Dose Planning Research Articles

Deep learning-based dose prediction for magnetic resonance-guided prostate radiotherapy.

Daily adaptive radiotherapy, as performed with the Elekta Unity MR-Linac, requires choosing between different adaptation methods, namely ATP (Adapt to Position) and ATS (Adapt to Shape), where the latter requires daily re-contouring to obtain a dose plan tailored to the daily anatomy. These steps are inherently resource-intensive, and quickly predicting the dose distribution and the dosimetric evaluation criteria while the patient is on the table could facilitate a fast selection of adaptation method and decrease the treatment times. In this work, we aimed to develop a deep-learning-based dose-prediction pipeline for prostate MR-Linac treatments. Two hundred twelve MR-images, structure sets, and dose distributions from 35 prostate patients treated with 6.1Gy for 7 or 6 fractions at our MR-Linac were included, split into train/test partitions of 152/60 images, respectively. A deep-learning segmentation network was trained to segment the CTV (prostate), bladder, and rectum. A second network was trained to predict the dose distribution based on manually delineated structures. At inference, the predicted segmentations acted as input to the dose prediction network, and the predicted dose was compared to the true (optimized in the treatment planning system) dose distribution. Median DSC values from the segmentation network were 0.90/0.94/0.87 for CTV/bladder/rectum. Predicted segmentations as input to the dose prediction resulted in mean differences between predicted and true doses of 0.7%/0.7%/1.7% (relative to the prescription dose) for D98%/D95%/D2% for the CTV. For the bladder, the difference was 0.7%/0.3% for Dmean/D2% and for the rectum 0.1/0.2/0.2 pp (percentage points) for V33Gy/V38Gy/V41Gy. In comparison, true segmentations as input resulted in differences of 1.1%/0.9%/1.6% for CTV, 0.5%/0.4% for bladder, and 0.7/0.4/0.3 pp for the rectum. Only D2% for CTV and Dmean/D2% for bladder were found to be statistically significantly better when using true structures instead of predicted structures as input to the dose prediction. Small differences in the fulfillment of clinical dose-volume constraints are seen between utilizing deep-learning predicted structures as input to a dose prediction network and manual structures. Overall mean differences<2% indicate that the dose-prediction pipeline is useful as a decision support tool where differences are>2%.

Technical note: Phantom-based evaluation of CBCT dose calculation accuracy for use in adaptive radiotherapy.

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 thepatient. 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 withHyperSight. 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%/2mm, 2%/1mm, and 1%/1mm 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 thisstudy. 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%. Using HyperSight CBCT images for direct dose calculation, for example, in (online) plan adaptation, seems feasible for the investigatedcases.

Deep learning for contour quality assurance for RTOG 0933: In-silico evaluation

PurposeTo validate a CT-based deep learning (DL) hippocampal segmentation model trained on a single-institutional dataset and explore its utility for multi-institutional contour quality assurance (QA). MethodsA DL model was trained to contour hippocampi from a dataset generated by an institutional observer (IO) contouring on brain MRIs from a single-institution cohort. The model was then evaluated on the RTOG 0933 dataset by comparing the treating physician (TP) contours to blinded IO and DL contours using Dice and Haussdorf distance (HD) agreement metrics as well as evaluating differences in dose to hippocampi when TP vs. IO vs. DL contours are used for planning. The specificity and sensitivity of the DL model to capture planning discrepancies was quantified using criteria of HD > 7 mm and Dmax hippocampi > 17 Gy. ResultsThe DL model showed greater agreement with IO contours compared to TP contours (DL:IO L/R Dice 74%/73%, HD 4.86/4.74; DL:TP L/R Dice 62%/65%, HD 7.23/6.94, all p < 0.001). Thirty percent of contours and 53 % of dose plans failed QA. The DL model achieved an AUC L/R 0.80/0.79 on the contour QA task via Haussdorff comparison and AUC of 0.91 via Dmax comparison. The false negative rate was 17.2%/20.5% (contours) and 5.8% (dose). False negative cases tended to demonstrate a higher DL:IO Dice agreement (L/R p = 0.42/0.03) and better qualitative visual agreement compared with true positive cases. ConclusionOur study demonstrates the feasibility of using a single-institutional DL model to perform contour QA on a multi-institutional trial for the task of hippocampal segmentation.

