Statistical image-based material decomposition for triple-energy computed tomography using total variation regularization.

BACKGROUND: Triple-energy computed tomography (TECT) can obtain x-ray attenuation measurements at three energy spectra, thereby allowing identification of different material compositions with same or very similar attenuation coefficients. This ability is known as material decomposition, which can decompose TECT images into different basis material image. However, the basis material image would be severely degraded when material decomposition is directly performed on the noisy TECT measurements using a matrix inversion method. OBJECTIVE: To achieve high quality basis material image, we present a statistical image-based material decomposition method for TECT, which uses the penalized weighted least-squares (PWLS) criteria with total variation (TV) regularization (PWLS-TV). METHODS: The weighted least-squares term involves the noise statistical properties of the material decomposition process, and the TV regularization penalizes differences between local neighboring pixels in a decomposed image, thereby contributing to improving the quality of the basis material image. Subsequently, an alternating optimization method is used to minimize the objective function. RESULTS: The performance of PWLS-TV is quantitatively evaluated using digital and mouse thorax phantoms. The experimental results show that PWLS-TV material decomposition method can greatly improve the quality of decomposed basis material image compared to the quality of images obtained using the competing methods in terms of suppressing noise and preserving edge and fine structure details. CONCLUSIONS: The PWLS-TV method can simultaneously perform noise reduction and material decomposition in one iterative step, and it results in a considerable improvement of basis material image quality.

Gold Nanoparticle Transport in the Injured Kidneys with Elevated Renal Function Biomarkers.

Renal function biomarkers such as serum blood urea nitrogen (BUN) and creatinine (Cr) serve as key indicators for guiding clinical decisions before administering kidney-excreted small-molecule agents. With engineered nanoparticles increasingly designed to be renally clearable to expedite their clinical translation, understanding the relationship between renal function biomarkers and nanoparticle transport in diseased kidneys becomes crucial to their biosafety in future clinical applications. In this study, renal-clearable gold nanoparticles (AuNPs) are used as X-ray contrast agents to noninvasively track their transport and retention in cisplatin-injured kidneys with varying BUN and Cr levels. The findings reveal that AuNP transport is significantly slowed in the medulla of severely injured kidneys, with BUN and Cr levels elevated to 10 times normal. In mildly injured kidneys, where BUN and Cr levels only four to five times higher than normal, AuNP transport and retention are not predictable by BUN and Cr levels but correlate strongly with the degree of tubular injury due to the formation of gold-protein casts in the Henle's loop of the medulla. These results underscore the need for caution when employing renal-clearable nanomedicines in compromised kidneys and highlight the potential of renal-clearable AuNPs as X-ray probes for assessing kidney injuries noninvasively.

Real-time marker-less tumor tracking with TOF PET:in silicofeasibility study.

Purpose.Although positron emission tomography (PET) can provide a functional image of static tumors for RT guidance, it's conventionally very challenging for PET to track a moving tumor in real-time with a multiple frame/s sampling rate. In this study, we developed a novel method to enable PET based three-dimension (3D) real-time marker-less tumor tracking (RMTT) and demonstrated its feasibility with a simulation study.Methods.For each line-of-response (LOR) acquired, its positron-electron annihilation position is calculated based on the time difference between the two gamma interactions detected by the TOF PET detectors. The accumulation of these annihilation positions from data acquired within a single sampling frame forms a coarsely measured 3D distribution of positron-emitter radiotracer uptakes of the lung tumor and other organs and tissues (background). With clinically relevant tumor size and sufficient differential radiotracer uptake concentrations between the tumor and background, the high-uptake tumor can be differentiated from the surrounding low-uptake background in the measured distribution of radiotracer uptakes. With a volume-of-interest (VOI) that closely encloses the tumor, the count-weighted centroid of the annihilation positions within the VOI can be calculated as the tumor position. All these data processes can be conducted online. The feasibility of the new method was investigated with a simulated cardiac-torso digital phantom and stationary dual-panel TOF PET detectors to track a 28 mm diameter lung tumor with a 4:1 tumor-to-background18FDG activity concentration ratio.Results.The initial study shows TOF PET based RMTT can achieve <2.0 mm tumor tracking accuracy with 5 frame s-1sampling rate under the simulated conditions. In comparison, using reconstructed PET images to track a similar size tumor would require >30 s acquisition time to achieve the same tracking accuracy.Conclusion.With the demonstrated feasibility, the new method may enable TOF PET based RMTT for practical RT applications.

