Comparison Of Dose Distributions Research Articles

An automation of Monte Carlo workflow for dosimetry study of an Elekta LINAC delivery system in radiotherapy

PurposeThis study aims to automate the Monte Carlo (MC) workflow utilized for radiotherapy dosimetry, focusing on an Elekta LINAC delivery system. It addresses the challenge of integrating MC simulations into routine clinical practice, making this accurate yet complex method more accessible and efficient for radiotherapy dosimetry. Methods and MaterialsWe developed a user-friendly software featuring a graphical user interface (GUI) that integrates EGSnrc for MC simulations. The software streamlines the process from retrieving Digital Imaging and Communications in Medicine (DICOM) data to executing dose calculations and comparing dose distributions. To validate our proposed tool, we compared its computed doses for IMRT and VMAT plans from the Pinnacle TPS for an Elekta Versa HD linear accelerator against MC simulation results. This comparison utilized our in-house software and GUI as the tool, covering various treatment sites and prescriptions. ResultsThe automated MC workflow demonstrated high accuracy in dose calculations and streamlined integration with clinical workflows. The comparison between the MC-simulated and TPS-calculated doses revealed excellent agreement, highlighting the reliability of MC for independent dose verification in complex treatment scenarios. ConclusionsThe automated MC workflow developed represents a substantial improvement in the practicality and efficiency of MC simulations in radiotherapy. This advancement not only simplifies the dosimetry process but also ensures high accuracy, establishing it as a valuable tool for routine patient-specific quality assurance and the development of specialized treatment procedures.

A comprehensive Study of the Out of Field Non Target Dose Associated with 6 and 10 MV Flattened and Flattening Filter Free X Ray Beam in a True Beam Linear Accelerator.

To evaluate the out-of-field dose associated with flattened (FF) and flattening filter-free (FFF) 6 and 10 MV X-ray beams in a TrueBeam linear accelerator (Linac). Measurements were taken in a slab phantom using the metal oxide semiconductor field effect transistor (MOSFET) detector at varying depths (dmax, 5 cm, and 10 cm) for clinically relevant field sizes and up to 30 cm from the field edges for 6 and 10 MV FF and FFF beams in TrueBeam Linac. Dose calculation accuracy of the analytic anisotropic algorithm (AAA) and Acuros algorithm was investigated in the out-of-field region. Similarly, the out-of-field dose associated with volumetric modulated arc therapy (VMAT) head-and-neck plan delivered to a body phantom was evaluated. The out-of-field dose for both FF and FFF photon beams (6 and 10 MV) decreased with increasing distance from the field boundary and size. Furthermore, regardless of FF in the field, higher-energy photon beams were associated with lower out-of-field dose. Both algorithms underestimated the dose in the out-of-field region, with AAA failing to calculate the out-of-field dose at 15 cm from the field edge and Acuros failing to calculate out-of-field radiation at 20 cm. At 5 cm from the field edge, an average of 50% underestimation was observed, and at 10 cm, an average of 60% underestimation was observed for both FF and FFF (6 and 10 MV) beams. The VMAT head-and-neck plan performed with the FFF beam resulted in a lower out-of-field dose than the FF beam for a comparable dose distribution. Compared with flattened beams, the FFF modes on TrueBeam Linac exhibited a clinically relevant reduction in the out-of-field dose. Further dosimetric studies are warranted to determine the significant benefit of FFF beams across different cancer sites.

GATE Monte Carlo approach to heterogeneity dose distribution in small fields used in radiation therapy

The Accurate dosage prediction in Radiation Therapy is challenging, prompting a need for precision beyond conventional clinical Treatment Planning Systems (TPS). Monte Carlo-based methods are sought for their superior accuracy. The aim of this study is to compare dose distributions between the ACUROS algorithm and the GATE platform in various tissue densities and field sizes, focusing on smaller fields. This study was initiated with a homogeneous validation of the TrueBeam STX system, using measurements obtained from the Centre Hospitalier Interregional Edith Cavell (CHIREC) in Brussels. The validation compared dosimetric functions (Percentage Depth Dose (PDD), Dose profile (DP) and Collimator scatter fraction (CSF)) employing the GAMMA index with a 2% / 2 mm criterion tolerance. Following this, heterogeneous studies examined dose distributions between the ACUROS algorithm and the GATE platform in various tissue densities and field sizes, with a specific focus on smaller fields. Simulations were conducted using both platforms on chest phantoms with heterogeneous slabs representing bone, lung, and heart, each housing a central tumor. The impact of electronic equilibrium on tumors for different small field sizes was evaluated. Results showed a remarkable 99% agreement between measurements and GATE calculations in the homogeneous validation of the TrueBeam STX system. However, in heterogeneous studies, ACUROS consistently overestimated lung doses by up to 8% compared to GATE simulation, especially evident with a flattening filter and smaller beam sizes at density interfaces. This highlights significant dose estimation discrepancies between ACUROS and GATE, emphasizing the need for precise calculations. The findings support exploring Monte Carlo-based methods for enhanced accuracy in Radiation Therapy treatment planning.

