Levels Of Adaptive Statistical Iterative Reconstruction Research Articles

CT Image Quality Assessment by a Channelized Hotelling Observer: Optimization of Adaptive Statistical Iterative Reconstruction for Radiation Dose Reduction and Improving Image Quality of Pediatric Abdominal CT Scan

Background: Iterative reconstruction (IR) techniques have tried to reduce the radiation dose of computed tomography (CT) scans while maintaining the image quality. One of the IR techniques is the adaptive statistical iterative reconstruction (ASIR). Increasing the amount of ASIR in image reconstruction can lead to the emergence of artifacts and reduce the ability to detect objects with low contrast. Objective: This study aimed to optimize the ASIR technique to reduce the radiation dose and increase image quality in pediatric abdominal CT. Methods: This is a phantom study performed using variable tube current (40,100,140 and 200mA) and ASIR level (ASIR 10% to ASIR 100%). Various criteria including noise, high-contrast spatial resolution, and Channelized Hotelling observer’s model were used to compare image quality at different captured levels. In this study CHO model was used for low contrast detectability. Results: The result was quit promising in the term of CHO’s used for mentioned purposes. The noise of reconstructed images with 30% ASIR and higher levels had a significant difference compared to the reconstructed images by the Filter Back Projection (FBP) method (P < 0.05). The spatial resolution of the images with tube currents of 140, 100, and 40 mA reconstructed with 30, 50, and 80% levels of ASIR technique was equal to 0.8 ± 0.144 pairs of lines per millimeter. The amount of the spatial resolution of images obtained with standard radiation dose and reconstructed by FBP method was 1 pair of lines per mm (p> 0.05). Conclusion: Based on the results of this study, using 50% ASIR for the pediatric population can reduce the radiation dose on abdominal and pelvic CT scans by 50% while maintaining image quality. Furthermore using ASIR 50% only for the reconstruction of abdominal and pelvic images in children at standard radiation dose leads to optimal image quality.

Quality Assessment of Computed Tomography Images using a Channelized Hoteling Observer: Optimization of Protocols in Clinical Practice.

This study investigated the feasibility of channelized hoteling observer (CHO) model in computed tomography (CT) protocol optimization regarding the image quality and patient exposure. While the utility of using model observers such as to optimize the clinical protocol is evident, the pitfalls associated with the use of this method in practice require investigation. This study was performed using variable tube current and adaptive statistical iterative reconstruction (ASIR) level (ASIR 10% to ASIR 100%). Various criteria including noise, high-contrast spatial resolution, CHOs model were used to compare image quality at different captured levels. For the implementation of CHO, we first tuned the model in a restricted dataset and then it to the evaluation of a large dataset of images obtained with different reconstruction ASIR and filtered back projection (FBP) levels. The results were promising in terms of CHO use for the stated purposes. Comparisons of the noise of reconstructed images with 30% ASIR and higher levels of noise in rebuilding images using the FBP approach showed a significant difference (P < 0.05). The spatial resolution obtained using various ASIR levels and tube currents were 0.8 pairs of lines per millimeter, which did not differ significantly from the FBP method (P > 0.05). Based on the results, using 80% ASIR can reduce the radiation dose on lungs, abdomen, and pelvis CT scans while maintaining image quality. Furthermore using ASIR 60% only for the reconstruction of lungs, abdomen, and pelvis images at standard radiation dose leads to optimal image quality.

Application of computer-aided detection (CAD) software to automatically detect nodules under SDCT and LDCT scans with different parameters

PurposeTo explore the application of computer-aided detection (CAD) software on automatically detecting nodules under standard-dose CT (SDCT) and low-dose CT (LDCT) scans with different parameters including definition modes and blending levels of adaptive statistical iterative reconstruction (ASIR), whose influence was important to optimize radiology workflow serving for clinical work. Materials and methods117 patients underwent SDCT and LDCT scans. The comprehensive performance of CAD in detect pulmonary nodules including under different ASIR blending levels (0%, 60%, and 80%) and high-definition (HD) or non-HD modes were assessed. The true positive (TP) rate, false positive (FP) rate and the sensitivity were recorded. ResultsThe stand-alone sensitivity of CAD system was 78.03% (515/660) in SDCT images and 70.15% (456/650) on LDCT images (p < 0.05). The sensitivity of CAD system to pulmonary nodules under non-HD mode was higher than that under HD mode. The detectability of nodules in images reconstructed with 60% and 80% ASIR was found significantly superior to that with 0% ASIR (p < 0.001). The overall sensitivity of CAD system on LDCT images reconstructed with 60% ASIR under HD mode was greater than that with 0% ASIR (p < 0.05), but lower than that with 80% ASIR. However, under non-HD mode, CAD demonstrated a comparable performance on LDCT images reconstructed with 60% ASIR to those reconstructed with 80% ASIR. ConclusionUsing the CAD system to detect pulmonary nodules on LDCT images with appropriate levels of ASIR could maintain high diagnostic sensitivity while reducing the radiation dose, which is useful to optimize the radiology workflow.

