Adaptive iterative dose reduction algorithm in CT: effect on image quality compared with filtered back projection in body phantoms of different sizes

Validation of deep learning-based CT image reconstruction for treatment planning

Deep learning-based CT image reconstruction (DLR) is a state-of-the-art method for obtaining CT images. This study aimed to evaluate the usefulness of DLR in radiotherapy. Data were acquired using a large-bore CT system and an electron density phantom for radiotherapy. We compared the CT values, image noise, and CT value-to-electron density conversion table of DLR and hybrid iterative reconstruction (H-IR) for various doses. Further, we evaluated three DLR reconstruction strength patterns (Mild, Standard, and Strong). The variations of CT values of DLR and H-IR were large at low doses, and the difference in average CT values was insignificant with less than 10 HU at doses of 100 mAs and above. DLR showed less change in CT values and smaller image noise relative to H-IR. The noise-reduction effect was particularly large in the low-dose region. The difference in image noise between DLR Mild and Standard/Strong was large, suggesting the usefulness of reconstruction intensities higher than Mild. DLR showed stable CT values and low image noise for various materials, even at low doses; particularly for Standard or Strong, the reduction in image noise was significant. These findings indicate the usefulness of DLR in treatment planning using large-bore CT systems.

Assessment of Image Quality of Coronary CT Angiography Using Deep Learning-Based CT Reconstruction: Phantom and Patient Studies

BACKGROUND

In coronary computed tomography angiography (CCTA), the main issue of image quality is noise in obese patients, blooming artifacts due to calcium and stents, high-risk coronary plaques, and radiation exposure to patients.

OBJECTIVE

To compare the CCTA image quality of deep learning-based reconstruction (DLR) with that of filtered back projection (FBP) and iterative reconstruction (IR).

METHODS

This was a phantom study of 90 patients who underwent CCTA. CCTA images were acquired using FBP, IR, and DLR. In the phantom study, the aortic root and the left main coronary artery in the chest phantom were simulated using a needleless syringe. The patients were classified into three groups according to their body mass index. Noise, the signal-to-noise ratio (SNR), and the contrast-to-noise ratio (CNR) were measured for image quantification. A subjective analysis was also performed for FBP, IR, and DLR.

RESULTS

According to the phantom study, DLR reduced noise by 59.8% compared to FBP and increased SNR and CNR by 121.4% and 123.6%, respectively. In a patient study, DLR reduced noise compared to FBP and IR. Furthermore, DLR increased the SNR and CNR more than FBP and IR. In terms of subjective scores, DLR was higher than FBP and IR.

CONCLUSION

In both phantom and patient studies, DLR effectively reduced image noise and improved SNR and CNR. Therefore, the DLR may be useful for CCTA examinations.

Quality of Thorax CT Scan Images among Covid-19 Cases using Variations of Filter

A typical image of the Thorax CT Scan as a sign of the early stages and development of Covid-19 is the finding of Ground Glass Opacities (GGO). GGO is an insignificant increase in the density of the lungs without occlusion of blood vessels and bronchi. In mild cases, GGO tends to be difficult to identify and requires high-resolution CT scanning. In this study, we intend to improve the resolution of the Thorax CT Scan image through filter settings, to analyze the difference in the variations of filters B50s, B70s, and B90s towards the quality of the CT Scan image and obtain the optimal use of filter in the Thorax CT Scan examination among Covid-19 cases. This was a quantitative analytical study conducted at one of the Regional General Hospital in Jakarta on March-April 2022. The samples were secondary data derived from 10 patients by using MSCT Siemens Somatom Perspective 128 slices. Data were collected through observation and experiment. The images collected were further analyzed using Image j software to find values of Signal to Noise Ratio (SNR) and Contrast to Noise Ratio (CNR). Furthermore, the values were compared by assessing the anatomical image information through various filters. The results of this study indicated that there were differences in the SNR and CNR values of the three filters. The higher resolution of the filter used, the more capable it was to sharper and more detailed the image but the noise level was also higher. Thorax CT Scan examination should be carried out using the B70s very sharp filter that was able to produce images with the optimal information and fairly low noise level. A very thin GGO image in the early stage of the manifestation of Covid-19 could be identified in the Thorax CT Scan examinations for diagnosis of Covid-19 case.

