ABSTRACT
Purpose: Online adaptive radiation therapy (OART) uses daily imaging to identify changes in the patient's anatomy and generate a new treatment plan adapted to these changes for each fraction. The aim of this study was to determine the intrafraction motion and planning target volume (PTV) margins required for an OART workflow on the Varian Ethos system. Methods and Materials: Sixty-five fractions from 13 previously treated OART patients were analyzed for this retrospective study. The prostate and seminal vesicles were contoured by a radiation oncologist on 2 cone beam computed tomography scans (CBCT) for each fraction, the initial CBCT at the start of the treatment session, and the verification CBCT immediately before beam-on. In part 1 of the study, PTVs of different sizes were defined on the initial CBCT, and the geometric overlap with the clinical target volume (CTV) on the verification CBCT was used to determine the optimal OART margin. This was performed with and without a patient realignment shift by registering the verification CBCT to the initial CBCT. In part 2 of the study, the margins determined in part 1 were used for simulated Ethos OART treatments on all 65 fractions. The resultant coverage to the CTV on the verification CBCT, was compared with an image guided radiation therapy (IGRT) workflow with 7-mm margins. Results: Part 1 of the study found, if a verification CBCT and shift is performed, a 4-mm margin on the prostate and 5 mm on the seminal vesicles resulted in 95% of the CTV covered by the PTV in >90% of fractions, and 98% of the CTV covered by the PTV in >80% of fractions. Part 2 of the study found when these margins were used in an Ethos OART workflow, they resulted in CTV coverage that was superior to an IGRT workflow with 7-mm margins. Conclusions: A 4mm prostate margin and 5-mm seminal vesicles margin in an OART workflow with verification imaging are adequate to ensure coverage on the Varian Ethos system. Larger margins may be required if using an OART workflow without verification imaging.
ABSTRACT
Deformable image registration (DIR) is a versatile tool used in many applications in radiotherapy (RT). DIR algorithms have been implemented in many commercial treatment planning systems providing accessible and easy-to-use solutions. However, the geometric uncertainty of DIR can be large and difficult to quantify, resulting in barriers to clinical practice. Currently, there is no agreement in the RT community on how to quantify these uncertainties and determine thresholds that distinguish a good DIR result from a poor one. This review summarises the current literature on sources of DIR uncertainties and their impact on RT applications. Recommendations are provided on how to handle these uncertainties for patient-specific use, commissioning, and research. Recommendations are also provided for developers and vendors to help users to understand DIR uncertainties and make the application of DIR in RT safer and more reliable.
Subject(s)
Image Processing, Computer-Assisted , Radiotherapy Planning, Computer-Assisted , Humans , Radiotherapy Dosage , Uncertainty , Image Processing, Computer-Assisted/methods , Radiotherapy Planning, Computer-Assisted/methods , AlgorithmsABSTRACT
Contouring has become an increasingly important aspect of radiotherapy due to inverse planning. Several studies have suggested that the clinical implementation of automated contouring tools can reduce inter-observer variation while increasing contouring efficiency, thereby improving the quality of radiotherapy treatment and reducing the time between simulation and treatment. In this study, a novel, commercial automated contouring tool based on machine learning, the AI-Rad Companion Organs RT™ (AI-Rad) software (Version VA31) (Siemens Healthineers, Munich, Germany), was assessed against both manually delineated contours and another commercially available automated contouring software, Varian Smart Segmentation™ (SS) (Version 16.0) (Varian, Palo Alto, CA, United States). The quality of contours generated by AI-Rad in Head and Neck (H&N), Thorax, Breast, Male Pelvis (Pelvis_M), and Female Pelvis (Pevis_F) anatomical areas was evaluated both quantitatively and qualitatively using several metrics. A timing analysis was subsequently performed to explore potential time savings achieved by AI-Rad. Results showed that most automated contours generated by AI-Rad were not only clinically acceptable and required minimal editing, but also superior in quality to contours generated by SS in multiple structures. In addition, timing analysis favored AI-Rad over manual contouring, indicating the largest time saving (753s per patient) in the Thorax area. AI-Rad was concluded to be a promising automated contouring solution that generated clinically acceptable contours and achieved time savings, thereby greatly benefiting the radiotherapy process.
