Assessment of image quality in abdominal CT: potential dose reduction with model-based iterative reconstruction

Image quality assessments in abdominal CT: Relative importance of dose, iterative reconstruction strength and slice thickness

INTRODUCTION

Low contrast resolution in abdominal computed tomography (CT) may be negatively affected by attempts to lower patient doses. Iterative reconstruction (IR) algorithms play a key role in mitigating this problem. The reconstructed slice thickness also influences image quality. The aim was to assess the interaction and influence of patient dose, slice thickness, and IR strength on image quality in abdominal CT.

METHOD

With a simultaneous acquisition, images at 42 and 98 mAs were obtained in 25 patients. Multiplanar images with slice thicknesses of 1, 2, and 3 mm and advanced modeled iterative reconstruction (ADMIRE) strengths of 3 (AD3) and 5 (AD5) were reconstructed. Four radiologists evaluated the images in a pairwise manner based on five image criteria. Ordinal logistic regression with mixed effects was used to evaluate the effect of tube load, ADMIRE strength, and slice thickness using the visual grading regression technique.

RESULTS

For all assessed image criteria, the regression analysis showed significantly (p < 0.001) higher image quality for AD5, but lower for tube load 42 mAs, and slice thicknesses of 1 mm and 2 mm, compared to the reference categories of AD3, 98 mAs, and 3 mm, respectively. AD5 at 2 mm was superior to AD3 at 3 mm for all image criteria studied. AD5 1 mm produced inferior image quality for liver parenchyma and overall image quality compared to AD3 3 mm. Interobserver agreement (ICC) ranged from 0.874 to 0.920.

CONCLUSION

ADMIRE 5 at 2 mm slice thickness may allow for further dose reductions due to its superiority when compared to ADMIRE 3 at 3 mm slice thickness.

IMPLICATIONS FOR PRACTICE

Combination of thinner slices and higher ADMIRE strength facilitates imaging at low dose.

An inventory of patient-image based risk/dose, image quality and body habitus/size metrics for adult abdomino-pelvic CT protocol optimisation

PURPOSE

Patient-specific protocol optimisation in abdomino-pelvic Computed Tomography (CT) requires measurement of body habitus/size (BH), sensitivity-specificity (surrogates image quality (IQ) metrics) and risk (surrogates often dose quantities) (RD). This work provides an updated inventory of metrics available for each of these three categories of optimisation variables derivable directly from patient measurements or images. We consider objective IQ metrics mostly in the spatial domain (i.e., those related directly to sharpness, contrast, noise quantity/texture and perceived detectability as these are used by radiologists to assess the acceptability or otherwise of patient images in practice).

MATERIALS AND METHODS

The search engine used was PubMed with the search period being 2010-2024. The key words used were: 'comput* tomography', 'CT', 'abdom*', 'dose', 'risk', 'SSDE', 'image quality', 'water equivalent diameter', 'size', 'body composition', 'habit*', 'BMI', 'obes*', 'overweight'. Since BH is critical for patient specific optimisation, articles correlating RD vs BH, and IQ vs BH were reviewed.

RESULTS

The inventory includes 11 BH, 12 IQ and 6 RD metrics. 25 RD vs BH correlation studies and 9 IQ vs BH correlation studies were identified. 7 articles in the latter group correlated metrics from all three categories concurrently.

CONCLUSIONS

Protocol optimisation should be fine-tuned to the level of the individual patient and particular clinical query. This would require a judicious choice of metrics from each of the three categories. It is suggested that, for increased utility in clinical practice, more future optimisation studies be clinical task based and involve the three categories of metrics concurrently.

Image Quality and Diagnostic Performance of Low-Dose Liver CT with Deep Learning Reconstruction versus Standard-Dose CT

Purpose To compare the image quality and diagnostic capability in detecting malignant liver tumors of low-dose CT (LDCT, 33% dose) with deep learning-based denoising (DLD) and standard-dose CT (SDCT, 100% dose) with model-based iterative reconstruction (MBIR). Materials and Methods In this prospective, multicenter, noninferiority study, individuals referred for liver CT scans were enrolled from three tertiary referral hospitals between February 2021 and August 2022. All liver CT scans were conducted using a dual-source scanner with the dose split into tubes A (67% dose) and B (33% dose). Blended images from tubes A and B were created using MBIR to produce SDCT images, whereas LDCT images used data from tube B and were reconstructed with DLD. The noise in liver images was measured and compared between imaging techniques. The diagnostic performance of each technique in detecting malignant liver tumors was evaluated by three independent radiologists using jackknife alternative free-response receiver operating characteristic analysis. Noninferiority of LDCT compared with SDCT was declared when the lower limit of the 95% CI for the difference in figure of merit (FOM) was greater than -0.10. Results A total of 296 participants (196 men, 100 women; mean age, 60.5 years ± 13.3 [SD]) were included. The mean noise level in the liver was significantly lower for LDCT (10.1) compared with SDCT (10.7) (P < .001). Diagnostic performance was assessed in 246 participants (108 malignant tumors in 90 participants). The reader-averaged FOM was 0.880 for SDCT and 0.875 for LDCT (P = .35). The difference fell within the noninferiority margin (difference, -0.005 [95% CI: -0.024, 0.012]). Conclusion Compared with SDCT with MBIR, LDCT using 33% of the standard radiation dose had reduced image noise and comparable diagnostic performance in detecting malignant liver tumors. Keywords: CT, Abdomen/GI, Liver, Comparative Studies, Diagnosis, Reconstruction Algorithms Clinical trial registration no. NCT05804799 © RSNA, 2024 Supplemental material is available for this article.

A prospective study comparing the quality of coronary computed tomography angiography images from photon counting and energy integrating detector systems

BACKGROUND

As guidelines endorse the use of computed tomography (CT) for examining coronary artery disease (CAD), it is important to compare the advantages and disadvantages of the novel photon counting detector CT (PCD-CT) technology with the established energy integrating detector CT (EID-CT).

PURPOSE

To compare the image quality of coronary computed tomography angiography (CCTA) and the Agatston scores (AS) derived from EID-CT and PCD-CT.

MATERIAL AND METHODS

In this prospective observational study, 28 patients underwent clinical calcium score and CCTA scans on an EID-CT and a PCD-CT scanner. CCTA images were qualitatively analyzed by five observers using visual grading characteristics. The correlation and agreement of the AS were assessed using Spearman's rank correlation and Bland-Altman plots.

RESULTS

This qualitative analyses demonstrated a high fraction of "good" or "excellent" ratings for the image criteria in both CT systems. The sharpness of the distal lumen and image quality regarding motion artifacts were rated significantly higher for EID-CT (P < 0.05). However, the sharpness of coronary calcification was rated significantly higher for PCD-CT (P < 0.05). Spearman's rank correlation and Bland-Altman plots showed good correlation (P = 0.95) and agreement regarding the AS between EID-CT and PCD-CT.

CONCLUSION

Both CT systems exhibited high CCTA image quality. The sharpness of calcifications was rated significantly higher for PCD-CT. A good correlation was observed between the AS derived from the two systems.

How Real Are Computed Tomography Low Dose Simulations? An Investigational In-Vivo Large Animal Study

OBJECTIVES

CT low-dose simulation methods have gained significant traction in protocol development, as they lack the risk of increased patient exposure. However, in-vivo validations of low-dose simulations are as uncommon as prospective low-dose image acquisition itself. Therefore, we investigated the extent to which simulated low-dose CT datasets resemble their real-dose counterparts.