Optimizing linear energy transfer distribution in intensity-modulated proton therapy using the alternating direction method of multipliers.

This study develop a novel linear energy transfer (LET) optimization method for intensity-modulated proton therapy (IMPT) with minimum monitor unit (MMU) constraint using the alternating direction method of multipliers (ADMM). The novel LET optimization method (ADMM-LET) was proposed with (1) the dose objective and the LET objective as the optimization objective and (2) the non-convex MMU threshold as a constraint condition. ADMM was used to solve the optimization problem. In the ADMM-LET framework, the optimization process entails iteratively solving the dose sub-problem and the LET sub-problem, simultaneously ensuring compliance with the MMU constraint. Three representative cases, including brain, liver, and prostate cancer, were utilized to evaluate the performance of the proposed method. The dose and LET distributions from ADMM-LET were compared to those obtained using the published iterative convex relaxation (ICR-LET) method. The results demonstrate the superiority of ADMM-LET over ICR-LET in terms of LET distribution while achieving a comparable dose distribution. More specifically, for the brain case, the maximum LET (unit: keV/µm) at the optic nerve decreased from 5.45 (ICR-LET) to 1.97 (ADMM-LET). For the liver case, the mean LET (unit: keV/µm) at the clinical target volume increased from 4.98 (ICR-LET) to 5.50 (ADMM-LET). For the prostate case, the mean LET (unit: keV/µm) at the rectum decreased from 2.65 (ICR-LET) to 2.14 (ADMM-LET). This study establishes ADMM-LET as a new approach for LET optimization with the MMU constraint in IMPT, offering potential improvements in treatment outcomes and biological effects.

Generation and evaluation of anatomy-preserving virtual CT for online adaptive proton therapy.

Daily CTs generated by CBCT correction are required for daily replanning in online-adaptive proton therapy (APT) to effectively deal with inter-fractional changes. Out of the currently available methods, the suitability of a daily CT generation method for proton dose calculation also depends on the anatomical site. We propose an anatomy-preserving virtual CT (APvCT) method as a hybrid method of CBCT correction, which is especially suitable for large anatomy deformations. The accuracy of the hybrid method was assessed by comparison with the corrected CBCT (cCBCT) and virtual CT (vCT) methods in the context of online APT. Seventy-one daily CBCTs of four prostate cancer patients treated with intensity modulated proton therapy (IMPT) were converted to daily CTs using cCBCT, vCT, and the newly proposed APvCT method. In APvCT, planning CT (pCT) were mapped to CBCT geometry using deformable image registration with boundary conditions on controlling regions of interest (ROIs) created with deep learning segmentation on cCBCT. The relative frequency distribution (RFD) of HU, mass density and stopping power ratio (SPR) values were assessed and compared with the pCT. The ROIs in the APvCT and vCT were compared with cCBCT in terms of Dice similarity coefficient (DSC) and mean distance-to-agreement (mDTA). For each patient, a robustly optimized IMPT plan was created on the pCT and subsequent daily adaptive plans on daily CTs. For dose distribution comparison on the same anatomy, the daily adaptive plans on cCBCT and vCT were recalculated on the corresponding APvCT. The dose distributions were compared in terms of isodose volumes and 3D global gamma-index passing rate (GPR) at γ(2%, 2mm) criterion. For all patients, no noticeable difference in RFDs was observed amongst APvCT, vCT, and pCT except in cCBCT, which showed a noticeable difference. The minimum DSC value was 0.96 and 0.39 for contours in APvCT and vCT respectively. The average value of mDTA for APvCT was 0.01cm for clinical target volume and ≤0.01cm for organs at risk, which increased to 0.18cm and ≤0.52cm for vCT. The mean GPR value was 90.9%, 64.5%, and 67.0% for APvCT versus cCBCT, vCT versus cCBCT, and APvCT versus vCT, respectively. When recalculated on APvCT, the adaptive cCBCT and vCT plans resulted in mean GPRs of 89.5±5.1% and 65.9±19.1%, respectively. The mean DSC values for 80.0%, 90.0%, 95.0%, 98.0%, and 100.0% isodose volumes were 0.97, 0.97, 0.97, 0.95, and 0.91 for recalculated cCBCT plans, and 0.89, 0.88, 0.87, 0.85, and 0.81 for recalculated vCT plans. Hausdorff distance for the 100.0% isodose volume in some cases of recalculated cCBCT plans on APvCT exceeded 1.00cm. APvCT contours showed good agreement with reference contours of cCBCT which indicates anatomy preservation in APvCT. A vCT with erroneous anatomy can result in an incorrect adaptive plan. Further, slightly lower values of GPR between the APvCT and cCBCT-based adaptive plans can be explained by the difference in the cCBCT's SPR RFD from the pCT.

