Detection and size measurements of kidney stones on virtual non-contrast reconstructions derived from dual-layer computed tomography in an ex vivo phantom setup

OBJECTIVES

To systematically investigate the usability of virtual non-contrast reconstructions (VNC) derived from dual-layer CT (DLCT) for detection and size measurements of kidney stones with regards to different degrees of surrounding iodine-induced attenuation and radiation dose.

METHODS

Ninety-two kidney stones of varying size (3-14 mm) and composition were placed in a phantom filled with different contrast media/water mixtures exhibiting specific iodine-induced attenuation (0-1500 HU). DLCT-scans were acquired using CTDI_vol of 2 mGy and 10 mGy. Conventional images (CI) and VNC_0H-1500HU were reconstructed. Reference stone size was determined using a digital caliper (Man-M). Visibility and stone size were assessed. Statistical analysis was performed using the McNemar test, Wilcoxon test, and the coefficient of determination.

RESULTS

All stones were visible on CI_0HU and VNC_200HU. Starting at VNC_{400 HU}, the detection rate decreased with increasing HU and was significantly lower as compared to CI_0HU on VNC_{≥ 600HU} (100.0 vs. 94.0%, p < 0.05). The overall detection rate was higher using 10 mGy as compared to 2 mGy protocol (87.9 vs. 81.8%; p < 0.001). Stone size was significantly overestimated on all VNC compared to Man-M (7.0 ± 3.5 vs. 6.6 ± 2.8 mm, p < 0.001). Again, the 10 mGy protocol tended to show a better correlation with Man-M as compared to 2 mGy protocol (R² = 0.39-0.68 vs. R² = 0.31-0.57).

CONCLUSIONS

Detection and size measurements of kidney stones surrounded by contrast media on VNC are feasible. The detection rate of kidney stones decreases with increasing iodine-induced attenuation and with decreasing radiation dose as well as stone size, while remaining comparable to CI_0HU on VNC _{≤ 400 HU}.

KEY POINTS

• The detection rate of kidney stones on VNC depends on the surrounding iodine-induced attenuation, the used radiation dose, and the stone size. • The detection rate of kidney stones on VNC decreases with greater iodine-induced attenuation and with lower radiation dose, particularly in small stones. • The visibility of kidney stones on VNC _{≤ 400 HU} remains comparable to true-non-contrast scans even when using a low-dose technique.

Physical and visual evaluations of CT image quality of large low-contrast objects with visual model-based iterative reconstruction technique: a phantom study

We aimed to verify whether the image quality of large low-contrast objects can be improved using visual model-based iterative reconstruction (VMR) while maintaining the visibility of conventional filtered back projection (FBP) and reducing radiation dose through physical and visual evaluation. A 64-row multi-slice CT system with SCENARIA View (FUJIFILM healthcare Corp. Tokyo, Japan) was used. The noise power spectrum (NPS), task-based transfer function (TTF), and signal-to-noise ratio (SNR) were physically evaluated. A low contrast object as a substitute for a liver mass was visually evaluated. In the noise measurement, STD1 showed an 18% lower noise compared to FBP. STR4 was able to reduce noise by 58% compared to FBP. The NPS of VMR was similar to those of FBP from low to high spatial frequency. The NPS of VMR reconstructions showed a similar variation with frequency as FBP reconstructions. STD1 showed the highest 10% TTF, and higher 10% TTF was observed with lower VMR level. The SNR of VMR was close to that of FBP, and higher SNR was observed with higher VMR level. In the results of the visual evaluation, there was no significant difference in visual evaluation between STD1 and FBP (p = 0.99) and between STD2 and FBP (p = 0.56). We found that the NPS of VMR images was similar to that of FBP images, and it can reduce noise and radiation dose by 25% and 50%, respectively, without decreasing the visual image quality compared to FBP.

Value of deep learning reconstruction at ultra-low-dose CT for evaluation of urolithiasis

OBJECTIVES

To determine the diagnostic accuracy and image quality of ultra-low-dose computed tomography (ULDCT) with deep learning reconstruction (DLR) to evaluate patients with suspected urolithiasis, compared with ULDCT with hybrid iterative reconstruction (HIR) by using low-dose CT (LDCT) with HIR as the reference standard.

METHODS

Patients with suspected urolithiasis were prospectively enrolled and underwent abdominopelvic LDCT, followed by ULDCT if any urinary stone was observed. Radiation exposure, stone characteristics, image noise, signal-to-noise ratio (SNR), and subjective image quality on a 5-point Likert scale were evaluated and compared.

RESULTS

The average effective radiation dose of ULDCT was significantly lower than that of LDCT (1.28 ± 0.34 vs. 5.49 ± 1.00 mSv, p < 0.001). According to the reference standard (LDCT-HIR), 148 urinary stones were observed in 85.0% (51/60) of patients. ULDCT-DLR detected 143 stones with a rate of 96.6%, and ULDCT-HIR detected 142 stones with a rate of 95.9%. The urinary stones that were not observed with ULDCT-DLR or ULDCT-HIR were renal calculi smaller than 3 mm. There were no significant differences in the detection of clinically significant calculi (≥ 3 mm) or stone size estimation among ULDCT-DLR, ULDCT-HIR, and LDCT-HIR. The image quality of ULDCT-DLR was better than that of ULDCT-HIR and LDCT-HIR with lower image noise, higher SNR, and higher average subjective score.

CONCLUSIONS

ULDCT-DLR performed comparably to LDCT-HIR in urinary stone detection and size estimation with better image quality and decreased radiation exposure. ULDCT-DLR may have potential to be considered the first-line choice to evaluate urolithiasis in practice.