Subject(s)
Head and Neck Neoplasms , Radiotherapy Planning, Computer-Assisted , Humans , Male , Female , Radiotherapy Planning, Computer-Assisted/methods , Neck , Head and Neck Neoplasms/radiotherapy , Head , Machine Learning , Organs at RiskABSTRACT
INTRODUCTION: The Ethos treatment planning system allows for the rapid generation of online adaptive treatment plans while the patient is on the treatment couch. One promising application of online adaptive radiotherapy is its use in stereotactic radiotherapy. The purpose of this study was to ensure the Ethos treatment planning system (TPS) can produce clinically acceptable stereotactic plans, that are non-inferior to those from the Eclipse TPS. METHOD: Forty patients that received previous stereotactic radiotherapy treatment on a Halcyon, 20 of which were lung cases, and 20 that were brain cases, were replanned using the Ethos TPS. The generated IMRT and VMAT plans were compared to the clinical Eclipse VMAT plan. RESULTS: This study found that the Ethos TPS can produce VMAT plans of equivalent quality (target coverage, conformity and OAR doses) to those from the Eclipse TPS for lung SBRT and brain SRT. The IMRT plans produced by the Ethos planning system were marginally inferior to Eclipse VMAT plans, with the differences likely primarily due to beam geometry rather than the optimization system. Ethos plans were generally more modulated than Eclipse plans. With careful selection of optimization structures and reduction in the body contour, VMAT plan generation time could be reduced by 87%. CONCLUSION: Ethos can generate stereotactic VMAT plans that are equivalent to those from Eclipse in the timeframe required for online adaptive radiotherapy.
Subject(s)
Radiation Oncology , Radiosurgery , Radiotherapy, Intensity-Modulated , Humans , Radiotherapy Planning, Computer-Assisted , Radiotherapy Dosage , Organs at RiskABSTRACT
The Varian Ethos system allows for online adaptive treatments through the utilization of artificial intelligence (AI) and deformable image registration which automates large parts of the anatomical contouring and plan optimization process. In this study, treatments of intact prostate and prostate bed, with and without nodes, were simulated for 182 online adaptive fractions, and then a further 184 clinical fractions were delivered on the Ethos system. Frequency and magnitude of contour edits were recorded, as well as a range of plan quality metrics. From the fractions analyzed, 11% of AI generated contours, known as influencer contours, required no change, and 81% required minor edits in any given fraction. The frequency of target and noninfluencer organs at risk (OAR) contour editing varied substantially between different targets and noninfluencer OARs, although across all targets 72% of cases required no edits. The adaptive plan was the preference in 95% of fractions. The adaptive plan met more goals than the scheduled plan in 78% of fractions, while in 15% of fractions the number of goals met was the same. The online adaptive recontouring and replanning process was carried out in 19 min on average. Significant improvements in dosimetry are possible with the Ethos online adaptive system in prostate radiotherapy.
Subject(s)
Prostatic Neoplasms , Radiotherapy, Intensity-Modulated , Artificial Intelligence , Humans , Male , Organs at Risk , Prostatic Neoplasms/diagnostic imaging , Prostatic Neoplasms/radiotherapy , Radiotherapy Dosage , Radiotherapy Planning, Computer-AssistedABSTRACT
PURPOSE: Cone-beam computed tomography (CBCT) is increasingly utilized in radiation therapy for image guidance and adaptive applications. While iterative reconstruction algorithms have been shown to outperform traditional filtered back-projection methods in improving image quality and reducing imaging dose, they cannot handle data truncation in the axial view, which frequently occurs in the full-fan partial-trajectory acquisition mode. This proof-of-concept study presents a novel approach on truncation artifact reduction by utilizing a priori preconditioned information as the initial input for the iterative algorithm. METHODS: Projections containing axial truncation were used for image reconstruction in extended axial field-of-view (AFOV) using the conjugate gradient least-squares (CGLS) algorithm. A priori information in the form of a planning fan-beam CT (FBCT) was repositioned in the expected CBCT imaging geometry, then further processed to dampen high-density features and convolved with a cubic Gaussian kernel to ensure differentiability for the gradient descent method. Anatomical and positional differences between the estimated and the actual imaging object were introduced to verify the efficacy of the proposed method. RESULTS: Extending the reconstruction AFOV alone could partially reduce truncation artifact. Using a priori information directly resulted in ghosting artifact when there were anatomical and positional differences between the estimated and the actual imaging object. Using a priori preconditioned information was shown to effectively reduce truncation artifact and recover peripheral information. CONCLUSIONS: Using a priori preconditioned information can effectively alleviate truncation artifact and assist recovery of peripheral information in iterative CBCT reconstruction.