Technical note: A small animal irradiation platform for investigating the dependence of the FLASH effect on electron beam parameters.

The recent rediscovery of the FLASH effect, a normal tissue sparing phenomenon observed in ultra-high dose rate (UHDR) irradiations, has instigated a surge of research endeavors aiming to close the gap between experimental observation and clinical treatment. However, the dependences of the FLASH effect and its underpinning mechanisms on beam parameters are not well known, and large-scale in vivo studies using murine models of human cancer are needed for these investigations. To commission a high-throughput, variable dose rate platform providing uniform electron fields(≥15cm diameter) at conventional (CONV) and UHDRs for in vivo investigations of the FLASH effect and its dependences on pulsed electron beam parameters. A murine whole-thoracic lung irradiation (WTLI) platform was constructed using a 1.3cm thick Cerrobend collimator forming a 15 × 1.6 cm2 slit. Control of dose and dose rate were realized by adjusting the number of monitor units and couch vertical position, respectively. Achievable doses and dose rates were investigated using Gafchromic EBT-XD film at 1cm depth in solid water and lung-density phantoms. Percent depth dose (PDD) and dose profiles at CONV and various UHDRs were also measured at depths from 0 to 2cm. A radiation survey was performed to assess radioactivation of the Cerrobend collimator by the UHDR electron beam in comparison to a precision-machined copper alternative. This platform allows for the simultaneous thoracic irradiation of at least three mice. A linear relationship between dose and number of monitor units at a given UHDR was established to guide the selection of dose, and an inverse-square relationship between dose rate and source distance was established to guide the selection of dose rate between 20 and 120Gy·s-1 . At depths of 0.5 to 1.5cm, the depth range relevant to murine lung irradiation, measured PDDs varied within±1.5%. Similar lateral dose profiles were observed at CONV and UHDRs with the dose penumbrae widening from 0.3mm at 0cm depth to 5.1mm at 2.0cm. The presence of lung-density plastic slabs had minimal effect on dose distributions as compared to measurements made with only solid water slabs. Instantaneous dose rate measurements of the activated copper collimator were up to two orders of magnitude higher than that of the Cerrobend collimator. A high-throughput, variable dose rate platform has been developed and commissioned for murine WTLI electron FLASH radiotherapy. The wide field of our UHDR-enabled linac allows for the simultaneous WTLI of at least three mice, and for the average dose rate to be modified by changing the source distance, without affecting dose distribution. The platform exhibits uniform, and comparable dose distributions at CONV and UHDRs up to 120Gy·s-1 , owing to matched and flattened 16 MeV CONV and UHDR electron beams. Considering radioactivation and exposure to staff, Cerrobend collimators are recommended above copper alternatives for electron FLASH research. This platform enables high-throughput animal irradiation, which is preferred for experiments using a large number of animals, which are required to effectively determine UHDR treatment efficacies.

Dosimetric and radiobiological comparison of IMRT, VMAT, and helical tomotherapy planning techniques in hippocampal sparing whole brain radiotherapy with simultaneous integrated boost for multiple brain metastases.

To compare treatment planning and dosimetric outcomes for hippocampal sparing whole brain radiotherapy (WBRT) with the simultaneous integrated boost (SIB) in brain metastasis (BM) patients using tumour control probability (TCP) and normal tissue complication probability (NTCP) formalism between IMRT, VMAT, and HT techniques. In this retrospective study, the treatment data of 20 BM patients who typically received whole brain radiation with SIB treatment were used. Prescription doses of 30Gy and 36Gy was delivered in 10 fractions for WBRT and SIB, respectively. Niemierko and LKB models were applied for calculating TCP and NTCP. All the plans were evaluated for the RTOG 0933 protocol criteria and found acceptable. Additionally, the homogeneity of the PTV boost is 0.07 ± 0.01, 0.1 ± 0.04, and 0.08 ± 0.02 for IMRT, VMAT, and HT, respectively (P < 0.05). The percentage of TCP for the PTV boost was 99.99 ± 0.003, 99.98 ± 0.004, and 99.99 ± 0.002 of IMRT, VMAT, and HT, respectively, (P < 0.005). The NTCP value of the lenses was higher with the VMAT plan as compared to IMRT and HT Plans. The hippocampal NTCP values are equal in all three planning proficiencies. The techniques like IMRT, VMAT, and HT can reduce the dose received by hippocampus to the dosimetric threshold during the delivery of WBRT with hippocampal sparing and can simultaneously boost multiple metastases. Overall, the high-quality dose distribution, TCP, and NTCP comparison between all three planning techniques show that the HT technique has better results when compared to the VMAT and IMRT techniques.

Clinical Use of a Commercial Artificial Intelligence-Based Software for Autocontouring in Radiation Therapy: Geometric Performance and Dosimetric Impact.

