Dosimetry: Was and Is an Absolute Requirement for Quality Radiation Research.

This review aims to trace the evolution of dosimetry, highlight its significance in the advancement of radiation research, and identify the current trends and methodologies in the field. Key historical milestones, starting with the first publications in the journal in 1954, will be synthesized before addressing contemporary practices in radiation medicine and radiobiological investigation. Finally, possibilities for future opportunities in dosimetry will be offered. The overarching goal is to emphasize the indispensability of accurate and reproducible dosimetry in enhancing the quality of radiation research and practical applications of ionizing radiation.

The effect of integrating knowledge-based planning with multicriteria optimization in treatment planning for prostate SBRT.

Knowledge-based planning (KBP) and multicriteria optimization (MCO) are two powerful tools to assist treatment planners in achieving optimal target coverage and organ-at-risk (OAR) sparing. The purpose of this work is to investigate if integrating MCO with conventional KBP can further improve treatment plan quality for prostate cancer stereotactic body radiation therapy (SBRT). A two-phase study was designed to investigate the impact of MCO and KBP in prostate SBRT treatment planning. The first phase involved the creation of a KBP model based on thirty clinical SBRT plans, generated by manual optimization (KBP_M). A ten-patient validation cohort was used to compare manual, MCO, and KBP_M optimization techniques. The next phase involved replanning the original model cohort with additional tradeoff optimization via MCO to create a second model, KBP_MCO. Plans were then generated using linear integration (KBP_M+MCO), non-linear integration (KBP_MCO), and a combination of integration methods (KBP_MCO+MCO). All plans were analyzed for planning target volume (PTV) coverage, OAR constraints, and plan quality metrics. Comparisons were generated to evaluate plan and model quality. Phase 1 highlighted the necessity of KBP and MCO in treatment planning, as both optimization methods improved plan quality metrics (Conformity and Heterogeneity Indices) and reduced mean rectal dose by 2 Gy, as compared to manual planning. Integrating MCO with KBP did not further improve plan quality, as little significance was seen over KBP or MCO alone. Principal component score (PCS) fitting showed KBP_MCO improved bladder and rectum estimated and modeled dose correlation by 5% and 22%, respectively; however, model improvements did not significantly impact plan quality. KBP and MCO have shown to reduce OAR dose while maintaining desired PTV coverage in this study. Further integration of KBP and MCO did not show marked improvements in treatment plan quality while requiring increased time in model generation and optimization time.

Characterization of Dosimetric Differences in Strut-Adjusted Volume Implant Treatment Plans Calculated With TG-43 Formalism and a Model-Based Dose Calculation Algorithm.

PURPOSE: To comprehensively characterize dosimetric differences between calculations with a commercial model-based dose calculation algorithm (MBDCA) and the TG-43 formalism in application to accelerated partial breast irradiation (APBI) with the strut-adjusted volume implant (SAVI) applicator. METHODS: Dose for 100 patients treated with the SAVI applicator was recalculated with an MBDCA for comparison to dose calculated via TG-43. For every pair of dose calculations, dose-volume histogram (DVH) metrics including V90%, V95%, V100%, V150%, and V200% for the PTV_EVAL were compared. Features were defined for each case including (1) applicator size, (2) ratio between PTV_EVAL contour and 1-cm rind surrounding SAVI applicator, (3) ratio between dwell time in central catheter and total dwell time, and (4) mean computed tomography (CT) number within the lumpectomy cavity. Wilcoxon rank sum tests were performed to test whether treatment plans could be stratified according to feature values into groups with statistically significant dosimetry differences between MBDCA and TG-43. RESULTS: For all DVH metrics, differences between TG-43 and MBDCA calculations were statistically significant (P < .05). Minimum (maximum) relative percent differences between the MBDCA and TG-43 for V90%, V95%, and V100% were -2.1% (0.1%), -3.1% (-0.1%), and -5.0% (-0.5%), respectively. The median relative percent difference in mean PTV_EVAL dose between the MBDCA and TG-43 was -3.9%, with minimum (maximum) difference of -6.5% (-1.8%). For V90%, V95%, and V100%, plan quality worsened beyond defined thresholds in 26, 23, and 31 cases with no instances of coverage improvement. Features 1, 2, and 4 were shown to be able to stratify treatment plans into groups with statistically significant differences in dosimetry metrics between MBDCA and TG-43. CONCLUSIONS: Investigated dose metrics for SAVI treatments were found to be systematically lower with MBDCA calculation in comparison to TG-43. Plans could be stratified according to several features by the magnitude of dosimetric differences between these calculations.

