Systematic Review on Learning-based Spectral CT.

Spectral computed tomography (CT) has recently emerged as an advanced version of medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two main forms: dual-energy computed tomography (DECT) and photon-counting computed tomography (PCCT), which offer image improvement, material decomposition, and feature quantification relative to conventional CT. However, the inherent challenges of spectral CT, evidenced by data and image artifacts, remain a bottleneck for clinical applications. To address these problems, machine learning techniques have been widely applied to spectral CT. In this review, we present the state-of-the-art data-driven techniques for spectral CT.

Reduction of cone-beam CT artifacts in a robotic CBCT device using saddle trajectories with integrated infrared tracking.

BACKGROUND: Cone beam computed tomography (CBCT) is widely used in many medical fields. However, conventional CBCT circular scans suffer from cone beam (CB) artifacts that limit the quality and reliability of the reconstructed images due to incomplete data. PURPOSE: Saddle trajectories in theory might be able to improve the CBCT image quality by providing a larger region with complete data. Therefore, we investigated the feasibility and performance of saddle trajectory CBCT scans and compared them to circular trajectory scans. METHODS: We performed circular and saddle trajectory scans using a novel robotic CBCT scanner (Mobile ImagingRing (IRm); medPhoton, Salzburg, Austria). For the saddle trajectory, the gantry executed yaw motion up to ± 10 ∘ $\pm 10^{\circ }$ using motorized wheels driving on the floor. An infrared (IR) tracking device with reflective markers was used for online geometric calibration correction (mainly floor unevenness). All images were reconstructed using penalized least-squares minimization with the conjugate gradient algorithm from RTK with 0.5 × 0.5 × 0.5 mm 3 $0.5 \times 0.5\times 0.5 \text{ mm}^3$ voxel size. A disk phantom and an Alderson phantom were scanned to assess the image quality. Results were correlated with the local incompleteness value represented by tan ( ψ ) $\tan (\psi)$ , which was calculated at each voxel as a function of the source trajectory and the voxel's 3D coordinates. We assessed the magnitude of CB artifacts using the full width half maximum (FWHM) of each disk profile in the axial center of the reconstructed images. Spatial resolution was also quantified by the modulation transfer function at 10% (MTF10). RESULTS: When using the saddle trajectory, the region without CB artifacts was increased from 43 to 190 mm in the SI direction compared to the circular trajectory. This region coincided with low values for tan ( ψ ) $\tan (\psi)$ . When tan ( ψ ) $\tan (\psi)$ was larger than 0.02, we found there was a linear relationship between the FWHM and tan ( ψ ) $\tan (\psi)$ . For the saddle, IR tracking allowed the increase of MTF10 from 0.37 to 0.98 lp/mm. CONCLUSIONS: We achieved saddle trajectory CBCT scans with a novel CBCT system combined with IR tracking. The results show that the saddle trajectory provides a larger region with reliable reconstruction compared to the circular trajectory. The proposed method can be used to evaluate other non-circular trajectories.

Systematic Review on Learning-based Spectral CT.

Spectral computed tomography (CT) has recently emerged as an advanced version of medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two main forms: dual-energy computed tomography (DECT) and photon-counting computed tomography (PCCT), which offer image improvement, material decomposition, and feature quantification relative to conventional CT. However, the inherent challenges of spectral CT, evidenced by data and image artifacts, remain a bottleneck for clinical applications. To address these problems, machine learning techniques have been widely applied to spectral CT. In this review, we present the state-of-the-art data-driven techniques for spectral CT.

Image quality improvement of a one-step spectral CT reconstruction on a prototype photon-counting scanner.