Adaptive statistical iterative reconstruction (ASIR) affects CT radiomics quantification in primary colorectal cancer

ObjectivesTo investigate whether adaptive statistical iterative reconstruction (ASIR), a hybrid iterative CT image reconstruction algorithm, affects radiomics feature quantification in primary colorectal cancer compared to filtered back projection. Additionally, to establish whether radiomics from single-slice analysis undergo greater change than those from multi-slice analysis.MethodsFollowing review board approval, contrast-enhanced CT studies from 32 prospective primary colorectal cancer patients were reconstructed with 20% ASIR level increments, from 0 to 100%. Radiomics analysis was applied to single-slice and multi-slice regions of interest outlining the tumour: 70 features, including statistical (first-, second- and high-order) and fractal radiomics, were generated per dataset. The effect of ASIR was calculated by means of multilevel linear regression.ResultsTwenty-eight CT datasets were suitable for analysis. Incremental ASIR levels determined a significant change (p < 0.001) in most statistical radiomics features, best described by a simple linear relationship. First-order statistical features, including mean, standard deviation, skewness, kurtosis, energy and entropy, underwent a relatively small change in both single-slice and multi-slice analysis (median standardised effect size B = 0.08). Second-order statistical features, including grey-level co-occurrence and difference matrices, underwent a greater change in single-slice analysis (median B = 0.36) than in multi-slice analysis (median B = 0.13). Fractal features underwent a significant change only in single-slice analysis (median B = 0.49).ConclusionsIncremental levels of ASIR affect significantly CT radiomics quantification in primary colorectal cancer. Second-order statistical and fractal features derived from single-slice analysis undergo greater change than those from multi-slice analysis.Key Points• Incremental levels of ASIR determine a significant change in most statistical (first-, second- and high-order) CT radiomics features measured in primary colorectal cancer, best described by a linear relationship.• First-order statistical features undergo a small change, both from single-slice and multi-slice radiomics analyses.• Most second-order statistical features undergo a greater change in single-slice analysis than in multi-slice analysis. Fractal features are only affected in single-slice analysis.

Computed Tomography-Guided Tumor Ablation: Analysis and Optimization of Computed Tomography Technique With Various Ablation Devices.

Ablation device-associated computed tomography beam hardening artifacts can make tumor margin visualization and its relationship to the ablation applicator tip challenging. Determine optimal scanning conditions for currently-used applicators. Eleven applicators were placed in ex vivo cow livers with implanted mock tumors, surrounded by bolus gel. Various computed tomography scans were performed at 440 mA with 5 mm thickness changing kVp (80, 100, 120, 140), scan time (0.5, 0.7, 1.0, 2.0 seconds), adaptive statistical iterative reconstruction (ASiR) (30, 60, 90), scan type (helical, axial), pitch (0.5, 0.94, 1.37, 1.75), and reconstruction algorithm (soft, standard, lung). Two radiologists blindly scored the images for image quality and artifact quantitatively. Cool-tip single (CTS) RF electrode (Covidien) performed significantly better than all other devices in both perceived image quality and artifact while Boston Scientific 4.0 RF electrode (Boston Scientific) underperformed (all P < 0.001), when not controlling for any other factors. An effect for artifact (P < 0.001) was found for kVp and device: for most conditions, 80 kVp was rated significantly lower than all other levels, whereas 120 and 140 performed significantly better than 100 and 80. No significant effect with ASiR level and device was found for the artifact. There was an effect observed for artifact (P < 0.001) between scan time and probe: for most devices, 0.5 seconds was rated significantly lower than all other scan times, but CTS was resilient-showing no difference from other scan times. Algorithm did not show any significant effects. Taking into account ASiR, kVp, and time, CTS outperformed all other devices. Higher kVp and scan times reduce device artifacts. It appears that CTS performs the best, even when considering ASiR, kVp, pitch, scan type, and scan time.

