Effect of iterative reconstruction techniques on image quality in low radiation dose chest CT: a phantom study

Age-specific DRLs for pediatric brain CT: A review for exploring the practices in Saudi Arabia

This review explores the establishment of diagnostic reference levels (DRLs) for pediatric brain computed tomography (CT) examinations in Saudi Arabia and compares them with nine other countries. An extensive search strategy was employed across various databases, resulting in the inclusion of 9 studies. The studies included patient-based and phantom-based investigations into DRLs, highlighting variations across age groups and countries. Findings suggest notable differences in CT dose index (CTDI mGy) and dose length product (DLP mGy.cm) values. There was a difference in the classification of age group between Saudi food and drug administration (SFDA) and literature. For the age groups 0-5 years and 6-15 years, the DRLs for the SFDA were as follows: CTDI (28 and 42 mGy) and DLP (482 and 697 mGy cm). The discussion emphasizes the importance of age-specific DRLs to optimize radiation doses while ensuring patient safety and diagnostic efficacy. Recommendations include adopting globally accepted standards for dose optimization and continued research into factors influencing DRL variations. Limitations include varying age groupings among studies and limited access to some relevant literature. Overall, this study underscores the importance of standardizing DRLs for pediatric CT to improve patient care and safety.

Hybrid iterative reconstruction in ultra-low-dose CT for accurate pulmonary nodule assessment: A Phantom study

This study evaluated hybrid iterative reconstruction in ultra-low-dose computed tomography (ULDCT) for solid pulmonary nodule detection. A 256-slice CT machine operating at 120 kVp imaged a chest phantom with 5 mm nodules. The imaging process involved adjusting low-dose computed tomography (LDCT) settings and conducting 3 ULDCT scans (A-C) with varied minimum and maximum mA settings (10/40 mA). Images were processed using iDose4 iterative reconstruction at levels 5 to 7. Measurements were taken for noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), noise power spectrum (NPS), and detectability index (D') to assess image quality, noise texture, and detectability. Analysis of variance (ANOVA) was used to compare the protocols. Noise levels varied significantly across iDose4 iterative reconstruction levels, with the highest noise at 178 HU in iDose4 L5 (protocol C) and the lowest at 54.85 HU in level 7 (protocol A). ULDCT scans showed noise increases of 38.5%, 104.2%, and 118.7% for protocols A, B, and C, respectively, compared to LDCT. Protocol A (iDose4 level 7) significantly improved SNR and CNR (P < .001). The mean volume CT dose index was 2.4 mGy for LDCT and 2.0 mGy, 1.2 mGy, and 0.7 mGy for ULDCT protocols A, B, and C, respectively. Increasing iDose4 levels reduced noise magnitude in the NPS and improved the D'. ULDCT with iDose4 level 7 provides diagnostically acceptable image quality for solid pulmonary nodule assessment at significantly reduced radiation doses. This approach, supported by advanced metrics like NPS and D', demonstrates a potential pathway for safer, effective lung cancer screening in high-risk populations. Further clinical studies are needed to validate these findings in diverse patient populations.

Impact of reconstruction techniques on low dose chest CT image quality: comparison of FBP, Clear View at Mzuzu Central Hospital, Malawi

Objective

To investigate the impact of two reconstruction techniques, Filtered Back Projection (FBP) and Clear View (CV) iterative algorithm, on the image quality of low-dose thin-slice chest CT.

Methods

A retrospective study of 42 patients undergoing low-dose chest CT at Mzuzu Central Hospital from Feb-Apr 2024 used automatic tube current modulation at 120 kV Raw data were reconstructed with FBP, 20% CV, 40% CV, 60% CV, and 80% CV, with 1 mm slice thickness and 0.625 mm spacing. Image noise, Signal-to-Noise Ratio (SNR), and Contrast-to-Noise Ratio (CNR) were measured, and image quality was rated on a 5-point scale for lung and mediastinal windows. Qualitative and quantitative parameters of the two different reconstruction algorithms in the five groups were comparatively analyzed.