Objective. X-ray spectral computed tomography (CT) allows for material decomposition (MD). This study compared a one-step material decomposition MD algorithm with a two-step reconstruction MD algorithm using acquisitions of a prototype CT scanner with a photon-counting detector (PCD).Approach. MD and CT reconstruction may be done in two successive steps, i.e. decompose the data in material sinograms which are then reconstructed in material CT images, or jointly in a one-step algorithm. The one-step algorithm reconstructed material CT images by maximizing their Poisson log-likelihood in the projection domain with a spatial regularization in the image domain. The two-step algorithm maximized first the Poisson log-likelihood without regularization to decompose the data in material sinograms. These sinograms were then reconstructed into material CT images by least squares minimization, with the same spatial regularization as the one step algorithm. A phantom simulating the CT angiography clinical task was scanned and the data used to measure noise and spatial resolution properties. Low dose carotid CT angiographies of 4 patients were also reconstructed with both algorithms and analyzed by a radiologist. The image quality and diagnostic clinical task were evaluated with a clinical score.Main results. The phantom data processing demonstrated that the one-step algorithm had a better spatial resolution at the same noise level or a decreased noise value at matching spatial resolution. Regularization parameters leading to a fair comparison were selected for the patient data reconstruction. On the patient images, the one-step images received higher scores compared to the two-step algorithm for image quality and diagnostic.Significance. Both phantom and patient data demonstrated how a one-step algorithm improves spectral CT image quality over the implemented two-step algorithm but requires a longer computation time. At a low radiation dose, the one-step algorithm presented good to excellent clinical scores for all the spectral CT images.

Extension of the cone-beam CT field-of-view using two complementary short scans.

BACKGROUND: Robotic C-arm cone-beam computed tomography (CBCT) scanners provide fast in-room imaging in radiotherapy. Their mobility extends beyond performing a gantry rotation, but they might encounter obstructions to their motion which limit the gantry angle range. The axial field-of-view (FOV) of a reconstructed CBCT image depends on the acquisition geometry. When imaging a large anatomical location, such as the thorax, abdomen, or pelvis, a centered cone beam might be insufficient to acquire untruncated projection images. Some CBCT scanners can laterally displace their detector and collimate the beam to increase the FOV, but the gantry must then perform a 360° rotation to provide complete data for reconstruction. PURPOSE: To extend the FOV of a CBCT image with a single short scan (gantry angle range of 180 ∘ + $180^{\circ}+$ fan angle) using two complementary short scans. METHODS: We defined an acquisition protocol using two short scans during which the source follows the same trajectory and where the detector has equal and opposite tilt and/or offset between the two scans, which we refer to as complementary scans. We created virtual acquisitions using a Monte Carlo simulator on a digital anthropomorphic phantom and on a computed tomography (CT) scan of a patient abdomen. For our proposed method, each simulation produced two complementary sets of projections, which were weighted for redundancies and used to reconstruct one CBCT image. We compared the resulting images to the ground truth phantoms and simulations of conventional scans. RESULTS: Reconstruction artifacts were slightly more prominent in the complementary scans w.r.t. a complete scan with untruncated projections but matched those in a single short scan without truncation. When analyzing reconstructed scans from simulated projections with scatter and corrected with prior CT information, we found a global agreement between complementary and conventional scan approaches. CONCLUSIONS: When dealing with a limited range of motion of the gantry of a CBCT scanner, two complementary short scans are a technically valid alternative to a full 360° scan with equal FOV. This approach enables FOV extension without collisions or hardware upgrades.

Image reconstruction from truncated fan-beam projections along a circular trajectory using the virtual fan-beam method.

Objective.In this paper, we investigate how the virtual fan-beam (VFB) method can be used to perform mathematically correct 2D reconstruction in a region-of-interest (ROI), using truncated fan-beam projections acquired on a circular scan, for truncation that only occurs on one side of the object.Approach.We start by choosing a virtual fan-beam trajectory and specifying how to obtain the corresponding virtual projections. Then, three VFB formulas are obtained by applying known super-short-scan (SSS) formulas to this virtual trajectory. Two of them perform the backprojection in a virtual parallel geometry and the third in the virtual fan-beam geometry. Next, we develop two VFB formulas that perform the backprojection step in the fan-beam acquisition geometry.Main results.We present five VFB reconstruction formulas for this truncation setting. To our knowledge, the two VFB formulas performing the backprojection in the fan-beam acquisition geometry are new. Moreover, the five VFB formulas presented here obtain accurate reconstruction in a larger ROI than what has been previously reported in the literature in the same setting. A complete mathematical derivation of these five VFB formulas is given, and their implementation is described step by step. Numerical simulations, using the Forbild head and thorax phantoms, demonstrate the efficacy of these formulas. A spatial resolution analysis and a variance study indicate minor differences between these five VFB formulas.Significance.This work shows that many different VFB formulas can be applied to perform mathematically correct 2D reconstruction in a ROI, in case of truncated fan-beam projections acquired on a circular scan. Moreover, the two new VFB formulas, with backprojection in the acquisition geometry, may open the path for an extension of the VFB method to 3D reconstruction from transversely truncated cone-beam projection acquired on a circular scan.

