Effect of the forward-projected model-based iterative reconstruction solution algorithm on image quality and radiation dose in pediatric cardiac computed tomography

Associations of fractional exhaled nitric oxide with airway dimension and mucus plugs on ultra-high-resolution computed tomography in former smokers and nonsmokers with asthma

BACKGROUND

Associations of fractional exhaled nitric oxide (FeNO) with airway wall remodeling and mucus plugs remain to be explored in smokers and nonsmokers with asthma. Ultra-high-resolution computed tomography (U-HRCT), which allows accurate structural quantification of airways >1 mm in diameter, was used in this study to examine whether higher FeNO was associated with thicker walls of the 3rd to 6th generation airways and mucus plugging in patients with asthma.

METHODS

The retrospective analyses included consecutive former smokers and nonsmokers with asthma who underwent U-HRCT in a hospital. The ratio of wall area to summed lumen and wall area was calculated as the wall area percent (WA%). Mucus plugging was visually scored.

RESULTS

Ninety-seven patients with asthma (including 59 former smokers) were classified into low (<20 ppb), middle (20-35 ppb), and high (>35 ppb) FeNO groups (n = 24, 26, and 47). In analysis including all patients and subanalysis including nonsmokers or former smokers, WA% in the 6th generation airways was consistently higher in the high FeNO group than in the low FeNO group, whereas WA% in the 3rd to 5th generation airways was not. In multivariable models, WA% in the 6th generation airways and the rate of mucus plugging were higher in the high FeNO group than in the low FeNO group after adjusting for age, sex, body mass index, smoking status, lung volume, and allergic rhinitis presence.

CONCLUSIONS

Higher FeNO may reflect the inflammation and remodeling of relatively peripheral airways in asthma in both former smokers and nonsmokers.

The estimation of coronary artery calcium thickness by computed tomography angiography based on optical coherence tomography measurements

Optical coherence tomography (OCT) is recommended to be the most appropriate modality in assessing calcium thickness, however, it has limitations associated with infrared attenuation. Although coronary computed tomography angiography (CCTA) detects calcification, it has low resolution and hence not recommended to measure the calcium size. The aim of this study was to devise a simple algorithm to estimate calcium thickness based on the CCTA image. A total of 68 patients who had CCTA for suspected coronary artery disease and subsequently went on to have OCT were included in the study. 238 lesions of them divided into derivation and validation dataset at 2:1 ratio (47 patients with 159 lesions and 21 with 79, respectively) were analyzed. A new method was developed to estimate calcium thickness from the maximum CT density within the calcification and compared with calcium thickness measured by OCT. Maximum Calcium density and measured calcium-border CT density had a good correlation with a linear equation of y = 0.58x + 201 (r = 0.892, 95% CI 0.855-0.919, p < 0.001). The estimated calcium thickness derived from this equation showed strong agreement with measured calcium thickness in validation and derivation dataset (r2 = 0.481 and 0.527, 95% CI 0.609-0.842 and 0.497-0.782, p < 0.001 in both, respectively), more accurate than the estimation by full width at half maximum and inflection point method. In conclusion, this novel method provided the estimation of calcium thickness more accurately than conventional methods.

Improvement of diagnostic performance of hyperacute ischemic stroke in head CT using an image-based noise reduction technique with non-black-boxed process

PURPOSE

This study aims to investigate whether an image-based noise reduction (INR) technique with a conventional rule-based algorithm involving no black-boxed processes can outperform an existing hybrid-type iterative reconstruction (HIR) technique, when applied to brain CT images for diagnosis of early CT signs, which generally exhibit low-contrast lesions that are difficult to detect.

METHODS

The subjects comprised 27 patients having infarctions within 4.5 h of onset and 27 patients with no change in brain parenchyma. Images with thicknesses of 5 mm and 0.625 mm were reconstructed by HIR. Images with a thickness of 0.625 mm reconstructed by filter back projection (FBP) were processed by INR. The contrast-to-noise ratios (CNRs) were calculated between gray and white matters; lentiform nucleus and internal capsule; infarcted and non-infarcted areas. Two radiologists subjectively evaluated the presence of hyperdense artery signs (HASs) and infarctions and visually scored three properties regarding image quality (0.625-mm HIR images were excluded because of their notably worse noise appearances).

RESULTS

The CNRs of INR were significantly better than those of HIR with P < 0.001 for all the indicators. INR yielded significantly higher areas under the curve for both infarction and HAS detections than HIR (P < 0.001). Also, INR significantly improved the visual scores of all the three indicators.

CONCLUSION

The INR incorporating a simple and reproducible algorithm was more effective than HIR in detecting early CT signs and can be potentially applied to CT images from a large variety of CT systems.

[Possible Radiation Dose Reduction in Abdominal Plain CT Using Deep Learning Reconstruction]

PURPOSE

The purposes of this study were to evaluate the low-contrast detectability of CT images assuming hepatocellular carcinoma and to determine whether dose reduction in abdominal plain CT imaging is possible.

METHODS

A Catphan 600 was imaged at 350, 250, 150, and 50 mA using an Aquilion ONE PRISM Edition (Canon) and reconstructed using deep learning reconstruction (DLR) and model-based iterative reconstruction (MBIR). A low-contrast object-specific contrast-to-noise ratio (CNR_LO) was measured and compared in a 5-mm module with a CT value difference of 10 HU, assuming hepatocellular carcinoma; a visual examination was also performed. Moreover, an NPS within a uniform module was measured.

RESULTS

CNR_LO was higher for DLR at all doses (1.12 at 150 mA for DLR and 1.07 at 250 mA for MBIR). On visual evaluation, DLR could detect up to 150 mA and MBIR up to 250 mA. The NPS was lower for DLR at 0.1 cycles/mm at 150 mA.

CONCLUSION

The low-contrast detection performance was better with DLR than with MBIR, indicating the possibility of dose reduction.

A novel algorithm for comprehensive quality assessment of clinical magnetic resonance images based on natural scene statistics in spatial domain

BACKGROUND

A magnetic resonance imaging (MRI)-specific objective image quality assessment (IQA) algorithm, the quality evaluation using multidirectional filters for MRI (QEMDIM), was previously reported. QEMDIM requires a set of reference images to calculate the quality score (S_Q) for an assessed image. S_Q may be affected by the quality of the reference set owing to the calculation procedure.

