Iterative reconstruction methods in X-ray CT

Computed Tomography Image Origin Identification Based on Original Sensor Pattern Noise and 3-D Image Reconstruction Algorithm Footprints

In this paper, we focus on the "blind" identification of the computed tomography (CT) scanner that has produced a CT image. To do so, we propose a set of noise features derived from the image chain acquisition and which can be used as CT-scanner footprint. Basically, we propose two approaches. The first one aims at identifying a CT scanner based on an original sensor pattern noise (OSPN) that is intrinsic to the X-ray detectors. The second one identifies an acquisition system based on the way this noise is modified by its three-dimensional (3-D) image reconstruction algorithm. As these reconstruction algorithms are manufacturer dependent and kept secret, our features are used as input to train a support vector machine (SVM) based classifier to discriminate acquisition systems. Experiments conducted on images issued from 15 different CT-scanner models of 4 distinct manufacturers demonstrate that our system identifies the origin of one CT image with a detection rate of at least 94% and that it achieves better performance than sensor pattern noise (SPN) based strategy proposed for general public camera devices.

Acceleration of EM-Based 3D CT Reconstruction Using FPGA

Reducing radiation doses is one of the key concerns in computed tomography (CT) based 3D reconstruction. Although iterative methods such as the expectation maximization (EM) algorithm can be used to address this issue, applying this algorithm to practice is difficult due to the long execution time. Our goal is to decrease this long execution time to an order of a few minutes, so that low-dose 3D reconstruction can be performed even in time-critical events. In this paper we introduce a novel parallel scheme that takes advantage of numerous block RAMs on field-programmable gate arrays (FPGAs). Also, an external memory bandwidth reduction strategy is presented to reuse both the sinogram and the voxel intensity. Moreover, a customized processing engine based on the FPGA is presented to increase overall throughput while reducing the logic consumption. Finally, a hardware and software flow is proposed to quickly construct a design for various CT machines. The complete reconstruction system is implemented on an FPGA-based server-class node. Experiments on actual patient data show that a 26.9 × speedup can be achieved over a 16-thread multicore CPU implementation.

ASSESSMENT OF CLINICAL IMAGE QUALITY IN PAEDIATRIC ABDOMINAL CT EXAMINATIONS: DEPENDENCY ON THE LEVEL OF ADAPTIVE STATISTICAL ITERATIVE RECONSTRUCTION (ASiR) AND THE TYPE OF CONVOLUTION KERNEL

The purpose of this study was to investigate the effect of different combinations of convolution kernel and the level of Adaptive Statistical iterative Reconstruction (ASiR™) on diagnostic image quality as well as visualisation of anatomical structures in paediatric abdominal computed tomography (CT) examinations. Thirty-five paediatric patients with abdominal pain with non-specified pathology undergoing abdominal CT were included in the study. Transaxial stacks of 5-mm-thick images were retrospectively reconstructed at various ASiR levels, in combination with three convolution kernels. Four paediatric radiologists rated the diagnostic image quality and the delineation of six anatomical structures in a blinded randomised visual grading study. Image quality at a given ASiR level was found to be dependent on the kernel, and a more edge-enhancing kernel benefitted from a higher ASiR level. An ASiR level of 70 % together with the Soft™ or Standard™ kernel was suggested to be the optimal combination for paediatric abdominal CT examinations.

AUTOMATIC SEGMENTATION OF PELVIS FOR BRACHYTHERAPY OF PROSTATE

Advanced model-based iterative reconstruction algorithms in quantitative computed tomography (CT) perform automatic segmentation of tissues to estimate material properties of the imaged object. Compared with conventional methods, these algorithms may improve quality of reconstructed images and accuracy of radiation treatment planning. Automatic segmentation of tissues is, however, a difficult task. The aim of this work was to develop and evaluate an algorithm that automatically segments tissues in CT images of the male pelvis. The newly developed algorithm (MK2014) combines histogram matching, thresholding, region growing, deformable model and atlas-based registration techniques for the segmentation of bones, adipose tissue, prostate and muscles in CT images. Visual inspection of segmented images showed that the algorithm performed well for the five analysed images. The tissues were identified and outlined with accuracy sufficient for the dual-energy iterative reconstruction algorithm whose aim is to improve the accuracy of radiation treatment planning in brachytherapy of the prostate.

THE EFFECT OF ADAPTIVE STATISTICAL ITERATIVE RECONSTRUCTION ON THE ASSESSMENT OF DIAGNOSTIC IMAGE QUALITY AND VISUALISATION OF ANATOMICAL STRUCTURES IN PAEDIATRIC CEREBRAL CT EXAMINATIONS

The purpose of this study was to investigate the effect of adaptive statistical iterative reconstruction (ASiR) on the visualisation of anatomical structures and diagnostic image quality in paediatric cerebral computed tomography (CT) examinations. Forty paediatric patients undergoing routine cerebral CT were included in the study. The raw data from CT scans were reconstructed into stacks of 5 mm thick axial images at various levels of ASiR. Three paediatric radiologists rated six questions related to the visualisation of anatomical structures and one question on diagnostic image quality, in a blinded randomised visual grading study. The evaluated anatomical structures demonstrated enhanced visibility with increasing level of ASiR, apart from the cerebrospinal fluid space around the brain. In this study, 60 % ASiR was found to be the optimal level of ASiR for paediatric cerebral CT examinations. This shows that the commonly used 30 % ASiR may not always be the optimal level.

