Knowledge-based iterative model reconstruction (IMR) algorithm in ultralow-dose CT for evaluation of urolithiasis: evaluation of radiation dose reduction, image quality, and diagnostic performance

Detection of urinary tract stones on submillisievert abdominopelvic CT imaging with deep-learning image reconstruction algorithm (DLIR)

PURPOSE

Urolithiasis is a chronic condition that leads to repeated CT scans throughout the patient's life. The goal was to assess the diagnostic performance and image quality of submillisievert abdominopelvic computed tomography (CT) using deep learning-based image reconstruction (DLIR) in urolithiasis.

METHODS

57 patients with suspected urolithiasis underwent both non-contrast low-dose (LD) and ULD abdominopelvic CT. Raw image data of ULD CT were reconstructed using hybrid iterative reconstruction (ASIR-V 70%) and high-strength-level DLIR (DLIR-H). The performance of ULD CT for the detection of urinary stones was assessed by two readers and compared with LD CT with ASIR-V 70% as a reference standard. Image quality was assessed subjectively and objectively.

RESULTS

266 stones were detected in 38 patients. Mean effective dose was 0.59 mSv for ULD CT and 1.96 mSv for LD CT. For diagnostic performance, sensitivity and specificity were 89% and 94%, respectively, for ULDCT with DLIR-H. There was an almost perfect intra-observer concordance on ULD CT with DLIR-H versus LDCT with ASIR-V 70% (ICC = 0.90 and 0.90 for the two readers). Image noise was significantly lower and signal-to-noise ratio significantly higher with DLIR-H compared to ASIR-V 70%. Subjective image quality was also significantly better with ULDCT with DLIR-H.

CONCLUSION

ULD CT with Deep Learning Image Reconstruction maintains a good diagnostic performance in urolithiasis, with better image quality than hybrid iterative reconstruction and a significant radiation dose reduction.

Comparison of diagnostic accuracy of ultra low-dose computed tomography and X-ray of the kidneys, ureters and bladder for urolithiasis in the follow-up setting

INTRODUCTION

Urolithiasis is frequently followed up with a low-dose computed tomography of the kidneys ureters and bladder (LD-CTKUB) with doses typically less than 3 millisieverts. Although X-ray is a lower dose (0.5-1.1 mSv) alternative for follow up, it has lower diagnostic accuracy and is limited to radiopaque calculi. This study aims to compare the diagnostic accuracy of sub-millisievert ultra-low dose CT (ULD-CTKUB) against X-ray KUB for the follow up of urolithiasis when both are compared against the standard of care of a low-dose CT KUB (LD-CTKUB).

METHODS

This prospective study included patients with a known diagnosis of urolithiasis on prior CTKUB presenting for follow up. Each patient underwent a repeat reference LD-CTKUB, ULD-CTKUB and X-ray KUB. All imaging studies were interpreted by three readers. The radiation dose and quantitative noise was calculated for each CT. Both CT and X-ray were assessed for the presence, number and size of all calculi ≥2 mm.

RESULTS

A total of 58 patients were included in this study. LD-CTKUB identified 197 calculi. ULD-CTKUB in our study had a mean effective dose of 0.5 mSv compared to X-ray KUB where doses range in the literature from 0.5 to 1.1 mSv. Per-patient pooled analysis for intrarenal calculi when comparing ULD-CTKUB versus X-ray KUB against a reference LD-CTKUB found a sensitivity of 90% versus 67% (P < 0.01) and specificity of 93% versus 98% (P = 0.18) respectively. For ureteric calculi, the sensitivity was 67% versus 33% (P < 0.01) and specificity 94% versus 94% (P = 1.00) respectively. Per-stone pooled analysis detection rate was 79% for ULD-CTKUB versus 48% for X-ray (P < 0.01) when each was compared to the reference LD-CTKUB. Interobserver agreement was high for intrarenal calculi and moderate for ureteric calculi.

CONCLUSION

Sub-millisievert ULD-CTKUB had lower doses and higher sensitivity than X-ray in patients requiring follow up of known urolithiasis.