KEY POINTS

• Ultra-low-dose computed tomography (ULDCT) has been investigated for diagnosis of urolithiasis, but stone evaluation may be adversely impacted by compromised image quality. • This study evaluated the value of novel deep learning reconstruction (DLR) at ULDCT by comparing the stone evaluation and image quality of ULDCT-DLR to the reference standard of low-dose CT (LDCT) with hybrid iterative reconstruction (HIR). • ULDCT-DLR performed comparably to LDCT-HIR in urinary stone detection and size estimation with better image quality and reduced radiation exposure.

Image quality and diagnostic accuracy of reduced-dose computed tomography enterography with model-based iterative reconstruction in pediatric Crohn's disease patients

This study assessed the image quality and diagnostic accuracy in determining disease activity of the terminal ileum of the reduced-dose computed tomography enterography using model-based iterative reconstruction in pediatric patients with Crohn's disease (CD). Eighteen patients were prospectively enrolled and allocated to the standard-dose (SD) and reduced-dose (RD) computed tomography enterography (CTE) groups (n = 9 per group). Image quality, reader confidence in interpreting bowel findings, accuracy in determining active CD in the terminal ileum, and radiation dose were evaluated. Objective image quality did not show intergroup differences, except for image sharpness. Although reader confidence in detecting mural stratification, ulcer, and perienteric fat stranding of the RD-CTE were inferior to SD-CTE, RD-CTE correctly diagnosed active disease in all patients. The mean values of radiation dose metrics (SD-CTE vs. RD-CTE) were 4.3 versus 0.74 mGy, 6.1 versus 1.1 mGy, 211.9 versus 34.5 mGy∙cm, and 4.4 versus 0.7 mSv mGy∙cm for CTDI_vol, size-specific dose estimation, dose-length product, and effective dose, respectively. RD-CTE showed comparable diagnostic accuracy to SD-CTE in determining active disease of the terminal ileum in pediatric CD patients. However, image quality and reader confidence in detecting ulcer and perienteric fat stranding was compromised.

Manual kidney stone size measurements in computed tomography are most accurate using multiplanar image reformatations and bone window settings

Computed tomography in suspected urolithiasis provides information about the presence, location and size of stones. Particularly stone size is a key parameter in treatment decision; however, data on impact of reformatation and measurement strategies is sparse. This study aimed to investigate the influence of different image reformatations, slice thicknesses and window settings on stone size measurements. Reference stone sizes of 47 kidney stones representative for clinically encountered compositions were measured manually using a digital caliper (Man-M). Afterwards stones were placed in a 3D-printed, semi-anthropomorphic phantom, and scanned using a low dose protocol (CTDIvol 2 mGy). Images were reconstructed using hybrid-iterative and model-based iterative reconstruction algorithms (HIR, MBIR) with different slice thicknesses. Two independent readers measured largest stone diameter on axial (2 mm and 5 mm) and multiplanar reformatations (based upon 0.67 mm reconstructions) using different window settings (soft-tissue and bone). Statistics were conducted using ANOVA ± correction for multiple comparisons. Overall stone size in CT was underestimated compared to Man-M (8.8 ± 2.9 vs. 7.7 ± 2.7 mm, p < 0.05), yet closely correlated (r = 0.70). Reconstruction algorithm and slice thickness did not significantly impact measurements (p > 0.05), while image reformatations and window settings did (p < 0.05). CT measurements using multiplanar reformatation with a bone window setting showed closest agreement with Man-M (8.7 ± 3.1 vs. 8.8 ± 2.9 mm, p < 0.05, r = 0.83). Manual CT-based stone size measurements are most accurate using multiplanar image reformatation with a bone window setting, while measurements on axial planes with different slice thicknesses underestimate true stone size. Therefore, this procedure is recommended when impacting treatment decision.

The effect of tube focal spot size and acquisition mode on task-based image quality performance of a GE revolution HD dual energy CT scanner

PURPOSE

To assess the task-based performance of images obtained under different focal spot size and acquisition mode on a dual-energy CT scanner.

METHODS

Axial CT image series of the Catphan phantom were obtained using a tube focus at different sizes. Acquisitions were performed in standard single-energy, high resolution (HR) and dual-energy modes. Images were reconstructed using conventional and high definition (HD) kernels. Task-based transfer function at the 50% level (TTF_50%) for teflon, delrin, low density polyethylene (LDPE) and acrylic, as well as image noise and noise texture, were assessed across all focal spots and acquisition modes using Noise Power Spectrum (NPS) analysis. A non-prewhitening mathematical observer model was used to calculate detectability index (d_NPW^').

RESULTS

TTF_50% degraded with increasing focal spot size. TTF_50% ranged from 0.67 mm^-1 for teflon to 0.25 mm^-1 for acrylic. For standard kernel, image noise and NPS-determined average spatial frequency were 8.3 HU and 0.29 mm^-1, respectively in single-energy, 12.0 HU and 0.37 mm^-1 in HR, and 7.9 HU and 0.26 mm^-1 in dual-energy mode. For standard kernel, d_NPW^' was 61 in single-energy and HR mode and reduced to 56 in dual-energy mode.

CONCLUSIONS

The task-based image quality assessment metrics have shown that spatial resolution is higher for higher image contrast materials and detectability is higher in the standard single-energy mode compared to HR and dual-energy mode. The results of the current study provide CT operators the required knowledge to characterize their CT system towards the optimization of its clinical performance.

Optimization of the scan length of head traumas on the pediatric and adult CT scan and proposition of a new acquisition limit

To propose a new method of reducing the scan length of head trauma while keeping the diagnostic efficiency of the examination in order to develop DRL in an African context. This is a retrospective single-center study including 145 patients who had cranial examinations on a 64-barettes scanner. All head trauma cases were selected. The interpretations of these CT scanners by the three radiologists of the service were noted to determine the acquisition limit. All patient acquisition lengths have been recorded. The acquisition limit for head trauma ended in clinical routine at cervical spine 4 (C4). The average scan length was 23.03 cm. Out of the CT scan results for 145 patients, only 2 (1.37%) had a C3 level cervical spine fracture and 2 (1.37%) at C4. By respecting the principles of radiation protection, this result has shown us that it is possible to limit the acquisition length of the CT scanners indicated for head trauma. The limit of the optimized scan length that we proposed is at cervical spine 2 (98.62%). Now, all head trauma are limited on cervical vertebra 2 in our hospital. The use of this new method is beneficial when the clinical indication of the examination and the type of trauma (multi-trauma) are taken into account. Based on the principles of radiation protection and the clinical indication for the examination, reducing the scan length from C4 to C2 is an effective way to reduce the dose absorbed by the patient.