Improving small animal cone beam CT resolution by mitigating x-ray focal spot induced blurring via deconvolution.

Objective.Modern preclinical small animal radiation platforms utilize cone beam computerized tomography (CBCT) for image guidance and experiment planning purposes. The resolution of CBCT images is of particular importance for visualizing fine animal anatomical structures. One major cause of spatial resolution reduction is the finite size of the x-ray focal spot. In this work, we proposed a simple method to measure x-ray focal spot intensity map and a CBCT image domain deblurring model to mitigate the effect of focal spot-induced image blurring.Approach.We measured a projection image of a tungsten ball bearing using the flat panel detector of the CBCT platform. We built a forward blurring model of the projection image and derived the spot intensity map by deconvolving the measured projection image. Based on the measured spot intensity map, we derived a CBCT image domain blurring model for images reconstructed by the filtered backprojection algorithm. Based on this model, we computed image domain blurring kernel and improved the CBCT image resolution by deconvolving the CBCT image.Main results.We successfully measured the x-ray focal spot intensity map. The spot size characterized by full width at half maximum was ∼0.75 × 0.55 mm2at 40 kVp. We computed image domain convolution kernels caused by the x-ray focal spot. A simulation study on noiseless projections was performed to evaluate the spatial resolution improvement exclusively by the focal spot kernel, and the modulation transfer function (MTF) at 50% was increased from 1.40 to 1.65 mm-1for in-plane images and 1.05-1.32 mm-1for cross-plane images. Experimental studies on a CT insert phantom and a plastinated mouse phantom demonstrated improved spatial resolution after image domain deconvolution, as indicated by visually improved resolution of fine structures. MTF at 50% was improved from 1.00 to 1.12 mm-1for in-plane direction and from 0.72 to 0.84 mm-1for cross-plane direction.Significance.The proposed method to mitigate blurring caused by finite x-ray spot size and improve CBCT image resolution is simple and effective.

Small animal photon counting cone-beam CT on a preclinical radiation research platform to improve radiation dose calculation accuracy.

Objective.Cone beam CT (CBCT) in preclinical small animal irradiation platforms provides essential information for image guidance and radiation dose calculation for experiment planning. This project developed a photon-counting detector (PCD)-based multi(3)-energy (ME-)CBCT on a small animal irradiator to improve the accuracy of material differentiation and hence dose calculation, and compared to conventional flat panel detector (FPD)-based CBCT.Approach.We constructed a mechanical structure to mount a PCD to an existing preclinical irradiator platform and built a data acquisition pipeline to acquire x-ray projection data with a 100 kVp x-ray beam using three different energy thresholds in a single gantry rotation. We implemented an energy threshold optimization scheme to determine optimal thresholds to balance signal-to-noise ratios (SNRs) among energy channels. Pixel-based detector response calibration was performed to remove ring artifacts in reconstructed CBCT images. Feldkamp-Davis-Kress method was employed to reconstruct CBCT images and a total-variance regularization-based optimization model was used to decompose CBCT images into bone and water material images. We compared dose calculation results using PCD-based ME-CBCT with that of FPD-based CBCT.Main results.The optimal nominal energy thresholds were determined as 26, 56, and 90 keV, under which SNRs in a selected region-of-interest in the water region were 6.11, 5.91 and 5.93 in the three energy channels, respectively. Compared with dose calculation results using FPD-based CBCT, using PCD-based ME-CBCT reduced the mean relative error from 49.5% to 16.4% in bone regions and from 7.5% to 6.9% in soft tissue regions.Significance.PCD-based ME-CBCT is beneficial in improving radiation dose calculation accuracy in experiment planning of preclinical small animal irradiation researches.

Machine characterization and central axis depth dose data of a superficial x-ray radiotherapy unit.