Results

(1) Objective evaluation showed noise decreased in lung parenchyma, aorta, and erector spinae muscle with increasing CV weight. Mean noise reductions in lung parenchyma were 23.34% and 27.69% in 60% CV and 80% CV (P < 0.05). Aorta noise decreased by 23.43%, 37.16%, and 46.18% in 40% CV, 60% CV, and 80% CV (P < 0.05, P < 0.001, P < 0.001). Erector spinae muscle noise decreased by 35.91% and 44.78% in 60% CV and 80% CV (P < 0.05, P < 0.001). SNR and CNR were higher in CV groups than FBP. Among them, the differences in SNR between the 60% CV and 80% CV groups and the FBP group were statistically significant (P < 0.05). (2) Subjective scores for all groups were > 3, meeting diagnostic standards, with 60% CV yielding the highest lung and mediastinal window image quality (P < 0.05).

Conclusion

Compared to FBP, CV iterative reconstruction reduces noise and improves chest CT image quality under low-dose conditions as the weight increases, with 60% CV showing optimal performance.

Reduced-dose deep learning iterative reconstruction for abdominal computed tomography with low tube voltage and tube current

BACKGROUND

The low tube-voltage technique (e.g., 80 kV) can efficiently reduce the radiation dose and increase the contrast enhancement of vascular and parenchymal structures in abdominal CT. However, a high tube current is always required in this setting and limits the dose reduction potential. This study investigated the feasibility of a deep learning iterative reconstruction algorithm (Deep IR) in reducing the radiation dose while improving the image quality for abdominal computed tomography (CT) with low tube voltage and current.

METHODS

Sixty patients (male/female, 36/24; Age, 57.72 ± 10.19 years) undergoing the abdominal portal venous phase CT were randomly divided into groups A (100 kV, automatic exposure control [AEC] with reference tube-current of 213 mAs) and B (80 kV, AEC with reference of 130 mAs). Images were reconstructed via hybrid iterative reconstruction (HIR) and Deep IR (levels 1-5). The mean CT and standard deviation (SD) values of four regions of interest (ROI), i.e. liver, spleen, main portal vein and erector spinae at the porta hepatis level in each image serial were measured, and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. The image quality was subjectively scored by two radiologists using a 5-point criterion.

RESULTS

A significant reduction in the radiation dose of 69.94% (5.09 ± 0.91 mSv vs. 1.53 ± 0.37 mSv) was detected in Group B compared with Group A. After application of the Deep IR, there was no significant change in the CT value, but the SD gradually increased. Group B had higher CT values than group A, and the portal vein CT values significantly differed between the groups (P < 0.003). The SNR and CNR in Group B with Deep IR at levels 1-5 were greater than those in Group A and significantly differed when HIR and Deep IR were applied at levels 1-3 of HIR and Deep IR (P < 0.003). The subjective scores (distortion, clarity of the portal vein, visibility of small structures and overall image quality) with Deep IR at levels 4-5 in Group B were significantly higher than those in group A with HIR (P < 0.003).

CONCLUSION

Deep IR algorithm can meet the clinical requirements and reduce the radiation dose by 69.94% in portal venous phase abdominal CT with a low tube voltage of 80 kV and a low tube current. Deep IR at levels 4-5 can significantly improve the image quality of the abdominal parenchymal organs and the clarity of the portal vein.

A multi-institutional assessment of low-dose protocols in chest computed tomography: Dose and image quality

Background

Low-dose CT (LDCT) chest protocols have widespread clinical applications for many indications; as a result, there is a need for protocol assessment prior to standardization. Dalhousie University and Oslo Metropolitan University have a formally established cooperative relationship.

Purpose

The purpose is to assess radiation dose and image quality for LDCT chest protocols in seven different hospital locations in Norway and Canada.

Material and methods

Retrospective dosimetry data, volumetric CT dose index (CTDIvol), and dose length product (DLP) from 240 average-sized patients as well as CT protocol parameters were included in the survey. Effective dose (ED) and size-specific dose estimate (SSDE) were calculated for each examination. For a quantitative image quality analysis, noise, CT number, and signal-to-noise ratio (SNR) were determined for three regions in the chest. The contrast-to-noise ratio (CNR) was calculated for lung parenchyma in comparison to the subcutaneous fat. Differences in dose and image quality were evaluated by a single-factor ANOVA test. A two-sample t-test was performed to determine differences in means between individual scanners.