Equal parallel and cone-beam projections: a curious property of D-symmetric object functions.

In tomographic image reconstruction, the object density function is the unknown quantity whose projections are measured by the scanner. In the three-dimensional case, we define the D-reflection of such a density function as the object obtained by a particular weighted reflection about the planez=D, and a D-symmetric function as one whose D-reflection is equal to itself. D-symmetric object functions have the curious property that their parallel projection onto the detector planez=Dis equal to their cone-beam projection onto the same detector with x-ray source location at the origin. Much more remarkable is the additional fact that for any fixed D-symmetric object,everyoblique parallel projection onto this same detector plane equals the cone-beam projection for a corresponding source location. The mathematical proof is straight forward but not particularly enlightening, and we also provide here an alternative physical demonstration that explains the various weighting terms in the context of classical tomosynthesis. Furthermore, we clarify the distinction between the new formulation presented here, and the original formulation of Edholm and co-workers who obtained similar properties but for a pair of objects whose divergent and parallel projections matched, but with no D-symmetry. We do not claim any immediate imaging application or useful physics from these notions, but we briefly comment on consequences for methods that apply data consistency conditions in image reconstruction.

The INFN proton computed tomography system for relative stopping power measurements: calibration and verification.

Objective. This paper describes the procedure to calibrate the three-dimensional (3D) proton stopping power relative to water (SPR) maps measured by the proton computed tomography (pCT) apparatus of the Istituto Nazionale di Fisica Nucleare (INFN, Italy). Measurements performed on water phantoms are used to validate the method. The calibration allowed for achieving measurement accuracy and reproducibility to levels below 1%.Approach. The INFN pCT system is made of a silicon tracker for proton trajectory determination followed by a YAG:Ce calorimeter for energy measurement. To perform the calibration, the apparatus has been exposed to protons of energies ranging from 83 to 210 MeV. Using the tracker, a position-dependent calibration has been implemented to keep the energy response uniform across the calorimeter. Moreover, correction algorithms have been developed to reconstruct the proton energy when this is shared in more than one crystal and to consider the energy loss in the non-uniform apparatus material. To verify the calibration and its reproducibility, water phantoms have been imaged with the pCT system during two data-taking sessions.Main results. The energy resolution of the pCT calorimeter resulted to beσEE≅0.9%at 196.5 MeV. The average values of the water SPR in fiducial volumes of the control phantoms have been calculated to be 0.995±0.002. The image non-uniformities were below 1%. No appreciable variation of the SPR and uniformity values between the two data-taking sessions could be identified.Significance. This work demonstrates the accuracy and reproducibility of the calibration of the INFN pCT system at a level below 1%. Moreover, the uniformity of the energy response keeps the image artifacts at a low level even in the presence of calorimeter segmentation and tracker material non-uniformities. The implemented calibration technique allows the INFN-pCT system to face applications where the precision of the SPR 3D maps is of paramount importance.

Characterization of the INFN proton CT scanner for cross-calibration of x-ray CT.

Objective. The goal of this study was to assess the imaging performances of the pCT system developed in the framework of INFN-funded (Italian National Institute of Nuclear Physics) research projects. The spatial resolution, noise power spectrum (NPS) and RSP accuracy has been investigated, as a preliminary step to implement a new cross-calibration method for x-ray CT (xCT).Approach. The INFN pCT apparatus, made of four planes of silicon micro-strip detectors and a YAG:Ce scintillating calorimeter, reconstructs 3D RSP maps by a filtered-back projection algorithm. The imaging performances (i.e. spatial resolution, NPS and RSP accuracy) of the pCT system were assessed on a custom-made phantom, made of plastic materials with different densities ((0.66, 2.18) g cm-3). For comparison, the same phantom was acquired with a clinical xCT system.Main results. The spatial resolution analysis revealed the nonlinearity of the imaging system, showing different imaging responses in air or water phantom background. Applying the Hann filter in the pCT reconstruction, it was possible to investigate the imaging potential of the system. Matching the spatial resolution value of the xCT (0.54 lp mm-1) and acquiring both with the same dose level (11.6 mGy), the pCT appeared to be less noisy than xCT, with an RSP standard deviation of 0.0063. Concerning the RSP accuracy, the measured mean absolute percentage errors were (0.23+-0.09)% in air and (0.21+-0.07)% in water.Significance. The obtained performances confirm that the INFN pCT system provides a very accurate RSP estimation, appearing to be a feasible clinical tool for verification and correction of xCT calibration in proton treatment planning.