Local and Non-local Regularization Techniques in Emission (PET/SPECT) Tomographic Image Reconstruction Methods

Emission tomographic image reconstruction is an ill-posed problem due to limited and noisy data and various image-degrading effects affecting the data and leads to noisy reconstructions. Explicit regularization, through iterative reconstruction methods, is considered better to compensate for reconstruction-based noise. Local smoothing and edge-preserving regularization methods can reduce reconstruction-based noise. However, these methods produce overly smoothed images or blocky artefacts in the final image because they can only exploit local image properties. Recently, non-local regularization techniques have been introduced, to overcome these problems, by incorporating geometrical global continuity and connectivity present in the objective image. These techniques can overcome drawbacks of local regularization methods; however, they also have certain limitations, such as choice of the regularization function, neighbourhood size or calibration of several empirical parameters involved. This work compares different local and non-local regularization techniques used in emission tomographic imaging in general and emission computed tomography in specific for improved quality of the resultant images.

PARALLELISATION OF THE MODEL-BASED ITERATIVE RECONSTRUCTION ALGORITHM DIRA

New paradigms for parallel programming have been devised to simplify software development on multi-core processors and many-core graphical processing units (GPU). Despite their obvious benefits, the parallelisation of existing computer programs is not an easy task. In this work, the use of the Open Multiprocessing (OpenMP) and Open Computing Language (OpenCL) frameworks is considered for the parallelisation of the model-based iterative reconstruction algorithm DIRA with the aim to significantly shorten the code's execution time. Selected routines were parallelised using OpenMP and OpenCL libraries; some routines were converted from MATLAB to C and optimised. Parallelisation of the code with the OpenMP was easy and resulted in an overall speedup of 15 on a 16-core computer. Parallelisation with OpenCL was more difficult owing to differences between the central processing unit and GPU architectures. The resulting speedup was substantially lower than the theoretical peak performance of the GPU; the cause was explained.

Radiation dose and diagnostic image quality associated with iterative reconstruction in coronary CT angiography: A systematic review

The aim of this systematic review is to evaluate the radiation dose reduction achieved using iterative reconstruction (IR) compared to filtered back projection (FBP) in coronary CT angiography (CCTA) and assess the impact on diagnostic image quality. A systematic search of seven electronic databases was performed to identify all studies using a developed keywords strategy. A total of 14 studies met the criteria and were included in a review analysis. The results showed that there was a significant reduction in radiation dose when using IR compared to FBP (P < 0.05). The mean and standard deviation (SD) difference of CTDIvol and dose-length-product (DLP) were 14.70 ± 6.87 mGy and 186 ± 120 mGy.cm respectively. The mean ± SD difference of effective dose (ED ) was 2.9 ± 1.7 mSv with the range from 1.0 to 5.0 mSv. The assessment of diagnostic image quality showed no significant difference (P > 0.05). The mean ± SD difference of image noise, signal-noise ratio (SNR) and contrast-noise ratio (CNR) were 1.05 ± 1.29 HU, 0.88 ± 0.56 and 0.63 ± 1.83 respectively. The mean ± SD percentages of overall image quality scores were 71.79 ± 12.29% (FBP) and 67.31 ± 22.96% (IR). The mean ± SD percentages of coronary segment analysis were 95.43 ± 2.57% (FBP) and 97.19 ± 2.62% (IR). In conclusion, this review analysis shows that CCTA with the use of IR leads to a significant reduction in radiation dose as compared to the use of FBP. Diagnostic image quality of IR at reduced dose (30-41%) is comparable to FBP at standard dose in the diagnosis of CAD.

Characteristic image quality of a third generation dual-source MDCT scanner: Noise, resolution, and detectability

PURPOSE

The purpose of this work was to assess the inherent image quality characteristics of a new multidetector computed tomography system in terms of noise, resolution, and detectability index as a function of image acquisition and reconstruction for a range of clinically relevant settings.

METHODS

A multisized image quality phantom (37, 30, 23, 18.5, and 12 cm physical diameter) was imaged on a SOMATOM Force scanner (Siemens Medical Solutions) under variable dose, kVp, and tube current modulation settings. Images were reconstructed with filtered back projection (FBP) and with advanced modeled iterative reconstruction (ADMIRE) with iterative strengths of 3, 4, and 5. Image quality was assessed in terms of the noise power spectrum (NPS), task transfer function (TTF), and detectability index for a range of detection tasks (contrasts of approximately 45, 90, 300, -900, and 1000 HU, and 2-20 mm diameter) based on a non-prewhitening matched filter model observer with eye filter.

RESULTS

Image noise magnitude decreased with decreasing phantom size, increasing dose, and increasing ADMIRE strength, offering up to 64% noise reduction relative to FBP. Noise texture in terms of the NPS was similar between FBP and ADMIRE (<5% shift in peak frequency). The resolution, based on the TTF, improved with increased ADMIRE strength by an average of 15% in the TTF 50% frequency for ADMIRE-5. The detectability index increased with increasing dose and ADMIRE strength by an average of 55%, 90%, and 163% for ADMIRE 3, 4, and 5, respectively. Assessing the impact of mA modulation for a fixed average dose over the length of the phantom, detectability was up to 49% lower in smaller phantom sections and up to 26% higher in larger phantom sections for the modulated scan compared to a fixed tube current scan. Overall, the detectability exhibited less variability with phantom size for modulated scans compared to fixed tube current scans.

CONCLUSIONS

Image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose. The use of tube current modulation resulted in more consistent image quality with changing phantom size.

Computed Tomography Angiography: A Review and Technical Update

The principles of computed tomography angiography (CTA) remain the following with modern-day computed tomography (CT): high-resolution volumetric CT data acquisition, imaging at maximum contrast medium enhancement, and subsequent angiographic two- and three-dimensional visualization. One prerequisite for adapting CTA to ever evolving CT technology is understanding the principle rules of contrast medium enhancement. Four key rules of early arterial contrast dynamics can help one understand the relationship between intravenously injected contrast medium and the resulting time-dependent arterial enhancement. The technical evolution of CT has continued with many benefits for CT angiography. Well-informed adaptations of CTA principles allow for leveraging of these innovations for the benefit of patients with cardiovascular diseases.