Deep learning-based denoising algorithm in comparison to iterative reconstruction and filtered back projection: a 12-reader phantom study

OBJECTIVES

(1) To compare low-contrast detectability of a deep learning-based denoising algorithm (DLA) with ADMIRE and FBP, and (2) to compare image quality parameters of DLA with those of reconstruction methods from two different CT vendors (ADMIRE, IMR, and FBP).

MATERIALS AND METHODS

Using abdominal CT images of 100 patients reconstructed via ADMIRE and FBP, we trained DLA by feeding FBP images as input and ADMIRE images as the ground truth. To measure the low-contrast detectability, the randomized repeat scans of Catphan® phantom were performed under various conditions of radiation exposures. Twelve radiologists evaluated the presence/absence of a target on a five-point confidence scale. The multi-reader multi-case area under the receiver operating characteristic curve (AUC) was calculated, and non-inferiority tests were performed. Using American College of Radiology CT accreditation phantom, contrast-to-noise ratio, target transfer function, noise magnitude, and detectability index (d') of DLA, ADMIRE, IMR, and FBPs were computed.

RESULTS

The AUC of DLA in low-contrast detectability was non-inferior to that of ADMIRE (p < .001) and superior to that of FBP (p < .001). DLA improved the image quality in terms of all physical measurements compared to FBPs from both CT vendors and showed profiles of physical measurements similar to those of ADMIRE.

CONCLUSIONS

The low-contrast detectability of the proposed deep learning-based denoising algorithm was non-inferior to that of ADMIRE and superior to that of FBP. The DLA could successfully improve image quality compared with FBP while showing the similar physical profiles of ADMIRE.

KEY POINTS

• Low-contrast detectability in the images denoised using the deep learning algorithm was non-inferior to that in the images reconstructed using standard algorithms. • The proposed deep learning algorithm showed similar profiles of physical measurements to advanced iterative reconstruction algorithm (ADMIRE).

Effect of New Model-Based Iterative Reconstruction on Quantitative Analysis of Airway Tree by Computer-Aided Detection Software in Chest Computed Tomography

OBJECTIVE

Compared the performance of computer-aided detection (CAD) software for quantitative analysis of airway using computed tomography (CT) images reconstructed with versions of model-based iterative reconstruction (MBIR) that either balances spatial and density resolution (MBIRSTND) or prefers spatial resolution (MBIRRP20), and adaptive statistical iterative reconstruction (ASIR) with lung kernel.

METHODS

Thirty patients were included who were scanned for pulmonary disease using a routine dose multidetector CT system. Data were reconstructed with ASIR, MBIRSTND, and MBIRRP20. Airway dimensions from the 3 reconstructions were measured using an automated, quantitative CAD software designed to segment and quantify the bronchial tree automatically using a skeletonization algorithm. For each patient and reconstruction algorithm, the right middle lobe bronchus was selected as a representative for measuring the bronchial length of the matched airways. Two radiologists used a semiquantitative 5-point scale to rate the subjective image quality of MBIRSTND and MBIRRP20 reconstructions on airway trees analysis.

RESULTS

Algorithm impacts the measurement variability of bronchus length in chest CT, MBIRRP20 were the best, whereas ASIR were the worst (P < 0.05). In addition, the optimal reconstruction algorithm was found to be MBIRSTND for the airway trees being assessed about subjective noise and MBIRRP20 about bronchial end shows, and there were no significant differences in the continuity and completeness of bronchial wall, whereas ASIR performed inferiorly compared with them (P < 0.05).

CONCLUSIONS

Compared with ASIR, MBIRSTND, and MBIRRP20 from MBIRn algorithm potentially allow the desired airway quantification accuracy to be achieved on the performance of CAD, especially for MBIRRP20.

Diagnostic value of deep learning reconstruction for radiation dose reduction at abdominal ultra-high-resolution CT

OBJECTIVES

We evaluated lower dose (LD) hepatic dynamic ultra-high-resolution computed tomography (U-HRCT) images reconstructed with deep learning reconstruction (DLR), hybrid iterative reconstruction (hybrid-IR), or model-based IR (MBIR) in comparison with standard-dose (SD) U-HRCT images reconstructed with hybrid-IR as the reference standard to identify the method that allowed for the greatest radiation dose reduction while preserving the diagnostic value.

METHODS

Evaluated were 72 patients who had undergone hepatic dynamic U-HRCT; 36 were scanned with the standard radiation dose (SD group) and 36 with 70% of the SD (lower dose [LD] group). Hepatic arterial and equilibrium phase (HAP, EP) images were reconstructed with hybrid-IR in the SD group, and with hybrid-IR, MBIR, and DLR in the LD group. One radiologist recorded the standard deviation of attenuation in the paraspinal muscle as the image noise. The overall image quality was assessed by 3 other radiologists; they used a 5-point confidence scale ranging from 1 (unacceptable) to 5 (excellent). Superiority and equivalence with prespecified margins were assessed.

RESULTS

With respect to the image noise, in the HAP and EP, LD DLR and LD MBIR images were superior to SD hybrid-IR images; LD hybrid-IR images were neither superior nor equivalent to SD hybrid-IR images. With respect to the quality scores, only LD DLR images were superior to SD hybrid-IR images.