Cone-Beam Pair-Wise Data Consistency Conditions in Helical CT.

Data consistency conditions (DCC) are mathematical equations characterizing the redundancy in X-ray projections. They have been used to correct inconsistent projections before computed tomography (CT) reconstruction. This article investigates DCC for a helical acquisition with a cylindrical detector, the geometry of most diagnostic CT scanners. The acquired projections are analyzed pair-by-pair. The intersection of each plane containing the two source positions with the corresponding cone-beams defines two fan-beams for which a DCC can be computed. Instead of rebinning the two fan-beam projections to a conventional detector, we directly derive the DCC in detector coordinates. If the line defined by two source positions intersects the field-of-view (FOV), the DCC presents a singularity which is accounted for in our numerical implementation to increase the number of DCC compared to previous approaches which excluded these pairs of source positions. Axial truncation of the projections is addressed by identifying for which set of planes containing the two source positions the fan-beams are not truncated. The ability of these DCC to detect breathing motion has been evaluated on simulated and real projections. Our results indicate that the DCC can detect motion if the baseline and the FOV do not intersect. If they do, the inconsistency due to motion is dominated by discretization errors and noise. We therefore propose to normalize the inconsistency by the noise to obtain a noise-aware metric which is mostly sensitive to inconsistencies due to motion. Combined with a moving average to reduce noise, the derived DCC can detect breathing motion.

A tomographic reconstruction algorithm for cross-sectional imaging of IMRT beams from six projections.

Objective. Patient-specific Quality Assurance (QA) measurements are of key importance in radiotherapy for safe and efficient treatment delivery and allow early detection of clinically relevant errors. Such QA processes remain challenging to implement for complex Intensity Modulated Radiation Therapy (IMRT) radiotherapy fields delivered using a multileaf collimator (MLC) which often feature small open segments and raise QA issues similar to those encountered in small field dosimetry. Recently, detectors based on long scintillating fibers have been proposed to measure a few parallel projections of the irradiation field with good performance for small field dosimetry. The purpose of this work is to develop and validate a novel approach to reconstruct MLC-shaped small irradiation fields from six projections.Approach. The proposed field reconstruction method uses a limited number of geometric parameters to model the irradiation field. These parameters are iteratively estimated with a steepest descent algorithm. The reconstruction method was first validated on simulated data. Real data were measured with a water-equivalent slab phantom equipped with a detector made of 6 scintillating-fiber ribbons placed at 1 m from the source. A radiochromic film was used to acquire a reference measurement of a first dose distribution in the slab phantom at the same source-to-detector distance and the treatment planning system (TPS) provided the reference for another dose distribution. In addition, simulated errors introduced on the delivered dose, field location and field shape were used to evaluate the ability of the proposed method to efficiently identify a deviation between the planned and delivered treatments.Main results. For a first small IMRT segment, 3%/3 mm, 2%/2 mm and 2%/1 mm gamma analysis conducted between the reconstructed dose distribution and the dose measured with radiochromic film exhibited pass rates of 100%, 99.9% and 95.7%, respectively. For a second and smaller IMRT segment, the same gamma analysis performed between the reconstructed dose distribution and the reference provided by the TPS showed pass rates of 100%, 99.4% and 92.6% for the 3%/3 mm, 2%/2 mm and 2%/1 mm gamma criteria, respectively. Gamma analysis of the simulated treatment delivery errors showed the ability of the reconstruction algorithm to detect a 3% deviation between the planned and delivered doses, as well as shifts lower than 7 mm and 3 mm when considering an individual leaf and a whole field shift, respectively.Significance. The proposed method allows accurate tomographic reconstruction of IMRT segments by processing projections measured with six scintillating-fiber ribbons and is suitable for water-equivalent real-time small IMRT segments QA.

Dosimetric impact of 3D motion-compensated SPECT reconstruction for SIRT planning.