Interlaced X-ray diffraction computed tomography

An X-ray diffraction computed tomography data-collection strategy that allows, post experiment, a choice between temporal and spatial resolution is reported. This strategy enables time-resolved studies on comparatively short timescales, or alternatively allows for improved spatial resolution if the system under study, or components within it, appear to be unchanging. The application of the method for studying an Mn-Na-W/SiO2 fixed-bed reactor in situ is demonstrated. Additionally, the opportunities to improve the data-collection strategy further, enabling post-collection tuning between statistical, temporal and spatial resolutions, are discussed. In principle, the interlaced scanning approach can also be applied to other pencil-beam tomographic techniques, like X-ray fluorescence computed tomography, X-ray absorption fine structure computed tomography, pair distribution function computed tomography and tomographic scanning transmission X-ray microscopy.

Investigation of cone-beam CT image quality trade-off for image-guided radiation therapy

It is well-known that projections acquired over an angular range slightly over 180° (so-called short scan) are sufficient for fan-beam reconstruction. However, due to practical imaging conditions (projection data and reconstruction image discretization, physical factors, and data noise), the short-scan reconstructions may have different appearances and properties from the full-scan (scans over 360°) reconstructions. Nevertheless, short-scan configurations have been used in applications such as cone-beam CT (CBCT) for head-neck-cancer image-guided radiation therapy (IGRT) that only requires a small field of view due to the potential reduced imaging time and dose. In this work, we studied the image quality trade-off for full, short, and full/short scan configurations with both conventional filtered-backprojection (FBP) reconstruction and iterative reconstruction algorithms based on total-variation (TV) minimization for head-neck-cancer IGRT. Anthropomorphic and Catphan phantoms were scanned at different exposure levels with a clinical scanner used in IGRT. Both visualization- and numerical-metric-based evaluation studies were performed. The results indicate that the optimal exposure level and number of views are in the middle range for both FBP and TV-based iterative algorithms and the optimization is object-dependent and task-dependent. The optimal view numbers decrease with the total exposure levels for both FBP and TV-based algorithms. The results also indicate there are slight differences between FBP and TV-based iterative algorithms for the image quality trade-off: FBP seems to be more in favor of larger number of views while the TV-based algorithm is more robust to different data conditions (number of views and exposure levels) than the FBP algorithm. The studies can provide a general guideline for image-quality optimization for CBCT used in IGRT and other applications.

A Practice Quality Improvement Project: Reducing Dose of Routine Chest CT Imaging in a Busy Clinical Practice

The purpose of this report is to describe our experience with the implementation of a practice quality improvement (PQI) project in thoracic imaging as part of the American Board of Radiology Maintenance of Certification process. The goal of this PQI project was to reduce the effective radiation dose of routine chest CT imaging in a busy clinical practice by employing the iDose(4) (Philips Healthcare) iterative reconstruction technique. The dose reduction strategy was implemented in a stepwise process on a single 64-slice CT scanner with a volume of 1141 chest CT scans during the year. In the first annual quarter, a baseline effective dose was established using the standard filtered back projection (FBP) algorithm protocol and standard parameters such as kVp and mAs. The iDose(4) technique was then applied in the second and third annual quarters while keeping all other parameters unchanged. In the fourth quarter, a reduction in kVp was also implemented. Throughout the process, the images were continually evaluated to assure that the image quality was comparable to the standard protocol from multiple other scanners. Utilizing a stepwise approach, the effective radiation dose was reduced by 23.62 and 43.63 % in quarters two and four, respectively, compared to our initial standard protocol with no perceived difference in diagnostic quality. This practice quality improvement project demonstrated a significant reduction in the effective radiation dose of thoracic CT scans in a busy clinical practice.

Performance evaluation of iterative reconstruction algorithms for achieving CT radiation dose reduction - a phantom study

The purpose of this study was to characterize image quality and dose performance with GE CT iterative reconstruction techniques, adaptive statistical iterative reconstruction (ASiR), and model‐based iterative reconstruction (MBIR), over a range of typical to low‐dose intervals using the Catphan 600 and the anthropomorphic Kyoto Kagaku abdomen phantoms. The scope of the project was to quantitatively describe the advantages and limitations of these approaches. The Catphan 600 phantom, supplemented with a fat‐equivalent oval ring, was scanned using a GE Discovery HD750 scanner at 120 kVp, 0.8 s rotation time, and pitch factors of 0.516, 0.984, and 1.375. The mA was selected for each pitch factor to achieve CTDIvol values of 24, 18, 12, 6, 3, 2, and 1 mGy. Images were reconstructed at 2.5 mm thickness with filtered back‐projection (FBP); 20%, 40%, and 70% ASiR; and MBIR. The potential for dose reduction and low‐contrast detectability were evaluated from noise and contrast‐to‐noise ratio (CNR) measurements in the CTP 404 module of the Catphan. Hounsfield units (HUs) of several materials were evaluated from the cylinder inserts in the CTP 404 module, and the modulation transfer function (MTF) was calculated from the air insert. The results were confirmed in the anthropomorphic Kyoto Kagaku abdomen phantom at 6, 3, 2, and 1 mGy. MBIR reduced noise levels five‐fold and increased CNR by a factor of five compared to FBP below 6 mGy CTDIvol, resulting in a substantial improvement in image quality. Compared to ASiR and FBP, HU in images reconstructed with MBIR were consistently lower, and this discrepancy was reversed by higher pitch factors in some materials. MBIR improved the conspicuity of the high‐contrast spatial resolution bar pattern, and MTF quantification confirmed the superior spatial resolution performance of MBIR versus FBP and ASiR at higher dose levels. While ASiR and FBP were relatively insensitive to changes in dose and pitch, the spatial resolution for MBIR improved with increasing dose and pitch. Unlike FBP, MBIR and ASiR may have the potential for patient imaging at around 1 mGy CTDIvol. The improved low‐contrast detectability observed with MBIR, especially at low‐dose levels, indicate the potential for considerable dose reduction.