Results

The ANOVA test revealed significant differences (p < .05) in dose values for all scanners, including identical scanner models. Statistically significant differences (p < .05) were determined in mean values of the SNR distributions between the scanners in all three measured regions in the chest, as well as the CNR values.

Conclusion

The observed variations in dose and image quality measurements, even within the same hospitals and between identical scanner models, indicate a potential for protocol optimization in the involved hospitals in both countries.

Evaluating the effects of variation in CT scanning parameters on the image quality and Hounsfield units for optimization of dose in radiotherapy treatment planning: A semi-anthropomorphic thorax phantom study

AIM

The diagnosis accuracy of computed tomography (CT) systems and the reliability of calculated Hounsfield Units (HUs) are critical in tumor detection and cancer patients' treatment planning. This study evaluated the effects of scan parameters (Kilovoltage peak or kVp, milli-Ampere-second or mAS reconstruction kernels and algorithms, reconstruction field of view, and slice thickness) on image quality, HUs, and the calculated dose in the treatment planning system (TPS).

MATERIALS AND METHODS

A quality dose verification phantom was scanned several times by a 16-slice Siemens CT scanner. The DOSIsoft ISO gray TPS was applied for dose calculations. The SPSS.24 software was used to analyze the results and the P-value <0.05 was considered significant.

RESULTS

Reconstruction kernels and algorithms significantly affected noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). The noise increased and CNR decreased by raising the sharpness of reconstruction kernels. SNR and CNR had considerable increments at iterative reconstruction compared with the filtered back-projection algorithm. The noise decreased by raising mAS in soft tissues. Also, KVp had a significant effect on HUs. TPS--calculated dose variations were less than 2% for mediastinum and backbone and less than 8% for rib.

CONCLUSIONS

Although HU variation depends on image acquisition parameters across a clinically feasible range, its dosimetric impact on the calculated dose in TPS can be neglected. Hence, it can be concluded that the optimized values of scan parameters can be applied to obtain the maximum diagnostic accuracy and calculate HUs more precisely without affecting the calculated dose in the treatment planning of cancer patients.

Computed Tomography Imaging under Artificial Intelligence Reconstruction Algorithm Used in Recovery of Sports Injury of the Knee Anterior Cruciate Ligament

This study aimed to analyze the influence of artificial intelligence (AI) reconstruction algorithm on computed tomography (CT) images and the application of CT image analysis in the recovery of knee anterior cruciate ligament (ACL) sports injuries. A total of 90 patients with knee trauma were selected for enhanced CT scanning and randomly divided into three groups. Group A used the filtered back projection (FBP) reconstruction algorithm, and the tube voltage was set to 120 kV during CT scanning. Group B used the iDose4 reconstruction algorithm, and the tube voltage was set to 120 kV during CT scanning. In group C, the iDose4 reconstruction algorithm was used, and the tube voltage was set to 100 kV during CT scanning. The noise, signal-to-noise ratio (SNR), carrier-to-noise ratio (CNR), CT dose index volume (CTDI), dose length product (DLP), and effective radiation dose (ED) of the three groups of CT images were compared. The results showed that the noise of groups B and C was smaller than that of group A (P < 0.05), and the SNR and CNR of groups B and C were higher than those of group A. The images of patients in group A with the FBP reconstruction algorithm were noisy, and the boundaries were not clear. The noise of the images obtained by the iDose4 reconstruction algorithm in groups B and C was improved, and the image resolution was also higher. The agreement between arthroscopy and CT scan results was 96%. Therefore, the iterative reconstruction algorithm of iDose4 can improve the image quality. It was of important value in the diagnosis of knee ACL sports injury.

Effects of tube potential selection together with computed tomography automatic tube current modulation on CT imaging performance