Dual-storage phosphor proton therapy dosimetry: Simultaneous quantification of dose and linear energy transfer.

PURPOSE: To investigate the feasibility of using the high Zeff storage phosphor material BaFBrI:Eu2+ in conjunction with the low Zeff storage phosphor material KCl:Eu2+ for simultaneous proton dose and linear energy transfer (LET) measurements by (a) measuring the fundamental optical and dosimetric properties of BaFBrI:Eu2+ , (b) evaluating its compatibility in being readout simultaneously with KCl:Eu2+ dosimeters, and (c) modeling and validating its LET dependence under elevated proton LET irradiation. METHODS: A commercial BaFBrI:Eu2+ storage phosphor detector (Model ST-VI, Fujifilm) was characterized with energy dispersive x-ray spectroscopy (EDS) analysis to obtain its elemental composition. The dosimeters were irradiated using both a Mevion S250 proton therapy unit (at the center of a spread-out Bragg peak, SOBP) and a Varian Clinac iX linear accelerator with the latter being a low LET irradiation. The photostimulated luminescence (PSL) emission spectra, excitation spectra, and luminescent lifetimes of the detector were measured after proton and photon irradiations. Dosimetric properties including dose linearity, dose rate dependence, radiation hardness, temporal, and readout stabilities were studied using a laboratory optical reader after proton irradiations. In addition, its proton energy dependence was analytically modeled and experimentally validated by irradiating the detectors at various depths within the SOBP (Range: 15.0 g/cm2 , Modulation: 10.0 g/cm2 ). RESULTS: The active detector composition for the high Zeff storage phosphor detector was found to be BaFBr0.85 I0.15 :Eu2+ . The BaFBr0.85 I0.15 :Eu2+ material's excitation and emission spectra were in agreement under proton and photon irradiations, with peaks of 586 ± 1 nm and 400 ± 1 nm, respectively, with a full width at half maximum (FWHM) of 119 ± 3 nm and 30 ± 2 nm, respectively. As dosimeter response under photon irradiation is generally believed to be free from LET effect, these results suggest LET independence of charge storage center types resulted from ionizing radiations. There is sufficient spectral overlaps with KCl:Eu2+ dosimeters allowing both dosimeters to be readout under equivalent readout conditions, that is, 594 nm stimulation and 420 nm detection wavelengths. Its PSL characteristic lifetime was found to be less than 5 microseconds which would make it suitable for fast 2D readout post irradiation. Its 420 nm emission band intensity was found to be linear up to 10 Gy absolute proton dose under the same irradiation conditions, dose rate independent, stable in time and under multiple readouts, and with high radiation hardness under cumulative proton dose histories up to 200 Gy as tested in this study. BaFBr0.85 I0.15 :Eu2+ showed significant proton energy-dependent dose under-response in regions of high LET which could be modeled by stopping power ratio calculations with an accuracy of 3% in low LET regions and a distance-to-agreement (DTA) of 1 mm in high LET regions (>5 keV/µm). CONCLUSION: We have proven the feasibility of dual-storage phosphor proton dosimetry for simultaneous proton dose and LET measurements. BaFBr0.85 I0.15 :Eu2+ has shown equally excellent dosimetry performance as its low Zeff complement KCl:Eu2+ with distinctive LET dependence merely as a result of its higher Zeff . These promising results pave the way for future studies involving simultaneous proton dose and LET measurements using this novel approach.

Quantitative proton radiation therapy dosimetry using the storage phosphor europium-doped potassium chloride.