PACS number(s): 87.57.Q‐, 87.57,nf, 87.57.C‐, 87.57.cj, 87.57.cf, 87.57.cm, 87.57.uq

A denoising algorithm for projection measurements in cone-beam computed tomography

The ability to reduce the radiation dose in computed tomography (CT) is limited by the excessive quantum noise present in the projection measurements. Sinogram denoising is, therefore, an essential step towards reconstructing high-quality images, especially in low-dose CT. Effective denoising requires accurate modeling of the photon statistics and of the prior knowledge about the characteristics of the projection measurements. This paper proposes an algorithm for denoising low-dose sinograms in cone-beam CT. The proposed algorithm is based on minimizing a cost function that includes a measurement consistency term and two regularizations in terms of the gradient and the Hessian of the sinogram. This choice of the regularization is motivated by the nature of CT projections. We use a split Bregman algorithm to minimize the proposed cost function. We apply the algorithm on simulated and real cone-beam projections and compare the results with another algorithm based on bilateral filtering. Our experiments with simulated and real data demonstrate the effectiveness of the proposed algorithm. Denoising of the projections with the proposed algorithm leads to a significant reduction of the noise in the reconstructed images without oversmoothing the edges or introducing artifacts.

Line Integral Alternating Minimization Algorithm for Dual-Energy X-Ray CT Image Reconstruction

We propose a new algorithm, called line integral alternating minimization (LIAM), for dual-energy X-ray CT image reconstruction. Instead of obtaining component images by minimizing the discrepancy between the data and the mean estimates, LIAM allows for a tunable discrepancy between the basis material projections and the basis sinograms. A parameter is introduced that controls the size of this discrepancy, and with this parameter the new algorithm can continuously go from a two-step approach to the joint estimation approach. LIAM alternates between iteratively updating the line integrals of the component images and reconstruction of the component images using an image iterative deblurring algorithm. An edge-preserving penalty function can be incorporated in the iterative deblurring step to decrease the roughness in component images. Images from both simulated and experimentally acquired sinograms from a clinical scanner were reconstructed by LIAM while varying the regularization parameters to identify good choices. The results from the dual-energy alternating minimization algorithm applied to the same data were used for comparison. Using a small fraction of the computation time of dual-energy alternating minimization, LIAM achieves better accuracy of the component images in the presence of Poisson noise for simulated data reconstruction and achieves the same level of accuracy for real data reconstruction.

[Ultra-low dose chest CT: The end of chest radiograph?]

Ultra-low dose chest CT (ULD-CT) is acquired at a radiation dose lowered to that of a PA and lateral chest X-ray. Its image quality is degraded, yet remains diagnostic in many clinical indications. Technological improvements, with iterative reconstruction at the foreground, allowed a strong increase in the image quality obtained with this examination, which is achievable on most recent (<5 years) scanner. Established clinical indications of ULD-CT are increasing, and its non-inferiority compared to the reference "full dose" chest CT are currently demonstrated for the detection of solid nodules, for asbestos-related pleural diseases screening and for the monitoring of infectious pneumonia. Its current limitations are the obese patients (BMI>35) and the interstitial pneumonia, situations in which their performances are insufficient.

A sinogram denoising algorithm for low-dose computed tomography

BACKGROUND

From the viewpoint of the patients' health, reducing the radiation dose in computed tomography (CT) is highly desirable. However, projection measurements acquired under low-dose conditions will contain much noise. Therefore, reconstruction of high-quality images from low-dose scans requires effective denoising of the projection measurements.

METHODS

We propose a denoising algorithm that is based on maximizing the data likelihood and sparsity in the gradient domain. For Poisson noise, this formulation automatically leads to a locally adaptive denoising scheme. Because the resulting optimization problem is hard to solve and may also lead to artifacts, we suggest an explicitly local denoising method by adapting an existing algorithm for normally-distributed noise. We apply the proposed method on sets of simulated and real cone-beam projections and compare its performance with two other algorithms.

RESULTS

The proposed algorithm effectively suppresses the noise in simulated and real CT projections. Denoising of the projections with the proposed algorithm leads to a substantial improvement of the reconstructed image in terms of noise level, spatial resolution, and visual quality.

CONCLUSION

The proposed algorithm can suppress very strong quantum noise in CT projections. Therefore, it can be used as an effective tool in low-dose CT.

Advanced Modeled Iterative Reconstruction in Low-Tube-Voltage Contrast-Enhanced Neck CT: Evaluation of Objective and Subjective Image Quality

BACKGROUND AND PURPOSE

Dose-saving techniques in neck CT cause increased image noise that can be counteracted by iterative reconstruction. Our aim was to evaluate the image quality of advanced modeled iterative reconstruction (ADMIRE) in contrast-enhanced low-tube-voltage neck CT.

MATERIALS AND METHODS

Sixty-one patients underwent 90-kV(peak) neck CT by using third-generation 192-section dual-source CT. Image series were reconstructed with standard filtered back-projection and ADMIRE strength levels 1, 3, and 5. Attenuation and noise of the sternocleidomastoid muscle, internal jugular vein, submandibular gland, tongue, subscapularis muscle, and cervical fat were measured. Signal-to-noise and contrast-to-noise ratios were calculated. Two radiologists assessed image noise, image contrast, delineation of smaller structures, and overall diagnostic acceptability. Interobserver agreement was calculated.

RESULTS

Image noise was significantly reduced by using ADMIRE compared with filtered back-projection with the lowest noise observed in ADMIRE 5 (filtered back-projection, 9.4 ± 2.4 Hounsfield units [HU]; ADMIRE 1, 8.3 ± 2.8 HU; ADMIRE 3, 6.7 ± 2.0 HU; ADMIRE 5, 5.4 ± 1.7 HU; all, P < .001). Sternocleidomastoid SNR and internal jugular vein-sternocleidomastoid contrast-to-noise ratios were significantly higher for ADMIRE with the best results in ADMIRE 5 (all, P < .001). Subjective image quality and image contrast of ADMIRE 3 and 5 were consistently rated better than those for filtered back-projection and ADMIRE 1 (all, P < .001). Image noise was rated highest for ADMIRE 5 (all, P < .005). Delineation of smaller structures was voted higher in all ADMIRE strength levels compared with filtered back-projection (P < .001). Global interobserver agreement was good (0.75).