CONCLUSIONS

DLR preserved the quality of abdominal U-HRCT images even when scanned with a reduced radiation dose.

KEY POINTS

• Lower dose DLR images were superior to the standard-dose hybrid-IR images quantitatively and qualitatively at abdominal U-HRCT. • Neither hybrid-IR nor MBIR may allow for a radiation dose reduction at abdominal U-HRCT without compromising the image quality. • Because DLR allows for a reduction in the radiation dose and maintains the image quality even at the thinnest slice section, DLR should be applied to abdominal U-HRCT scans.

Size and volume of kidney stones in computed tomography: Influence of acquisition techniques and image reconstruction parameters

PURPOSE

Computed tomography (CT) is routinely used to assess suspected urolithiasis. Information obtained from CT include presence, location and size of stones, with the latter frequently determining treatment strategy. While there is consensus regarding measurements procedures of kidney stones, influence of radiation dose and reconstruction techniques on stone measurements are unknown. The purpose of this study was to systematically evaluate the influence of these technical determinants on kidney stone size measurements.

METHOD

47 kidney stones of different composition were scanned using a 64-row-multi-detector CT in a 3D-printed, semi-anthropomorphic phantom. Reference stone sizes were measured manually with a digital caliper (Man-M). Stones were imaged with 2 and 10 mGy CTDI. Images were reconstructed using filtered-back-projection, hybrid-iterative and model-based-iterative reconstruction algorithms (FBP, HIR, MBIR) in combination with different kernels and denoising levels. All stones underwent semi-automatic, threshold-based segmentation for computation of maximum diameter and volume. Statistics were conducted using ANOVA ± correction for multiple comparisons.

RESULTS

Overall stone size as compared to manual measurements was overestimated in CT (10.0 ± 3.1 vs. 8.8 ± 2.9 mm, p < 0.05) yet showing a good correlation (R² = 0.66). Radiation dose and denoising levels did not significantly influence measurements (p > 0.05). MBIR and sharp kernels showed closest agreement with Man-M (9.3 ± 3.1 vs. 8.8 ± 2.9 mm, p < 0.05). Differences within single stones were as high as 40 % (e.g. Man-M: 5.9 mm, CT: 7.3-12.0 mm).

CONCLUSIONS

CT-based measurements of kidney stone size appear unaffected by radiation dose and denoising technique, whereas reconstruction algorithms and kernels demonstrate a relevant impact on size measurements. Smallest differences were found using MBIR with a sharp kernel.

Using the T11 vertebra to minimise the CT-KUB scan field

OBJECTIVES

Computed tomography scans of the kidney, ureters, and bladder (CT-KUB) are crucial in investigating urinary calculi but impart a substantial radiation doses. Radiation can be limited by minimising the scanning field to the necessary area (i.e. from the kidneys to urethra). Before auditing, the superior limit of CT-KUB scans had not been formally clarified at our trust. Consistently ensuring the upper limit of scans is at or below T10 has been shown to be a viable method of performing CT-KUB scans. This study aimed to assess the overscan length of CT-KUB investigations and modify practice accordingly to minimise it. There were two standards that were set for CT-KUB scanning. First, the mean percentage overscan length (i.e. percentage of the scan above the kidneys) should be <15%. Second, all scans should include the superior borders of both kidneys.

METHODS

90 consecutive CT-KUB scans for ureteric calculus were retrospectively investigated using IMPAX software in the first phase of data collection. After these data were analysed, a newly devised protocol using T11 as the superior scan limit was delivered to radiographers in the department. and 105 in the second phase (re-audit). The analysis parameters were: percentage overscan length, distance between diaphragm and upper border of kidneys, vertebral level at which the scan commenced, and whether both kidneys were fully included.

RESULTS

In the first phase, overscan of >15% was present in 94.4% of scans. The mean percentage overscan length was 28.2%. The superior vertebral limit of 59% of scans was at T10 or below and a lower superior vertebral limit correlated with decreasing overscan. 99% of scans fully included both kidneys. In the second phase (3 months later), the mean overscan percentage reduced to 10.6% (standard deviation = 4.4%). Excessive overscan affected 35.2% of scans. The superior vertebral limit of 8% of scans was at T10 or below. 100% of scans fully included both kidneys.

CONCLUSION

Excessive overscanning was due to inconsistent technique in capturing CT-KUB scans. Before this audit, the superior limit of CT-KUB scans had not been formally clarified at our trust. By successfully standardising the process with a reproducible method, the overscan target was comfortably met. Therefore, patient dose was minimised without compromising scan quality.

ADVANCES IN KNOWLEDGE

This audit has successfully shown a feasible standardised protocol for CT-KUB investigations which can be used to minimise overscanning of patients.

A New Class of Smart Gadolinium Contrast Agent for Tissue pH Probing Using Magnetic Resonance Imaging

Detecting tissue pH in vivo is extremely vital for medical diagnosis and formulation of treatment decisions. To this end, many investigations have been carried out to develop an accurate and efficient method of in vivo pH measurement. Most of the techniques developed so far suffer from inadequate accuracy, due to poor sensitivity at low concentration of the target or nonspecific interactions within the tissue matrix. To overcome these issues, we describe herein the development of a simple, yet reliable, way to estimate pH with high precision using a Gd(III)-DOTA-silyl-based acid-labile group as a pH-sensitive contrast agent with Magnetic Resonance Imaging (MRI). With this method, a change in T1 weighted image intensity of the newly developed pH-sensitive contrast is directly linked to the proton concentration in the media. As a result, we were able estimate the pH of the target with 95% reliability.

Whole-Body Computed Tomography Using Low-Dose Biphasic Injection Protocol With Adaptive Statistical Iterative Reconstruction V: Assessment of Dose Reduction and Image Quality in Trauma Patients

AIM

This study aimed to evaluate potential dose savings on a revised protocol for whole-body computed tomography and image quality after implementing Adaptive Statistical Iterative Reconstruction V (ASiR-V) algorism for trauma patients and compare it with routine protocol.

