Radiation dose reduction in computed tomography: techniques and future perspective

Does an elevated bony ridge along the course of the metopic suture equal metopic synostosis? Implications for management

Metopic synostosis represents an increasingly prevalent form of nonsyndromic craniosynostosis. Premature fusion of the metopic suture classically results in trigonocephaly, hypotelorism, temporal narrowing, and a pronounced midline forehead ridge. However, as varying degrees of skull deformity exist, there is confusion regarding the appropriate management for an infant with a metopic ridge. We report on a 2-month-old infant with clinical manifestations of metopic synostosis but with a patent metopic suture documented on computed tomography scan. We examine the implications for management related to fusion of the suture, age of the patient, and severity of the head deformity.

Deterministic absorbed dose estimation in computed tomography using a discrete ordinates method

PURPOSE

Organ dose estimation for a patient undergoing computed tomography (CT) scanning is very important. Although Monte Carlo methods are considered gold-standard in patient dose estimation, the computation time required is formidable for routine clinical calculations. Here, the authors instigate a deterministic method for estimating an absorbed dose more efficiently.

METHODS

Compared with current Monte Carlo methods, a more efficient approach to estimating the absorbed dose is to solve the linear Boltzmann equation numerically. In this study, an axial CT scan was modeled with a software package, Denovo, which solved the linear Boltzmann equation using the discrete ordinates method. The CT scanning configuration included 16 x-ray source positions, beam collimators, flat filters, and bowtie filters. The phantom was the standard 32 cm CT dose index (CTDI) phantom. Four different Denovo simulations were performed with different simulation parameters, including the number of quadrature sets and the order of Legendre polynomial expansions. A Monte Carlo simulation was also performed for benchmarking the Denovo simulations. A quantitative comparison was made of the simulation results obtained by the Denovo and the Monte Carlo methods.

RESULTS

The difference in the simulation results of the discrete ordinates method and those of the Monte Carlo methods was found to be small, with a root-mean-square difference of around 2.4%. It was found that the discrete ordinates method, with a higher order of Legendre polynomial expansions, underestimated the absorbed dose near the center of the phantom (i.e., low dose region). Simulations of the quadrature set 8 and the first order of the Legendre polynomial expansions proved to be the most efficient computation method in the authors' study. The single-thread computation time of the deterministic simulation of the quadrature set 8 and the first order of the Legendre polynomial expansions was 21 min on a personal computer.

CONCLUSIONS

The simulation results showed that the deterministic method can be effectively used to estimate the absorbed dose in a CTDI phantom. The accuracy of the discrete ordinates method was close to that of a Monte Carlo simulation, and the primary benefit of the discrete ordinates method lies in its rapid computation speed. It is expected that further optimization of this method in routine clinical CT dose estimation will improve its accuracy and speed.

Computed Tomography Angiography of Carotid Arteries and Vertebrobasilar System: A Simulation Study for Radiation Dose Reduction

Computed tomography angiography (CTA) of carotid arteries and vertebrobasilar system is a standardized procedure with excellent image quality, but radiation exposure remains a matter of concern. The aim of this study is to examine to what extent radiation dose can be lowered in relation to a standard protocol by simulating examinations with lower tube currents applying a dedicated software.Lower tube current was simulated by a dedicated noise insertion and reconstruction software (ReconCT). In a phantom study, true scans were performed with different dose protocols and compared to the results of simulated dose reductions of the same degree, respectively. In a patient study, 30 CTAs of supra-aortic vessels were reconstructed at a level of 100%, 75%, 50%, and 25% of the initial dose. Objective and subjective image analyses were performed.No significant noise differences between true scans and simulated scans of mimicked contrasted vessels were found. In the patient study, the quality scores of the 4 dose groups differed statistically significant; this difference vanished for the comparison of the 100% and 75% datasets after dichotomization into the categories of diagnostic and nondiagnostic image quality (P = .50).This study suggests an easy-to-implement method of simulating CTAs of carotid arteries and vertebrobasilar system with lower tube current for dose reduction by artificially adding noise to the original raw data. Lowering the radiation dose in a moderate extent to 75% of the original dose levels does not significantly alter the diagnostic image quality.

Virtual single-source computed tomography using dual-source acquisition: a new technique for the dose-neutral intraindividual comparison of different scan protocols

OBJECTIVES

The objective of this study was to compare the image quality of a standard single-source (SSS) computed tomography (CT) with that of a virtual single-source CT (VSS-CT) data set reconstructed from 2 raw data sets obtained by dual-source CT acquisition in abdominal CT to establish a radiation dose-neutral approach for the intraindividual comparison of 3 acquisition protocols at different radiation dose levels (RDLs).

MATERIALS AND METHODS

An abdominal phantom representing an 80-kg male was imaged using dual-source CT (SOMATOM Definition; Siemens Healthcare) at 3 RDLs with 120 kV(p) and different tube currents (low, standard, and high milliampere-second protocol). For each RDL, raw data were obtained once in single-source mode using x-ray tube A only and 5 times in dual-source mode using different ratios for tube current of x-ray tubes A and B (same total radiation dose; A/B: 90%/10%, 80%/20%, 70%/30%, 60%/40%, 50%/50%). For each RDL, SSS-CT and 5 virtual single-source image data sets (VSS-CT50 - 90) were reconstructed. To compare SSS-CT and VSS-CT data sets, image quality was assessed in terms of high- and low-contrast performance by calculating the modulation transfer function, image noise, noise power spectrum, and, for low contrast lesion detectability, the modified multiscale structural similarity index (MS-SSIM*). A maximum decrease of Δ = 5% of image quality compared with SSS-CT was defined as acceptable, and a noninferiority analysis with Δ was performed.

