Volumetric Modulated Arc Therapy Delivery Research Articles

Dosimetric impact of VMAT delivery angles for early glottic cancer treatment

This study investigates the dosimetric effects of different gantry rotation angles used in volumetric modulated arc therapy (VMAT) for early glottic carcinoma. VMAT treatment plans using full-arc, half-arc, and partial-arc gantry rotation angles were generated from 22 computed tomography datasets of early-stage (T1-2N0) glottic laryngeal cancer. Dosimetric parameters associated with the planning target volume (PTV) and organs at risk (OARs), specifically the carotid arteries and thyroid, were compared. To assess the robustness of the VMAT plans, dose variations were analyzed by introducing positional shifts of 1, 3, and 5 mm from the isocenter of each plan along the superior-inferior, left-right, and anterior-posterior axes. Furthermore, we examined the size of the PTV, the air cavity volume within the PTV, and the variability of the beam path length through the gantry angles to investigate their correlations with PTV dose variations in the presence of positioning errors. Compared to full-arc and half-arc plans, the dosimetric parameters of partial-arc plans were found to be higher in PTV (D2%, D5%, D50%, and Dmean) and lower in OARs, while their dose variations of OAR parameters were greater for positioning errors. In addition, a correlation was observed between PTV size and PTV dose variations. Air cavity volume and depth variability were also correlated with some PTV parameters, depending on the arc plan. The results presented in this study suggest that the partial-arc gantry angles can allow higher PTV doses while minimizing OAR doses in VMAT treatment planning for early glottic cancer. However, the small delivery angles may lead to greater dose variations in the OARs when positioning errors occur.

Commissioning and dosimetric verification of volumetric modulated arc therapy for multiple modalities using electronic portal imaging device-based 3D dosimetry system: a novel approach.

The purpose of this study was to validate an electronic portal imaging device (EPID) based 3-dimensional (3D) dosimetry system for the commissioning of volumetric modulated arc therapy (VMAT) delivery for flattening filter (FF) and flattening filter free (FFF) modalities based on test suites developed according to American Association of Physicists in Medicine Task Group 119 (AAPM TG 119) and pre-treatment patient specific quality assurance (PSQA).With ionisation chamber, multiple-point measurement in various planes becomes extremely difficult and time-consuming, necessitating repeated exposure of the plan. The average agreement between measured and planned doses for TG plans is recommended to be within 3%, and both the ionisation chamber and PerFRACTION™ measurement were well within this prescribed limit. Both point dose differences with the planned dose and gamma passing rates are comparable with TG reported multi-institution results. From our study, we found that no significant differences were found between FF and FFF beams for measurements using PerFRACTION™ and ion chamber. Overall, PerFRACTION™ produces acceptable results to be used for commissioning and validating VMAT and for performing PSQA. The findings support the feasibility of integrating PerFRACTION™ into routine quality assurance procedures for VMAT delivery. Further multi-institutional studies are recommended to establish global baseline values and enhance the understanding of PerFRACTION™'s capabilities in diverse clinical settings.

Automatic end-to-end VMAT treatment planning for rectal cancers.

The treatment planning process from segmentation to producing a deliverable plan is time-consuming and labor-intensive. Existing solutions automate the segmentation and planning processes individually. The feasibility of combining auto-segmentation and auto-planning for volumetric modulated arc therapy (VMAT) for rectal cancers in an end-to-end process is not clear. To create and clinically evaluate a complete end-to-end process for auto-segmentation and auto-planning of VMAT for rectal cancer requiring only the gross tumor volume contour and a CT scan as inputs. Patient scans and data were retrospectively selected from our institutional records for patients treated for malignant neoplasm of the rectum. We trained, validated, and tested deep learning auto-segmentation models using nnU-Net architecture for clinical target volume (CTV), bowel bag, large bowel, small bowel, total bowel, femurs, bladder, bone marrow, and female and male genitalia. For the CTV, we identified 174 patients with clinically drawn CTVs. We used data for 18 patients for all structures other than the CTV. The structures were contoured under the guidance of and reviewed by a gastrointestinal (GI) radiation oncologist. The predicted results for CTV in 35 patients and organs at risk (OAR) in six patients were scored by the GI radiation oncologist using a five-point Likert scale. For auto-planning, a RapidPlan knowledge-based planning solution was modeled for VMAT delivery with a prescription of 25Gy in five fractions. The model was trained and tested on 20 and 34 patients, respectively. The resulting plans were scored by two GI radiation oncologists using a five-point Likert scale. Finally, the end-to-end pipeline was evaluated on 16 patients, and the resulting plans were scored by two GI radiation oncologists. In 31 of 35 patients, CTV contours were clinically acceptable without necessary modifications. The CTV achieved a Dice similarity coefficient of 0.85 (±0.05) and 95% Hausdorff distance of 15.25 (±5.59)mm. All OAR contours were clinically acceptable without edits, except for large and small bowel which were challenging to differentiate. However, contours for total, large, and small bowel were clinically acceptable. The two physicians accepted 100% and 91% of the auto-plans. For the end-to-end pipeline, the two physicians accepted 88% and 62% of the auto-plans. This study demonstrated that the VMAT treatment planning technique for rectal cancer can be automated to generate clinically acceptable and safe plans with minimal human interventions.

