Effect of acquisition techniques, latest kernels, and advanced monoenergetic post-processing for stent visualization with third-generation dual-source CT

PURPOSEThe purpose of this study is to systematically evaluate the effect of tube voltage, current kernels, and monoenergetic post-processing on stent visualization.METHODSA 6 mm chrome-cobalt peripheral stent was placed in a dedicated phantom and scanned with the available tube voltage settings of a third-generation dual-source scanner in single-energy (SE) and dual-energy (DE) mode. Images were reconstructed using the latest convolution kernels and monoenergetic reconstructions (40-190 keV) for DE. The sharpness of stent struts (S), struts width (SW), contrast-to-noise-ratios (CNR), and pseudoenhancement (PE) between the vessel with and without stent were analyzed using an in-house built automatic analysis tool. Measurements were standardized through calculated z-scores. Z-scores were combined for stent (SQ), luminal (LQ), and overall depiction quality (OQ) by adding S and SW, CNR and SW and PE, and S and SW and CNR and PE. Two readers rated overall stent depiction on a 5-point Likert-scale. Agreement was calculated using linear-weighted kappa. Correlations were calculated using Spearman correlation coefficient.RESULTSMaximum values of S and CNR were 169.1 HU/pixel for [DE; 100/ Sn 150 kV; Qr59; 40 keV] and 50.0 for [SE; 70 kV; Bv36]. Minimum values of SW and PE were 2.615 mm for [DE; 80 to 90/ Sn 150 kV; Qr59; 140 to 190 keV] and 0.12 HU for [DE; 80/ Sn 150 kV; Qr36; 190 keV]. Best combined z-scores of SQ, LQ, and OQ were 4.53 for [DE; 100/ Sn 150 kV; Qr 59; 40 keV], 1.23 for [DE; 100/ Sn 150 kV; Qr59; 140 keV] and 2.95 for [DE; 90/ Sn 150 kV; Qr59; 50 keV]. Best OQ of SE was ranked third with 2.89 for [SE; 90 kV; Bv59]. Subjective agreement was excellent (kappa=0.86; P < .001) and correlated well with OQ (rs=0.94, P < .001).CONCLUSIONCombining DE computed tomography (CT) acquisition with the latest kernels and monoenergetic post-processing allows for improved stent visualization as compared with SECT. The best overall results were obtained for monoenergetic reconstructions with 50 keV from DECT 90/Sn 150 kV acquisitions using kernel Qr59

Case Report: MRI, CEUS, and CT Imaging Features of Metanephric Adenoma with Histopathological Correlation and Literature Review

The metanephric adenoma is an extremely rare, benign, embryonal-epithelial neoplasm of the kidney and has a good prognosis with appropriate treatment. It can present at any age and is often asymptomatic. Histologically, the lesion is well established; however, there have been only a few cases described with available detailed imaging findings, most of them with large renal masses typically depicted by computed tomography (CT). This case report includes imaging of contrast-enhanced MRI, contrast-enhanced ultrasound (CEUS), and CT, and thus adds to the information available, potentially promoting a nephron-sparing clinical pathway. We report on the clinical presentation, imaging, histopathological diagnosis, and treatment data of a 27-year-old female, in whom an incidental, symptomatic kidney tumor was detected. CT, CEUS, and MRI showed a suspicious unifocal renal lesion with inhomogeneous enhancement, which was indistinguishable from renal cell carcinoma. After laparoscopic resection, a metanephric adenoma with microscopically partially glandular, partially nest-like solid growth and without distinctive atypia was diagnosed pathohistologically. Immunohistochemistry results were positive for Wilms Tumor 1 and CD57 and negative for EMA and CK7: 2&ndash;3% positive cells in MIB1 coloring. At 3-month and 1-year follow-up, the patient was asymptomatic and imaging showed no recurrence of renal masses or metastases

Dual-Energy Computed Tomography-Based Quantitative Bone Marrow Imaging in Non-Hematooncological Subjects: Associations with Age, Gender and Other Variables