RESULTS

For modulation transfer function, noninferiority was observed for all VSS-CT data sets and RDL (P < 0.05). Image noise demonstrated an acceptable increase (<3.2%, P < 0.05) for each RDL and noise power spectrum showed only minor differences in the midfrequency range. The MS-SSIM* index demonstrated for the high RDL protocol a minor decrease for VSS-CT data sets (<2%, P < 0.05). For the standard and low RDL, the relative differences of the MS-SSIM* index increased and were only in 1 case above Δ (standard RDL, mean VSS-CT80 5.1%, P > 0.05).

CONCLUSIONS

The image quality obtained by virtual and SSS reconstruction using equivalent total radiation exposure to the patient showed only negligible differences in image quality. Therefore, this technique might allow an intraindividual comparison of full and reduced radiation dose protocols within 1 image acquisition step by simply splitting the radiation dose between the 2 x-ray tubes of a dual-source CT.

Observer Performance in the Detection and Classification of Malignant Hepatic Nodules and Masses with CT Image-Space Denoising and Iterative Reconstruction

PURPOSE

To determine if lower-dose computed tomographic (CT) scans obtained with adaptive image-based noise reduction (adaptive nonlocal means [ANLM]) or iterative reconstruction (sinogram-affirmed iterative reconstruction [SAFIRE]) result in reduced observer performance in the detection of malignant hepatic nodules and masses compared with routine-dose scans obtained with filtered back projection (FBP).

MATERIALS AND METHODS

This study was approved by the institutional review board and was compliant with HIPAA. Informed consent was obtained from patients for the retrospective use of medical records for research purposes. CT projection data from 33 abdominal and 27 liver or pancreas CT examinations were collected (median volume CT dose index, 13.8 and 24.0 mGy, respectively). Hepatic malignancy was defined by progression or regression or with histopathologic findings. Lower-dose data were created by using a validated noise insertion method (10.4 mGy for abdominal CT and 14.6 mGy for liver or pancreas CT) and images reconstructed with FBP, ANLM, and SAFIRE. Four readers evaluated routine-dose FBP images and all lower-dose images, circumscribing liver lesions and selecting diagnosis. The jackknife free-response receiver operating characteristic figure of merit (FOM) was calculated on a per-malignant nodule or per-mass basis. Noninferiority was defined by the lower limit of the 95% confidence interval (CI) of the difference between lower-dose and routine-dose FOMs being less than -0.10.

RESULTS

Twenty-nine patients had 62 malignant hepatic nodules and masses. Estimated FOM differences between lower-dose FBP and lower-dose ANLM versus routine-dose FBP were noninferior (difference: -0.041 [95% CI: -0.090, 0.009] and -0.003 [95% CI: -0.052, 0.047], respectively). In patients with dedicated liver scans, lower-dose ANLM images were noninferior (difference: +0.015 [95% CI: -0.077, 0.106]), whereas lower-dose FBP images were not (difference -0.049 [95% CI: -0.140, 0.043]). In 37 patients with SAFIRE reconstructions, the three lower-dose alternatives were found to be noninferior to the routine-dose FBP.

CONCLUSION

At moderate levels of dose reduction, lower-dose FBP images without ANLM or SAFIRE were noninferior to routine-dose images for abdominal CT but not for liver or pancreas CT.

Adaptively Tuned Iterative Low Dose CT Image Denoising

Improving image quality is a critical objective in low dose computed tomography (CT) imaging and is the primary focus of CT image denoising. State-of-the-art CT denoising algorithms are mainly based on iterative minimization of an objective function, in which the performance is controlled by regularization parameters. To achieve the best results, these should be chosen carefully. However, the parameter selection is typically performed in an ad hoc manner, which can cause the algorithms to converge slowly or become trapped in a local minimum. To overcome these issues a noise confidence region evaluation (NCRE) method is used, which evaluates the denoising residuals iteratively and compares their statistics with those produced by additive noise. It then updates the parameters at the end of each iteration to achieve a better match to the noise statistics. By combining NCRE with the fundamentals of block matching and 3D filtering (BM3D) approach, a new iterative CT image denoising method is proposed. It is shown that this new denoising method improves the BM3D performance in terms of both the mean square error and a structural similarity index. Moreover, simulations and patient results show that this method preserves the clinically important details of low dose CT images together with a substantial noise reduction.

Few-View Prereconstruction Guided Tube Current Modulation Strategy Based on the Signal-to-Noise Ratio of the Sinogram

The radiation dose reduction without sacrificing the image quality as an important issue has raised the attention of CT manufacturers and different automatic exposure control (AEC) strategies have been adopted in their products. In this paper, we focus on the strategy of tube current modulation. It is deduced based on the signal-to-noise (SNR) of the sinogram. The main idea behind the proposed modulation strategy is to keep the SNR of the sinogram proximately invariable using the few-view reconstruction as a good reference because it directly affects the noise level of the reconstructions. The numerical experiment results demonstrate that, compared with constant tube current, the noise distribution is more uniform and the SNR and CNR of the reconstruction are better when the proposed strategy is applied. Furthermore it has the potential to distinguish the low-contrast target and to reduce the radiation dose.

