Adaptive Iterative Dose Reduction 3D Research Articles

Deep learning image reconstruction for quality assessment of iodine concentration in computed tomography: A phantom study.

Recently, deep learning reconstruction (DLR) technology aiming to improve image quality with minimal radiation dose has been applied not only to pediatric scans, but also to computed tomography angiography (CTA). To evaluate image quality characteristics of filtered back projection (FBP), hybrid iterative reconstruction [Adaptive Iterative Dose Reduction 3D (AIDR 3D)], and DLR (AiCE) using different iodine concentrations and scan parameters. Phantoms with eight iodine concentrations (ranging from 1.2 to 25.9 mg/mL) located at the edge of a cylindrical water phantom with a diameter of 19 cm were scanned. Data were reconstructed with FBP, AIDR 3D, and AiCE using various scan parameters of tube current and voltage using a 320 row-detector CT scanner. Data obtained using different reconstruction techniques were quantitatively compared by analyzing Hounsfield units (HU), noise, and contrast-to-noise ratios (CNRs). HU values of FBP and AIDR 3D were constant even when the iodine concentration was changed, whereas AiCE showed the highest HU value when the iodine concentration was low, but the HU value reversed when the iodine concentration exceeded a certain value. In the AIDR 3D and AiCE, the noise decreased as the tube current increased, and the change in noise when the iodine concentration was inconsistent. AIDR 3D and AiCE yielded better noise reduction rates than with FBP at a low tube current. The noise reduction rate of AIDR 3D and AiCE compared to that of FBP showed characteristics ranging from 7% to 35%, and the noise reduction rate of AiCE compared to that of AIDR 3D ranged from 2.0% to 13.3%. The evaluated reconstruction techniques showed different image quality characteristics (HU value, noise, and CNR) according to dose and scan parameters, and users must consider these results and characteristics before performing patient scans.

Effect of Deep Learning-based Contrast-enhanced CT Image Reconstruction on the Image Quality of the Biliary System

Objective To evaluate the effect of a deep learning reconstruction (DLR) method on the visibility of contrast-enhanced CT images of the biliary system by comparing it with different iterative reconstruction algorithms including the adaptive iterative dose reduction 3D (AIDR 3D) algorithm,forward projected model based iterative reconstruction solution (FIRST),and filtered back projection (FBP) algorithm. Methods A total of 30 patients subjected to abdominal contrast-enhanced CT and diagnosed with dilatation of common bile duct or extrahepatic bile duct were retrospectively included in this study.The images of the portal phase were reconstructed via four different algorithms (FBP,AIDR 3D,FIRST,and DLR).Signal to noise ratio (SNR) and contrast to noise ratio (CNR) of the dilated bile duct,liver parenchyma,measurable bile duct lesions,and image noise were compared between the four datasets.In subjective analyses,two radiologists independently scored the image quality (best:4 points,second:3 points;third:2 points;fourth:1 point) of the four datasets based on the noise and image visual quality of the biliary system.The Friedman and the Bonferroni-Dunn post-hoc tests were performed for comparison. Results The DLR images (bile duct:4.42±0.87;liver parenchyma:3.78±1.47) yielded higher CNR than the FBP (bile duct:2.21±1.02,P<0.001;liver parenchyma:1.43±1.29,P<0.001),AIDR 3D (bile duct:2.81±0.91,P=0.024;liver parenchyma:2.39±1.94,P=0.278),and FIRST (bile duct:2.51±1.24,P<0.001;liver parenchyma:2.45±1.81,P=0.003) images.Furthermore,the DLR images had higher SNR (bile duct:1.39±0.85,liver parenchyma:9.75±1.90) than the FBP (bile duct:0.86±0.63,P<0.001;liver parenchyma:3.31±1.12,P<0.001) and FIRST (bile duct:1.01±0.61,P=0.013;liver parenchyma:5.73±1.37,P<0.001) images,and showed lower noise (10.51±3.53) than the FBP(4.10±3.92,P<0.001),AIDR 3D (15.72±2.41,P=0.032),and FIRST (17.20±3.82,P<0.001) images.SNR and CNR showed no significant differences between FIRST and AIDR 3D images (all P>0.05).DLR images [4(4,4)] obtained higher score than FPB [1(1,1),P<0.001],AIDR3D[3 (2,3),P=0.029],and FIRST[2 (2,3),P<0.001] images. Conclusion DLR algorithm improved the subjective and objective quality of the contrast-enhanced CT image of the biliary system.

