BACKGROUND: Emerging evidence indicates that intravenous ketamine is effective in managing treatment-resistant unipolar and bipolar depression. Clinical studies highlight its favorable efficacy, safety, and tolerability profile within a dosage range of 0.5-1.0 mg/kg based on actual body weight. However, data on alternative dosage calculation methods, particularly in relation to body mass index (BMI) and therapeutic outcomes, remain limited.
METHODS: This retrospective analysis of an open-label study aims to evaluate dose calculation strategies and their impact on treatment response among inpatients with treatment-resistant major depressive disorder (MDD) (n = 28). The study employed the Boer and Devine formulas to determine lean body mass (LBM) and ideal body weight (IBW), and the Mosteller formula to estimate body surface area (BSA). The calculated doses were then compared with the actual doses administered or converted to a dosage per square meter for both responders and non-responders.
RESULTS: Regardless of treatment response, defined as a reduction of 50% in the Montgomery-Åsberg Depression Rating Scale, the use of alternative ketamine dosing formulas resulted in underdosing compared to the standardized dose of 0.5 mg/kg. Only two participants received higher doses (102.7% and 113.0%) when the Devine formula was applied.
CONCLUSIONS: This study suggests that ketamine dosing formulas, alternative to the standardized 0.5 mg/kg based on body weight, may lead to underdosing and potentially impact outcome interpretation. To enhance dosing accuracy, future studies should consider incorporating body impedance analysis and waist-to-hip ratio measurements, as this study did not account for body composition.

OBJECTIVE: A dose calculation algorithm Computed Tomography (CT)-based analytical dose calculation method (CTanly), which can correct for subject inhomogeneity and size-dependent scatter doses, was applied to the 198Au seed. In this study, we evaluated the effectiveness of the CTanly method by comparing the gold standard Monte Carlo (MC) method and the conventional TG43 method on two virtual phantoms and patient CT images simulating oral cancer.
METHODS: As virtual phantoms, a water phantom and a heterogeneous phantom with soft tissue inserted cubic fat, lung, and bone were used. A 2-mm-thick lead plate was also inserted into the heterogeneous phantom as a dose attenuator. Virtual 198Au seeds and a 2-mm-thick lead plate were placed on the patient CT images. Dose distributions obtained via the TG43 and CTanly methods were compared with those of the MC by gamma analysis with 2%/2-mm thresholds. The computation durations were also compared.
RESULTS: In the water phantom, dose distributions comparable to those obtained via the MC method were obtained regardless of the algorithm. For the inhomogeneity phantom and patient case, the CTanly method showed an improvement in the gamma passing rate and dose distributions similar to those of the MC method were obtained. The computation time, which was days with the MC method, was reduced to minutes with the CTanly method.
CONCLUSIONS: The CTanly method is effective for 198Au seed dose calculations and takes a shorter time to obtain the dose distributions than the MC method.

BACKGROUND: High-quality 3D-anatomy of the day is needed for treatment plan adaptation in radiotherapy. For online x-ray-based CBCT workflows, one approach is to create a synthetic CT or to utilize a fan-beam CT with corresponding registrations. The former potentially introduces uncertainties in the dose calculation if deformable image registration is used. The latter can introduce burden and complexity to the process, the facility, and the patient.
OBJECTIVE: Using the CBCT of the day, acquired on the treatment device, for direct dose calculation and plan adaptation can overcome these limitations. This study aims to assess the accuracy of the calculated dose on the CBCT scans acquired on a Halcyon linear accelerator equipped with HyperSight.
METHODS: HyperSight\'s new CBCT reconstruction algorithm includes improvements in scatter correction, HU calibration of the imager, and beam shape adaptation. Furthermore, HyperSight introduced a new x-ray detector. To show the effect of the implemented improvements, gamma comparisons of 2%/2 mm, 2%/1 mm, and 1%/1 mm were made between the dose distribution in phantoms calculated on the CBCT reconstructions and the simulation CT scans, considering this the standard of care. The resulting gamma passing rates were compared to those obtained with the Halcyon 3.0 reconstruction and hardware without HyperSight\'s technologies. Various anatomical phantoms for dosimetric evaluations on brain, head and neck, lung, breast, and prostate cases have been used in this study.
RESULTS: The overall results demonstrated that HyperSight outperformed the Halcyon 3.0 version. Based on the gamma analysis, the calculated dose using HyperSight was closer to the CT scan-based doses than the calculated dose using iCBCT Halcyon 3.0 for most cases. Over all plans and gamma criteria, Halcyon 3.0 achieved an average passing rate of 92.9%, whereas HyperSight achieved 98.1%.
CONCLUSIONS: Using HyperSight CBCT images for direct dose calculation, for example, in (online) plan adaptation, seems feasible for the investigated cases.