MATERIALS AND METHODS

One hundred trauma patients were classified into 2 groups using 2 different scanning protocols. Group A (n = 50; age, 32.48 ± 8.09 years) underwent routine 3-phase protocol. Group B (n = 50; age, 35.94 ± 13.57 years) underwent biphasic injection protocol including unenhanced scan for the brain and cervical spines, followed by a 1-step acquisition of the thorax, abdomen, and pelvis. The ASiR-V level was kept at 50% for all examinations, and then studies were reconstructed at 0% ASiR-V level. Radiation dose, total acquisition time, and image count were compared between groups (A and B). Two radiologists independently graded image quality and artifacts between both groups and 2 ASiR-V levels (0 and 50%).

RESULTS

The mean (±SD) dose-length product value for postcontrast scans in group A was 1602.3 ± 271.8 mGy · cm and higher when compared with group B (P < 0.001), which was 951.1 ± 359.6 mGy · cm. Biphasic injection protocol gave a dose reduction of 40.4% and reduced the total acquisition time by 11.4% and image count by 37.6%. There was no statistically significant difference between the image quality scores for both groups; however, group A scored higher grades (4.62 ± 0.56 and 4.56 ± 0.67). Similarly, the image quality scores for both ASiR-V levels in both groups were not significantly different.

CONCLUSIONS

Biphasic computed tomography protocol reduced radiation dose with maintenance of diagnostic accuracy and image quality after implementing ASiR-V algorism.

Deep Learning-based CT Image Reconstruction: Initial Evaluation Targeting Hypovascular Hepatic Metastases

Purpose

To evaluate the effect of a deep learning-based reconstruction (DLR) method on the conspicuity of hypovascular hepatic metastases on abdominal CT images.

Materials and Methods

This retrospective study with institutional review board approval included 58 patients with hypovascular hepatic metastases. A radiologist recorded the standard deviation of attenuation in the paraspinal muscle as the image noise and the contrast-to-noise ratio (CNR). CNR was calculated as region of interest ([ROI]_L - ROI_T)/N, where ROI_L is the mean liver parenchyma attenuation, ROI_T, the mean tumor attenuation, and N, the noise. Two other radiologists graded the conspicuity of the liver lesion on a five-point scale where 1 is unidentifiable and 5 is detected without diagnostic compromise. Only the smallest liver lesion in each patient, classified as smaller or larger than 10 mm, was evaluated. The difference between hybrid iterative reconstruction (IR) and DLR images was determined by using a two-sided Wilcoxon signed-rank test.

Results

The image noise was significantly lower, and the CNR was significantly higher on DLR images than hybrid IR images (median image noise: 19.2 vs 12.8 HU, P < .001; median CNR: tumors < 10 mm: 1.9 vs 2.5; tumors > 10 mm: 1.7 vs 2.2, both P < .001). The scores for liver lesions were significantly higher for DLR images than hybrid IR images (P < .01 for both in tumors smaller or larger than 10 mm).

Conclusion

DLR improved the quality of abdominal CT images for the evaluation of hypovascular hepatic metastases.© RSNA, 2019Supplemental material is available for this article.

Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT

OBJECTIVES

Deep learning reconstruction (DLR) is a new reconstruction method; it introduces deep convolutional neural networks into the reconstruction flow. This study was conducted in order to examine the clinical applicability of abdominal ultra-high-resolution CT (U-HRCT) exams reconstructed with a new DLR in comparison to hybrid and model-based iterative reconstruction (hybrid-IR, MBIR).

METHODS

Our retrospective study included 46 patients seen between December 2017 and April 2018. A radiologist recorded the standard deviation of attenuation in the paraspinal muscle as the image noise and calculated the contrast-to-noise ratio (CNR) for the aorta, portal vein, and liver. The overall image quality was assessed by two other radiologists and graded on a 5-point confidence scale ranging from 1 (unacceptable) to 5 (excellent). The difference between CT images subjected to hybrid-IR, MBIR, and DLR was compared.

RESULTS

The image noise was significantly lower and the CNR was significantly higher on DLR than hybrid-IR and MBIR images (p < 0.01). DLR images received the highest and MBIR images the lowest scores for overall image quality.

CONCLUSIONS

DLR improved the quality of abdominal U-HRCT images.

KEY POINTS

• The potential degradation due to increased noise may prevent implementation of ultra-high-resolution CT in the abdomen. • Image noise and overall image quality for hepatic ultra-high-resolution CT images improved with deep learning reconstruction as compared to hybrid- and model-based iterative reconstruction.

Quantitative Analysis of Airway Tree in Low-dose Chest CT with a New Model-based Iterative Reconstruction Algorithm: Comparison to Adaptive Statistical Iterative Reconstruction in Routine-dose CT

OBJECTIVE

We aimed to evaluate a new model-based iterative reconstruction (MBIRn) algorithm either with spatial resolution and noise reduction balance (MBIR_STND) or spatial resolution preference (MBIR_RP20) for quantitative analysis of airway in low-dose chest computed tomography (CT) with a computer-aided detection (CAD) software, in comparison to adaptive statistical iterative reconstruction (ASIR) in routine-dose CT.

METHODS

Thirty patients who underwent both the routine-dose (noise index [NI] = 14 HU) and low-dose (at 30% level with NI = 28 HU) CT examination for pulmonary disease were included. Image acquisition was performed with 120 kVp tube voltage and automatic tube current modulation. Routine-dose scans were reconstructed with ASIR, whereas low-dose scans were reconstructed with ASIR, MBIR_STND, and MBIR_RP20. Airway dimensions of the right middle lobe bronchus from the four reconstructions were measured using CAD software. Two radiologists used a semiquantitative 5 scoring criteria (-2, inferior to; +2, superior to; -1 slightly inferior to; +1, slightly superior to; and 0, equal to ASIR in routine-dose CT) to rate the subjective image quality of MBIR_STND and MBIR_RP20 of airway trees. The paired t test and Wilcoxon signed-rank test were used for statistical comparison.