Subject(s)
Artifacts , Image Processing, Computer-Assisted , Algorithms , Cone-Beam Computed Tomography , Phantoms, ImagingABSTRACT
Varian (Palo Alto, California, United States) recently released an online adaptation treatment platform, Ethos, which has introduced a new Dose Preview and Automated Plan Generation module despite sharing identical beam data with the existing Halcyon linac. The module incorporates a preconfigured beam model and the Acuros XB algorithm (Ethos AXB model) to generate final dose calculations from an initial fluence optimization. In this study, we comprehensively validated the accuracy of the Ethos AXB model by comparing it against the Halcyon AXB model, the Halcyon Anisotropic Analytical Algorithm (AAA) model, and measurements acquired on an Ethos linac. Results indicated that the Ethos AXB model demonstrated a comparable if not superior dosimetric accuracy to the Halcyon AXB model in basic and complex calculations, and at the same time its dosimetric accuracy in modulated and heterogeneous plans was better than that of the Halcyon AAA model. Despite the fact that the same algorithm was utilized, the Ethos AXB model and the Halcyon AXB model still exhibited variations across a range of tests, although these variations were predominantly insignificant in the clinical environment. The accuracy of the Ethos AXB model has been successfully verified in this study and is considered appropriate for the current clinical scope. On the basis of this study, clinical physicists can perform a data validation instead of a full data commissioning when implementing the Ethos system, thereby adopting a more efficient approach for Ethos installation.
Subject(s)
Radiometry , Radiotherapy Planning, Computer-Assisted , Algorithms , Humans , Phantoms, Imaging , Radiotherapy DosageABSTRACT
PURPOSE: To present the development of an in-house coded solution for treatment planning of tangential breast radiotherapy that creates single click plans by emulating the iterative optimization process of human dosimetrists. METHOD: One hundred clinical breast cancer patients were retrospectively planned with an automated planning (AP) code incorporating the hybrid intensity-modulated radiotherapy (IMRT) approach. The code automates all planning processes including plan generation, beam generation, gantry and collimator angle determination, open segments and dynamic IMRT fluence and calculations. Thirty-nine dose volume histogram (DVH) metrics taken from three international recommendations were compared between the automated and clinical plans (CP), along with median interquartile analysis of the DVH distributions. Total planning time and delivery QA were also compared between the plan sets. RESULTS: Of the 39 planning metrics analyzed 23 showed no significant difference between clinical and automated planning techniques. Of the 16 metrics with statistically significant variations, 2 were improved in the clinical plans in comparison to 14 improved in the AP plans. Automated plans produced a greater number of ideal plans against international guidelines as per EviQ (AP:77%, CP:68%), RTOG 1005 (AP:80%, CP:71%), and London Cancer references (AP:80%, CP:75%). Delivery QA results for both techniques were equivalent. Automated planning techniques resulted in an average reduction in planning time from 23 to 5 minutes. CONCLUSION: We have introduced an automated planning code with iterative optimization that produces equivalent quality plans to manual clinical planning. The resultant change in workflow results in a reduction in treatment planning times.