MATERIALS AND METHODS

Fourteen veterinarian-sedated alive pigs underwent three CT scans on the same third generation dual-source scanner with 2 months between each scan. At each time, three additional scans ensued, with mAs reduced to 50%, 25%, and 10%. All scans were reconstructed using wFBP and ADMIRE levels 1-5. Matching low-dose datasets were generated from the 100% scans using reconstruction-based and DICOM-based simulations. Objective image quality (CT numbers stability, noise, and signal-to-noise ratio) was measured via consistent regions of interest. Three radiologists independently rated all possible dataset combinations per time point for subjective image quality (-1=inferior, 0=equal, 1=superior). The points were averaged for a semiquantitative score, and inter-rater-agreement was measured using Spearman's correlation coefficient. A structural similarity index (SSIM) analyzed the voxel-wise similarity of the volumes. Adequately corrected mixed-effects analysis compared objective and subjective image quality. Multiple linear regression with three-way interactions measured the contribution of dose, reconstruction mode, simulation method, and rater to subjective image quality.

RESULTS

There were no significant differences between objective and subjective image quality of reconstruction-based and DICOM-based simulation on all dose levels (p≥0.137). However, both simulation methods produced significantly lower objective image quality than real-dose images below 25% mAs due to noise overestimation (p<0.001; SSIM≤89±3). Overall, inter-rater-agreement was strong (r≥0.68, mean 0.93±0.05, 95% CI 0.92-0.94; each p<0.001). In regression analysis, significant decreases in subjective image quality were observed for lower radiation doses (b ≤ -0.387, 95%CI -0.399 to -0.358; p<0.001) but not for reconstruction modes, simulation methods, raters, or three-way interactions (p≥0.103).

CONCLUSION

Simulated low-dose CT datasets are subjectively and objectively indistinguishable from their real-dose counterparts down to 25% mAs, making them an invaluable tool for efficient low-dose protocol development.

Learning effects in visual grading assessment of model-based reconstruction algorithms in abdominal Computed Tomography

Objectives

Images reconstructed with higher strengths of iterative reconstruction algorithms may impair radiologists' subjective perception and diagnostic performance due to changes in the amplitude of different spatial frequencies of noise. The aim of the present study was to ascertain if radiologists can learn to adapt to the unusual appearance of images produced by higher strengths of Advanced modeled iterative reconstruction algorithm (ADMIRE).

Methods

Two previously published studies evaluated the performance of ADMIRE in non-contrast and contrast-enhanced abdominal CT. Images from 25 (first material) and 50 (second material) patients, were reconstructed with ADMIRE strengths 3, 5 (AD3, AD5) and filtered back projection (FBP). Radiologists assessed the images using image criteria from the European guidelines for quality criteria in CT. To ascertain if there was a learning effect, new analyses of data from the two studies was performed by introducing a time variable in the mixed-effects ordinal logistic regression model.

Results

In both materials, a significant negative attitude to ADMIRE 5 at the beginning of the viewing was strengthened during the progress of the reviews for both liver parenchyma (first material: -0.70, p < 0.01, second material: -0.96, p < 0.001) and overall image quality (first material:-0.59, p < 0.05, second material::-1.26, p < 0.001). For ADMIRE 3, an early positive attitude for the algorithm was noted, with no significant change over time for all criteria except one (overall image quality), where a significant negative trend over time (-1.08, p < 0.001) was seen in the second material.

Conclusions

With progression of reviews in both materials, an increasing dislike for ADMIRE 5 images was apparent for two image criteria. In this time perspective (weeks or months), no learning effect towards accepting the algorithm could be demonstrated.

Ultra-low-dose hepatic multiphase CT using deep learning-based image reconstruction algorithm focused on arterial phase in chronic liver disease: A non-inferiority study

PURPOSE

This study determined whether image quality and detectability of ultralow-dose hepatic multiphase CT (ULDCT, 33.3% dose) using a vendor-agnostic deep learning model(DLM) are noninferior to those of standard-dose CT (SDCT, 100% dose) using model-based iterative reconstruction(MBIR) in patients with chronic liver disease focusing on arterial phase.

METHODS

Sixty-seven patients underwent hepatic multiphase CT using a dual-source scanner to obtain two different radiation dose CT scans (100%, SDCT and 33.3%, ULDCT). ULDCT using DLM and SDCT using MBIR were compared. A margin of -0.5 for the difference between the two protocols was pre-defined as noninferiority of the overall image quality of the arterial phase image. Quantitative image analysis (signal to noise ratio[SNR] and contrast to noise ratio[CNR]) was also conducted. The detectability of hepatic arterial focal lesions was compared using the Jackknife free-response receiver operating characteristic analysis. Non-inferiority was satisfied if the margin of the lower limit of 95%CI of the difference in figure-of-merit was less than -0.1.

RESULTS

Mean overall arterial phase image quality scores with ULDCT using DLM and SDCT using MBIR were 4.35 ± 0.57 and 4.08 ± 0.58, showing noninferiority (difference: -0.269; 95 %CI, -0.374 to -0.164). ULDCT using DLM showed a significantly superior contrast-to-noise ratio of arterial enhancing lesion (p < 0.05). Figure-of-merit for detectability of arterial hepatic focal lesion was 0.986 for ULDCT using DLM and 0.963 for SDCT using MBIR, showing noninferiority (difference: -0.023, 95 %CI: -0.016 to 0.063).

CONCLUSION

ULDCT using DLM with 66.7% dose reduction showed non-inferior overall image quality and detectability of arterial focal hepatic lesion compared to SDCT using MBIR.

"Image quality evaluation of the Precise image CT deep learning reconstruction algorithm compared to Filtered Back-projection and iDose4: a phantom study at different dose levels"

PURPOSE

To characterize the performance of the Precise Image (PI) deep learning reconstruction (DLR) algorithm for abdominal Computed Tomography (CT) imaging.

METHODS

CT images of the Catphan-600 phantom (equipped with an external annulus) were acquired using an abdominal protocol at four dose levels and reconstructed using FBP, iDose⁴ (levels 2,5) and PI ('Soft Tissue' definition, levels 'Sharper','Sharp','Standard','Smooth','Smoother'). Image noise, image non-uniformity, noise power spectrum (NPS), target transfer function (TTF), detectability index (d'), CT numbers accuracy and image histograms were analyzed.

RESULTS

The behavior of the PI algorithm depended strongly on the selected level of reconstruction. The phantom analysis suggested that the PI image noise decreased linearly by varying the level of reconstruction from Sharper to Smoother, expressing a noise reduction up to 80% with respect to FBP. Additionally, the non-uniformity decreased, the histograms became narrower, and d' values increased as PI reconstruction levels changed from Sharper to Smoother. PI had no significant impact on the average CT number of different contrast objects. The conventional FBP NPS was deeply altered only by Smooth and Smoother levels of reconstruction. Furthermore, spatial resolution was found to be dose- and contrast-dependent, but in each analyzed condition it was greater than or comparable to FBP and iDose⁴ TTFs.

CONCLUSIONS

The PI algorithm can reduce image noise with respect to FBP and iDose⁴; spatial resolution, CT numbers and image uniformity are generally preserved by the algorithm but changes in NPS for the Smooth and Smoother levels need to be considered in protocols implementation.