Enhanced 3D dose prediction for hypofractionated SRS (gamma knife radiosurgery) in brain tumor using cascaded-deep-supervised convolutional neural network.

Gamma Knife radiosurgery (GKRS) is a well-established technique in radiation therapy (RT) for treating small-size brain tumors. It administers highly concentrated doses during each treatment fraction, with even minor dose errors posing a significant risk of causing severe damage to healthy tissues. It underscores the critical need for precise and meticulous precision in GKRS. However, the planning process for GKRS is complex and time-consuming, heavily reliant on the expertise of medical physicists. Incorporating deep learning approaches for GKRS dose prediction can reduce this dependency, improve planning efficiency and homogeneity, streamline clinical workflows, and reduce patient lagging times. Despite this, precise Gamma Knife plan dose distribution prediction using existing models remains a significant challenge. The complexity stems from the intricate nature of dose distributions, subtle contrasts in CT scans, and the interdependence of dosimetric metrics. To overcome these challenges, we have developed a "Cascaded-Deep-Supervised" Convolutional Neural Network (CDS-CNN) that employs a hybrid-weighted optimization scheme. Our innovative method incorporates multi-level deep supervision and a strategic sequential multi-network training approach. It enables the extraction of intra-slice and inter-slice features, leading to more realistic dose predictions with additional contextual information. CDS-CNN was trained and evaluated using data from 105 brain cancer patients who underwent GKRS treatment, with 85 cases used for training and 20 for testing. Quantitative assessments and statistical analyses demonstrated high consistency between the predicted dose distributions and the reference doses from the treatment planning system (TPS). The 3D overall gamma passing rates (GPRs) reached 97.15% ± 1.36% (3mm/3%, 10% threshold), surpassing the previous best performance by 2.53% using the 3D Dense U-Net model. When evaluated against more stringent criteria (2mm/3%, 10% threshold, and 1mm/3%, 10% threshold), the overall GPRs still achieved 96.53% ± 1.08% and 95.03% ± 1.18%. Furthermore, the average target coverage (TC) was 98.33% ± 1.16%, dose selectivity (DS) was 0.57 ± 0.10, gradient index (GI) was 2.69 ± 0.30, and homogeneity index (HI) was 1.79 ± 0.09. Compared to the 3D Dense U-Net, CDS-CNN predictions demonstrated a 3.5% improvement in TC, and CDS-CNN's dose prediction yielded better outcomes than the 3D Dense U-Net across all evaluation criteria. The experimental results demonstrated that the proposed CDS-CNN model outperformed other models in predicting GKRS dose distributions, with predictions closely matching the TPS doses.

Comprehensive stereotactic radiosurgery platform characterization: A novel end-to-end approach with anthropomorphic 3D dosimetry.