Deep learning reconstruction allows low-dose imaging while maintaining image quality: comparison of deep learning reconstruction and hybrid iterative reconstruction in contrast-enhanced abdominal CT.

We aimed to compare the radiation dose and image quality of a low-dose abdominal computed tomography (CT) protocol reconstructed with deep learning reconstruction (DLR) with those of a routine-dose protocol reconstructed with hybrid-iterative reconstruction. This retrospective study enrolled 71 patients [61 men; average age, 71.9 years; mean body mass index (BMI), 24.3 kg/m2] who underwent both low-dose abdominal CT with DLR [advanced intelligent clear-IQ engine (AiCE)] and routine-dose abdominal CT with hybrid-iterative reconstruction [adaptive iterative dose reduction 3D (AIDR 3D)]. Radiation dose parameters included volume CT dose index (CTDIvol), effective dose (ED), and size-specific dose estimate (SSDE). Mean image noise and contrast-to-noise ratio (CNR) were calculated. Image noise was measured in the hepatic parenchyma and bilateral erector spinae muscles. Moreover, subjective assessment of perceived image quality and diagnostic acceptability was performed. The low-dose protocol helped reduce the CTDIvol by 44.3%, ED by 43.7%, and SSDE by 44.9%. Moreover, the noise was significantly lower and CNR significantly higher with the low-dose protocol than with the normal-dose protocol (P<0.001). In the subjective assessment of image quality, there was no significant difference between the protocols with regard to image noise. Overall, AiCE was superior to AIDR 3D in terms of diagnostic acceptability (P=0.001). The use of AiCE can reduce overall radiation dose by more than 40% without loss of image quality compared to routine-dose abdominal CT with AIDR 3D.

Reliability and benefits of single-energy projection-based metallic artifact reduction (SEMAR) in the different orthopedic hardware for the hip.

To evaluate the performance and reliability of the single-energy metal artifact reduction (SEMAR) algorithm in patients with different orthopedic hardware at the hips. A total of 153 patients with hip instrumentation who had undergone CT with adaptive iterative dose reduction (AIDR) 3D and SEMAR algorithms between February 2015 and October 2019 were included retrospectively. Patients were divided into 5 groups by the hardware type. Two readers with 21 and 13years of experience blindly reviewed all image sets and graded the extent of artifacts and imaging quality using 5-point scales. To evaluate reliability, the mean densities and image noises were measured at the urinary bladder, veins, and fat in images with artifacts and the reference images. No significant differences were found in the mean densities of the urinary bladder, veins, and fat between the SEMAR images with artifacts (7.57 ± 9.49, 40.29 ± 23.07, 86.78 ± 38.34) and the reference images (7.77 ± 6.2, 40.27 ± 8.66, 89.10 ± 20.70) (P = .860, .994, .392). Image noises of the urinary bladder in the SEMAR images with artifacts (14.25 ± 4.50) and the SEMAR reference images (9.69 ± 1.29) were significantly higher than those in the AIDR 3D reference images (9.11 ± 1.12) (P < .001; P < .001). All AIDR 3D images were non-diagnostic (overall quality ≤ 3) and less than a quarter of the SEMAR images were non-diagnostic (16.7-23.7%), mainly in patients with prostheses [reader 1: 91.7% (22/24); reader 2: 92.6% (25/27)]. The SEMAR algorithm significantly reduces metal artifacts in CT images, more in patients with internal fixations than in patients with prostheses, and provides reliable attenuation of soft tissues.

Improvement of Image Quality Using Hybrid Iterative Reconstruction with Noise Power Spectrum Model in Computed Tomography During Hepatic Arteriography.

Objectives:In CT during hepatic arteriography (CTHA), the addition of a noise power spectrum (NPS) model to conventional hybrid iterative reconstruction (HIR) may improve spatial resolution and reduce image noise. This study aims at assessing the image quality provided by HIR with a NPS model at CTHA.Methods:This institutional review board-approved retrospective analysis included 26 patients with hepatocellular carcinomas (HCCs) who underwent CTHA. In all acquisitions, images were reconstructed with filtered back projection (FBP), adaptive iterative dose reduction 3D (AIDR), and AIDR enhanced (eAIDR) with the NPS model. Four radiologists analyzed the signal-to-noise ratio (SNR) of HCC nodules and its associated feeding arteries. The radiologists used a semiquantitative scale (–3 to +3) to rate the subjective image quality comparing both the FBP and eAIDR images with the AIDR images.Results:The feeding arteries’ attenuation was significantly higher in eAIDR compared to AIDR [514.3 ± 121.4 and 448.3 ± 107.3 Hounsfield units (HU), p < 0.05]. The image noise of eAIDR was significantly lower than that of FBP (15.2 ± 2.2 and 28.5 ± 4.8 HU, p < 0.05) and comparable to that of AIDR. The SNR of feeding arteries on eAIDR was significantly higher than on AIDR (34.1 ± 7.9 and 27.4 ± 6.3, p < 0.05). Subjective assessment scores showed that eAIDR provided better visibility of feeding arteries and overall image quality compared to AIDR (p < 0.05). The HCC nodule visibility was not significantly different among the three reconstructions.Conclusion:In CTHA, eAIDR improved the visibility of feeding arteries associated with HCC nodules without compromising nodule detection.