Dose Optimization Using a Deep Learning Tool in Various CT Protocols for Urolithiasis: A Physical Human Phantom Study

Background and Objectives: We attempted to determine the optimal radiation dose to maintain image quality using a deep learning application in a physical human phantom. Materials and Methods: Three 5 × 5 × 5 mm3 uric acid stones were placed in a physical human phantom in various locations. Three tube voltages (120, 100, and 80 kV) and four current-time products (100, 70, 30, and 15 mAs) were implemented in 12 scans. Each scan was reconstructed with filtered back projection (FBP), statistical iterative reconstruction (IR, iDose), and knowledge-based iterative model reconstruction (IMR). By applying deep learning to each image, we took 12 more scans. Objective image assessments were calculated using the standard deviation of the Hounsfield unit (HU). Subjective image assessments were performed by one radiologist and one urologist. Two radiologists assessed the subjective assessment and found the stone under the absence of information. We used this data to calculate the diagnostic accuracy. Results: Objective image noise was decreased after applying a deep learning tool in all images of FBP, iDose, and IMR. There was no statistical difference between iDose and deep learning-applied FBP images (10.1 ± 11.9, 9.5 ± 18.5 HU, p = 0.583, respectively). At a 100 kV-30 mAs setting, deep learning-applied FBP obtained a similar objective noise in approximately one third of the radiation doses compared to FBP. In radiation doses with settings lower than 100 kV-30 mAs, the subject image assessment (image quality, confidence level, and noise) showed deteriorated scores. Diagnostic accuracy was increased when the deep learning setting was lower than 100 kV-30 mAs, except for at 80 kV-15 mAs. Conclusions: At the setting of 100 kV-30 mAs or higher, deep learning-applied FBP did not differ in image quality compared to IR. At the setting of 100 kV-30 mAs, the radiation dose can decrease by about one third while maintaining objective noise.

Deep-Learning-Based Image Denoising in Imaging of Urolithiasis: Assessment of Image Quality and Comparison to State-of-the-Art Iterative Reconstructions

This study aimed to compare the image quality and diagnostic accuracy of deep-learning-based image denoising reconstructions (DLIDs) to established iterative reconstructed algorithms in low-dose computed tomography (LDCT) of patients with suspected urolithiasis. LDCTs (CTDIvol, 2 mGy) of 76 patients (age: 40.3 ± 5.2 years, M/W: 51/25) with suspected urolithiasis were retrospectively included. Filtered-back projection (FBP), hybrid iterative and model-based iterative reconstruction (HIR/MBIR, respectively) were reconstructed. FBP images were processed using a Food and Drug Administration (FDA)-approved DLID. ROIs were placed in renal parenchyma, fat, muscle and urinary bladder. Signal- and contrast-to-noise ratios (SNR/CNR, respectively) were calculated. Two radiologists evaluated image quality on five-point Likert scales and urinary stones. The results showed a progressive decrease in image noise from FBP, HIR and DLID to MBIR with significant differences between each method (p < 0.05). SNR and CNR were comparable between MBIR and DLID, while it was significantly lower in HIR followed by FBP (e.g., SNR: 1.5 ± 0.3; 1.4 ± 0.4; 1.0 ± 0.3; 0.7 ± 0.2, p < 0.05). Subjective analysis confirmed best image quality in MBIR, followed by DLID and HIR, both being superior to FBP (p < 0.05). Diagnostic accuracy for urinary stone detection was best using MBIR (0.94), lowest using FBP (0.84) and comparable between DLID (0.90) and HIR (0.90). Stone size measurements were consistent between all reconstructions and showed excellent correlation (r2 = 0.958-0.975). In conclusion, MBIR yielded the highest image quality and diagnostic accuracy, with DLID producing better results than HIR and FBP in image quality and matching HIR in diagnostic precision.

Evaluation of Ultra-Low-Dose Chest Computed Tomography Images in Detecting Lung Lesions Related to COVID-19: A Prospective Study

Background

The present study aimed to evaluate the effectiveness of ultra-low-dose (ULD) chest computed tomography (CT) in comparison with the routine dose (RD) CT images in detecting lung lesions related to COVID-19.

Methods

A prospective study was conducted during April-September 2020 at Shahid Faghihi Hospital affiliated with Shiraz University of Medical Sciences, Shiraz, Iran. In total, 273 volunteers with suspected COVID-19 participated in the study and successively underwent RD-CT and ULD-CT chest scans. Two expert radiologists qualitatively evaluated the images. Dose assessment was performed by determining volume CT dose index, dose length product, and size-specific dose estimate. Data analysis was performed using a ranking test and kappa coefficient (κ). P<0.05 was considered statistically significant.