CONCLUSIONS

Contrast-enhanced 90-kVp neck CT is feasible, and ADMIRE 5 shows superior objective image quality compared with filtered back-projection. ADMIRE 3 and 5 show the best subjective image quality.

Low-dose CT statistical iterative reconstruction via modified MRF regularization

It is desirable to reduce the excessive radiation exposure to patients in repeated medical CT applications. One of the most effective ways is to reduce the X-ray tube current (mAs) or tube voltage (kVp). However, it is difficult to achieve accurate reconstruction from the noisy measurements. Compared with the conventional filtered back-projection (FBP) algorithm leading to the excessive noise in the reconstructed images, the approaches using statistical iterative reconstruction (SIR) with low mAs show greater image quality. To eliminate the undesired artifacts and improve reconstruction quality, we proposed, in this work, an improved SIR algorithm for low-dose CT reconstruction, constrained by a modified Markov random field (MRF) regularization. Specifically, the edge-preserving total generalized variation (TGV), which is a generalization of total variation (TV) and can measure image characteristics up to a certain degree of differentiation, was introduced to modify the MRF regularization. In addition, a modified alternating iterative algorithm was utilized to optimize the cost function. Experimental results demonstrated that images reconstructed by the proposed method could not only generate high accuracy and resolution properties, but also ensure a higher peak signal-to-noise ratio (PSNR) in comparison with those using existing methods.

Anthropomorphic model observer performance in three-dimensional detection task for low-contrast computed tomography

X-ray medical imaging is increasingly becoming three-dimensional (3-D). The dose to the population and its management are of special concern in computed tomography (CT). Task-based methods with model observers to assess the dose-image quality trade-off are promising tools, but they still need to be validated for real volumetric images. The purpose of the present work is to evaluate anthropomorphic model observers in 3-D detection tasks for low-contrast CT images. We scanned a low-contrast phantom containing four types of signals at three dose levels and used two reconstruction algorithms. We implemented a multislice model observer based on the channelized Hotelling observer (msCHO) with anthropomorphic channels and investigated different internal noise methods. We found a good correlation for all tested model observers. These results suggest that the msCHO can be used as a relevant task-based method to evaluate low-contrast detection for CT and optimize scan protocols to lower dose in an efficient way.

Quantitative Features of Liver Lesions, Lung Nodules, and Renal Stones at Multi-Detector Row CT Examinations: Dependency on Radiation Dose and Reconstruction Algorithm

PURPOSE

To determine if radiation dose and reconstruction algorithm affect the computer-based extraction and analysis of quantitative imaging features in lung nodules, liver lesions, and renal stones at multi-detector row computed tomography (CT).

MATERIALS AND METHODS

Retrospective analysis of data from a prospective, multicenter, HIPAA-compliant, institutional review board-approved clinical trial was performed by extracting 23 quantitative imaging features (size, shape, attenuation, edge sharpness, pixel value distribution, and texture) of lesions on multi-detector row CT images of 20 adult patients (14 men, six women; mean age, 63 years; range, 38-72 years) referred for known or suspected focal liver lesions, lung nodules, or kidney stones. Data were acquired between September 2011 and April 2012. All multi-detector row CT scans were performed at two different radiation dose levels; images were reconstructed with filtered back projection, adaptive statistical iterative reconstruction, and model-based iterative reconstruction (MBIR) algorithms. A linear mixed-effects model was used to assess the effect of radiation dose and reconstruction algorithm on extracted features.

RESULTS

Among the 23 imaging features assessed, radiation dose had a significant effect on five, three, and four of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). Adaptive statistical iterative reconstruction had a significant effect on three, one, and one of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). MBIR reconstruction had a significant effect on nine, 11, and 15 of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). Of note, the measured size of lung nodules and renal stones with MBIR was significantly different than those for the other two algorithms (P < .002 for all comparisons). Although lesion texture was significantly affected by the reconstruction algorithm used (average of 3.33 features affected by MBIR throughout lesion types; P < .002, for all comparisons), no significant effect of the radiation dose setting was observed for all but one of the texture features (P = .002-.998).

CONCLUSION

Radiation dose settings and reconstruction algorithms affect the extraction and analysis of quantitative imaging features in lesions at multi-detector row CT.

Improved image quality of helical computed tomography of the head in children by iterative reconstruction

BACKGROUND AND PURPOSE

Iterative reconstruction (IR) offers noise reduction and improved image quality of computed tomography (CT). Our aim was to assess the imaging quality of non-contrast helical CT of the head in children using IR.

MATERIALS AND METHODS

This study recruited 78 consecutive children aged ≤5 years (range: from 3 months to 5 years; mean: 1.7 years) who underwent an emergent non-enhanced helical CT of the head with no abnormal findings. The acquired data were reconstructed using filtered back projection (FBP) and sinogram-affirmed IR (SAFIRE) with strength levels of 2 (IR2) and 4 (IR4). The imaging quality of FBP, IR2 and IR4 was scored by two experienced neuroradiologists in terms of the contrast between the gray-white matter junction and artifacts from the skull at the level of the semioval center, basal ganglia and fourth ventricle. FBP, IR2 and IR4 scores were compared at each slice level. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated for FBP, IR2 and IR4 and were compared among the three reconstruction algorithms.

RESULTS

The score of IR2 and IR4 was significantly higher than that of FBP in terms of both the contrast between the gray-white matter junction and artifacts from the skull at each slice level (P<0.001). SNR and CNR on IR4 were the highest followed by those on IR2 and FBP (P<0.001).