Comparison of low-contrast detectability between uniform and anatomically realistic phantoms\u2014influences on CT image quality assessment

ObjectivesTo evaluate the effects of anatomical phantom structure on task-based image quality assessment compared with a uniform phantom background.MethodsTwo neck phantom types of identical shape were investigated: a uniform type containing 10-mm lesions with 4, 9, 18, 30, and 38 HU contrast to the surrounding area and an anatomically realistic type containing lesions of the same size and location with 10, 18, 30, and 38 HU contrast. Phantom images were acquired at two dose levels (CTDIvol of 1.4 and 5.6 mGy) and reconstructed using filtered back projection (FBP) and adaptive iterative dose reduction 3D (AIDR 3D). Detection accuracy was evaluated by seven radiologists in a 4-alternative forced choice experiment.ResultsAnatomical phantom structure impaired lesion detection at all lesion contrasts (p < 0.01). Detectability in the anatomical phantom at 30 HU contrast was similar to 9 HU contrast in uniform images (91.1% vs. 89.5%). Detection accuracy decreased from 83.6% at 5.6 mGy to 55.4% at 1.4 mGy in uniform FBP images (p < 0.001), whereas AIDR 3D preserved detectability at 1.4 mGy (80.7% vs. 85% at 5.6 mGy, p = 0.375) and was superior to FBP (p < 0.001). In the assessment of anatomical images, superiority of AIDR 3D was not confirmed and dose reduction moderately affected detectability (74.6% vs. 68.2%, p = 0.027 for FBP and 81.1% vs. 73%, p = 0.018 for AIDR 3D).ConclusionsA lesion contrast increase from 9 to 30 HU is necessary for similar detectability in anatomical and uniform neck phantom images. Anatomical phantom structure influences task-based assessment of iterative reconstruction and dose effects.Key Points• A lesion contrast increase from 9 to 30 HU is necessary for similar low-contrast detectability in anatomical and uniform neck phantom images.• Phantom background structure influences task-based assessment of iterative reconstruction and dose effects.• Transferability of CT assessment to clinical imaging can be expected to improve as the realism of the test environment increases.

Relative Enhancement Ratio of Portal Venous Phase to Unenhanced CT in the Diagnosis of Lipid-poor Adrenal Adenomas.

Background The development of an accurate, practical, noninvasive, and widely available diagnostic approach to characterize lipid-poor adrenal lesions (greater than 10 HU at unenhanced CT) remains an ongoing demand. Purpose To investigate whether combined assessment of unenhanced and portal venous phase CT allows for the differentiation of lipid-poor adrenal adenomas from nonadenomas. Materials and Methods Patients with lipid-poor adrenal lesions who underwent unenhanced and portal venous phase CT with a single-energy scanner between January 2016 and March 2020 were identified retrospectively. For each lesion, the unenhanced and contrast-enhanced attenuation were measured; the absolute enhancement (contrast-enhanced minus unenhanced attenuation [HU]) and relative enhancement ratio ([absolute enhancement divided by unenhanced attenuation] × 100%) were calculated. The sensitivity achieved at 95% specificity to distinguish adenomas from nonadenomas was determined with receiver operating characteristic curve analysis and compared among parameters with use of the McNemar test. Results A total of 220 patients (mean age ± standard deviation, 66 years ± 12; 134 men) with 131 lipid-poor adenomas and 89 nonadenomas were analyzed. The sensitivity (achieved at 95% specificity) of the relative enhancement ratio (86% [113 of 131 adenomas; 95% CI: 79, 92] at a threshold of >210%) was higher than that of unenhanced attenuation (50% [66 of 131 adenomas; 95% CI: 42, 59] at a threshold of ≤21 HU), contrast-enhanced attenuation (3% [four of 131 adenomas; 95% CI: 1, 8] at a threshold of >120 HU), and absolute enhancement (24% [32 of 131 adenomas; 95% CI: 17, 33] at a threshold of >74 HU; all P < .001). The sensitivities of the relative enhancement ratio were 100% (58 of 58 adenomas; 95% CI: 94, 100), 83% (52 of 63 adenomas; 95% CI: 71, 91), and 30% (three of 10 adenomas; 95% CI: 7, 65) for adenomas measuring unenhanced attenuation of more than 10 HU up to 20 HU, 21-30 HU, and more than 30 HU, respectively. Conclusion A relative enhancement ratio threshold of greater than 210%, measured at unenhanced and portal venous phase CT, accurately differentiated lipid-poor adenomas from nonadenomas, particularly for lesions with unenhanced attenuation of 10-30 HU. © RSNA, 2021 Online supplemental material is available for this article.

