEnergy-based inverse optimization resulted in lower OAR doses for equivalent target doses and isodose coverage. The statistical tests showed dose reduction to the OARs with Energy-based optimization ranging from ∼2% to ∼15%.ConclusionsIntegral dose minimization based inverse optimization for HNSCC promises lower doses to nearby OARs. For comparable therapeutic effect the incorporation of density information into the optimization cost function allows reduction in the normal tissue doses and possibly in the risk and the severity of treatment related toxicities.     

Dosimetric evaluation of irregular surface compensator and intensity-modulated radiotherapy in breast radiotherapy

BackgroundThis dosimetric study aims to evaluate the dosimetric advantage of the irregular surface compensator (ISC) compared with the intensity-modulated radiotherapy (IMRT).Materials and methodsTen patients with whole breast irradiation were planned with the ISC and IMRT techniques. Six different beam directions were selected for IMRT and ISC plans. The treatment plans were evaluated with respect to planning target coverage, dose homogeneity index (DHI) and organs at risk (OARs) sparing. Monitor units (MUs) and the delivery time were analysed for treatment efficiency.ResultsThe ISC technique provides a better coverage of the PTV and statistically significantly better homogeneity of the dose distribution. For the ipsilateral lung and heart, ISC and IMRT techniques deliver almost the same dose in all plans. However, MU counts and delivery time were significantly lower with the IMRT technique (p < 0.05).ConclusionFor breast radiotherapy, when the ISC method was compared to the IMRT method, ISC provided better dose distribution for the target.     

Proton re-irradiation of unresectable recurrent head and neck cancers

BackgroundThis study presents a retrospective analysis (efficacy and toxicity) of outcomes in patients with unresectable recurrence of previously irradiated head and neck (H&N) cancers treated with proton therapy. Locoregional recurrence is the main pattern of failure in the treatment of H&N cancers. Proton re-irradiation in patients with relapse after prior radiotherapy might be valid as promising as a challenging treatment option.Materials and methodsFrom November 2015 to January 2020, 30 patients with in-field recurrence of head and neck cancer, who were not suitable for surgery due to medical contraindications, tumor localization, or extent, received re-irradiation with intensity-modulated proton therapy (IMPT). Sites of retreatment included the aerodigestive tract (60%) and the base of skull (40%). The median total dose of prior radiotherapy was 55.0 Gy. The median time to the second course was 38 months. The median re-irradiated tumor volume was 158.1 cm³. Patients were treated with 2.0, 2.4, and 3.0 GyRBE per fraction, with a median equivalent dose (EQD₂) of 57.6 Gy (α/β = 10). Radiation-induced toxicity was recorded according to the RTOG/EORTC criteria.ResultsThe 1- and 2-year local control (LC), progression-free survival (PFS), and overall survival (OS) were 52.6/21.0, 21.9/10.9, and 73.4/8.4%, respectively, with a median follow-up time of 21 months. The median overall survival was 16 months. Acute grade 3 toxicity was observed in one patient (3.3%). There were five late severe side effects (16.6%), with one death associated with re-irradiation.ConclusionRe-irradiation with a proton beam can be considered a safe and efficient treatment even for a group of patients with unresectable recurrent H&N cancers.     

Analysis of a volumetric-modulated arc therapy (VMAT) single phase prostate template as a class solution

AimTo assess a class solution template for volumetric-modulated arc therapy (VMAT) for prostate cancer using plan analysis software.BackgroundVMAT is a development of intensity-modulated radiotherapy (IMRT) with potential advantages for the delivery of radiotherapy (RT) in prostate cancer. Class solutions are increasingly used for facilitating RT planning. Plan analysis software provides an objective tool for evaluating class solutions.Materials and methodsThe class solution for VMAT was based on the current static field IMRT template. The plans of 77 prostate cancer patients were evaluated using a set of in-house plan quality metrics (scores) (PlanIQ™, Sun Nuclear Corporation). The metrics compared the class solution for VMAT planning with the IMRT template and the delivered clinical plan (CP). Eight metrics were associated with target coverage and ten with organs-at-risk (OAR). Individual metrics were summed and the combined scores were subjected to non-parametric analysis. The low-dose wash for both static IMRT and VMAT plans were evaluated using 40 Gy and 25 Gy isodose volumes.ResultsVMAT plans were of equal or better quality than the IMRT template and CP for target coverage (combined score) and OAR combined score. The 40 Gy isodose volume was marginally higher with VMAT than IMRT (4.9%) but lower than CP (−6.6%)(P = 0.0074). The 25 Gy volume was significantly lower with VMAT than both IMRT (−32.7%) and CP (−34.4%)(P < 0.00001).ConclusionsAutomated VMAT planning for prostate cancer is feasible and the plans are equal to or better than the current IMRT class solution and the delivered clinical plan.     