PURPOSE

To propose a modified version of the IQA algorithm and compare the IQA performance of the original and modified algorithms.

ASSESSMENT

Brain axial T₁- and T₂-weighted spin-echo images of varying quality levels (noise and blurring) were acquired from seven healthy men. Subjective IQA (paired comparisons) was conducted on the images, and subjective quality scores were obtained. With reference sets of various quality levels, QEMDIM and modified IQA were applied to the same images that underwent the subjective IQA. The correlation of each S_Q and modified score (S_mod) with the subjective scores was evaluated for content-related subsets of assessed images and for each reference set. The effect of the reference-set quality on the distribution of the correlation coefficients (CCs) was statistically evaluated for S_Q and S_mod using a one-way analysis of variance test with a significance level of 0.05. We also evaluated the variation in S_mod for images with almost the same qualities using the standard deviation (SD).

RESULTS

The CCs of S_Q varied significantly with the quality of the reference set, whereas that of S_mod did not. The SD of S_mod for almost-same-quality images was less than that corresponding to the confidence interval of the subjective scores.

CONCLUSION

Our modified algorithm was superior to QEMDIM in terms of IQA performance in clinical practice, especially in terms of accuracy, robustness, and reproducibility.

Optimization of a customized simultaneous algebraic reconstruction technique algorithm for phase-contrast breast computed tomography

Objective. To introduce the optimization of a customized GPU-based simultaneous algebraic reconstruction technique (cSART) in the field of phase-contrast breast computed tomography (bCT). The presented algorithm features a 3D bilateral regularization filter that can be tuned to yield optimal performance for clinical image visualization and tissues segmentation. Approach. Acquisitions of a dedicated test object and a breast specimen were performed at Elettra, the Italian synchrotron radiation (SR) facility (Trieste, Italy) using a large area CdTe single-photon counting detector. Tomographic images were obtained at 5 mGy of mean glandular dose, with a 32 keV monochromatic x-ray beam in the free-space propagation mode. Three independent algorithms parameters were optimized by using contrast-to-noise ratio (CNR), spatial resolution, and noise texture metrics. The results obtained with the cSART algorithm were compared with conventional SART and filtered back projection (FBP) reconstructions. Image segmentation was performed both with gray scale-based and supervised machine-learning approaches. Main results. Compared to conventional FBP reconstructions, results indicate that the proposed algorithm can yield images with a higher CNR (by 35% or more), retaining a high spatial resolution while preserving their textural properties. Alternatively, at the cost of an increased image ‘patchiness’, the cSART can be tuned to achieve a high-quality tissue segmentation, suggesting the possibility of performing an accurate glandularity estimation potentially of use in the realization of realistic 3D breast models starting from low radiation dose images. Significance. The study indicates that dedicated iterative reconstruction techniques could provide significant advantages in phase-contrast bCT imaging. The proposed algorithm offers great flexibility in terms of image reconstruction optimization, either toward diagnostic evaluation or image segmentation.

Quantum Iterative Reconstruction for Low-Dose Ultra-High-Resolution Photon-Counting Detector CT of the Lung

The aim of this study was to characterize image quality and to determine the optimal strength levels of a novel iterative reconstruction algorithm (quantum iterative reconstruction, QIR) for low-dose, ultra-high-resolution (UHR) photon-counting detector CT (PCD-CT) of the lung. Images were acquired on a clinical dual-source PCD-CT in the UHR mode and reconstructed with a sharp lung reconstruction kernel at different strength levels of QIR (QIR-1 to QIR-4) and without QIR (QIR-off). Noise power spectrum (NPS) and target transfer function (TTF) were analyzed in a cylindrical phantom. 52 consecutive patients referred for low-dose UHR chest PCD-CT were included (CTDIvol: 1 ± 0.6 mGy). Quantitative image quality analysis was performed computationally which included the calculation of the global noise index (GNI) and the global signal-to-noise ratio index (GSNRI). The mean attenuation of the lung parenchyma was measured. Two readers graded images qualitatively in terms of overall image quality, image sharpness, and subjective image noise using 5-point Likert scales. In the phantom, an increase in the QIR level slightly decreased spatial resolution and considerably decreased noise amplitude without affecting the frequency content. In patients, GNI decreased from QIR-off (202 ± 34 HU) to QIR-4 (106 ± 18 HU) (p < 0.001) by 48%. GSNRI increased from QIR-off (4.4 ± 0.8) to QIR-4 (8.2 ± 1.6) (p < 0.001) by 87%. Attenuation of lung parenchyma was highly comparable among reconstructions (QIR-off: -849 ± 53 HU to QIR-4: -853 ± 52 HU, p < 0.001). Subjective noise was best in QIR-4 (p < 0.001), while QIR-3 was best for sharpness and overall image quality (p < 0.001). Thus, our phantom and patient study indicates that QIR-3 provides the optimal iterative reconstruction level for low-dose, UHR PCD-CT of the lungs.

Image quality and radiologists' subjective acceptance using model-based iterative and deep learning reconstructions as adjuncts to ultrahigh-resolution CT in low-dose contrast-enhanced abdominopelvic CT: phantom and clinical pilot studies

Purpose

In contrast-enhanced abdominopelvic CT (CE-APCT) for oncologic follow-up, ultrahigh-resolution CT (UHRCT) may improve depiction of fine lesions and low-dose scans are desirable for minimizing the potential adverse effects by ionizing radiation. We compared image quality and radiologists’ acceptance of model-based iterative (MBIR) and deep learning (DLR) reconstructions of low-dose CE-APCT by UHRCT.

Methods

Using our high-resolution (matrix size: 1024) and low-dose (tube voltage 100 kV; noise index: 20–40 HU) protocol, we scanned phantoms to compare the modulation transfer function and noise power spectrum between MBIR and DLR and assessed findings in 36 consecutive patients who underwent CE-APCT (noise index: 35 HU; mean CTDI_vol: 4.2 ± 1.6 mGy) by UHRCT. We used paired t-test to compare objective noise and contrast-to-noise ratio (CNR) and Wilcoxon signed-rank test to compare radiologists’ subjective acceptance regarding noise, image texture and appearance, and diagnostic confidence between MBIR and DLR using our routine protocol (matrix size: 512; tube voltage: 120 kV; noise index: 15 HU) for reference.