When autocontouring based on artificial intelligence (AI) is used in the radiotherapy (RT) workflow, the contours are reviewed and eventually adjusted by a radiation oncologist before an RT treatment plan is generated, with the purpose of improving dosimetry and reducing both interobserver variability and time for contouring. The purpose of this study was to evaluate the results of application of a commercial AI-based autocontouring for RT, assessing both geometric accuracies and the influence on optimized dose from automatically generated contours after review by human operator. A commercial autocontouring system was applied to a retrospective database of 40 patients, of which 20 were treated with radiotherapy for prostate cancer (PCa) and 20 for head and neck cancer (HNC). Contours resulting from AI were compared against AI contours reviewed by human operator and human-only contours using Dice similarity coefficient (DSC), Hausdorff distance (HD), and relative volume difference (RVD). Dosimetric indices such as Dmean, D0.03cc, and normalized plan quality metrics were used to compare dose distributions from RT plans generated from structure sets contoured by humans assisted by AI against plans from manual contours. The reduction in contouring time obtained by using automated tools was also assessed. A Wilcoxon rank sum test was computed to assess the significance of differences. Interobserver variability of the comparison of manual vs. AI-assisted contours was also assessed among two radiation oncologists for PCa. For PCa, AI-assisted segmentation showed good agreement with expert radiation oncologist structures with average DSC among patients ≥ 0.7 for all structures, and minimal radiation oncology adjustment of structures (DSC of adjusted versus AI structures ≥ 0.91). For HNC, results of comparison between manual and AI contouring varied considerably e.g., 0.77 for oral cavity and 0.11-0.13 for brachial plexus, but again, adjustment was generally minimal (DSC of adjusted against AI contours 0.97 for oral cavity, 0.92-0.93 for brachial plexus). The difference in dose for the target and organs at risk were not statistically significant between human and AI-assisted, with the only exceptions of D0.03cc to the anal canal and Dmean to the brachial plexus. The observed average differences in plan quality for PCa and HNC cases were 8% and 6.7%, respectively. The dose parameter changes due to interobserver variability in PCa were small, with the exception of the anal canal, where large dose variations were observed. The reduction in time required for contouring was 72% for PCa and 84% for HNC. When an autocontouring system is used in combination with human review, the time of the RT workflow is significantly reduced without affecting dose distribution and plan quality.

Patient specific quality assurance of volumetric modulated arc therapy of synchronous bilateral breast cancer

Synchronous bilateral breast cancers (SBBC) present a considerable issue in external beam radiotherapy because of large fields size and large target volumes. Mono-isocentric volumetric modulated arc therapy (VMAT) appears as an appropriate irradiation technique for these types of tumors. The aim of this study was to demonstrate the utility of a 3D DVH pretreatment quality assurance program in VMAT of SBBC cases. Twenty SBBC patients who underwent radiation therapy in our department were retrospectively enrolled in this study. Fifteen patients were treated exclusively to the mammary glands. Five patients benefited from a dose boost on the tumor bed (60Gy). Nine patients were irradiated on the supraclavicular nodes (50Gy). This dose was delivered in 25 fractions and integrated boost was used when appropriate. Depending on the complexity of the treatment plans; 2 or 4 arcs VMAT plans were used in a mono-isocentric technique. The patient specific quality assurance (PSQA) was evaluated using COMPASS measured data, COMPASS reconstructed (CR) and COMPASS computed (CC) dose compared to treatment planning system (TPS) dose. Clinical evaluation was based on DVH metrics for target volumes and organ at risks.The maximum average dose deviation between TPS, CC, and CR was below 3%. The paired t-test between TPS, CC, and CR shows a strong agreement (p < 0.001). The 3DVH dose distribution comparison between TPS and COMPASS were also performed with good gamma score for global analysis.COMPASS was successfully evaluated as a 3DVH pretreatment system for SBBC despite the large fields size and complex target volumes. It allows the verification of the plan in 3D patient anatomy and the evaluation of dose discrepancies.

A GPU-based fast Monte Carlo code that supports proton transport in magnetic field for radiation therapy.

This paper presents the effort to extend a previously reported code ARCHER, a GPU-based Monte Carlo (MC) code for coupled photon and electron transport, into protons including the consideration of magnetic fields. The proton transport is modeled using a Class-II condensed-history algorithm with continuous slowing-down approximation. The model includes ionization, multiple scattering, energy straggling, elastic and inelastic nuclear interactions, as well as deflection due to the Lorentz force in magnetic fields. An additional direction change is added for protons at the end of each step in the presence of the magnetic field. Secondary charge particles, except for protons, are terminated depositing kinetic energies locally, whereas secondary neutral particles are ignored. Each proton is transported step by step until its energy drops to below 0.5 MeV or when the proton leaves the phantom. The code is implemented using the compute unified device architecture (CUDA) platform for optimized GPU thread-level parallelism and efficiency. The code is validated by comparing it against TOPAS. Comparisons of dose distributions between our code and TOPAS for several exposure scenarios, ranging from single square beams in water to patient plan with magnetic fields, show good agreement. The 3D-gamma pass rate with a 2mm/2% criterion in the region with dose greater than 10% of the maximum dose is computed to be over 99% for all tested cases. Using a single NVIDIA TITAN V GPU card, the computational time of ARCHER is found to range from 0.82 to 4.54 seconds for 1×107 proton histories. Compared to a few hours running on TOPAS, this speed improvement is significant. This work presents, for the first time, the performance of a GPU-based MC code to simulate proton transportation magnetic fields, demonstrating the feasibility of accurate and efficient dose calculations in potential magnetic resonance imaging (MRI)-guided proton therapy.

