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Dual-energy computed tomography (DECT) increases confidence in hepatobiliary computed tomography (CT) evaluation by boosting visible iodine enhancement and differentiating between materials based on relative attenuation of 2 different X-ray energy spectra. Image reconstructions from DECT scans improve the detection and characterization of focal liver lesions, allows for quantification of diffuse liver disease, and reveals gallstones that may be missed on standard CT imaging. Our article aims to illustrate the basic concepts of DECT and types of image reconstruction relevant for the assessment of hepatobiliary diseases. We then review literature on the use of DECT for evaluating focal and diffuse hepatobiliary diseases.

Objectives To investigate the differentiation of premalignant from benign colorectal polyps detected by CT colonography using deep learning. Methods In this retrospective analysis of an average risk colorectal cancer screening sample, polyps of all size categories and morphologies were manually segmented on supine and prone CT colonography images and classified as premalignant (adenoma) or benign (hyperplastic polyp or regular mucosa) according to histopathology. Two deep learning models SEG and noSEG were trained on 3D CT colonography image subvolumes to predict polyp class, and model SEG was additionally trained with polyp segmentation masks. Diagnostic performance was validated in an independent external multicentre test sample. Predictions were analysed with the visualisation technique Grad-CAM++. Results The training set consisted of 107 colorectal polyps in 63 patients (mean age: 63 ± 8 years, 40 men) comprising 169 polyp segmentations. The external test set included 77 polyps in 59 patients comprising 118 polyp segmentations. Model SEG achieved a ROC-AUC of 0.83 and 80% sensitivity at 69% specificity for differentiating premalignant from benign polyps. Model noSEG yielded a ROC-AUC of 0.75, 80% sensitivity at 44% specificity, and an average Grad-CAM++ heatmap score of ≥ 0.25 in 90% of polyp tissue. Conclusions In this proof-of-concept study, deep learning enabled the differentiation of premalignant from benign colorectal polyps detected with CT colonography and the visualisation of image regions important for predictions. The approach did not require polyp segmentation and thus has the potential to facilitate the identification of high-risk polyps as an automated second reader. Key Points • Non-invasive deep learning image analysis may differentiate premalignant from benign colorectal polyps found in CT colonography scans. • Deep learning autonomously learned to focus on polyp tissue for predictions without the need for prior polyp segmentation by experts. • Deep learning potentially improves the diagnostic accuracy of CT colonography in colorectal cancer screening by allowing for a more precise selection of patients who would benefit from endoscopic polypectomy, especially for patients with polyps of 6–9 mm size.

Background and Purpose: Basilar artery occlusion is associated with high morbidity and mortality. Optimal imaging and treatment strategy are still controversial and prognosis estimation challenging. We, therefore, aimed to determine the predictive value of computed tomography perfusion (CTP) parameters for functional outcome in patients with basilar artery occlusion in the context of endovascular treatment. Methods: Patients with basilar artery occlusion who underwent endovascular treatment were selected from a prospectively acquired cohort. Ischemic changes were assessed with the posterior-circulation Acute Stroke Prognosis Early Computed Tomography Score on noncontrast computed tomography, computed tomography angiography (CTA) source images, and CTP maps. Basilar artery on CTA score, posterior-circulation CTA score, and posterior-circulation collateral score were evaluated on CTA. Perfusion deficit volumes were quantified on CTP maps. Good functional outcome was defined as modified Rankin Scale score ≤3 at 90 days. Statistical analysis included binary logistic regressions and receiver operating characteristics analyses. Results: Among 49 patients who matched the inclusion criteria, 24 (49.0%) achieved a good outcome. In univariate analysis, age, National Institutes of Health Stroke Scale score on admission, posterior cerebral artery involvement, absence of or hypoplastic posterior communicating arteries, basilar artery on CTA score, posterior-circulation Acute Stroke Prognosis Early Computed Tomography Score, and perfusion deficit volumes on all CTP parameter maps presented significant association with functional outcome ( P Conclusions: CTP imaging parameters contain prognostic information for functional outcome in patients with stroke due to basilar artery occlusion and may identify patients with higher risk of disability at an early stage of hospitalization.