Results

Phantom studies demonstrated higher spatial resolution and lower low-frequency noise by DLR than MBIR at equal doses. Clinical studies indicated significantly worse objective noise, CNR, and subjective noise by DLR than MBIR, but other subjective characteristics were better (P < 0.001 for all). Compared with the routine protocol, subjective noise was similar or better by DLR, and other subjective characteristics were similar or worse by MBIR.

Conclusion

Image quality, except regarding noise characteristics, and acceptance by radiologists were better by DLR than MBIR in low-dose CE-APCT by UHRCT.

Graphical abstract

Quantitative measurements of emphysema in ultra-high resolution computed tomography using model-based iterative reconstruction in comparison to that using hybrid iterative reconstruction

The percentage of low attenuation volume ratio (LAVR), which is measured using computed tomography (CT), is an index of the severity of emphysema. For LAVR evaluation, ultra-high-resolution (U-HR) CT images are useful. To improve the image quality of U-HRCT, iterative reconstruction is used. There are two types of iterative reconstruction: hybrid iterative reconstruction (HIR) and model-based iterative reconstruction (MBIR). In this study, we physically and clinically evaluated U-HR images reconstructed with HIR and MBIR, and demonstrated the usefulness of U-HR images with MBIR for quantitative measurements of emphysema. Both images were reconstructed with a slice thickness of 0.25 mm and an image matrix size of 1024 × 1024 pixels. For physical evaluation, the modulation transfer function (MTF) and noise power spectrum (NPS) of HIR and MBIR were compared. For clinical evaluation, LAVR calculated from HIR and MBIR were compared using the Wilcoxon matched-pairs signed-rank test. In addition, the correlation between LAVR and forced expiratory volume in one second (FEV₁%) was evaluated using the Spearman rank correlation test. The MTFs of HIR and MBIR were comparable. The NPS of MBIR was lower than that of HIR. The mean LAVR values calculated from HIR and MBIR were 19.5 ± 12.6% and 20.4 ± 11.7%, respectively (p = 0.84). The correlation coefficients between LAVR and FEV₁% that were taken from HIR and MBIR were 0.64 and 0.74, respectively (p < 0.01). MBIR is more useful than HIR for the quantitative measurements of emphysema with U-HR images.

Deep learning-based reconstruction of chest ultra-high-resolution computed tomography and quantitative evaluations of smaller airways

The full-iterative model reconstruction generates ultra-high-resolution computed tomography (U-HRCT) images comprising a 1024 × 1024 matrix and 0.25 mm thickness while suppressing image noises, allowing evaluating small airways 1-2 mm in diameter. However, this technique imposes huge computational burdens and requires a long reconstruction time. This study evaluated whether a recently-established deep learning-based reconstruction, Advanced intelligent Clear-IQ Engine (AiCE), allows quantitative morphological analyses of smaller airways with equal or better quality than the full-iterative model reconstruction while shortening the reconstruction time. In phantom tubes mimicking small airways, the measurement error of 0.5-mm-thickness wall was smaller on the AiCE-based than the full-iterative model-based U-HRCT. Moreover, in five patients with chronic obstructive pulmonary disease, the AiCE-based U-HRCT decreased the reconstruction time approximately by 90% with a modest improvement in image noise, contrast, and sharpness compared to the full-iterative model-based U-HRCT. Therefore, the AiCE-based U-HRCT can be readily used clinically for morphologically evaluating peripheral small airways.

Model-based iterative reconstruction for 320-detector row CT angiography reduces radiation exposure in infants with complex congenital heart disease

PURPOSE

We investigated the impact of model-based iterative reconstruction (MBIR) on 320-detector row computed tomography angiography (CTA) in infants with complex congenital heart disease (CHD).

METHODS

Seventy infants with complex CHD who underwent 320-detector row CTA (40 boys and 30 girls; age range, 0-22 months; median age, 60 days) were retrospectively evaluated. First, the images were reconstructed by filtered back projection (FBP), hybrid iterative reconstruction (HIR), or MBIR in 20 cases, and variables were compared among the three iterative reconstruction methods (IR test). Second, the variables were compared between 25 cases scanned using HIR and 25 cases scanned using MBIR, with a 20 standard deviation noise level for both. Attenuation values and contrast-to-noise ratios (CNRs) of the great vessels and heart chambers were calculated. Total dose-length products were recorded for all patients (radiation dose: RD test).

RESULTS

In the IR test, the mean CNR values were 4.8±1.3 for FBP, 6.9±1.4 for HIR, and 8.2±1.7 for MBIR (P < 0.0001). The best subjective image qualities in the great vessels and heart chambers were obtained with MBIR. In RD testing, no significant differences between HIR and MBIR in image quality (CNR: HIR, 8.4±2.4; MBIR, 8.3±2.4) were observed. The effective dose was significantly lower for MBIR than for HIR (0.7±0.2 vs. 1.1±0.3 mSv; P < 0.001).

CONCLUSION

The MBIR algorithm significantly improved image quality and decreased radiation exposure in 320-row CTA of infants with complex CHD, providing an alternative to FBP or HIR that is both safer and produces better results.

Reduction of streak artifacts caused by low photon counts utilizing an image-based forward projection in computed tomography

BACKGROUND

The streak artifacts in computed tomography (CT) images caused by low photon counts are known to be effectively suppressed by raw-data-based techniques. This study aims to propose a technique to reduce the streak artifact without accessing the raw data.

METHODS

The proposed streak artifact reduction (SAR) technique consists of three steps: numerical forward projection to a CT image, adaptive filtering of the generated sinogram, and image reconstruction from the processed sinogram. The authors have expanded the two-dimensional method (2D-SAR) to three dimensions (3D-SAR) by using consecutive CT images. The modulation transfer function (MTF), the image noise (standard deviation), and the visibility of comb-shaped objects were evaluated at a low dose of 5 mGy. Using anthropomorphic abdominal and chest phantoms, CT images and the artifact index (AI) were compared between 3D-SAR and two types of iterative reconstruction (IR).