CONCLUSIONS

IR may improve the image quality of helical CT of the head in children.

Dental cone beam CT: A review

For the maxillofacial region, there are various indications that cannot be interpreted from 2D images and will benefit from multiplanar viewing. Dental cone beam CT (CBCT) utilises a cone- or pyramid-shaped X-ray beam using mostly flat-panel detectors for 3D image reconstruction with high spatial resolution. The vast increase in availability and amount of these CBCT devices offers many clinical benefits, and their ongoing development has potential to bring various new clinical applications for medical imaging. Additionally, there is also a need for high quality research and education. European guidelines promote the use of a medical physics expert for advice on radiation protection, patient dose optimisation, and equipment testing. In this review article, we perform a comparison of technical equipment based on manufacturer data, including scanner specific X-ray spectra, and describe issues concerning CBCT image reconstruction and image quality, and also address radiation dose issues, dosimetry, and optimisation. We also discuss clinical needs and what type of education users should have in order to operate CBCT systems safely. We will also take a look into the future and discuss the issues that still need to be solved.

A Web simulation of medical image reconstruction and processing as an educational tool

Web educational resources integrating interactive simulation tools provide students with an in-depth understanding of the medical imaging process. The aim of this work was the development of a purely Web-based, open access, interactive application, as an ancillary learning tool in graduate and postgraduate medical imaging education, including a systematic evaluation of learning effectiveness. The pedagogic content of the educational Web portal was designed to cover the basic concepts of medical imaging reconstruction and processing, through the use of active learning and motivation, including learning simulations that closely resemble actual tomographic imaging systems. The user can implement image reconstruction and processing algorithms under a single user interface and manipulate various factors to understand the impact on image appearance. A questionnaire for pre- and post-training self-assessment was developed and integrated in the online application. The developed Web-based educational application introduces the trainee in the basic concepts of imaging through textual and graphical information and proceeds with a learning-by-doing approach. Trainees are encouraged to participate in a pre- and post-training questionnaire to assess their knowledge gain. An initial feedback from a group of graduate medical students showed that the developed course was considered as effective and well structured. An e-learning application on medical imaging integrating interactive simulation tools was developed and assessed in our institution.

Spectral response model for a multibin photon-counting spectral computed tomography detector and its applications

Variations among detector channels in computed tomography can lead to ring artifacts in the reconstructed images and biased estimates in projection-based material decomposition. Typically, the ring artifacts are corrected by compensation methods based on flat fielding, where transmission measurements are required for a number of material-thickness combinations. Phantoms used in these methods can be rather complex and require an extensive number of transmission measurements. Moreover, material decomposition needs knowledge of the individual response of each detector channel to account for the detector inhomogeneities. For this purpose, we have developed a spectral response model that binwise predicts the response of a multibin photon-counting detector individually for each detector channel. The spectral response model is performed in two steps. The first step employs a forward model to predict the expected numbers of photon counts, taking into account parameters such as the incident x-ray spectrum, absorption efficiency, and energy response of the detector. The second step utilizes a limited number of transmission measurements with a set of flat slabs of two absorber materials to fine-tune the model predictions, resulting in a good correspondence with the physical measurements. To verify the response model, we apply the model in two cases. First, the model is used in combination with a compensation method which requires an extensive number of transmission measurements to determine the necessary parameters. Our spectral response model successfully replaces these measurements by simulations, saving a significant amount of measurement time. Second, the spectral response model is used as the basis of the maximum likelihood approach for projection-based material decomposition. The reconstructed basis images show a good separation between the calcium-like material and the contrast agents, iodine and gadolinium. The contrast agent concentrations are reconstructed with more than 94% accuracy.

Limiting CT radiation dose in children with craniosynostosis: phantom study using model-based iterative reconstruction

BACKGROUND

Medical professionals need to exercise particular caution when developing CT scanning protocols for children who require multiple CT studies, such as those with craniosynostosis.

OBJECTIVE

To evaluate the utility of ultra-low-dose CT protocols with model-based iterative reconstruction techniques for craniosynostosis imaging.

MATERIALS AND METHODS

We scanned two pediatric anthropomorphic phantoms with a 64-slice CT scanner using different low-dose protocols for craniosynostosis. We measured organ doses in the head region with metal-oxide-semiconductor field-effect transistor (MOSFET) dosimeters. Numerical simulations served to estimate organ and effective doses. We objectively and subjectively evaluated the quality of images produced by adaptive statistical iterative reconstruction (ASiR) 30%, ASiR 50% and Veo (all by GE Healthcare, Waukesha, WI). Image noise and contrast were determined for different tissues.

RESULTS

Mean organ dose with the newborn phantom was decreased up to 83% compared to the routine protocol when using ultra-low-dose scanning settings. Similarly, for the 5-year phantom the greatest radiation dose reduction was 88%. The numerical simulations supported the findings with MOSFET measurements. The image quality remained adequate with Veo reconstruction, even at the lowest dose level.

CONCLUSION

Craniosynostosis CT with model-based iterative reconstruction could be performed with a 20-μSv effective dose, corresponding to the radiation exposure of plain skull radiography, without compromising required image quality.

Development of a fan-beam TDLAS-based tomographic sensor for rapid imaging of temperature and gas concentration

This work aims to develop a fan-beam tomographic sensor using tunable diode lasers that can simultaneously image temperature and gas concentration with both high spatial and temporal resolutions. The sensor features three key advantages. First, the sensor bases on a stationary fan-beam arrangement, by which a high spatial resolution is guaranteed because the distance between two neighboring detectors in a view is approximately reduced to the size of a photodiode. Second, fan-beam illumination from five views is simultaneously generated instead of rotating either the fanned beams or the target, which significantly enhances the temporal resolution. Third, a novel set of optics with the combination of anamorphic prism pair and cylindrical lens is designed, which greatly improves the uniformity of the planar beams, and hence improves the reconstruction fidelity. This paper reports the tomographic model, optics design, numerical simulation and experimental validation of the sensor. The sensor exhibits good applicability for flame monitoring and combustion diagnosis.