Stereotactic radiosurgery (SRS) is a widely employed strategy for intracranial metastases, utilizing linear accelerators and volumetric modulated arc therapy (VMAT). Ensuring precise linear accelerator performance is crucial, given the small planning target volume (PTV) margins. Rapid dose falloff is vital to minimize brain radiation necrosis. Despite advances in SRS planning, tools for end-to-end testing of SRS treatments are lacking, hindering confidence in the procedure. This study introduces a novel end-to-end three-dimensional (3D) anthropomorphic dosimetry system for characterization of a radiosurgery platform, aiming to measure planning metrics, dose gradient index (DGI), brain volumes receiving at least 10 and 12Gy (V10, V12), as well as assess delivery uncertainties in multitarget treatments. The study also compares metrics from benchmark plans to enhance understanding and confidence in SRS treatments. The developed anthropomorphic 3D dosimetry system includes a modified Stereotactic End-to-End Verification (STEEV) phantom with a customized insert integrating 3D dosimeters and a fiber optic CT scanner. Labview and MATLAB programs handle optical scanning, image preprocessing, and dosimetric analysis. SlicerRT is used for 3D dose visualization and analysis. A film stack insert was used to validate the 3D dosimeter measurements at specific slices. Benchmark plans were developed and measured to investigate off-axis errors, dose spillage, small field dosimetry, and multi-target delivery. The accuracy of the developed 3D dosimetry system was rigorously assessed using radiochromic films. Two two-dimensional (2D) dose planes, extracted from the 3D dose distribution, were compared with film measurements, resulting in high passing rates of 99.9% and 99.6% in gamma tests. The mean relative dose difference between film and 3D dosimeter measurements was -1%, with a standard deviation of 2.2%, well within dosimeter uncertainties. In the first module, evaluating single-isocenter multitarget treatments, a 1.5mm dose distribution shift was observed when targets were 7cm off-axis. This shift was attributed to machine mechanical errors and image-guided system uncertainties, indicating potential limitations in conventional gamma tests. The second module investigated discrepancies in intermediate-to-low dose spillage, revealing higher measured doses in the connecting region between closely positioned targets. This discrepancy was linked to uncertainties in treatment planning system (TPS) modeling of out-of-field dose and multileaf collimator (MLC) characteristics, resulting in lower DGI values and higher V10 and V12 values compared to TPS calculations. In the third module, irradiating multiple targets showed consistent V10 and V12 values within 1 cm3 agreement with dose calculations. However, lower DGI values from measurements compared to calculations suggested intricacies in the treatment process. Conducting vital end-to-end testing demonstrated the anthropomorphic 3D dosimetry system's capacity to assess overall treatment uncertainty, offering a valuable tool for enhancing treatment accuracy in radiosurgery platforms. The study introduces a novel anthropomorphic 3D dosimetry system for end-to-end testing of a radiosurgery platform. The system effectively measures plan quality metrics, captures mechanical errors, and visualizes dose discrepancies in 3D space. The comprehensive evaluation capability enhances confidence in the commissioning and verification process, ensuring patient safety. The system is recommended for commissioning new radiosurgery platforms and remote auditing of existing programs.

Proton dose deposition matrix prediction using multi-source feature driven deep learning approach

Proton dose deposition results are influenced by various factors, such as irradiation angle, beamlet energy and other parameters. The calculation of the proton dose deposition matrix (DDM) can be highly complex but is crucial in intensity-modulated proton therapy (IMPT). In this work, we present a novel deep learning (DL) approach using multi-source features for proton DDM prediction. The DL5 proton DDM prediction method involves five input features containing beamlet geometry, dosimetry and treatment machine information like patient CT data, beamlet energy, distance from voxel to beamlet axis, distance from voxel to body surface, and pencil beam (PB) dose. The dose calculated by Monte Carlo (MC) method was used as the ground truth dose label. A total of 40 000 features, corresponding to 8000 beamlets, were obtained from head patient datasets and used for the training data. Additionally, seventeen head patients not included in the training process were utilized as testing cases. The DL5 method demonstrates high proton beamlet dose prediction accuracy, with an average determination coefficient R 2 of 0.93 when compared to the MC dose. Accurate beamlet dose estimation can be achieved in as little as 1.5 milliseconds for an individual proton beamlet. For IMPT plan dose comparisons to the dose calculated by the MC method, the DL5 method exhibited gamma pass rates of γ(2 mm, 2%) and γ(3 mm, 3%) ranging from 98.15% to 99.89% and 98.80% to 99.98%, respectively, across all 17 testing cases. On average, the DL5 method increased the gamma pass rates to γ(2 mm, 2%) from 82.97% to 99.23% and to γ(3 mm, 3%) from 85.27% to 99.75% when compared with the PB method. The proposed DL5 model enables rapid and precise dose calculation in IMPT plan, which has the potential to significantly enhance the efficiency and quality of proton radiation therapy.

Effect of Different Dose Rates on Dosimetric Parameters and Accuracy of the Pretreatment Quality Assurance During Intensity-modulated Radiotherapy Planning Using Anthropomorphic Phantom