Canine primary liver tumors treated with stereotactic body radiation therapy: A case series.

Stereotactic body radiation therapy (SBRT) is an increasingly used alternative treatment option for nonresectable hepatocellular carcinoma (HCC) in people. Comparatively, the publication of SBRT of dogs with HCC is limited. The objective of this retrospective, descriptive case series was to evaluate the clinical outcomes and toxicity data of SBRT in dogs with HCC and imaging-documented primary liver tumors using volumetric-modulated arc therapy delivery at two private institutions. Medical records of 14 dogs treated between 2018 and 2023 were reviewed. All dogs had macroscopic tumors, and 9 of 14 dogs had HCC diagnoses confirmed on cytology or histopathology. The median longest tumor diameter was 5.5cm. The median percentage of planning target volume relative to liver volume was 27.1%. Most dogs were treated with three daily fractions of 7-7.5Gy. All dogs completed their radiotherapy protocols. Three of nine HCC dogs experienced partial responses and clinical improvement. Five of nine HCC dogs had stable disease. Overall median survival time was 164 days for nine HCC dogs (range: 93-706 days). One late grade 5 liver and two late grade 3 kidney side effects were reported. One dog received repeated SBRT to the same HCC treatment field, and one dog had two courses of SBRT to bifocal HCC treatment fields, both with no more than grade 2 acute and chronic toxicities.

Technical note: Feasibility of gating for dynamic trajectory radiotherapy - Mechanical accuracy and dosimetric performance.

Dynamic trajectory radiotherapy (DTRT) extends state-of-the-art volumetric modulated arc therapy (VMAT) by dynamic table and collimator rotations during beam-on. The effects of intrafraction motion during DTRT delivery are unknown, especially regarding the possible interplay between patient and machine motion with additional dynamic axes. To experimentally assess the technical feasibility and quantify the mechanical and dosimetric accuracy of respiratory gating during DTRT delivery. A DTRT and VMAT plan are created for a clinically motivated lung cancer case and delivered to a dosimetric motion phantom (MP) placed on the table of a TrueBeam system using Developer Mode. The MP reproduces four different 3D motion traces. Gating is triggered using an external marker block, placed on the MP. Mechanical accuracy and delivery time of the VMAT and DTRT deliveries with and without gating are extracted from the logfiles. Dosimetric performance is assessed by means of gamma evaluation (3% global/2 mm, 10% threshold). The DTRT and VMAT plans are successfully delivered with and without gating for all motion traces. Mechanical accuracy is similar for all experiments with deviations<0.14° (gantry angle),<0.15° (table angle),<0.09° (collimator angle) and<0.08 mm (MLC leaf positions). For DTRT (VMAT), delivery times are 1.6-2.3 (1.6- 2.5) times longer with than without gating for all motion traces except one, where DTRT (VMAT) delivery is 5.0 (3.6) times longer due to a substantial uncorrected baseline drift affecting only DTRT delivery. Gamma passing rates with (without) gating for DTRT/VMAT were ≥96.7%/98.5% (≤88.3%/84.8%). For one VMAT arc without gating it was 99.6%. Gating is successfully applied during DTRT delivery on a TrueBeam system for the first time. Mechanical accuracy is similar for VMAT and DTRT deliveries with and without gating. Gating substantially improved dosimetric performance for DTRT and VMAT.

Advancing Precision in Post-mastectomy Chest Wall Radiotherapy: A Comparative Dosimetric Analysis of Volumetric-Modulated Arc Therapy (VMAT) and Intensity-Modulated Radiotherapy (IMRT) Based on Institutional Experience.