BACKGROUND: In selective internal radiation therapy, 99mTc SPECT images are used to optimize patient treatment planning, but they are affected by respiratory motion. In this study, we evaluated on patient data the dosimetric impact of motion-compensated SPECT reconstruction on several volumes of interest (VOI), on the tumor-to-normal liver (TN) ratio and on the activity to be injected. METHODS: Twenty-nine patients with liver cancer or hepatic metastases treated by radioembolization were included in this study. The biodistribution of 90Y is assumed to be the same as that of 99mTc when predictive dosimetry is implemented. A total of 31 99mTc SPECT images were acquired and reconstructed with two methods: conventional OSEM (3D) and motion-compensated OSEM (3Dcomp). Seven VOI (liver, lungs, tumors, perfused liver, hepatic reserve, healthy perfused liver and healthy liver) were delineated on the CT or obtained by thresholding SPECT images followed by Boolean operations. Absorbed doses were calculated for each reconstruction using Monte Carlo simulations. Percentages of dose difference (PDD) between 3Dcomp and 3D reconstructions were estimated as well as the relative differences for TN ratio and activities to be injected. The amplitude of movement was determined with local rigid registration of the liver between the 3Dcomp reconstructions of the extreme phases of breathing. RESULTS: The mean amplitude of the liver was 9.5 ± 2.7 mm. Medians of PDD were closed to zero for all VOI except for lungs (6.4%) which means that the motion compensation overestimates the absorbed dose to the lungs compared to the 3D reconstruction. The smallest lesions had higher PDD than the largest ones. Between 3D and 3Dcomp reconstructions, means of differences in lung dose and TN ratio were not statistically significant, but in some cases these differences exceed 1 Gy (4/31) and 8% (2/31). The absolute differences in activity were on average 3.1% ± 5.1% and can reach 22.8%. CONCLUSION: The correction of respiratory motion mainly impacts the lung and tumor doses but only for some patients. The largest dose differences are observed for the smallest lesions.

Scatter correction of 4D cone beam computed tomography to detect dosimetric effects due to anatomical changes in proton therapy for lung cancer.

BACKGROUND: The treatment of moving tumor entities is expected to have superior clinical outcomes, using image-guided adaptive intensity-modulated proton therapy (IMPT). PURPOSE: For 21 lung cancer patients, IMPT dose calculations were performed on scatter-corrected 4D cone beam CTs (4DCBCTcor ) to evaluate their potential for triggering treatment adaptation. Additional dose calculations were performed on corresponding planning 4DCTs and day-of-treatment 4D virtual CTs (4DvCTs). METHODS: A 4DCBCT correction workflow, previously validated on a phantom, generates 4DvCT (CT-to-CBCT deformable registration) and 4DCBCTcor images (projection-based correction using 4DvCT as a prior) with 10 phase bins, using day-of-treatment free-breathing CBCT projections and planning 4DCT images as input. Using a research planning system, robust IMPT plans administering eight fractions of 7.5 Gy were created on a free-breathing planning CT (pCT) contoured by a physician. The internal target volume (ITV) was overridden with muscle tissue. Robustness settings for range and setup uncertainties were 3% and 6 mm, and a Monte Carlo dose engine was used. On every phase of planning 4DCT, day-of-treatment 4DvCT, and 4DCBCTcor , the dose was recalculated. For evaluation, image analysis as well as dose analysis were performed using mean error (ME) and mean absolute error (MAE) analysis, dose-volume histogram (DVH) parameters, and 2%/2-mm gamma pass rate analysis. Action levels (1.6% ITV D98 and 90% gamma pass rate) based on our previous phantom validation study were set to determine which patients had a loss of dosimetric coverage. RESULTS: Quality enhancements of 4DvCT and 4DCBCTcor over 4DCBCT were observed. ITV D98% and bronchi D2% had its largest agreement for 4DCBCTcor -4DvCT, and the largest gamma pass rates (>94%, median 98%) were found for 4DCBCTcor -4DvCT. Deviations were larger and gamma pass rates were smaller for 4DvCT-4DCT and 4DCBCTcor -4DCT. For five patients, deviations were larger than the action levels, suggesting substantial anatomical changes between pCT and CBCT projections acquisition. CONCLUSIONS: This retrospective study shows the feasibility of daily proton dose calculation on 4DCBCTcor for lung tumor patients. The applied method is of clinical interest as it generates up-to-date in-room images, accounting for breathing motion and anatomical changes. This information could be used to trigger replanning.

A novel QA phantom based on scintillating fiber ribbons with implementation of 2D dose tomography for small-field radiotherapy.