Monte Carlo simulations for targeted beta therapy: An optimization for liver lesions and comparison of dose distributions in other organs

ObjectiveTo optimize targeted beta therapy for liver lesions in adult male phantom by comparing the efficacy and safety profiles of five different beta-emitting radionuclides: 90Y, 166Ho, 153Sm, 47Sc, and 177Lu. MethodsThis study includes Monte Carlo simulations of the behavioral characteristics of five different beta emitters that have current or potential use in targeted beta therapy. The energy loss of beta particles moving within the material through ionization or chemical processes, the energy transferred to the material, the energy lost by beta particles along the distance traveled within the tissue, and consequently, the stopping power are calculated using the Bethe-Bloch formula. The CSDA (continuous slowing-down approximation) range of beta particles within the tissue is examined using ESTAR and GEANT codes, while the stopping power of the tissue is investigated using FLUKA, ESTAR, and GEANT codes. Tissue dose calculations for the target organ are obtained using the IDAC-Dose2.1 and MIRDcalc simulation programs, using parameters such as absorbed dose per accumulated activity (S-factor) and specific absorbed fraction (SAF). Additionally, dose and flux values are obtained using the PHITS program. ResultsThe behaviors and dose contribution of beta particles in liver tissue have been addressed in various ways. 90Y, which has the highest average beta energy, was observed to provide a higher absorbed dose value in the liver compared to other beta-emitting isotopes, while the lowest absorbed dose was observed with 177Lu. In other organs, it has been observed that 90Y and 47Sc contribute to a higher absorbed dose compared to other beta-emitting isotopes. ConclusionsThis study emphasizes the complexity and significance of targeted beta therapy optimization.

Generalisation of radiotherapy dose calculation for Monte Carlo algorithm combined with 3D Swin-Unet: a multi-institutional IMRT evaluation

Objective. Accurate dose calculations are essential prerequisites for precise radiotherapy. The integration of deep learning into dosimetry could consider computational accuracy and efficiency and has potential applicability to clinical dose calculation. The generalisation of a deep learning dose calculation method (hereinafter referred to as TERMA-Monte Carlo network, T-MC net) was evaluated in clinical practice using intensity-modulated radiotherapy (IMRT) plans for various human body regions and multiple institutions, with the Monte Carlo (MC) algorithm serving as a benchmark. Approach. Sixty IMRT plans were selected from four institutions for testing the head and neck, chest and abdomen, and pelvis regions. Using the MC results as the benchmark, the T-MC net calculation results were used to perform three-dimensional dose distribution and dose-volume histogram (DVH) comparisons of the entire body, planning target volume (PTV) and organs at risk (OARs), respectively, and calculate the mean ±95% confidence interval of gamma pass rate (GPR), percentage of agreement (PA) and dose difference ratio (DDR) of dose indices D95, D50, and D5. Main results. For the entire body, the GPRs of 3%/3 mm, 2%/2 mm, 2%/1 mm, and the PA were 99.62 ± 0.32%, 98.50 ± 1.09%, 95.60 ± 2.90% and 97.80 ± 1.12%, respectively. For the PTV, the GPRs of 3%/3 mm, 2%/2 mm, 2%/1 mm and the PA were 98.90 ± 1.00%, 95.78 ± 2.83%, 92.23 ± 4.74% and 98.93 ± 0.62%, respectively. The absolute value of average DDR was less than 1.4%. Significance. We proposed a general dose calculation framework based on deep learning, using the MC algorithm as a benchmark, performing a generalisation test for IMRT treatment plans across multiple institutions. The framework provides high computational speed while maintaining the accuracy of MC and may become an effective dose algorithm engine in treatment planning, adaptive radiotherapy, and dose verification.