Construction of Realistic Liver Phantoms from Patient Images using 3D Printer and Its Application in CT Image Quality Assessment

The purpose of this study is to use 3D printing techniques to construct a realistic liver phantom with heterogeneous background and anatomic structures from patient CT images, and to use the phantom to assess image quality with filtered backprojection and iterative reconstruction algorithms. Patient CT images were segmented into liver tissues, contrast-enhanced vessels, and liver lesions using commercial software, based on which stereolithography (STL) files were created and sent to a commercial 3D printer. A 3D liver phantom was printed after assigning different printing materials to each object to simulate appropriate attenuation of each segmented object. As high opacity materials are not available for the printer, we printed hollow vessels and filled them with iodine solutions of adjusted concentration to represent enhance levels in contrast-enhanced liver scans. The printed phantom was then placed in a 35×26 cm oblong-shaped water phantom and scanned repeatedly at 4 dose levels. Images were reconstructed using standard filtered backprojection and an iterative reconstruction algorithm with 3 different strength settings. Heterogeneous liver background were observed from the CT images and the difference in CT numbers between lesions and background were representative for low contrast lesions in liver CT studies. CT numbers in vessels filled with iodine solutions represented the enhancement of liver arteries and veins. Images were run through a Channelized Hotelling model observer with Garbor channels and ROC analysis was performed. The AUC values showed performance improvement using the iterative reconstruction algorithm and the amount of improvement increased with strength setting.

Statistical image reconstruction for low-dose CT using nonlocal means-based regularization. Part II: An adaptive approach

To reduce radiation dose in X-ray computed tomography (CT) imaging, one common strategy is to lower the tube current and exposure time settings during projection data acquisition. However, this strategy would inevitably increase the projection data noise, and the resulting image by the conventional filtered back-projection (FBP) method may suffer from excessive noise and streak artifacts. The well-known edge-preserving nonlocal means (NLM) filtering can reduce the noise-induced artifacts in the FBP reconstructed image, but it sometimes cannot completely eliminate the artifacts, especially under the very low-dose circumstance when the image is severely degraded. Instead of taking NLM filtering, we proposed a NLM-regularized statistical image reconstruction scheme, which can effectively suppress the noise-induced artifacts and significantly improve the reconstructed image quality. From our previous investigation on NLM-based strategy, we noted that using a spatially invariant filtering parameter in the regularization was rarely optimal for the entire field of view (FOV). Therefore, in this study we developed a novel strategy for designing spatially variant filtering parameters which are adaptive to the local characteristics of the image to be reconstructed. This adaptive NLM-regularized statistical image reconstruction method was evaluated with low-contrast phantoms and clinical patient data to show (1) the necessity in introducing the spatial adaptivity and (2) the efficacy of the adaptivity in achieving superiority in reconstructing CT images from low-dose acquisitions.

Detection of pure ground-glass nodules in the lung by low-dose multi-detector computed tomography, with use of an iterative reconstruction method: a comparison with conventional image reconstruction by the filtered back-projection method

PURPOSE

To evaluate the feasibility of the iterative reconstruction (IR) method with low-dose multi-detector computed tomography (MDCT) for lung cancer screening.

MATERIALS AND METHODS

A chest CT phantom containing simulated ground-glass nodules (GGNs) of 5 different sizes was scanned by use of 16-row and 64-row MDCT. Tube currents of 10, 20, and 30 mA were used for the low-dose CT. To assess the detectability of pure GGNs, a radiologist-performance test was conducted. Mean visual scores for simulated GGNs were compared for reconstructed images from filtered back-projection (FBP) and the IR method.

RESULTS

When 64-row MDCT was used, visual scores for simulated GGNs were significantly higher for the IR method than for the FBP method under any conditions; scores were also significantly higher for 16-row MDCT under some conditions.

CONCLUSIONS

The results of this experimental chest phantom study showed that use of the IR method improved the detectability of simulated pure GGNs.

Value of gadolinium-enhanced MRI in detection of acute appendicitis in children and adolescents

OBJECTIVE

The aim of this study was to determine both the value of gadolinium-enhanced MRI in children with suspected acute appendicitis and the best sequences for detecting acute appendicitis, to thereby decrease imaging time.

MATERIALS AND METHODS

This was a retrospective review of pediatric patients with suspected appendicitis who had undergone MRI at our institution between 2010 and 2011 after an indeterminate ultrasound examination. MRI examinations included T1-weighted unenhanced and contrast-enhanced, T2-weighted, and balanced steady-state free precession (SSFP) sequences in axial and coronal planes. Sequences were reviewed together and individually by five radiologists who were blinded to the final diagnosis. Radiologists were asked to score their confidence of appendicitis diagnosis using a 5-point scale. The diagnostic performance of each MR sequence was obtained by comparing the mean area under the curve (AUC) using receiver operating characteristic (ROC) analysis.

RESULTS

A total of 49 patients with clinically suspected appendicitis were included, of whom 16 received a diagnosis of appendicitis. The mean AUCs for reviewing all sequences together, contrast-enhanced sequences alone, T2-weighted sequences alone, and balanced SSFP alone were 0.984, 0.979, 0.944, and 0.910, respectively. No significant difference was observed between reviewing all sequences together versus contrast-enhanced sequences alone (p = 0.90) and T2-weighted sequences alone (p = 0.23). A significant difference was observed between contrast-enhanced sequences and balanced SSFP (p < 0.03).

CONCLUSION

Gadolinium-enhanced images and T2-weighted images are most helpful in the assessment of acute appendicitis in the pediatric population. These findings have led to protocol modifications that have reduced imaging time.