PURPOSE: To develop a novel instrument for real-time quality assurance (QA) procedures in radiotherapy. The system implements a scintillation-based phantom and associated signal acquisition and processing modules and aims to monitor two-dimensional (2D) dose distributions of small fields. MATERIALS AND METHODS: For the proposed phantom, we have designed and realized a prototype implementing six high-resolution tissue-equivalent scintillating fiber ribbons stacked with in-plane 30° rotated orientations from each other. Each ribbon output is coupled to a silicon photodiode linear array (with an element pitch of 400 µm) to detect scintillating signal, which represents the projected irradiation profile perpendicular to the ribbon's orientation. For the system providing six acquired projected dose profiles at different orientations, we have developed a two-step signal processing method to perform 2D dose reconstruction. The first step is to determine irradiation field geometry parameters using a tomographic geometry approach, and the second one is to perform specific penumbra estimation. The QA system prototype has been tested on a Novalis TrueBeam STX with a 6-MV photon beam for small elliptic fields defined by 5- and 10-mm cone collimators and for 10 × 10- and 20 × 10-mm2 rectangular fields defined by the micro-multileaf collimator. Gamma index analysis using EBT3 films as reference has been carried out with tight 2%-dose-difference (DD)/700-µm-distance-to-agreement (DTA) as well as 1%-DD/1-mm-DTA criteria for evaluating the system performances. The testing also includes an evaluation of the proposed two-step field reconstruction method in comparison with two conventional methods: filtered back projection (FBP) and simultaneous iterative reconstruction technique (SIRT). RESULTS: The reconstructed 2D dose distributions have gamma index pass rates higher than 95% for all the tested configurations as compared with EBT3 film measurements with both 2%-DD/700-µm-DTA and 1%-DD/1-mm criteria. 2D global gamma analysis shows that the two-step and FBP radiation field reconstruction methods systematically outperform the SIRT approach. Moreover, higher gamma index success rates are obtained with the two-step method than with FBP in the case of the fields defined with the stereotactic cones. CONCLUSIONS: The proposed small-field QA system makes a use of six water-equivalent scintillating detectors (fiber ribbons) to acquire dose distribution. The developed two-step signal processing method performs tomographic 2D dose reconstruction. A system prototype has been built and tested using hospital facilities with small rectangular and elliptic fields. Testing results show 2D reconstructed dose distributions with high accuracy and resolution. Such a system could potentially be an alternative approach to film dosimetry for small-field QA, which is still widely used as reference in clinical practice.

Deep learning-based segmentation in prostate radiation therapy using Monte Carlo simulated cone-beam computed tomography.

PURPOSE: Segmenting organs in cone-beam CT (CBCT) images would allow to adapt the radiotherapy based on the organ deformations that may occur between treatment fractions. However, this is a difficult task because of the relative lack of contrast in CBCT images, leading to high inter-observer variability. Deformable image registration (DIR) and deep-learning based automatic segmentation approaches have shown interesting results for this task in the past years. However, they are either sensitive to large organ deformations, or require to train a convolutional neural network (CNN) from a database of delineated CBCT images, which is difficult to do without improvement of image quality. In this work, we propose an alternative approach: to train a CNN (using a deep learning-based segmentation tool called nnU-Net) from a database of artificial CBCT images simulated from planning CT, for which it is easier to obtain the organ contours. METHODS: Pseudo-CBCT (pCBCT) images were simulated from readily available segmented planning CT images, using the GATE Monte Carlo simulation. CT reference delineations were copied onto the pCBCT, resulting in a database of segmented images used to train the neural network. The studied segmentation contours were: bladder, rectum, and prostate contours. We trained multiple nnU-Net models using different training: (1) segmented real CBCT, (2) pCBCT, (3) segmented real CT and tested on pseudo-CT (pCT) generated from CBCT with cycleGAN, and (4) a combination of (2) and (3). The evaluation was performed on different datasets of segmented CBCT or pCT by comparing predicted segmentations with reference ones thanks to Dice similarity score and Hausdorff distance. A qualitative evaluation was also performed to compare DIR-based and nnU-Net-based segmentations. RESULTS: Training with pCBCT was found to lead to comparable results to using real CBCT images. When evaluated on CBCT obtained from the same hospital as the CT images used in the simulation of the pCBCT, the model trained with pCBCT scored mean DSCs of 0.92 ± 0.05, 0.87 ± 0.02, and 0.85 ± 0.04 and mean Hausdorff distance 4.67 ± 3.01, 3.91 ± 0.98, and 5.00 ± 1.32 for the bladder, rectum, and prostate contours respectively, while the model trained with real CBCT scored mean DSCs of 0.91 ± 0.06, 0.83 ± 0.07, and 0.81 ± 0.05 and mean Hausdorff distance 5.62 ± 3.24, 6.43 ± 5.11, and 6.19 ± 1.14 for the bladder, rectum, and prostate contours, respectively. It was also found to outperform models using pCT or a combination of both, except for the prostate contour when tested on a dataset from a different hospital. Moreover, the resulting segmentations demonstrated a clinical acceptability, where 78% of bladder segmentations, 98% of rectum segmentations, and 93% of prostate segmentations required minor or no corrections, and for 76% of the patients, all structures of the patient required minor or no corrections. CONCLUSION: We proposed to use simulated CBCT images to train a nnU-Net segmentation model, avoiding the need to gather complex and time-consuming reference delineations on CBCT images.