Prospective evaluation of low-dose multiphase hepatic computed tomography for detecting and characterizing hepatocellular carcinoma in patients with chronic liver disease

BACKGROUND

Knowing the lowest acceptable radiation dose of multiphase hepatic CT may allow us to reduce the radiation dose for detecting HCC.

PURPOSE

To prospectively assess the image quality and diagnostic performance of low-dose and ultra-low-dose multiphase hepatic computed tomography using a dual-source CT scanner.

METHODS

Three reconstructed different dose scan images (standard-dose, low-dose, and ultra-low-dose) of hepatic multiphase CT were obtained from 67 patients with a dual-source CT scanner. The image quality and the diagnostic performance of the three radiation dose CT scans of the hepatic focal lesion (≥ 0.5 cm) were analyzed by two independent readers using the Liver Imaging Reporting and Data System.

RESULTS

Qualitative image quality and signal-to-noise ratio were significantly different among the radiation doses (p < 0.001). In total, 154 lesions comprising 32 hepatocellular carcinomas (HCC) and 122 non-HCC were included. The sensitivities of SDCT, LDCT, and ULDCT were 90.6%(29/32), 81.3%(26/32), and 56.2%(18/32), respectively. The accuracies of SDCT, LDCT, and ULDCT were 98.1%(151/154), 96.1%(148/154), and 89.6%(138/154), respectively. On per-lesion analysis, SDCT and LDCT did not show significantly different sensitivity and accuracy in diagnosing HCC (p = 0.250 and 0.250).

CONCLUSIONS

The diagnostic performance of dynamic hepatic LDCT with 33% reduced radiation dose in comparison to SDCT would be acceptable even though its image quality was qualitatively and quantitatively inferior. However, few HCCs could be overlooked. Therefore, with caution, radiation dose reduction by one-third could be implemented for follow-up CT scans for patients suspected of having HCC with caution and further studies are needed in the future.

Comparison of Radiation Dose and Image Quality between the 2nd Generation and 3rd Generation Dual-Source Single-Energy and Dual-Source Dual-Energy CT of the Abdomen

Purpose

We compared the radiation dose and image quality between the 2nd generation and the 3rd generation dual-source single-energy (DSSE) and dual-source dual-energy (DSDE) CT of the abdomen.

Materials and Methods

We included patients undergoing follow-up abdominal CT after partial or radical nephrectomy in the first 10 months of 2019 (2nd generation DS CT) and the first 10 months of 2020 (3rd generation DS CT). We divided the 320 patients into 4 groups (A, 2nd generation DSSE CT; B, 2nd generation DSDE CT; C, 3rd generation DSSE CT; and D, 3rd generation DSDE CT) (n = 80 each) matched by sex and body mass index. Radiation dose and image quality (objective and subjective qualities) were compared between the groups.

Results

The mean size-specific dose estimation of 3rd generation DSDE CT group was significantly lower than that of the 2nd generation DSSE CT (42.5%, p = 0.013) and 2nd generation DSDE CT (46.9%, p = 0.015) groups. Interobserver agreement was excellent for the overall image quality (intraclass correlation coefficient [ICC]: 0.8867) and image artifacts (ICC: 0.9423).

Conclusion

Our results showed a considerable reduction in the radiation dose while maintaining high image quality with 3rd generation DSDE CT as compared to the 2nd generation DSDE CT and 2nd generation DSSE CT.

Application of Different Levels of Advanced Modeling Iterative Reconstruction in Brain CT Scanning

BACKGROUND

Advanced Modeling Iterative Reconstruction (ADMIRE) algorithm has five intensity levels; it is important to study which algorithm is better for brain CT scanning.

OBJECTIVE

The aim of the study is to compare the influence of different strength levels of ADMIRE and traditional Filtered Back Projection (FBP) on image quality in brain CT scanning.

METHODS

60 patients were retrospectively selected, and the data from each of these patients' brains were reconstructed by four different reconstruction methods (FBP, ADMIRE1, ADMIRE3, and ADMIRE5). A five-point Likert Scale was implemented to evaluate the subjective image quality. Image noise, CT value of brain tissue , signal-to-noise ratio (SNR) of gray white matter, contrast-to-noise ratio (CNR), and beam hardening artifact index (AI) of the posterior fossa, were measured for evaluating the objective image quality. Finally, the differences between the subjective and objective evaluations were compared.

RESULTS

There were no statistical differences observed in CT values of gray matter and white matter between the four groups (all P >0.05). The image noise gradually decreased with the increase of ADMIRE algorithm level. The AI exhibited no statistical difference between the four groups (F =0.793, P =0.499), but it tended to decrease slightly with the increase of ADMIRE algorithm level. Compared to other groups (all p <0.001), the ADMIRE5 group demonstrated the best objective image quality. Nevertheless, the highest subjective score was observed in the ADMIRE3 group, which exhibited significant differences with other images (all P <0.001).

CONCLUSION

ADMIRE algorithm can clearly improve image quality, but it cannot significantly improve the linear sclerosis artifacts in the posterior cranial fossa. Based on the subjective evaluation of image quality, ADMIRE3 algorithm is recommended in brain CT scanning.

Comparison of multiphase data from CT perfusion vs clinical 4-phase CT scans with respect to image quality, lesion detection, and LI-RADS classification in HCC patients

Purpose

The aim of this study was to assess the image quality and diagnostic performance of reconstructed arterial (A) and portal venous (PV) phases in computed tomography perfusion (CTP) scans compared to the corresponding phases in standard 4-phase CT and to assess the utility for LI-RADS classification using CTP and 4-phase 4CT.

Methods

A total of 26 scans with each method (CTP and 4-phase CT) from 19 hepatocellular carcinoma patients were analyzed and compared. Arterial and PV phases reconstructed by advanced modeled iterative reconstruction at strength 4 (ADMIRE 4) from raw CTP data were compared with image sets from arterial and PV phases of 4-phase CT (ADMIRE 3) in the same patient with respect to image quality.

Results

Quantitative image analysis showed that reconstructed CTP datasets were equivalent to 4-phase CT image sets. Qualitative image analysis revealed similar lesion detection rates with the 2 methods for patients with an abdominal diameter ≤36 cm and body weight <90 kg, but lower detection rates with CTP for patients with an abdominal diameter >37 cm. There was no difference in Liver Imaging Reporting and Data System (LI-RADS) classifications between the 2 methods.

Conclusion

Reconstructed CTP images can potentially replace 4-phase CT images in patients weighing <90 kg and with a body diameter <37 cm, as the 2 methods are comparable in terms of quantitative image quality and ability to detect and classify lesions based on LI-RADS criteria.

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Reconstructed A- and PV-CTP images have comparable image quality to 4-phase CT.

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Reconstructed A- and PV-CTP images can be used for LI-RADS classification of HCC.

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A-/PV-CTP has the potential to reliably detect lesions in patients weighing <90 kg with body diameter ≤36 cm.

Iterative reconstruction improves image quality and reduces radiation dose in trauma protocols; A human cadaver study

Background

Radiation-related cancer risk is an object of concern in CT of trauma patients, as these represent a young population. Different radiation reducing methods, including iterative reconstruction (IR), and spilt bolus techniques have been introduced in the recent years in different large scale trauma centers.