PURPOSE: To (a) characterize the fundamental optical and dosimetric properties of the storage phosphor europium-doped potassium chloride for quantitative proton dosimetry, and (b) investigate if its dose radiation response can be described by an analytic radiation transport model. METHODS: Cylindrical KCl:Eu2+ dosimeters with dimensions of 6 mm diameter and 1 mm thickness were fabricated in-house. The dosimeters were irradiated using both a Mevion S250 passive scattering proton therapy system and a Varian Clinac iX linear accelerator. Photostimulated luminescence (PSL) emission spectra, excitation spectra, and luminescence lifetimes were measured for both proton and photon irradiations. Dosimetric properties including radiation hardness, dose linearity, signal stabilization, dose rate sensitivity, and energy dependence were studied using a laboratory optical reader after irradiations. The dosimeters were modeled using physical quantities including mass stopping powers in the storage phosphor and water for a given proton beam, and mass energy absorption coefficients and massing stopping powers in detector and water for a given photon beam. RESULTS: KCl:Eu2+ exhibited optical emission and stimulation peaks at 421 and 560 nm, respectively, for both proton and photon irradiations, enabling postirradiation readouts using a visible light source while detecting the PSL using a photomultiplier tube. KCl:Eu2+ showed a linear response from 0 to 8 Gy absorbed dose-to-water, a large dynamic range up to 60 Gy, dose-rate independence measured from 83 to 500 MU/min, and a PSL lifetime of <5 ms that is sufficiently short for supporting rapid scanning in a two-dimensional geometry. KCl:Eu2+ was highly reusable with only a slight signal decrease of ~3% at accumulated doses over 100 Gy, which could be managed by a periodic recalibration. The detected PSL signal strength of the dosimeter in the proton field had been calculated accurately to a maximum discrepancy of 2% using known physical quantities along with its prior signal strength as measured in a photon field at the same dose-to-water. This discrepancy might be attributed to an under-response due to linear energy transfer (LET) effect. However, comparisons of depth-dose measurements in a spread-out Bragg peak (SOBP) field with a parallel-plate ionization chamber showed no clear evidence of LET effects. Furthermore, range measurements agreed with ionization chamber measurements to within 1 mm. CONCLUSIONS: KCl:Eu2+ showed linear response over a large dynamic range for proton irradiations and reliably reproduced SOBP measurements as measured by ionization chambers. Its relatively low atomic number of 18 and near LET independence make it suited for quantitative proton dosimetry. In addition, its high radiation hardness means that it can be reused numerous times. Any potential measurement artifacts encountered in complex irradiation conditions should be able to be corrected for using known physical quantities.

Automated and robust beam data validation of a preconfigured ring gantry linear accelerator using a 1D tank with synchronized beam delivery and couch motions.

PURPOSE: To develop an efficient and automated methodology for beam data validation for a preconfigured ring gantry linear accelerator using scripting and a one-dimensional (1D) tank with automated couch motions. MATERIALS AND METHODS: Using an application programming interface, a program was developed to allow the user to choose a set of beam data to validate with measurement. Once selected the program generates a set of instructions for radiation delivery with synchronized couch motions for the linear accelerator in the form of an extensible markup language (XML) file to be delivered on the ring gantry linear accelerator. The user then delivers these beams while measuring with the 1D tank and data logging electrometer. The program also automatically calculates this set of beams on the measurement geometry within the treatment planning system (TPS) and extracts the corresponding calculated dosimetric data for comparison to measurement. Once completed the program then returns a comparison of the measurement to the predicted result from the TPS to the user and prints a report. In this work lateral, longitudinal, and diagonal profiles were taken for fields sizes of 6 × 6, 8 × 8, 10 × 10, 20 × 20, and 28 × 28 cm2 at depths of 1.3, 5, 10, 20, and 30 cm. Depth dose profiles were taken for all field sizes. RESULTS: Using this methodology, the TPS was validated to agree with measurement. All compared points yielded a gamma value less than 1 for a 1.5%/1.5 mm criteria (100% passing rate). Off axis profiles had >98.5% of data points producing a gamma value <1 with a 1%/1 mm criteria. All depth profiles produced 100% of data points with a gamma value <1 with a 1%/1 mm criteria. All data points measured were within 1.5% or 2 mm distance to agreement. CONCLUSIONS: This methodology allows for an increase in automation in the beam data validation process. Leveraging the application program interface allows the user to use a single system to create the measurement files, predict the result, and then compare to actual measurement increasing efficiency and reducing the chance for user input errors.

Dose uncertainty and resolution of polymer gel dosimetry using an MRI guided radiation therapy system's onboard 0.35 T scanner.