The effects of tube potential selection with a computed tomography (CT) automatic tube current modulation (ATCM) system on radiation dose and image quality have been investigated on a Canon CT scanner. The use of different values of tube voltage for imaging, and the appropriate settings of the ATCM system, were evaluated. The custom-made phantom consisted of three sections of different sizes with inserts of various materials. It was scanned using tube potentials of 80-140 kV and different image quality ATCM settings. CTDI_voland image quality in terms of noise, contrast, and contrast-to-noise ratio (CNR) for air, polyethylene (PE), acrylic, polyoxymethylene (POM) and polyvinylchloride (PVC) were analysed. A figure of merit (FOM) was estimated by combining CNR and CTDI_vol. CTDI_volvalues were similar for all values of tube voltage and individual image quality ATCM settings when tube current was not restricted by the maximum value. The contrasts were independent of ATCM image quality setting, but CNR increased at the higher image quality level as image noise decreased. Both contrast and CNR decreased with increasing tube voltage for PVC and PE, but increased for POM and acrylic. PVC was the only insert material for which there was a significant improvement in contrast at lower tube potentials. FOM indicated that standard (SD = 10) and low dose (SD = 12.5) ATCM settings might be appropriate. The optimum tube voltage settings for imaging the PVC was 80-100 kV, but not for the lower contrast POM and acrylic, for which the standard tube voltage setting of 120 kV was better. The tube potential should be carefully set to gain radiological protection optimisation and keep the radiation dose as low as possible. Results indicate that 100 kV is likely to be appropriate for imaging small and medium-sized Thai patients when iodine contrast is used.

The reliability of low-dose chest CT for the initial imaging of COVID-19: comparison of structured findings, categorical diagnoses and dose levels

PURPOSE

The widespread use of computed tomography (CT) in COVID-19 may cause adverse biological effects. Many recommend to minimize radiation dose while maintaining diagnostic quality. This study was designed to evaluate the difference between findings of COVID-19 pneumonia on standard and low-dose protocols to provide data on the utility of the latter during initial imaging of COVID-19.

METHODS

Patients suspected of having COVID-19 were scanned with a 128-slices scanner using two consecutive protocols in the same session (standard-dose scan: 120 kV and 300 mA; low-dose scan: 80 kV and 40 mA). Dose data acquisition and analysis was performed using an automated software. High and low-dose examinations were anonymized, shuffled and read by two radiologist with consensus according to a highly structured reporting format that was primarily based on the consensus statement of the RSNA. Accordingly, 8 typical, 2 indeterminate, and 7 atypical findings were investigated. Cases were then assigned to one of the categories: (i) Cov19Typ, typical COVID-19; (ii) Cov19Ind, indeterminate COVID-19; (iii) Cov19Aty, atypical COVID-19; (iv) Cov19Neg, not COVID-19. McNemar test was used to analyze the number of disagreements between standard and low-dose scans regarding paired proportions of structured findings. Inter- test reliability was tested using kappa coefficient.

RESULTS

The study included 740 patients with a mean age of 44.05±16.59 years. The median (minimum-maximum) dose level for standard protocol was 189.98 mGy•cm (98.20-493.54 mGy•cm) and for low-dose protocol was 15.59 mGy•cm (11.59-32.37 mGy•cm) differing by -80 and -254 mGy•cm from pan-European diagnostic reference levels. Only two findings for typical, one finding for indeterminate, and three findings for atypical categories were statistically similar (p > 0.05). The difference in other categories resulted in significantly different final diagnosis for COVID-19 (p < 0.001). Overall, 626 patients received matching diagnoses with the two protocols. According to intertest reliability analysis, kappa value was found to be 0.669 (p < 0.001) to indicate substantial match. CT with standard-dose had a sensitivity of 94% and a specificity of 72%, while CT with low-dose had a sensitivity of 90% and a specificity of 81%.

CONCLUSION

Low kV and mA scans, as used in this study according to scanner manufacturer's global recommendations, may significantly lower exposure levels. However, these scans are significantly inferior in the detection of several individual CT findings of COVID-19 pneumonia, particularly the ones with GGO. Therefore, they should not be used as the protocol of choice in the initial imaging of COVID-19 patients during which higher sensitivity is required.

Forward-projected Model-based Iterative Reconstruction SoluTion in Temporal Bone Computed Tomography: A Comparison Study of All Reconstruction Modes

OBJECTIVE

Identify appropriate reconstruction modes of Forward-projected model-based Iterative Reconstruction SoluTion (FIRST) in temporal bone computed tomography (CT) and investigate the contribution of spatial resolution and noise to the visual assessment.

METHODS

Sixteen temporal bone CT images were reconstructed. Two blinded radiologists assessed 8 anatomical structures and classified the visual assessment. These visual scores were compared across reconstruction modes among each anatomical structure. Visual scores and contrast-to-noise ratio, noise power spectrum (NPS) at low (NPSLow) and high (NPSHigh) spatial frequencies, and 50% modulation transfer function relationships were evaluated.

