A Monte Carlo software bench for simulation of spectral k-edge CT imaging: Initial results

PurposeSpectral Computed Tomography (SCT) systems equipped with photon counting detectors (PCD) are clinically desired, since such systems provide not only additional diagnostic information but also radiation dose reductions by a factor of two or more. The current unavailability of clinical PCDs makes a simulation of such systems necessary.MethodsIn this paper, we present a Monte Carlo-based simulation of a SCT equipped with a PCD. The aim of this development is to facilitate research on potential clinical applications. Our MC simulator takes into account scattering interactions within the scanned object and has the ability to simulate scans with and without scatter and a wide variety of imaging parameters. To demonstrate the usefulness of such a MC simulator for development of SCT applications, a phantom with contrast targets covering a wide range of clinically significant iodine concentrations is simulated. With those simulations the impact of scatter and exposure on image quality and material decomposition results is investigated.ResultsOur results illustrate that scatter radiation plays a significant role in visual as well as quantitative results. Scatter radiation can reduce the accuracy of contrast agent concentration by up to 15%.ConclusionsWe present a reliable and robust software bench for simulation of SCTs equipped with PCDs.     

A newly-developed metal artifact reduction algorithm improves the visibility of oral cavity lesions on 320-MDCT volume scans

PurposeTo investigate whether a newly-developed single-energy metal artifact reduction (SEMAR) algorithm applied to images acquired on a 320-MDCT volume scanner reduces image artifacts from dental metal.MethodsWe inserted the lower right teeth covered with a dental metal alloy and crown in a skull phantom and performed single-volume scanning on a second-generation 320-MDCT scanner. A 12-mm diameter spherical lesion was placed either close to or far from the dental metal. The tube voltage and current were 120 kVp and 80 or 155 mA, respectively. Images were reconstructed with filtered back projection (FBP) or iterative reconstruction (IR), with or without SEMAR. We calculated the signal-to-artifact ratios (SAR) to quantify the visibility of the lesion. Two radiologists inspected 96 images (48 with lesion and 48 without) for the presence or absence of the lesion using a 5-point ordinal scale (1 = definitely absent to 5 = definitely present).ResultsOn images reconstructed with FPB and IR with SEMAR, streak artifacts from the dental metal were reduced substantially compared to images without SEMAR. At 155 mA with the lesion near the dental metal, the SARs were better on FBP and IR images (FBP: 1.7 and 0.5 with and without SEMAR, respectively; IR: 1.6 and 0.9 with and without SEMAR, respectively). The observer visual scores improved with SEMAR (FBP: 4.2 and 3.2 with and without SEMAR, respectively; IR: 4.2 and 3.0).ConclusionThe SEMAR algorithm reduces dental metal artifacts and improves lesion detectability and image quality in patients with oral cavity lesions.     

An iterative deconvolution algorithm for image recovery in clinical CT: A phantom study

PurposeTo study the feasibility of using an iterative reconstruction algorithm to improve previously reconstructed CT images which are judged to be non-diagnostic on clinical review. A novel rapidly converging, iterative algorithm (RSEMD) to reduce noise as compared with standard filtered back-projection algorithm has been developed.Materials and methodsThe RSEMD method was tested on in-silico, Catphan^®500, and anthropomorphic 4D XCAT phantoms. The method was applied to noisy CT images previously reconstructed with FBP to determine improvements in SNR and CNR. To test the potential improvement in clinically relevant CT images, 4D XCAT phantom images were used to simulate a small, low contrast lesion placed in the liver.ResultsIn all of the phantom studies the images proved to have higher resolution and lower noise as compared with images reconstructed by conventional FBP. In general, the values of SNR and CNR reached a plateau at around 20 iterations with an improvement factor of about 1.5 for in noisy CT images. Improvements in lesion conspicuity after the application of RSEMD have also been demonstrated. The results obtained with the RSEMD method are in agreement with other iterative algorithms employed either in image space or with hybrid reconstruction algorithms.ConclusionsIn this proof of concept work, a rapidly converging, iterative deconvolution algorithm with a novel resolution subsets-based approach that operates on DICOM CT images has been demonstrated. The RSEMD method can be applied to sub-optimal routine-dose clinical CT images to improve image quality to potentially diagnostically acceptable levels.     