Magnetic Resonance Imaging (MRI) scanners are widely used for 3D gel dosimeters readout. However, limited access to MRI scanners is a challenge in MRI-based gel dosimetry. Recent clinical implementation of MRI-guided radiation therapy machines provides potential opportunities for onboard gel dosimetry using its MRI subsystem. The objective of this study was to investigate the feasibility of gel dosimetry using ViewRay's onboard 0.35 T MRI scanner. A BANG® polymer gel dosimeter was irradiated by three beams of 3 × 3 cm2 field size. The T2 relaxation rate (R2) of the irradiated gel was measured using a Philips 1.5 T Ingenia MRI and a ViewRay 0.35 T onboard MRI and spin-echo pulse sequences. The number of signal averages (NSA) was set to 16 for the ViewRay acquisitions and one for the Philips 1.5 T MRI to achieve similar signal-to-noise ratios. The in-plane spatial resolution was 1.5 × 1.5 mm2 and the slice thickness was 5 mm. The relative dose uncertainty was obtained using R2 versus dose curves to compare the performance of dosimetry using the two different MRIs and field strengths. The dose uncertainty decreased from 12% at 2 Gy to 3.5% at 7.5 Gy at 1.5 T. The dose uncertainty decreased from 13% at 2 Gy to 4% at 7.5 Gy with NSA = 16 and 3 × 3 mm2 pixel size, and from 10.5% at 2 Gy to 3.2% at 7.5 Gy with NSA = 16 and denoised R2 maps (1.5 × 1.5 mm2 pixel size) at 0.35 T. The mean of dose resolution was 0.4 Gy at 1.5 T while the mean of dose resolution was 0.8 Gy and 0.64 Gy at 0.35 T by downsampling and denoising the R2 map, respectively. Therefore, comparable dose uncertainty was achievable using the ViewRay's onboard 0.35 T and Philips 1.5 T MRI scanners. 3D gel dosimetry using onboard low-field MRI scanner provides ViewRay users a 3D high resolution dosimetry option besides film and ionization chamber.

Development and Validation of a Bayesian Network Method to Detect External Beam Radiation Therapy Physician Order Errors.

PURPOSE: To investigate a Bayesian network (BN)-based method to detect errors in external beam radiation therapy physician orders. METHODS AND MATERIALS: A total of 4431 external beam radiation therapy orders from 2008 to 2017 at the authors' institution were obtained from clinical treatment management systems and divided into 3 groups: single prescription, concurrent boost, and sequential boost. Multiple BNs were developed for each group to detect errors in new orders using joint posterior probabilities of the order parameters, given disease information. Each BN was trained with a group of orders using a Bayesian learning algorithm. A procedure was developed to select the optimal BN for each treatment site in each group and to determine site-specific parameters and error detection thresholds. Potential clinical errors, created both manually and automatically, were applied to test error detection performance. RESULTS: The average true-positive rate (TPR) and false-positive rate (FPR) of error detection were 95.72% and 1.99%, respectively, for the single-prescription cohort with 9 treatment sites. For the concurrent-boost cohort, the TPR and FPR were 92.94% and 14.53%, respectively. For the sequential-boost cohort, the TPR and FPR were 100% and 9.48%, respectively, for the prescribed dose values and 100% and 4.34%, respectively, for the remaining order parameters. For the patient simulation and imaging parameters for 9 treatment sites, the TPR and FPR were 100% and 4.96%, respectively. CONCLUSIONS: The probabilistic BN method was able to perform physician order error detection at a higher accuracy than previously reported in a variety of complex prescription instances, thus warranting further development in incorporating BNs into clinical error detection tools to assist manual physician order checks.

A novel MRI segmentation method using CNN-based correction network for MRI-guided adaptive radiotherapy.