Total marrow lymphoid irradiation IMRT treatment using a novel CT-linac

BackgroundA novel CT-linac (kilovolt fan-beam CT-linac) has been introduced into total marrow and lymphoid irradiation (TMLI) treatment. Its integrated kilovolt fan-beam CT (kV FBCT) can be used not only for image guidance (IGRT) but also to re-calculate the dose.PurposeThis study reported our clinical routine on performing TMIL treatment on the CT-linac, as well as dose distribution comparison between planned and re-calculated based on IGRT FBCT image sets.Methods11 sets of data from 5 male and 6 female patients who had underwent the TMLI treatment with uRT-linac 506c were selected for this study. The planning target volumes consist of all skeletal bones exclusion of the mandible and lymphatic sanctuary sites. A planned dose of 10 Gy was prescribed to all skeletal bones exclusion of the mandible in two fractions and 12 Gy in two fractions was prescribed to lymphatic sanctuary sites. Each TMLI plan contained two sub-plans, one dynamic IMRT for the upper body and the other VMAT for the lower extremity. Two attempts were made to obtain homogeneous dose in the overlapping region, i.e., applying two plans with different isocenters for the treatment of two fractions, and using a dose gradient matching scheme. The CT scans, including planning CT and IGRT FBCT, were stitched to a whole body CT scan for dose distribution evaluation.ResultsThe average beam-on time of Planupper is 30.6 min, ranging from 24.9 to 37.5 min, and the average beam-on time of Planlower is 6.3 min, ranging from 5.7 to 8.2 min. For the planned dose distribution, the 94.79% of the PTVbone is covered by the prescription dose of 10 Gy (V10), and the 94.68% of the PTVlymph is covered by the prescription dose of 12 Gy (V12). For the re-calculated dose distribution, the 92.17% of the PTVbone is covered by the prescription dose of 10 Gy (V10), and the 90.07% of the PTVlymph is covered by the prescription dose of 12 Gy (V12). The results showed that there is a significant difference (p < 0.05) between planning V10, V12 and delivery V10, V12. There is no significant difference (p > 0.05) between planned dose and re-calculated dose on selected organs, except for right lens (p < 0.05, Dmax). The actual delivered maximum dose of right lens is apparently larger than the planned dose of it.ConclusionTMLI treatment can be performed on the CT-linac with clinical acceptable quality and high efficiency. Evaluation of the recalculated dose on IGRT FBCT suggests the treatment was delivered with adequate target coverage.

Commissioning of Mobius3D/FX for patient-specific quality assurance: The CUIMC-NewYork Presbyterian Hospital experience.

To present the process undertaken by our institute in commissioning Mobius3D (M3D) for patient-specific quality assurance. 168 plans were randomly selected to compare dose distribution measured with ArcCheck and dose calculated from M3D, both compared against the treatment planning system (TPS). The gamma criteria for measurement and M3D are 3%/2mm with 10% and 50% dose thresholds, respectively. The effect of tissue inhomogeneity was investigated on 11 plans by recalculating the dose in M3D on a homogeneous phantom. Tolerance and action limits were established following the AAPM Task Group 218 recommendations. The M3D showed high variability in gamma passing rate compared to the measurement. Twenty-three out of 168 plans had false negative dose comparisons. These plans fall under high tissue inhomogeneity like lung and metal implants, small field targets, and breast plans planned with high energy. One false negative case (0.6%) was observed. A single tolerance limit of 91% and 92% gamma passing rate for the M3D and measurement-based PSQA were established, respectively. Against the expectation, recalculating plans on the homogeneous phantom in M3D did not necessarily increase the gamma passing rate. These plans have a duty cycle >4.2, and the small field sizes combined with differences in slice thickness contributed to observed dose differences in the homogeneous phantom comparisons. Following the commissioning, M3Dis adopted in our institute. Currently, the gamma criteria used for measurement and M3Dare 3%/2mm, 40% dose threshold, with gamma passing rates of 92% and 95%, respectively. A higher passing rate for M3D is adopted until more data is available. The combined effect of plan modulation, the field sizes, the tissue inhomogeneity, the dose algorithm, and the volume averaging effect from differences in slice thickness can contribute to the differences in dose in M3Dand TPS.

Extracting the gradient component of the gamma index using the Lie derivative method

Objective. The gamma index (γ) has been extensively investigated in the medical physics and applied in clinical practice. However, γ has a significant limitation when used to evaluate the dose-gradient region, leading to inconveniences, particularly in stereotactic radiotherapy (SRT). This study proposes a novel evaluation method combined with γ to extract clinically problematic dose-gradient regions caused by irradiation including certain errors. Approach. A flow-vector field in the dose distribution is obtained when the dose is considered a scalar potential. Using the Lie derivative from differential geometry, we defined L, S, and U to evaluate the intensity, vorticity, and flow amount of deviation between two dose distributions, respectively. These metrics multiplied by γ (γL, γS, γU), along with the threshold value σ, were verified in the ideal SRT case and in a clinical case of irradiation near the brainstem region using radiochromic films. Moreover, Moran’s gradient index (MGI), Bakai’s χ factor, and the structural similarity index (SSIM) were investigated for comparisons. Main results. A high L-metric value mainly extracted high-dose-gradient induced deviations, which was supported by high S and U metrics observed as a robust deviation and an influence of the dose-gradient, respectively. The S-metric also denotes the measured similarity between the compared dose distributions. In the γ distribution, γL sensitively detected the dose-gradient region in the film measurement, despite the presence of noise. The threshold σ successfully extracted the gradient-error region where γ > 1 analysis underestimated, and σ = 0.1 (plan) and σ = 0.001 (film measurement) were obtained according to the compared resolutions. However, the MGI, χ, and SSIM failed to detect the clinically interested region. Significance. Although further studies are required to clarify the error details, this study demonstrated that the Lie derivative method provided a novel perspective for the identifying gradient-induced error regions and enabled enhanced and clinically significant evaluations of γ.