RESULTS

The low-dose CT provided 70.76% dose reduction compared to the routine-dose CT (0.88 ± 0.83 mSv vs 3.01 ± 1.89 mSv). MBIR_STND and MBIR_RP20 with low-dose CT provided longer bronchial length measurements and were better in measurement variability and continuity and completeness of bronchial walls than ASIR in routine-dose CT (P < .05). MBIR_STND was better for subjective noise and MBIR_RP20 for showing distal branches_. CONCLUSIONS: MBIR_STND and MBIR_RP20 algorithms provide better airway quantification at 30% of the radiation dose, compared to ASIR at routine-dose CT.

Radiation dose reduction for CT assessment of urolithiasis using iterative reconstruction: A prospective intra-individual study

OBJECTIVE

To assess the performance of hybrid (HIR) and model-based iterative reconstruction (MIR) in patients with urolithiasis at reduced-dose computed tomography (CT).

METHODS

Twenty patients scheduled for unenhanced abdominal CT for follow-up of urolithiasis were prospectively included. Routine dose acquisition was followed by three low-dose acquisitions at 40%, 60% and 80% reduced doses. All images were reconstructed with filtered back projection (FBP), HIR and MIR. Urolithiasis detection rates, gall bladder, appendix and rectosigmoid evaluation and overall subjective image quality were evaluated by two observers.

RESULTS

74 stones were present in 17 patients. Half the stones were not detected on FBP at the lowest dose level, but this improved with MIR to a sensitivity of 100%. HIR resulted in a slight decrease in sensitivity at the lowest dose to 72%, but outperformed FBP. Evaluation of other structures with HIR at 40% and with MIR at 60% dose reductions was comparable to FBP at routine dose, but 80% dose reduction resulted in non-evaluable images.

CONCLUSIONS

CT radiation dose for urolithiasis detection can be safely reduced by 40 (HIR)-60 (MIR) % without affecting assessment of urolithiasis, possible extra-urinary tract pathology or overall image quality.

KEY POINTS

• Iterative reconstruction can be used to substantially lower the radiation dose. • This allows for radiation reduction without affecting sensitivity of stone detection. • Possible extra-urinary tract pathology evaluation is feasible at 40-60% reduced dose.

Iterative Reconstructions in Reduced-Dose CT: Which Type Ensures Diagnostic Image Quality in Young Oncology Patients?

RATIONALE AND OBJECTIVES

To compare adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) algorithms for reduced-dose computed tomography (CT).

MATERIALS AND METHODS

Forty-four young oncology patients (mean age 30 ± 9 years) were included. After routine thoraco-abdominal CT (dose 100%, average CTDI_vol 9.1 ± 2.4 mGy, range 4.4-16.9 mGy), follow-up CT was acquired at 50% (average CTDI_vol 4.5 ± 1.2 mGy, range 2.2-8.4 mGy) in 29 patients additionally at 20% dose (average CTDI_vol 1.9 ± 0.5 mGy, range 0.9-3.4 mGy). Each reduced-dose CT was reconstructed using both ASIR and MBIR. Four radiologists (two juniors and two seniors) blinded to dose and technique read each set of CT images regarding objective and subjective image qualities (high- or low-contrast structures), subjective noise or pixilated appearance, diagnostic confidence, and lesion detection.

RESULTS

At all dose levels, objective image noise was significantly lower with MBIR than with ASIR (P < 0.001). The subjective image quality for low-contrast structures was significantly higher with MBIR than with ASIR (P < 0.001). Reduced-dose abdominal CT images of patients with higher body mass index (BMI) were read with significantly higher diagnostic confidence than images of slimmer patients (P < 0.001) and had higher subjective image quality, regardless of technique. Although MBIR images appeared significantly more pixilated than ASIR images, they were read with higher diagnostic confidence, especially by juniors (P < 0.001).

CONCLUSIONS

Reduced-dose CT during the follow-up of young oncology patients should be reconstructed with MBIR to ensure diagnostic quality. Elevated body mass index does not hamper the quality of reduced-dose CT.

Evaluation of Kidney Stones with Reduced-Radiation Dose CT: Progress from 2011-2012 to 2015-2016-Not There Yet

Purpose To determine if the use of reduced-dose computed tomography (CT) for evaluation of kidney stones increased in 2015-2016 compared with that in 2011-2012, to determine variability in radiation exposure according to facility for this indication, and to establish a current average radiation dose for CT evaluation for kidney stones by querying a national dose registry. Materials and Methods This cross-sectional study was exempt from institutional review board approval. Data were obtained from the American College of Radiology dose registry for CT examinations submitted from July 2015 to June 2016. Study descriptors consistent with single-phase unenhanced CT for evaluation of kidney stones and associated RadLex® Playbook identifiers (RPIDs) were retrospectively identified. Facilities actively submitting data on kidney stone-specific CT examinations were included. Dose metrics including volumetric CT dose index, dose-length product, and size-specific dose estimate, when available, were reported, and a random effects model was run to account for clustering of CT examinations at facilities. A z-ratio was calculated to test for a significant difference between the proportion of reduced-radiation dose CT examinations (defined as those with a dose-length product of 200 mGy · cm or less) performed in 2015-2016 and the proportion performed in 2011-2012. Results Three hundred four study descriptors for kidney stone CT corresponding to data from 328 facilities that submitted 105 334 kidney stone CT examinations were identified. Reduced-dose CT examinations accounted for 8040 of 105 334 (7.6%) CT examinations, a 5.6% increase from the 1010 of 49 903 (2%) examinations in 2011-2012 (P < .001). Mean overall dose-length product was 689 mGy · cm (95% confidence interval: 667, 712), decreased from the mean of 746 mGy · cm observed in 2011-2012. Median facility dose-length product varied up to sevenfold, from less than 200 mGy · cm to greater than 1600 mGy · cm. Conclusion Use of reduced-radiation dose CT for evaluation of kidney stones has increased since 2011-2012, but remains low; variability of radiation dose according to facility continues to be wide. National mean CT radiation exposure for evaluation of renal colic during 2015-2016 decreased relative to 2011-2012 values, but remained well above what is reasonably achievable. ^© RSNA, 2017.