Results

Lung lesions could be detected with both RD-CT and ULD-CT images in patients with suspected or confirmed COVID-19 (κ=1.0, P=0.016). The estimated effective dose for the RD-CT protocol was 22-fold higher than in the ULD-CT protocol. In the case of the ULD-CT protocol, sensitivity, specificity, accuracy, and positive predictive value for the detection of consolidation were 60%, 83%, 80%, and 20%, respectively. Comparably, in the case of RD-CT, these percentages for the detection of ground-glass opacity (GGO) were 62%, 66%, 66%, and 18%, respectively. Assuming the result of real-time polymerase chain reaction as true-positive, analysis of the receiver-operating characteristic curve for GGO detected using the ULD-CT protocol showed a maximum area under the curve of 0.78.

Conclusion

ULD-CT, with 94% dose reduction, can be an alternative to RD-CT to detect lung lesions for COVID-19 diagnosis and follow-up.An earlier preliminary report of a similar work with a lower sample size was submitted to the arXive as a preprint. The preprint is cited as: https://arxiv.org/abs/2005.03347.

Advances in deep learning for computed tomography denoising

Computed tomography (CT) has seen a rapid increase in use in recent years. Radiation from CT accounts for a significant proportion of total medical radiation. However, given the known harmful impact of radiation exposure to the human body, the excessive use of CT in medical environments raises concerns. Concerns over increasing CT use and its associated radiation burden have prompted efforts to reduce radiation dose during the procedure. Therefore, low-dose CT has attracted major attention in the radiology, since CT-associated x-ray radiation carries health risks for patients. The reduction of the CT radiation dose, however, compromises the signal-to-noise ratio, which affects image quality and diagnostic performance. Therefore, several denoising methods have been developed and applied to image processing technologies with the goal of reducing image noise. Recently, deep learning applications that improve image quality by reducing the noise and artifacts have become commercially available for diagnostic imaging. Deep learning image reconstruction shows great potential as an advanced reconstruction method to improve the quality of clinical CT images. These improvements can provide significant benefit to patients regardless of their disease, and further advances are expected in the near future.

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.

Improved visualization of a fine intrahepatic biliary duct on drip infusion cholangiography-computed tomography: Impact of knowledge-based iterative model reconstruction

AIM

The purpose of this study was to investigate the visualization of fine biliary ducts with knowledge-based iterative model reconstruction (IMR) in low-dose drip infusion computed tomography (CT) cholangiography (DIC-CT) as compared with filtered back projection (FBP) and hybrid iterative reconstruction (iDose⁴ ).

METHODS

A total of 38 patients underwent DIC-CT for living donor liver transplantation. CT was performed approximately 20 min after the end of the infusion of meglumine iotroxate (100 mL). Images were reconstructed using FBP, iDose⁴ , and IMR, and 1-mm slice images at fixed window level and width were prepared for assessment. Two reviewers independently evaluated the quality of visualization of the fine biliary ducts of the caudate lobe (B1) using a 5-point scale. The visualization scores of three reconstructed images were compared using the Kruskal-Wallis test and Mann-Whitney U-test.

RESULTS

For reviewer 1, the visualization score of IMR was significantly higher than that of FBP (P = 0.012), and tended to be higher than that of iDose⁴ (P = 0.078). For reviewer 2, the visualization score of IMR was significantly higher than those of both FBP and iDose⁴ (P < 0.01).

CONCLUSIONS

IMR showed better visualization of B1 on DIC-CT than FBP or iDose⁴ . DIC-CT reconstructed with IMR may be useful to the anatomical grasp of biliary tracts in cases of hepatectomy.

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

PURPOSE

We aimed to evaluate the quality of chest computed tomography (CT) images obtained with low-dose CT using three iterative reconstruction (IR) algorithms.

METHODS

Two 64-detector spiral CT scanners (HDCT and iCT) were used to scan a chest phantom containing 6 ground-glass nodules (GGNs) at 11 radiation dose levels. CT images were reconstructed by filtered back projection or three IR algorithms. Reconstructed images were analyzed for CT values, average noise, contrast-to-noise ratio (CNR) values, subjective image noise, and diagnostic acceptability of the GGNs. Repeated-measures analysis of variance was used for statistical analyses.

RESULTS

Average noise decreased and CNR increased with increasing radiation dose when the same reconstruction algorithm was applied. Average image noise was significantly lower when reconstructed with MBIR than with iDOSE4 at the same low radiation doses. The two radiologists showed good interobserver consistency in image quality with kappa 0.83. A significant relationship was found between image noise and diagnostic acceptability of the GGNs.