Background: Our aim is to assess the utility and associations of quantitative bone marrow attenuation (BMA) values measured on clinical dual-energy computed tomography (DECT) exams in non-hematooncologic subjects with skeletal regions, patient age, gender, and other clinical variables. Methods: Our local ethics committee approved this retrospective image data analysis. Between July 2019 and July 2021, 332 eligible patients (mean age, 64 &plusmn; 18 years; female, 135) were identified. Inclusion criteria were the availability of a standardized abdominopelvic DECT data set acquired on the same scanner with identical protocol. Eleven regions-of-interest were placed in the T11-L5 vertebral bodies, dorsal iliac crests, and femur necks. Patient age, gender, weight, clinical, habitual variables, inflammation markers, and anemia were documented in all cases. Results: Multi-regression analyses (all, p &lt; 0.05) identified age as the strongest predictor of lumbar BMA (standardized coefficient: &beta; = &minus;0.74), followed by CRP (&beta; = 0.11), LDH (&beta; = 0.11), and gender (&beta; = &minus;0.10). In the lower thoracic spine, age was the strongest predictor (&beta; = &minus;0.58) of BMA, followed by gender (&beta; = &minus;0.09) and LDH (&beta; = 0.12). In femoral bones, age was negatively predictive of BMA (&beta; = &minus;0.12), whereas LDH and anemia were positively predictive (&beta; = 0.16 both). Heart insufficiency significantly decreased (&beta; = 0.12, p = 0.034) a BMA value gradient from higher to lower HU values along the vertebrae T11 and L5, whereas age significantly increased this gradient (&beta; = &minus;0.2, p &le; 0.001). Conclusions: DECT-based BMA measurements can be obtained from clinical CT exams. BMA values are negatively associated with patient age and influenced by gender, anemia, and inflammatory markers

Accuracy of Non-Enhanced CT in Detecting Early Ischemic Edema Using Frequency Selective Non-Linear Blending.

PURPOSE:Ischemic brain edema is subtle and hard to detect by computed tomography within the first hours of stroke onset. We hypothesize that non-enhanced CT (NECT) post-processing with frequency-selective non-linear blending ("best contrast"/BC) increases its accuracy in detecting edema and irreversible tissue damage (infarction). METHODS:We retrospectively analyzed the NECT scans of 76 consecutive patients with ischemic stroke (exclusively middle cerebral artery territory-MCA) before and after post-processing with BC both at baseline before reperfusion therapy and at follow-up (5.73±12.74 days after stroke onset) using the Alberta Stroke Program Early CT Score (ASPECTS). We assessed the differences in ASPECTS between unprocessed and post-processed images and calculated sensitivity, specificity, and predictive values of baseline NECT using follow-up CT serving as reference standard for brain infarction. RESULTS:NECT detected brain tissue hypoattenuation in 35 of 76 patients (46.1%). This number increased to 71 patients (93.4%) after post-processing with BC. Follow-up NECT confirmed brain infarctions in 65 patients (85.5%; p = 0.012). Post-processing increased the sensitivity of NECT for brain infarction from 35/65 (54%) to 65/65 (100%), decreased its specificity from 11/11 (100%) to 7/11 (64%), its positive predictive value (PPV) from 35/35 (100%) to 65/69 (94%) and increased its accuracy 46/76 (61%) to 72/76 (95%). CONCLUSIONS:This post-hoc analysis suggests that post-processing of NECT with BC may increase its sensitivity for ischemic brain damage significantly

Differentiation of Hamartomas and Malignant Lung Tumors in Single-Phased Dual-Energy Computed Tomography