RESULTS

Sufficient artifact reductions associated with 54% and 61% reduction of noise for 2D- and 3D-SAR, respectively, were obtained in the phantom images, although the 50%MTF decreased by 28%. The visibility of the combs was improved with both the 2D- and 3D-SAR methods. The AI results of 3D-SAR were better than one type of IR and almost equal to the other type of IR, which was consistent with observed artifacts.

CONCLUSION

Both 2D-SAR and 3D-SAR have turned out to be effective in reducing streak artifacts. The proposed technique will be an effective tool since it needs no raw data, and thus can be applied to any CT images produced by a wide variety of CT systems.

Image quality improvement with deep learning-based reconstruction on abdominal ultrahigh-resolution CT: A phantom study

Purpose

In an ultrahigh‐resolution CT (U‐HRCT), deep learning‐based reconstruction (DLR) is expected to drastically reduce image noise without degrading spatial resolution. We assessed a new algorithm's effect on image quality at different radiation doses assuming an abdominal CT protocol.

Methods

For the normal‐sized abdominal models, a Catphan 600 was scanned by U‐HRCT with 100%, 50%, and 25% radiation doses. In all acquisitions, DLR was compared to model‐based iterative reconstruction (MBIR), filtered back projection (FBP), and hybrid iterative reconstruction (HIR). For the quantitative assessment, we compared image noise, which was defined as the standard deviation of the CT number, and spatial resolution among all reconstruction algorithms.

Results

Deep learning‐based reconstruction yielded lower image noise than FBP and HIR at each radiation dose. DLR yielded higher image noise than MBIR at the 100% and 50% radiation doses (100%, 50%, DLR: 15.4, 16.9 vs MBIR: 10.2, 15.6 Hounsfield units: HU). However, at the 25% radiation dose, the image noise in DLR was lower than that in MBIR (16.7 vs. 26.6 HU). The spatial frequency at 10% of the modulation transfer function (MTF) in DLR was 1.0 cycles/mm, slightly lower than that in MBIR (1.05 cycles/mm) at the 100% radiation dose. Even when the radiation dose decreased, the spatial frequency at 10% of the MTF of DLR did not change significantly (50% and 25% doses, 0.98 and 0.99 cycles/mm, respectively).

Conclusion

Deep learning‐based reconstruction performs more consistently at decreasing dose in abdominal ultrahigh‐resolution CT compared to all other commercially available reconstruction algorithms evaluated.

Comparison of CT image quality between the AIDR 3D and FIRST iterative reconstruction algorithms: an assessment based on phantom measurements and clinical images

Modern CT iterative reconstruction algorithms are transitioning from a statistical-based to model-based approach. However, increasing complexity does not ensure improved image quality for all indications, and thorough characterization of new algorithms is important to understand their potential clinical impacts. This study performs both quantitative and qualitative analyses of image quality to compare Canon's statistical-based Adaptive Iterative Dose Reduction 3D (AIDR 3D) algorithm to its model-based algorithm, Forward-projected model-based Iterative Reconstruction SoluTion(FIRST). A phantom was used to measure the task-specific modulation transfer function (MTF_Task), the noise power spectrum (NPS), and the low-contrast object-specific CNR (CNR_LO) for each algorithm using three dose levels and the convolution algorithm (kernel) appropriate for abdomen, lung, and brain imaging. Additionally, MTF_Taskwas measured at four contrast levels, and CNR_LOwas measured for two object sizes. Lastly, three radiologists participated in a preference study to compare clinical image quality for three study types: non-contrast abdomen, pulmonary embolism (PE), and lung screening. Nine questions related to the appearance of anatomical features or image quality characteristics were scored for twenty exams of each type. The behavior of both algorithms depended strongly on the kernel selected. Phantom measurements suggest that FIRST should be beneficial over AIDR 3D for abdomen imaging, but do not suggest a clear overall benefit to FIRST for lung or brain imaging; metrics suggest performance may be equivalent to or slightly favor AIDR 3D, depending on the size of the object being imaged and whether spatial resolution or low-contrast resolution is more important for the task at hand. Overall, radiologists strongly preferred AIDR 3D for lung screening, slightly preferred AIDR 3D for non-contrast abdomen, and had no preference for PE. FIRST was superior for the reduction of metal artifacts. Radiologist preference may be influenced by changes to noise texture.

[Quantitative Analysis of Emphysema in Ultra-high-resolution CT by Using Deep Learning Reconstruction: Comparison with Hybrid Iterative Reconstruction]

PURPOSE

The noise generated in ultra-high-resolution computed tomography (U-HRCT) images affects the quantitative analysis of emphysema. In this study, we compared the physical properties of reconstructed images for hybrid iterative reconstruction (HIR) and deep learning reconstruction (DLR), which are reconstruction methods for reducing image noise. Using clinical evaluation, we evaluated the correlation between low attenuation volume (LAV) % obtained by CT and forced expiratory volume in 1 s per forced vital capacity (FEV₁/FVC) obtained by respiratory function tests.

MATERIALS AND METHODS

CT data obtained by HIR and DLR were used for analysis (matrix size: 1024´1024, slice thickness: 0.25 mm). The physical characteristics were evaluated for the modulation transfer function (MTF) and noise power spectrum (NPS). Display-field of view (D-FOV) was analyzed by varying between 300 mm and 400 mm. The clinical data evaluated the relationship between LAV% and FEV₁/FVC by Spearman's correlation coefficient.

RESULT

The 10% MTFs were 1.3 cycles/mm (HIR) and 1.3 cycles/mm (DLR) at D-FOV 300 mm, and 1.2 cycles/mm (HIR) and 1.1 cycles/mm (DLR) at D-FOV 400 mm. The NPS had less noise in DLR than HIR in all frequency ranges. The correlation coefficients between LAV% and FEV₁/FVC were 0.64 and 0.71, respectively, in HIR and DLR.

CONCLUSION

There was no difference in the resolution characteristics of HIR and DLR. DLR had better noise characteristics than HIR. The correlation between LAV% measured by HIR and DLR and FEV₁/FVC is equivalent. The noise characteristics of the DLR enable the reduction of exposure to emphysema quantitative analysis by CT.