CONCLUSION

Three IR algorithms are able to reduce the image noise and improve the image quality of low-dose CT. In the same radiation dose, the low-dose CT image quality reconstructed with MBIR algorithms is better than that of other IR algorithms.

Very low-dose computerized tomography for confirmation of urinary stone presence

PURPOSE

To determine whether a modified non-contrast very low-dose computed tomography (VLD-CT) protocol is applicable for confirmation of known urolithiasis.

METHODS AND MATERIALS

Consecutive adult patients with a CT scan showing urinary tract stone(s) between 6/2017-12/2018 were included. They were referred to a modified VLD-CT protocol if stone presence was equivocal or if stone location needed reassessment before an endourological interventional procedure. The scanned area was limited to the level of initial stone location caudally. Data on patients' demographics andbody mass index, were collected. The scanned length and radiation dose were calculated. Images were reviewed by two radiologists who assessed stone size and location. Follow-up reference standard included stone passage, surgical removal, and other imaging and clinical information.

RESULTS

Sixty-three patients [63 stones, mean BMI 28.7 (range 19-41.9)] were included. VLD-CTs revealed 31 stones in 31 patients, with a mean stone length of 5.5 mm. Fifteen stones remained at the same location, and 16 had migrated, of which two appeared in the bladder. Thirty-two stones were not observed on VLD-CT. The mean span scanned on the VLD-CT was 274 mm (± 80). The average radiation exposure was 1.47 mGy (range 1.09-3.3), and the absorbed dose was 0.77 mSv (range 0.39-1.43), compared to 10.24 mGy (range 1.75-28.9) and 7.87 mSv (range 1.44-18.5) in the previous scan. The mean radiation dose reduction between scans was 89%. On follow-up, all VLD-CT findings were confirmed.

CONCLUSION

A modified imaging protocol is applicable for confirmation of stone presence and location by utilizing very low-dose radiation exposure.

Coronary computed tomography angiography using model-based iterative reconstruction algorithms in the detection of significant coronary stenosis: how the plaque type influences the diagnostic performance

Purpose

To evaluate the ability of coronary computed tomography angiography (CCTA) with model-based iterative reconstruction (MBIR) algorithm in detecting significant coronary artery stenosis compared with invasive coronary angiography (ICA).

Material and methods

We retrospectively identified 55 patients who underwent CCTA using the MBIR algorithm with evidence of at least one significant stenosis (≥ 50%) and an ICA within three months. Patients were stratified based on calcium score; stenoses were classified by type and by coronary segment involved. Dose-length-product was compared with the literature data obtained with previous reconstruction algorithms. Coronary artery stenosis was estimated on ICAs based on a qualitative method.

Results

CCTA data were confirmed by ICA in 89% of subjects, and in 73% and 94% of patients with CS < 400 and ≥ 400, respectively. ICA confirmed 81% of calcific stenoses, 91% of mixed, and 67% of soft plaques. Both the dose exposure of patients with prospective acquisition (34) and the exposure of the whole population were significantly lower than the standard of reference (p < 0.001 and p = 0.007).

Conclusions

CCTA with MBIR is valuable in detecting significant coronary artery stenosis with a solid reduction of radiation dose. Diagnostic performance was influenced by plaque composition, being lower compared with ICA for patients with lower CAC score and soft plaques; the visualisation of an intraluminal hypodensity could cause false positives, particularly in D1 and MO segments.

Diagnosis of urine leakage after bladder repair: a prospective comparative study of ultra-low-dose CT cystography and conventional retrograde cystography

PURPOSE

We performed this prospective cohort study to compare the accuracy and technical characteristics of ultra-low-dose CT cystography with those of conventional retrograde cystography.

MATERIALS AND METHODS

A cohort of 31 patients referred for cystography after bladder repair were enrolled. To detect urine leakage, we initially performed conventional cystography after retrograde distention of the bladder with dilute iodinated contrast material, followed by ultra-low-dose CT cystography. The diagnostic accuracy of these two modalities was compared, and the technical characteristics of ultra-low-dose CT cystography were examined.

RESULTS

All 31 referred patients were included in this study. Of the 31 patients, 27 (87.1%) underwent bladder repair after radical prostatectomy, 3 (9.7%) after radical cystectomy, and 1 (3.2%) after bladder diverticulectomy. Four of the 31 patients were diagnosed with urine leakage by conventional cystography. These four patients were confirmed to have urine leakage by ultra-low-dose CT cystography. Another five patients who did not have urine leakage according to conventional cystography were diagnosed with urine leakage by ultra-low-dose CT cystography. Moreover, performing ultra-low-dose CT cystography enabled us to identify the precise location and amount of urine leakage in all nine patients. Based on these findings, we were able to establish a proper treatment plan.