OBJECTIVE: The Monte Carlo (MC) method, the gold standard method for radiotherapy dose calculations, is underused in clinical research applications mainly due to computational speed limitations. Another reason is the time-consuming and error prone conversion of treatment plan specifications into MC parameters. To address this issue, we developed an interface tool that creates a set of TOPAS parameter control files (PCF) from information exported from a clinical treatment planning system (TPS) for plans delivered by the TrueBeam radiotherapy system.
METHODS: The interface allows the user to input DICOM-RT files, exported from a TPS and containing the plan parameters, and choose different multileaf-collimator models, variance reduction technique parameters, scoring quantities and simulation output formats. Radiation sources are precomputed phase space files obtained from Varian. Based on this information, ready-to-run TOPAS PCF that incorporate the position and angular rotation of the TrueBeam dynamic collimation devices, gantry, couch, and patient according to treatment plan specifications are created.
RESULTS: Dose distributions computed using these PCF were compared against predictions from commercial TPS for different clinical treatment plans and techniques (3D-CRT, IMRT step-and-shoot and VMAT) to evaluate the performance of the interface. The agreement between dose distributions from TOPAS and TPS (>98 % pass ratio in the gamma test) confirmed the correct parametrization of treatment plan specifications into MC PCF.
CONCLUSIONS: This interface tool is expected to widen the use of MC methods in the clinical medical physics field by facilitating the straightforward transfer of treatment plan parameters from commercial TPS into MC PCF.

This article examines the critical role of fast Monte Carlo (MC) dose calculations in advancing proton therapy techniques, particularly in the context of increasing treatment customization and precision. As adaptive radiotherapy and other patient-specific approaches evolve, the need for accurate and precise dose calculations, essential for techniques like proton-based stereotactic radiosurgery, becomes more prominent. These calculations, however, are time-intensive, with the treatment planning/optimization process constrained by the achievable speed of dose computations. Thus, enhancing the speed of MC methods is vital, as it not only facilitates the implementation of novel treatment modalities but also leads to more optimal treatment plans. Today, the state-of-the-art in MC dose calculation speeds is 106-107protons per second. This review highlights the latest advancements in fast MC dose calculations that have led to such speeds, including emerging artificial intelligence-based techniques, and discusses their application in both current and emerging proton therapy strategies.

BACKGROUND: Conventional single-energy CT can only provide a raw estimation of electron density (ED) for dose calculation by developing a calibration curve that simply maps the HU values to ED values through their correlations. Spectral CT, also known as dual-energy CT (DECT) or multi-energy CT, can generate a series of quantitative maps, such as ED maps. Using spectral CT for radiotherapy simulations can directly acquire ED information without developing specific calibration curves. The purpose of this study is to assess the feasibility of utilizing electron density (ED) maps generated by a novel dual-layer detector spectral CT simulator for dose calculation in radiotherapy treatment plans.
METHODS: 30 patients from head&neck, chest, and pelvic treatment sites were selected retrospectively, and all of them underwent spectral CT simulation. Treatment plans based on conventional CT images were transplanted to ED maps with the same structure set, including planning target volume (PTV) and organs at risk (OARs), and the dose distributions were then recalculated. The differences in dose and volume histogram (DVH) parameters of the PTV and OARs between the two types of plans were analyzed and compared. Besides, gamma analysis between these plans was performed by using MEPHYSTO Navigator software.
RESULTS: In terms of PTV, the homogeneity index (HI), gradient index (GI), D2%, D98%, and Dmean showed no significant difference between conventional plans and ED plans. For OARs, statistically significant differences were observed in parotids D50%, brainstem in head&neck plans, spinal cord in chest plans and rectum D50% in pelvic plans, whereas the variance remained minor. For the rest, the DVH parameters exhibited no significant difference between conventional plans and ED plans. All of the mean gamma passing rates (GPRs) of gamma analysis were higher than 90%.
CONCLUSIONS: Compared to conventional treatment plans relying on CT images, plans utilizing ED maps demonstrated similar dosimetric quality. However, the latter approach enables direct utilization in dose calculation without the requirements of establishing and selecting a specific Hounsfield unit (HU) to ED calibration curve, providing an advantage in clinical applications.