Background: This study investigates the impact of varying dose rates on dosimetric parameters and pretreatment quality assurance (QA) accuracy in intensity-modulated radiotherapy (IMRT) planning using anthropomorphic phantoms. The research explores the dosimetric effects of different dose rates ranging from 100 to 600 monitor units per minute (MU/min) on parameters such as Homogeneity Index (HI), Conformity Index (CI), and dose to organs at risk (OAR). Method: Anthropomorphic phantoms, mimicking human tissues, were employed for simulation. Treatment plans were generated using the Eclipse Treatment Planning System, and dosimetric evaluations were conducted using cumulative dose-volume histograms (DVH). Furthermore, pretreatment patient-specific QA was performed using EPID portal dosimetry and Delta4 dosimetry system. Result: Treatment plans adhere to institutional protocol, ensuring the target receives ≥95% of the prescription dose while meeting OAR constraints. All plans maintain target homogeneity and conformality, keeping maximum doses within the target below 107%. Low dose plans exhibit superior target coverage, conformality, and homogeneity compared to higher doses. However, increased dose rates elevate delivered Monitor Units and maximum doses to critical structures. Gamma passing rates vary with dose rates, with the lowest at 100 MU/min and the highest at 400 MU/min for 1% 1mm criteria. Dosimetric evaluations using Delta 4 and EPID QA methods confirm plan validity across different dose rates. Conclusion: Low dose rate dosimetry is superior to higher rates for target and organ-at-risk (OAR) delivery, albeit prolonging delivery time and affecting internal organ motion. Portal dosimetry offers a faster, more convenient tool for IMRT pretreatment quality assurance (QA). Optimal results are achieved at 400 MU/min, enhancing gamma agreement between calculated and measured portal doses for complex fields. This improvement in QA enhances IMRT treatment delivery quality. However, patient-specific QA using the DELTA4 dosimetry system and ICRU 83 recommendations are insufficient for discussing dosimetric differences relevant to patient treatment.

Prediction of personalised postprandial glycaemic response in type 1 diabetes mellitus.

Patients with type 1 diabetes (T1D) face unique challenges in glycaemic control due to the complexity and uniqueness of the dietary structure in China, especially in terms of postprandial glycaemic response (PPGR). This study aimed to establish a personalized model for predicting PPGR in patients with T1D. Data provided by the First People's Hospital of Yunnan Province, 13 patients with T1D, were recruited and provided with an intervention for at least two weeks. All patients were asked to wear a continuous glucose monitoring (CGM) device under free-living conditions during the study period. To tackle the challenge of incomplete data from wearable devices for CGM measurements, the GAIN method was used in this paper to achieve a more rational interpolation process. In this study, patients' PPGRs were calculated, and a LightGBM prediction model was constructed based on a Bayesian hyperparameter optimisation algorithm and a random search algorithm, which integrated glucose measurement, insulin dose, dietary nutrient content, blood measurement and anthropometry as inputs. The experimental outcomes revealed that the PPGR prediction model presented in this paper demonstrated superior accuracy (R=0.63) compared to both the carbohydrate content only model (R=0.14) and the baseline model emulating the standard of care for insulin administration (R=0.43). In addition, the interpretation of the model using the SHAP method showed that blood glucose levels at meals and blood glucose trends 30 minutes before meals were the most important features of the model. The proposed model offers a heightened precision in predicting PPGR in patients with T1D, so it can better guide the diet plan and insulin intake dose of patients with T1D.

Patient-specific quality assurance of dynamically-collimated proton therapy treatment plans.

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. 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. 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. Measured and calculated dose distributions were compared using 2D gamma analysis with 3%/3mm 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). 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.

Impact Assessment of Systemic Geometric Distortion in 1.5T Magnetic Resonance Imaging Simulation through Three-dimensional Geometric Distortion Phantom on Dosimetric Accuracy for Magnetic Resonance Imaging-only Prostate Treatment Planning.

Magnetic resonance imaging (MRI)-only radiotherapy has emerged as a solution to address registration errors that can lead to missed dose delivery. However, the presence of systemic geometric distortion (SGD) stemming from gradient nonlinearity (GNL) and inhomogeneity of the main magnetic field (B0) necessitates consideration. This study aimed to quantitatively assess residual SGD in 1.5T MRI simulation using a three-dimensional (3D) geometric distortion phantom and evaluate its impact on dosimetric accuracy for retrospective prostate cancer patients. Ten retrospective cases of prostate cancer patients treated with volumetric modulated arc radiotherapy (VMAT) were randomly selected. A geometric distortion phantom was scanned on a 1.5T MRI simulation using a 3D T1 volumetric interpolated breath-hold examination sequence, varying bandwidth (BW), and two-phase-encoding directions. Distortion maps were generated and applied to the original computed tomography (oriCT) plan to create a distorted computed tomography plan (dCT), and a dice similarity coefficient (DSC) was observed. Dosimetric accuracy was evaluated by recalculating radiation dose for dCT plans using identical beam parameters as oriCT. The SGD increased with distance from the isocenter in all series. DSC exceeded 0.95 for all plans except the rectum. Regarding GNL's impact on dosimetric accuracy, most mean percentage errors for clinical target volume, planning target volume, and both femurs were under 2% in all plans, except for the bladder and rectum. SGD pre-evaluation is crucial and should be incorporated into a quality assurance program to ensure effective MRI-simulation performance before MRI-only treatment planning for prostate cancer.