Purpose

To compare image quality in human cadaver exposed to thoracoabdominal computed tomography using IR and standard filtered back-projection (FBP) at different dose levels.

Material and methods

Ten cadavers were scanned at full dose and a dose reduction in CTDIvol of 5 mGy (low dose 1) and 7.5 mGy (low dose 2) on a Siemens Definition Flash 128-slice computed tomography scanner. Low dose images were reconstructed with FBP and Sinogram affirmed iterative reconstruction (SAFIRE) level 2 and 4. Quantitative image quality was analyzed by comparison of contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR). Qualitative image quality was evaluated by use of visual grading regression (VGR) by four radiologists.

Results

Readers preferred SAFIRE reconstructed images over FBP at a dose reduction of 40% (low dose 1) and 56% (low dose 2), with significant difference in overall impression of image quality. CNR and SNR showed significant improvement for images reconstructed with SAFIRE 2 and 4 compared to FBP at both low dose levels.

Conclusions

Iterative image reconstruction, SAFIRE 2 and 4, resulted in equal or improved image quality at a dose reduction of up to 56% compared to full dose FBP and may be used a strong radiation reduction tool in the young trauma population.

Image quality in liver CT: low-dose deep learning vs standard-dose model-based iterative reconstructions

OBJECTIVES

To compare the overall image quality and detectability of significant (malignant and pre-malignant) liver lesions of low-dose liver CT (LDCT, 33.3% dose) using deep learning denoising (DLD) to standard-dose CT (SDCT, 100% dose) using model-based iterative reconstruction (MBIR).

METHODS

In this retrospective study, CT images of 80 patients with hepatic focal lesions were included. For noninferiority analysis of overall image quality, a margin of - 0.5 points (scored in a 5-point scale) for the difference between scan protocols was pre-defined. Other quantitative or qualitative image quality assessments were performed. Additionally, detectability of significant liver lesions was compared, with 64 pairs of CT, using the jackknife alternative free-response ROC analysis, with noninferior margin defined by the lower limit of 95% confidence interval (CI) of the difference of figure-of-merit less than - 0.1.

RESULTS

The mean overall image quality scores with LDCT and SDCT were 3.77 ± 0.38 and 3.94 ± 0.34, respectively, demonstrating a difference of - 0.17 (95% CI: - 0.21 to - 0.12), which did not cross the predefined noninferiority margin of - 0.5. Furthermore, LDCT showed significantly superior quantitative results of liver lesion contrast to noise ratio (p < 0.05). However, although LDCT scored higher than the average score in qualitative image quality assessments, they were significantly lower than those of SDCT (p < 0.05). Figure-of-merit for lesion detection was 0.859 for LDCT and 0.878 for SDCT, showing noninferiority (difference: - 0.019, 95% CI: - 0.058 to 0.021).

CONCLUSION

LDCT using DLD with 67% radiation dose reduction showed non-inferior overall image quality and lesion detectability, compared to SDCT.

KEY POINTS

• Low-dose liver CT using deep learning denoising (DLD), at 67% dose reduction, provided non-inferior overall image quality compared to standard-dose CT using model-based iterative reconstruction (MBIR). • Low-dose CT using DLD showed significantly less noise and higher CNR _{lesion to liver} than standard-dose CT using MBIR and demonstrated at least average image quality score among all readers, albeit with lower scores than standard-dose CT using MBIR. • Low-dose liver CT showed noninferior detectability for malignant and pre-malignant liver lesions, compared to standard-dose CT.

IMAGE QUALITY AND POTENTIAL DOSE REDUCTION USING ADVANCED MODELED ITERATIVE RECONSTRUCTION (ADMIRE) IN ABDOMINAL CT - A REVIEW

Traditional filtered back projection (FBP) reconstruction methods have served the computed tomography (CT) community well for over 40 years. With the increased use of CT during the last decades, efforts to minimise patient exposure, while maintaining sufficient or improved image quality, have led to the development of model-based iterative reconstruction (MBIR) algorithms from several vendors. The usefulness of the advanced modeled iterative reconstruction (ADMIRE) (Siemens Healthineers) MBIR in abdominal CT is reviewed and its noise suppression and/or dose reduction possibilities explored. Quantitative and qualitative methods with phantom and human subjects were used. Assessment of the quality of phantom images will not always correlate positively with those of patient images, particularly at the higher strength of the ADMIRE algorithm. With few exceptions, ADMIRE Strength 3 typically allows for substantial noise reduction compared to FBP and hence to significant (≈30%) patient dose reductions. The size of the dose reductions depends on the diagnostic task.

Model-based iterative reconstruction in paediatric head computed tomography: a pilot study on dose reduction in children

Purpose

To evaluate the potential of model-based iterative reconstruction (MBIR) on dose reduction and image quality in children undergoing computed tomography (CT) head examinations.

Material and methods

This prospective study was approved by the institutional ethics committee. A total of 88 children (age range of 5 to 16 years) with a history of seizures underwent contrast-enhanced CT scan. Forty-one children underwent CT study according to the MBIR technique, while 47 children underwent CT of the head with the non-MBIR protocol. Images were reviewed by 2 blinded paediatric radiologists in a random order. Mean dose-length product, CT dose index (CTDI) volume, and mean effective dose were recorded for both groups. Image quality, image noise, and diagnostic acceptability of 2 image sets were also recorded.

Results

In the MBIR group, the mean dose-length product was reduced by 79.8%; the mean CTDI volume was reduced by 88.5%, while the mean effective dose was reduced by 81% when compared to the non-MBIR group. No significant difference was seen in diagnostic acceptability, image noise, and image quality between the 2 groups.

Conclusions

MBIR technique is highly effective in reducing radiation dose in paediatric head CT examinations without any significant difference in image quality, image noise, and diagnostic acceptability.

Superior objective and subjective image quality of deep learning reconstruction for low-dose abdominal CT imaging in comparison with model-based iterative reconstruction and filtered back projection

Objective:

This study aimed to conduct objective and subjective comparisons of image quality among abdominal computed tomography (CT) reconstructions with deep learning reconstruction (DLR) algorithms, model-based iterative reconstruction (MBIR), and filtered back projection (FBP).

Methods:

Datasets from consecutive patients who underwent low-dose liver CT were retrospectively identified. Images were reconstructed using DLR, MBIR, and FBP. Mean image noise and contrast-to-noise ratio (CNR) were calculated, and noise, artifacts, sharpness, and overall image quality were subjectively assessed. Dunnett’s test was used for statistical comparisons.

Results:

Ninety patients (67 ± 12.7 years; 63 males; mean body mass index [BMI], 25.5 kg/m²) were included. The mean noise in the abdominal aorta and hepatic parenchyma of DLR was lower than that in FBP and MBIR (p < .001). For FBP and MBIR, image noise was significantly higher for obese patients than for those with normal BMI. The CNR for the abdominal aorta and hepatic parenchyma was higher for DLR than for FBP and MBIR (p < .001). MBIR images were subjectively rated as superior to FBP images in terms of noise, artifacts, sharpness, and overall quality (p < .001). DLR images were rated as superior to MBIR images in terms of noise (p < .001) and overall quality (p = .03).

Conclusions:

Based on objective and subjective comparisons, the image quality of DLR was found to be superior to that of MBIR and FBP on low-dose abdominal CT. DLR was the only method for which image noise was not higher for obese patients than for those with a normal BMI.