Impact of ROI Size on the Accuracy of Noise Measurement in CT on Computational and ACR Phantoms

BACKGROUND

The effect of region of interest (ROI) size variation on producing accurate noise levels is not yet studied.

OBJECTIVE

This study aimed to evaluate the influence of ROI sizes on the accuracy of noise measurement in computed tomography (CT) by using images of a computational and American College of Radiology (ACR) phantoms.

MATERIAL AND METHODS

In this experimental study, two phantoms were used, including computational and ACR phantoms. A computational phantom was developed by using Matlab R215a software (Mathworks Inc., Natick, MA Natick, MA) with a homogeneously +100 Hounsfield Unit (HU) value and an added-Gaussian noise with various levels of 5, 10, 25, 50, 75, and 100 HU. The ACR phantom was scanned with a Philips MX-16 slice CT scanner in different slice thicknesses of 1.5, 3, 5, and 7 mm to obtain noise variation. Noise measurement was conducted at the center of the phantom images and four locations close to the edge of the phantom images using different ROI sizes from 3 × 3 to 41 × 41 pixels, with an increased size of 2 × 2 pixels.

RESULTS

The use of a minimum ROI size of 21 × 21 pixels shows noise in the range of ± 5% ground truth noise. The measured noise increases above the ± 5% range if the used ROI is smaller than 21 × 21 pixels.

CONCLUSION

A minimum acceptable ROI size is required to maintain the accuracy of noise measurement with a size of 21 × 21 pixels.

Evaluation and comparison of performance of low-dose 128-slice CT scanner with different mAs values: A phantom study

OBJECTIVE:

Radiation dose in computed tomography (CT) has been the concern of physicists ever since the introduction of CT scan. The objective of this study was to evaluate the performance of low-dose 128-slice CT scanner with different mAs values.

MATERIALS AND METHODS:

Quantitative study was carried out at different values of mAs. Philips brilliance CT phantom with Philips ingenuity 128-slice low-dose CT scanner was chosen for this study. CT number linearity, CT number accuracy, slice thickness accuracy, high-contrast resolution, and low-contrast resolution were calculated and estimated computed tomography dose index volume (CTDI_vol) for all the mAs values were recorded. Noise was calculated for all mAs values for comparison.

RESULTS:

Data analysis shows that image quality was acceptable for all protocols. High-contrast resolution for all protocols was 20 line pairs per centimeter. Low-contrast resolution for 50 mAs images was 4 mm and 3 mm for other mAs protocols. Images acquired using 100 mAs revealed ring artifacts. CTDI_vol using 50 mAs was 33% of the CTDI_vol using 150 mAs. The dose–length product at 100 mAs was reduced to 66% of the dose–length product at 150 mAs, and the same at 50 mAs was reduced to 33%.

CONCLUSION:

It is evident here that mAs has direct impact on the radiation dose to patient. With iDose4, mAs can be reduced to 50 mAs in multislice low-dose CT scan to reduce the radiation dose with minimal effect on image quality for slice thickness 4 mm. However, noise would dominate at tube current lower than 50 mAs for 120 kVp.

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.

Comparisons of Hounsfield Unit Linearity between Images Reconstructed using an Adaptive Iterative Dose Reduction (AIDR) and a Filter Back-Projection (FBP) Techniques

Background:

The HU linearity is an essential parameter in a quantitative imaging and the treatment planning systems of radiotherapy.

Objective:

This study aims to evaluate the linearity of Hounsfield unit (HU) in applying the adaptive iterative dose reduction (AIDR) on CT scanner and its comparison to the filtered back-projection (FBP).