Objectives. The purpose of this study is to present data from the clinical commissioning of an Xstrahl 150 x-ray unit used for superficial radiotherapy,Methods. Commissioning tasks included vendor acceptance tests, timer reproducibility, linearity and end-effect measurements, half-value layer (HVL) measurements, inverse square law verification, head-leakage measurements, and beam output calibration. In addition, percent depth dose (PDD) curves were determined for different combinations of filter/kV settings and applicators. Automated PDD water phantom scans were performed utilizing four contemporary detectors: a microDiamond detector, a microSilicon detector, an EDGE detector, and a PinPoint ionization chamber. The measured PDD data were compared to the published values in BJR Supplement 25,Results. The x-ray unit's mechanical, safety, and radiation characteristics were within vendor-stated specifications. Across sixty commissioned x-ray beams, the PDDs determined in water using solid state detectors were in excellent agreement with the BJR 25 data. For the lower (<100 kVp) and medium-energy (≥100 kVp) superficial beams the average agreement was within [-3.6,+0.4]% and [-3.7,+1.4]% range, respectively. For the high-energy superficial (low-energy orthovoltage) x-rays at 150 kVp, the average difference for the largest 20 × 20 cm2collimator was (-0.7 ± 1.0)%,Conclusions. This study presents machine characterization data collected for clinical use of a superficial x-ray unit. Special focus was placed on utilizing contemporary detectors and techniques for the relative PDD measurements using a motorized water phantom. The results in this study confirm that the aggregate values published in the BJR 25 report still serve as a valid benchmark when comparing data from site-specific measurements, or the reference data for clinical utilization without such measurements,Advances in knowledge. This paper presents comprehensive data from the acceptance and commissioning of a modern kilovoltage superficial x-ray radiotherapy machine. Comparisons between the PDD data measured in this study using different detectors and BJR 25 data are highlighted.

High resolution dual detector volume-of-interest cone beam breast CT--Demonstration with a bench top system.

PURPOSE: In this study, we used a small field high resolution detector in conjunction with a full field flat panel detector to implement and investigate the dual detector volume-of-interest (VOI) cone beam breast computed tomography (CBCT) technique on a bench-top system. The potential of using this technique to image small calcifications without increasing the overall dose to the breast was demonstrated. Significant reduction of scatter components in the high resolution projection image data of the VOI was also shown. METHODS: With the regular flat panel based CBCT technique, exposures were made at 80 kVp to generate an air kerma of 6 mGys at the isocenter. With the dual detector VOI CBCT technique, a high resolution small field CMOS detector was used to scan a cylindrical VOI (2.5 cm in diameter and height, 4.5 cm off-center) with collimated x-rays at four times of regular exposure level. A flat panel detector was used for full field scan with low x-ray exposures at half of the regular exposure level. The low exposure full field image data were used to fill in the truncated space in the VOI scan data and generate a complete projection image set. The Feldkamp-Davis-Kress (FDK) filtered backprojection algorithm was used to reconstruct high resolution images for the VOI. Two scanning techniques, one breast centered and the other VOI centered, were implemented and investigated. Paraffin cylinders with embedded thin aluminum (Al) wires were imaged and used in conjunction with optically stimulated luminescence (OSL) dose measurements to demonstrate the ability of this technique to image small calcifications without increasing the mean glandular dose (MGD). RESULTS: Using exposures that produce an air kerma of 6 mGys at the isocenter, the regular CBCT technique was able to resolve the cross-sections of Al wires as thin as 254 µm in diameter in the phantom. For the specific VOI studied, by increasing the exposure level by a factor of 4 for the VOI scan and reducing the exposure level by a factor of 2 for the full filed scan, the dual-detector CBCT technique was able to resolve the cross-sections of Al wires as thin as 152 µm in diameter. The CNR evaluated for the entire Al wire cross-section was found to be improved from 5.5 in regular CBCT to 14.4 and 16.8 with the breast centered and VOI centered scanning techniques, respectively. Even inside VOI center, the VOI scan resulted in significant dose saving with the dose reduced by a factor of 1.6 at the VOI center. Dose saving outside the VOI was substantial with the dose reduced by a factor of 7.3 and 7.8 at the breast center for the breast centered and VOI centered scans, respectively, when compared to full field scan at the same exposure level. The differences between the two dual detector techniques in terms of dose saving and scatter reduction were small with VOI scan at 4× exposure level and full field scan at 0.5 × exposure level. The MGDs were only 94% of that from the regular CBCT scan. CONCLUSIONS: For the specific VOI studied, the dual detector VOI CBCT technique has the potential to provide high quality images inside the VOI with MGD similar to or even lower than that of full field breast CBCT. It was also found that our results were compromised by the use of inadequate detectors for the VOI scan. An appropriately selected detector would better optimize the image quality improvement that can be achieved with the VOI CBCT technique.