Influence of Adaptive Statistical Iterative Reconstruction on coronary plaque analysis in coronary computed tomography angiography

PurposeThe purpose of this study was to study the effect of iterative reconstruction (IR) software on quantitative plaque measurements in coronary computed tomography angiography (CCTA). MethodsThirty patients with a three clinical risk factors for coronary artery disease (CAD) had one CCTA performed. Images were reconstructed using FBP, 30% and 60% adaptive statistical IR (ASIR). Coronary plaque analysis was performed as per patient and per vessel (LM, LAD, CX and RCA) measurements. Lumen and vessel volumes and plaque burden measurements were based on automatic detected contours in each reconstruction. Lumen and plaque intensity measurements and HU based plaque characterization were based on corrected contours copied to each reconstruction. ResultsNo significant changes between FBP and 30% ASIR were found except for lumen- (−2.53 HU) and plaque intensities (−1.28 HU). Between FBP and 60% ASIR the change in total volume showed an increase of 0.94%, 4.36% and 2.01% for lumen, plaque and vessel, respectively. The change in total plaque burden between FBP and 60% ASIR was 0.76%. Lumen and plaque intensities decreased between FBP and 60% ASIR with −9.90 HU and −1.97 HU, respectively. The total plaque component volume changes were all small with a maximum change of −1.13% of necrotic core between FBP and 60% ASIR. ConclusionsQuantitative plaque measurements only showed modest differences between FBP and the 60% ASIR level. Differences were increased lumen-, vessel- and plaque volumes, decreased lumen- and plaque intensities and a small percentage change in the individual plaque component volumes.

Dose reduction in computed tomography using adaptive statistical iterative reconstruction (ASIR). A phantom study

Introduction Computed Tomography (CT) has been an invaluable tool in medical diagnosis, but its increasing use has been also responsible for a significant increase in population radiation exposure. Iterative reconstruction algorithms have been recently introduced in clinical practice, in an attempt to decrease CT radiation dose. Purpose The purpose of this work was to investigate quantitatively the relationship between image quality and dose in CT and to establish the effectiveness of ASIR in reducing radiation dose, without compromising image quality. Materials and methods A CT image quality phantom was scanned in a 64-slice GE Optima CT660 scanner, using a typical head acquisition protocol with mA modulation, at 8 different Noise Index levels, corresponding to a CTDI vol range of 18.7–91.2 mGy. Scanned data were used to reconstruct 5 mm slices, using (a) only FBP and (b) FBP blended with 3 ASIR levels (20%–40%–60%). Mean CT number, image noise (SD) and CNR were measured in appropriately selected slices in all reconstructed images by three different observers. Results A reduction in image noise by 35–55% for the same radiation dose was observed in the ASIR reconstructed images compared to FBP, whereas images with similar noise levels could be produced using ASIR with 55–75% less dose compared to FBP. Similarly, ASIR with at least 40% blending, was found to increase CNR by 20–45% compared to FBP at the same radiation dose, and could produce images with comparable CNR with 20–60% less dose compared to FBP. Conclusion ASIR can be very effective in reducing the radiation dose in CT, while preserving image quality.

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

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

Optimal Adaptive Statistical Iterative Reconstruction Percentage in Dual-energy Monochromatic CT Portal Venography