Image Quality of 3rd Generation Spiral Cranial Dual-Source CT in Combination with an Advanced Model Iterative Reconstruction Technique: A Prospective Intra-Individual Comparison Study to Standard Sequential Cranial CT Using Identical Radiation Dose

Objectives

To prospectively intra-individually compare image quality of a 3^rd generation Dual-Source-CT (DSCT) spiral cranial CT (cCT) to a sequential 4-slice Multi-Slice-CT (MSCT) while maintaining identical intra-individual radiation dose levels.

Methods

35 patients, who had a non-contrast enhanced sequential cCT examination on a 4-slice MDCT within the past 12 months, underwent a spiral cCT scan on a 3^rd generation DSCT. CTDI_vol identical to initial 4-slice MDCT was applied. Data was reconstructed using filtered backward projection (FBP) and 3^rd-generation iterative reconstruction (IR) algorithm at 5 different IR strength levels. Two neuroradiologists independently evaluated subjective image quality using a 4-point Likert-scale and objective image quality was assessed in white matter and nucleus caudatus with signal-to-noise ratios (SNR) being subsequently calculated.

Results

Subjective image quality of all spiral cCT datasets was rated significantly higher compared to the 4-slice MDCT sequential acquisitions (p<0.05). Mean SNR was significantly higher in all spiral compared to sequential cCT datasets with mean SNR improvement of 61.65% (p*_{Bonferroni0.05}<0.0024). Subjective image quality improved with increasing IR levels.

Conclusion

Combination of 3^rd-generation DSCT spiral cCT with an advanced model IR technique significantly improves subjective and objective image quality compared to a standard sequential cCT acquisition acquired at identical dose levels.

CT Metal Artifact Reduction in the Spine: Can an Iterative Reconstruction Technique Improve Visualization?

BACKGROUND AND PURPOSE

Metal-related artifacts from spine instrumentation can obscure relevant anatomy and pathology. We evaluated the ability of CT images reconstructed with and without iterative metal artifact reduction to visualize critical anatomic structures in postoperative spines and assessed the potential for implementation into clinical practice.

MATERIALS AND METHODS

We archived CT projection data in patients with instrumented spinal fusion. CT images were reconstructed by using weighted filtered back-projection and iterative metal artifact reduction. Two neuroradiologists evaluated images in the region of spinal hardware and assigned a score for the visualization of critical anatomic structures by using soft-tissue and bone windows (critical structures totally obscured, n = 0; anatomic recognition with high diagnostic confidence, n = 5). Using bone windows, we measured the length of the most pronounced linear artifacts. For each patient, neuroradiologists made recommendations regarding the optimal use of iterative metal artifact reduction and its impact on diagnostic confidence.

RESULTS

Sixty-eight patients met the inclusion criteria. Visualization of critical soft-tissue anatomic structures was significantly improved by using iterative metal artifact reduction compared with weighted filtered back-projection (median, 1 ± 1.5 versus 3 ± 1.3, P < .001), with improvement in the worst visualized anatomic structure in 88% (60/68) of patients. There was not significant improvement in visualization of critical osseous structures. Linear metal artifacts were reduced from 29 to 11 mm (P < .001). In 87% of patients, neuroradiologists recommended reconstructing iterative metal artifact reduction images instead of weighted filtered back-projection images, with definite improvement in diagnostic confidence in 32% (22/68).

CONCLUSIONS

Iterative metal artifact reduction improves visualization of critical soft-tissue structures in patients with spinal hardware. Routine generation of these images in addition to routine weighted filtered back-projection is recommended.

Impact of Dose-Modified Protocols on Radiation Doses in Patients Undergoing CT Examinations following Image-Guided Catheter Placement

PURPOSE

To investigate the impact of dose-modified (DM) scan protocols on decreasing radiation exposure from computed tomography (CT) scans obtained following image-guided catheter procedures.

MATERIALS AND METHODS

In this retrospective analysis, between December 2012 and June 2014, 192 patients (mean age, 60.7 y; 102 men) who underwent abdomen/pelvis CT examinations for catheter placement follow-up were included. The standard-dose (SD) baseline CT parameters included tube potential of 120 kVp, tube current of 75-550 mA, and noise index (NI) of 18-22. Weight-based scan parameters applied for follow-up CT were based on two reconstruction algorithms: filtered back projection (FBP; 120 kVp, 75-350 mA, NI = 30) and iterative reconstruction technique (IRT; 100/120 kVp, 75-250/350 mA, NI = 35). Two readers reviewed image quality (IQ) of follow-up and baseline CT examinations for 22 randomly sampled patients. Radiation doses were retrieved by dose monitoring software.

RESULTS

Compared with baseline, DM follow-up CT protocols enabled substantial (62.4%) dose reductions (mean CT dose indexes: 4.1 mGy at follow-up, 10.9 mGy at baseline; P < .0001). Doses were significantly lower for IRT follow-up CT examinations compared with FBP (mean CT dose indexes: IRT, 3.6 mGy; FBP, 4.6 mGy; P < .05). In 47 patients with more than one follow-up CT examination (mean, 3.1 examinations per patient; range, 2-6), the observed cumulative radiation dose (CRD) was 42.1% lower than the expected CRD (observed, 1,437.9 mGy·cm; expected, 2,483.6 mGy·cm; P < .0001). Subjective IQ scores were acceptable for follow-up CT examinations (follow-up, 3.6; baseline, 4; P < .05).

CONCLUSIONS

DM CT examinations enable substantial dose reduction (62.4%) for each follow-up examination compared with SD baseline scans, without any IQ concerns. Use of IRT decreases dose by an additional 22%. The CRD is lowered by 42% in patients undergoing multiple DM follow-up CT examinations.