Isodose surface differences: A novel tool for the comparison of dose distributions.

Comparing dose distributions is a routine task in radiotherapy, mainly in patient-specific quality assurance (PSQA). Currently, the evaluation of the dose distributions is being performed mainly with statistical methods, which could underestimate the clinical importance of the spotted differences, as per the literature. This paper aims to provide proof-of-concept for a novel dose distribution comparison method based on the difference of the isodose surfaces. The new method connects acceptance tolerance to QA limitations (equipment capabilities) and integrates a clinical approach into the analysis procedure. The distance of dose points from the isocenter can be used as a function to define the shape of an isodose surface expressed as a histogram. Isodose surface differences (ISD) are defined as the normalized differences of reference and evaluated surface histograms plotted against their corresponding isodose. Acceptance tolerances originate from actual QA tolerances and are presented clinically intuitively. The ISD method was compared to the gamma index using intentionally erroneous VMAT and IMRT plans. Results revealed that the ISD method is sensitive to all errors induced in the plans. Discrepancies are presented per isodose, enabling the evaluation of the plan in two regions representing PTV and Normal Tissue.ISD manages to flag errors that would remain undetected under the gamma analysis. The ISD method is a meaningful, QA-related, registration-free, and clinically oriented technique of dose distribution evaluation. This method can be used either as a standalone or an auxiliary tool to the well-established evaluation procedures, overcoming significant limitations reported in the literature.

A Comparison of Two Plan Optimization Methods in Three-Dimensional Brachytherapy for Cervical Cancer

To compare dose distributions created by using two Inverse Planning Simulated Annealing (IPSA) and Hybrid Inverse Planning Optimization (HIPO) in three-dimensional (with CT image guidance) brachytherapy planning for cervical cancer. Brachytherapy plans for thirty patients with cervical cancer were created using the IPSA and HIPO algorithms (The IPSA algorithm is calculated based on the anatomical structure, and the simulated annealing algorithm is used to optimize the residence time, and the HIPO algorithm is the optimization and replacement for the IPSA). To obtain a HIPO plan, a manually optimized post-loading treatment plan was applied to these 30 patients, and then the treatment plan was reoptimized using the HIPO algorithm based on the original image information. Individual patients will consider interpolation therapy according to the needs of their condition. The types of plans were compared based on a variety of dose volume parameters, including the mean dose covering 90% of high-risk clinical target volume (D90 for HR-CTV), the mean dose to 2 cm3 volume (D2cc) for bladder, rectum, intestine and sigmoid, and average treatment time were compared and analyzed. Compared with the two groups of plans, mean value of HR-CTV D90 for the HIPO plans was (585 cGy), which was significantly higher than that for the IPSA plans (567 cGy. This difference is statistically significant (P<0.05). The HIPO plans had mean D2cc 422±47 cGy for bladder, 403±38 cGy for rectum, which were lower than those from the SA plans, i.e., 446±42 cGy for bladder and 427±31 cGy for rectum; These differences were statistically significant (t = 5.125, 4.729, P <0.05). There was no statistically significant difference in the sigmoid D2cc doses between the two algorithms. The treatment times for delivering the two types of plans were not significant different. Depending on patient's condition, whether conventional brachytherapy therapy or interpolation therapy is used, the use of the HIPO algorithm to design the treatment regimen without additional treatment time can provide a higher target dose than the manually optimized brachytherapy regimen. Meanwhile, the bladder and rectum doses can be reduced to a certain extent under the premise of ensuring that the target dose met the treatment requirements. There is some increasement for the intestine dose with HIPO planning group, but the dose limits required by the guidelines are still met clinical requirement.