Iterative image reconstruction using modified non-local means filtering for limited-angle computed tomography

PurposeLimited-angle CT imaging is an effective technique to reduce radiation. However, existing image reconstruction methods can effectively reduce streak artifacts but fail to suppress those artifacts around edges due to incomplete projection data. Thus, a modified NLM (mNLM) based reconstruction method is proposed.MethodsSince the artifacts around edges mainly exist in local position, it is possible to restore the true pixels in artifacts using pixels located in artifacts-free regions. In each iteration, mNLM is performed on image reconstructed by ART followed by positivity constraint. To solve the problem caused by ART-mNLM that there is undesirable information that may appear in the image, ART-TV is then utilized in the following iterative process after ART-mNLM iterates for a number of iterations. The proposed algorithm is named as ART-mNLM/TV.ResultsSimulation experiments are performed to validate the feasibility of algorithm. When the scanning range is [0, 150°], our algorithm outperforms the ART-NLM and ART-TV with more than 40% and 29% improvement in terms of SNR and with more than 58% and 49% reduction in terms of MAE. Consistently, reconstructed images from real projection data also demonstrate the effectiveness of presented algorithm.ConclusionThis paper uses mNLM which benefits from redundancy of information across the whole image, to recover the true value of pixels in artifacts region by utilizing pixels from artifact-free regions, and artifacts around the edges can be mitigated effectively. Experiments show that the proposed ART-mNLM/TV is able to achieve better performances compared to traditional methods.     

Quantifying near metal visibility using dual energy computed tomography and iterative metal artifact reduction in a fracture phantom

PurposeTo quantitatively assess CT image quality and fracture visibility using virtual monochromatic imaging and iterative metal artifact reduction (iMAR) in a femoral bone fracture phantom with different fixation implants.MethodsA custom made phantom was scanned at 120-kVp and 140-kVp single-energy and 100/150-kVp dual-energy. Three stainless steel and two titanium implants with different thicknesses were placed on the phantom containing simulated one and two mm fractures. Single-energy CT images were reconstructed with and without iMAR, while DECT images were reconstructed at monochromatic energies between 70 and 190 keV. Non-metal scans were used as a reference. A Fourier power spectrum method and fracture model were used to analyze several anatomical areas.ResultsCT-value deviations of titanium implants were much lower compared to stainless steel implants. These deviations decreased for both DECT and iMAR. Fracture visibility, measured with the fracture model, improved the most when DECT was used while artifact reduction benefitted more from iMAR. The optimal monochromatic energy for metal artifact reduction, based on CT-value deviation, varied for each metal between 130 and 150 keV. The fracture model provided a signal-to-noise ratio for the near metal fracture visibility, providing the optimal keV.ConclusioniMAR and high keV monochromatic images extracted from DECT both reduce metal artifacts caused by different metal fixation implants. Quantitative femoral phantom results show that DECT is superior to iMAR regarding fracture visualization adjacent to metal fixation implants. The introduction of new artifacts when using iMAR impedes its value in near metal fixation implant imaging.     

A Novel Weighted Total Difference Based Image Reconstruction Algorithm for Few-View Computed Tomography

In practical applications of computed tomography (CT) imaging, due to the risk of high radiation dose imposed on the patients, it is desired that high quality CT images can be accurately reconstructed from limited projection data. While with limited projections, the images reconstructed often suffer severe artifacts and the edges of the objects are blurred. In recent years, the compressed sensing based reconstruction algorithm has attracted major attention for CT reconstruction from a limited number of projections. In this paper, to eliminate the streak artifacts and preserve the edge structure information of the object, we present a novel iterative reconstruction algorithm based on weighted total difference (WTD) minimization, and demonstrate the superior performance of this algorithm. The WTD measure enforces both the sparsity and the directional continuity in the gradient domain, while the conventional total difference (TD) measure simply enforces the gradient sparsity horizontally and vertically. To solve our WTD-based few-view CT reconstruction model, we use the soft-threshold filtering approach. Numerical experiments are performed to validate the efficiency and the feasibility of our algorithm. For a typical slice of FORBILD head phantom, using 40 projections in the experiments, our algorithm outperforms the TD-based algorithm with more than 60% gains in terms of the root-mean-square error (RMSE), normalized root mean square distance (NRMSD) and normalized mean absolute distance (NMAD) measures and with more than 10% gains in terms of the peak signal-to-noise ratio (PSNR) measure. While for the experiments of noisy projections, our algorithm outperforms the TD-based algorithm with more than 15% gains in terms of the RMSE, NRMSD and NMAD measures and with more than 4% gains in terms of the PSNR measure. The experimental results indicate that our algorithm achieves better performance in terms of suppressing streak artifacts and preserving the edge structure information of the object.     