Evidence of dose saving in routine CT practice using iterative reconstruction derived from a national diagnostic reference level survey

OBJECTIVE

To assess the influence and significance of the use of iterative reconstruction (IR) algorithms on patient dose in CT in Australia.

METHODS

We examined survey data submitted to the Australian Radiation Protection and Nuclear Safety Agency (ARPANSA) National Diagnostic Reference Level Service (NDRLS) during 2013 and 2014. We compared median survey dose metrics with categorization by scan region and use of IR.

RESULTS

The use of IR results in a reduction in volume CT dose index of between 17% and 44% and a reduction in dose-length product of between 14% and 34% depending on the specific scan region. The reduction was highly significant (p < 0.001, Wilcoxon rank-sum test) for all six scan regions included in the NDRLS. Overall, 69% (806/1167) of surveys included in the analysis used IR.

CONCLUSION

The use of IR in CT is achieving dose savings of 20-30% in routine practice in Australia. IR appears to be widely used by participants in the ARPANSA NDRLS with approximately 70% of surveys submitted employing this technique.

ADVANCES IN KNOWLEDGE

This study examines the impact of the use of IR on patient dose in CT on a national scale.

NUFFT-Based Iterative Image Reconstruction via Alternating Direction Total Variation Minimization for Sparse-View CT

Sparse-view imaging is a promising scanning method which can reduce the radiation dose in X-ray computed tomography (CT). Reconstruction algorithm for sparse-view imaging system is of significant importance. The adoption of the spatial iterative algorithm for CT image reconstruction has a low operation efficiency and high computation requirement. A novel Fourier-based iterative reconstruction technique that utilizes nonuniform fast Fourier transform is presented in this study along with the advanced total variation (TV) regularization for sparse-view CT. Combined with the alternating direction method, the proposed approach shows excellent efficiency and rapid convergence property. Numerical simulations and real data experiments are performed on a parallel beam CT. Experimental results validate that the proposed method has higher computational efficiency and better reconstruction quality than the conventional algorithms, such as simultaneous algebraic reconstruction technique using TV method and the alternating direction total variation minimization approach, with the same time duration. The proposed method appears to have extensive applications in X-ray CT imaging.

Towards the clinical implementation of iterative low-dose cone-beam CT reconstruction in image-guided radiation therapy: cone/ring artifact correction and multiple GPU implementation

PURPOSE

Compressed sensing (CS)-based iterative reconstruction (IR) techniques are able to reconstruct cone-beam CT (CBCT) images from undersampled noisy data, allowing for imaging dose reduction. However, there are a few practical concerns preventing the clinical implementation of these techniques. On the image quality side, data truncation along the superior-inferior direction under the cone-beam geometry produces severe cone artifacts in the reconstructed images. Ring artifacts are also seen in the half-fan scan mode. On the reconstruction efficiency side, the long computation time hinders clinical use in image-guided radiation therapy (IGRT).

METHODS

Image quality improvement methods are proposed to mitigate the cone and ring image artifacts in IR. The basic idea is to use weighting factors in the IR data fidelity term to improve projection data consistency with the reconstructed volume. In order to improve the computational efficiency, a multiple graphics processing units (GPUs)-based CS-IR system was developed. The parallelization scheme, detailed analyses of computation time at each step, their relationship with image resolution, and the acceleration factors were studied. The whole system was evaluated in various phantom and patient cases.

RESULTS

Ring artifacts can be mitigated by properly designing a weighting factor as a function of the spatial location on the detector. As for the cone artifact, without applying a correction method, it contaminated 13 out of 80 slices in a head-neck case (full-fan). Contamination was even more severe in a pelvis case under half-fan mode, where 36 out of 80 slices were affected, leading to poorer soft tissue delineation and reduced superior-inferior coverage. The proposed method effectively corrects those contaminated slices with mean intensity differences compared to FDK results decreasing from ∼497 and ∼293 HU to ∼39 and ∼27 HU for the full-fan and half-fan cases, respectively. In terms of efficiency boost, an overall 3.1 × speedup factor has been achieved with four GPU cards compared to a single GPU-based reconstruction. The total computation time is ∼30 s for typical clinical cases.

CONCLUSIONS

The authors have developed a low-dose CBCT IR system for IGRT. By incorporating data consistency-based weighting factors in the IR model, cone/ring artifacts can be mitigated. A boost in computational efficiency is achieved by multi-GPU implementation.

An assessment of image distortion and CT number accuracy within a wide-bore CT extended field of view

Although wide bore computed tomography (CT) scanners provide increased space for patients, the scan field of view (sFOV) remains considerably smaller than the bore size. Consequently, patient anatomy which spans beyond the sFOV is truncated and the information is lost. As a solution, some manufacturers provide the capacity to reconstruct CT images from a partial dataset at an extended field of view (eFOV). To assess spatial distortion within this eFOV three phantoms were considered a 30 × 30 × 20 cm(3) slab of solid water, the Gammex electron density CT phantom and a female anthropomorphic phantom. For each phantom, scans were taken centrally within the sFOV as a reference image and with the phantom edge extended at 1 cm intervals from 0 to 5 cm beyond the sFOV into the eFOV. To assess CT number accuracy various tissue equivalent materials were scanned in the eFOV and resulting CT numbers were compared to inserts scanned within the sFOV. For all phantom geometries, objects within the eFOV were geometrically overestimated with elongation of phantom shapes into the eFOV. The percentage increase in size ranged from 0.22 to 15.94 % over all phantoms considered. The difference between eFOV and sFOV CT numbers was dependent upon insert density. The eFOV underestimated CT numbers in the range of -127 to -230 HU for soft tissue densities and -278 to -640 for bone densities. This trend reversed for low tissue densities with the CT numbers in the eFOV being overestimated by 100-130 HU for lung equivalent inserts. Initial correlation between eFOV and sFOV CT numbers was seen and a correction function was successfully applied to better estimate the CT number representative of that seen within the sFOV.