Emergency assessment of patients with acute abdominal pain using low-dose CT with iterative reconstruction: a comparative study

OBJECTIVES

To determine if radiation dose delivered by contrast-enhanced CT (CECT) for acute abdominal pain can be reduced to the dose administered in abdominal radiography (<2.5 mSv) using low-dose CT (LDCT) with iterative reconstruction algorithms.

METHODS

One hundred and fifty-one consecutive patients requiring CECT for acute abdominal pain were included, and their body mass index (BMI) was calculated. CECT was immediately followed by LDCT. LDCT series was processed using 1) 40% iterative reconstruction algorithm blended with filtered back projection (LDCT-IR-FBP) and 2) model-based iterative reconstruction algorithm (LDCT-MBIR). LDCT-IR-FBP and LDCT-MBIR images were reviewed independently by two board-certified radiologists (Raters 1 and 2).

RESULTS

Abdominal pathology was revealed on CECT in 120 (79%) patients. In those with BMI <30, accuracies for correct diagnosis by Rater 1 with LDCT-IR-FBP and LDCT-MBIR, when compared to CECT, were 95.4% (104/109) and 99% (108/109), respectively, and 92.7% (101/109) and 100% (109/109) for Rater 2. In patients with BMI ≥30, accuracies with LDCT-IR-FBP and LDCT-MBIR were 88.1% (37/42) and 90.5% (38/42) for Rater 1 and 78.6% (33/42) and 92.9% (39/42) for Rater 2.

CONCLUSIONS

The radiation dose delivered by CT to non-obese patients with acute abdominal pain can be safely reduced to levels close to standard radiography using LDCT-MBIR.

KEY POINTS

• LDCT-MBIR (<2.5 mSv) can be used to assess acute abdominal pain. • LDCT-MBIR (<2.5 mSv) cannot safely assess acute abdominal pain in obese patients. • LDCT-IR-FBP (<2.5 mSv) cannot safely assess patients with acute abdominal pain.

Iterative reconstruction: comparison of techniques for reduced-dose liver computed tomography following transarterial chemoembolization for hepatocellular carcinoma

Background Adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) algorithms have the potential to reduce dose while maintaining image quality. Purpose To compare computed tomography (CT) image quality and diagnostic performance among three reconstruction techniques - ASIR, MBIR, and filtered back projection (FBP) - after transcatheter arterial chemoembolization (TACE) of hepatocellular carcinomas (HCC). Material and Methods Of 60 patients that underwent initial TACE for HCCs, half underwent dynamic liver CT with conventional scanning protocol, and the other half with dose reduction to approximately 60% of conventional exposure. All images were reconstructed using three algorithms: FBP, ASIR, and MBIR. For objective analysis, image noise and signal-to-noise ratio (SNR) were compared. For subjective analysis, three radiologists independently assessed image quality. Ability to detect viable HCCs was also evaluated. Results MBIR and ASIR produced images with less noise and higher SNR compared with FBP regardless of radiation dosage ( P < 0.017). However, in terms of subjective parameters, such as image blotchiness, artifacts, and overall quality, MBIR was inferior to FBP and ASIR ( P < 0.001). Regarding diagnostic performance, there were no significant differences among reviewers in the detection of viable HCCs depending on the reconstruction algorithm, regardless of the dose reduction protocol ( P > 0.017). Conclusion Although subjective evaluations suggest that MBIR images are of lower quality compared with FBP and ASIR regardless of radiation dosage, there were no significant differences among reconstruction algorithms in diagnosis of viable HCC after TACE.

Image Quality Required for the Diagnosis of Skull Fractures Using Head CT: A Comparison of Conventional and Improved Reconstruction Kernels

BACKGROUND AND PURPOSE

Although skull fractures are generally assessed on bone images obtained by using head CT, the combined multikernel technique that enables evaluation of both brain and bone through a change in the window settings of an image set has been reported. The purpose of this retrospective study was to determine the image quality required for the accurate assessment of skull fractures by using head CT.

MATERIALS AND METHODS

A random sample of 50 patients (25 nonfracture and 25 simple nondisplaced skull fractures) was selected, and sets of conventional brain and bone images and improved combined multikernel images were reconstructed (4614 images). Three radiologists indicated their confidence levels regarding the presence of skull fractures by marking on a continuous scale for each image set. The mean area under the receiver operating characteristic curve was calculated for each kernel, and the statistical significance of differences was tested by using the Dorfman-Berbaum-Metz method.

RESULTS

Although a difference in the diagnostic performance of the 3 radiologists was suggested, the mean area under the curve value showed no significant differences among the 3 reconstruction kernels (P = .95 [bone versus combined]), P = .91 [bone versus brain]), and P = .88 [brain versus combined]). However, the quality of brain images was distinctly poorer than the quality of the other 2 images.

CONCLUSIONS

There was no significant difference in the diagnostic performance of brain, bone, and combined multikernel images for skull fractures. Skull fracture diagnosis is made possible by brain image assessments. Combined multikernel images offer the advantage of high-quality brain and bone images.

Optimizing z-axis coverage of abdominal CT scans of the urinary tract: a proposed alternative proximal landmark for acquisition planning

OBJECTIVE

To evaluate an alternative method to reduce the acquisition coverage of urinary tract CT.