Iterative Image Reconstruction for Sparse-View CT Using Normal-Dose Image Induced Total Variation Prior

X-ray computed tomography (CT) iterative image reconstruction from sparse-view projection data has been an important research topic for radiation reduction in clinic. In this paper, to relieve the requirement of misalignment reduction operation of the prior image constrained compressed sensing (PICCS) approach introduced by Chen et al, we present an iterative image reconstruction approach for sparse-view CT using a normal-dose image induced total variation (ndiTV) prior. The associative objective function of the present approach is constructed under the penalized weighed least-square (PWLS) criteria, which contains two terms, i.e., the weighted least-square (WLS) fidelity and the ndiTV prior, and is referred to as “PWLS-ndiTV”. Specifically, the WLS fidelity term is built based on an accurate relationship between the variance and mean of projection data in the presence of electronic background noise. The ndiTV prior term is designed to reduce the influence of the misalignment between the desired- and prior- image by using a normal-dose image induced non-local means (ndiNLM) filter. Subsequently, a modified steepest descent algorithm is adopted to minimize the associative objective function. Experimental results on two different digital phantoms and an anthropomorphic torso phantom show that the present PWLS-ndiTV approach for sparse-view CT image reconstruction can achieve noticeable gains over the existing similar approaches in terms of noise reduction, resolution-noise tradeoff, and low-contrast object detection.     

Dual-energy CT imaging of orbits during episcleral brachytherapy with Ru-106 plaques: A phantom study on its potential for plaque position verification

PurposeTo investigate the potential of dual energy CT (DECT) to suppress metal artifacts and accurately depict episcleral brachytherapy Ru-106 plaques after surgical placement.MethodsAn anthropomorphic phantom simulating the adult head after surgical placement of a Ru-106 plaque was employed. Nine DECT acquisition protocols for orbital imaging were applied. Monochromatic 140 keV images were generated using iterative reconstruction and an available metal artifact reduction algorithm. Generated image datasets were graded by four observers regarding the ability to accurate demarcate the Ru-106 plaque. Objective image quality and visual grading analysis (VGA) was performed to compare different acquisition protocols. The DECT imaging protocol which allowed accurate plaque demarcation at minimum exposure was identified. The eye-lens dose from orbital DECT, with and without the use of radioprotective bismuth eye-shields, was determined using Monte Carlo methods.ResultsAll DECT acquisition protocols were judged to allow clear demarcation of the plaque borders despite some moderate streaking/shading artifacts. The differences between mean observers’ VGA scores for the 9 DECT imaging protocols were not statistically significant (p > 0.05). The eye-lens dose from the proposed low-exposure DECT protocol was found to be 20.1 and 22.8 mGy for the treated and the healthy eye, respectively. Bismuth shielding was found to accomplish >40% reduction in eye-lens dose without inducing shielding-related artifacts that obscure plaque delineation.ConclusionsDECT imaging of orbits after Ru-106 plaque positioning for ocular brachytherapy was found to allow artifact-free delineation of plaque margins at relatively low patient exposure, providing the potential for post-surgery plaque position verification.     

Accurate proton treatment planning for pencil beam crossing titanium fixation implants

PurposeTo present a planning strategy for proton pencil-beam scanning when titanium implants need to be crossed by the beam.MethodsWe addressed three issues: the implementation of a CT calibration curve to assign to titanium the correct stopping power; the effect of artefacts on CT images and their reduction by a dedicated algorithm; the differences in dose computation depending on the dose engine, pencil-beam vs Monte-Carlo algorithms. We performed measurement tests on a simple cylinder phantom and on a real implant. These phantoms were irradiated with three geometries (single spots, uniform mono-energetic layer and uniform box), measuring the exit dose either by radio-chromic film or multi-layer ionization chamber. The procedure was then applied on two patients treated for chordoma.ResultsWe had to set in the calibration curve a mass density equal to 4.37 g/cm³ to saturated Hounsfield Units, in order to have the correct stopping power assigned to titanium in TPS. CT artefact reduction algorithm allowed a better reconstruction of the shape and size of the implant. Monte-Carlo resulted accurate in computing the dose distribution whereas the pencil-beam algorithm failed due to sharp density interfaces between titanium and the surrounding material. Finally, the treatment plans obtained on two patients showed the impact of the dose engine algorithm, with 10–20% differences between pencil-beam and Monte-Carlo in small regions distally to the titanium screws.ConclusionThe described combination of CT calibration, artefacts reduction and Monte-Carlo computation provides a reliable methodology to compute dose in patients with titanium implants.     