Subject(s)
Breast Neoplasms , Radiotherapy, Intensity-Modulated , Breast , Breast Neoplasms/diagnostic imaging , Breast Neoplasms/radiotherapy , Female , Humans , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted , Retrospective StudiesABSTRACT
Cone-beam computed tomography (CBCT) is an important imaging modality for image-guided radiotherapy and adaptive radiotherapy. Feldkamp-Davis-Kress (FDK) method is widely adopted in clinical CBCT reconstructions due to its fast and robust application. While iterative algorithms have been shown to outperform FDK techniques in reducing noise and imaging dose, they are unable to correct projection-domain artefacts such as beam hardening and scatter. Empirical correction techniques require a holistic approach as beam hardening and scatter coexist in the measurement data. This multi-part proof of concept study conducted in MATLAB presents a novel approach to artefact reduction for CBCT image reconstruction. Firstly, we decoupled the beam hardening and scatter contributions originating from the imaging object and the bowtie filter. Next, a model was constructed to apply pixel-wise corrections to separately account for artefacts induced by the imaging object and the bowtie filter, in order to produce mono-energetic equivalent and scatter-compensated projections. Finally, the effectiveness of the correction model was tested on an offset phantom scan as well as a clinical brain scan. A conjugate-gradient least-squares algorithm was implemented over five iterations using FDK result as the initial input. Our proposed correction model was shown to effectively reduce cupping and shading artefacts in both phantom and clinical studies. This simple yet effective correction model could be readily implemented by physicists seeking to explore the benefits of iterative reconstruction.
Subject(s)
Artifacts , Cone-Beam Computed Tomography , Algorithms , Image Processing, Computer-Assisted , Phantoms, ImagingABSTRACT
Image registration is a process that underlies many new techniques in radiation oncology - from multimodal imaging and contour propagation in treatment planning to dose accumulation throughout treatment. Deformable image registration (DIR) is a subset of image registration subject to high levels of complexity in process and validation. A need for local guidance to assist in high-quality utilisation and best practice was identified within the Australian community, leading to collaborative activity and workshops. This report communicates the current limitations and best practice advice from early adopters to help guide those implementing DIR in the clinic at this early stage. They are based on the state of image registration applications in radiotherapy in Australia and New Zealand (ANZ), and consensus discussions made at the 'Deforming to Best Practice' workshops in 2018. The current status of clinical application use cases is presented, including multimodal imaging, automatic segmentation, adaptive radiotherapy, retreatment, dose accumulation and response assessment, along with uptake, accuracy and limitations. Key areas of concern and preliminary suggestions for commissioning, quality assurance, education and training, and the use of automation are also reported. Many questions remain, and the radiotherapy community will benefit from continued research in this area. However, DIR is available to clinics and this report is intended to aid departments using or about to use DIR tools now.
Subject(s)
Image Processing, Computer-Assisted/methods , Radiotherapy Planning, Computer-Assisted/methods , Radiotherapy, Image-Guided/methods , HumansABSTRACT
Respiratory motion management has become increasingly important in the accurate delivery of radiotherapy. Recently, a novel device, Breathe Well, has been developed, which provides motion management by tracking the movement of external surrogates. This paper has comprehensively assessed the measurement accuracy of Breathe Well in various clinical conditions. The results suggest that the Breathe Well device has good reproducibility, although it demonstrates larger measurement errors in certain setup positions. However, this measurement error becomes trivial if it is setup consistently over the entire course of treatment. For other setup positions, the Breathe Well device can reach a ± 1.0 mm spatial accuracy when the motion amplitude is less than or equal to 20 mm, similar to that of the Varian RPM system. The phase measurement from Breathe Well agrees well with that of the RPM and the QUASAR phantom, indicating that the device has potentials for phase-related clinical applications such as gating.
Subject(s)
Monitoring, Physiologic , Respiration , Humans , Phantoms, Imaging , Reproducibility of ResultsABSTRACT
BACKGROUND AND PURPOSE: Post-operative spine stereotactic body radiation therapy (SBRT) represents a significant challenge as there are many restrictions on beam geometry to avoid metal hardware as it surrounds the target volume. In this study, an international multi-institutional end-to-end test using an in-house spine phantom was developed and executed. The aim was to evaluate the impact of titanium spine hardware on planned and delivered dose for post-operative spine SBRT. MATERIALS AND METHODS: Five centers performed simulation, planning and irradiation of the spine phantom, with/without titanium metal hardware (MB/B), following our pre-specified protocol. The doses were calculated using the centers' treatment planning system (TPS) and measured with radiophotoluminescent glass dosimeters (RPLDs) embedded within each phantom. RESULTS: The dose differences between the RPLD measured and calculated doses in the target region were within⯱â¯5% for both phantoms studied. Differences greater than 5% were observed for the spinal cord and the out-of-the target regions due to steeper dose gradient regions that are created in these plans. Dose measurements within⯱â¯3% were observed between RPLDs that were embedded in MB and B inserts. For the spinal cord and the out-of-target regions surrounded by metal hardware, the dose measured using RPLDs was within 3% different near the titanium screws compared to the dose measured near only the metal rods. CONCLUSION: We have successfully performed the first multi-institutional end-to-end dose analysis using an in-house phantom built specifically for post-operative spine SBRT. The differences observed between the measured and planned doses in the presence of metal hardware were clinically insignificant.