Material and Methods:

In this experimental phantom study, a TOS-phantom was scanned using a Toshiba Alexion 6 CT scanner. The images were reconstructed using the FBP and AIDR. Measurements of HU and noise values were performed on images of the “HU linearity” module of the TOS-phantom. The module had five embedded objects, i.e., air, polypropylene, nylon, acrylic, and Delrin. On each object, a circle area of 4.32 cm² was drawn and used to measure HU and noise values. The R² of the relation between mass densities vs. HU values was used to measure HU linearities at four different tube voltages. The Mann-Whitney U test was used to compare unpaired data and p-value < 0.05 was considered statistically significant.

Results:

The AIDR method produced a significant smaller image noise than the FBP method (p-value < 0.05). There were no significant differences in HU values of images reconstructed using FBP and AIDR methods (p-value > 0.05). The HU values acquired by the methods showed the same linearity marked by coinciding linear lines with the same R² value (> 0.999).

Conclusion:

AIDR methods produce the HU linearity as FBP methods with a smaller image noise level.

Thorax CT Dose Reduction Based on Patient Features: Effect of Patient Characteristics on Image Quality and Effective Dose

Computed tomography (CT) radiation dose reduction is vital without compromising image quality. The aim was to determine the effects of patient characteristics on the received radiation dose and image quality in chest CT examinations and to be able to predict dose and image quality prior to scanning. Consecutive 230 patients underwent routine chest CT examinations were included. CT examination and patients input parameters were recorded for each patient. The effect of patients' demographics/anthropometrics on received dose and image quality was investigated by linear regression analysis. All parameters were evaluated using an artificial neural network (ANN). Of all parameters, patient demographics/anthropometrics were found to be 98% effective in calculating dose reduction. Using ANN on 60 new patients was more than 90% accurate for output parameters and 91% for image quality. Patient characteristics have a significant impact on radiation dose and image quality. Dose and image quality can be determined before CT. This will allow setting the most appropriate scanning parameters before the CT scan.

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

OBJECTIVE

The 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 METHODS

A 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.

RESULTS

In 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.

CONCLUSION

Renal 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.

CT automated exposure control using a generalized detectability index

PURPOSE

Identifying an appropriate tube current setting can be challenging when using iterative reconstruction due to the varying relationship between spatial resolution, contrast, noise, and dose across different algorithms. This study developed and investigated the application of a generalized detectability index ( d gen ' ) to determine the noise parameter to input to existing automated exposure control (AEC) systems to provide consistent image quality (IQ) across different reconstruction approaches.

METHODS

This study proposes a task-based automated exposure control (AEC) method using a generalized detectability index ( d gen ' ). The proposed method leverages existing AEC methods that are based on a prescribed noise level. The generalized d gen ' metric is calculated using lookup tables of task-based modulation transfer function (MTF) and noise power spectrum (NPS). To generate the lookup tables, the American College of Radiology CT accreditation phantom was scanned on a multidetector CT scanner (Revolution CT, GE Healthcare) at 120 kV and tube current varied manually from 20 to 240 mAs. Images were reconstructed using a reference reconstruction algorithm and four levels of an in-house iterative reconstruction algorithm with different regularization strengths (IR1-IR4). The task-based MTF and NPS were estimated from the measured images to create lookup tables of scaling factors that convert between d gen ' and noise standard deviation. The performance of the proposed d gen ' -AEC method in providing a desired IQ level over a range of iterative reconstruction algorithms was evaluated using the American College of Radiology (ACR) phantom with elliptical shell and using a human reader evaluation on anthropomorphic phantom images.

RESULTS

The study of the ACR phantom with elliptical shell demonstrated reasonable agreement between the d gen ' predicted by the lookup table and d ' measured in the images, with a mean absolute error of 15% across all dose levels and maximum error of 45% at the lowest dose level with the elliptical shell. For the anthropomorphic phantom study, the mean reader scores for images resulting from the d gen ' -AEC method were 3.3 (reference image), 3.5 (IR1), 3.6 (IR2), 3.5 (IR3), and 2.2 (IR4). When using the d gen ' -AEC method, the observers' IQ scores for the reference reconstruction were statistical equivalent to the scores for IR1, IR2, and IR3 iterative reconstructions (P > 0.35). The d gen ' -AEC method achieved this equivalent IQ at lower dose for the IR scans compared to the reference scans.