Relative stopping power resolution in time-of-flight proton CT.

Objective.Proton computed tomography (CT) is similar to x-ray CT but relies on protons rather than photons to form an image. In its most common operation mode, the measured quantity is the amount of energy that a proton has lost while traversing the imaged object from which a relative stopping power map can be obtained via tomographic reconstruction. To this end, a calorimeter which measures the energy deposited by protons downstream of the scanned object has been studied or implemented as energy detector in several proton CT prototypes. An alternative method is to measure the proton's residual velocity and thus its kinetic energy via the time of flight (TOF) between at least two sensor planes. In this work, we study the RSP resolution, seen as image noise, which can be expected from TOF proton CT systems.Approach.We rely on physics models on the one hand and statistical models of the relevant uncertainties on the other to derive closed form expressions for the noise in projection images. The TOF measurement error scales with the distance between the TOF sensor planes and is reported as velocity error in ps/m. We use variance reconstruction to obtain noise maps of a water cylinder phantom given the scanner characteristics and additionally reconstruct noise maps for a calorimeter-based proton CT system as reference. We use Monte Carlo simulations to verify our model and to estimate the noise due to multiple Coulomb scattering inside the object. We also provide a comparison of TOF helium and proton CT.Main results.We find that TOF proton CT with 30 ps m-1velocity error reaches similar image noise as a calorimeter-based proton CT system with 1% energy error (1 sigma error). A TOF proton CT system with a 50 ps m-1velocity error produces slightly less noise than a 2% calorimeter system. Noise in a reconstructed TOF proton CT image is spatially inhomogeneous with a marked increase towards the object periphery. Our modelled noise was consistent with Monte Carlo simulated images. TOF helium CT offers lower RSP noise at equal fluence, but is less advantageous at equal imaging dose.Significance.This systematic study of image noise in TOF proton CT can serve as a guide for future developments of this alternative solution for estimating the residual energy of protons and helium ions after the scanned object.

Comparative accuracy and resolution assessment of two prototype proton computed tomography scanners.

BACKGROUND: Improving the accuracy of relative stopping power (RSP) in proton therapy may allow reducing range margins. Proton computed tomography (pCT) has been shown to provide state-of-the-art RSP accuracy estimation, and various scanner prototypes have recently been built. The different approaches used in scanner design are expected to impact spatial resolution and RSP accuracy. PURPOSE: The goal of this study was to perform the first direct comparison, in terms of spatial resolution and RSP accuracy, of two pCT prototype scanners installed at the same facility and by using the same image reconstruction algorithm. METHODS: A phantom containing cylindrical inserts of known RSP was scanned at the phase-II pCT prototype of the U.S. pCT collaboration and at the commercially oriented ProtonVDA scanner. Following distance-driven binning filtered backprojection reconstruction, the radial edge spread function of high-density inserts was used to estimate the spatial resolution. RSP accuracy was evaluated by the mean absolute percent error (MAPE) over the inserts. No direct imaging dose estimation was possible, which prevented a comparison of the two scanners in terms of RSP noise. RESULTS: In terms of RSP accuracy, both scanners achieved the same MAPE of 0.72% when excluding the porous sinus insert from the evaluation. The ProtonVDA scanner reached a better overall MAPE when all inserts and the body of the phantom were accounted for (0.81%), compared to the phase-II scanner (1.14%). The spatial resolution with the phase-II scanner was found to be 0.61 lp/mm, while for the ProtonVDA scanner somewhat lower at 0.46 lp/mm. CONCLUSIONS: The comparison between two prototype pCT scanners operated in the same clinical facility showed that they both fulfill the requirement of an RSP accuracy of about 1%. Their spatial resolution performance reflects the different design choices of either a scanner with full tracking capabilities (phase-II) or of a more compact tracker system, which only provides the positions of protons but not their directions (ProtonVDA).