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INTRODUCTION: Contouring has become an increasingly important aspect of radiation therapy due to inverse planning, and yet is extremely time-consuming. To improve contouring efficiency and reduce potential inter-observer variation, the atlas-based auto-segmentation (ABAS) function in Velocity was introduced to ICON cancer centres (ICC) throughout Australia as a solution for automatic contouring. METHODS: This paper described the implementation process of the ABAS function and the construction of user-defined atlas sets and compared the contouring efficiency before and after the introduction of ABAS. RESULTS: The results indicate that the main limitation to the ABAS performance was Velocity's sub-optimal atlas selection method. Three user-defined atlas sets were constructed. Results suggested that the introduction of the ABAS saved at least 5 minutes of manual contouring time (P < 0.05), although further verification was required due to limitations in the data collection method. The pilot rollout adopting a 'champion' approach was successful and provided an opportunity to improve the user-defined atlases prior to the national implementation. CONCLUSION: The implementation of user-defined ABAS for head and neck (H&N) and female thorax patients at ICCs was successful, which achieved at least 5 minutes of efficiency gain.
Subject(s)
Radiotherapy Planning, Computer-Assisted/methods , Australia , Data Collection , Female , Head and Neck Neoplasms/radiotherapy , Humans , Male , Thoracic Neoplasms/radiotherapyABSTRACT
BACKGROUND: The automated and integrated machine performance check (MPC) tool was verified against independent detectors to evaluate its beam uniformity and output detection abilities to consider it suitable for daily quality assurance (QA). METHODS: Measurements were carried out on six linear accelerators (each located at six individual sites) using clinically available photon and electron energies for a period up to 12 months (n = 350). Daily constancy checks on beam symmetry and output were compared against independent devices such as the SNC Daily QA 3, PTW Farmer ionization chamber, and SNC field size QA phantom. MPC uniformity detection of beam symmetry adjustments was also assessed. Sensitivity of symmetry and output measurements were assessed using statistical process control (SPC) methods to derive tolerances for daily machine QA and baseline resets to account for drifts in output readings. I-charts were used to evaluate systematic and nonsystematic trends to improve error detection capabilities based on calculated upper and lower control levels (UCL/LCL) derived using standard deviations from the mean dataset. RESULTS: This study investigated the vendor's method of uniformity detection. Calculated mean uniformity variations were within ± 0.5% of Daily QA 3 vertical symmetry measurements. Mean MPC output variations were within ± 1.5% of Daily QA 3 and ±0.5% of Farmer ionization chamber detected variations. SPC calculated UCL values were a measure of change observed in the output detected for both MPC and Daily QA 3. CONCLUSIONS: Machine performance check was verified as a daily quality assurance tool to check machine output and symmetry while assessing against an independent detector on a weekly basis. MPC output detection can be improved by regular SPC-based trend analysis to measure drifts in the inherent device and control systematic and random variations thereby increasing confidence in its capabilities as a QA device. A 3-monthly MPC calibration assessment was recommended based on SPC capability and acceptability calculations.