CONCLUSIONS

A novel AEC method, based on a generalized detectability index, was investigated. The proposed method can be used with some existing AEC systems to derive the tube current profile for iterative reconstruction algorithms. The results provide preliminary evidence that the proposed d gen ' -AEC can produce similar IQ across different iterative reconstruction approaches at different dose levels.

Low-Tube-Voltage CT Urography Using Low-Concentration-Iodine Contrast Media and Iterative Reconstruction: A Multi-Institutional Randomized Controlled Trial for Comparison with Conventional CT Urography

Objective

To compare the image quality of low-tube-voltage and low-iodine-concentration-contrast-medium (LVLC) computed tomography urography (CTU) with iterative reconstruction (IR) with that of conventional CTU.

Materials and Methods

This prospective, multi-institutional, randomized controlled trial was performed at 16 hospitals using CT scanners from various vendors. Patients were randomly assigned to the following groups: 1) the LVLC-CTU (80 kVp and 240 mgI/mL) with IR group and 2) the conventional CTU (120 kVp and 350 mgI/mL) with filtered-back projection group. The overall diagnostic acceptability, sharpness, and noise were assessed. Additionally, the mean attenuation, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and figure of merit (FOM) in the urinary tract were evaluated.

Results

The study included 299 patients (LVLC-CTU group: 150 patients; conventional CTU group: 149 patients). The LVLC-CTU group had a significantly lower effective radiation dose (5.73 ± 4.04 vs. 8.43 ± 4.38 mSv) compared to the conventional CTU group. LVLC-CTU showed at least standard diagnostic acceptability (score ≥ 3), but it was non-inferior when compared to conventional CTU. The mean attenuation value, mean SNR, CNR, and FOM in all pre-defined segments of the urinary tract were significantly higher in the LVLC-CTU group than in the conventional CTU group.

Conclusion

The diagnostic acceptability and quantitative image quality of LVLC-CTU with IR are not inferior to those of conventional CTU. Additionally, LVLC-CTU with IR is beneficial because both radiation exposure and total iodine load are reduced.

Forward-Projected Model-Based Iterative Reconstruction in Screening Low-Dose Chest CT: Comparison With Adaptive Iterative Dose Reduction 3D

OBJECTIVE

The objective of this study is to compare forward-projected model-based iterative reconstruction solution (FIRST), a newer fully iterative CT reconstruction method, with adaptive iterative dose reduction 3D (AIDR 3D) in low-dose screening CT for lung cancer. Differences in image noise, image quality, and pulmonary nodule detection, size, and characterization were specifically evaluated.

MATERIALS AND METHODS

Low-dose chest CT images obtained for 50 consecutive patients between December 2015 and January 2016 were retrospectively reviewed. Images were reconstructed using FIRST and AIDR 3D for both lung and soft-tissue reconstruction. Images were independently reviewed to assess image noise, subjective image quality (with use of a 5-point Likert scale, with 1 denoting far superior image quality; 2, superior quality; 3, equivalent quality; 4, inferior quality; and 5, far inferior quality), pulmonary nodule count, size of the largest pulmonary nodule, and characterization of the largest pulmonary nodule (i.e., solid, part solid, or ground glass).

RESULTS

Across all 50 cases, measured image noise was lower with FIRST than with AIDR 3D (lung window, 44% reduction, 41 ± 7 vs 74 ± 8 HU, respectively; soft-tissue window, 32% reduction, 11 ± 2 vs 16 ± 2 HU, respectively). Readers subjectively rated images obtained with FIRST as comparable to images obtained with AIDR 3D (mean [± SD] Likert score for FIRST vs AIDR 3D, 3.2 ± 0.3 for soft-tissue reconstructions and 3.0 ± 0.3 for lung reconstructions). For each reader, very good agreement regarding nodule count was noted between FIRST and AIDR 3D (interclass correlation coefficient [ICC], 0.83 for reader 1 and 0.78 for reader 2). Excellent agreement regarding nodule size (ICC, 0.99 for reader 1 and 0.99 for reader 2) and characterization of the largest nodule (kappa value, 0.92 for reader 1 and 0.82 for reader 2) also existed.