Post-mastectomy radiation therapy (PMRT) is an important component in the management of breast cancer patients who have undergone mastectomy. Intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) are two popular methods of delivering PMRT. With IMRT, high radiation doses are directed at the tumor, while exposure to healthy tissue is kept to a minimum. VMAT, on the other hand, is a more advanced version of IMRT that allows for faster radiation dose delivery while maintaining precision. The complexity of the VMAT treatment planning and delivery process, on the other hand, may increase the risk of technical errors, which can reduce treatment effectiveness. Studies have compared VMAT and IMRT in PMRT for breast cancer patients, but most have found no significant differences in treatment outcomes between the two methods. Individual patient factors such as treatment goals, available resources, and other characteristics may influence the choice between the two techniques. This prospective observational study aimed to compare the dosimetry of two cutting-edge modern radiotherapy techniques for post-mastectomy breast cancer patients receiving hypofractionated doses. For 58 patients with breast cancer, 116 plans for radiotherapy treatment were generated by both VMAT and IMRT. To maintain the uniformity of contouring, every CT image was contoured by the same physician, and Radiotherapy Oncology Group (RTOG) contouring guidelines were strictly followed during contouring. Both techniques had comparable target volume coverage, but VMAT produced a significantly better conformity index than IMRT for both the left (0.71 vs. 0.65) and right (0.72 vs. 0.66) breasts (p-value < 0.05). VMAT plans had significantly higher low-dose spillage to the ipsilateral lung (V5Gy and V10Gy) but significantly lower high-dose spillage (V20Gy, V30Gy, and V40Gy) than IMRT plans (p-value < 0.05). Dmax and Dmean for the ipsilateral lung were comparable for both techniques. When compared to alternative treatment approaches, IMRT treatment plans were found to be more effective in minimizing radiation exposure to the heart for all patients with right-sided breast cancer, resulting in considerably lower levels of Dmean, V5Gy, V10Gy, V20Gy, and V35Gy. Plans for VMAT treatment were found to be significantly superior to left-side chest wall radiotherapy in terms of lower exposure to the heart for higher doses. IMRT plans, on the other hand, were successful in dramatically lowering the levels of Dmax that reached the spinal cord for both right- and left-sided breast cancers. Apart from similar planning target volume (PTV) coverage to IMRT plans, VMAT produced significantly better conformity. VMAT plans have more low-dose spillage to normal tissues, while IMRT plans spare various organs at risk significantly better at lower doses in both right and left-sided breast cancer. VMAT was found to be better at sparing the heart (in left-sided breast cancer only) and ipsilateral lung at a high dose range. The best radiotherapy approach for breast cancer should be established on an individual basis, taking into account tumor laterality and the risk-benefit ratio.

139 - Comparison of VMAT (volumetric modulated arc therapy) delivery of high-dose palliative radiotherapy (RT) to lung via Eclipse Planning System (EPS), to conventional palliative radiotherapy delivery via ADW planning system

139 - Comparison of VMAT (volumetric modulated arc therapy) delivery of high-dose palliative radiotherapy (RT) to lung via Eclipse Planning System (EPS), to conventional palliative radiotherapy delivery via ADW planning system

Electronic Portal Imaging Device in Pre-Treatment Patient-Specific Quality Assurance of volumetric-modulated arc therapy delivery

Abstract Background: Radiotherapy treatment delivery is evaluated by a pre-treatment patient-specific quality assurance (PSQA) procedure to ensure the patient receives an accurate radiation dose. The current PSQA practice by using conventional phantoms requires more set-up time and cost of purchasing the tools. Therefore, this study aimed to investigate the efficiency of an electronic portal imaging device (EPID) of linear accelerator (LINAC) as a PSQA tool for volumetric-modulated arc therapy (VMAT) planning technique for nasopharyngeal carcinoma (NPC) treatment delivery. Methods: A NPC VMAT plan on a Rando phantom was performed by following the Radiation Therapy Oncology Group (RTOG) 0615 protocol. The gamma passing rate of the EPID and PSQA phantom (ArcCHECK) were compared among the gamma criteria of 3%/3 mm, 2%/2 mm and 1%/1 mm, respectively. Results: Both EPID and ArcCHECK phantom had distinguishable gamma passing rates in 3%/3 mm and 2%/2 mm with a difference of 0·87% and 0·30%, respectively. Meanwhile, the EPID system had a lower gamma passing rate than the ArcCHECK phantom in 1%/1 mm (21·23% difference). Furthermore, the sensitivity of the EPID system was evaluated and had the largest deviation in gamma passing rate from the reference position in gamma criteria of 2%/2 mm (41·14%) compared to the 3%/3 mm (25·45%) and 1%/1 mm (31·78%), discretely. The best fit line of the linear regression model for EPID was steeper than the ArcCHECK phantom in 3%/3 mm and 2%/2 mm, and vice versa in gamma criteria of 1%/1 mm. This indicates that the EPID had a higher sensitivity than the ArcCHECK phantom in 3%/3 mm and 2%/2 mm but less sensitivity in 1%/1 mm. Conclusions: The EPID system was efficient in performing the PSQA test of VMAT treatment in HUSM with the gamma criteria of 3%/3 mm and 2%/2 mm.