Advances in knowledge:

This study provides previously unavailable information on the properties of DLR systems and their clinical utility.

Comparison of image quality and lesion diagnosis in abdominopelvic unenhanced CT between reduced-dose CT using deep learning post-processing and standard-dose CT using iterative reconstruction: A prospective study

PURPOSE

To compare image quality and lesion diagnosis between reduced-dose abdominopelvic unenhanced computed tomography (CT) using deep learning (DL) post-processing and standard-dose CT using iterative reconstruction (IR).

METHOD

Totally 251 patients underwent two consecutive abdominopelvic unenhanced CT scans of the same range, including standard and reduced doses, respectively. In group A, standard-dose data were reconstructed by (blend 30 %) IR. In group B, reduced-dose data were reconstructed by filtered back projection reconstruction to obtain group B1 images, and post-processed using the DL algorithm (NeuAI denosing, Neusoft medical, Shenyang, China) with 50 % and 100 % weights to obtain group B2 and B3 images, respectively. Then, CT values of the liver, the second lumbar vertebral centrum, the erector spinae and abdominal subcutaneous fat were measured. CT values, noise levels, signal-to-noise ratios (SNRs), contrast-to-noise ratios (CNRs), radiation doses and subjective scores of image quality were compared. Subjective evaluations of low-density liver lesions were compared by diagnostic results from enhanced CT or Magnetic Resonance Imaging.

RESULTS

Groups B3 and B1 showed the lowest and highest noise levels, respectively (P < 0.001). The SNR and CNR in group B3 were highest (P < 0.001). The radiation dose in group B was reduced by 71.5 % on average compared to group A. Subjective scores in groups A and B2 were highest (P < 0.001). Diagnostic sensitivity and confidence for liver metastases in groups A and B2 were highest (P < 0.001).

CONCLUSIONS

Reduced-dose abdominopelvic unenhanced CT combined with DL post-processing could ensure image quality and satisfy diagnostic needs.

Deep learning image reconstruction for improvement of image quality of abdominal computed tomography: comparison with hybrid iterative reconstruction

PURPOSE

To evaluate the usefulness of the deep learning image reconstruction (DLIR) to enhance the image quality of abdominal CT, compared to iterative reconstruction technique.

METHOD

Pre and post-contrast abdominal CT images in 50 patients were reconstructed with 2 different algorithms: hybrid iterative reconstruction (hybrid IR: ASiR-V 50%) and DLIR (TrueFidelity). Standard deviation of attenuation in normal liver parenchyma was measured as the image noise on pre and post-contrast CT. The contrast-to-noise ratio (CNR) for the aorta, and the signal-to-noise ratio (SNR) of the liver were calculated on post-contrast CT. The overall image quality was graded on a 5-point scale ranging from 1 (poor) to 5 (excellent).

RESULTS

The image noise was significantly decreased by DLIR compared to hybrid-IR [hybrid IR, median 8.3 Hounsfield unit (HU) (interquartile range (IQR) 7.6-9.2 HU); DLIR, median 5.2 HU (IQR 4.6-5.8), P < 0.0001 for post-contrast CT]. The CNR and SNR were significantly improved by DLIR [CNR, median 4.5 (IQR 3.8-5.6) vs 7.3 (IQR 6.2-8.8), P < 0.0001; SNR, median 9.4 (IQR 8.3-10.1) vs 15.0 (IQR 13.2-16.4), P < 0.0001]. The overall image quality score was also higher for DLIR compared to hybrid-IR (hybrid IR 3.1 ± 0.6 vs DLIR 4.6 ± 0.5, P < 0.0001 for post-contrast CT).

CONCLUSIONS

Image noise, overall image quality, CNR and SNR for abdominal CT images are improved with DLIR compared to hybrid IR.

Simulated Radiation Dose Reduction in Whole-Body CT on a 3rd Generation Dual-Source Scanner: An Intraindividual Comparison

To evaluate the effect of radiation dose reduction on image quality and diagnostic confidence in contrast-enhanced whole-body computed tomography (WBCT) staging. We randomly selected March 2016 for retrospective inclusion of 18 consecutive patients (14 female, 60 ± 15 years) with clinically indicated WBCT staging on the same 3rd generation dual-source CT. Using low-dose simulations, we created data sets with 100, 80, 60, 40, and 20% of the original radiation dose. Each set was reconstructed using filtered back projection (FBP) and Advanced Modeled Iterative Reconstruction (ADMIRE^®, Siemens Healthineers, Forchheim, Germany) strength 1–5, resulting in 540 datasets total. ADMIRE 2 was the reference standard for intraindividual comparison. The effective radiation dose was calculated using commercially available software. For comparison of objective image quality, noise assessments of subcutaneous adipose tissue regions were performed automatically using the software. Three radiologists blinded to the study evaluated image quality and diagnostic confidence independently on an equidistant 5-point Likert scale (1 = poor to 5 = excellent). At 100%, the effective radiation dose in our population was 13.3 ± 9.1 mSv. At 20% radiation dose, it was possible to obtain comparably low noise levels when using ADMIRE 5 (p = 1.000, r = 0.29). We identified ADMIRE 3 at 40% radiation dose (5.3 ± 3.6 mSv) as the lowest achievable radiation dose with image quality and diagnostic confidence equal to our reference standard (p = 1.000, r > 0.4). The inter-rater agreement for this result was almost perfect (ICC ≥ 0.958, 95% CI 0.909–0.983). On a 3rd generation scanner, it is feasible to maintain good subjective image quality, diagnostic confidence, and image noise in single-energy WBCT staging at dose levels as low as 40% of the original dose (5.3 ± 3.6 mSv), when using ADMIRE 3.

Diagnostic Performance of Different Simulated Low-Dose Levels in Patients with Suspected Cervical Abscess Using a Third-Generation Dual-Source CT Scanner

The aim of this study was to investigate the effects of dose reduction on diagnostic accuracy and image quality of cervical computed tomography (CT) in patients with suspected cervical abscess. Forty-eight patients (mean age 45.5 years) received a CT for suspected cervical abscess. Low-dose CT (LDCT) datasets with 25%, 50%, and 75% of the original dose were generated with a realistic simulation. The image data were reconstructed with filtered back projection (FBP) and with advanced modeled iterative reconstruction (ADMIRE) (strengths 3 and 5). A five-point Likert scale was used to assess subjective image quality and diagnostic confidence. The signal-to-noise ratio (SNR) of the sternocleidomastoid muscle and submandibular gland and the contrast-to-noise ratio (CNR) of the sternocleidomastoid muscle and submandibular glandular fat were calculated to assess the objective image quality. Diagnostic accuracy was calculated for LDCT using the original dose as the reference standard. The prevalence of cervical abscesses was high (72.9%) in the cohort; the mean effective dose for all 48 scans was 1.8 ± 0.8 mSv. Sternocleidomastoid and submandibular SNR and sternocleidomastoid muscle fat and submandibular gland fat CNR increased with higher doses and were significantly higher for ADMIRE compared to FBP, with the best results in ADMIRE 5 (all p < 0.001). Subjective image quality was highest for ADMIRE 5 at 75% and lowest for FBP at 25% of the original dose (p < 0.001). Diagnostic confidence was highest for ADMIRE 5 at 75% and lowest for FBP at 25% (p < 0.001). Patient-based diagnostic accuracy was high for all LDCT datasets, down to 25% for ADMIRE 3 and 5 (sensitivity: 100%; specificity: 100%) and lower for FBP at 25% dose reduction (sensitivity: 88.6-94.3%; specificity: 92.3-100%). The use of a modern dual-source CT of the third generation and iterative reconstruction allows a reduction in the radiation dose to 25% (0.5 mSv) of the original dose with the same diagnostic accuracy for the assessment of neck abscesses.