Can different Catphan phantoms be used in a multi-centre audit of radiotherapy CT image quality?

PurposeTo determine the variation between Catphan image quality CT phantoms, specifically for use in a future multi-centre image quality audit.Method14 Catphan phantoms (models 503, 504 and 604) were scanned on a Canon Aquilion Prime CT scanner using a single scan protocol. Measurements were made of noise in the uniformity section, visibility of low contrast targets and contrast, x-ray attenuation and CT number for 5 materials in the sensitometry section. Scans were also acquired using one phantom and varying reconstruction field of view, image slice thickness, effective tube-current-time product and iterative reconstruction settings to determine how the degree of inter-phantom variability compared with the magnitude of changes from scan parameter alteration.ResultsAcross all phantoms the mean CT value in the uniformity section was 7.0 (SD 0.9) range: 4.9–8.1 HU. For the different materials the CT numbers were air: −1004 ± 5, Polymethylpentene: −190 ± 2, Polystyrene: −42 ± 2, Delrin: 321 ± 5 and Teflon: 898 ± 8 HU. Consistency of low contrast targets through visual scoring was good. Measured contrast was lower (p < 0.001) with more variability for 504 versus 604 models. All phantoms produced identical tube current settings with x-ray tube current modulation, indicating no x-ray attenuation differences. The degree of change in image quality metrics between phantoms was small compared with results when scan parameters were varied.ConclusionCatphan phantoms model 604 showed minimal differences and will be used for multi-centre inter-comparison work, with the consistency between phantoms appropriate for measuring possible variations in image quality.     

Ultra-low dose whole-body CT for attenuation correction in a dual tracer PET/CT protocol for multiple myeloma

PurposeTo investigate within phantoms the minimum CT dose allowed for accurate attenuation correction of PET data and to quantify the effective dose reduction when a CT for this purpose is incorporated in the clinical setting.MethodsThe NEMA image quality phantom was scanned within a large parallelepiped container. Twenty-one different CT images were acquired to correct attenuation of PET raw data. Radiation dose and image quality were evaluated.Thirty-one patients with proven multiple myeloma who underwent a dual tracer PET/CT scan were retrospectively reviewed. ¹⁸F-fluorodeoxyglucose PET/CT included a diagnostic whole-body low dose CT (WBLDCT: 120 kV-80mAs) and ¹¹C-Methionine PET/CT included a whole-body ultra-low dose CT (WBULDCT) for attenuation correction (100 kV-40mAs). Effective dose and image quality were analysed.ResultsOnly the two lowest radiation dose conditions (80 kV-20mAs and 80 kV-10mAs) produced artifacts in CT images that degraded corrected PET images. For all the other conditions (CTDI_vol ≥ 0.43 mGy), PET contrast recovery coefficients varied less than ± 1.2%.Patients received a median dose of 6.4 mSv from diagnostic CT and 2.1 mSv from the attenuation correction CT. Despite the worse image quality of this CT, 94.8% of bone lesions were identifiable.ConclusionPhantom experiments showed that an ultra-low dose CT can be implemented in PET/CT procedures without any noticeable degradation in the attenuation corrected PET scan. The replacement of the standard CT for this ultra-low dose CT in clinical PET/CT scans involves a significant radiation dose reduction.     

Brain PET imaging optimization with time of flight and point spread function modelling