Feasibility study of a proton CT system based on 4D-tracking and residual energy determination via time-of-flight.

Objective.For dose calculations in ion beam therapy, it is vital to accurately determine the relative stopping power (RSP) distribution within the treatment volume. A suitable imaging modality to achieve the required RSP accuracy is proton computed tomography (pCT), which usually uses a tracking system and a separate residual energy (or range) detector to directly measure the RSP distribution. This work investigates the potential of a novel pCT system based on a single detector technology, namely low gain avalanche detectors (LGADs). LGADs are fast 4D-tracking detectors, which can be used to simultaneously measure the particle position and time with precise timing and spatial resolution. In contrast to standard pCT systems, the residual energy is determined via a time-of-flight (TOF) measurement between different 4D-tracking stations.Approach.To show the potential of using 4D-tracking for proton imaging, we studied and optimized the design parameters for a realistic TOF-pCT system using Monte Carlo simulations. We calculated the RSP accuracy and RSP resolution inside the inserts of the CTP404 phantom and compared the results to a simulation of an ideal pCT system.Main results.After introducing a dedicated calibration procedure for the TOF calorimeter, RSP accuracies less than 0.6% could be achieved. We also identified the design parameters with the strongest impact on the RSP resolution and proposed a strategy to further improve the image quality.Significance.This comprehensive study of the most important design aspects for a novel TOF-pCT system could help guide future hardware developments and, once implemented, improve the quality of treatment planning in ion beam therapy.

Image quality of dual-energy cone-beam CT with total nuclear variation regularization.

Despite the improvements in image quality of cone beam computed tomography (CBCT) scans, application remains limited to patient positioning. In this study, we propose to improve image quality by dual energy (DE) imaging and iterative reconstruction using least squares fitting with total variation (TV) regularization. The generalization of TV called total nuclear variation (TNV) was used to generate DE images. We acquired single energy (SE) and DE scans of an image quality phantom (IQP) and of an anthropomorphic human male phantom (HMP). The DE scans were dual arc acquisitions of 70 kV and 130 kV with a variable dose partitioning between low energy (LE) and high energy (HE) arcs. To investigate potential benefits from a larger spectral separation between LE and HE, DE scans with an additional 2 mm copper beam filtration in the HE arc were acquired for the IQP. The DE TNV scans were compared to SE scans reconstructed with FDK and iterative TV with varying parameters. The contrast-to-noise ratio (CNR), spatial frequency, and structural similarity (SSIM) were used as image quality metrics. Results showed largely improved image quality for DE TNV over FDK for both phantoms. DE TNV with the highest dose allocation in the LE arm yielded the highest CNR. Compared to SE TV, these DE TNV results had a slightly lower CNR with similar spatial resolution for the IQP. A decrease in the dose allocated to the LE arm improved the spatial resolution with a trade-off against CNR. For the HMP, DE TNV displayed a lower CNR and/or lower spatial resolution depending on the reconstruction parameters. Regarding the SSIM, DE TNV was superior to FDK and SE TV for both phantoms. The additional beam filtration for the IQP led to improved image quality in all metrics, surpassing the SE TV results in CNR and spatial resolution.

The role of Monte Carlo simulation in understanding the performance of proton computed tomography.

Proton computed tomography (pCT) is a promising tomographic imaging modality allowing direct reconstruction of proton relative stopping power (RSP) required for proton therapy dose calculation. In this review article, we aim at highlighting the role of Monte Carlo (MC) simulation in pCT studies. After describing the requirements for performing proton computed tomography and the various pCT scanners actively used in recent research projects, we present an overview of available MC simulation platforms. The use of MC simulations in the scope of investigations of image reconstruction, and for the evaluation of optimal RSP accuracy, precision and spatial resolution omitting detector effects is then described. In the final sections of the review article, we present specific applications of realistic MC simulations of an existing pCT scanner prototype, which we describe in detail.