Quantification of airway dimensions using a high-resolution CT scanner: A phantom study.

Small airways with inner diameters less than 2mm are sites of major airflow limitations in patients with chronic obstructive pulmonary disease (COPD) and asthma. The purpose of this study is to investigate the limitations for accurate assessment of small airway dimensions using both high-resolution CT (HRCT) and conventional normal-resolution CT at low dose levels. To model the normal human airways from the 3rd to 20th generations, a cylindrical polyurethane phantom with 14 airway tubes of inner diameters (ID) ranging from 0.3 to 3.4mm and wall thicknesses (WT) ranging from 0.15 to 1.6mm was placed within an Anthropomorphic QRM-Thorax phantom. The Aquilion Precision (Canon Medical Systems Corporation) HRCT scanner was used to acquire images at 80, 100, and 120kV using high resolution mode (HR, 0.25mm×160 detector configuration) and normal-resolution (NR) mode (0.5mm×80 detector configuration). The HR data were reconstructed using a 1024×1024matrix (0.22×0.22×0.25mm voxel size) and the NR data were reconstructed using a 512×512matrix (0.43×0.43×0.50mm). Two reconstruction algorithms (filtered back projection; FBP and an adaptive iterative dose reduction 3D algorithm; AIDR 3D) and three reconstruction kernels (FC30, FC52, and FC56) were investigated. The dose values ranged from 0.2 to 6.2mGy. A refined automated full-width half-maximum (FWHM) method was used for the measurement of airway dimensions, where the density profiles were computed by radial oversampling using a polar coordinate system. Both ID and WT were compared to the known dimensions using a regression model, and the root-mean-square error (RMSE) and average error were computed across all 14 airway tubes. The results indicate that the ID can be measured within a 15% error down to approximately 0.8 and 2.0mm using the HR and NR modes, respectively. The overall RMSE (and average error) of ID measurements for HR and NR were 0.10mm (-0.70%) and 0.31mm (-2.63%), respectively. The RMSE (and average error) of WT measurements using HR and NR were 0.10mm (23.27%) and 0.27mm (53.56%), respectively. The WT measurement using HR yielded a factor of two improvement in accuracy as compared to NR. High-resolution CT can provide more accurate measurements of airway dimensions as compared with NR CT, potentially improving quantitative assessment of pathologies such as COPD and asthma. The HR mode acquired and reconstructed with AIDR3D and the FC52kernel provides most accurate measurement of airway dimensions. Low-dose HR measurements at dose level above 0.9mGy can provide improved accuracy on both inner diameters and wall thicknesses compared to full dose NR airway phantom measurements.

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 (MTFTask), the noise power spectrum (NPS), and the low-contrast object-specific CNR (CNRLO) for each algorithm using three dose levels and the convolution algorithm (kernel) appropriate for abdomen, lung, and brain imaging. Additionally, MTFTask was measured at four contrast levels, and CNRLO was 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.

CT based Acute Appendicitis Severity Index for acute appendicitis and validate its effectiveness in predicting complicated appendicitis.