Radiation doses in cone-beam breast computed tomography: a Monte Carlo simulation study.

PURPOSE: In this article, we describe a method to estimate the spatial dose variation, average dose and mean glandular dose (MGD) for a real breast using Monte Carlo simulation based on cone beam breast computed tomography (CBBCT) images. We present and discuss the dose estimation results for 19 mastectomy breast specimens, 4 homogeneous breast models, 6 ellipsoidal phantoms, and 6 cylindrical phantoms. METHODS: To validate the Monte Carlo method for dose estimation in CBBCT, we compared the Monte Carlo dose estimates with the thermoluminescent dosimeter measurements at various radial positions in two polycarbonate cylinders (11- and 15-cm in diameter). Cone-beam computed tomography (CBCT) images of 19 mastectomy breast specimens, obtained with a bench-top experimental scanner, were segmented and used to construct 19 structured breast models. Monte Carlo simulation of CBBCT with these models was performed and used to estimate the point doses, average doses, and mean glandular doses for unit open air exposure at the iso-center. Mass based glandularity values were computed and used to investigate their effects on the average doses as well as the mean glandular doses. Average doses for 4 homogeneous breast models were estimated and compared to those of the corresponding structured breast models to investigate the effect of tissue structures. Average doses for ellipsoidal and cylindrical digital phantoms of identical diameter and height were also estimated for various glandularity values and compared with those for the structured breast models. RESULTS: The absorbed dose maps for structured breast models show that doses in the glandular tissue were higher than those in the nearby adipose tissue. Estimated average doses for the homogeneous breast models were almost identical to those for the structured breast models (p=1). Normalized average doses estimated for the ellipsoidal phantoms were similar to those for the structured breast models (root mean square (rms) percentage difference = 1.7%; p = 0.01), whereas those for the cylindrical phantoms were significantly lower (rms percentage difference = 7.7%; p < 0.01). Normalized MGDs were found to decrease with increasing glandularity. CONCLUSIONS: Our results indicate that it is sufficient to use homogeneous breast models derived from CBCT generated structured breast models to estimate the average dose. This investigation also shows that ellipsoidal digital phantoms of similar dimensions (diameter and height) and glandularity to actual breasts may be used to represent a real breast to estimate the average breast dose with Monte Carlo simulation. We have also successfully demonstrated the use of structured breast models to estimate the true MGDs and shown that the normalized MGDs decreased with the glandularity as previously reported by other researchers for CBBCT or mammography.

Design and experimental validation of a unilateral magnet for MRI-guided small animal radiation experiments.

Small animal radiation experiments are of paramount importance for the advancement of human radiation therapy. These experiments use a dedicated radiation platform to deliver radiation to small animals, such as mice and rats, similar to how human radiation therapy is performed. By acquiring images immediately before radiation delivery to guide positioning of the animals, image guidance plays a critical role to ensure accuracy of the experiments. Recently, MR-based image guidance has been enabled in human radiation therapy. This paper proposes a new concept using a unilateral magnet-based MRI scanner to realize image guidance for small animal radiation experiments. We reported our design, optimization, construction, and characterization of the magnet. The magnet was designed using eight 2-inch neodymium magnet cubes arranged in a modified Halbach ring configuration. The ring has an opening to allow for animal positioning. We considered a spherical region of interest (ROI) located outside of the ring's plane to allow radiation delivery to the ROI without obstruction of the magnet. An optimization problem was formulated and solved to determine the positions and orientations of the magnet cubes to generate a magnetic field with desired properties in the ROI. The optimization improved the average magnetic flux density from 55 mT to 72 mT and reduced variation from 1.2 T/m to 1.0 T/m. We constructed the magnet using 3D-printed templates to hold the neodymium magnet cubes with the optimized positions and orientations. We measured the spatial distribution of the magnetic flux density. The measurement results and computed results agreed with an average difference of 0.35% through the ROI.