CONCLUSION

Images reconstructed with FIRST are superior to those reconstructed AIDR 3D with regard to image noise and are equivalent with regard to subjective image quality, pulmonary nodule count, and nodule characterization.

LOW-DOSE CT PROTOCOL OPTIMIZATION FOR THE ASSESSMENT OF ACUTE APPENDICITIS: THE OPTICAP PHANTOM STUDY

The aim was to evaluate effects of voltage, noise input (NI) and iterative reconstruction (IR) on radiation dose and image quality in order to establish a contrast enhanced low-dose protocol for assessment of acute appendicitis. An anthropomorphic abdominal phantom mimicking contrast enhanced abdomen was scanned with 80, 100 and 120 kV, standard and strong IR and 11 NIs (66 protocols). A total of 14 test tubes of increasing iodine dilutions and one tube with an appendicolith were evaluated within the phantom. The dose, HUs, noise, contrast-to-noise ratio (CNR) and figure of merit (FOM) were determined. Visual quality scores were assessed by two readers. A clinically used voltage-IR combination (120 kV, standard IR) was used as a reference. Overall, 100 kV with standard IR (p = 0.002) and 80 kV with both IRs (p < 0.001) showed higher CNR than the reference, but noise was most pronounced at 80 kV (p < 0.001). The highest FOM was found in the 100 kV protocols (p < 0.001). The reference and 100 kV with standard IR had highest image quality scores, where the 100 kV protocol enabled a distinct dose reduction. Lowering the voltage seems to be a more favorable tool than IR changes in optimizing the dose in contrast enhanced abdominal CT.

TRIAL REGISTRATION

ClinicalTrials.gov number, NCT01022567.

Image quality of virtual monochromatic images obtained using 320-detector row CT: A phantom study evaluating the effects of iterative reconstruction and body size

OBJECTIVES

To compare the image quality between virtual monochromatic spectral (VMS) images obtained using 320-row detector CT and polychromatic 120-kVp images reconstructed with or without iterative reconstruction using various phantom sizes.

MATERIALS AND METHODS

Torso phantoms simulating three patient sizes and containing four syringes filled with water or different contrast media (5, 10, 15mgI/mL15mgI/ml) were used. The phantoms were scanned using dual-energy (80/135-kVp) and single-energy (120-kVp) protocols at different settings (20mGy, 12mGy, and 6mGy). VMS images were generated at 1-keV intervals (range, 35-135keV). Both the VMS images and the single-energy 120-kVp images were reconstructed using filtered back projection (FBP) and adaptive iterative dose reduction 3D (AIDR-3D). The signal-to-noise ratio (SNR), and the contrast-to-noise ratio (CNR) were assessed.

RESULTS

Using FBP reconstruction, the SNR and CNR of the VMS images were lower than or similar to those of the 120-kVp images for most dose settings. Using AIDR-3D reconstruction, however, the 70-keV VMS images had higher SNRs and CNRs than the 120-kVp images at most settings.

CONCLUSIONS

The image quality of VMS images with FBP reconstruction tended to be lower than that of the 120-kVp images. With the use of AIDR-3D, however, approximately 70-keV VMS images had a higher image quality than the 120-kVp images.

Adaptive Statistical Iterative Reconstruction-V: Impact on Image Quality in Ultralow-Dose Coronary Computed Tomography Angiography

OBJECTIVE

The clinical utility of a latest generation iterative reconstruction algorithm (adaptive statistical iterative reconstruction [ASiR-V]) has yet to be elucidated for coronary computed tomography angiography (CCTA). This study evaluates the impact of ASiR-V on signal, noise and image quality in CCTA.