CONCLUSIONS

Ultra-low-dose CT cystography is an accurate method for evaluating urine leakage after bladder repair, and this technique may help determine the most appropriate treatment strategy for patients with urine leakage after bladder repair.

Evaluation of the Impact of Iterative Reconstruction Algorithms on Computed Tomography Texture Features of the Liver Parenchyma Using the Filtration-Histogram Method

OBJECTIVE

To evaluate whether computed tomography (CT) reconstruction algorithms affect the CT texture features of the liver parenchyma.

MATERIALS AND METHODS

This retrospective study comprised 58 patients (normal liver, n = 34; chronic liver disease [CLD], n = 24) who underwent liver CT scans using a single CT scanner. All CT images were reconstructed using filtered back projection (FBP), hybrid iterative reconstruction (IR) (iDOSE⁴), and model-based IR (IMR). On arterial phase (AP) and portal venous phase (PVP) CT imaging, quantitative texture analysis of the liver parenchyma using a single-slice region of interest was performed at the level of the hepatic hilum using a filtration-histogram statistic-based method with different filter values. Texture features were compared among the three reconstruction methods and between normal livers and those from CLD patients. Additionally, we evaluated the inter- and intra-observer reliability of the CT texture analysis by calculating intraclass correlation coefficients (ICCs).

RESULTS

IR techniques affect various CT texture features of the liver parenchyma. In particular, model-based IR frequently showed significant differences compared to FBP or hybrid IR on both AP and PVP CT imaging. Significant variation in entropy was observed between the three reconstruction algorithms on PVP imaging (p < 0.05). Comparison between normal livers and those from CLD patients revealed that AP images depend more strongly on the reconstruction method used than PVP images. For both inter- and intra-observer reliability, ICCs were acceptable (> 0.75) for CT imaging without filtration.

CONCLUSION

CT texture features of the liver parenchyma evaluated using the filtration-histogram method were significantly affected by the CT reconstruction algorithm used.

Low-dose computed tomography of urolithiasis in obese patients: a feasibility study to evaluate image reconstruction algorithms

Purpose: Retrospective evaluation and comparison of image quality generated by low-dose computed tomography (LDCT) from obese patients with urolithiasis using alternative reconstruction algorithms. Materials and methods: Twenty-five obese patients (body mass index [BMI]>25 kg/m²) underwent LDCT scans for suspected urolithiasis. The scans were recompiled using filtered-back projection (FBP), statistical iterative reconstruction (iDose) and iterative model-based reconstruction (IMR). Dose-length product (DLP) and patient details were obtained from the CT dose report and clinical charts, respectively. Objective image noise was assessed by measuring the SD of Hounsfield units (HUs) in defined locations. Additionally, subjective image evaluation was independently performed by two radiologists using a 3-point Likert scale. The inter-reviewer agreement of image quality was calculated. Results: Ureteral concretions were observed in all CT scans, two of which revealed bilateral stones. The assessed patients' mean BMI was 29.29±3.74 kg/m², and the DLP of the CT scans was 100.04±10.00 mGy*cm. All scans were rated diagnostic with the iDose and iterative model-based reconstructions, whereas 41% of the scans performed with FBP reconstruction were nondiagnostic. With respect to image quality, IMR was superior to iDose and FBP, both in the objective (P<0.001) and overall subjective (P≤0.008) evaluation of the respective data sets. The inter-reviewer agreement for overall image quality was "almost perfect" for IMR, "substantial" for iDose and "moderate" for FBP (κ values of 1.0, 0.6 and 0.46, respectively). Conclusion: Using iterative image reconstruction algorithms, LDCT of urolithiasis is feasible in overweight patients with a BMI between 25 and 35 kg/m². Due to higher image quality, IMR is the preferred algorithm for scan reconstruction as it may help to avoid repeated examinations due to initial nondiagnostic scans.

Comparison of image noise and image quality between full-dose abdominal computed tomography scans reconstructed with weighted filtered back projection and half-dose scans reconstructed with improved sinogram-affirmed iterative reconstruction (SAFIRE*)

PURPOSE

To retrospectively compare the image noise, signal-to-noise ratio (SNR), and subjective image quality between CT images acquired with a dual-source, split-dose imaging protocol reconstructed at full and half doses with weighted filtered back projection (wFBP) and an improved sinogram-affirmed iterative reconstruction algorithm (SAFIRE*).