PurposeTo assess the influence of reconstruction algorithms and parameters on the PET image quality of brain phantoms in order to optimize reconstruction for clinical PET brain studies in a new generation PET/CT.MethodsThe 3D Hoffman phantom that simulates ¹⁸F-fluorodeoxyglucose (FDG) distribution was imaged in a Siemens Biograph mCT TrueV PET/CT with Time of Flight (TOF) and Point Spread Function (PSF) modelling. Contrast-to-Noise Ratio (CNR), contrast and noise were studied for different reconstruction models: OSEM, OSEM + TOF, OSEM + PSF and OSEM + PSF + TOF.The 2D multi-compartment Hoffman phantom was filled to simulate 4 different tracers' spatial distribution: FDG, ¹¹C-flumazenil (FMZ), ¹¹C-Methionine (MET) and 6-¹⁸F-fluoro-l-dopa (FDOPA). The best algorithm for each tracer was selected by visual inspection. The maximization of CNR determined the optimal parameters for each reconstruction.ResultsIn the 3D Hoffman phantom, both noise and contrast increased with increasing number of iterations and decreased with increasing FWHM. OSEM + PSF + TOF reconstruction was generally superior to other reconstruction models. Visual analysis of the 2D Hoffman brain phantom suggested that OSEM + PSF + TOF is the optimum algorithm for tracers with focal uptake, such as MET or FDOPA, and OSEM + TOF for tracers with diffuse cortical uptake (i.e. FDG and FMZ). Optimization of CNR demonstrated that OSEM + TOF reconstruction must be performed with 2 iterations and a filter FWHM of 3 mm, and OSEM + PSF + TOF reconstruction with 4 iterations and 1 mm FWHM filter.ConclusionsOptimization of reconstruction algorithm and parameters has been performed to take particular advantage of the last generation PET scanner, recommending specific settings for different brain PET radiotracers.     

Automatic exposure control at single- and dual-heartbeat CTCA on a 320-MDCT volume scanner: Effect of heart rate,exposure phase window setting,and reconstruction algorithm

PurposeTo investigate whether electrocardiogram (ECG)-gated single- and dual-heartbeat computed tomography coronary angiography (CTCA) with automatic exposure control (AEC) yields images with uniform image noise at reduced radiation doses.Materials and methodsUsing an anthropomorphic chest CT phantom we performed prospectively ECG-gated single- and dual-heartbeat CTCA on a second-generation 320-multidetector CT volume scanner. The exposure phase window was set at 75%, 70–80%, 40–80%, and 0–100% and the heart rate at 60 or 80 or corr80 bpm; images were reconstructed with filtered back projection (FBP) or iterative reconstruction (IR, adaptive iterative dose reduction 3D). We applied AEC and set the image noise level to 20 or 25 HU. For each technique we determined the image noise and the radiation dose to the phantom center.ResultsWith half-scan reconstruction at 60 bpm, a 70–80% phase window- and a 20-HU standard deviation (SD) setting, the imagenoise level and -variation along the z axis manifested similar curves with FBP and IR. With half-scan reconstruction, the radiation dose to the phantom center with 70–80% phase window was 18.89 and 12.34 mGy for FBP and 4.61 and 3.10 mGy for IR at an SD setting SD of 20 and 25 HU, respectively. At 80 bpm with two-segment reconstruction the dose was approximately twice that of 60 bpm at both SD settings. However, increasing radiation dose at corr80 bpm was suppressed to 1.39 times compared to 60 bpm.ConclusionAEC at ECG-gated single- and dual-heartbeat CTCA controls the image noise at different radiation dose.     

Feasibility of spectral CT imaging for the detection of liver lesions with gold-based contrast agents – A simulation study

PurposeTo demonstrate the feasibility of gold-specific spectral CT imaging for the detection of liver lesions in humans at low concentrations of gold as targeted contrast agent.MethodsA Monte Carlo simulation study of spectral CT imaging with a photon-counting and energy-resolving detector (with 6 energy bins) was performed in a realistic phantom of the human abdomen. The detector energy thresholds were optimized for the detection of gold. The simulation results were reconstructed with the K-edge imaging algorithm; the reconstructed gold-specific images were filtered and evaluated with respect to signal-to-noise ratio and contrast-to-noise ratio (CNR).ResultsThe simulations demonstrate the feasibility of spectral CT with CNRs of the specific gold signal between 2.7 and 4.8 after bilateral filtering. Using the optimized bin thresholds increases the CNRs of the lesions by up to 23% compared to bin thresholds described in former studies.ConclusionsGold is a promising new CT contrast agent for spectral CT in humans; minimum tissue mass fractions of 0.2 wt% of gold are required for sufficient image contrast.     

Statistical learning methods as a preprocessing step for survival analysis: evaluation of concept using lung cancer data

Background

Despite its superb lateral resolution, flat-panel-detector (FPD) based tomosynthesis suffers from low contrast and inter-plane artifacts caused by incomplete cancellation of the projection components stemming from outside the focal plane. The incomplete cancellation of the projection components, mostly due to the limited scan angle in the conventional tomosynthesis scan geometry, often makes the image contrast too low to differentiate the malignant tissues from the background tissues with confidence.