The aim of this article was to study the influence of different adaptive statistical iterative reconstruction (ASIR) percentages on the image quality of dual-energy computed tomography (DECT) portal venography in portal hypertension patients. DECT scans of 40 patients with cirrhosis (mean age, 56 years) at the portal venous phase were retrospectively analyzed. Monochromatic images at 60 and 70 keV were reconstructed with four ASIR percentages: 0%, 30%, 50%, and 70%. Computed tomography (CT) numbers of the portal veins (PVs), liver parenchyma, and subcutaneous fat tissue in the abdomen were measured. The standard deviation from the region of interest of the liver parenchyma was interpreted as the objective image noise (IN). The contrast-noise ratio (CNR) between PV and liver parenchyma was calculated. The diagnostic acceptability (DA) and sharpness of PV margins were obtained using a 5-point score. The IN, CNR, DA, and sharpness of PV were compared among the eight groups with different keV + ASIR level combinations. The IN, CNR, DA, and sharpness of PV of different keV + ASIR groups were all statistically different (P < 0.05). In the eight groups, the best and worst CNR were obtained in the 60 keV + 70% ASIR and 70 keV + 0% ASIR (filtered back-projection [FBP]) combination, respectively, whereas the largest and smallest objective IN were obtained in the 60 keV + 0% ASIR (FBP) and 70 keV + 70% combination. The highest DA and sharpness values of PV were obtained at 50% ASIR for 60 keV. An optimal ASIR percentage (50%) combined with an appropriate monochromatic energy level (60 keV) provides the highest DA in portal venography imaging, whereas for the higher monochromatic energy (70 keV) images, 30% ASIR provides the highest image quality, with less IN than 60 keV with 50% ASIR.

CT colonography at low tube potential: using iterative reconstruction to decrease noise

To determine the level of iterative reconstruction required to reduce increased image noise associated with low tube potential computed tomography (CT). Fifty patients underwent CT colonography with a supine scan at 120kVp and a prone scan at 100kVp with other scan parameters unchanged. Both scans were reconstructed with filtered back projection (FBP) and increasing levels of adaptive statistical iterative reconstruction (ASiR) at 30%, 60%, and 90%. Mean noise, soft tissue and tagged fluid attenuation, contrast, and contrast-to-noise ratio (CNR) were collected from reconstructions at both 120 and 100kVp and compared using a generalised linear mixed model. Decreasing tube potential from 120 to 100kVp significantly increased image noise by 30-34% and tagged fluid attenuation by 120HU at all ASiR levels (p<0.0001, all measures). Increasing ASiR from 0% (FBP) to 30%, 60%, and 90% resulted in significant decreases in noise and increases in CNR at both tube potentials (p<0.001, all comparisons). Compared to 120kVp FBP, ASiR greater than 30% at 100kVp yielded similar or lower image noise. Iterative reconstruction adequately compensates for increased image noise associated with low tube potential imaging while improving CNR. An ASiR level of approximately 50% at 100kVp yields similar noise to 120kVp without ASiR.

Qualitative and quantitative assessment of smoking-related lung disease: effect of iterative reconstruction on low-dose computed tomographic examinations.

The purpose of this research is to examine the role that differing levels of adaptive statistical iterative reconstruction (ASIR) have on the qualitative and quantitative assessment of smoking-related lung disease. Institutional board review approval was obtained. A total of 52 patients undergoing clinically indicated low-dose computed tomographic (CT) examinations of the chest (100 kVp, 65 mAs, mean radiation dose 1.0±0.12 mSv), with reconstruction of data with different levels of blended ASIR (0%, 40%, and 100%), were consented. Qualitative assessment of CT data sets was performed by 2 trained thoracic radiologists blinded to clinical history, spirometry, and quantitative data for the presence of emphysema (%/lung zone) and the degree of respiratory bronchiolitis. Quantitative analysis was performed (Apollo Image analysis, VIDA Diagnostics) to assess emphysema and airway measures of chronic obstructive pulmonary disease. The application of ASIR results in alterations in both qualitative and quantitative assessment of smoking-related lung disease. As levels of ASIR increased, both readers scored more respiratory bronchiolitis (P<0.05). At increased levels of ASIR (ie, 100% vs. 0%), the amount of emphysema measured (% below -950 HU) decreased, the number of airways measured diminished, and the airway thickness (Pi10mm) increased (P<0.001). The use of ASIR alters both the qualitative and quantitative assessment of smoking-related lung disease. Although a powerful tool to allow dose reduction, caution must be exercised when iterative reconstruction techniques are utilized when evaluating CT examinations for findings of chronic obstructive pulmonary disease.