Influence of Asthma Onset on Airway Dimensions on Ultra-high-resolution Computed Tomography in Chronic Obstructive Pulmonary Disease

PURPOSE

Asthma onset before the age of 40 years is associated with distinct clinical manifestations in chronic obstructive pulmonary disease (COPD) patients, but its morphologic features remain unestablished. This study aimed to explore airway morphology in COPD patients with asthma onset before 40 years of age using ultra-high-resolution computed tomography (U-HRCT), which allows a more accurate quantitation of the lumen and the wall in smaller airways than using conventional CT.

MATERIALS AND METHODS

Clinical data of 500 consecutive patients undergoing full inspiratory U-HRCT (1024×1024 matrix and 0.25 mm slice thickness) were retrospectively analyzed. COPD patients without asthma, COPD patients with asthma onset at age below or 40 years and above, and non-COPD smoker controls (N=137, 29, 34, and 22, respectively) were enrolled. The length, lumen area (LA), wall thickness and area (WA), and wall area percent (WA%) of the segmental (third-generation) to sub-subsegmental (fifth-generation) bronchus and the low attenuation volume percent (LAV%) were measured.

RESULTS

LA and WA were smaller in the fourth and fifth generation in COPD patients than in non-COPD controls, regardless of the age of asthma onset. LA was smaller and WA% was larger in the fourth-generation and fifth-generation airways in COPD with asthma onset before 40 years than COPD without asthma, whereas WA did not differ between them. In multivariate analyses, asthma onset before 40 years was associated with smaller LA in COPD patients independent of demographics, use of inhaled corticosteroids and long-acting bronchodilators, airflow limitation, and LAV%.

CONCLUSIONS

Asthma onset before 40 years of age could be associated with greater lumen narrowing of the airways in COPD.

Cardiac computed tomography angiography in the paediatric population: Expert consensus from the Filiale de cardiologie pédiatrique et congénitale (FCPC) and the Société française d'imagerie cardiaque et vasculaire diagnostique et interventionnelle (SFICV)

This paper aims to provide a paediatric cardiac computed tomography angiography expert panel consensus based on the opinions of experts from the Société française d'imagerie cardiaque et vasculaire diagnostique et interventionnelle (SFICV) and the Filiale de cardiologie pédiatrique congénitale (FCPC). This expert panel consensus includes recommendations for indications, patient preparation, computed tomography angiography radiation dose reduction techniques and postprocessing techniques. We think that to realize its full potential and to avoid pitfalls, cardiac computed tomography angiography in children with congenital heart disease requires training and experience. Moreover, paediatric cardiac computed tomography angiography protocols should be standardized to acquire optimal images in this population with the lowest radiation dose possible, to prevent unnecessary radiation exposure. We also provide a suggested structured report and a list of acquisition protocols and technical parameters in relation to specific vendors.

The effect of the reconstruction algorithm for the pulmonary nodule detection under the metal artifact caused by a pacemaker

The aim was to compare the effects of metal artifacts from a pacemaker on pulmonary nodule detection among computed tomography (CT) images reconstructed using filtered back projection (FBP), single-energy metal artifact reduction (SEMAR), and forward-projected model-based iterative reconstruction solution (FIRST).Nine simulated nodules were placed inside a chest phantom with a pacemaker. CT images reconstructed using FBP, SEMAR, and FIRST were acquired at low and standard dose, and were evaluated by 2 independent radiologists.FIRST demonstrated the most significantly improved metal artifact and nodule detection on low dose CT (P < .0032), except at 10 mA and 5-mm thickness. At standard-dose CT, SEMAR showed the most significant metal artifact reduction (P < .00001). In terms of nodule detection, no significant differences were observed between FIRST and SEMAR (P = .161).With a pacemaker present, FIRST showed the best nodule detection ability at low-dose CT and SEMAR is comparable to FIRST at standard dose CT.

Pediatric cardiac computed tomography angiography: Expert consensus from the Filiale de Cardiologie Pédiatrique et Congénitale (FCPC) and the Société Française d'Imagerie Cardiaque et Vasculaire diagnostique et interventionnelle (SFICV)

This article was designed to provide a pediatric cardiac computed tomography angiography (CCTA) expert panel consensus based on opinions of experts of the Société Française d'Imagerie Cardiaque et Vasculaire diagnostique et interventionnelle (SFICV) and of the Filiale de Cardiologie Pédiatrique Congénitale (FCPC). This expert panel consensus includes recommendations for indications, patient preparation, CTA radiation dose reduction techniques, and post-processing techniques. The consensus was based on data from available literature (original papers, reviews and guidelines) and on opinions of a group of specialists with extensive experience in the use of CT imaging in congenital heart disease. In order to reach high potential and avoid pitfalls, CCTA in children with congenital heart disease requires training and experience. Moreover, pediatric cardiac CCTA protocols should be standardized to acquire optimal images in this population with the lowest radiation dose possible to prevent unnecessary radiation exposure. We also provided a suggested structured report and a list of acquisition protocols and technical parameters in relation to specific vendors.

Effect of Ultra High-Resolution Computed Tomography and Model-Based Iterative Reconstruction on Detectability of Simulated Submillimeter Artery

OBJECTIVE

To evaluate the effect of ultra high-resolution computed tomography (UHRCT) and model-based iterative reconstruction (MBIR) on the detectability of simulated submillimeter artery.

METHODS

A small vessel phantom ranging from 0.4 to 2.0 mm in diameter and edge phantoms of low to high attenuation values were scanned by UHRCT (super-high-resolution mode and normal-resolution-mode) and conventional CT, and data were reconstructed by MBIR and filtered back projection (FBP). Vessel detectability was assessed subjectively and the effective size at which 50% of response was achieved (ES50 [mm]) was calculated. Modulation transfer function (MTF) was calculated by an edge spread function method.

RESULTS

ES50 of super high-resolution mode (0.36 mm for MBIR and 0.50 mm for FBP) was significantly smaller than those of normal-resolution mode (P < 0.01). In the MTF analysis, the MTF of MBIR improved as the edge phantom attenuation increased, whereas that of FBP was stable.