METHODS

Sixty-five patients underwent clinically indicated CCTA on a 256-slice CT scanner using an ultralow-dose protocol. Data sets from each patient were reconstructed at 6 different levels of ASiR-V. Signal intensity was measured by placing a region of interest in the aortic root, LMA, and RCA. Similarly, noise was measured in the aortic root. Image quality was visually assessed by 2 readers.

RESULTS

Median radiation dose was 0.49 mSv. Image noise decreased with increasing levels of ASiR-V resulting in a significant increase in signal-to-noise ratio in the RCA and LMA (P < 0.001). Correspondingly, image quality significantly increased with higher levels of ASiR-V (P < 0.001).

CONCLUSIONS

ASiR-V yields substantial noise reduction and improved image quality enabling introduction of ultralow-dose CCTA.

Low-Tube Voltage Computed Tomography During Hepatic Arterial Phase: The Effect of Body Habitus on Image Quality

PURPOSE

This study aimed to evaluate the impact of body habitus factors on image quality of low-tube voltage computed tomography (CT) during the hepatic arterial phase.

MATERIALS AND METHODS

Ninety-seven patients (66 men, 31 women; age range, 26-78 years) who underwent clinically indicated liver dynamic CT examination were enrolled in the study. Analysis with 80-kVp CT and intermediate tube current (277-337 mA) was performed in the late hepatic arterial phase using a 320-detector row scanner with adaptive iterative dose reduction 3-dimensional reconstruction. Patient body habitus was measured using body weight (BW), body mass index (BMI), lateral width (LW) of the abdomen, and muscle volume (MV) of the abdominal wall. On hepatic arterial phase, the mean image noise and contrast-to-noise ratio (CNR) for the aorta and liver were assessed. The correlations between body habitus factors and image quality parameters were evaluated.

RESULTS

In all patients, MV showed the strongest correlation with image noise, followed by BW and LW (r = 0.684, 0.570, and 0.555, respectively). The BMI showed the fourth strongest correlation with image noise among all body habitus factors (r = 0.377). With respect to CNR of the aorta, MV and BW showed the strongest inverse correlation (r = -0.590 and -0.600, respectively), followed by LW and BMI (r = -0.557 and -0.423, respectively). Regarding the CNR of the liver, MV showed the strongest inverse correlation (r = -0.279), although the correlation efficiency was weak compared with other correlations.

CONCLUSIONS

Among various body habitus factors, MV showed the strongest association with image noise and CNR in the hepatic arterial phase using 80-kVp CT.

A comparison of adaptive iterative dose reduction 3D and filtered back projection in craniocervical CT angiography

AIM

To compare the effects of exposure parameters on image quality and radiation dose for craniocervical computed tomography angiography (CTA) using adaptive iterative dose reduction in three dimensions (AIDR 3D) and filtered back projection (FBP) algorithms.

MATERIALS AND METHODS

One hundred and eighty patients were divided into three groups; group A (120 kV, 300 mA, FBP), group B (100 kV, automatic mA, AIDR 3D) and group C (80kV, automatic mA, AIDR 3D). Image quality and radiation dose were evaluated for each group.

RESULTS

For both cervical and intracranial vessels, CT attenuation, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were higher in the AIDR 3D groups. The difference in mean vascular noise was also statistically significant (p<0.001), with group B having the lowest value at 16.5±3.2 HU and group C having the highest at 19.1±2.9 HU. FBP reconstruction resulted in lower image-quality scores for the common carotid artery. Parenchymal image-quality scores also varied significantly different between groups with group C partially failing to meet the minimum standards for diagnostic use. For the middle cerebral artery, image-quality scores were significantly better in group A, although images from groups B and C also satisfied clinical diagnostic requirements. The image quality of the internal carotid artery was the best in group B. Image-quality scores between groups were not significantly different for the carotid sinus. Radiation doses in the groups using AIDR 3D were >70% lower than in the FBP group.

CONCLUSION

AIDR 3D (100 kV, automatic modulation) provides optimal image quality of vascular and parenchymal tissues at significantly lower radiation doses (mSV) than FBP in craniocervical CTA. For cases in which highly accurate parenchymal assessment is not required, the tube voltage can be lowered to 80 kV to further decrease radiation dose.