PURPOSE: The purpose of this study was to expedite the contouring process for MRI-guided adaptive radiotherapy (MR-IGART), a convolutional neural network (CNN) deep-learning (DL) model is proposed to accurately segment the liver, kidneys, stomach, bowel and duodenum in 3D MR images. METHODS: Images and structure contours for 120 patients were collected retrospectively. Treatment sites included pancreas, liver, stomach, adrenal gland, and prostate. The proposed DL model contains a voxel-wise label prediction CNN and a correction network which consists of two sub-networks. The prediction CNN and sub-networks in the correction network each includes a dense block which consists of twelve densely connected convolutional layers. The correction network was designed to improve the voxel-wise labeling accuracy of a CNN by learning and enforcing implicit anatomical constraints in the segmentation process. Its sub-networks learn to fix the erroneous classification of its previous network by taking as input both the original images and the softmax probability maps generated from its previous sub-network. The parameters of each sub-network were trained independently using piecewise training. The model was trained on 100 datasets, validated on 10 datasets and tested on the remaining 10 datasets. Dice coefficient, Hausdorff distance (HD) were calculated to evaluate the segmentation accuracy. RESULTS: The proposed DL model was able to segment the organs with good accuracy. The correction network outperformed the conditional random field (CRF), a most comparable method that is usually applied as a post-processing step. For the 10 testing patients, the average Dice coefficients were 95.3 ± 0.73, 93.1 ± 2.22, 85.0 ± 3.75, 86.6 ± 2.69, and 65.5 ± 8.90 for liver, kidneys, stomach, bowel, and duodenum, respectively. The mean Hausdorff Distance (HD) were 5.41 ± 2.34, 6.23 ± 4.59, 6.88 ± 4.89, 5.90 ± 4.05, and 7.99 ± 6.84 mm, respectively. Manual contouring, as to correct the automatic segmentation results, was four times as fast as manual contouring from scratch. CONCLUSION: The proposed method can automatically segment the liver, kidneys, stomach, bowel, and duodenum in 3D MR images with good accuracy. It is useful to expedite the manual contouring for MR-IGART.

Equivalency of beam scan data collection using a 1D tank and automated couch movements to traditional 3D tank measurements.

This work shows the feasibility of collecting linear accelerator beam data using just a 1-D water tank and automated couch movements with the goal to maximize the cost effectiveness in resource-limited clinical settings. Two commissioning datasets were acquired: (a) using a standard of practice 3D water tank scanning system (3DS) and (b) using a novel technique to translate a commercial TG-51 complaint 1D water tank via automated couch movements (1DS). The Extensible Markup Language (XML) was used to dynamically move the linear accelerator couch position (and thus the 1D tank) during radiation delivery for the acquisition of inline, crossline, and diagonal profiles. Both the 1DS and 3DS datasets were used to generate beam models (BM1 DS and BM3 DS ) in a commercial treatment planning system (TPS). 98.7% of 1DS measured points had a gamma value (2%/2 mm) < 1 when compared with the 3DS. Static jaw defined field and dynamic MLC field dose distribution comparisons for the TPS beam models BM1 DS and BM3 DS had 3D gamma values (2%/2 mm) < 1 for all 24,900,000 data points tested and >99.5% pass rate with gamma value (1%/1 mm) < 1. In conclusion, automated couch motions and a 1D scanning tank were used to collect commissioning beam data with accuracy comparable to traditionally acquired data using a 3D scanning system. TPS beam models generated directly from 1DS measured data were clinically equivalent to a model derived from 3DS data.

First clinical implementation of real-time, real anatomy tracking and radiation beam control.

PURPOSE: We describe the acceptance testing, commissioning, periodic quality assurance, and workflow procedures developed for the first clinically implemented magnetic resonance imaging-guided radiation therapy (MR-IGRT) system for real-time tracking and beam control. METHODS: The system utilizes real-time cine imaging capabilities at 4 frames per second for real-time tracking and beam control. Testing of the system was performed using an in-house developed motion platform and a commercially available motion phantom. Anatomical tracking is performed by first identifying a target (a region of interest that is either tissue to be treated or a critical structure) and generating a contour around it. A boundary contour is also created to identify tracking margins. The tracking algorithm deforms the anatomical contour (target or a normal organ) on every subsequent cine frame and compares it to the static boundary contour. If the anatomy of interest moves outside the boundary, the radiation delivery is halted until the tracked anatomy returns to treatment portal. The following were performed to validate and clinically implement the system: (a) spatial integrity evaluation; (b) tracking accuracy; (c) latency; (d) relative point dose and spatial dosimetry; (e) development of clinical workflow for gating; and (f) independent verification by an outside credentialing service. RESULTS: The spatial integrity of the MR system was found to be within 2 mm over a 45-cm diameter field-of-view. The tracking accuracy for geometric targets was within 1.2 mm. The average system latency was measured to be within 394 ms. The dosimetric accuracy using ionization chambers was within 1.3% ± 1.7%, and the dosimetric spatial accuracy was within 2 mm. The phantom irradiation for the outside credentialing service had satisfactory results, as well. CONCLUSIONS: The first clinical MR-IGRT system was validated for real-time tracking and gating capabilities and shown to be reliable and accurate. Patient workflow methods were developed for efficient treatment. Periodic quality assurance tests can be efficiently performed with commercially available equipment to ensure accurate system performance.