CONCLUSIONS

Both UHRCT and MBIR are effective for the detectability of simulated submillimeter artery.

[Improvement of Image Quality in the Axial Section Using High-resolution Scan Mode and Hybrid Iterative Reconstruction in Ultra-high-resolution Computed Tomography]

The purpose of this study is to compare the physical characteristics and visibility of high-resolution and conventional images acquired with the same X-ray dose, and to investigate the superiority of super high-resolution imaging. A Catphan phantom was scanned in the normal resolution (NR), high-resolution (HR), and super high-resolution (SHR) modes of ultra-high-resolution computed tomography at 120 kV and 75 mAs. All images were reconstructed into a 5-mm thick image slices with filtered back-projection (FBP) and hybrid image reconstruction (HIR), which included normal and enhanced adaptive iterative dose reduction 3D (AIDR and eAIDR, respectively). The modulation transfer function (MTF) and noise power spectrum (NPS) were measured using the circular edge method and radial frequency method, respectively. The signal-to-noise ratio (SNR) was then calculated. High-contrast resolution and low-contrast detectability were evaluated visually by five radiological technologists. The MTFs of HR_eAIDR and HR_FBP images were higher than those of NR_FBP images. However, the NPSs of HR_eAIDR and HR_FBP images were larger than those of NR_FBP images. The SNR of HR_eAIDR images was higher than that of NR_FBP and HR_FBP images. The scores of high-contrast resolution of HR_eAIDR, NR_FBP, and HR_FBP images were 13, 8, and 13 cycles/cm, respectively, and the scores of low-contrast detectability were 5, 5, and 6 mm, respectively. Hence, an improvement in high-contrast resolution of signal more than 400 HU in the axial section can be achieved without increasing the radiation dose and decreasing low-contrast detectability with 10 HU using the HR mode and eAIDR.

Quantitative measurement of airway dimensions using ultra-high resolution computed tomography

BACKGROUND

Quantitative measurement of airway dimensions using computed tomography (CT) is performed in relatively larger airways due to the limited resolution of CT scans. Nevertheless, the small airway is an important pathological lesion in lung diseases such as chronic obstructive pulmonary disease (COPD) and asthma. Ultra-high resolution scanning may resolve the smaller airway, but its accuracy and limitations are unclear.

METHODS

Phantom tubes were imaged using conventional (512 × 512) and ultra-high resolution (1024 × 1024 and 2048 × 2048) scans. Reconstructions were performed using the forward-projected model-based iterative reconstruction solution (FIRST) algorithm in 512 × 512 and 1024 × 1024 matrix scans and the adaptive iterative dose reduction 3D (AIDR-3D) algorithm for all scans. In seven subjects with COPD, the airway dimensions were measured using the 1024 × 1024 and 512 × 512 matrix scans.

RESULTS

Compared to the conventional 512 × 512 scan, variations in the CT values for air were increased in the ultra-high resolution scans, except in the 1024×1024 scan reconstructed through FIRST. The measurement error of the lumen area of the tube with 2-mm diameter and 0.5-mm wall thickness (WT) was minimal in the ultra-high resolution scans, but not in the conventional 512 × 512 scan. In contrast to the conventional scans, the ultra-high resolution scans resolved the phantom tube with ≥ 0.6-mm WT at an error rate of < 11%. In seven subjects with COPD, the WT showed a lower value with the 1024 × 1024 scans versus the 512 × 512 scans.

CONCLUSIONS

The ultra-high resolution scan may allow more accurate measurement of the bronchioles with smaller dimensions compared with the conventional scan.

Comparison of full-iodine conventional CT and half-iodine virtual monochromatic imaging: advantages and disadvantages

PURPOSE

To compare image quality of abdominal arteries between full-iodine-dose conventional CT and half-iodine-dose virtual monochromatic imaging (VMI).

MATERIALS AND METHODS

We retrospectively evaluated images of 21 patients (10 men, 11 women; mean age, 73.9 years) who underwent both full-iodine (600 mg/kg) conventional CT and half-iodine (300 mg/kg) VMI. For each patient, we measured and compared CT attenuation and the contrast-to-noise ratio (CNR) of the aorta, celiac artery, and superior mesenteric artery (SMA). We also compared CT dose index (CTDI). Two board-certified diagnostic radiologists evaluated visualisation of the main trunks and branches of the celiac artery and SMA in maximum-intensity-projection images. We evaluated spatial resolution of the two scans using an acrylic phantom.

RESULTS

The two scans demonstrated no significant difference in CT attenuation of the aorta, celiac artery, and SMA, but CNRs of the aorta and celiac artery were significantly higher in VMI (p = 0.011 and 0.030, respectively). CTDI was significantly higher in VMI (p = 0.024). There was no significant difference in visualisation of the main trunk of the celiac artery and SMA, but visualisation of the gastroduodenal artery, pancreatic arcade, branch of the SMA, marginal arteries, and vasa recta was significantly better in the conventional scan (p < 0.001). The calculated modular transfer function (MTF) suggested decreased spatial resolution of the half-iodine VMI.

CONCLUSION

Large-vessel depiction and CNRs were comparable between full-iodine conventional CT and half-iodine VMI images, but VMI did not permit clear visualisation of small arteries and required a larger radiation dose.

KEY POINTS

・Reducing the dose of iodine contrast medium is essential for chronic kidney disease patients to prevent contrast-induced nephropathy. ・In virtual monochromatic images at low keV, contrast of relatively large vessels is maintained even with reduced iodine load, but visibility of small vessels is impaired with decreased spatial resolution. ・We should be aware about the advantages and disadvantages associated with virtual monochromatic imaging with reduced iodine dose.

Regularization strategies in statistical image reconstruction of low-dose x-ray CT: A review

Statistical image reconstruction (SIR) methods have shown potential to substantially improve the image quality of low-dose x-ray computed tomography (CT) as compared to the conventional filtered back-projection (FBP) method. According to the maximum a posteriori (MAP) estimation, the SIR methods are typically formulated by an objective function consisting of two terms: (a) a data-fidelity term that models imaging geometry and physical detection processes in projection data acquisition, and (b) a regularization term that reflects prior knowledge or expectations of the characteristics of the to-be-reconstructed image. SIR desires accurate system modeling of data acquisition, while the regularization term also has a strong influence on the quality of reconstructed images. A variety of regularization strategies have been proposed for SIR in the past decades, based on different assumptions, models, and prior knowledge. In this paper, we review the conceptual and mathematical bases of these regularization strategies and briefly illustrate their efficacies in SIR of low-dose CT.