Improving dose calculation accuracy in preclinical radiation experiments using multi-energy element resolved cone-beam CT.

Objective.Cone-beam CT (CBCT) in modern pre-clinical small-animal radiation research platforms provides volumetric images for image guidance and experiment planning purposes. In this work, we implemented multi-energy element-resolved (MEER) CBCT using three scans with different kVps on a SmART platform (Precision x-ray Inc.) to determine images of relative electron density (rED) and elemental composition (EC) that are needed for Monte Carlo-based radiation dose calculation.Approach.We performed comprehensive calibration tasks to achieve sufficient accuracy for this quantitative imaging purpose. For geometry calibration, we scanned a ball bearing phantom and used an analytical method together with an optimization approach to derive gantry angle specific geometry parameters. Intensity calibration and correction included the corrections for detector lag, glare, and beam hardening. The corrected CBCT projection images acquired at 30, 40, and 60 kVp in multiple scans were used to reconstruct CBCT images using the Feldkamp-Davis-Kress reconstruction algorithm. After that, an optimization problem was solved to determine images of rED and EC. We demonstrated the effectiveness of our CBCT calibration steps by showing improvements in image quality and successful material decomposition in cases with a small animal CT calibration phantom and a plastinated mouse phantom.Main results.It was found that artifacts induced by geometry inaccuracy, detector lag, glare, and beam hardening were visually reduced. CT number mean errors were reduced from 19% to 5%. In the CT calibration phantom case, median errors in H, O, and Ca fractions for all the inserts were below 1%, 2%, and 4% respectively, and median error in rED was less than 5%. Compared to the standard approach deriving material type and rED via CT number conversion, our approach improved Monte Carlo simulation-based dose calculation accuracy in bone regions. Mean dose error was reduced from 47.5% to 10.9%.Significance.The MEER-CBCT implemented on an existing CBCT system of a small animal irradiation platform achieved accurate material decomposition and significantly improved Monte Carlo dose calculation accuracy.

Experimental and numerical studies on kV scattered x-ray imaging for real-time image guidance in radiation therapy.

Motion management is a critical component of image guided radiotherapy for lung cancer. We previously proposed a scheme using kV scattered x-ray photons for marker-less real-time image guidance in lung cancer radiotherapy. This study reports our recent progress using the photon counting detection technique to demonstrate potential feasibility of this method and using Monte Carlo (MC) simulations and ray-tracing calculations to characterize the performance. In our scheme, a thin slice of x-ray beam was directed to the target and we measured the outgoing scattered photons using a photon counting detector with a parallel-hole collimator to establish the correspondence between detector pixels and scatter positions. Image corrections of geometry, beam attenuation and scattering angle were performed to convert the raw image to the actual image of Compton attenuation coefficient. We set up a MC simulation system using an in-house developed GPU-based MC package modeling the image formation process. We also performed ray-tracing calculations to investigate the impacts of imaging system geometry on resulting image resolution. The experiment demonstrated feasibility of using a photon counting detector to measure scattered x-ray photons and generate the proposed scattered x-ray image. After correction, x-ray scattering image intensity and Compton scattering attenuation coefficient were linearly related, with R 2 greater than 0.9. Contrast to noise ratios of different objects were improved and the values in experimental results and MC simulation results agreed with each other. Ray-tracing calculations revealed the dependence of image resolution on imaging geometry. The image resolution increases with reduced source to object distance and increased collimator height. The study demonstrated potential feasibility of using scattered x-ray imaging as a real-time image guidance method in radiation therapy.

Novel On-line PET Imaging for Intra-Beam Range Verification and Delivery Optimization: A Simulation Feasibility Study.