Patient-based low dose cone beam CT acquisition settings for prostate image-guided radiotherapy treatments on a Varian TrueBeam linear accelerator

OBJECTIVE

To evaluate the performance of low dose cone beam CT (CBCT) acquisition protocols for image-guided radiotherapy of prostate cancer.

METHODS

CBCT images of patients undergoing prostate cancer radiotherapy were acquired with the settings currently used in our department and two low dose settings at 50% and 63% lower exposure. Four experienced radiation oncologists and two radiation therapy technologists graded the images on five image quality characteristics. The scores were analysed through Visual Grading Regression, using the acquisition settings and the patient size as covariates.

RESULTS

The low dose acquisition settings have no impact on the image quality for patients with body profile length at hip level below 100 cm.

CONCLUSIONS

A reduction of about 60% of the dose is feasible for patients with size below 100 cm. The visibility of low contrast features can be compromised if using the low dose acquisition settings for patients with hip size above 100 cm.

ADVANCES IN KNOWLEDGE

Low dose CBCT acquisition protocols for the pelvis, based on subjective evaluation of patient images.

Evaluation of Image Quality for 7 Iterative Reconstruction Algorithms in Chest Computed Tomography Imaging: A Phantom Study

OBJECTIVES

This study aimed to evaluate the image quality of 7 iterative reconstruction (IR) algorithms in comparison to filtered back-projection (FBP) algorithm.

METHODS

An anthropomorphic chest phantom was scanned on 4 computed tomography scanners and reconstructed with FBP and IR algorithms. Image quality of anatomical details-large/medium-sized pulmonary vessels, small pulmonary vessels, thoracic wall, and small and large lesions-was scored. Furthermore, general impression of noise, image contrast, and artifacts were evaluated. Visual grading regression was used to analyze the data. Standard deviations were measured, and the noise power spectrum was calculated.

RESULTS

Iterative reconstruction algorithms showed significantly better results when compared with FBP for these criteria (regression coefficients/P values in parentheses): vessels (FIRST: -1.8/0.05, AIDR Enhanced: <-2.3/0.01, Veo: <-0.1/0.03, ADMIRE: <-2.1/0.04), lesions (FIRST: <-2.6/0.01, AIDR Enhanced: <-1.9/0.03, IMR1: <-2.7/0.01, Veo: <-2.4/0.02, ADMIRE: -2.3/0.02), image noise (FIRST: <-3.2/0.004, AIDR Enhanced: <-3.5/0.002, IMR1: <-6.1/0.001, iDose: <-2.3/0.02, Veo: <-3.4/0.002, ADMIRE: <-3.5/0.02), image contrast (FIRST: -2.3/0.01, AIDR Enhanced: -2.5/0.01, IMR1: -3.7/0.001, iDose: -2.1/0.02), and artifacts (FIRST: <-3.8/0.004, AIDR Enhanced: <-2.7/0.02, IMR1: <-2.6/0.02, iDose: -2.1/0.04, Veo: -2.6/0.02). The iDose algorithm was the only IR algorithm that maintained the noise frequencies.

CONCLUSIONS

Iterative reconstruction algorithms performed differently on all evaluated criteria, showing the importance of careful implementation of algorithms for diagnostic purposes.

Comparison of submillisievert CT with standard-dose CT for urolithiasis

BACKGROUND

Patients with renal stones receive multiple computed tomography (CT) examinations. We investigated whether submillisievert (sub-mSv) CT for stone detection could reduce radiation dose at exposure levels comparable to kidney, ureter, and bladder (KUB) radiography.

PURPOSE

To evaluate the radiation dose exposure, diagnostic performance, and image quality of sub-mSv non-contrast CT using advanced modelled iterative reconstruction algorithm with spectral filtration for the detection of urolithiasis.

MATERIAL AND METHODS

A total of 145 consecutive patients underwent non-contrast CT using a third-generation dual-source scanner to obtain two datasets, i.e. 16.7% (sub-mSv CT, tube detector A) and 100% (standard-dose CT, combination of tube detector A and B) tube loads with spectral filtration. The performance of sub-mSv CT for the detection of stones was analyzed by two readers and compared with that of standard-dose CT. Image quality was measured subjectively and objectively.

RESULTS

In total, 171 stones were detected in 79 patients. The mean effective radiation doses of sub-mSv CT was 0.3 mSv. The sensitivity and specificity values for diagnosis of stones measuring ≥3 mm was 95.1% and 100% for sub-mSv CT. The sensitivity and specificity for all stone detection was 74.9% and 97.8%, respectivey, for sub-mSv CT. The image quality was lower for sub-mSv CT than for standard-dose CT (P < 0.01).

CONCLUSION

Sub-mSv CT can be achieved with radiation doses close to KUB radiography. Sub-mSv CT with spectral filtration can be used to detect stones measuring ≥3 mm and be used as a follow-up imaging modality as an alternative to KUB radiography.

Feasibility of thin-slice abdominal CT in overweight patients using a vendor neutral image-based denoising algorithm: Assessment of image noise, contrast, and quality

The purpose of this study was to investigate whether the novel image-based noise reduction software (NRS) improves image quality, and to assess the feasibility of using this software in combination with hybrid iterative reconstruction (IR) in image quality on thin-slice abdominal CT. In this retrospective study, 54 patients who underwent dynamic liver CT between April and July 2017 and had a body mass index higher than 25 kg/m² were included. Three image sets of each patient were reconstructed as follows: hybrid IR images with 1-mm slice thickness (group A), hybrid IR images with 5-mm slice thickness (group B), and hybrid IR images with 1-mm slice thickness denoised using NRS (group C). The mean image noise and contrast-to-noise ratio relative to the muscle of the aorta and liver were assessed. Subjective image quality was evaluated by two radiologists for sharpness, noise, contrast, and overall quality using 5-point scales. The mean image noise was significantly lower in group C than in group A (p < 0.01), but no significant difference was observed between groups B and C. The contrast-to-noise ratio was significantly higher in group C than in group A (p < 0.01 and p = 0.01, respectively). Subjective image quality was also significantly higher in group C than in group A (p < 0.01), in terms of noise and overall quality, but not in terms of sharpness and contrast (p = 0.65 and 0.07, respectively). The contrast of images in group C was greater than that in group A, but this difference was not significant. Compared with hybrid IR alone, the novel NRS combined with a hybrid IR could result in significant noise reduction without sacrificing image quality on CT. This combined approach will likely be particularly useful for thin-slice abdominal CT examinations of overweight patients.

Dose Reduction While Preserving Diagnostic Quality in Head CT: Advancing the Application of Iterative Reconstruction Using a Live Animal Model

BACKGROUND AND PURPOSE

Iterative reconstruction has promise in lowering the radiation dose without compromising image quality, but its full potential has not yet been realized. While phantom studies cannot fully approximate the subjective effects on image quality, live animal models afford this assessment. We characterize dose reduction in head CT by applying advanced modeled iterative reconstruction (ADMIRE) in a live ovine model while evaluating preservation of gray-white matter detectability and image texture compared with filtered back-projection.