Radiation dose reduction in CBCT imaging using K-edge filtering and energy weighting

This paper presents K-edge filtering and energy weighting methods which enhance the contrast with less radiation does. Usually, energy weighting methods are used with photon-counting detector based CT for each energy bin data obtained to enhance the quality of image. However, we used these methods combine with K-edge filtering in energy-integrating detector. Using K-edge filtering, different energy bin data for energy weighting methods were obtained, and then energy weighting factors were calculated to enhance the contrast of image. We report an evaluation of the contrast-to-noise ratio (CNR) of reconstructed image with and without these two methods. This evaluation was proceeded with two phantoms; one is the phantom created personally, and the other is Sendentexct IQ dental CBCT (SENDENTEXCT, EU). As for the phantom created personally, the CNR of images reconstructed with these methods were increased than CNR of standard images. It was seen that 31% to 81% in each energy weighting method for optimizing each material (cortical bone, inner bone, soft tissue, iodine (18.5 g/l), iodine (37 g/l)). In conclusion, we can enhance the contrast of CT images with less radiation dose using K-edge filtering and energy weighting method.

EMPIRICAL AVERAGE-CASE RELATION BETWEEN UNDERSAMPLING AND SPARSITY IN X-RAY CT

In X-ray computed tomography (CT) it is generally acknowledged that reconstruction methods exploiting image sparsity allow reconstruction from a significantly reduced number of projections. The use of such reconstruction methods is inspired by recent progress in compressed sensing (CS). However, the CS framework provides neither guarantees of accurate CT reconstruction, nor any relation between sparsity and a sufficient number of measurements for recovery, i.e., perfect reconstruction from noise-free data. We consider reconstruction through 1-norm minimization, as proposed in CS, from data obtained using a standard CT fan-beam sampling pattern. In empirical simulation studies we establish quantitatively a relation between the image sparsity and the sufficient number of measurements for recovery within image classes motivated by tomographic applications. We show empirically that the specific relation depends on the image class and in many cases exhibits a sharp phase transition as seen in CS, i.e., same-sparsity images require the same number of projections for recovery. Finally we demonstrate that the relation holds independently of image size and is robust to small amounts of additive Gaussian white noise.

A Longitudinal Low Dose μCT Analysis of Bone Healing in Mice: A Pilot Study

Low dose microcomputed tomography (μCT) is a recently matured technique that enables the study of longitudinal bone healing and the testing of experimental treatments for bone repair. This imaging technique has been used for studying craniofacial repair in mice but not in an orthopedic context. This is mainly due to the size of the defects (approximately 1.0 mm) in long bone, which heal rapidly and may thus negatively impact the assessment of the effectiveness of experimental treatments. We developed a longitudinal low dose μCT scan analysis method combined with a new image segmentation and extraction software using Hounsfield unit (HU) scores to quantitatively monitor bone healing in small femoral cortical defects in live mice. We were able to reproducibly quantify bone healing longitudinally over time with three observers. We used high speed intramedullary reaming to prolong healing in order to circumvent the rapid healing typical of small defects. Bone healing prolongation combined with μCT imaging to study small bone defects in live mice thus shows potential as a promising tool for future preclinical research on bone healing.

Advances in diagnostic imaging for pathologic conditions of the jaws

Advances in dental and maxillofacial imaging are delineated along with the advantages and disadvantages of each imaging modality. The imaging modalities that are included are intraoral radiography, panoramic radiography, cone-beam computed tomography, multidetector computed tomography, magnetic resonance imaging, nuclear medicine, and ultrasound.

CT protocol review and optimization

To reduce the radiation dose associated with CT scans, much attention is focused on CT protocol review and improvement. In fact, annual protocol reviews will soon be required for ACR CT accreditation. A major challenge in the protocol review process is determining whether a current protocol is optimal and deciding what steps to take to improve it. In this paper, the authors describe methods for pinpointing deficiencies in CT protocols and provide a systematic approach for optimizing them. Emphasis is placed on a team approach, with a team consisting of at least one radiologist, one physicist, and one technologist. This core team completes a critical review of all aspects of a CT protocol and carefully evaluates proposed improvements. Changes to protocols are implemented only with consensus of the core team, with consideration of all aspects of the CT examination, including image quality, radiation dose, patient care and safety, and workflow.

Optimizing CT radiation dose based on patient size and image quality: the size-specific dose estimate method

The principle of ALARA (dose as low as reasonably achievable) calls for dose optimization rather than dose reduction, per se. Optimization of CT radiation dose is accomplished by producing images of acceptable diagnostic image quality using the lowest dose method available. Because it is image quality that constrains the dose, CT dose optimization is primarily a problem of image quality rather than radiation dose. Therefore, the primary focus in CT radiation dose optimization should be on image quality. However, no reliable direct measure of image quality has been developed for routine clinical practice. Until such measures become available, size-specific dose estimates (SSDE) can be used as a reasonable image-quality estimate. The SSDE method of radiation dose optimization for CT abdomen and pelvis consists of plotting SSDE for a sample of examinations as a function of patient size, establishing an SSDE threshold curve based on radiologists' assessment of image quality, and modifying protocols to consistently produce doses that are slightly above the threshold SSDE curve. Challenges in operationalizing CT radiation dose optimization include data gathering and monitoring, managing the complexities of the numerous protocols, scanners and operators, and understanding the relationship of the automated tube current modulation (ATCM) parameters to image quality. Because CT manufacturers currently maintain their ATCM algorithms as secret for proprietary reasons, prospective modeling of SSDE for patient populations is not possible without reverse engineering the ATCM algorithm and, hence, optimization by this method requires a trial-and-error approach.

Effect of iDose4 iterative reconstruction algorithm on image quality and radiation exposure in prospective and retrospective electrocardiographically gated coronary computed tomographic angiography

OBJECTIVES

The aims of this study were to compare a commercially available reconstruction algorithm (iDose4) with filtered back projection (FBP) in terms of image quality (IQ) for both retrospective electrocardiographically gated and prospective electrocardiographically triggered cardiac computed tomographic angiography (CCTA) protocols and to evaluate the achievable radiation dose reduction.