Tradeoff between noise reduction and inartificial visualization in a model-based iterative reconstruction algorithm on coronary computed tomography angiography

We aimed to evaluate the image quality performance of coronary CT angiography (CTA) under the different settings of forward-projected model-based iterative reconstruction solutions (FIRST).Thirty patients undergoing coronary CTA were included. Each image was reconstructed using filtered back projection (FBP), adaptive iterative dose reduction 3D (AIDR-3D), and 2 model-based iterative reconstructions including FIRST-body and FIRST-cardiac sharp (CS). CT number and noise were measured in the coronary vessels and plaque. Subjective image-quality scores were obtained for noise and structure visibility.In the objective image analysis, FIRST-body produced the significantly highest contrast-to-noise ratio. Regarding subjective image quality, FIRST-CS had the highest score for structure visibility, although the image noise score was inferior to that of FIRST-body.In conclusion, FIRST provides significant improvements in objective and subjective image quality compared with FBP and AIDR-3D. FIRST-body effectively reduces image noise, but the structure visibility with FIRST-CS was superior to FIRST-body.

Model-based Iterative Reconstruction in Low-radiation-dose Computed Tomography Colonography: Preoperative Assessment in Patients with Colorectal Cancer

RATIONALE AND OBJECTIVES

To assess the effect of model-based iterative reconstruction (MBIR) on image quality and diagnostic performance of low-radiation-dose computed tomography colonography (CTC) in the preoperative assessment of colorectal cancer.

MATERIALS AND METHODS

This study included 30 patients with colorectal cancer referred for surgical treatment. All patients underwent CTC with a standard dose (SD) protocol in the supine position and a low-dose (LD; radiation dose reduction of approximately 85%) protocol in the prone position. The SD protocol images were post-processed using filtered back projection (FBP), whereas the LD protocol images were post-processed using FBP and MBIR. Objective and subjective image quality parameters were compared among the three different methods. Preoperative evaluations, including site, length, and tumor and node staging were performed, and the findings were compared to the postsurgical findings.

RESULTS

The mean image noise of SD-FBP, LD-FBP, and LD-MBIR images was 17.3 ± 3.2, 40.5 ± 10.9, and 11.2 ± 2.0 Hounsfield units, respectively. There were significant differences for all comparison combinations among the three methods (P < .01). For image noise, the mean visual scores were significantly higher for SD-FBP and LD-MBIR than for LD-FBP, and the scores for SD-FBP and LD-MBIR were equivalent (3.9 ± 0.3 [SD-FBP], 2.0 ± 0.5 [LD-FBP], and 3.7 ± 0.3 [LD-MBIR]). Preoperative information was more accurate under SD-FBP and LD-MBIR than under LD-FBP, and the information was comparable between SD-FBP and LD-MBIR.

CONCLUSION

MBIR can yield significantly improved image quality on low-radiation-dose CTC and provide preoperative information equivalent to that of standard-radiation-dose protocol.

Quantitative and qualitative evaluation of hybrid iterative reconstruction, with and without noise power spectrum models: A phantom study

The purpose of this phantom study was to investigate the feasibility of dose reduction with hybrid iterative reconstruction, with and without a noise power spectrum (NPS) model, using both quantitative and qualitative evaluations. Standard dose (SD), three‐quarter dose (TQD), and half‐dose (HD) of radiation were used. Images were reconstructed with filtered back projection (FBP), adaptive iterative dose reduction 3D (AIDR 3D) (MILD, STR), and AIDR 3D enhanced (eAIDR 3D) (eMILD, eSTR). An NPS analysis, task‐based modulation transfer function (MTF_task) analysis, and comparisons of low‐contrast detectability and image texture were performed. Although the eAIDR 3D had a higher NPS value in the high‐frequency range and improved image texture and resolution as compared with AIDR 3D at the same radiation dose and iteration levels, it yielded higher noise than AIDR 3D. Additionally, although there was no statistically significant difference between SD‐FBP and the TQD series in the comparison of the mean area under the curve (AUC), the mean AUC was statistically significantly different between SD‐FBP and the HD series. NPS values in the high‐frequency range, 10% MTF_task values, low‐contrast detectability, and image textures of TQD‐eMILD were comparable to those of SD‐FBP. Our findings suggested that using eMILD can reduce the radiation dose by 25%, while potentially maintaining diagnostic performance, spatial resolution, and image texture; this could support selecting the appropriate protocol in a clinical setting.

Improved Estimation of Coronary Plaque and Luminal Attenuation Using a Vendor-specific Model-based Iterative Reconstruction Algorithm in Contrast-enhanced CT Coronary Angiography

RATIONALE AND OBJECTIVES

To investigate the stabilities of plaque attenuation and coronary lumen for different plaque types, stenotic degrees, lumen densities, and reconstruction methods using coronary vessel phantoms and the visualization of coronary plaques in clinical patients through coronary computed tomography (CT) angiography.

MATERIALS AND METHODS

We performed 320-detector volume scanning of vessel tubes with stenosis and a tube without stenosis using three types of plaque CT numbers. The stenotic degrees were 50% and 75%. Images were reconstructed with filtered back projection (FBP) and two types of iterative reconstructions (AIDR3D and FIRST [forward-projected model-based iterative reconstruction solution]), with stenotic CT number of approximately 40, 80, and 150 HU (Hounsfield unit), respectively. In each case, the tubing of the coronary vessel was filled with diluted contrast material and distilled water to reach the target lumen CT numbers of approximately 350 HU and 450 HU, and 0 HU, respectively. Peak lumen and plaque CT numbers were measured to calculate the lumen-plaque contrast. In addition, we retrospectively evaluated the image quality with regard to coronary arterial lumen and the plaque in 10 clinical patients on a 4-point scale.