MATERIALS AND METHODS

A live sheep was scanned on a Force CT scanner (Siemens) at 12 dose levels (82-982 effective mAs). Images were reconstructed with filtered back-projection and ADMIRE (strengths, 1-5). A total of 72 combinations (12 doses × 6 reconstructions) were evaluated qualitatively for resemblance to the reference image (highest dose with filtered back-projection) using 2 metrics: detectability of gray-white matter differentiation and noise-versus-smoothness in image texture. Quantitative analysis for noise, SNR, and contrast-to-noise was also performed across all dose-strength combinations.

RESULTS

Both qualitative and quantitative results confirm that gray-white matter differentiation suffers at a lower dose but recovers when complemented by higher iterative reconstruction strength, and image texture acquires excessive smoothness with a higher iterative reconstruction strength but recovers when complemented by dose reduction. Image quality equivalent to the reference image is achieved by a 58% dose reduction with ADMIRE-5.

CONCLUSIONS

An approximately 60% dose reduction may be possible while preserving diagnostic quality with the appropriate dose-strength combination. This in vivo study can serve as a useful guide for translating the full implementation of iterative reconstruction in clinical practice.

Reducing radiation dose for multi-phase contrast-enhanced dual energy renal CT: pilot study evaluating prior iterative reconstruction

PURPOSE

Prior iterative reconstruction (PIR) uses spatial information from one phase of enhancement to reduce image noise in other phases. We sought to determine if PIR could reduce radiation dose while preserving observer performance and CT number at multi-phase dual energy (DE) renal CT.

METHODS

CT projection data from multi-phase DE renal CT examinations were collected. Images corresponding to 40% radiation dose were reconstructed using validated noise insertion and PIR. Three genitourinary radiologists examined routine and 40% dose PIR images. Probability of malignancy was assessed [from 0 to 100] with malignancy assumed at probability ≥ 75. Observer performance was compared on a per patient and per lesion level. CT number accuracy was measured.

RESULTS

Twenty-three patients had 49 renal lesions (11 solid renal neoplasms). CT number was nearly identical between techniques (mean CT number difference: unenhanced 2 ± 2 HU; enhanced 4 ± 4 HU). AUC for malignancy was similar between multi-phase routine dose DE and lower dose PIR images [per patient: 0.950 vs. 0.916 (p = 0.356); per lesion: 0.931 vs. 0.884 (p = 0.304)]. Per patient sensitivity was also similar (78% routine dose vs. 82% lower dose [p ≥ 0.99]), as was specificity (91% routine dose vs. 93% lower dose PIR [p > 0.99]), with similar findings on a per lesion level. Subjective image quality was also similar (p = 0.34).

CONCLUSIONS

Prior iterative reconstruction is a new reconstruction method for multi-phase CT examinations that promises to facilitate radiation dose reduction by over 50% for multi-phase DE renal CT exams without compromising CT number or observer performance.

[Vascular causes of clinically unclear acute abdomen]

CLINICAL ISSUE

Vascular abnormalities are a rare cause of an acute abdomen. They include arterial bleeding and ischemia, the latter being either in the arterial or venous system. The most common cause of an acute ischemic abdomen is acute mesenteric ischemia caused by a thromboembolic occlusion of the superior mesenteric artery, followed by thrombotic occlusion of the portal vein, the mesenteric vein as well as the hepatic veins and the suprahepatic part of the inferior vena cava. In the case of an acute abdomen due to internal bleeding, all abdominal arteries can be the source but most common are ruptures of aortic aneurysms and inflammatory-driven bleeding from the superior mesenteric artery.

PRACTICAL RECOMMENDATIONS

Due to the high mortality, vascular causes should be diagnosed as soon as possible. For this purpose, computed tomography (CT) has evolved into the preferred tool due to its high availability and speed. To differentiate various vascular causes of an acute abdomen, it is important to incorporate a CT protocol without contrast media as well as contrast-enhanced series in arterial and venous phases. Conventional angiography has been replaced by CT for the diagnosis of vascular pathologies causing an acute abdomen; however, it plays an increasing role in the treatment of these pathologies.

Image quality and pathology assessment in CT Urography: when is the low-dose series sufficient?

BACKGROUND

Our aim was to compare CT images from native, nephrographic and excretory phases using image quality criteria as well as the detection of positive pathological findings in CT Urography, to explore if the radiation burden to the younger group of patients or patients with negative outcomes can be reduced.

METHODS

This is a retrospective study of 40 patients who underwent a CT Urography examination on a 192-slice dual source scanner. Image quality was assessed for four specific renal image criteria from the European guidelines, together with pathological assessment in three categories: renal, other abdominal, and incidental findings without clinical significance. Each phase was assessed individually by three radiologists with varying experience using a graded scale. Certainty scores were derived based on the graded assessments. Statistical analysis was performed using visual grading regression (VGR). The limit for significance was set at p = 0.05.

RESULTS

For visual reproduction of the renal parenchyma and renal arteries, the image quality was judged better for the nephrogram phase (p < 0.001), whereas renal pelvis/calyces and proximal ureters were better reproduced in the excretory phase compared to the native phase (p < 0.001). Similarly, significantly higher certainty scores were obtained in the nephrogram phase for renal parenchyma and renal arteries, but in the excretory phase for renal pelvis/calyxes and proximal ureters. Assessment of pathology in the three categories showed no statistically significant differences between the three phases. Certainty scores for assessment of pathology, however, showed a significantly higher certainty for renal pathology when comparing the native phase to nephrogram and excretory phase and a significantly higher score for nephrographic phase but only for incidental findings.

CONCLUSION

Visualisation of renal anatomy was as expected with each post-contrast phase showing favourable scores compared to the native phase. No statistically significant differences in the assessment of pathology were found between the three phases. The low-dose CT (LDCT) seems to be sufficient in differentiating between normal and pathological examinations. To reduce the radiation burden in certain patient groups, the LDCT could be considered a suitable alternative as a first line imaging method. However, radiologists should be aware of its limitations.

Trends in radiation dose and image quality for pediatric patients with a multidetector CT and a third-generation dual-source dual-energy CT

AIM

To provide an overview on dose reduction and image quality after the installation of a third-generation dual-source CT (dsCT) in a Pediatric Radiology Department.

MATERIALS AND METHODS

We included pediatric patients (< 20 years old) undergoing CT for oncological staging (neck, chest and abdomen) or low-dose chest CT for lung diseases. Each of these two groups were further divided in two age groups (≤ or > 10 years old) including patients scanned in the same period of two consecutive years, in 2017 with a 16-row LightSpeed CT (GE Healthcare) or in 2018 with a Somatom Force dsCT (Siemens Healthineers). Technical parameters such as kVp, mAs, slice thickness, exposure times and dose indicators were retrieved and compared. Image quality was evaluated in consensus by two radiologists on a five-point semiquantitative scale. Nonparametric tests were used.

RESULTS

In oncological patients, significantly lower kVp and tube current with better image quality were achieved with the dsCT. Radiation dose (total DLP) was 5-6 times lower with dsCT, thanks also to virtual non-contrast images. In low-dose chest CT, the frequent use of tin filter required higher tube current; a total DLP 3 times lower was achieved with dsCT in patients ≤ 10 years old. The image quality was better with the dsCT in low-dose chest CT protocols.