An efficient model to guide prospective T2-weighted 4D magnetic resonance imaging acquisition.

PURPOSE: To establish a mathematical model to guide prospective T2-weighted four-dimensional magnetic resonance imaging (4DMRI) acquisition and to propose an efficient solution to expedite prospective T2-weighted 4DMRI acquisition. METHODS: Prospective T2-weighted 4DMRI acquisition was characterized by a mathematical model with 4DMRI acquisition time as the objective function and completeness of the image set, acquisition timing, image contrast, and image artifacts as constraints. Given the irregular nature of human respiration, an efficient solution based on the greedy strategy (ESGS) was proposed. The efficiency of the ESGS method was validated using healthy human subjects. Comparisons were made with the previous 4DMRI method incorporating the prefixed-order respiratory state splitting (PO-RSS) technique. RESULTS: 4DMRI image sets acquired using the ESGS and PO-RSS methods had similar image quality. The average time to acquire a 4DMRI image set covering 60 slices at 10 respiratory states was reduced by 30%, from 13.1 min using the PO-RSS method to 9.0 min using the ESGS method. It was demonstrated that high-quality T2-weighted 4DMRI could be obtained within a reasonable amount of time and all slices within each of the three-dimensional volumes were indeed acquired at the same respiratory state. CONCLUSIONS: The ESGS method substantially reduces the acquisition time for T2-weighted 4DMRI, making it ready for clinical evaluation to obtain abdominal tumor motion for radiotherapy treatment planning.

An adaptive motion regularization technique to support sliding motion in deformable image registration.

PURPOSE: Isotropic smoothing has been conventionally used to regularize deformation vector fields (DVFs) in deformable image registration (DIR). However, the isotropic smoothing method enforces global smoothness and therefore cannot accurately model the complex tissue deformation, such as sliding motion at organ boundaries. To accurately model and estimate sliding tissue motion, an adaptive direction-dependent DVF regularization technique was developed in this study. METHODS: A DVF is computed and updated iteratively by minimizing the intensity differences between the images. In each iteration, the DVF was smoothed using an adaptive direction-dependent filter which enforces different motion propagation mechanisms along the primary normal and tangential directions of soft tissue local structures. A Gaussian isotropic filter was used along the normal direction while a bilateral filter was used along the tangential direction. To support large sliding motion, an automatic method was developed to delineate sliding surfaces, such as the chest wall and abdominal wall, where large organ sliding motion occurs. Parameters of the DVF regularization were adjusted adaptively based on a distance map to the sliding surfaces. The proposed method was tested on 14 4D-CT datasets at End-Inhalation (EI) and End-Exhalation (EE) phases of a respiratory cycle (10 public lung datasets, 3 upper abdomen datasets and 1 digital phantom dataset). TRE results of the 10 lung datasets were compared to results from six other existing DIR methods. For the three upper abdomen patient datasets, DIR accuracy was evaluated using manually defined landmarks across the lung and the abdomen. For the digital phantom dataset, DIR accuracy was evaluated using the ground truth displacement of a total 40,000 points that were evenly distributed across the phantom. RESULTS: The results showed that the sliding motion was preserved near the surface of chest wall and abdominal wall. The average target registration error (TRE) was reduced by 35.1% using the proposed method in comparison with five other methods on the 10 lung datasets. The sum of squared difference (SSD) after registration using the proposed method was 4.4% and 11.4% smaller than the SSDs obtained using isotropic smoothing and bilateral smoothing respectively. On the digital phantom, the average TRE was reduced by 59.6% near the surface of liver and by 53.7% near the surface of spleen using the proposed method. Contour propagation and Jacobian determinant analysis of DVF suggested an overall improved accuracy using the proposed method. CONCLUSION: An adaptive direction-dependent DVF regularization method has been developed to model the sliding tissue motion of the thoracic and abdominal organs. The overall motion estimation accuracy has been improved especially near the chest wall and abdominal wall where large organ sliding motion occurs.

Adaptive anatomical preservation optimal denoising for radiation therapy daily MRI.