Evaluation of the clinical feasibility of cone-beam computed tomography guided online adaption for simulation-free palliative radiotherapy

Background and purposeSimulation-free radiotherapy, where diagnostic imaging is used for treatment planning, improves accessibility of radiotherapy for eligible palliative patients. Combining this pathway with online adaptive radiotherapy (oART) may improve accuracy of treatment, expanding the number of eligible patients. This study evaluated the adaptive process duration, plan dose volume histogram (DVH) metrics and geometric accuracy of a commercial cone-beam computed tomography (CBCT)-guided oART system for simulation-free, palliative radiotherapy. Materials and methodsTen previously treated palliative cases were used to compare system-generated contours against clinician contours in a test environment with Dice Similarity Coefficient (DSC). Twenty simulation-free palliative patients were treated clinically using CBCT-guided oART. Analysis of oART clinical treatment data included; evaluation of the geometric accuracy of system-generated synthetic CT relative to session CBCT anatomy using a Likert scale, comparison of adaptive plan dose distributions to unadapted, using DVH metrics and recording the duration of key steps in the oART workflow. ResultsAuto-generated contours achieved a DSC of higher than 0.85, excluding the stomach which was attributed to CBCT image quality issues. Synthetic CT was locally aligned to CBCT anatomy for approximately 80% of fractions, with the remaining suboptimal yet clinically acceptable. Adaptive plans achieved a median CTV V95% of 99.5%, compared to 95.6% for unadapted. The median overall oART process duration was found to be 13.2 mins, with contour editing being the most time-intensive adaptive step. ConclusionsThe CBCT-guided oART system utilising a simulation-free planning approach was found to be sufficiently accurate for clinical implementation, this may further streamline and improve care for palliative patients.

Hybrid planning techniques for early-stage left-sided breast cancer: dose distribution analysis and estimation of projected secondary cancer-relative risk

Purpose The purpose of this study was to evaluate three techniques of irradiation of left-sided breast cancer patients, three-dimensional conformal radiotherapy (3D-CRT), hybrid Intensity-Modulated Radiotherapy (h-IMRT), and hybrid Volumetric-Modulated Arc Therapy (h-VMAT, h-ARC), in terms of dose distribution in the planning target volume (PTV) and organs at risk (OARs). The second aim was to estimate the projected relative risk of radiation-induced secondary cancers for hybrid techniques. Materials and methods Three treatment plans were prepared in 3D-CRT, h-IMRT, and h-VMAT techniques for each of the 40 patients, who underwent CT simulation in deep inspiration breath-hold (DIBH). For hybrid techniques, plans were created by combining 3D-CRT and dynamic fields with an 80%/20% dose ratio for 3D-CRT and IMRT or VMAT. Cumulative dose–volume histograms were used to compare dose distributions within the PTV and OARs (heart, left anterior descending coronary artery [LAD], left and right lung [LL, RL], right breast [RB]). Projected risk ratios for secondary cancers were estimated relative to 3D-CRT using the organ equivalent dose (OED) concept for the Schneider’s linear exponential, plateau, and full mechanistic dose–response model. Results All plans fulfilled the PTV criterium: V95%≥95%. Compared to 3D-CRT, both hybrid techniques showed significantly better target coverage (PTV: V95%>98%, p < 0.001), and the best conformality was achieved by h-ARC plans (CI: 1.18 ± 0.09, p < 0.001). Compared to 3D-CRT and h-ARC, h-IMRT increased the average sum of monitor units (MU) over 129.9% (p < 0.001). H-ARC increased the mean dose of contralateral organs and the LL V5Gy parameter (p < 0.001). Both hybrid techniques significantly reduced the D max of the heart by 5 Gy. Compared to h-IMRT, h-ARC increased secondary cancer projected relative risk ratios for LL, RL, and RB by 18, 152, and 81%, respectively. Conclusions The results confirmed that both hybrid techniques provide better target quality and OARs sparing than 3D-CRT. Hybrid VMAT delivers less MU compared to hybrid IMRT but may increase the risk of radiation-induced secondary malignancies.

Automated treatment planning for proton pencil beam scanning using deep learning dose prediction and dose-mimicking optimization.

The purpose of this study is to investigate the use of a deep learning architecture for automated treatment planning for proton pencil beam scanning (PBS). A 3-dimensional (3D) U-Net model has been implemented in a commercial treatment planning system (TPS) that uses contoured regions of interest (ROI) binary masks as model inputs with a predicted dose distribution as the model output. Predicted dose distributions were converted to deliverable PBS treatment plans using a voxel-wise robust dose mimicking optimization algorithm. This model was leveraged to generate machine learning (ML) optimized plans for patients receiving proton PBS irradiation of the chest wall. Model training was carried out on a retrospective set of 48 previously-treated chest wall patient treatment plans. Model evaluation was carried out by generating ML-optimized plans on a hold-out set of 12 contoured chest wall patient CT datasets from previously treated patients. Clinical goal criteria and gamma analysis were used to compare dose distributions of the ML-optimized plans against the clinically approved plans across the test patients. Statistical analysis of mean clinical goal criteria indicates that compared to the clinical plans, the ML optimization workflow generated robust plans with similar dose to the heart, lungs, and esophagus while achieving superior dosimetric coverage to the PTV chest wall (clinical mean V95=97.6% vs. ML mean V95=99.1%, p<0.001) across the 12 test patients. ML-based automated treatment plan optimization using the 3D U-Net model can generate treatment plans of similar clinical quality compared to human-driven optimization.