CONCLUSION

The third-generation dsCT provides high-quality images with reduced motion artifacts at lower dose.

Improving image quality with model-based iterative reconstruction algorithm for chest CT in children with reduced contrast concentration

OBJECTIVE

To evaluate model-based iterative reconstruction (MBIR) in improving the image quality of chest CT in children with reduced concentration contrast medium (CM).

METHODS

Fifty-six children (median age of 4 years) who received low-dose enhanced chest CT were enrolled as the study group and compared with the control group of 56 children. Both groups used the automatic tube current modulation to achieve age-based noise index values of 11-15 HU. The study group used 100 kVp and reduced CM concentration of 270 mgI/ml, and the images in this group were reconstructed with 50% adaptive statistical iterative reconstruction (ASIR) and MBIR. The control group used 120 kV and standard CM of 320 mgI/ml, and the images in this group were reconstructed with ASIR only. Subjective image quality and objective image quality of the three image sets were evaluated. The subjective quality included overall image noise, enhancement degree, lesion (including mediastinum mass, pulmonary space-occupying lesions, and parenchymal infiltrative lesions) conspicuity, and beam-hardening artifacts. The objective quality included the measurement of noise in the left ventricle and back muscle to calculate signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of ventricle.

RESULTS

There was no difference in radiation dose between the study (CTDIvol of 1.79 ± 1.45 mGy) and control (1.68 ± 0.92 mGy) groups (p = 0.65). However, the study group used 19.7% lower CM dose than the control group (5.84 ± 2.69 vs. 7.27 ± 3.80 gI), and the enhancement in all images met the diagnostic requirements. MBIR reduced image noise by 58.6% and increased SNR and CNR by 143.6% and 165.7%, respectively, compared to ASIR images in the control group. The two ASIR image sets had similar image quality.

CONCLUSION

MBIR improved the image quality of low-radiation-dose chest CT in children at 19.3% reduced CM dose.

CT radiation dose reduction in patients with total hip arthroplasties using model-based iterative reconstruction and orthopaedic metal artefact reduction

OBJECTIVE

To evaluate the impact of radiation dose reduction on image quality in patients with metal-on-metal total hip arthroplasties (THAs) using model-based iterative reconstruction (MBIR) combined with orthopaedic metal artefact reduction (O-MAR).

MATERIALS AND METHODS

Patients with metal-on-metal THAs received a pelvic CT with a full (FD) and a reduced radiation dose (RD) with -20%, -40%, -57%, or -80% CT radiation dose respectively, when assigned to group 1, 2, 3, or 4 respectively. FD acquisitions were reconstructed with iterative reconstruction, iDose⁴. RD acquisitions were additionally reconstructed with iterative model-based reconstruction (IMR) levels 1-3 with different levels of noise suppression. CT numbers, noise and contrast-to-noise ratios were measured in muscle, fat and bladder. Subjective image quality was evaluated on seven aspects including artefacts, osseous structures, prosthetic components and soft tissues.

RESULTS

Seventy-six patients were randomly assigned to one of the four groups. While reducing radiation dose by 20%, 40%, 57%, or 80% in combination with IMR, CT numbers remained constant. Compared with iDose⁴, the noise decreased (p < 0.001) and contrast-to-noise ratios increased (p < 0.001) with IMR. O-MAR improved CT number accuracy in the bladder and reduced noise in the bladder, muscle and fat (p < 0.01). Subjective image quality was rated lower on RD IMR images than FD iDose⁴ images on all seven aspects (p < 0.05) and was not related to the applied radiation dose reduction.

CONCLUSION

In RD IMR with O-MAR images, CT numbers remained constant, noise decreased and contrast-to-noise ratios between muscle and fat increased compared with FD iDose⁴ with O-MAR images in patients with metal-on-metal THAs. Subjective image quality reduced, regardless of the degree of radiation dose reduction.

Prospective evaluation of ultra-low-dose contrast-enhanced 100-kV abdominal computed tomography with tin filter: effect on radiation dose reduction and image quality with a third-generation dual-source CT system

OBJECTIVES

To investigate the radiation dose exposure, image quality, and diagnostic performance of enhanced 100-kVp abdominopelvic single-energy CT protocol with tin filter (TF).

METHODS

Ninety-three consecutive patients referred for a single-phase enhanced abdominopelvic CT were prospectively included after informed consent. They underwent in addition to a standard protocol (SP) an acquisition with TF. Both examinations were performed on a third-generation dual-source CT system (DSCT), in single energy, using automatic tube current modulation, identical pitch, and identical level of iterative reconstruction. Radiation metrics were compared. Size-specific dose estimates (SSDE), contrast to noise ratio (CNR), and figure of merit (FOM) were calculated. Diagnostic confidence for the assessment of a predetermined list of abdominal lesions was rated by two independent readers.

RESULTS

The mean dose of the TF protocol was significantly lower (CDTI 1.56 ± 0.43 mGy vs. 8.13 ± 3.32, p < 0.001; SSDE 9.94 ± 3.08 vs. 1.93 ± 0.39, p < 0.001), with an effective dose close to 1 mSv (1.14 mSv ± 0.34; p < 0.001). TF group exhibited non-significant lower liver CNR (2.76 vs. 3.03, p = 0.56) and was more dose efficient (FOM 10.6 vs. 2.49/mSv, p < 0.001) in comparison to SP. The mean diagnostic confidence for visceral, bone, and peritoneal tumors was equivalent between both groups.

CONCLUSIONS

Enhanced 100-kVp abdominopelvic CT acquired after spectral shaping with tin filtration can achieve similar diagnostic performance and CNR compared to a standard CT protocol, while reducing the radiation dose by 81%.

KEY POINTS

• 100-kVp spectral filtration enables enhanced abdominal CT with high-dose efficiency. • The radiation dose reaches the 1-mSv range. • Predetermined abdominopelvic lesions can be assessed without impairing on diagnostic confidence.

New cross-sectional imaging in IBD

PURPOSE OF REVIEW

Cross-sectional imaging, namely ultrasound, CT and MR enterography, complements clinical and endoscopic monitoring of activity and complications in IBD, and emerging new radiological technologies may have clinical applications in the near future. This review offers an update on the potential role of these new imaging methods in the management of IBD.

RECENT FINDINGS

Specific MR techniques [diffusion-weighted imaging (DWI), diffusion kurtosis imaging (DKI) and magnetization transfer] allow accurate detection of inflammation (DWI and maybe DKI) and fibrosis (magnetization transfer) in Crohn's disease, without the need of intravenous gadolinium administration. ultrasonography developments (elastography, contrast-enhanced ultrasonography, small intestine contrast ultrasonography and multispectral optoacoustic tomography) are promising techniques for evaluation of fibrosis (elastography) and inflammation (contrast ultrasonography). Dose-reduction techniques in CT allow similar quality imaging and diagnostic accuracy with lower radiation exposure. Hybrid imaging (PET/MR and PET/CT) hold promise for grading inflammation in Crohn's disease.

SUMMARY

The potential benefits of new cross-sectional imaging techniques in IBD include better inflammation grading, such as identification of mild degree of activity, which may be relevant whenever assessing response to treatment and, of uttermost importance, accurate preoperative detection and grading of fibrosis in stricturing Crohn's disease, facilitating surgical vs. medical therapeutic decisions.