Impact of deep learning-based image reconstruction on image quality compared with adaptive statistical iterative reconstruction-Veo in renal and adrenal computed tomography.

OBJECTIVE: To evaluate image quality of deep learning-based image reconstruction (DLIR) in contrast-enhanced renal and adrenal computed tomography (CT) compared with adaptive statistical iterative reconstruction-Veo (ASiR-V). METHODS: We prospectively recruited 52 patients. All images were reconstructed with ASiR-V 30%, ASiR-V 70%, and DLIR at low, medium, and high reconstruction strengths. CT number, noise, noise reduction rate, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured and calculated within the region of interest (ROI) on subcutaneous fat, bilateral renal cortices, renal medulla, renal arteries, and adrenal glands. For qualitative analyses, the differentiation of the renal cortex and medulla, conspicuity of the adrenal gland boundary, sharpness, artifacts, and subjective noise were assessed. The overall image quality was calculated on a scale from 0 (worst) to 15 (best) based on the five values above and the score≥9 was acceptable. RESULTS: CT number does not significantly differ between the reconstruction datasets. Noise does not significantly differ between ASiR-V 30% and DLIR-L, but it is significantly lower using ASiR-V 70%, DLIR-M, and DLIR-H. The noise reduction rate relative to ASiR-V 30% is significantly different between the DLIR groups and ASiR-V 70%, and DLIR-H yields the highest noise reduction rate (61.6%). SNR and CNR are higher for DLIR-M, DLIR-H, and ASiR-V 70% than for ASiR-V 30% and DLIR-L. DLIR-H shows the best SNR and CNR. The overall image quality yields the same pattern for DLIR-H, with the highest score. Percentages of cases with overall image quality score≥9 are 100% (DLIR-H), 94.23% (DLIR-M), 90.38% (ASiR-V70%), 67.31% (DLIR-L), and 63.46% (ASiR-V30%), respectively. CONCLUSIONS: DLIR significantly improved the objective and subjective image quality of renal and adrenal CTs, yielding superior noise reduction compared with ASiR-V.

Inter-rater reliability in the radiological classification of renal injuries.

INTRODUCTION: Although many radiologists invoke the surgical classification of renal injury proposed by the American Association for Surgery in Trauma (AAST), there has been only limited work on the role of the AAST system as an imaging stratification. The aim was to determine the inter-rater reliability (IRR) amongst radiologists and urologists using the AAST system. METHODS: A 1-year retrospective study of consecutive patients with computed tomography (CT) evidence of renal trauma managed at a Level 1 trauma center. Three radiologists and three urologists independently stratified the presentation CT findings according to the AAST renal trauma classification. Agreement between independent raters and mutually exclusive groups was determined utilizing weighted kappa coefficients. RESULTS: One hundred and one patients were included. Individual inter-observer agreements ranged from 54/101 (53.4%) to 62/101 (61.4%), with corresponding weighted kappa values from 0.61 to 0.69, constituting substantial agreement. Urologists achieved intra-disciplinary agreement in 49 cases (48.5%) and radiologists in 36 cases (35.6%). Six-reader agreement was achieved in 24 cases (23.7%). The AAST grade I injuries had the highest level of agreement, overall. CONCLUSION: The finding of substantial IRR amongst radiologists and urologists utilizing the AAST system supports continued use of the broad parameters of the AAST system, with some modification in specific categories with lower agreement.

Multiplanar Reformations in the Measurement of Renal Length on CT: Is It Plain Which Plane to Use?

OBJECTIVE: The objective of this study was to determine the accuracy of renal measurement on CT in multiple imaging planes. MATERIALS AND METHODS: In this study, three board-certified radiologists retrospectively measured 110 kidneys on CT in 55 consecutive patients. Five measurement methods were used: axial, coronal single image, coronal multiimage, sagittal single image, and sagittal multiimage. The coronal database was sent to a postprocessing workstation, and each radiologist performed a maximum renal measurement using a best off-axis plane that was our reference standard. An ANOVA test with repeated measures and posthoc Bonferroni corrected t tests were performed. RESULTS: The mean differences (± standard error) compared with the reference standard method were as follows: axial, 7.7 ± 0.7 mm; coronal single image, 13.1 ± 1.4 mm; coronal multiimage, 6.4 ± 0.8 mm; sagittal single image, 6.4 ± 0.6 mm; and sagittal multiimage, 2.8 ± 0.3 mm. The reference standard measurement was larger (p < 0.001), whereas the coronal single-image measurement (p ≤ 0.006) was smaller than all other methods. The sagittal multiimage (p ≤ 0.005) was statistically significantly different from all other methods. There were no statistically significant differences among the axial, coronal multiimage, and sagittal single-image methods (p ≥ 0.088). CONCLUSION: The single-image coronal method is the least accurate, with an error of approximately 13 mm. The axial, multiimage coronal, and single-image sagittal methods underestimate renal size by approximately 6-8 mm. Multiimage sagittal is the most accurate method for measuring kidneys with an error of approximately 3 mm.