METHODS

A total cohort of 58 patients underwent either prospective CTCA or retrospective CTCA with full or reduced tube current-time product (in milliampere-second) protocol on a 64-slice multidetector computed tomographic scanner. All images were reconstructed with FBP, whereas the reduced milliampere-second images were also reconstructed using 2 levels (levels 4 and 6) of iDose4. Subjective and objective IQ was evaluated.

RESULTS

Dose reductions of 43% in the retrospective CCTA protocol and 27% in the prospective CCTA protocol were achieved without compromising IQ. In the prospective CCTA protocol, the reduced-dose images were highly scored; thus, additional reduction of exposure settings is feasible. In the retrospective acquisition, dose reduction has led to similar IQ scores between the reduced-dose iDose4 images and the full-dose FBP images. Considering different reconstructions (FBP, iDose-L4 and -L6) of the same acquisition data, increase in iDose4 level resulted in less noisy images. A slight improvement was also noticed in all IQ indices; however, this improvement was not statistically significant for both acquisition protocols.

CONCLUSIONS

This study demonstrated that the application of iDose at CCTA facilitates significant radiation dose reduction by maintaining diagnostic quality. The combination of iDose4 with prospective acquisition is able to significantly reduce effective dose associated with CTCA at values of approximately 2 mSv and even lower.

Imaging subclinical atherosclerosis: is it ready for prime time? A review

Imaging subclinical atherosclerosis holds the promise of individualized cardiovascular (CV) risk assessment. The large arsenal of noninvasive imaging techniques available today is playing an increasingly important role in the diagnosis and monitoring of subclinical atherosclerosis. However, there is a debate about the advisability of clinical screens for subclinical atherosclerosis and which modality is the most appropriate for monitoring risk and atherosclerosis progression. This article offers an overview of the traditional and emerging noninvasive imaging modalities used to detect early atherosclerosis, surveys population studies addressing the value of subclinical atherosclerosis detection, and also examines guideline recommendations for their clinical implementation. The clinical relevance of this manuscript lies in the potential of current imaging technology to improve CV risk prediction based on traditional risk factors and the present recommendations for subclinical atherosclerosis assessment. Noninvasive imaging will also help to identify individuals at high CV who would benefit from intensive prevention or therapeutic interventions.

Effects of sparse sampling schemes on image quality in low-dose CT

PURPOSE

Various scanning methods and image reconstruction algorithms are actively investigated for low-dose computed tomography (CT) that can potentially reduce a health-risk related to radiation dose. Particularly, compressive-sensing (CS) based algorithms have been successfully developed for reconstructing images from sparsely sampled data. Although these algorithms have shown promises in low-dose CT, it has not been studied how sparse sampling schemes affect image quality in CS-based image reconstruction. In this work, the authors present several sparse-sampling schemes for low-dose CT, quantitatively analyze their data property, and compare effects of the sampling schemes on the image quality.

METHODS

Data properties of several sampling schemes are analyzed with respect to the CS-based image reconstruction using two measures: sampling density and data incoherence. The authors present five different sparse sampling schemes, and simulated those schemes to achieve a targeted dose reduction. Dose reduction factors of about 75% and 87.5%, compared to a conventional scan, were tested. A fully sampled circular cone-beam CT data set was used as a reference, and sparse sampling has been realized numerically based on the CBCT data.

RESULTS

It is found that both sampling density and data incoherence affect the image quality in the CS-based reconstruction. Among the sampling schemes the authors investigated, the sparse-view, many-view undersampling (MVUS)-fine, and MVUS-moving cases have shown promising results. These sampling schemes produced images with similar image quality compared to the reference image and their structure similarity index values were higher than 0.92 in the mouse head scan with 75% dose reduction.

CONCLUSIONS

The authors found that in CS-based image reconstructions both sampling density and data incoherence affect the image quality, and suggest that a sampling scheme should be devised and optimized by use of these indicators. With this strategic approach, one can acquire optimally sampled sparse data so that the CS-based algorithms can best perform in terms of image quality.

Low-dose X-ray computed tomography image reconstruction with a combined low-mAs and sparse-view protocol

To realize low-dose imaging in X-ray computed tomography (CT) examination, lowering milliampere-seconds (low-mAs) or reducing the required number of projection views (sparse-view) per rotation around the body has been widely studied as an easy and effective approach. In this study, we are focusing on low-dose CT image reconstruction from the sinograms acquired with a combined low-mAs and sparse-view protocol and propose a two-step image reconstruction strategy. Specifically, to suppress significant statistical noise in the noisy and insufficient sinograms, an adaptive sinogram restoration (ASR) method is first proposed with consideration of the statistical property of sinogram data, and then to further acquire a high-quality image, a total variation based projection onto convex sets (TV-POCS) method is adopted with a slight modification. For simplicity, the present reconstruction strategy was termed as "ASR-TV-POCS." To evaluate the present ASR-TV-POCS method, both qualitative and quantitative studies were performed on a physical phantom. Experimental results have demonstrated that the present ASR-TV-POCS method can achieve promising gains over other existing methods in terms of the noise reduction, contrast-to-noise ratio, and edge detail preservation.

Raise the bar and lower the dose: current and future strategies for radiation dose reduction in head and neck imaging

SUMMARY

Technologic advances in CT have generated a dramatic increase in the number of CT studies, with a resultant increase in the radiation dose related to CT scanning. Such increase in radiation dose is becoming a concern for the radiology community, especially with increasing public awareness of the dose burden related to examinations. To cope with the increase in CT-related radiation exposure, it is becoming necessary to optimize CT imaging protocols and apply radiation dose reduction techniques to ensure the best imaging with the lowest radiation dose.