3D Dose-Driven, Automatic VMAT Machine Parameter Generation with Deep Learning

<h3>Purpose/Objective(s)</h3> Recent research efforts utilizing knowledge-based treatment planning for the prediction of 3D radiation dose distributions from planning structure sets have achieved positive results. Most ongoing efforts to generate deliverable plans from the predicted doses rely on full inverse optimizations using dose-volume histogram (DVH) objectives derived from these doses. In this study, we aim to leverage deep learning (DL) to rapidly generate machine delivery parameters for volumetric modulated arc therapy (VMAT) from predicted desired doses. <h3>Materials/Methods</h3> Data of 50 previously treated patients at our institution with prostate adenocarcinoma who received definitive radiotherapy were retrospectively obtained. All plans were generated with a one-arc VMAT technique, with conventional fractionation (78 Gy in 39 fx or 79.2 Gy in 44 fx to the prostate gland +/- seminal vesicles). A multi-task U-Net was constructed: it takes the 2D projections of the 3D dose and planning structures as inputs, and it predicts the numerical multi-leaf collimator (MLC) sequence and weights for the 178 control points. Five cases were randomly selected for testing only, and the remaining 45 formed the training set. The algorithm was implemented in Python 3.8 with PyTorch 1.7 as the DL framework. Model training was performed on a GPU. The DL-predicted plans underwent further inverse optimization with the 3D-dose-derived DVH objectives, utilizing only the last step of the Photon Optimizer (PO) in a treatment planning system. The optimization time and plan quality were compared to plans generated with one full PO optimization with the same objectives and clinical plans (all normalized to D95%=100% Rx dose). <h3>Results</h3> The DL model was trained for 200 epochs. On average, DL-predicted plans could be optimized in 22% (range, 18-26%) of the time required for full optimization plans. Dosimetric comparison (Table 1) demonstrated that the quality of the DL-predicted plans was comparable with clinical plans and full optimization plans, but the DL-predicted plans tended to have increased dose inhomogeneity within the PTVs. <h3>Conclusion</h3> We demonstrated the feasibility of rapidly generating deliverable VMAT plans from desired 3D doses with deep learning. Further work is needed to improve PTV dose homogeneity and generalize the method to multi-arc VMAT delivery.

Efficient dose-volume histogram-based pretreatment patient-specific quality assurance methodology with combined deep learning and machine learning models for volumetric modulated arc radiotherapy.

Weak correlation between gamma passing rates and dose differences in target volumes and organs at risk (OARs) has been reported in several studies. Evaluation on the differences between planned dose-volume histogram (DVH) and reconstructed DVH from measurement was adopted and incorporated into patient-specific quality assurance (PSQA). However, it is difficult to develop a methodology allowing the evaluation of errors on DVHs accurately and quickly. To develop a DVH-based pretreatment PSQA for volumetric modulated arc therapy (VMAT) with combined deep learning (DL) and machine learning models to overcome the limitation of conventional gamma index (GI) and improve the efficiency of DVH-based PSQA. A DL model with a three-dimensional squeeze-and-excitation residual blocks incorporated into a modified U-net was developed to predict the measured PSQA DVHs of 208 head-and-neck (H&N) cancer patients underwent VMAT between 2018 and 2021 from two hospitals, in which 162 cases was randomly selected for training, 18 for validation, and 28 for testing. After evaluating the differences between treatment planning system (TPS) and PSQA DVHs predicted by DL model with multiple metrics, a pass or fail (PoF) classification model was developed using XGBoost algorithm. Evaluation of domain experts on dose errors between TPS and reconstructed PSQA DVHs was taken as ground truth for PoF classification model training. The prediction model was able to achieve a good agreement between predicted, measured, and TPS doses. Quantitative evaluation demonstrated no significant difference between predicted PSQA dose and measured dose for target and OARs, except for Dmean of PTV6900 (p=0.001), D50 of PTV6000 (p=0.014), D2 of PTV5400 (p=0.009), D50 of left parotid (p=0.015), and Dmax of left inner ear (p=0.007). The XGBoost model achieved an area under curves, accuracy, sensitivity, and specificity of 0.89 versus 0.88, 0.89 versus 0.86, 0. 71 versus 0.71, and 0.95 versus 0.91 with measured and predicted PSQA doses, respectively. The agreement between domain experts and the classification model was 86% for 28 test cases. The successful prediction of PSQA doses and classification of PoF for H&N VMAT PSQA indicating that this DVH-based PSQA method is promising to overcome the limitations of GI and to improve the efficiency and accuracy of VMAT delivery.

Is a weekly qualitative picket fence test sufficient? A proposed alternate EPID-based weekly MLC QA program.

PurposeWell‐designed routine multileaf collimator (MLC) quality assurance (QA) is important to assure external‐beam radiation treatment delivery accuracy. This study evaluates the clinical necessity of a comprehensive weekly (C‐Weekly) MLC QA program compared to the American Association of Physics in Medicinerecommended weekly picket fence test (PF‐Weekly), based on our seven‐year experience with weekly MLC QA.MethodsThe C‐Weekly MLC QA program used in this study includes 5 tests to analyze: (1) absolute MLC leaf position; (2) interdigitation MLC leaf position; (3) picket fence MLC leaf positions at static gantry angle; (4) minimum leaf‐gap setting; and (5) volumetric‐modulated arc therapy delivery. A total of 20,226 QA images from 16,855 tests (3,371 tests × 5) for 11 linacs at 5 photon clinical sites from May 2014 to June 2021 were analyzed. Failure mode and effects analysis was performed with 5 failure modes related to the 5 tests. For each failure mode, a risk probability number (RPN) was calculated for a C‐Weekly and a PF‐Weekly MLC QA program. The probability of occurrence was evaluated from statistical analyses of the C‐Weekly MLC QA.ResultsThe total number of failures for these 16,855 tests was 143 (0.9%): 39 (27.3%) for absolute MLC leaf position, 13 (9.1%) for interdigitation position, 9 (6.3%) for static gantry picket fence, 2 (1.4%) for minimum leaf‐gap setting, and 80 (55.9%) for VMAT delivery. RPN scores for PF‐Weekly MLC QA ranged from 60 to 192 and from 48 to 96 for C‐Weekly MLC QA.ConclusionRPNs for the 5 failure modes of MLC QA tests were quantitatively determined and analyzed. A comprehensive weekly MLC QA is imperative to lower the RPNs of the 5 failure modes to the desired level (<125); those from the PF‐Weekly MLC QA program were found to be higher (>125). This supports the clinical necessity for comprehensive weekly MLC QA.