To propose a CT-based scoring system called Acute Appendicitis Severity Index (AASI) for diagnosis of acute appendicitis and validates its effectiveness in predicting complicated appendicitis. Retrospective analyses of CT images of 120 adult patients with pathologically proven uncomplicated (n = 64) and complicated (n = 56) acute appendicitis were performed. All patients had undergone a CT scan of the abdomen and pelvis using 320 multi-detectors computed tomography with Adaptive Iterative Dose Reduction 3D (AIDR 3D). CT image parameters were identified and used to develop a CT-based scoring system (AASI) to predict the severity of acute appendicitis and its outcome. All image analysis was performed by 2 radiologists and the total score was assigned to each patient based on the proposed CT scoring system. Validation of the effectiveness of the proposed scoring system (AASI) was done using statistical models. The mean and standard deviation of AASI was found to be significantly higher (P value = 0.001) in the complicated appendicitis group (observer 1 = 10.2 ± 1.6 and observer 2 = 9.63 ± 2.3) as compared to that in uncomplicated acute appendicitis group (observer 1 = 7.09 ± 2.2 and observer 2 = 6.38 ± 1.9). There was an excellent interobserver agreement of the Acute Appendicitis Severity Index for both the uncomplicated and complicated appendicitis groups (K = 0.89, 95% CI = 0.87-0.92, P = 0.001). The cutoff value for AASI used to predict complicated appendicitis was taken as 9.5 and 8.5. This resulted in an AUC of 0.877 and 0.848, accuracy of 83% and 81%, the sensitivity of 75% and 80%, the specificity of 90% and 81%, the positive predictive value of 87% and 78%, and a negative predictive value of 81% and 83% by both reviewers respectively. The proposed CT-based AASI is a reliable parameter for the prediction of complicated appendicitis.

PERANAN ADAPTIVE ITERATIVE DOSE REDUCTION 3D (AIDR 3D) DALAM MENINGKATKAN KUALITAS CITRA MSCT ABDOMEN

Background: Abdominal MSCT has better sensitivity and specificity, however its radiation exposure is high. Adaptive Iterative Dose Reduction (AIDR) 3D is an iterative reconstruction technology on Toshiba which produces a better image quality by reducing noise and streak artifacts in low dose. Based on author’s observation, abdominal MSCT performed at the hospital uses a standard routine abdominal MSCT protocol without adjusting the level of AIDR 3D. AIDR 3D has several strength level allowing an optimal image quality. This study was aimed to explain the role of AIDR 3D in improving the image quality and radiation dose of abdominal MSCT.&#x0D; Methods: This research method is descriptive with the literature study approach, by collecting articles from ProQuest, Google Scholar, PubMed, SpringerLink, and ScienceDirect about the role of AIDR 3D on abdominal MSCT published 2013-2020. The articles were selected according to the inclusion criteria. So there were 4 relevant journals which were then analyzed by making a journal summary, evaluating, giving opinions so that conclusions and suggestions can be drawn.&#x0D; Result: The results showed that AIDR 3D can improve the image quality of abdominal MSCT by reducing noise, artifacts and increasing CNR, SNR, image sharpness. Noise reduction and CNR increase, the most prominent SNR is found in AIDR 3D Strong, followed by Standard and Mild. AIDR 3D can reduce radiation doses better without reducing image quality&#x0D; Conclusion: AIDR 3D can improve image quality on abdominal MSCT and the use of integrated AIDR 3D SUREExposore 3D can reduce radiation doses better without reducing image quality. Reduction of radiation dose between 23% to 76%.

Double Dose Reduction in the Equilibrium Phase of Chest-Pelvic CT With Low Tube Voltage and Forward-Projected Model-Based Iterative Reconstruction Solution.

ObjectivesThis study aimed to examine whether a new imaging method (80-kV forward-projected model-based iterative reconstruction solution [FIRST] protocol) that uses a combination of low tube voltage and FIRST can reduce radiation dose and contrast medium volume by comparing the quality of the resulting image with that of the image obtained by 120-kV adaptive iterative dose reduction 3D protocol in the equilibrium phase of chest-pelvic computed tomography (CT).Subjects and methodsTwenty-seven patients underwent CT by both protocols on different days. Two radiologists subjectively assessed image quality by scoring axial images for sharpness, contrast enhancement, noise, artifacts, and overall quality. The mean CT values, standard deviations, contrast-to-noise ratios, and signal-to-noise ratios in the liver, aorta, and erector spinae muscles were used for objective assessment. Radiation dose parameters included the CT dose index volume, dose-length product, effective dose, and size-specific dose estimate. Results were compared for different body mass index categories.ResultsThe 80-kV FIRST protocol helped achieve mean reductions of 36.3%, 35.7%, and 36.6% in CT dose index volume, effective dose, and size-specific dose estimate, respectively (p < 0.01). Therefore, this protocol was regarded as comparable to the conventional protocol in image quality, except for visual sharpness.ConclusionsThe 80-kV FIRST protocol is capable of reducing radiation dose and contrast medium volume compared to the adaptive iterative dose reduction 3D protocol in the equilibrium phase of chest-pelvic CT.

Development of a method to create uniform phantoms for task-based assessment of CT image quality.