Combining Automatic Tube Current Modulation with Adaptive Statistical Iterative Reconstruction for Low-Dose Chest CT Screening

ObjectiveTo reduce radiation dose while maintaining image quality in low-dose chest computed tomography (CT) by combining adaptive statistical iterative reconstruction (ASIR) and automatic tube current modulation (ATCM).MethodsPatients undergoing cancer screening (n = 200) were subjected to 64-slice multidetector chest CT scanning with ASIR and ATCM. Patients were divided into groups 1, 2, 3, and 4 (n = 50 each), with a noise index (NI) of 15, 20, 30, and 40, respectively. Each image set was reconstructed with 4 ASIR levels (0% ASIR, 30% ASIR, 50% ASIR, and 80% ASIR) in each group. Two radiologists assessed subjective image noise, image artifacts, and visibility of the anatomical structures. Objective image noise and signal-to-noise ratio (SNR) were measured, and effective dose (ED) was recorded.ResultsIncreased NI was associated with increased subjective and objective image noise results (P<0.001), and SNR decreased with increasing NI (P<0.001). These values improved with increased ASIR levels (P<0.001). Images from all 4 groups were clinically diagnosable. Images with NI = 30 and 50% ASIR had average subjective image noise scores and nearly average anatomical structure visibility scores, with a mean objective image noise of 23.42 HU. The EDs for groups 1, 2, 3 and 4 were 2.79±1.17, 1.69±0.59, 0.74±0.29, and 0.37±0.22 mSv, respectively. Compared to group 1 (NI = 15), the ED reductions were 39.43%, 73.48%, and 86.74% for groups 2, 3, and 4, respectively.ConclusionsUsing NI = 30 with 50% ASIR in the chest CT protocol, we obtained average or above-average image quality but a reduced ED.

Evaluation of image quality and radiation dose by adaptive statistical iterative reconstruction technique level for chest CT examination

The purpose of this research is to determine the adaptive statistical iterative reconstruction (ASIR) level that enables optimal image quality and dose reduction in the chest computed tomography (CT) protocol with ASIR. A chest phantom with 0-50 % ASIR levels was scanned and then noise power spectrum (NPS), signal and noise and the degree of distortion of peak signal-to-noise ratio (PSNR) and the root-mean-square error (RMSE) were measured. In addition, the objectivity of the experiment was measured using the American College of Radiology (ACR) phantom. Moreover, on a qualitative basis, five lesions' resolution, latitude and distortion degree of chest phantom and their compiled statistics were evaluated. The NPS value decreased as the frequency increased. The lowest noise and deviation were at the 20 % ASIR level, mean 126.15 ± 22.21. As a result of the degree of distortion, signal-to-noise ratio and PSNR at 20 % ASIR level were at the highest value as 31.0 and 41.52. However, maximum absolute error and RMSE showed the lowest deviation value as 11.2 and 16. In the ACR phantom study, all ASIR levels were within acceptable allowance of guidelines. The 20 % ASIR level performed best in qualitative evaluation at five lesions of chest phantom as resolution score 4.3, latitude 3.47 and the degree of distortion 4.25. The 20 % ASIR level was proved to be the best in all experiments, noise, distortion evaluation using ImageJ and qualitative evaluation of five lesions of a chest phantom. Therefore, optimal images as well as reduce radiation dose would be acquired when 20 % ASIR level in thoracic CT is applied.

Reduction in radiation dose with reconstruction technique in the brain perfusion CT

The principal objective of this study was to verify the utility of the reconstruction imaging technique in the brain perfusion computed tomography (PCT) scan by assessing reductions in the radiation dose and analyzing the generated images. The setting used for image acquisition had a detector coverage of 40 mm, a helical thickness of 0.625 mm, a helical shuttle mode scan type and a rotation time of 0.5 s as the image parameters used for the brain PCT scan. Additionally, a phantom experiment and an animal experiment were carried out. In the phantom and animal experiments, noise was measured in the scanning with the tube voltage fixed at 80 kVp (kilovolt peak) and the level of the adaptive statistical iterative reconstruction (ASIR) was changed from 0% to 100% at 10% intervals. The standard deviation of the CT coefficient was measured three times to calculate the mean value. In the phantom and animal experiments, the absorbed dose was measured 10 times under the same conditions as the ones for noise measurement before the mean value was calculated. In the animal experiment, pencil-type and CT-dedicated ionization chambers were inserted into the central portion of pig heads for measurement. In the phantom study, as the level of the ASIR changed from 0% to 100% under identical scanning conditions, the noise value and dose were proportionally reduced. In our animal experiment, the noise value was lowest when the ASIR level was 50%, unlike in the phantom study. The dose was reduced as in the phantom study.