Reduction of systematic dosimetric uncertainties in volumetric modulated arc therapy triggered by patient-specific quality assurance.

Background and purposeDosimetric patient-Specific Quality Assurance (PSQA) data contain in addition to cases with alerts, many cases without alerts. The aim of this study was to present a procedure to investigate long-term trend analysis of the complete set of PSQA data for the presence of site-specific deviations to reduce underlying systematic dose uncertainties.Materials and methodsThe procedure started by analysing a large set of prostate Volumetric Modulated Arc Therapy (VMAT) PSQA data obtained by comparing 3D electronic portal image device (EPID)_based in vivo dosimetry measurements with dose values predicted by the Treatment Planning System (TPS). If systematic deviations were present, several actions were required. These included confirmation of these deviations with an independent dose verification system for which a 2D detector array in a phantom was used, and analysing calculated with measured PSQA data, or delivery machine characteristics. Further analysis revealed that the under-dosage correlated with plan complexity and coincided with changes in clinically applied planning techniques.ResultsProstate VMAT PSQA data showed an under-dosage gradual increasing to about 2% in 3 years, which was confirmed by the measurements with the 2D detector array in a phantom. The implementation of new beam fits in the TPS led to a reduction of the observed deviations.ConclusionLong-term analysis of site-specific PSQA data is a useful method to monitor incremental changes in a radiotherapy department due to various changes in the treatment planning and delivery of prostate VMAT, and may lead to a reduction of systematic dose uncertainties in complex treatments.

Positron emission tomography guided dose painting by numbers of lung cancer: Alanine dosimetry in an anthropomorphic phantom.

Dose painting by numbers (DPBN) require a high degree of dose modulation to fulfill the image-based voxel wise dose prescription. The aim of this study was to assess the dosimetric accuracy of 18F-fluoro-2-deoxy-glucose positron emission tomography(18F-FDG-PET)-based DPBN in an anthropomorphic lung phantom using alanine dosimetry. A linear dose prescription based on 18F-FDG-PET image intensities within the gross tumor volume (GTV) of a lung cancer patient was employed. One DPBN scheme with low dose modulation (Scheme A; minimum/maximum fraction dose to the GTV 2.92/4.26Gy) and one with a high modulation (Scheme B; 2.81/4.52Gy) were generated. The plans were transferred to a computed tomograpy (CT) scan of a thorax phantom based on CT images of the patient. Using volumetric modulated arc therapy (VMAT), DPBN was delivered to the phantom with embedded alanine dosimeters. A plan was also delivered to an intentionally misaligned phantom. Absorbed doses at various points in the phantom were measured by alanine dosimetry. A pointwise comparison between GTV doses from prescription, treatment plan calculation and VMAT delivery showed high correspondence, with a mean and maximum dose difference of <0.1Gy and 0.3Gy, respectively. No difference was found in dosimetric accuracy between scheme A and B. The misalignment caused deviations up to 1Gy between prescription and delivery. DPBN can be delivered with high accuracy, showing that the treatment may be applied correctly from a dosimetric perspective. Still, misalignment may cause considerable dosimetric erros, indicating the need for patient immobilization and monitoring.

Optimized Conformal Total Body Irradiation Among Recipients of TCRαβ/CD19-Depleted Grafts in Pediatric Patients With Hematologic Malignancies: Single-Center Experience