On-line PET image-based method uses an initial particle beam to measure the particle beam range (BR) within the same fraction so that any measured range-shift with respect to the predicted BR can be compensated before the rest therapeutic beam deliveries. However, the method requires to use a low-dose initial beam to minimize the risk of beam overshooting, which leads to low image count and inaccurate BR measurement. In this in-silico study, we evaluated the feasibility of a new on-line PET imaging method that measures BR at the mid-plane of a target volume with part of the high-dose therapy beams to verify BR and guide adaptive treatment re-planning. Simulations included various processes of proton beam radiations to a tumor inside a human brain phantom, positron and PET image generation at the mid-plane with initial beams, activity range measurement, and range-shift compensated beam delivery. The results demonstrated that the new method, under the simulated conditions, can achieve ~1.1 mm mid-plane BR measurement accuracy and closely match the delivered range-shift compensated dose distribution with the planned one. Overall, it is promising that this new method may significantly improve particle therapy accuracy.

Dose rate determination for preclinical total body irradiation.

The accuracy of delivered radiation dose and the reproducibility of employed radiotherapy methods are key factors for preclinical radiobiology applications and research studies. In this work, ionization chamber (IC) measurements and Monte Carlo (MC) simulations were used to accurately determine the dose rate for total body irradiation (TBI), a classic radiobiologic and immunologic experimental method. Several phantom configurations, including large solid water slab, small water box and rodentomorphic mouse and rat phantoms were simulated and measured for TBI setup utilizing a preclinical irradiator XRad320. The irradiator calibration and the phantom measurements were performed using an ADCL calibrated IC N31010 following the AAPM TG-61 protocol. The MC simulations were carried out using Geant4/GATE to compute absorbed dose distributions for all phantom configurations. All simulated and measured geometries had favorable agreement. On average, the relative dose rate difference was 2.3%. However, the study indicated large dose rate deviations, if calibration conditions are assumed for a given experimental setup as commonly done for a quick determination of irradiation times utilizing lookup tables and hand calculations. In a TBI setting, the reference calibration geometry at an extended source-to-surface distance and a large reference field size is likely to overestimate true photon scatter. Consequently, the measured and hand calculated dose rates, for TBI geometries in this study, had large discrepancies: 16% for a large solid water slab, 27% for a small water box, and 31%, 36%, and 30% for mouse phantom, rat phantom, and mouse phantom in a pie cage, respectively. Small changes in TBI experimental setup could result in large dose rate variations. MC simulations and the corresponding measurements specific to a designed experimental setup are vital for accurate preclinical dosimetry and reproducibility of radiobiological findings. This study supports the well-recognized need for physics consultation for all radiobiological investigations.

Dual resolution cone beam breast CT: a feasibility study.

PURPOSE: In this study, the authors investigated the feasibility of a dual resolution volume-of-interest (VOI) cone beam breast CT technique and compared two implementation approaches in terms of dose saving and scatter reduction. METHODS: With this technique, a lead VOI mask with an opening is inserted between the x-ray source and the breast to deliver x-ray exposure to the VOI while blocking x rays outside the VOI. A CCD detector is used to collect the high resolution projection data of the VOI. Low resolution cone beam CT (CBCT) images of the entire breast, acquired with a flat panel (FP) detector, were used to calculate the projection data outside the VOI with the ray-tracing reprojection method. The Feldkamp-Davis-Kress filtered backprojection algorithm was used to reconstruct the dual resolution 3D images. Breast phantoms with 180 microm and smaller microcalcifications (MCs) were imaged with both FP and FP-CCD dual resolution CBCT systems, respectively. Two approaches of implementing the dual resolution technique, breast-centered approach and VOI-centered approach, were investigated and evaluated for dose saving and scatter reduction with Monte Carlo simulation using a GEANT4 package. RESULTS: The results showed that the breast-centered approach saved more breast absorbed dose than did VOI-centered approach with similar scatter reduction. The MCs in fatty breast phantom, which were invisible with FP CBCT scan, became visible with the FP-CCD dual resolution CBCT scan. CONCLUSIONS: These results indicate potential improvement of the image quality inside the VOI with reduced breast dose both inside and outside the VOI.

gPET: a GPU-based, accurate and efficient Monte Carlo simulation tool for PET.