PurposeTo develop a customized method to produce uniform phantoms for task‐based assessment of CT image quality.MethodsContrasts between polymethyl methacrylate (PMMA) and fructose solutions of different concentrations (240, 250, 260, 280, 290, 300, 310, 320, 330, and 340 mg/mL) were calculated. A phantom was produced by laser cutting PMMA slabs to the shape of a patient’s neck. An opening of 10 mm diameter was cut into the left parapharyngeal space. An angioplasty balloon was inserted and filled with the fructose solutions to simulate low‐contrast lesions. The phantom was scanned with six tube currents. Images were reconstructed with filtered back projection (FBP) and adaptive iterative dose reduction 3D (AIDR 3D). Calculated and measured contrasts were compared. The phantom was evaluated in a detectability experiment using images with 4 and 20 HU lesion contrast.ResultsLow‐contrast lesions of 4, 9, 11, 13, 18, 20, 24, 30, 35, and 37 HU contrast were simulated. Calculated and measured contrasts correlated excellently (r = 0.998; 95% confidence interval: 0.991 to 1). The mean ± SD difference was 0.41 ± 2.32 HU (P < 0.0001). Detection accuracy and reader confidence were 62.9 ± 18.2% and 1.58 ± 0.68 for 4 HU lesion contrast and 99.6 ± 1.3% and 4.27 ± 0.92 for 20 HU lesion contrast (P < 0.0001), confirming that the method produced lesions at the threshold of detectability.ConclusionA cost‐effective and flexible approach was developed to create uniform phantoms with low‐contrast signals. The method should facilitate access to customized phantoms for task‐based image quality assessment.

Improvement of image quality on low-dose dynamic myocardial perfusion computed tomography with a novel 4-dimensional similarity filter.

The aim of this study was to evaluate the effect of a novel 4-dimensional similarity filter (4DSF) on quantitative and qualitative parameters of low-dose dynamic myocardial computed tomography perfusion (CTP) images.In this retrospective study, medical records of 32 patients with suspected or known coronary artery disease who underwent dynamic myocardial CTP at 80 kV were included. The 4DSF reduces noise by averaging voxels that have similar dynamic behavior after adaptive iterative dose reduction 3D (AIDR3D) and deformable image registration were applied. Qualitative (artefact, contour sharpness, and myocardial homogeneity [1 = poor; 2 = intermediate; 3 = good]) and quantitative measurement (standard deviation [SD] and signal-to-noise ratio [SNR]) were compared between the 4DSF and AIDR3D. Contrast-to-noise ratio (CNR) between ischemic and normal remote myocardium was also assessed using myocardial perfusion magnetic resonance imaging as the reference standard in seven patients.The 4DSF was successfully applied to all the images. Improvement in subjective image quality yielded by 4DSF was higher than that yielded by AIDR3D (homogeneity, 1.0 [3 vs 2]; artefact, 1.5 [3 vs 1.5]; P < .001) in all patients. The 4DSF significantly decreased the SD by 59% (AIDR3D vs 4DSF: 33.5 ± 0.4 vs 13.8 ± 0.4, P < .001), increased the SNR by 134% (AIDR3D vs 4DSF: 4.4 ± 0.2 vs 10.3 ± 0.2, P < .001), and increased the CNR by 131% (AIDR3D vs 4DSF: 1.6 ± 0.2 vs 3.7 ± 0.2, P < .001).The 4DSF improved the qualitative and quantitative parameters of low-dose dynamic myocardial CTP images.

P6182Combination of a new iterative reconstruction technique with low tube voltage and high tube current has important role of detection of late enhancement on 320 slice CT