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

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

Image Quality and Radiation Dose of CT Coronary Angiography with Automatic Tube Current Modulation and Strong Adaptive Iterative Dose Reduction Three-Dimensional (AIDR3D)

Purpose

To investigate image quality and radiation dose of CT coronary angiography (CTCA) scanned using automatic tube current modulation (ATCM) and reconstructed by strong adaptive iterative dose reduction three-dimensional (AIDR3D).

Methods

Eighty-four consecutive CTCA patients were collected for the study. All patients were scanned using ATCM and reconstructed with strong AIDR3D, standard AIDR3D and filtered back-projection (FBP) respectively. Two radiologists who were blinded to the patients' clinical data and reconstruction methods evaluated image quality. Quantitative image quality evaluation included image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). To evaluate image quality qualitatively, coronary artery is classified into 15 segments based on the modified guidelines of the American Heart Association. Qualitative image quality was evaluated using a 4-point scale. Radiation dose was calculated based on dose-length product.

Results

Compared with standard AIDR3D, strong AIDR3D had lower image noise, higher SNR and CNR, their differences were all statistically significant (P<0.05); compared with FBP, strong AIDR3D decreased image noise by 46.1%, increased SNR by 84.7%, and improved CNR by 82.2%, their differences were all statistically significant (P<0.05 or 0.001). Segments with diagnostic image quality for strong AIDR3D were 336 (100.0%), 486 (96.4%), and 394 (93.8%) in proximal, middle, and distal part respectively; whereas those for standard AIDR3D were 332 (98.8%), 472 (93.7%), 378 (90.0%), respectively; those for FBP were 217 (64.6%), 173 (34.3%), 114 (27.1%), respectively; total segments with diagnostic image quality in strong AIDR3D (1216, 96.5%) were higher than those of standard AIDR3D (1182, 93.8%) and FBP (504, 40.0%); the differences between strong AIDR3D and standard AIDR3D, strong AIDR3D and FBP were all statistically significant (P<0.05 or 0.001). The mean effective radiation dose was (2.55±1.21) mSv.

Conclusion

Compared with standard AIDR3D and FBP, CTCA with ATCM and strong AIDR3D could significantly improve both quantitative and qualitative image quality.

Correlation of clinical and physical-technical image quality in chest CT: a human cadaver study applied on iterative reconstruction

Background

The first aim of this study was to evaluate the correlation between clinical and physical-technical image quality applied to different strengths of iterative reconstruction in chest CT images using Thiel cadaver acquisitions and Catphan images. The second aim was to determine the potential dose reduction of iterative reconstruction compared to conventional filtered back projection based on different clinical and physical-technical image quality parameters.

Methods

Clinical image quality was assessed using three Thiel embalmed human cadavers. A Catphan phantom was used to assess physical-technical image quality parameters such as noise, contrast-detail and contrast-to-noise ratio (CNR).

Both Catphan and chest Thiel CT images were acquired on a multislice CT scanner at 120 kVp and 0.9 pitch. Six different refmAs settings were applied (12, 30, 60, 90, 120 and 150refmAs) and each scan was reconstructed using filtered back projection (FBP) and iterative reconstruction (SAFIRE) algorithms (1,3 and 5 strengths) using a sharp kernel, resulting in 24 image series. Four radiologists assessed the clinical image quality, using a visual grading analysis (VGA) technique based on the European Quality Criteria for Chest CT.

Results

Correlation coefficients between clinical and physical-technical image quality varied from 0.88 to 0.92, depending on the selected physical-technical parameter. Depending on the strength of SAFIRE, the potential dose reduction based on noise, CNR and the inverse image quality figure (IQF_inv) varied from 14.0 to 67.8 %, 16.0 to 71.5 % and 22.7 to 50.6 % respectively. Potential dose reduction based on clinical image quality varied from 27 to 37.4 %, depending on the strength of SAFIRE.