Monte Carlo (MC) simulation method plays an essential role in the refinement and development of positron emission tomography (PET) systems. However, most existing MC simulation packages suffer from long execution time for practical PET simulations. To fully address this issue, we developed and validated gPET, a graphics processing unit (GPU)-based MC simulation tool for PET. gPET was built on the NVidia CUDA platform. The simulation process was modularized into three functional parts and carried out by the GPU parallel threads: (1) source management, including positron decay, transport and annihilation; (2) gamma transport inside the phantom; and (3) signal detection and processing inside the detector. A hybrid of voxelized (for patient phantoms) and parametrized (for detectors) geometries were employed to sufficiently support particle navigations. Multiple inputs and outputs were available. Hence, a user can flexibly examine different aspects of a PET simulation. We evaluated the performance of gPET in three test cases with benchmark work from GATE8.0, in terms of the testing of the functional modules, the physics models used for gamma transport inside the detector, and the geometric configuration of an irregularly shaped PET detector. Both accuracy and efficiency were quantified. In all test cases, the differences between gPET and GATE for the coincidences with respect to the energy and crystal index distributions are below 3.18% and 2.54%, respectively. The speedup factor is 500 for gPET on a single Titan Xp GPU (1.58 GHz) over GATE8.0 on a single core of Intel i7-6850K CPU (3.6 GHz) for all test cases. In summary, gPET is an accurate and efficient MC simulation tool for PET.

Technical Note: Deriving ventilation imaging from 4DCT by deep convolutional neural network.

PURPOSE: Ventilation images can be derived from four-dimensional computed tomography (4DCT) by analyzing the change in HU values and deformable vector fields between different respiration phases of computed tomography (CT). As deformable image registration (DIR) is involved, accuracy of 4DCT-derived ventilation image is sensitive to the choice of DIR algorithms. To overcome the uncertainty associated with DIR, we develop a method based on deep convolutional neural network (CNN) to derive ventilation images directly from the 4DCT without explicit image registration. METHODS: A total of 82 sets of 4DCT and ventilation images from patients with lung cancer were used in this study. In the proposed CNN architecture, the CT two-channel input data consist of CT at the end of exhale and the end of inhale phases. The first convolutional layer has 32 different kernels of size 5 × 5 × 5, followed by another eight convolutional layers each of which is equipped with an activation layer (ReLU). The loss function is the mean-squared-error (MSE) to measure the intensity difference between the predicted and reference ventilation images. RESULTS: The predicted images were comparable to the label images of the test data. The similarity index, correlation coefficient, and Gamma index passing rate averaged over the tenfold cross validation were 0.880 ± 0.035, 0.874 ± 0.024, and 0.806 ± 0.014, respectively. CONCLUSIONS: The results demonstrate that deep CNN can generate ventilation imaging from 4DCT without explicit deformable image registration, reducing the associated uncertainty.

Quantitative 4D-PET reconstruction for small animal using SMEIR-reconstructed 4D-CBCT.

Respiratory motions in small animals PET cause image degradation during reconstruction. This work aims to develop a motion compensated 4D-PET reconstruction method using accurate motion corrections and attenuation corrections from 4D-CBCT images reconstructed using a simultaneous motion estimation and image reconstruction (SMEIR) method. Projections of 4D-CBCT were calculated using a ray-tracing method on a digital 4D rat phantom, and list-mode data of 4D-PET with matched respiratory phases were simulated using the GATE Monte Carlo package. The respiratory rate was set at 1.0 second per cycle with 10 phases of 30 projection images each. 4D-CBCT images were reconstructed using the SMEIR method and motion information and linear attenuation from 4D-CBCT were subsequently used for motion compensated 4D-PET reconstruction and attenuation corrections. We quantitatively evaluate the reconstructed 4D-PET using the errors of tumor volume and standard uptake values of tumors with different sizes. The tumor motion was successfully reconstructed and showed good agreement with the original phantom. The proposed method reduced tumor volume errors and standard uptake value errors. For tumor diameters of 3.0, 4.5, and 6.0 mm, the tumor volume errors are 32.5%, 29.2% and 19.4% respectively with motion compensation and 45.1%, 37.5% and 20.2% respectively without compensation.

Mid-range probing-towards range-guided particle therapy.