Total body irradiation (TBI) in combination with chemotherapy is widely used as a conditioning regimen in pediatric and adult hematopoietic stem cell transplantation (HSCT). The combination of TBI with chemotherapy has demonstrated superior survival outcomes in patients with acute lymphoblastic and myeloid leukemia when compared with conditioning regimens based only on chemotherapy. The clinical application of intensity-modulated radiation therapy (IMRT)-based methods (volumetric modulated arc therapy (VMAT) and TomoTherapy) seems to be promising and has been actively used worldwide. The optimized conformal total body irradiation (OC-TBI) method described in this study provides selected dose reduction for organs at risk with respect to the most significant toxicity (lungs, kidneys, lenses). This study included 220 pediatric patients who received OC-TBI with subsequent chemotherapy and allogenic HSCT with TCRαβ/CD19 depletion. A group of 151 patients received OC-TBI using TomoTherapy, and 40 patients received OC-TBI using the Elekta Synergy™ linac with an Agility-MLC (Elekta, Crawley, UK) using volumetric modulated arc therapy (VMAT). Twenty-nine patients received OC-TBI with supplemental simultaneous boost to bone marrow—(SIB to BM) up to 15 Gy: 28 patients (pts)—TomoTherapy; one patient—VMAT. The follow-up duration ranged from 0.3 to 6.4 years (median follow-up, 2.8 years). Overall survival (OS) for all the patients was 63% (95% CI: 56–70), and event-free survival (EFS) was 58% (95% CI: 51–65). The cumulative incidence of transplant-related mortality (TRM) was 10.7% (95% CI: 2.2–16) for all patients. The incidence of early TRM (<100 days) was 5.0% (95% CI: 1.5–8.9), and that of late TRM (>100 days) was 5.7 (95% CI: 1.7–10.2). The main causes of death for all the patients were relapse and infection. The concept of OC-TBI using IMRT VMAT and helical treatment delivery on a TomoTherapy treatment unit provides maximum control of the dose distribution in extended targets with simultaneous dose reduction for organs at risk. This method demonstrated a low incidence of severe side effects after radiation therapy and predictable treatment effectiveness. Our initial experience demonstrates that OC-TBI appears to be a promising technique for the treatment of pediatric patients.

Siamese-Based Deep Learning for Markerless Lung Tumor Tracking During Stereotactic Radiotherapy

<h3>Purpose/Objective(s)</h3> During stereotactic lung radiotherapy we want to monitor the target position to ensure it remains inside the planning target volume (PTV). This ensures accurate treatment delivery and may allow for margin reduction. Many LINAC systems have a kilo-voltage (kV) imaging system mounted orthogonally to the MV beam. This can acquire images during volumetric modulated arc therapy delivery. The 2D-kV images can be used to identify the tumor position, e.g., using template matching and triangulation (TMT). However, small lung targets are difficult to track, due to e.g., low tumor contrast, occlusion (e.g., by spine), or noisy images. We investigated deep learning (DL) as an alternative method for lung tumor tracking. <h3>Materials/Methods</h3> Clinical data from 6 patients (P1-P6) with small lung tumors (0.5-3 cm diameter) and a 3D-printed anthropomorphic phantom (P0), including a low-density lung tumor, was used. For each patient, data included 4D-CT scans, fluoroscopic kV images and breathing-related surface motion (Real-Time Position Management, RPM). For the phantom, a 3D-CT scan and kV images taken with a static and moving couch (regular and irregular motion) were available. Due to lack of ground truth tumor locations for the kV images, a patient-specific DL model is trained on Digitally Reconstructed Radiographs (DRRs), generated from the planning CT scans. To enhance the tumor's visual diversity in DRRs, we augmented the training data with locally deformed CT scans. A Siamese-based tracking by similarity method is hypothesized to be better suited for the tumor tracking task than other DL methods, due to its more localized search space and the use of previous frames (temporal information). <h3>Results</h3> Table 1 shows the superior-inferior (SI) direction results obtained by the Siamese model and TMT, on all kV images. For the patient data, the <b>Correlation coefficient</b> between estimated tumor trajectory and RPM was computed, due to lack of ground truth locations. For the phantom, the <b>Mean Absolute Distance</b> (MAD) between detected and ground truth center coordinates was computed. For all 6 patients and the phantom, the Siamese model outperformed TMT. <h3>Conclusion</h3> A novel approach for real-time markerless lung tumor tracking is presented, based on deep Siamese networks. The model compares favorably to the template matching/triangulation-based technique and merits further investigation. The current analysis presents only SI tracking. Reliable 3D tracking, with sub-mm accuracy, is the ultimate goal. Further work is needed to achieve this.

Dosimetric justification for the use of volumetric modulated arc therapy in head and neck cancer-A systematic review of the literature.

IntroductionRadiotherapy for head and neck cancer (HNC) has evolved rapidly in the past decades from conformal three‐dimensional technique (3D‐CRT) to intensity‐modulated radiotherapy (IMRT) and volumetric‐modulated arc therapy (VMAT). This paper presents a dosimetric comparative study between VMAT and IMRT delivery based on current literature, while also presenting the potential challenges encountered with volumetric arc therapy.MethodsA systematic search of the scientific literature was conducted within Medline/Pubmed databases. A number of 13 papers fulfilled the search criteria which was based on the main objective to evaluate dosimetric characteristics of comparative treatment delivery with VMAT vs IMRT in HNC.ResultsOverall, from a dosimetric perspective, dose delivery via VMAT and IMRT present comparable results. Beside the delivery technique, target volume coverage also depends on the planner's expertise as well as the employed planning algorithm. At times, the superiority of VMAT emerges from the improved sparing of normal tissue, reduction of monitor units (MU) and of treatment delivery time. Similar to IMRT, one of the most important challenges of VMAT is the risk of developing secondary cancer due to the higher number of MUs compared to 3D‐CRT.ConclusionsBased on the comparative results with the more established IMRT, VMAT in HNC can be safely delivered either as a single treatment or combined with other techniques.