The combined effect of multidetector-row computed tomographic tube voltage, tube current, and image reconstruction algorithm on the detection of pneumothorax after intervention

OBJECTIVES

The objective of the study was to determine the lowest multidetector-row computed tomographic radiation dose parameters for the detection of pneumothorax after thoracic intervention.

MATERIALS AND METHODS

An anthropomorphic chest phantom containing pneumothoraces was imaged with different tube voltages (80, 100, and 120 kV[p]) and tube currents (10, 20, 40, 75, and 110 mAs). The images were reconstructed with both filtered back projection (FBP) and iterative reconstruction (IR) algorithms. Two blinded radiologists scored images independently for the presence or absence of pneumothorax. Effective dose, image noise, contrast-to-noise ratio, and signal-to-noise ratio were recorded.

RESULTS

At radiation dose below 0.48 mSv, sensitivity for the detection of pneumothorax decreased in both reconstruction algorithms (80% for FBP vs 83% for IR; P > 0.05). Interobserver agreement was good (k = 0.78). The IR data sets showed lower image noise as well as higher signal-to-noise ratio and contrast-to-noise ratio when compared with FBP on all acquisition parameters (P < 0.0001).

CONCLUSIONS

Very low computed tomographic dose parameters may be suitable for confident detection of small pneumothoraces after intervention.

Radial differential interior tomography and its image reconstruction with differentiated backprojection and projection onto convex sets

PURPOSE

Interior tomography has been recognized as one of the most effective approaches in computed tomography (CT) to reduce radiation dose rendered to patients. In this work, the authors propose and evaluate an imaging method of radial differential interior tomography.

METHODS

In interior tomography, an x-ray beam is collimated to only irradiate the region of interest (ROI) with suspected lesions while the surrounding area∕volume of normal tissues∕organs is spared. In the proposed imaging method of radial differential interior tomography, the outcome is a ROI image that has gone through a radial differential filtering. The image reconstruction algorithm for the radial differential interior tomography is kept in the fashion of differentiated backprojection and projection onto convex sets, but the required a priori knowledge in a small round area becomes zero and may be more readily available in practice.

RESULTS

Using the projection data simulated by computer and acquired by CT scanner, the authors evaluate and verify the performance of the proposed radial differential interior tomography method and its associated image reconstruction algorithm. The preliminary results show that the proposed imaging method can generate an image that is the radial differentiation of a conventional tomographic image and is robust over noise that inevitably exist in practice.

CONCLUSIONS

It is believed that the proposed imaging method may find its utility in advanced clinical applications wherein a ROI-based image processing and analysis is required for lesion visualization, characterization, and diagnosis.

Reducing radiation dose in CT enterography

Computed tomographic (CT) enterography is a diagnostic examination that is increasingly being used to evaluate disorders of the small bowel. An undesirable consequence of CT, however, is patient exposure to ionizing radiation. This is of particular concern with CT enterography because patients tend to be young and require numerous follow-up examinations. There are multiple strategies to reduce radiation dose at CT enterography, including adjusting acquisition parameters, reducing scan length, and reducing tube voltage or tube current. The drawback to dose reduction strategies is degradation of image quality due to increased image noise. However, image noise can be reduced with commercial iterative reconstruction and denoising techniques. With a combination of low-dose techniques and noise-control strategies, one can markedly reduce radiation dose at CT enterography while maintaining diagnostic accuracy.

Optimal dose levels in screening chest CT for unimpaired detection and volumetry of lung nodules, with and without computer assisted detection at minimal patient radiation

OBJECTIVES

The aim of this phantom study was to minimize the radiation dose by finding the best combination of low tube current and low voltage that would result in accurate volume measurements when compared to standard CT imaging without significantly decreasing the sensitivity of detecting lung nodules both with and without the assistance of CAD.

METHODS

An anthropomorphic chest phantom containing artificial solid and ground glass nodules (GGNs, 5-12 mm) was examined with a 64-row multi-detector CT scanner with three tube currents of 100, 50 and 25 mAs in combination with three tube voltages of 120, 100 and 80 kVp. This resulted in eight different protocols that were then compared to standard CT sensitivity (100 mAs/120 kVp). For each protocol, at least 127 different nodules were scanned in 21-25 phantoms. The nodules were analyzed in two separate sessions by three independent, blinded radiologists and computer-aided detection (CAD) software.

RESULTS

The mean sensitivity of the radiologists for identifying solid lung nodules on a standard CT was 89.7% ± 4.9%. The sensitivity was not significantly impaired when the tube and current voltage were lowered at the same time, except at the lowest exposure level of 25 mAs/80 kVp [80.6% ± 4.3% (p = 0.031)]. Compared to the standard CT, the sensitivity for detecting GGNs was significantly lower at all dose levels when the voltage was 80 kVp; this result was independent of the tube current. The CAD significantly increased the radiologists' sensitivity for detecting solid nodules at all dose levels (5-11%). No significant volume measurement errors (VMEs) were documented for the radiologists or the CAD software at any dose level.

CONCLUSIONS

Our results suggest a CT protocol with 25 mAs and 100 kVp is optimal for detecting solid and ground glass nodules in lung cancer screening. The use of CAD software is highly recommended at all dose levels.