Particle therapy can achieve excellent dose localization but is sensitive to range uncertainty. Therefore, online in vivo range verification before treatment is critical for treatment safety and quality assurance. We introduce a novel range-probing technique that uses mid-range treatment spots selected from the treatment plan as probing beams to be delivered before other treatment spots in pencil beam scanning. The probing spot signal can be acquired by an in-beam positron emission tomography (PET) scanner, and the reconstructed spot positions are compared with pre-calculated positions to measure the range shift. Mid-range probing ensures that the Bragg peaks stay inside the tumor even with significant range variation from the plan. Single-layered spots enable easier spot detection than multi-layered spots without cross-layered spot smearing. With therapeutic dose, the probing beam offers higher positron activities and range detectability than the low-dose imaging beam by up to two orders of magnitude, without exposing patients to extra radiation. Higher positron activities allow sufficient signal statistics in shorter acquisition time, therefore reducing metabolic washout of positron emitters. Thus, range shifts from the plan can be measured easily. We also describe two online range-compensated plan modification methods. We apply correction, if the range shift is above a certain tolerance. We studied feasibility using simulated particle treatment plans with online anatomical changes. For illustration, we demonstrate range shift measurement using simulated probing dose. The proposed range probing and correction effectively handled range shifts in the simulated cases. Both range-compensated adaptation and optimization accounted for online changes so that the delivered dose matched the planned dose. With a dedicated online in-beam PET scanner and phantom and clinical studies, which are currently being developed, this novel strategy may open up a range-guided particle therapy1 paradigm.

4D cone-beam computed tomography (CBCT) using a moving blocker for simultaneous radiation dose reduction and scatter correction.

Four-dimensional (4D) x-ray cone-beam computed tomography (CBCT) is important for a precise radiation therapy for lung cancer. Due to the repeated use and 4D acquisition over a course of radiotherapy, the radiation dose becomes a concern. Meanwhile, the scatter contamination in CBCT deteriorates image quality for treatment tasks. In this work, we propose the use of a moving blocker (MB) during the 4D CBCT acquisition ('4D MB') and to combine motion-compensated reconstruction to address these two issues simultaneously. In 4D MB CBCT, the moving blocker reduces the x-ray flux passing through the patient and collects the scatter information in the blocked region at the same time. The scatter signal is estimated from the blocked region for correction. Even though the number of projection views and projection data in each view are not complete for conventional reconstruction, 4D reconstruction with a total-variation (TV) constraint and a motion-compensated temporal constraint can utilize both spatial gradient sparsity and temporal correlations among different phases to overcome the missing data problem. The feasibility simulation studies using the 4D NCAT phantom showed that 4D MB with motion-compensated reconstruction with 1/3 imaging dose reduction could produce satisfactory images and achieve 37% improvement on structural similarity (SSIM) index and 55% improvement on root mean square error (RMSE), compared to 4D reconstruction at the regular imaging dose without scatter correction. For the same 4D MB data, 4D reconstruction outperformed 3D TV reconstruction by 28% on SSIM and 34% on RMSE. A study of synthetic patient data also demonstrated the potential of 4D MB to reduce the radiation dose by 1/3 without compromising the image quality. This work paves the way for more comprehensive studies to investigate the dose reduction limit offered by this novel 4D MB method using physical phantom experiments and real patient data based on clinical relevant metrics.

Iterative reconstruction for photon-counting CT using prior image constrained total generalized variation.

In this paper, we present an iterative reconstruction for photon-counting CT using prior image constrained total generalized variation (PICTGV). This work aims to exploit structural correlation in the energy domain to reduce image noise in photon-counting CT with narrow energy bins. This is motived by the fact that the similarity between high-quality full-spectrum image and target image is an important prior knowledge for photon-counting CT reconstruction. The PICTGV method is implemented using a splitting-based fast iterative shrinkage-threshold algorithm (FISTA). Evaluations conducted with simulated and real photon-counting CT data demonstrate that PICTGV method outperforms the existing prior image constrained compressed sensing (PICCS) method in terms of noise reduction, artifact suppression and resolution preservation. In the simulated head data study, the average relative root mean squared error is reduced from 2.3% in PICCS method to 1.2% in PICTGV method, and the average universal quality index increases from 0.67 in PICCS method to 0.76 in PICTGV method. The results show that the present PICTGV method improves the performance of the PICCS method for photon-counting CT reconstruction with narrow energy bins.