Renal Masses With Equivocal Enhancement at CT: Characterization With Contrast-Enhanced Ultrasound.

OBJECTIVE: The purpose of this article is to retrospectively investigate in two radiology centers the role of contrast-enhanced ultrasound in the characterization of renal masses with equivocal enhancement at CT (i.e., with a density increase of 10-20 HU between unenhanced and contrast-enhanced scans) not characterized with conventional ultrasound modes. MATERIALS AND METHODS: Forty-seven renal lesions (range, 0.8-7.7 cm; average, 2.6 cm) with equivocal enhancement at CT underwent contrast-enhanced ultrasound using sulfur hexafluoride-filled microbubbles. Examinations were digitally recorded for retrospective blinded evaluation by two radiologists with 20 and 10 years' experience in urologic imaging. Histologic results were available for 30 of 47 (64%) lesions (25 primary malignant tumors, two metastases, and three primary benign lesions). Two lesions increased in size and complexity during the follow-up and were considered malignant. One Bosniak category III and 14 category IIF cysts were stable after a follow-up of at least 3 years and were considered benign. ROC curve analysis was used to assess the capability of contrast-enhanced ultrasound to differentiate benign from malignant lesions. RESULTS: Twelve likely complex cystic lesions at gray-scale ultrasound were cystic also on contrast-enhanced ultrasound and reference procedures. Eleven of 34 lesions that appeared solid at gray-scale ultrasound were cystic on contrast-enhanced ultrasound and reference procedures. One lesion considered likely solid by one radiologist and possibly cystic by the other was a solid tumor at contrast-enhanced ultrasound and histologic analysis. The diagnostic performance of contrast-enhanced ultrasound to characterize the lesions as benign or malignant was high for both readers (AUC, 0.958 and 0.966, respectively). CONCLUSION: Contrast-enhanced ultrasound is effective for characterizing renal lesions presenting with equivocal enhancement at CT.

A Multicentric Audit to Reevaluate the Guidelines Adherence in Computed Tomography of Kidneys, Ureters, and Bladder (CT-KUB) X-ray Imaging in Jordan.

Background With the increasing use of imaging techniques involving ionizing radiation, the area of the body scanned should be restricted to what is required to answer the clinical question. Therefore, this is a retrospective audit that intends to evaluate the presence of overscanning in renal computed tomography (CT) scan images during the process of evaluation for urinary symptoms. Objective This study aims to reduce the unnecessary scan length and exposure to radiation in patients who undergo CT scans for urinary symptoms. Materials and Methods In two months duration, patients from different clinics underwent CT imaging, and the resulting radiographic images were collected and analyzed. Overscanning was defined to be more than 10% of the total scan. Subsequently, the total length of the CT scan was measured which is used to measure the unnecessary overscan above the highest kidney margin as a percentage of the total length. Results Out of the 88 patients who were evaluated, 100% did not meet the guidelines for renal CT imaging and were exposed to a high radiation dose. However, the minimum percentage of overscanned patients was 20-40%. Conclusion A significant number of scans demonstrated surplus overscanning above the highest kidney. Therefore, recognizing the suitable anatomical landmarks for scanning and establishing a follow-up audit are suggested measures to minimize the noxious effects of radiation exposure.

The Diverse Utility of Contrast Media Delivery and Dosing During Computed Tomography: An International Assessment of Knowledge and Practices.