BACKGROUND: The dynamic collimation system (DCS) provides energy layer-specific collimation for pencil beam scanning (PBS) proton therapy using two pairs of orthogonal nickel trimmer blades. While excellent measurement-to-calculation agreement has been demonstrated for simple cube-shaped DCS-trimmed dose distributions, no comparison of measurement and dose calculation has been made for patient-specific treatment plans.
OBJECTIVE: To validate a patient-specific quality assurance (PSQA) process for DCS-trimmed PBS treatment plans and evaluate the agreement between measured and calculated dose distributions.
METHODS: Three intracranial patient cases were considered. Standard uncollimated PBS and DCS-collimated treatment plans were generated for each patient using the Astroid treatment planning system (TPS). Plans were recalculated in a water phantom and delivered at the Miami Cancer Institute (MCI) using an Ion Beam Applications (IBA) dedicated nozzle system and prototype DCS. Planar dose measurements were acquired at two depths within low-gradient regions of the target volume using an IBA MatriXX ion chamber array.
RESULTS: Measured and calculated dose distributions were compared using 2D gamma analysis with 3%/3 mm criteria and low dose threshold of 10% of the maximum dose. Median gamma pass rates across all plans and measurement depths were 99.0% (PBS) and 98.3% (DCS), with a minimum gamma pass rate of 88.5% (PBS) and 91.2% (DCS).
CONCLUSIONS: The PSQA process has been validated and experimentally verified for DCS-collimated PBS. Dosimetric agreement between the measured and calculated doses was demonstrated to be similar for DCS-collimated PBS to that achievable with noncollimated PBS.

Objective.High-dose-rate (HDR) brachytherapy lacks routinely available treatment verification methods. Real-time tracking of the radiation source during HDR brachytherapy can enhance treatment verification capabilities. Recent developments in source tracking allow for measurement of dwell times and source positions with high accuracy. However, more clinically relevant information, such as dose discrepancies, is still needed. To address this, a real-time dose calculation implementation was developed to provide more relevant information from source tracking data. A proof-of-principle of the developed tool was shown using source tracking data obtained from a 3D-printed anthropomorphic phantom.Approach.Software was developed to calculate dose-volume-histograms (DVH) and clinical dose metrics from experimental HDR prostate treatment source tracking data, measured in a realistic pelvic phantom. Uncertainty estimation was performed using repeat measurements to assess the inherent dose measuring uncertainty of thein vivodosimetry (IVD) system. Using a novel approach, the measurement uncertainty can be incorporated in the dose calculation, and used for evaluation of cumulative dose and clinical dose-volume metrics after every dwell position, enabling real-time treatment verification.Main results.The dose calculated from source tracking measurements aligned with the generated uncertainty bands, validating the approach. Simulated shifts of 3 mm in 5/17 needles in a single plan caused DVH deviations beyond the uncertainty bands, indicating errors occurred during treatment. Clinical dose-volume metrics could be monitored in a time-resolved approach, enabling early detection of treatment plan deviations and prediction of their impact on the final dose that will be delivered in real-time.Significance.Integrating dose calculation with source tracking enhances the clinical relevance of IVD methods. Phantom measurements show that the developed tool aids in tracking treatment progress, detecting errors in real-time and post-treatment evaluation. In addition, it could be used to define patient-specific action limits and error thresholds, while taking the uncertainty of the measurement system into consideration.