IMRT QA and gamma comparisons: The impact of detector geometry, spatial sampling, and delivery technique on gamma comparison sensitivity.

To separately quantify sensitivity differences in patient-specific quality assurance comparisons analyzed with the gamma comparison for different measurement geometries, spatial samplings, and delivery techniques [intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT)]. Error-free calculations for 20 IMRT and 20 VMAT cases were compared to calculations with known induced errors of varying magnitudes, using gamma comparisons. Five error types (MU scaling, three different MLC errors, and collimator errors) were induced in plan calculations on three different detector geometries - ArcCHECK, MapCHECK, and Delta 4. To study detector geometry sensitivity effects alone, gamma comparisons were made with 1mm error-free calculations compared to 1mm error-induced calculations for each device. Effects of spatial sampling were studied by making the same gamma comparisons, but down-sampling the error-induced calculations to the real spatial sampling of each device. Additionally, 1mm vs 1mm comparisons between the IMRT and VMAT cases were compared to investigate sensitivity differences between IMRT and VMAT using IMRT and VMAT cohorts with similar ranges of plan complexity and average aperture size. For each case, induced error type, and device, five different gamma criteria were studied to ensure sensitivity differences between devices, spatial sampling scenarios, and delivery technique were not gamma criterion specific, resulting in over 36,000 gamma comparisons. For IMRT cases, Delta4 and MapCHECK devices had similar error sensitivities for lagging leaf, bank shift, and MU errors, while the ArcCHECK had considerably lower sensitivity than the planar-type devices. For collimator errors and perturbational leaf errors the ArcCHECK had higher error sensitivity than planar-type devices. This behavior was independent of gamma parameters (percent dose difference, distance-to-agreement, and low dose threshold), though use of local normalization resulted in error sensitivites that were markedly similar between all three devices. Differences between detector geometries were less pronounced for VMAT deliveries. Error sensitivity for a given gamma criterion when comparing IMRT and VMAT deliveries on the same devices showed that VMAT plans were more sensitive to some specific error types and less sensitive to others, when compared to IMRT plans. For the ArcCHECK device, the sensitivity of IMRT and VMAT cases was quite similar, whereas this was not the case for the planar-type devices. When comparing error sensitivity between 1mm vs 1mm calculations and 1mm vs the real spatial sampling for each device, results showed that increased spatial sampling did not systematically increase error sensitivity. Noticeable differences in error sensitivity were observed for different detector geometries, but differences were dependent on induced error type, and a particular device geometry did not offer universal improvements in error sensitivity across studied error types. This study demonstrates that the sensitivity of the gamma comparison does not largely hinge on detector spatial sampling. VMAT deliveries were generally less sensitive to errors when compared to IMRT plans for the planar-type devices, while similar sensitivities were observed between delivery techniques for the ArcCHECK device. Results of this work suggest that a universal gamma criterion is inappropriate for IMRT QA and that the percent pixels passing is an insufficient metric for evaluating quality assurance checks in the clinic.

Solution of Lagrange's equation of motion form the first principle for volumetric modulated arc therapy delivery

To calculate the Lagrange’s equation of motion from first principle for volumetric modulated arc therapy delivery. The delivery of volumetric modulated arc therapy (VMAT) is based on a rotational co-ordinate system. This delivery technique differs from any other delivery technique with static beams. VMAT delivery is a complex many-body problem, to represent the VMAT uniquely, it is necessary to find the equation of motion in a non-inertial (rotating) fame. In the non-inertial frame of reference, Newton's equations of motion do not hold, hence Lagrange's equation of motion (Lagrange's equation of motion of second kind) needs to be solved. If A is the aperture created by Multileaf collimator (MLC), MU is delivered Monitor Unit of radiation dose and θ is the gantry angle, then equation of motion for volumetric arc therapy delivery is represented by following three equations 1. $$\frac{d\theta }{dt}=\dot{\theta }=$$ constant between two control points, 2. $$m\ddot{x}-m x \dot{\theta }2= Fx$$ ; where Fx is the external force along $$\overrightarrow{x}$$ direction, causing the MLC movement along the x-direction only and m is the mass of the MLC, and $${MU}_{delivered}\left(t\right)={\int }_{t=0}^{t=t}MU{(t)}_{planned}dt$$ . This piece of derivation presents the calculation of the equation of motion for VMAT delivery in terms of MLC movement, gantry angle, and delivered dose by deriving Lagrangian formulation from the first principle.