METHODS

Fifty-three consecutive patients underwent contrast-enhanced CT of the abdomen using a standardized dual-source, single energy CT protocol. Half-dose images were retrospectively generated using data from one detector only. Full-dose datasets were reconstructed with wFBP, while half-dose datasets were reconstructed with wFBP and SAFIRE* strengths 1-5. Region of interest analysis was performed to assess SNR and noise. Diagnostic acceptability, subjective noise, and spatial resolution were graded on a 10-point scale by two readers. Statistical analysis was carried out with repeated measures analysis of variance, Wilcoxon signed rank test, and Cohen's κ test.

RESULTS

With the increasing strengths of SAFIRE*, a progressive reduction in noise and increase in SNR (p < 0.01) was observed. There was a statistically significant decrease in objective noise and increase in SNR in half-dose SAFIRE* strength 4 and 5 reconstructions compared to full-dose reconstructions using wFBP (p < 0.01). Qualitative analysis revealed a progressive increase in diagnostic acceptability, decrease in subjective noise and increase in spatial resolution for half-dose images reconstructed with the increasing strengths of SAFIRE* (p < 0.01).

CONCLUSIONS

Half-dose CT images reconstructed with SAFIRE* at strength 4 and 5 have superior image quality compared to full-dose images reconstructed with wFBP. SAFIRE* potentially allows dose reductions in the order of 50% over wFBP.

Contrast-Enhanced CT with Knowledge-Based Iterative Model Reconstruction for the Evaluation of Parotid Gland Tumors: A Feasibility Study

Objective

The purpose of this study was to determine the diagnostic utility of low-dose CT with knowledge-based iterative model reconstruction (IMR) for the evaluation of parotid gland tumors.

Materials and Methods

This prospective study included 42 consecutive patients who had undergone low-dose contrast-enhanced CT for the evaluation of suspected parotid gland tumors. Prior or subsequent non-low-dose CT scans within 12 months were available in 10 of the participants. Background noise (BN), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared between non-low-dose CT images and images generated using filtered back projection (FBP), hybrid iterative reconstruction (iDose⁴; Philips Healthcare), and knowledge-based IMR. Subjective image quality was rated by two radiologists using five-point grading scales to assess the overall image quality, delineation of lesion contour, image sharpness, and noise.

Results

With the IMR algorithm, background noise (IMR, 4.24 ± 3.77; iDose⁴, 8.77 ± 3.85; FBP, 11.73 ± 4.06; p = 0.037 [IMR vs. iDose⁴] and p < 0.001 [IMR vs. FBP]) was significantly lower and SNR (IMR, 23.93 ± 7.49; iDose⁴, 10.20 ± 3.29; FBP, 7.33 ± 2.03; p = 0.011 [IMR vs. iDose⁴] and p < 0.001 [IMR vs. FBP]) was significantly higher compared with the other two algorithms. The CNR was also significantly higher with the IMR compared with the FBP (25.76 ± 11.88 vs. 9.02 ± 3.18, p < 0.001). There was no significant difference in BN, SNR, and CNR between low-dose CT with the IMR algorithm and non-low-dose CT. Subjective image analysis revealed that IMR-generated low-dose CT images showed significantly better overall image quality and delineation of lesion contour with lesser noise, compared with those generated using FBP by both reviewers 1 and 2 (4 vs. 3; 4 vs. 3; and 3–4 vs. 2; p < 0.05 for all pairs), although there was no significant difference in subjective image quality scores between IMR-generated low-dose CT and non-low-dose CT images.

Conclusion

Iterative model reconstruction-generated low-dose CT is an alternative to standard non-low-dose CT without significantly affecting image quality for the evaluation of parotid gland tumors.

Low-Dose Unenhanced Computed Tomography with Iterative Reconstruction for Diagnosis of Ureter Stones

PURPOSE

To study the clinical application of low-dose unenhanced computed tomography with iterative reconstruction technique (LDCT-IR) on renal colic in the emergency department.

MATERIALS AND METHODS

We conducted a prospective, single-blinded, randomized, and non-inferiority study. From March 2014 to August 2015, 112 patients with renal colic were included, and were randomized to either LDCT-IR (n=46) or standard-dose unenhanced CT (SDCT) (n=66) groups. The accuracy of urolithiasis diagnosis was the primary endpoint of this study. Radiation dose, size and location of the stone, hydronephrosis, other diseases except urolithiasis, and results of treatment were analyzed between the two groups.