Critical Structure Sparing in Stereotactic Ablative Radiotherapy for Central Lung Lesions: Helical Tomotherapy vs. Volumetric Modulated Arc Therapy

Background

Helical tomotherapy (HT) and volumetric modulated arc therapy (VMAT) are both advanced techniques of delivering intensity-modulated radiotherapy (IMRT). Here, we conduct a study to compare HT and partial-arc VMAT in their ability to spare organs at risk (OARs) when stereotactic ablative radiotherapy (SABR) is delivered to treat centrally located early stage non-small-cell lung cancer or lung metastases.

Methods

12 patients with centrally located lung lesions were randomly chosen. HT, 2 & 8 arc (Smart Arc, Pinnacle v9.0) plans were generated to deliver 70 Gy in 10 fractions to the planning target volume (PTV). Target and OAR dose parameters were compared. Each technique’s ability to meet dose constraints was further investigated.

Results

HT and VMAT plans generated essentially equivalent PTV coverage and dose conformality indices, while a trend for improved dose homogeneity by increasing from 2 to 8 arcs was observed with VMAT. Increasing the number of arcs with VMAT also led to some improvement in OAR sparing. After normalizing to OAR dose constraints, HT was found to be superior to 2 or 8-arc VMAT for optimal OAR sparing (meeting all the dose constraints) (p = 0.0004). All dose constraints were met in HT plans. Increasing from 2 to 8 arcs could not help achieve optimal OAR sparing for 4 patients. 2/4 of them had 3 immediately adjacent structures.

Conclusion

HT appears to be superior to VMAT in OAR sparing mainly in cases which require conformal dose avoidance of multiple immediately adjacent OARs. For such cases, increasing the number of arcs in VMAT cannot significantly improve OAR sparing.     

A support vector machine tool for adaptive tomotherapy treatments: Prediction of head and neck patients criticalities

PurposeAdaptive radiation therapy (ART) is an advanced field of radiation oncology. Image-guided radiation therapy (IGRT) methods can support daily setup and assess anatomical variations during therapy, which could prevent incorrect dose distribution and unexpected toxicities. A re-planning to correct these anatomical variations should be done daily/weekly, but to be applicable to a large number of patients, still require time consumption and resources. Using unsupervised machine learning on retrospective data, we have developed a predictive network, to identify patients that would benefit of a re-planning.Methods1200 MVCT of 40 head and neck (H&N) cases were re-contoured, automatically, using deformable hybrid registration and structures mapping. Deformable algorithm and MATLAB^® homemade machine learning process, developed, allow prediction of criticalities for Tomotherapy treatments.ResultsUsing retrospective analysis of H&N treatments, we have investigated and predicted tumor shrinkage and organ at risk (OAR) deformations. Support vector machine (SVM) and cluster analysis have identified cases or treatment sessions with potential criticalities, based on dose and volume discrepancies between fractions. During 1st weeks of treatment, 84% of patients shown an output comparable to average standard radiation treatment behavior. Starting from the 4th week, significant morpho-dosimetric changes affect 77% of patients, suggesting need for re-planning. The comparison of treatment delivered and ART simulation was carried out with receiver operating characteristic (ROC) curves, showing monotonous increase of ROC area.ConclusionsWarping methods, supported by daily image analysis and predictive tools, can improve personalization and monitoring of each treatment, thereby minimizing anatomic and dosimetric divergences from initial constraints.     

Dosimetric study of Hounsfield number correction effect in areas influenced by contrast product in lungs case

BackgroundThe aim of the study was dosimetric effect quantification of exclusive computed tomography (CT) use with an intravenous (IV) contrast agent (CA ), on dose distribution of 3D-CRT treatment plans for lung cancer. Furthermore, dosimetric advantage investigation of manually contrast-enhanced region overriding, especially the heart.Materials and methodsTen patients with lung cancer were considered. For each patient two planning CT sets were initially taken with and without CA. Treatment planning were optimized based on CT scans without CA. All plans were copied and recomputed on scans with CA. In addition, scans with IV contrast were copied and density correction was performed for heart contrast enhanced. Same plans were copied and replaced to undo dose calculation errors that may be caused by CA. Eventually, dosimetric evaluations based on dose volume histograms (DVHs) of planning target volumes (PTV) and organs at-risk were studied and analyzed using the Wilcoxon’s signed rank test.ResultsThere is no statistically significant difference in dose calculation for the PTV maximum, mean, minimum doses, spinal cord maximum doses and lung volumes that received 20 and 30 Gy, between planes calculated with and without contrast scans (p > 0.05) and also for contrast scan, with manual regions overriding.ConclusionsDose difference caused by the contrast agent is negligible and not significant. Therefore, there is no justification to perform two scans, and using an IV contrast enhanced scan for dose calculation is sufficient.