This study investigated the efficacy of single-phase dual-energy CT (DECT) in differentiating pulmonary hamartomas from malignant lung lesions using virtual non-contrast (VNC), iodine, and fat quantification. Forty-six patients with 47 pulmonary lesions (mean age: 65.2 ± 12.1 years; hamartomas-to-malignant lesions = 22:25; male: 67%) underwent portal venous DECT using histology, PET-CT and follow-up CTs as a reference. Quantitative parameters such as VNC, fat fraction, iodine density and CT mixed values were statistically analyzed. Significant differences were found in fat fractions (hamartomas: 48.9%; malignancies: 22.9%; p ≤ 0.0001) and VNC HU values (hamartomas: −20.5 HU; malignancies: 17.8 HU; p ≤ 0.0001), with hamartomas having higher fat content and lower VNC HU values than malignancies. CT mixed values also differed significantly (p ≤ 0.0001), but iodine density showed no significant differences. ROC analysis favored the fat fraction (AUC = 96.4%; sensitivity: 100%) over the VNC, CT mixed value and iodine density for differentiation. The study concludes that the DECT-based fat fraction is superior to the single-energy CT in differentiating between incidental pulmonary hamartomas and malignant lesions, while post-contrast iodine density is ineffective for differentiation

AI Denoising Significantly Enhances Image Quality and Diagnostic Confidence in Interventional Cone-Beam Computed Tomography

(1) To investigate whether interventional cone-beam computed tomography (cbCT) could benefit from AI denoising, particularly with respect to patient body mass index (BMI); (2) From 1 January 2016 to 1 January 2022, 100 patients with liver-directed interventions and peri-procedural cbCT were included. The unenhanced mask run and the contrast-enhanced fill run of the cbCT were reconstructed using weighted filtered back projection. Additionally, each dataset was post-processed using a novel denoising software solution. Place-consistent regions of interest measured signal-to-noise ratio (SNR) per dataset. Corrected mixed-effects analysis with BMI subgroup analyses compared objective image quality. Multiple linear regression measured the contribution of &ldquo;Radiation Dose&rdquo;, &ldquo;Body-Mass-Index&rdquo;, and &ldquo;Mode&rdquo; to SNR. Two radiologists independently rated diagnostic confidence. Inter-rater agreement was measured using Spearman correlation (r); (3) SNR was significantly higher in the denoised datasets than in the regular datasets (p &lt; 0.001). Furthermore, BMI subgroup analysis showed significant SNR deteriorations in the regular datasets for higher patient BMI (p &lt; 0.001), but stable results for denoising (p &gt; 0.999). In regression, only denoising contributed positively towards SNR (0.6191; 95%CI 0.6096 to 0.6286; p &lt; 0.001). The denoised datasets received overall significantly higher diagnostic confidence grades (p = 0.010), with good inter-rater agreement (r &ge; 0.795, p &lt; 0.001). In a subgroup analysis, diagnostic confidence deteriorated significantly for higher patient BMI (p &lt; 0.001) in the regular datasets but was stable in the denoised datasets (p &ge; 0.103).; (4) AI denoising can significantly enhance image quality in interventional cone-beam CT and effectively mitigate diagnostic confidence deterioration for rising patient BMI

Bland & Altman plot of the ASPECTS score of the NECT analysis in comparison to the “best contrast” image analysis.

<p>Bland & Altman plot of the ASPECTS score of the NECT analysis in comparison to the “best contrast” image analysis.</p

Schematic illustration of the “best contrast” (BC) post-processing.

<p>The center is defining the attenuation level, at which image information is highlighted. By adjustment of the slope and delta of the attenuation curve, the expression of the post-processing can be modulated.</p

64 year-old male patient with ischemic stroke of the right cerebral hemisphere due to an isolated occlusion of the right internal carotid artery.

<p>While the NECT (A) only give an idea of a slight dedifferentiation of gray and white matter at the insular cortex, the “best contrast” image (B) shows a great delineated infarction (long arrows) with involvement of the internal capsule (short arrow). The diagnosis was confirmed on follow-up CT, which shows that the BC image reflects the infarct size more accurately (C).</p

50-year-old male patient with ischemic stroke of the left hemisphere due to occlusion of the left internal carotid artery (ICA).

<p>The NECT (A) does not show a significant infarct demarcation, whilst the “best contrast” optimized images (B) show a demarcation of the left basal ganglia and the insular cortex (arrows), which was confirmed by follow-up CT (C).</p