The impact of plan complexity on calculation and measurement-based pre-treatment verifications for sliding-window intensity-modulated radiotherapy

Background and purposeIn sliding-window intensity-modulated radiotherapy, increased plan modulation often leads to increased plan complexities and dose uncertainties. Dose calculation and/or measurement checks are usually adopted for pre-treatment verification. This study aims to evaluate the relationship among plan complexities, calculated doses and measured doses. Materials and methodsA total of 53 plan complexity metrics (PCMs) were selected, emphasizing small field characteristics and leaf speed/acceleration. Doses were retrieved from two beam-matched treatment devices. The intended dose was computed employing the Anisotropic Analytical Algorithm and validated through Monte Carlo (MC) and Collapsed Cone Convolution (CCC) algorithms. To measure the delivered dose, 3D diode arrays of various geometries, encompassing helical, cross, and oblique cross shapes, were utilized. Their interrelation was assessed via Spearman correlation analysis and principal component linear regression (PCR). ResultsThe correlation coefficients between calculation-based (CQA) and measurement-based verification quality assurance (MQA) were below 0.53. Most PCMs showed higher correlation rpcm-QA with CQA (max: 0.84) than MQA (max: 0.65). The proportion of rpcm-QA ≥ 0.5 was the largest in the pelvis compared to head-and-neck and chest-and-abdomen, and the highest rpcm-QA occurred at 1 %/1mm. Some modulation indices for the MLC speed and acceleration were significantly correlated with CQA and MQA. PCR’s determination coefficients (R2) indicated PCMs had higher accuracy in predicting CQA (max: 0.75) than MQA (max: 0.42). ConclusionsCQA and MQA demonstrated a weak correlation. Compared to MQA, CQA exhibited a stronger correlation with PCMs. Certain PCMs related to MLC movement effectively indicated variations in both quality assurances.

Motion-induced dose perturbations in photon radiotherapy and proton therapy measured by deformable liver-shaped 3D dosimeters in an anthropomorphic phantom

Background and purposeThe impact of intrafractional motion and deformations on clinical radiotherapy delivery has so far only been investigated by simulations as well as point and planar dose measurements. The aim of this study was to combine anthropomorphic 3D dosimetry with a deformable abdominal phantom to measure the influence of intra-fractional motion and gating in photon radiotherapy and evaluate the applicability in proton therapy. Material and methodsAn abdominal phantom was modified to hold a deformable anthropomorphic 3D dosimeter shaped as a human liver. A liver-specific photon radiotherapy and a proton pencil beam scanning therapy plan were delivered to the phantom without motion as well as with 12 mm sinusoidal motion while using either no respiratory gating or respiratory gating. ResultsUsing the stationary irradiation as reference the local 3 %/2 mm 3D gamma index pass rate of the motion experiments in the planning target volume (PTV) was above 97 % (photon) and 78 % (proton) with gating whereas it was below 74 % (photon) and 45 % (proton) without gating. ConclusionsFor the first time a high-resolution deformable anthropomorphic 3D dosimeter embedded in a deformable abdominal phantom was applied for experimental validation of both photon and proton treatments of targets exhibiting respiratory motion. It was experimentally shown that gating improves dose coverage and the geometrical accuracy for both photon radiotherapy and proton therapy.