RESULTS

The average effective dose radiation of SDCT was approximately four times higher than that of LDCT-IR (6.52 mSv vs. 1.63 mSv, p<0.001). There was no significant difference in the accuracy of ureteral stone diagnosis between the two groups (LDCT-IR group: 96.97% vs. SDCT group: 98.96%, p=0.392). No significant difference was observed regarding the size and location of a stone, hydronephrosis, and diagnosis of other diseases, except urolithiasis. False negative results were found in two LDCT-IR patients and in one SDCT patient. In these patients, stones were misread as vascular calcification, and were difficult to diagnose because evidence of hydronephrosis and ureteral dilatation was not found.

CONCLUSION

LDCT-IR, as a first-line imaging test, was non-inferior to SDCT with respect to diagnosis of ureter stones, and was clinically available for the evaluation of renal colic.

High-pitch low-dose abdominopelvic CT with tin-filtration technique for detecting urinary stones

OBJECTIVES

To evaluate urinary stone detection, radiation exposure, image quality, breathing-motion artifacts, and scanning time with high-pitch tin filter-based abdominopelvic CT.

METHODS

Sixty-three consecutive patients with urolithiasis underwent non-enhanced abdominopelvic CT with both regular (120 kV, pitch 0.6) and low-dose (Sn150kV, pitch 3.0) protocols on a third-generation dual-source CT. Stone characteristics, image noise (SD), signal-to-noise ratio (SNR), subjective image quality on a 5-point likert scale breathing-motion artifacts, and scanning time were evaluated. Volume CT dose index (CTDIvol), dose-length product (DLP), effective dose (ED) were compared.

RESULTS

A total of 157 urinary stones were detected by regular protocol; 154 were correctly identified by low-dose protocol with an overall detection rate of 98.1%. No significant differences were observed in SD, SNR, or subjective image quality between two protocols (P > 0.05). Compared to regular protocol, CTDIvol and ED were 56.6% (7.19 vs. 3.12 mGy, P < 0.001) and 55.6% (5.25 vs. 2.33 mSv, P < 0.001) lower; scanning time was 89.5% (7.9 vs. 0.83, P < 0.001) shorter; and breathing-motion artifacts were fewer (8 vs. 0 patients) with low-dose protocol.

CONCLUSIONS

High-pitch abdominopelvic CT with Sn150kV substantially reduced radiation exposure and scanning time, while maintained stone detection and image quality and prevented breathing-motion artifacts.

Use of Model-based Iterative Reconstruction to Improve Detection of Congenital Cardiovascular Anomalies in Infants Undergoing Free-breathing Computed Tomographic Angiography

PURPOSE

The aim of the study was to assess the detection of congenital cardiovascular anomalies (congenital heart disease) in neonates and infants using model-based iterative reconstruction (MBIR) algorithm compared with hybrid iterative reconstruction (HIR) and filtered back projection (FBP) reconstructions on axial computed tomography (CT) performed at minimum scanner dose.

MATERIALS AND METHODS

Over 1 year, all CT angiographies performed in infants below 3 months of age with congenital heart disease were assessed retrospectively. All were scanned on a 256-slice CT (Brilliance iCT) using single axial rotation at minimum allowable scanner dose (80 kV/10 mAs), with patients free-breathing. Intravenous contrast was 1 mL/kg. Scan reconstruction was 0.9 mm/0.45 mm overlap, reconstructed with FBP, HIR (iDose5), and MBIR (IMR2). The 3 reconstructions per study were anonymized and randomized. Four cardiac radiologists (23, 9, 7, and 6 y experience) evaluated each reconstruction on a workstation for presence of an atrial septal defect, a ventricular septal defect, patent ductus arteriosus, and surgical shunt or anomalies of the aorta, pulmonary arteries, and pulmonary veins. Unevaluable structures were classified as nondiagnostic. Gold standard was surgery or both echocardiogram and cardiac catheterization. The sensitivity, specificity, and accuracy were determined for each reconstruction.

RESULTS

Fifteen scans in 14 infants met the inclusion criteria, with a total of 48 anomalies. Pooled sensitivity for MBIR of 0.82 (range, 0.75 to 0.9) was significantly better than those for FBP (0.58; range, 0.54 to 0.6; P<0.001) and HIR (0.67; range, 0.60 to 0.79; P<0.001). Pooled accuracy of MBIR, HIR, and FBP was 0.91, 0.84, and 0.81, respectively. Readers deemed 39 and 15 structures nondiagnostic with FBP and HIR, respectively, versus 2 with MBIR (MBIR-FBP, MBIR-HIR, P<0.0001). The CTDIvol, DLP, and estimated dose for all cases was 0.52 mGy, 4.2 mGy×cm, and 0.16 mSv.