Adaptive projection selection for computed tomography

The number of projections is a critical factor in tomographic imaging. The larger the number, the better the quality of the reconstructed image; however, it increases the radiation dose delivered to the patient. Therefore, it is important to keep the number of projections as small as possible. Traditionally, the projections are taken by moving the x-ray source around the patient at uniform angular steps. Taking projections at nonuniform steps may result in better images as compared with that obtained using uniform projections. This paper describes two different approaches that adjust the step size to adaptively select the angle of projections. The first one is based on the spectral richness of the acquired projections and the second relies on the amount of new information added by successive projections. The superior performance of the two proposed methods over the uniform projection scheme is demonstrated through simulation results using both phantom and real images.

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.

Iterative reconstruction for x-ray computed tomography using prior-image induced nonlocal regularization

Repeated X-ray computed tomography (CT) scans are often required in several specific applications such as perfusion imaging, image-guided biopsy needle, image-guided intervention, and radiotherapy with noticeable benefits. However, the associated cumulative radiation dose significantly increases as comparison with that used in the conventional CT scan, which has raised major concerns in patients. In this study, to realize radiation dose reduction by reducing the X-ray tube current and exposure time (mAs) in repeated CT scans, we propose a prior-image induced nonlocal (PINL) regularization for statistical iterative reconstruction via the penalized weighted least-squares (PWLS) criteria, which we refer to as "PWLS-PINL". Specifically, the PINL regularization utilizes the redundant information in the prior image and the weighted least-squares term considers a data-dependent variance estimation, aiming to improve current low-dose image quality. Subsequently, a modified iterative successive overrelaxation algorithm is adopted to optimize the associative objective function. Experimental results on both phantom and patient data show that the present PWLS-PINL method can achieve promising gains over the other existing methods in terms of the noise reduction, low-contrast object detection, and edge detail preservation.

Improving low-dose blood-brain barrier permeability quantification using sparse high-dose induced prior for Patlak model

Blood-brain barrier permeability (BBBP) measurements extracted from the perfusion computed tomography (PCT) using the Patlak model can be a valuable indicator to predict hemorrhagic transformation in patients with acute stroke. Unfortunately, the standard Patlak model based PCT requires excessive radiation exposure, which raised attention on radiation safety. Minimizing radiation dose is of high value in clinical practice but can degrade the image quality due to the introduced severe noise. The purpose of this work is to construct high quality BBBP maps from low-dose PCT data by using the brain structural similarity between different individuals and the relations between the high- and low-dose maps. The proposed sparse high-dose induced (shd-Patlak) model performs by building a high-dose induced prior for the Patlak model with a set of location adaptive dictionaries, followed by an optimized estimation of BBBP map with the prior regularized Patlak model. Evaluation with the simulated low-dose clinical brain PCT datasets clearly demonstrate that the shd-Patlak model can achieve more significant gains than the standard Patlak model with improved visual quality, higher fidelity to the gold standard and more accurate details for clinical analysis.

Perspective on radiation risk in CT imaging

Awareness of and communication about issues related to radiation dose are beneficial for patients, clinicians, and radiology departments. Initiating and facilitating discussions of the net benefit of CT by enlisting comparisons to more familiar activities, or by conveying that the anticipated radiation dose to an exam is similar to or much less than annual background levels help resolve the concerns of many patients and providers. While radiation risk estimates at the low doses associated with CT contain considerable uncertainty, we choose to err on the side of safety by assuming a small risk exists, even though the risk at these dose levels may be zero. Thus, radiologists should individualize CT scans according to patient size and diagnostic task to ensure that maximum benefit and minimum risk is achieved. However, because the magnitude of net benefit is driven by the potential benefit of a positive exam, radiation dose should not be reduced if doing so may compromise making an accurate diagnosis. The benefits and risks of CT are also highly individualized, and require consideration of many factors by patients, clinicians, and radiologists. Radiologists can assist clinicians and patients with understanding many of these factors, including test performance, potential patient benefit, and estimates of potential risk.

CT imaging with fistulography for perianal fistula: does it really help the surgeon?

OBJECTIVE

To prospectively evaluate the relative accuracy of computed tomography (CT) fistulography for preoperative assessment of fistula in ano.

MATERIALS AND METHODS

Ethical committee approval and informed consent were obtained. A total of 22 patients (15 male and 7 female, age 21-58 years) who were suspected of having fistula in ano underwent preoperative CT fistulography (CTF). The CT images of 0.6 mm were obtained respectively before and after fistulography; contrast-enhanced CT scan was also performed in 22 patients. CTF images were evaluated by two expert radiologists to assess the fistulas in the following respects: (a) the volume-rendered imaging; (b) the extensions of active inflammatory tissue; (c) the internal opening and external opening; (d) the hidden areas of tract or abscess; and (e) the deep abscess adjacent to fistula. CT findings in 18 patients were compared with surgical findings or exam under anesthesia.

RESULTS

The CTF findings in 18 cases were basically in accordance with the surgical findings and/or examination findings under anesthesia. Both coronal and transverse planes were useful in assessing the location and direction of tracts or abscesses. Complicated spatial information within the perianal soft tissue about the fistula with secondary ramifications or abscesses can be easily demonstrated to the surgeons. Contrast-enhanced images were useful in assessing the inflammatory lesion activity and infiltrated area.

CONCLUSION

CTF exquisitely depicts the perianal anatomy and shows the fistulous tracks with their associated ramifications, enables selection of the most appropriate surgical treatment, and therefore minimizes all chances of recurrence.