Inter-fraction motion robustness in a prospective phase II trial on dose-escalated proton reirradiation for locally recurrent rectal cancer

Background and purposeIntensity modulated proton therapy (IMPT) enables generation of conformal dose plans with organ at risk (OAR) sparing potential. However, pelvic IMPT robustness is challenged by inter-fraction motion caused by constant anatomical variations. In this study, the dosimetric impact of inter-fraction motion on target coverage and dose to OAR was quantified in the prospective phase II study ReRad-II on dose-escalated proton reirradiation for locally recurrent rectal cancer (LRRC). Materials and methodsThe inter-fraction motion robustness was assessed for the initial twelve patients enrolled in the ReRad-II study. Patients with resectable LRRC were assessed for neoadjuvant IMPT (55 Gy(RBE)/44Fx) and unresectable recurrences for definitive IMPT (57.5–65 Gy(RBE)/ 46-52Fx). Target coverage and dose to OAR were assessed for robustly optimised three-field IMPT, on 12 plan computerized tomography (CT) scans (pCT) − and 47 repetitive control CT scans (cCTs) during the treatment. The target coverage and doses to OAR were re-calculated on each cCT and the mean dose ratio (pCT/cCT-ratio) and target coverage (V95%) was evaluated. ResultsThe target coverage was robust with a mean dose pCT/cCT-ratio of 1.00 (+/-1%). The V95% target coverage for every cCT were above the accepted worst-case scenario in the robust evaluation. Considerable variation in bladder-, bowel bag-, and bowel loop volume was observed. The OAR with the largest variation in ratio was the bladder (pCT/cCT-ratio: 1.3 (range: 0.5–4.7). ConclusionsIMPT for dose-escalated reirradiation of LRRC provided anatomically robust target coverage despite OAR changes. Inter-fraction motion resulted in OAR doses varying within clinically acceptable range.

Pseudoprogression After Adaptive Radiation Therapy For Early-Stage Non-Small Cell Lung Cancer: Case Report

Background: Differentiating local recurrence from pseudoprogression after radiotherapy for early-stage non-small cell lung cancer (NSCLC) can be challenging. Adaptive radiation therapy (ART) is an innovative radiotherapy technique that adjusts the radiation dose and treatment plan to ensure the tumor receives the optimal radiation while minimizing exposure to the surrounding healthy tissue. To our knowledge, there is no report of pseudoprogression in a patient with NSCLC who received ART. Objectives: The purpose of this article is to present the CT and 18-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) imaging findings of pseudoprogression after ART and discuss the imaging findings important for diagnosis and management. Case summaries: An 87-year-old woman with early-stage NSCLC underwent ART, receiving a total dose of 74 Gy administered in 37 fractions. The maximum standard uptake value (SUVmax) of 18F-FDG in the tumor increased from 2.5 before ART to 3.7 six months after ART on PET, suggesting local recurrence. However, the SUVmax decreased to 2.2 one year after ART, and on CT, the tumor size decreased consistently after ART. Based on serial CT and PET imaging findings, the temporal uptake of 18F-FDG at 6 months after ART was diagnosed as pseudoprogression. Conclusion: Serial CT and PET imaging findings may help differentiate local recurrence from pseudoprogression when tumor size decreases on CT but 18F-FDG uptake increases on PET. Keywords: Differential Diagnosis; Lung Neoplasms; Adaptive Radiation Therapy, Positron-emission Tomography

Quantifying the Dosimetric Impact of Proton Range Uncertainties on RBE-Weighted Dose Distributions in Intensity-Modulated Proton Therapy for Bilateral Head and Neck Cancer.

In current clinical practice, intensity-modulated proton therapy (IMPT) head and neck cancer (HNC) plans are generated using a constant relative biological effectiveness (cRBE) of 1.1. The primary goal of this study was to explore the dosimetric impact of proton range uncertainties on RBE-weighted dose (RWD) distributions using a variable RBE (vRBE) model in the context of bilateral HNC IMPT plans. The current study included the computed tomography (CT) datasets of ten bilateral HNC patients who had undergone photon therapy. Each patient's plan was generated using three IMPT beams to deliver doses to the CTV_High and CTV_Low for doses of 70 Gy(RBE) and 54 Gy(RBE), respectively, in 35 fractions through a simultaneous integrated boost (SIB) technique. Each nominal plan calculated with a cRBE of 1.1 was subjected to the range uncertainties of ±3%. The McNamara vRBE model was used for RWD calculations. For each patient, the differences in dosimetric metrices between the RWD and nominal dose distributions were compared. The constrictor muscles, oral cavity, parotids, larynx, thyroid, and esophagus showed average differences in mean dose (Dmean) values up to 6.91 Gy(RBE), indicating the impact of proton range uncertainties on RWD distributions. Similarly, the brachial plexus, brain, brainstem, spinal cord, and mandible showed varying degrees of the average differences in maximum dose (Dmax) values (2.78-10.75 Gy(RBE)). The Dmean and Dmax to the CTV from RWD distributions were within ±2% of the dosimetric results in nominal plans. The consistent trend of higher mean and maximum doses to the OARs with the McNamara vRBE model compared to cRBE model highlighted the need for consideration of proton range uncertainties while evaluating OAR doses in bilateral HNC IMPT plans.