OBJECTIVE: To assess the precision of dose calculations for Volumetric Modulated Arc Therapy (VMAT) using megavoltage (MV) photon beams, we validated the accuracy of two algorithms: AUROS XB and Analytical Anisotropic Algorithm (AAA). This validation will encompass both flattening filter (FF) and flattening filter-free beam (FFF) modes, using AAPM Medical Physics Practice Guideline (MPPG 5b).
METHODS: VMAT validation tests were generated for 6 MV FF and 6 MV FFF beams using the AAA and AXB algorithms in the Eclipse V.15.1 treatment planning system (TPS). Corresponding measurements were performed on a linear accelerator using a diode detector and a radiation field analyzer. Point dose (PD) and in-vivo measurements were conducted using an A1SL ion chamber and (TLD) from Thermofisher, respectively. The Rando Phantom was employed for end-to-end (E2E) tests.
RESULTS: The mean difference (MD) between the TPS-calculated values and the measured values for the PDD and output factors were within 1% and 0.5%, respectively, for both 6 MV FF and 6 MV FFF. In the TG 119 sets, the MD for PD with both AAA and AXB was <0.9%. For the TG 244 sets, the minimum, maximum, and mean deviations in PD for both 6 MV FF and 6 MV FFF beams were 0.3%, 1.4% and 0.8% respectively. In the E2E test, using the Rando Phantom, the MD between the TLD dose and the TPS dose was within 0.08% for both 6 MV FF (p=1.0) and 6 MV FFF (0.018) beams.
CONCLUSIONS: The accuracy of the TPS and its algorithms (AAA and AXB) has been successfully validated. The recommended tests included in the VMAT/IMRT validation section proved invaluable for verifying the PDD, output factors, and the feasibility of complex clinical cases. E2E tests were instrumental in validating the entire workflow from CT simulation to treatment delivery.

BACKGROUND: Seed implant brachytherapy (SIBT) is a promising treatment modality for parotid gland cancers (PGCs). However, the current clinical standard dose calculation method based on the American Association of Physicists in Medicine (AAPM) Task Group 43 (TG-43) Report oversimplifies patient anatomy as a homogeneous water phantom medium, leading to significant dose calculation errors due to heterogeneity surrounding the parotid gland. Monte Carlo Simulation (MCS) can yield accurate dose distributions but the long computation time hinders its wide application in clinical practice.
OBJECTIVE: This paper aims to develop an end-to-end deep convolutional neural network-based dose engine (DCNN-DE) to achieve fast and accurate dose calculation for PGC SIBT.
METHODS: A DCNN model was trained using the patient\'s CT images and TG-43-based dose maps as inputs, with the corresponding MCS-based dose maps as the ground truth. The DCNN model was enhanced based on our previously proposed model by incorporating attention gates (AGs) and large kernel convolutions. Training and evaluation of the model were performed using a dataset comprising 188 PGC I-125 SIBT patient cases, and its transferability was tested on an additional 16 non-PGC head and neck cancers (HNCs) I-125 SIBT patient cases. Comparison studies were conducted to validate the superiority of the enhanced model over the original one and compare their overall performance.
RESULTS: On the PGC testing dataset, the DCNN-DE demonstrated the ability to generate accurate dose maps, with percentage absolute errors (PAEs) of 0.67% ± 0.47% for clinical target volume (CTV) D90 and 1.04% ± 1.33% for skin D0.1cc. The comparison studies revealed that incorporating AGs and large kernel convolutions resulted in 8.2% (p < 0.001) and 3.1% (p < 0.001) accuracy improvement, respectively, as measured by dose mean absolute error. On the non-PGC HNC dataset, the DCNN-DE exhibited good transferability, achieving a CTV D90 PAE of 1.88% ± 1.73%. The DCNN-DE can generate a dose map in less than 10 ms.
CONCLUSIONS: We have developed and validated an end-to-end DCNN-DE for PGC SIBT. The proposed DCNN-DE enables fast and accurate dose calculation, making it suitable for application in the plan optimization and evaluation process of PGC SIBT.