Subject(s)
Particle Accelerators/instrumentation , Particle Accelerators/standards , Phantoms, Imaging , Quality Assurance, Health Care/standards , Radiotherapy Planning, Computer-Assisted/standards , Statistics as Topic , Calibration , Humans , Photons , Radiometry , Radiotherapy Dosage , Radiotherapy, Intensity-ModulatedABSTRACT
TomoTherapy can provide highly accurate SABR deliveries, but currently it does not have any effective motion management techniques. Shallow breathing has been identified as one possible motion management solution on TomoTherapy, which has been made possible with the BreatheWell audiovisual biofeedback (AVB) device. Since both the shallow breathing technique and the clinical use of the BreatheWell device are novel, their implementation requires comprehensive verification and validation work. As the first stage of the validation, this paper investigates the impact of target motion on a TomoTherapy SABR delivery is assessed on both 3D CT and 4D CT using a 4D respiratory phantom. A dosimetric study on a 4D respiratory phantom was conducted, with the phantom's insert designed to move at four different amplitudes in the superior-inferior direction. SABR plans on 3D and 4D CT scans were created and measured. Critical plan statistics and measurement results were compared. It is found that for TomoTherapy SABR deliveries, by reducing the targets respiratory motion, target coverage, organ-at-risk (OAR) sparing, and delivery accuracy were improved.
Subject(s)
Four-Dimensional Computed Tomography , Neoplasms/diagnostic imaging , Neoplasms/radiotherapy , Radiosurgery , Motion , Organs at Risk , Phantoms, Imaging , Radiotherapy Planning, Computer-AssistedABSTRACT
PURPOSE: CT ventilation imaging (CTVI) is being used to achieve functional avoidance lung cancer radiation therapy in three clinical trials (NCT02528942, NCT02308709, NCT02843568). To address the need for common CTVI validation tools, we have built the Ventilation And Medical Pulmonary Image Registration Evaluation (VAMPIRE) Dataset, and present the results of the first VAMPIRE Challenge to compare relative ventilation distributions between different CTVI algorithms and other established ventilation imaging modalities. METHODS: The VAMPIRE Dataset includes 50 pairs of 4DCT scans and corresponding clinical or experimental ventilation scans, referred to as reference ventilation images (RefVIs). The dataset includes 25 humans imaged with Galligas 4DPET/CT, 21 humans imaged with DTPA-SPECT, and 4 sheep imaged with Xenon-CT. For the VAMPIRE Challenge, 16 subjects were allocated to a training group (with RefVI provided) and 34 subjects were allocated to a validation group (with RefVI blinded). Seven research groups downloaded the Challenge dataset and uploaded CTVIs based on deformable image registration (DIR) between the 4DCT inhale/exhale phases. Participants used DIR methods broadly classified into B-splines, Free-form, Diffeomorphisms, or Biomechanical modeling, with CT ventilation metrics based on the DIR evaluation of volume change, Hounsfield Unit change, or various hybrid approaches. All CTVIs were evaluated against the corresponding RefVI using the voxel-wise Spearman coefficient rS , and Dice similarity coefficients evaluated for low function lung ( DSClow ) and high function lung ( DSChigh ). RESULTS: A total of 37 unique combinations of DIR method and CT ventilation metric were either submitted by participants directly or derived from participant-submitted DIR motion fields using the in-house software, VESPIR. The rS and DSC results reveal a high degree of inter-algorithm and intersubject variability among the validation subjects, with algorithm rankings changing by up to ten positions depending on the choice of evaluation metric. The algorithm with the highest overall cross-modality correlations used a biomechanical model-based DIR with a hybrid ventilation metric, achieving a median (range) of 0.49 (0.27-0.73) for rS , 0.52 (0.36-0.67) for DSClow , and 0.45 (0.28-0.62) for DSChigh . All other algorithms exhibited at least one negative rS value, and/or one DSC value less than 0.5. CONCLUSIONS: The VAMPIRE Challenge results demonstrate that the cross-modality correlation between CTVIs and the RefVIs varies not only with the choice of CTVI algorithm but also with the choice of RefVI modality, imaging subject, and the evaluation metric used to compare relative ventilation distributions. This variability may arise from the fact that each of the different CTVI algorithms and RefVI modalities provides a distinct physiologic measurement. Ultimately this variability, coupled with the lack of a "gold standard," highlights the ongoing importance of further validation studies before CTVI can be widely translated from academic centers to the clinic. It is hoped that the information gleaned from the VAMPIRE Challenge can help inform future validation efforts.