Proton 3D dose measurement with a multi-layer strip ionization chamber (MLSIC) device

Objective. In current clinical practice for quality assurance (QA), intensity modulated proton therapy (IMPT) fields are verified by measuring planar dose distributions at one or a few selected depths in a phantom. A QA device that measures full 3D dose distributions at high spatiotemporal resolution would be highly beneficial for existing as well as emerging proton therapy techniques such as FLASH radiotherapy. Our objective is to demonstrate feasibility of 3D dose measurement for IMPT fields using a dedicated multi-layer strip ionization chamber (MLSIC) device. Approach. Our developed MLSIC comprises a total of 66 layers of strip ion chamber (IC) plates arranged, alternatively, in the x and y direction. The first two layers each has 128 channels in 2 mm spacing, and the following 64 layers each has 32/33 IC strips in 8 mm spacing which are interconnected every eight channels. A total of 768-channel IC signals are integrated and sampled at a speed of 6 kfps. The MLSIC has a total of 19.2 cm water equivalent thickness and is capable of measurement over a 25 × 25 cm2 field size. A reconstruction algorithm is developed to reconstruct 3D dose distribution for each spot at all depths by considering a double-Gaussian–Cauchy–Lorentz model. The 3D dose distribution of each beam is obtained by summing all spots. The performance of our MLSIC is evaluated for a clinical pencil beam scanning (PBS) plan. Main results. The dose distributions for each proton spot can be successfully reconstructed from the ionization current measurement of the strip ICs at different depths, which can be further summed up to a 3D dose distribution for the beam. 3D Gamma Index analysis indicates acceptable agreement between the measured and expected dose distributions from simulation, Zebra and MatriXX. Significance. The dedicated MLSIC is the first pseudo-3D QA device that can measure 3D dose distribution in PBS proton fields spot-by-spot.

Biological-equivalent-dose-based integrated optimization framework for fast-energy-switching Bragg peak FLASH-RT using single-beam-per-fraction.

When comparing the delivery of all beams per fraction (ABPF) to single beam per fraction (SBPF), it is observed that SBPF not only helps meet the FLASH dose threshold but also mitigates the uncertainty with beam switching in the FLASH effect. However, SBPF might lead to a higher biological equivalent dose in 2Gy (EQD2) for normal tissues. This study aims to develop an EQD2-based integrated optimization framework (EQD2-IOF), encompassing robust dose, delivery efficiency, and beam orientation optimization (BOO) for Bragg peak FLASH plans using the SBPF treatment schedule. The EQD2-IOF aims to enhance both dose sparing and the FLASH effect. A superconducting gantry was employed for fast energy switching within 27ms, while universal range shifters were utilized to improve beam current in the implementation of FLASH plans with five Bragg peak beams. To enhance dose delivery efficiency while maintaining plan quality, a simultaneous dose and spot map optimization (SDSMO) algorithm for single field optimization was incorporated into a Bayesian optimization-based auto-planning algorithm. Subsequently, a BOO algorithm based on Tabu search was developed to select beam angle combinations (BACs) for 10 lung cases. To simultaneously consider dose sparing and FLASH effect, a quantitative model based on dose-dependent dose modification factor (DMF) was used to calculate FLASH-enhanced dose distribution. The EQD2-IOF plan was compared to the plan optimized without SDSMO using BAC selected by a medical physicist (Manual plan) in the SBPF treatment schedule. Meanwhile, the mean EQD2 in the normal tissue was evaluated for the EQD2-IOF plan in both SBPF and ABPF treatment schedules. No significant difference was found in D2% and D98% of the target between EQD2-IOF plans and Manual Plans. When using a minimum DMF of 0.67 and a dose threshold of 4Gy, EQD2-IOF plans showed a significant reduction in FLASH-enhanced EQD2mean of the ipsilateral lung and normal tissue by 10.5% and 11.5%, respectively, compared to Manual plans. For normal tissues that received a dose greater than 70% of the prescription dose, using a minimum DMF of 0.7 for FLASH sparing compensated for the increase in EQD2mean resulting from replacing ABPF with SBPF schedules. The EQD2-IOF can automatically optimize SBPF FLASH-RT plans to achieve optimal sparing of normal tissues. With an energy switching time of 27ms, the loss of fractionate repairing using SBPF schedules in high-dose regions can be compensated for by the FLASH effect. However, when an energy switching time of 500ms is utilized, the SBPF schedule needs careful consideration, as the FLASH effect diminishes with longer irradiation time.