RESULTS

At 50% stenosis, the plaque CT number with contrast enhancement increased for FBP and AIDR3D, and the difference in the plaque CT number with and without contrast enhancement was 15-44 HU for FBP and 10-31 HU for AIDR3D. However, the plaque CT number for FIRST had a smaller variation and the difference with and without contrast enhancement was -12 to 8 HU. The visual evaluation score for the vessel lumen was 2.8 ± 0.6, 3.5 ± 0.5, and 3.7 ± 0.5 for FBP, AIDR3D, and FIRST, respectively.

CONCLUSIONS

The FIRST method controls the increase in plaque density and the lumen-plaque contrast. Consequently, it improves the visualization of coronary plaques in coronary CT angiography.

Recent advances in cardiac computed tomography dose reduction strategies: a review of scientific evidence and technical developments

Cardiac imagers worldwide are bracing for increased utilization of cardiac computed tomography (CT) in clinical practice. This expanding opportunity brings along a responsibility to produce diagnostic quality images with optimized radiation dose. The following review aims to address the dose reduction strategies in cardiac CT in light of recent scientific evidence and technical developments.

Coronary Artery Stent Evaluation with Model-based Iterative Reconstruction at Coronary CT Angiography

RATIONALE AND OBJECTIVES

This study aims to compare the image quality of coronary artery stent scans on computed tomography images reconstructed with forward projected model-based iterative reconstruction solution (FIRST) and adaptive iterative dose reduction 3D (AIDR 3D).

MATERIALS AND METHODS

Coronary computed tomography angiography scans of 23 patients with 32 coronary stents were used. The images were reconstructed with AIDR 3D and FIRST. We generated computed tomography attenuation profiles across the stents and measured the width of the edge rise distance and the edge rise slope (ERS). We also calculated the stent lumen attenuation increase ratio (SAIR) and measured visible stent lumen diameters. Two radiologists visually evaluated the image quality of the stents using a 4-point scale (1 = poor, 4 = excellent).

RESULTS

There was no significant difference in the edge rise distance between the two reconstruction methods (P = 0.36). The ERS on FIRST images was greater than the ERS on AIDR 3D images (325.2 HU/mm vs 224.4 HU/mm; P <0.01). The rate of the visible stent lumen diameter compared to the true diameter on FIRST images was higher than that on AIDR 3D images (51.4% vs 47.3%, P <0.01). The SAIR on FIRST images was lower than the SAIR on AIDR 3D images (0.19 vs 0.30, P <0.01). The mean image quality scores for AIDR 3D and FIRST images were 3.18 and 3.63, respectively; the difference was also significant (P <0.01).

CONCLUSION

The image quality of coronary artery stent scans is better on FIRST than on AIDR 3D images.

Image quality in coronary CT angiography: challenges and technical solutions

Multidetector CT angiography (CTA) has become a widely accepted examination for non-invasive evaluation of the heart and coronary arteries. Despite its ongoing success and worldwide clinical implementation, it remains an often-challenging procedure in which image quality, and hence diagnostic value, is determined by both technical and patient-related factors. Thorough knowledge of these factors is important to obtain high-quality examinations. In this review, we discuss several key elements that may adversely affect coronary CTA image quality as well as potential measures that can be taken to mitigate their impact. In addition, several recent vendor-specific advances and future directions to improve image quality are discussed.

Pediatric 320-row cardiac computed tomography using electrocardiogram-gated model-based full iterative reconstruction

BACKGROUND

Full iterative reconstruction algorithm is available, but its diagnostic quality in pediatric cardiac CT is unknown.

OBJECTIVE

To compare the imaging quality of two algorithms, full and hybrid iterative reconstruction, in pediatric cardiac CT.

MATERIALS AND METHODS

We included 49 children with congenital cardiac anomalies who underwent cardiac CT. We compared quality of images reconstructed using the two algorithms (full and hybrid iterative reconstruction) based on a 3-point scale for the delineation of the following anatomical structures: atrial septum, ventricular septum, right atrium, right ventricle, left atrium, left ventricle, main pulmonary artery, ascending aorta, aortic arch including the patent ductus arteriosus, descending aorta, right coronary artery and left main trunk. We evaluated beam-hardening artifacts from contrast-enhancement material using a 3-point scale, and we evaluated the overall image quality using a 5-point scale. We also compared image noise, signal-to-noise ratio and contrast-to-noise ratio between the algorithms.

RESULTS

The overall image quality was significantly higher with full iterative reconstruction than with hybrid iterative reconstruction (3.67±0.79 vs. 3.31±0.89, P=0.0072). The evaluation scores for most of the gross structures were higher with full iterative reconstruction than with hybrid iterative reconstruction. There was no significant difference between full and hybrid iterative reconstruction for the presence of beam-hardening artifacts. Image noise was significantly lower in full iterative reconstruction, while signal-to-noise ratio and contrast-to-noise ratio were significantly higher in full iterative reconstruction.

CONCLUSION

The diagnostic quality was superior in images with cardiac CT reconstructed with electrocardiogram-gated full iterative reconstruction.

Reducing radiation exposure with iterative reconstruction: an inter- and intra-scanner analysis

Our purpose in this study was to compare delivered radiation exposure via computed tomography dose index volume (CTDI_vol) and dose length production (DLP) measurements from computed tomography (CT) examinations performed on scanners with and without image-quality enhancing iterative reconstruction (IR) software. A retrospective analysis was conducted on randomly selected chest, abdomen, and/or pelvis CT examinations from three different scanners from 1 January 2013 to 31 December 2013. CTDI_vol and DLP measurements were obtained from two CT scanners with and one CT scanner without IR software. To evaluate inter-scanner variability, we compared measurements from the same model CT scanners, one with and one without IR software. To evaluate intra-scanner variability, we compared measurements between two scanners with IR software from different manufacturers. CT scanners with IR software aided in the overall reduction in radiation exposure, measured as CTDI_vol by 30% and DLP by 39% when compared to a scanner without IR. There was no significant difference in CTDl_vol or DLP measurements across different manufacturers with IR software. As a result, IR software significantly decreased the radiation exposure to patients, but there were no differences in radiation measurements across CT manufacturers with IR software.