RESULTS

Visual scores differed significantly for the stapedius muscle and osseous spiral lamina, with CARDIAC SHARP, BONE, and LUNG modes for the osseous spiral lamina scoring highest. Visual scores significantly positively correlated with NPSLow, NPSHigh, and 50% modulation transfer function but negatively with contrast-to-noise ratio.

CONCLUSIONS

Modes providing higher spatial resolution and lower noise reduction showed an improved visual assessment of CT images reconstructed with FIRST.

Deep learning trained algorithm maintains the quality of half-dose contrast-enhanced liver computed tomography images: Comparison with hybrid iterative reconstruction: Study for the application of deep learning noise reduction technology in low dose

PURPOSE

This study compares the image and diagnostic qualities of a DEep Learning Trained Algorithm (DELTA) for half-dose contrast-enhanced liver computed tomography (CT) with those of a commercial hybrid iterative reconstruction (HIR) method used for standard-dose CT (SDCT).

METHODS

This study enrolled 207 adults, and they were divided into two groups: SDCT and low-dose CT (LDCT). SDCT was reconstructed using the HIR method (SDCT_HIR), and LDCT was reconstructed using both the HIR method (LDCT_HIR) and DELTA (LDCT_DL). Noise, Hounsfield unit (HU) values, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were compared between three image series. Two radiologists assessed the noise, artefacts, overall image quality, visualisation of critical anatomical structures and lesion detection, characterisation and visualisation.

RESULTS

The mean effective doses were 5.64 ± 1.96 mSv for SDCT and 2.87 ± 0.87 mSv for LDCT. The noise of LDCT_DL was significantly lower than that of SDCT_HIR and LDCT_HIR. The SNR and CNR of LDCT_DL were significantly higher than those of the other two groups. The overall image quality, visualisation of anatomical structures and lesion visualisation between LDCT_DL and SDCT_HIR were not significantly different. For lesion detection, the sensitivities and specificities of SDCT_HIR vs. LDCT_DL were 81.9 % vs. 83.7 % and 89.1 % vs. 86.3 %, respectively, on a per-patient basis. SDCT_HIR showed 75.4 % sensitivity and 82.6 % specificity for lesion characterisation on a per-patient basis, whereas LDCT_DL showed 73.5 % sensitivity and 82.4 % specificity.

CONCLUSIONS

LDCT with DELTA had approximately 49 % dose reduction compared with SDCT with HIR while maintaining image quality on contrast-enhanced liver CT.

Low-dose chest CT and the impact on nodule visibility

INTRODUCTION

The need to continually optimise CT protocols is essential to ensure the lowest possible radiation dose for the clinical task and individual patient. The aim of this study was to explore the effect of reducing effective mAs on nodule detection and radiation dose across six scanners.

METHODS

An anthropomorphic chest phantom was scanned using a low-dose chest CT protocol, with the effective mAs lowered to the lowest permissible level. All other acquisition parameters remained consistent. Images were evaluated by five radiologists to determine their sensitivity in detecting six simulated nodules within the phantom. Image noise was calculated together with DLP.

RESULTS

The lowest possible mAs achievable ranged from 7 to 19 mAs. The two highest mAs setting (17 mAs + 19 mAs) had kV modulation enabled (100 kV instead of 120 kV) which consequently resulted in a higher nodule detection rate. Overall nodule detection averaged at 91% (range 80-97%). Out of a possible 180 nodules, 16 were missed, with 12 of those 16 being the same nodule. Noise was double for the Somatom Sensation scanner when compared to the others; however, this scanner did not have iterative reconstruction and it was installed over 10 years ago. There was a strong correlation between image noise and scanner age.

CONCLUSION

This study highlighted that nodules can be detected at very low effective mAs (<20 mAs) but only when other acquisition parameters are optimised i.e. iterative reconstruction and kV modulation. Nodule detection rates were affected by nodule location and image noise.

IMPLICATIONS FOR PRACTICE

This study consolidates previous findings on how to successfully optimise low-dose chest CT. It also highlights the difficulty with standardisation owing to factors such as scanner age and different vendor attributes.