Abstract Background New iterative reconstruction tecniques, including Adaptive Iterative Dose Reduction 3D (AIDR 3D) and Forward Projected Model-based Iterative Reconstruction SoluTion (FIRST), have been recently available on new generation 320 slice CT, and they can provide high-quality CT images. Purpose The aim of this study was to evaluate the diagnostic performance of detection of abnormal late enhancement (LE) in left ventricular (LV) myocardium (LVM) using 320-slice CT with new iterative reconstruction techiniques, AIDR 3D (Figure A) and FIRST (Figure B). Methods A total of 100 patients who were suspected of having various myocardial diseases and underwent late phase acquisition both on cardiac CT and CMR within 3 months were analyzed. The first 50 consecutive patients (Group 1) underwent 320-slice CT with AIDR 3D, 120 Kv tube voltage, 519±71 mA tube current. The next 50 consecutive patients (Group 2) underwent 320-slice CT with FIRST, 80 or 100Kv tube voltage, 803±20 mA tube current. We compared diagnostic accuracy of CT for detection of LE in LVM against that of CMR (the gold standard) in between the 2 groups. Results On patient-by-patient analysis, sensitivity, specificity, positive (PPV) and negative predictive values (NPV), and overall accuracy for detection of LE on CT vs CMR were 87, 95, 96, 82, and 90% in Group 1, and 97, 83, 91, 88, and 90% in Group 2. There were no significant difference of diagnostic accuracy on patient-by-patient analysis in between the 2 groups (Figure C). However, on a segment-by-segment analysis (using 17 American Heart Association LV segment model), these values for detection of LE on CT vs CMR were 60, 95, 73, 91, and 88% in Group 1, and 85, 95, 86, 95, and 93% in Group 2. Sensitivity, PPV, NPV and overall accuracy were significantly higher in Group 2 than in Group 1 (all P&lt;0.01) (Figure D). Conclusions Diagnostic accuracy of detection of LE in LVM on CT combining low tube voltage and high tube current acquisition on a new generation 320-slice CT with FIRST was superior to 320-slice CT with AIDR 3D. Acknowledgement/Funding TSUCHIYA MEMORIAL MEDICAL FOUNDATION

Evaluation of the depiction ability of the microanatomy of the temporal bone in quarter-detector CT: Model-based iterative reconstruction vs hybrid iterative reconstruction.

Little is known regarding differences between model-based iterative reconstruction (MBIR) and hybrid iterative reconstruction (HIR) in temporal bone computed tomography (CT). This study compared the ability to depict microstructures in temporal bone in quarter-detector CT (QDCT) between MBIR and HIR.Sixty-two temporal bones in 31 consecutive adult patients who underwent QDCT were included. Reconstruction was performed with Forward projected model-based Iterative Reconstruction SoluTion (FIRST) BONE mild mode and Adaptive Iterative Dose Reduction 3D (AIDR3D) enhanced mild mode. Imaging quality was graded for 3 microstructures (spiral osseous lamina, tympanic membrane, and singular canal).Spiral osseous lamina was significantly well-delineated in the AIDR3D enhanced group, compared with the FIRST group. In nearly all cases with FIRST, spiral osseous lamina was poorly defined. Although there was no significant difference, depiction of the tympanic membrane and singular canal tended to be better with AIDR3D enhanced mode.Routine reconstruction for preoperative temporal bone CT should be performed with HIR, rather than MBIR.

The usefulness of full-iterative reconstruction algorithm for the visualization of cystic artery on CT angiography.

To evaluate the potential of full-iterative reconstruction (IR) for improving image quality of the cystic artery on CT angiography and to assess observer performance. Thirty patients who underwent both liver dynamic CT and conventional angiography were included in this retrospective study. All CT data were reconstructed through filtered back projection (FBP), adaptive iterative dose reduction 3D (AIDR3D), and forward-projected, model-based, iterative reconstruction solution (FIRST), respectively. In objective study, we analyzed mean ΔCT numbers (the difference between the HU peak of the vessel and the background) and full-width at tenth-maximum (FWTM) of three parts of the cystic artery by profile curve method comparing the three reconstructions. Subjectively, visualization was evaluated using a four-point scale performed by two blinded observers. ANOVA was used for statistical analysis. In all parts of the cystic artery, the mean ΔCT number of FIRST was shown to be significantly better than that of FBP and AIDR3D (p < 0.05). FWTM in FIRST was the smallest in all of the vessels. The mean visualization score was significantly better with FIRST than with other CT reconstructions (p < 0.05). The FIRST algorithm led to improved CTA visualization of the cystic artery.

Characterization of office laser printers for 3-D printing of soft tissue CT phantoms.

The purpose of our study is to develop and evaluate a method for radiopaque 3-D printing (R3P) of soft tissue computed tomography (CT) phantoms with office laser printers. Five laser printers from different vendors are tested for toner CT attenuation. A liver phantom is created by printing CT images of a patient liver on office paper. One thousand eight hundred sixty paper sheets are printed with three repeated prints per page, resulting in a stack of 18.6cm. The phantom is examined with 12 tube current settings. Images are reconstructed using filtered back projection (FBP) and iterative reconstruction [adaptive iterative dose reduction 3D (AIDR 3D)]. Seven radiologists rated image quality of all acquisitions. Toner attenuation of all investigated printers increased linearly with the print template grayscale. The liver phantom reproduced anatomic detail and attenuation values of the patient ( HU difference ). Image quality scores increased with dose but did not vary significantly above a threshold dose for AIDR 3D. Overall, AIDR 3D reconstructed images are rated superior to FBP reconstructions ( ). In conclusion, R3P with standard office laser printers can generate soft tissue CT phantoms without hardware manipulations but with limited flexibility regarding attenuation properties of the printed toner material.