CONCLUSIONS

MBIR significantly improves the detection of congenital anomalies in neonates and infants undergoing CT angiography at minimum allowable dose.

Imaging in the diagnosis of pediatric urolithiasis

Pediatric urolithiasis is an important and increasingly prevalent cause of pediatric morbidity and hospital admission. Ultrasound (US) is the recommended primary imaging modality for suspected urolithiasis in children. There is, however, widespread use of CT as a first-line study for abdominal pain in many institutions involved in pediatric care. The objective of this review is to outline state-of-the-art imaging modalities and methods for diagnosing urolithiasis in children. The pediatric radiologist plays a key role in ensuring that the appropriate imaging modality is performed in the setting of suspected pediatric urolithiasis. Our proposed imaging algorithm starts with US, and describes the optimal technique and indications for the use of CT. We emphasize the importance of improved communication with a greater collaborative approach between pediatric and general radiology departments so children undergo the appropriate imaging evaluation.

Comparison of image quality from filtered back projection, statistical iterative reconstruction, and model-based iterative reconstruction algorithms in abdominal computed tomography

The purpose of this study was to compare the image noise-reducing abilities of iterative model reconstruction (IMR) with those of traditional filtered back projection (FBP) and statistical iterative reconstruction (IR) in abdominal computed tomography (CT) imagesThis institutional review board-approved retrospective study enrolled 103 patients; informed consent was waived. Urinary bladder (n = 83) and renal cysts (n = 44) were used as targets for evaluating imaging quality. Raw data were retrospectively reconstructed using FBP, statistical IR, and IMR. Objective image noise and signal-to-noise ratio (SNR) were calculated and analyzed using one-way analysis of variance. Subjective image quality was evaluated and analyzed using Wilcoxon signed-rank test with Bonferroni correction.Objective analysis revealed a reduction in image noise for statistical IR compared with that for FBP, with no significant differences in SNR. In the urinary bladder group, IMR achieved up to 53.7% noise reduction, demonstrating a superior performance to that of statistical IR. IMR also yielded a significantly superior SNR to that of statistical IR. Similar results were obtained in the cyst group. Subjective analysis revealed reduced image noise for IMR, without inferior margin delineation or diagnostic confidence.IMR reduced noise and increased SNR to greater degrees than did FBP and statistical IR. Applying the IMR technique to abdominal CT imaging has potential for reducing the radiation dose without sacrificing imaging quality.

Determination of optimal imaging settings for urolithiasis CT using filtered back projection (FBP), statistical iterative reconstruction (IR) and knowledge-based iterative model reconstruction (IMR): a physical human phantom study

OBJECTIVE

The purpose of this study was to compare CT image quality for evaluating urolithiasis using filtered back projection (FBP), statistical iterative reconstruction (IR) and knowledge-based iterative model reconstruction (IMR) according to various scan parameters and radiation doses.

METHODS

A 5 × 5 × 5 mm(3) uric acid stone was placed in a physical human phantom at the level of the pelvis. 3 tube voltages (120, 100 and 80 kV) and 4 current-time products (100, 70, 30 and 15 mAs) were implemented in 12 scans. Each scan was reconstructed with FBP, statistical IR (Levels 5-7) and knowledge-based IMR (soft-tissue Levels 1-3). The radiation dose, objective image quality and signal-to-noise ratio (SNR) were evaluated, and subjective assessments were performed.

RESULTS

The effective doses ranged from 0.095 to 2.621 mSv. Knowledge-based IMR showed better objective image noise and SNR than did FBP and statistical IR. The subjective image noise of FBP was worse than that of statistical IR and knowledge-based IMR. The subjective assessment scores deteriorated after a break point of 100 kV and 30 mAs.

CONCLUSION

At the setting of 100 kV and 30 mAs, the radiation dose can be decreased by approximately 84% while keeping the subjective image assessment.

ADVANCES IN KNOWLEDGE

Patients with urolithiasis can be evaluated with ultralow-dose non-enhanced CT using a knowledge-based IMR algorithm at a substantially reduced radiation dose with the imaging quality preserved, thereby minimizing the risks of radiation exposure while providing clinically relevant diagnostic benefits for patients.