Establishing Updated Safety Standards for Independent 99mTc-MAA SPECT/CT Treatment Planning in Radioembolization

Significant improvements within radioembolization imaging and dosimetry permit the development of an accurate and personalized pretreatment plan using technetium 99m-labeled macroaggregated albumin (99mTc-MAA) and single-photon emission computed tomography (SPECT) combined with anatomical CT (SPECT/CT). Despite these potential advantages, the clinical transition to pretreatment protocols with SPECT/CT is hindered by their unknown safety constraints. This study aimed to address this issue by establishing novel dose limits for 99mTc-MAA SPECT/CT to enable quantitative pretreatment planning. Stratification criteria to determine images most viable for dosimetry analysis were created from a cohort of 85 patients. SPECT/CT, cone beam CT, and activity calculations derived from the local deposition method were used to create an accurate pretreatment protocol. Planar and SPECT/CT images were compared using linear regression and modified Bland-Altman analyses to convert accepted planar dose limits to SPECT/CT. To validate these new dose limits, activity calculations based on SPECT/CT were compared with those calculated with the body surface area and planar methods for three treatment plans. A total of 38 of 85 patients were deemed viable for dosimetry analysis. SPECT yielded greater lung shunt fractions (LSFs) than planar imaging when LSFs were <4.89%, whereas SPECT yielded lower LSFs than planar imaging when LSFs were >4.89%. Planar to SPECT/CT dose conversions were 0.76×, 0.70×, and 0.55× for the whole liver, normal liver, and lungs, respectively. Patients with SPECT LSFs ≤4.89% were safely treated with the direct application of planar lung dose limits. Activity calculations with the newly established SPECT/CT dose limits were greater than those of the body surface area method by a median range of 33.1% to 61.9% and were lower than planar-based activity calculations by a median range of 12.5% to 13.7% for the whole liver and by 29.4% to 32.2% for the normal liver. This study demonstrated a safe method for translating dose limits from 99mTc-MAA planar imaging to SPECT/CT. A robust pretreatment protocol was further developed guided by the current knowledge in the field. Established SPECT/CT dose limits safely treated 97.5% of patients and permitted the application of independent pretreatment planning with 99mTc-MAA SPECT/CT.

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.

The impact of the titanium cranial hardware in proton single-field uniform dose plans.

Neurosurgical cranial titanium mesh and screws are commonly encountered in postoperative radiation therapy. However, only a limited number of reports are available in the context of proton therapy, resulting in a lack of consensus among the proton centers regarding the protocol for handling the hardware. This study is to examine the impact of the hardware in proton plans. The results serve as evidence for proton centers to generate standard operating procedures to manage the hardware in proton treatment. Plans with different gantry angles and material overrides are generated on the CT images of a phantom made of the hardware. The dose distributions of the plans with and without material override, at different depths are compared. Films and ionization chambers are used to measure the plans and the measurements are compared to the treatment planning system (TPS) calculations by gamma analysis. There are some overdose and underdose regions downstream of the hardware. The overdose and underdose values are within a few percent of the prescribed dose when multiple fields with large hinge angles are used. The gamma analysis results show that the measurements agree with the TPS calculations within limits that are clinically relevant. The study has demonstrated the influence of the hardware on proton plans. Based on the result of this study, a standard operating procedure of managing the hardware has been implemented in our clinic.