The impact of adaptive iterative dose reduction 3D on the improvement of shoulder image quality in head and neck CTA

Objective: The aim of this study was to determine the impact of adaptive iterative dose reduction 3 D (AIDR3D) on the improvement of shoulder image quality in low-radiographic dose head and neck CT angiography (CTA).Materials and methods: Ninety patients who underwent CTA examination were randomly divided into two groups, namely group A (n = 45) and B (n = 45). Patients in group A were scanned under 120 kV and 300 mA, with images reconstructed by filtered back projection (FBP), and patients in group B were scanned under 80 kV and auto mA with images reconstructed by AIDR3D. Image quality was accessed by two experienced radiologists. The noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of common carotid artery (CCA) at C7 level, and radiation dosage were compared between the two groups.Results: The score of CCA in group B was significantly higher than group A (p < 0.05), and there were no significant differences in the scores of carotid sinus and internal carotid artery between the two groups (p > 0.05). The score of intracranial artery in group B was lower than that of group A, however, the image quality in group B can meet the requirement of clinical diagnosis. The noise value of CCA at C7 level in group B was significantly lower than that of group A (p < 0.05). SNR and CNR values of CCA at C7 level in group B were significantly higher than those of group A (p < 0.05). Effective radiation dose in group B was significantly decreased compared with group A (p < 0.05).Conclusion: AIDR3D remarkably improved image quality in low-radiographic dose head and neck CTA over FBP, which made the low-dose CTA images meet the requirement of clinical diagnosis.

Assessment of iterative image reconstruction on kidney and liver donors: Potential role of adaptive iterative dose reduction 3D (AIDR 3D) technology

ObjectiveThe aim of this study was to evaluate the radiation exposure levels in two different types of subjects including liver and kidney donors in diagnostic assessment of transplant operation and also the significance of dose reduction on total effective dose. Materials and methodsA number of Sixty subjects (40 males and 20 females, average age of 35 ± 10 years) were randomly prospectively recruited and equally divided into two distinct groups namely kidney donors (KD, 24 M and 6 F) and liver donors (LD, 21 M and 9 female). Kidney donors were divided into full dose (KFD, n = 20) group and low dose (KLD, n = 10) group. They had undergone dynamic renal scan using Tc99 m-DTPA, CT renal angiography and x-ray plain radiograph. Liver donors were divided into full dose (LFD, n = 20) and low dose (LLD, n = 10) groups and performed CT liver volumetry. The CT dose index (CTDIvol), dose length product (DLP), total milli-ampere product time mAs, effective dose and image noise index were measured in all subjects of kidney and liver donors comparing full dose and low dose protocols. ResultsIn comparison of all subjects of kidney donor groups (KFD vs KLD), the parameters (mAs = 16386.8 ± 3140.7 vs 2830.286 ± 831.676), (CTDIvol = 183.19 ± 32.58 mGy vs. 45.5 ± 13.3 mGy), DLP = 2884 ± 859.0 mGy.cm vs. 1437.5 ± 399 mGy.cm) and (effective dose = 49.0 ± 9.0 mSv vs. 18.9 mSv±5.7 mSv) were significant, p < 0.0005. Statistical evaluation of liver donors groups (LFD vs LLD) showed that (mAs = 14348.8 ± 4571.8 vs 3123.357 ± 794.5), (CTDIvol = 333.6 ± 59.5 mGy vs. 51.4 ± 13 mGy), (DLP = 3268.3 ± 604.3 mGy.cm vs 1260.5 ± 404.6 mGy.cm) and (effective dose = 43.3 mSv±12.9 mSv vs. 21.6 ± 5.9 mSv) are statistically significant, p < 0.0005. Nevertheless, the comparative evaluation of the image quality noise index of KFD vs KLD groups and LFD vs LLD showed a no statistical significance p > 0.05. ConclusionRenal and liver donors bear a relatively significant radiation dose due to diagnostic evaluation and patient management. The CT iterative reconstruction using AIDR3D proved very valuable tool in dose reduction such that it can reduce 37% in kidney donors and 48% in liver donors while able to maintain an acceptable image quality. Monitoring of those subjects on the clinical and radiobiological levels are recommended.