Low-field magnetic resonance imaging (MRI) has recently been integrated with radiation therapy systems to provide image guidance for daily cancer radiation treatments. The main benefit of the low-field strength is minimal electron return effects. The main disadvantage of low-field strength is increased image noise compared to diagnostic MRIs conducted at 1.5 T or higher. The increased image noise affects both the discernibility of soft tissues and the accuracy of further image processing tasks for both clinical and research applications, such as tumor tracking, feature analysis, image segmentation, and image registration. An innovative method, adaptive anatomical preservation optimal denoising (AAPOD), was developed for optimal image denoising, i.e., to maximally reduce noise while preserving the tissue boundaries. AAPOD employs a series of adaptive nonlocal mean (ANLM) denoising trials with increasing denoising filter strength (i.e., the block similarity filtering parameter in the ANLM algorithm), and then detects the tissue boundary losses on the differences of sequentially denoised images using a zero-crossing edge detection method. The optimal denoising filter strength per voxel is determined by identifying the denoising filter strength value at which boundary losses start to appear around the voxel. The final denoising result is generated by applying the ANLM denoising method with the optimal per-voxel denoising filter strengths. The experimental results demonstrated that AAPOD was capable of reducing noise adaptively and optimally while avoiding tissue boundary losses. AAPOD is useful for improving the quality of MRIs with low-contrast-to-noise ratios and could be applied to other medical imaging modalities, e.g., computed tomography.

A Method to Recognize Anatomical Site and Image Acquisition View in X-ray Images.

A method was developed to recognize anatomical site and image acquisition view automatically in 2D X-ray images that are used in image-guided radiation therapy. The purpose is to enable site and view dependent automation and optimization in the image processing tasks including 2D-2D image registration, 2D image contrast enhancement, and independent treatment site confirmation. The X-ray images for 180 patients of six disease sites (the brain, head-neck, breast, lung, abdomen, and pelvis) were included in this study with 30 patients each site and two images of orthogonal views each patient. A hierarchical multiclass recognition model was developed to recognize general site first and then specific site. Each node of the hierarchical model recognized the images using a feature extraction step based on principal component analysis followed by a binary classification step based on support vector machine. Given two images in known orthogonal views, the site recognition model achieved a 99% average F1 score across the six sites. If the views were unknown in the images, the average F1 score was 97%. If only one image was taken either with or without view information, the average F1 score was 94%. The accuracy of the site-specific view recognition models was 100%.

Variable step size methods for solving simultaneous algebraic reconstruction technique (SART)-type cbct reconstructions.

Compared to analytical reconstruction by Feldkamp-Davis-Kress (FDK), simultaneous algebraic reconstruction technique (SART) offers a higher degree of flexibility in input measurements and often produces superior quality images. Due to the iterative nature of the algorithm, however, SART requires intense computations which have prevented its use in clinical practice. In this paper, we developed a fast-converging SART-type algorithm and showed its clinical feasibility in CBCT reconstructions. Inspired by the quasi-orthogonal nature of the x-ray projections in CBCT, we implement a simple yet much faster algorithm by computing Barzilai and Borwein step size at each iteration. We applied this variable step-size (VS)-SART algorithm to numerical and physical phantoms as well as cancer patients for reconstruction. By connecting the SART algebraic problem to the statistical weighted least squares problem, we enhanced the reconstruction speed significantly (i.e., less number of iterations). We further accelerated the reconstruction speed of algorithms by using the parallel computing power of GPU.

Development of a fast Monte Carlo dose calculation system for online adaptive radiation therapy quality assurance.

Online adaptive radiation therapy (ART) based on real-time magnetic resonance imaging represents a paradigm-changing treatment scheme. However, conventional quality assurance (QA) methods based on phantom measurements are not feasible with the patient on the treatment couch. The purpose of this work is to develop a fast Monte Carlo system for validating online re-optimized tri-60Co IMRT adaptive plans with both high accuracy and speed. The Monte Carlo system is based on dose planning method (DPM) code with further simplification of electron transport and consideration of external magnetic fields. A vendor-provided head model was incorporated into the code. Both GPU acceleration and variance reduction were implemented. Additionally, to facilitate real-time decision support, a C++ GUI was developed for visualizing 3D dose distributions and performing various analyses in an online adaptive setting. A thoroughly validated Monte Carlo code (gPENELOPE) was used to benchmark the new system, named GPU-accelerated DPM with variance reduction (gDPMvr). The comparison using 15 clinical IMRT plans demonstrated that gDPMvr typically runs 43 times faster with only 0.5% loss in accuracy. Moreover, gDPMvr reached 1% local dose uncertainty within 2.3 min on average, and thus is well-suited for ART QA.

Technical Note: Direct measurement of continuous TMR data with a 1D tank and automated couch movements.