Conclusion

Our results demonstrate that noise assessments in a uniform phantom overestimate the potential dose reduction for the SAFIRE IR algorithm. Since the IQF_inv based dose reduction is quite consistent with the clinical based dose reduction, an optimised contrast-detail phantom could improve the use of contrast-detail analysis for image quality assessment in chest CT imaging. In conclusion, one should be cautious to evaluate the performance of CT equipment taking into account only physical-technical parameters as noise and CNR, as this might give an incomplete representation of the actual clinical image quality performance.

Initial phantom study comparing image quality in computed tomography using adaptive statistical iterative reconstruction and new adaptive statistical iterative reconstruction v

PURPOSE

The purpose of this study was to assess the image quality of a novel advanced iterative reconstruction (IR) method called as "adaptive statistical IR V" (ASIR-V) by comparing the image noise, contrast-to-noise ratio (CNR), and spatial resolution from those of filtered back projection (FBP) and adaptive statistical IR (ASIR) on computed tomography (CT) phantom image.

MATERIALS AND METHODS

We performed CT scans at 5 different tube currents (50, 70, 100, 150, and 200 mA) using 3 types of CT phantoms. Scanned images were subsequently reconstructed in 7 different scan settings, such as FBP, and 3 levels of ASIR and ASIR-V (30%, 50%, and 70%). The image noise was measured in the first study using body phantom. The CNR was measured in the second study using contrast phantom and the spatial resolutions were measured in the third study using a high-resolution phantom. We compared the image noise, CNR, and spatial resolution among the 7 reconstructed image scan settings to determine whether noise reduction, high CNR, and high spatial resolution could be achieved at ASIR-V.

RESULTS

At quantitative analysis of the first and second studies, it showed that the images reconstructed using ASIR-V had reduced image noise and improved CNR compared with those of FBP and ASIR (P < 0.001). At qualitative analysis of the third study, it also showed that the images reconstructed using ASIR-V had significantly improved spatial resolution than those of FBP and ASIR (P < 0.001).

CONCLUSIONS

Our phantom studies showed that ASIR-V provides a significant reduction in image noise and a significant improvement in CNR as well as spatial resolution. Therefore, this technique has the potential to reduce the radiation dose further without compromising image quality.

Accuracy of lung nodule volumetry in low-dose CT with iterative reconstruction: an anthropomorphic thoracic phantom study

OBJECTIVE

The purpose of this study was to assess accuracy of lung nodule volumetry in low-dose CT with application of iterative reconstruction (IR) according to nodule size, nodule density and CT tube currents, using artificial lung nodules within an anthropomorphic thoracic phantom.

METHODS

Eight artificial nodules (four diameters: 5, 8, 10 and 12 mm; two CT densities: -630 HU that represents ground-glass nodule and +100 HU that represents solid nodule) were randomly placed inside a thoracic phantom. Scans were performed with tube current-time product to 10, 20, 30 and 50 mAs. Images were reconstructed with IR and filtered back projection (FBP). We compared volume estimates to a reference standard and calculated the absolute percentage error (APE).

RESULTS

The APE of all nodules was significantly lower when IR was used than with FBP (7.5 ± 4.7% compared with 9.0 ±6.9%; p < 0.001). The effect of IR was more pronounced for smaller nodules (p < 0.001). IR showed a significantly lower APE than FBP in ground-glass nodules (p < 0.0001), and the difference was more pronounced at the lowest tube current (11.8 ± 5.9% compared with 21.3 ± 6.1%; p < 0.0001). The effect of IR was most pronounced for ground-glass nodules in the lowest CT tube current.

CONCLUSION

Lung nodule volumetry in low-dose CT by application of IR showed reliable accuracy in a phantom study. Lung nodule volumetry can be reliably applicable to all lung nodules including small, ground-glass nodules even in ultra-low-dose CT with application of IR.

ADVANCES IN KNOWLEDGE

IR significantly improved the accuracy of lung nodule volumetry compared with FBP particularly for ground-glass (-630 HU) nodules. Volumetry in low-dose CT can be utilized in patient with lung nodule work-up, and IR has benefit for small, ground-glass lung nodules in low-dose CT.