Subject(s)
Algorithms , Four-Dimensional Computed Tomography/methods , Image Processing, Computer-Assisted/methods , Lung Neoplasms/diagnostic imaging , Lung Neoplasms/radiotherapy , Pulmonary Ventilation , Animals , Humans , Radiotherapy Dosage , Radiotherapy, Intensity-Modulated/methods , Respiration , Sheep , Tomography, Emission-Computed, Single-PhotonABSTRACT
Radiotherapy to the breast after surgery sometimes requires adjoining nodes to be included in the treatment volume. In these cases, the traditional approach has been a complex 3-Dimensional Conformal Radiotherapy (3DCRT) beam arrangement which can result in significant dose heterogeneity at the beam junctions. A Volumetric Modulated Arc Therapy (VMAT) beam arrangement has previously been proposed for breast cases, where the chest wall/breast is treated with a limited angle (partial arc) tangential VMAT technique (Virén et al. [2015] Radiat Oncol. 10:79). In our study, this approach is extended to breast and chest wall cases with adjoining nodes by adding a separate conventional VMAT arc field specifically limited to the superior nodes. This VMAT method was implemented using a semiautomated approach on 27 patients, and the resultant plan compared to a monoisocentric 3DCRT plan. Plan statistics, Dose-Volume Histogram (DVH) analysis and Radiation Oncologist (RO) preference were assessed. When compared to the 3DCRT technique, the VMAT planning method was found to result in better target volume coverage, high doses to organs at risk (OAR) were reduced but greater OAR volumes received low doses. Having said that, the volume receiving low doses with this tangential VMAT technique was less than that of other VMAT planning methods described in the literature, and the integral dose was less than the 3DCRT method. The VMAT technique also resulted in more robust junction doses that the 3DCRT method. RO review found that the VMAT technique was preferred in 81% of cases. Specifically, the VMAT plans were preferred in all categories of patients except left chest wall cases where the intermammary nodes were also treated. The VMAT technique described here is a useful addition to the treatment options available for breast/chest wall and nodal patients.
Subject(s)
Thoracic Wall , Breast , Humans , Organs at Risk , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted , Radiotherapy, Conformal , Radiotherapy, Intensity-ModulatedABSTRACT
Dedicated rapid access palliative radiation therapy improves patients' access to care, allowing more timely treatment which would positively impact on quality of life. The TomoTherapy (Accuray, Sunnyvale, CA) system provides megavoltage (MV) fan-beam computed tomography (FBCT) as the image guidance technique, and a module called "statRT" that allows the use of these MV FBCT images for direct planning. The possibility of using this imaging modality for palliative radiotherapy treatment planning is assessed against accepted planning CT standards by performing tests following AAPM TG 66 and an end-to-end measurement. Results have shown that MV FBCT images acquired by TomoTherapy are of sufficient quality for the purpose of target delineation and dose calculation for palliative treatments. Large image noise and extended scan acquisition time are the two main drawbacks, so this imaging modality should only be used for palliative treatments at areas with well-known, easily distinguishable, and relatively immobile targets such as spine and whole brain.
ABSTRACT
In inverse planning of lung radiotherapy, techniques are required to ensure dose coverage of target disease in the presence of tumor motion as a result of respiration. A range of published techniques for mitigating motion effects were compared for dose stability across 5 breath cycles of ±2 cm. Techniques included planning target volume (PTV) expansions, internal target volumes with (OITV) and without tissue override (ITV), average dataset scans (ADS), and mini-max robust optimization. Volumetric arc therapy plans were created on a thorax phantom and verified with chamber and film measurements. Dose stability was compared by DVH analysis in calculations across all geometries. The lung override technique resulted in a substantial lack of dose coverage (-10%) to the tumor in the presence of large motion. PTV, ITV and ADS techniques resulted in substantial (up to 25%) maximum dose increases where solid tissue travelled into low density optimized regions. The results highlight the need for care in optimization of highly heterogeneous where density variations may occur with motion. Robust optimization was shown to provide greater stability in both maximum (<3%) and minimum dose variations (<2%) over all other techniques.