METHODS

This retrospective study included 365 abdominopelvic CT studies. Three radiographers simulated shortened acquisition coverages using three methods to determine the upper limit of the acquisition: Method 1 used the renal contours; Method 2 used the inferior margin of the 10th thoracic vertebra; and Method 3 used the point of intersection of the left diaphragmatic dome and the anterior margin of the vertebral bodies. Reductions in acquisition coverage and number of CT scans with a portion of the kidney excluded from the simulated reduced acquisition were compared between the three methods.

RESULTS

The mean ± standard deviation reduction of acquisition coverage for the three readers with Methods 1, 2 and 3 were 20.5 ± 4.8, 15.1 ± 6.5 and 18.2 ± 5.3%, respectively. Compared with Method 2, Method 3 allowed a mean scan length reduction of 3.6%. The proportions of CT scans with a portion of the kidney excluded from the simulated reduced acquisition with Methods 1, 2 and 3 and averaged over the three readers were 6.7, 0.7 and 1.4%, respectively, with no significant difference between Methods 2 and 3. Interreader and intrareader agreements were excellent with all methods, but interclass correlation coefficients were higher with Method 3.

CONCLUSION

The method using the renal contours should not be used owing to its high proportion of kidneys with a portion excluded from the acquisition. Using the intersection of the left diaphragmatic dome and the anterior margin of the vertebral bodies for proximal landmark for urinary tract CT represents a new alternative method with a better reduction of scan length compared with the method using the inferior margin of T10 and with no significant increase in the number of kidneys with a portion excluded from the reduced acquisition. Advances in knowledge: A new method using the point of intersection of the left diaphragmatic dome and the anterior border of the vertebral bodies on the lateral scout radiograph is introduced to reduce the z-axis coverage of urinary tract CT scans.

Submillisievert CT using model-based iterative reconstruction with lung-specific setting: An initial phantom study

OBJECTIVE

To assess image quality of filtered back-projection (FBP) and model-based iterative reconstruction (MBIR) with a conventional setting and a new lung-specific setting on submillisievert CT.

METHODS

A lung phantom with artificial nodules was scanned with 10 mA at 120 kVp and 80 kVp (0.14 mSv and 0.05 mSv, respectively); images were reconstructed using FBP and MBIR with conventional setting (MBIR_Stnd) and lung-specific settings (MBIR_RP20/Tx and MBIR_RP20). Three observers subjectively scored overall image quality and image findings on a 5-point scale (1 = worst, 5 = best) compared with reference standard images (50 mA-FBP at 120, 100, 80 kVp). Image noise was measured objectively.

RESULTS

MBIR_RP20/Tx performed significantly better than MBIR_Stnd for overall image quality in 80-kVp images (p < 0.01), blurring of the border between lung and chest wall in 120p-kVp images (p < 0.05) and the ventral area of 80-kVp images (p < 0.001), and clarity of small vessels in the ventral area of 80-kVp images (p = 0.037). At 120 kVp, 10 mA-MBIR_RP20 and 10 mA-MBIR_RP20/Tx showed similar performance to 50 mA-FBP. MBIR_Stnd was better for noise reduction. Except for blurring in 120 kVp-MBIR_Stnd, MBIRs performed better than FBP.

CONCLUSION

Although a conventional setting was advantageous in noise reduction, a lung-specific setting can provide more appropriate image quality, even on submillisievert CT.

KEY POINTS

• Lung-specific submillisievert 10 mA-MBIR CT setting has similar performance to 50 mA-FBP • The new lung-specific settings improve vessel clarity and blurring of borders • The new settings may provide more appropriate images than conventional settings.

A pilot study using low-dose Spectral CT and ASIR (Adaptive Statistical Iterative Reconstruction) algorithm to diagnose solitary pulmonary nodules

BACKGROUND

Lung cancer is the most common cancer which has the highest mortality rate. With the development of computed tomography (CT) techniques, the case detection rates of solitary pulmonary nodules (SPN) has constantly increased and the diagnosis accuracy of SPN has remained a hot topic in clinical and imaging diagnosis. The aim of this study was to evaluate the combination of low-dose spectral CT and ASIR (Adaptive Statistical Iterative Reconstruction) algorithm in the diagnosis of solitary pulmonary nodules (SPN).

METHODS

62 patients with SPN (42 cases of benign SPN and 20 cases of malignant SPN, pathology confirmed) were scanned by spectral CT with a dual-phase contrast-enhanced method. The iodine and water concentration (IC and WC) of the lesion and the artery in the image that had the same density were measured by the GSI (Gemstone Spectral Imaging) software. The normalized iodine and water concentration (NIC and NWC) of the lesion and the normalized iodine and water concentration difference (ICD and WCD) between the arterial and venous phases (AP and VP) were also calculated. The spectral HU (Hounsfield Unit ) curve was divided into 3 sections based on the energy (40-70, 70-100 and 100-140 keV) and the slopes (λHU) in both phases were calculated. The ICAP, ICVP, WCAP and WCVP, NIC and NWC, and the λHU in benign and malignant SPN were compared by independent sample t-test.

RESULTS

The iodine related parameters (ICAP, ICVP, NICAP, NICVP, and the ICD) of malignant SPN were significantly higher than that of benign SPN (t = 3.310, 1.330, 2.388, 1.669 and 3.251, respectively, P <0.05). The 3 λHU values of venous phase in malignant SPN were higher than that of benign SPN (t = 3.803, 2.846 and 3.205, P <0.05). The difference of water related parameters (WCAP, WCVP, NWCAP, NWCVP and WCD) between malignant and benign SPN were not significant (t = 0.666, 0.257, 0.104, 0.550 and 0.585, P > 0.05).

CONCLUSIONS

The iodine related parameters and the slope of spectral curve are useful markers to distinguish the benign from the malignant lung diseases, and its application is extremely feasible in clinical applications.