PURPOSE: Real-time dynamic control of the linear accelerator, couch, and imaging parameters during radiation delivery was investigated as a novel technique for acquiring tissue maximum ratio (TMR) data. METHODS: TrueBeam Developer Mode (Varian Medical Systems, Palo Alto, CA, USA) was used to control the linear accelerator using the Extensible Markup Language (XML). A single XML file was used to dynamically manipulate the machine, couch, and imaging parameters during radiation delivery. A TG-51 compliant 1D water tank was placed on the treatment couch, and used to position a detector at isocenter at a depth of 24.5 cm. A depth scan was performed towards the water surface. Via XML control, the treatment couch vertical position was simultaneously lowered at the same rate, maintaining the detector position at isocenter, allowing for the collection of TMR data. To ensure the detector remained at isocenter during the delivery, the in-room camera was used to monitor the detector. Continuous kV fluoroscopic images during 10 test runs further confirmed this result. TMR data at multiple Source to Detector Distances (SDD) and scan speeds were acquired to investigate their impact on the TMR data. Percentage depth dose (PDD) scans (for conversion to TMR) along with traditional discrete TMR data were acquired as a standard for comparison. RESULTS: More than 99.8% of the measured points had a gamma value (1%/1 mm) < 1 when compared with discrete or PDD converted TMR data. Fluoroscopic images showed that the concurrent couch and tank movements resulted in SDD errors < 1 mm. TMRs acquired at SDDs of 99, 100, and 101 cm showed differences less than 0.004. CONCLUSION: TrueBeam Developer Mode was used to collect continuous TMR data with the same accuracy as traditionally collected discrete data, but yielded higher sampled resolution and reduced acquisition time. This novel method does not require the modification of any equipment and does not use a 3D tank or reservoir.

Three-Dimensional Dosimetric Validation of a Magnetic Resonance Guided Intensity Modulated Radiation Therapy System.

PURPOSE: To validate the dosimetric accuracy of a commercially available magnetic resonance guided intensity modulated radiation therapy (MRgIMRT) system using a hybrid approach: 3-dimensional (3D) measurements and Monte Carlo calculations. METHODS AND MATERIALS: We used PRESAGE radiochromic plastic dosimeters with remote optical computed tomography readout to perform 3D high-resolution measurements, following a novel remote dosimetry protocol. We followed the intensity modulated radiation therapy commissioning recommendations of American Association of Physicists in Medicine Task Group 119, adapted to incorporate 3D data. Preliminary tests ("AP" and "3D-Bands") were delivered to 9.5-cm usable diameter cylindrical PRESAGE dosimeters to validate the treatment planning system (TPS) for nonmodulated deliveries; assess the sensitivity, uniformity, and rotational symmetry of the PRESAGE dosimeters; and test the robustness of the remote dosimetry protocol. Following this, 4 clinical MRgIMRT plans ("MultiTarget," "Prostate," "Head/Neck," and "C-Shape") were measured using 13-cm usable diameter PRESAGE dosimeters. For all plans, 3D-γ (3% or 3 mm global, 10% threshold) passing rates were calculated and 3D-γ maps were examined. Point doses were measured with an IBA-CC01 ionization chamber for validation of absolute dose. Finally, by use of an in-house-developed, GPU-accelerated Monte Carlo algorithm (gPENELOPE), we independently calculated dose for all 6 Task Group 119 plans and compared against the TPS. RESULTS: For PRESAGE measurements, 3D-γ analysis yielded passing rates of 98.7%, 99.2%, 98.5%, 98.0%, 99.2%, and 90.7% for AP, 3D-Bands, MultiTarget, Prostate, Head/Neck, and C-Shape, respectively. Ion chamber measurements were within an average of 0.5% (±1.1%) from the TPS dose. Monte Carlo calculations demonstrated good agreement with the TPS, with a mean 3D-γ passing rate of 98.5% ± 1.9% using a stricter 2%/2-mm criterion. CONCLUSIONS: We have validated the dosimetric accuracy of a commercial MRgIMRT system using high-resolution 3D techniques. We have demonstrated for the first time that hybrid 3D remote dosimetry is a comprehensive and feasible approach to commissioning MRgIMRT. This may provide better sensitivity in error detection compared with standard 2-dimensional measurements and could be used when implementing complex new magnetic resonance guided radiation therapy technologies.