Methods

In this paper, we propose a new method to suppress the inter-plane artifacts in FPD-based tomosynthesis. If 3D whole volume CT images are available before the tomosynthesis scan, the CT image data can be incorporated into the tomosynthesis image reconstruction to suppress the inter-plane artifacts, hence, improving the image contrast. In the proposed technique, the projection components stemming from outside the region-of-interest (ROI) are subtracted from the measured tomosynthesis projection data to suppress the inter-plane artifacts. The projection components stemming from outside the ROI are calculated from the 3D whole volume CT images which usually have lower lateral resolution than the tomosynthesis images. The tomosynthesis images are reconstructed from the subtracted projection data which account for the x-ray attenuation through the ROI. After verifying the proposed method by simulation, we have performed both CT scan and tomosynthesis scan on a phantom and a sacrificed rat using a FPD-based micro-CT.

Results

We have measured contrast-to-noise ratio (CNR) from the tomosynthesis images which is an indicator of the residual inter-plane artifacts on the focal-plane image. In both cases of the simulation and experimental imaging studies of the contrast evaluating phantom, CNRs have been significantly improved by the proposed method. In the rat imaging also, we have observed better visual contrast from the tomosynthesis images reconstructed by the proposed method.

Conclusions

The proposed tomosynthesis technique can improve image contrast with aids of 3D whole volume CT images. Even though local tomosynthesis needs extra 3D CT scanning, it may find clinical applications in special situations in which extra 3D CT scan is already available or allowed.     

An inhomogeneous most likely path formalism for proton computed tomography

PurposeMultiple Coulomb scattering (MCS) poses a challenge in proton CT (pCT) image reconstruction. The assumption of straight paths is replaced with Bayesian models of the most likely path (MLP). Current MLP-based pCT reconstruction approaches assume a water scattering environment. We propose an MLP formalism based on accurate determination of scattering moments in inhomogeneous media.MethodsScattering power relative to water (RScP) was calculated for a range of human tissues and investigated against relative stopping power (RStP). Monte Carlo simulation was used to compare the new inhomogeneous MLP formalism to the water approach in a slab geometry and a human head phantom. An MLP-Spline-Hybrid method was investigated for improved computational efficiency.ResultsA piecewise-linear correlation between RStP and RScP was shown, which may assist in iterative pCT reconstruction. The inhomogeneous formalism predicted Monte Carlo proton paths through a water cube with thick bone inserts to within 1.0 mm for beams ranging from 210 to 230 MeV incident energy. Improvement in accuracy over the conventional MLP ranged from 5% for a 230 MeV beam to 17% for 210 MeV. There was no noticeable gain in accuracy when predicting 200 MeV proton paths through a clinically relevant human head phantom. The MLP-Spline-Hybrid method reduced computation time by half while suffering negligible loss of accuracy.ConclusionsWe have presented an MLP formalism that accounts for material composition. In most clinical cases a water scattering environment can be assumed, however in certain cases of significant heterogeneity the proposed algorithm may improve proton path estimation.     

Objective assessment of low contrast detectability in computed tomography with Channelized Hotelling Observer

PurposeIterative algorithms introduce new challenges in the field of image quality assessment. The purpose of this study is to use a mathematical model to evaluate objectively the low contrast detectability in CT.Materials and methodsA QRM 401 phantom containing 5 and 8 mm diameter spheres with a contrast level of 10 and 20 HU was used. The images were acquired at 120 kV with CTDI_vol equal to 5, 10, 15, 20 mGy and reconstructed using the filtered back-projection (FBP), adaptive statistical iterative reconstruction 50% (ASIR 50%) and model-based iterative reconstruction (MBIR) algorithms. The model observer used is the Channelized Hotelling Observer (CHO). The channels are dense difference of Gaussian channels (D-DOG). The CHO performances were compared to the outcomes of six human observers having performed four alternative forced choice (4-AFC) tests.ResultsFor the same CTDI_vol level and according to CHO model, the MBIR algorithm gives the higher detectability index. The outcomes of human observers and results of CHO are highly correlated whatever the dose levels, the signals considered and the algorithms used when some noise is added to the CHO model. The Pearson coefficient between the human observers and the CHO is 0.93 for FBP and 0.98 for MBIR.ConclusionThe human observers' performances can be predicted by the CHO model. This opens the way for proposing, in parallel to the standard dose report, the level of low contrast detectability expected. The introduction of iterative reconstruction requires such an approach to ensure that dose reduction does not impair diagnostics.     