Beam complexity and monitor unit efficiency comparison in two different volumetric modulated arc therapy delivery systems using automated planning

BackgroundTo investigate the beam complexity and monitor unit (MU) efficiency issues for two different volumetric modulated arc therapy (VMAT) delivery technologies for patients with left-sided breast cancer (BC) and nasopharyngeal carcinoma (NPC).MethodsTwelve left-sided BC and seven NPC cases were enrolled in this study. Each delivered treatment plan was optimized in the Pinnacle3 treatment planning system with the Auto-Planning module for the Trilogy and Synergy systems. Similar planning dose objectives and beam configurations were used for each site in the two different delivery systems to produce clinically acceptable plans. The beam complexity was evaluated in terms of the segment area (SA), segment width (SW), leaf sequence variability (LSV), aperture area variability (AAV), and modulation complexity score (MCS) based on the multileaf collimator sequence and MU. Plan delivery and a gamma evaluation were performed using a helical diode array.ResultsWith similar plan quality, the average SAs for the Trilogy plans were smaller than those for the Synergy plans: 55.5 ± 21.3 cm2 vs. 66.3 ± 17.9 cm2 (p < 0.05) for the NPC cases and 100.7 ± 49.2 cm2 vs. 108.5 ± 42.7 cm2 (p < 0.05) for the BC cases, respectively. The SW was statistically significant for the two delivery systems (NPC: 6.87 ± 1.95 cm vs. 6.72 ± 2.71 cm, p < 0.05; BC: 8.84 ± 2.56 cm vs. 8.09 ± 2.63 cm, p < 0.05). The LSV was significantly smaller for Trilogy (NPC: 0.84 ± 0.033 vs. 0.86 ± 0.033, p < 0.05; BC: 0.89 ± 0.026 vs. 0.90 ± 0.26, p < 0.05). The mean AAV was significantly larger for Trilogy than for Synergy (NPC: 0.18 ± 0.064 vs. 0.14 ± 0.037, p < 0.05; BC: 0.46 ± 0.15 vs. 0.33 ± 0.13, p < 0.05). The MCS values for Trilogy were higher than those for Synergy: 0.14 ± 0.016 vs. 0.12 ± 0.017 (p < 0.05) for the NPC cases and 0.42 ± 0.106 vs. 0.30 ± 0.087 (p < 0.05) for the BC cases. Compared with the Synergy plans, the average MUs for the Trilogy plans were larger: 828.6 ± 74.1 MU and 782.9 ± 85.2 MU (p > 0.05) for the NPC cases and 444.8 ± 61.3 MU and 393.8 ± 75.3 MU (p > 0.05) for the BC cases. The gamma index agreement scores were never below 91% using 3 mm/3% (global) distance to agreement and dose difference criteria and a 10% lower dose exclusion threshold.ConclusionsThe Pinnacle3 Auto-Planning system can optimize BC and NPC plans to achieve the same plan quality using both the Trilogy and Synergy systems. We found that these two systems resulted in different SAs, SWs, LSVs, AAVs and MCSs. As a result, we suggested that the beam complexity should be considered in the development of further methodologies while optimizing VMAT autoplanning.

Determination of Multileaf Collimator Positional Errors as a Function of Dose Rate, Speed, and Delivery Interruption for Volumetric-Modulated Arc Therapy Delivery.

Aim:To determine the multileaf collimator positional error (MLC-PE) during volumetric modulated arc therapy (VMAT) delivery by studying the time-dependent MLC velocity in mathematically derivable trajectories such as straight line and conic sections.Materials and Methods:VMAT delivery is planned in a way that MLCs are moving in a locus which can be defined by mathematical functions such as linear, parabolic, or circular velocity (PV or CV). The VMAT delivery was interrupted either once or multiple times during the delivery and projection images of the same were acquired in electronic portal imaging device. MLC-PE was then analyzed as a function of dose rate (DR), and MLC speed (SP) and number of interruptions in treatment delivery. In VMAT delivery with linear MLC motion, the delivery was interrupted either once (linear motion single interruption) or multiple (three) times (linear motion multiple interruptions). For PV and CV MLC velocity, the MLC motions are interrupted multiple times.Results:The maximum individual error obtained (DR of 35 MU/min, SP of 2.0 cm/s) was 1.96 ± 0.1 mm. Only 4.4% of MLCs showed ≥ ±1 mm positional error. When the treatment delivery is interrupted multiple times in VMAT delivery, the influence of interruption in MLC-PE overwhelmed the influence by DR and SP. For a sub-group analysis of independent and dependent variables, the mean MLC-PE was 0.18 ± 0.4 mm 0.19 ± 0.42 mm, respectively.Conclusion:Determination of MLC-PEs using a mathematical function without approximation indicates that MLC-PE is not a function of MLC speed. In less than 5% of the studied scenarios, the MLC-PE exceeds its tolerance value (±1 mm). The MLC-PE is significantly less in modern machines due to advancements in the delivery mechanism.