BACKGROUND: Despite the escalated production rate, the Iodinated Contrast Media (ICM) shortage continues, and demand outweighs supply. AIM: The aim of this study is to investigate the knowledge and practice of ICM delivery in computed tomography (CT) among radiographers and radiologic technologists worldwide. METHODS: An IRB-approved cross-sectional survey used Google Forms for data collection. It involved 94 CT radiographers from 27 countries and was divided into five sections. The first section gathered demographic information, followed by sections on experience, self-assessment of ICM reactions, and delivery technique. The third section explored ICM knowledge and its relation to CT parameters. The fourth and fifth sections focus on practices during pulmonary angiography CT and renal CT scans. Data analysis involved descriptive statistics, the Chi- Square test, and ANOVA. RESULTS: Knowledge was assessed with seven questions, and a score of at least 3.5 was needed for categorization. The median score was two, indicating low knowledge. Specifically, 64.9% of the participants scored lower than the two scores. Years of experience are strongly correlated with the level of knowledge, with 51.6% of radiographers having more than 10 years of experience demonstrating adequate knowledge. 41.7% of respondents demonstrated adequate knowledge when their duty was focused on CT. Furthermore, wide practice variability exists in all CT pulmonary angiography protocols among radiographers with adequate and inadequate knowledge. CONCLUSION: Inexperienced individuals showed knowledge gaps, leading to varied practices and highlighting the need for educational programs. The study underscores establishing standardized Protocols and Practice Guidelines (PPGs) for contrast media administration in Radiology Departments. Additionally, it emphasizes the importance of regular training programs, and international knowledge sharing. The potential for self-selection bias in the online survey sample is highlighted.

A framework to distinguish healthy/cancer renal CT images using the fused deep features.

Introduction: Cancer happening rates in humankind are gradually rising due to a variety of reasons, and sensible detection and management are essential to decrease the disease rates. The kidney is one of the vital organs in human physiology, and cancer in the kidney is a medical emergency and needs accurate diagnosis and well-organized management. Methods: The proposed work aims to develop a framework to classify renal computed tomography (CT) images into healthy/cancer classes using pre-trained deep-learning schemes. To improve the detection accuracy, this work suggests a threshold filter-based pre-processing scheme, which helps in removing the artefact in the CT slices to achieve better detection. The various stages of this scheme involve: (i) Image collection, resizing, and artefact removal, (ii) Deep features extraction, (iii) Feature reduction and fusion, and (iv) Binary classification using five-fold cross-validation. Results and discussion: This experimental investigation is executed separately for: (i) CT slices with the artefact and (ii) CT slices without the artefact. As a result of the experimental outcome of this study, the K-Nearest Neighbor (KNN) classifier is able to achieve 100% detection accuracy by using the pre-processed CT slices. Therefore, this scheme can be considered for the purpose of examining clinical grade renal CT images, as it is clinically significant.

Attenuation values of renal parenchyma in virtual noncontrast images acquired from multiphase renal dual-energy CT: Comparison with standard noncontrast CT.

OBJECTIVES: To compare the renal parenchyma attenuation of virtual noncontrast (VNC) images derived from multiphase renal dual-energy computed tomography (DECT) with standard noncontrast (SNC) images, and to determine the optimum phase for VNC images. MATERIALS AND METHODS: Twenty-nine men and 16 women (mean age, 61 ±â€¯13 years; range, 37-89 years) underwent dynamic renal DECT (100/Sn140 kVp) were included in this institutional review board-approved retrospective study. There were four phases of the scan, which included noncontrast, corticomedullary (CMP), nephrographic (NP), and excretory phases (EP). The VNC images was generated from CMP, NP and EP. CT numbers of SNC images and VNC images of each phases were measured in the renal cortex and medulla. Mean standard deviation of subcutaneous fat was measured as image noise on SNC and VNC images. Radiation dose was recorded and potential radiation dose reduction was estimated. Results were tested for statistical significance using the unpaired t-test and agreement using Bland-Altman plot analysis. RESULTS: The difference in mean attenuation between SNC and each phase of VNC images were ≤4 HU. The mean attenuation of renal cortex and medulla was 33.2 ±â€¯4.4 HU, and 34.2 ±â€¯4.8 HU in SNC, 33.6 ±â€¯7.6 HU and 31.1 ±â€¯8.3 HU in VNC of CMP, 34.8 ±â€¯8.6 HU and 35.6 ±â€¯8.5 HU in VNC of NP, 31.5 ±â€¯7.6 HU and 32.4 ±â€¯7.5 HU in VNC of EP. In VNC of CMP, the attenuation of the cortex was higher than the medulla (p < 0.05), and the attenuation of medulla was significant lower than that of SNC (p < 0.01). In VNC of NP, the attenuation of renal cortex was higher than SNC (p < 0.05). In VNC of EP, the attenuation of cortex and medulla were lower than SNC (p < 0.05), and inadequate iodine subtraction in collecting system was noted. Image noise was significantly greater in SNC (p < 0.001). Mean radiation dose reduction achievable by removing the SNC was 12.3% ±â€¯0.9%. CONCLUSIONS: VNC images from multiphase renal DECT were similar to SNC images. Using the nephrographic phase can gives more comparable VNC images to SNC images in renal parenchyma than other phases.