Assessment of the variation in CT scanner performance (image quality and Hounsfield units) with scan parameters,for image optimisation in radiotherapy treatment planning

PurposeTo define a method and investigate how the adjustment of scan parameters affected the image quality and Hounsfield units (HUs) on a CT scanner used for radiotherapy treatment planning. A lack of similar investigations in the literature may be a contributing factor in the apparent reluctance to optimise radiotherapy CT protocols.MethodA Catphan phantom was used to assess how image quality on a Toshiba Aquilion LB scanner changed with scan parameters. Acquisition and reconstruction field-of-view (FOV), collimation, image slice thickness, effective mAs per rotation and reconstruction algorithm were varied. Changes were assessed for HUs of different materials, high contrast spatial resolution (HCSR), contrast-noise ratio (CNR), HU uniformity, scan direction low contrast and CT dose-index.ResultsCNR and HCSR varied most with reconstruction algorithm, reconstruction FOV and effective mAs. Collimation, but not image slice width, had a significant effect on CT dose-index with narrower collimation giving higher doses. Dose increased with effective mAs. Highest HU differences were seen when changing reconstruction algorithm: 56 HU for densities close to water and 117 HU for bone-like materials. Acquisition FOV affected the HUs but reconstruction FOV and effective mAs did not.ConclusionsAll the scan parameters investigated affected the image quality metrics. Reconstruction algorithm, reconstruction FOV, collimation and effective mAs were most important. Reconstruction algorithm and acquisition FOV had significant effect on HU. The methodology is applicable to radiotherapy CT scanners when investigating image quality optimisation, prior to assessing the impact of scan protocol changes on clinical CT images and treatment plans.     

Algorithm-based artifact reduction in patients with arms-down positioning in computed tomography

PurposeArm-artifact, a type of streak artifact frequently observed in computed tomography (CT) images obtained at arms-down positioning in polytrauma patients, is known to degrade image quality. This study aimed to develop a novel arm-artifact reduction algorithm (AAR) applied to projection data.MethodsA phantom resembling an adult abdomen with two arms was scanned using a 16-row CT scanner. The projection data were processed by AAR, and CT images were reconstructed. The artifact reduction for the same phantom was compared with that achieved by two latest iterative reconstruction (IR) techniques (IR1 and IR2) using a normalized artifact index (nAI) at two locations (ventral and dorsal side). Image blurring as a processing side effect was compared with IR2 of the model-based IR using a plastic needle phantom. Additionally, the projection data of two clinical cases were processed using AAR, and the image noise was evaluated.ResultsAAR and IR2 significantly reduced nAI by 87.5% and 74.0%, respectively at the ventral side and 84.2% and 69.6%, respectively, at the dorsal side compared with each filtered back projection (P < 0.01), whereas IR1 did not. The proposed algorithm mostly maintained the original spatial resolution, compared with IR2, which yielded apparent image blurring. The image noise in the clinical cases was also reduced significantly (P < 0.01).ConclusionsAAR was more effective and superior than the latest IR techniques and is expected to improve the image quality of polytrauma CT imaging with arms-down positioning.     

3D TOF-PET image reconstruction using total variation regularization

In this paper we introduce a semi-analytic algorithm for 3-dimensional image reconstruction for positron emission tomography (PET). The method consists of the back-projection of the acquired data into the most likely image voxel according to time-of-flight (TOF) information, followed by the filtering step in the image space using an iterative optimization algorithm with a total variation (TV) regularization. TV regularization in image space is more computationally efficient than usual iterative optimization methods for PET reconstruction with full system matrix that use TV regularization. The efficiency comes from the one-time TOF back-projection step that might also be described as a reformatting of the acquired data. An important aspect of our work concerns the evaluation of the filter operator of the linear transform mapping an original radioactive tracer distribution into the TOF back-projected image. We obtain concise, closed-form analytical formula for the filter operator. The proposed method is validated with the Monte Carlo simulations of the NEMA IEC phantom using a one-layer, 50 cm-long cylindrical device called Jagiellonian PET scanner. The results show a better image quality compared with the reference TOF maximum likelihood expectation maximization algorithm.