SR-NLM: a sinogram restoration induced non-local means image filtering for low-dose computed tomography

Radiation dose has raised significant concerns to patients and operators in modern X-ray computed tomography (CT) examinations. A simple and cost-effective means to perform a low-dose CT scan is to lower the milliampere-seconds (mAs) as low as reasonably achievable in data acquisition. However, the associated image quality with lower-mAs scans (or low-dose scans) will be unavoidably degraded due to the excessive data noise, if no adequate noise control is applied during image reconstruction. For image reconstruction with low-dose scans, sinogram restoration algorithms based on modeling the noise properties of measurement can produce an image with noise-induced artifact suppression, but they often suffer noticeable resolution loss. As an alternative technique, the noise-reduction algorithms via edge-preserving image filtering can yield an image without noticeable resolution loss, but they often do not completely eliminate the noise-induced artifacts. With above observations, in this paper, we present a sinogram restoration induced non-local means (SR-NLM) image filtering algorithm to retain the CT image quality by fully considering the advantages of the sinogram restoration and image filtering algorithms in low-dose image reconstruction. Extensive experimental results show that the present SR-NLM algorithm outperforms the existing methods in terms of cross profile, noise reduction, contrast-to-ratio measure, noise-resolution tradeoff and receiver operating characteristic (ROC) curves.

Assessment of bilateral filter on 1/2-dose chest-pelvis CT views

A bilateral filter (BF) is a non-linear filter that has been proved to de-noise images without overrunning edges. Multi-slice computerized tomography (CT) may employ a BF to participate in dose reduction. This paper quantifies the role of the BF in achieving this objective on 1/2-dose CT. Two sets of CT images are acquired for the chest-pelvis at two different radiation doses. The BF was applied on the 1/2-dose CT images by use of various window sizes. Each time, a set of values of the BF range was fixed while the BF domain was modified. The goal was to observe the behavior of the BF on 1/2-dose CT images in comparison with full-dose CT images. The comparison was carried out by use of four co-occurrence matrix descriptors. Additionally, the peak signal-to-noise ratio (PSNR) and the mean square error (MSE) were reported. The study was applied to the sagittal, coronal, and axial CT views. The results showed that the impact of applying a BF varies among different CT views. The BF can retrieve only part of the signal being lost due to reduction of the radiation dose by one half. Yet, the BF improves the appearance of the 1/2-dose chest-pelvis CT examination. Thus, the BF can contribute to a 50% dose reduction. A procedure for employing the BF on CT machines is proposed. The results also showed that texture descriptors are similar to the PSNR and MSE in providing quantities for assessing medical image quality.

Greek dose reference levels in pediatric pelvis computed tomography examinations

The fact that children do undergo computed tomography (CT) examinations similar to those for adults adults has been a research issue, especially since the former are exposed to greater risk levels (developing stochastic late effects, such as cancer) due to their increased radiosensitivity compared to the latter. In a previous research paper (), the values of dose levels were recorded, analyzed, and compared with the reference values for groups of 0, 1, 5 and 10 y-old children for the regions of head, chest, and abdomen. In this paper, the same age group has been considered for measuring dose levels of the pelvic region. Scanning the pelvic region has been one of the most important CT examination procedures, in which unfortunately part of the lower abdomen region is included without adapting any pediatric protocols. Furthermore, the study determines whether the adjustment of the scanning parameters results in any possible reduction in the radiation dose levels to which the patient is being exposed during the examination. The present work also includes the Greek reference levels for the pelvic CT examination for the 5- and 10-y-old children that have been used for comparison against the European ones.

Quando a fase de equilíbrio pode ser suprimida nos exames de tomografia computadorizada de abdome?

OBJETIVO: Avaliar a necessidade de realização da fase de equilíbrio nos exames de tomografia computadorizada de abdome. MATERIAIS E MÉTODOS: Realizou-se estudo retrospectivo, transversal e observacional, avaliando 219 exames consecutivos de tomografia computadorizada de abdome com contraste intravenoso, realizados num período de três meses, com diversas indicações clínicas. Para cada exame foram emitidos dois pareceres, um avaliando o exame sem a fase de equilíbrio (primeira análise) e o outro avaliando todas as fases em conjunto (segunda análise). Ao final de cada avaliação, foi estabelecido se houve mudança nos diagnósticos principais e secundários, entre a primeira e a segunda análise. Foi utilizada a extensão do teste exato de Fisher para avaliar a modificação dos diagnósticos principais (p < 0,05 como significante). RESULTADOS: Entre os 219 casos avaliados, a supressão da fase de equilíbrio provocou alteração no diagnóstico principal em apenas um exame (0,46%; p > 0,999). Com relação aos diagnósticos secundários, cinco exames (2,3%) foram modificados. CONCLUSÃO: Para indicações clínicas como estadiamento tumoral, abdome agudo e pesquisa de coleção abdominal, a fase de equilíbrio não acrescenta contribuição diagnóstica expressiva, podendo ser suprimida dos protocolos de exame.

Improving spatial adaptivity of nonlocal means in low-dosed CT imaging using pointwise fractal dimension

NLMs is a state-of-art image denoising method; however, it sometimes oversmoothes anatomical features in low-dose CT (LDCT) imaging. In this paper, we propose a simple way to improve the spatial adaptivity (SA) of NLMs using pointwise fractal dimension (PWFD). Unlike existing fractal image dimensions that are computed on the whole images or blocks of images, the new PWFD, named pointwise box-counting dimension (PWBCD), is computed for each image pixel. PWBCD uses a fixed size local window centered at the considered image pixel to fit the different local structures of images. Then based on PWBCD, a new method that uses PWBCD to improve SA of NLMs directly is proposed. That is, PWBCD is combined with the weight of the difference between local comparison windows for NLMs. Smoothing results for test images and real sinograms show that PWBCD-NLMs with well-chosen parameters can preserve anatomical features better while suppressing the noises efficiently. In addition, PWBCD-NLMs also has better performance both in visual quality and peak signal to noise ratio (PSNR) than NLMs in LDCT imaging.