Background CT colonography does not enable definite differentiation between benign and premalignant colorectal polyps. Purpose To perform machine learning-based differentiation of benign and premalignant colorectal polyps detected with CT colonography in an average-risk asymptomatic colorectal cancer screening sample with external validation using radiomics. Materials and Methods In this secondary analysis of a prospective trial, colorectal polyps of all size categories and morphologies were manually segmented on CT colonographic images and were classified as benign (hyperplastic polyp or regular mucosa) or premalignant (adenoma) according to the histopathologic reference standard. Quantitative image features characterizing shape (n = 14), gray level histogram statistics (n = 18), and image texture (n = 68) were extracted from segmentations after applying 22 image filters, resulting in 1906 feature-filter combinations. Based on these features, a random forest classification algorithm was trained to predict the individual polyp character. Diagnostic performance was validated in an external test set. Results The random forest model was fitted using a training set consisting of 107 colorectal polyps in 63 patients (mean age, 63 years ± 8 [standard deviation]; 40 men) comprising 169 segmentations on CT colonographic images. The external test set included 77 polyps in 59 patients comprising 118 segmentations. Random forest analysis yielded an area under the receiver operating characteristic curve of 0.91 (95% CI: 0.85, 0.96), a sensitivity of 82% (65 of 79) (95% CI: 74%, 91%), and a specificity of 85% (33 of 39) (95% CI: 72%, 95%) in the external test set. In two subgroup analyses of the external test set, the area under the receiver operating characteristic curve was 0.87 in the size category of 6-9 mm and 0.90 in the size category of 10 mm or larger. The most important image feature for decision making (relative importance of 3.7%) was quantifying first-order gray level histogram statistics. Conclusion In this proof-of-concept study, machine learning-based image analysis enabled noninvasive differentiation of benign and premalignant colorectal polyps with CT colonography. © RSNA, 2021 Online supplemental material is available for this article.

Background: Peristalsis-related streak artifacts on the liver compromise image quality and diagnostic accuracy. Purpose: To assess dual-layer spectral-detector computed tomography (CT) image reconstructions for reducing intestinal peristalsis-related streak artifacts on the liver. Methods: We retrospectively evaluated 220 contrast-enhanced abdominal dual-energy CT scans in 131 consecutive patients (mean age: 68 ± 10 years, 120 men) who underwent routine clinical dual-layer spectral-detector CT imaging (120 kVp, 40 keV, 200 keV, virtual non-contrast (VNC), iodine images). Two independent readers evaluated bowel peristalsis streak artifacts on the liver qualitatively on a five-point Likert scale (1 = none to 5 = severe) and quantitatively by depth of streak artifact extension into the liver and measurements of Hounsfield Unit and iodine concentration differences from normal liver. Artifact severity between image reconstructions were compared by Wilcoxon signed-rank and paired t-tests. Results: 12 scans were excluded due to missing spectral data, artifacts on the liver originating from metallic foreign materials, or oral contrast material. Streak artifacts on the liver were seen in 51/208 (25%) scans and involved the left lobe only in 49/51 (96%), the right lobe only in 0/51 (0%), and both lobes in 2/51 (4%) scans. Artifact frequency was lower in iodine than in 120 kVp images (scans 18/208 vs. 51/208, p < 0.001). Artifact severity was less in iodine than in 120 kVp images (median score 1 vs. 3, p < 0.001). Streak artifact extension into the liver was shorter in iodine than 120 kVp images (mean length 2 ± 4 vs. 12 ± 5 mm, p < 0.001). Hounsfield Unit and iodine concentration differed significantly between bright streak artifacts and normal liver in 120 kVp, 40 keV, 200 keV, and VNC images (p < 0.001, each), but not in iodine images (p = 0.23). Conclusion: Intestinal peristalsis-related streak artifacts commonly affect the left liver lobe at CT and can be substantially reduced by viewing iodine dual-energy CT image reconstructions.

Purpose: To assess the influence of different dual-energy CT (DECT) scanner techniques on the severity of visceral-motion-related artifacts on the liver. Methods: Two independent readers retrospectively evaluated visceral-motion-related artifacts on the liver on 120-kVp(-like), monoenergetic low- and high-keV, virtual non-contrast (VNC), and iodine images acquired on a dual-source, twin-beam, fast kV-switching, and dual-layer spectral detector scanner. Quantitative assessment: Depth of artifact extension into the liver, measurements of Hounsfield Units (HU) and iodine concentrations. Qualitative assessment: Five-point Likert scale (1 = none to 5 = severe). Artifact severity between image reconstructions were compared by Wilcoxon signed-rank and paired t-tests. Results: 615 contrast-enhanced routine clinical DECT scans of the abdomen were evaluated in 458 consecutive patients (mean age: 61 ± 14 years, 331 men). For dual-source and twin-beam scanners, depth of extension of artifacts into the liver was significantly shorter and artifact severity scores significantly lower for 120-kVp-like images compared with the other image reconstructions (p < 0.001, each). For fast kV-switching and spectral detector scanner images, depth of extension of artifacts was significantly shorter and artifact severity scores significantly lower for iodine images (p < 0.001, each). Dual-source 120-kVp-like and spectral detector iodine images reduced artifacts to an extent that no significant difference in HU or iodine concentrations between artifacts (dual-source: 97 HU, spectral detector: 1.9 mg/mL) and unaffected liver parenchyma (dual-source: 108 HU, spectral detector: 2.1 mg/mL) was measurable (dual-source: p = 0.32, spectral detector: p = 0.15). Conclusion: Visceral-motion-related artifacts on the liver can be markedly reduced by viewing 120-kVp-like images for dual-source and twin-beam DECT scanners and iodine images for fast kV-switching and dual-layer spectral detector DECT scanners.

Background: Neurologic symptom severity and deterioration at 24 hours (h) predict long-term outcomes in patients with acute large vessel occlusion (LVO) stroke of the anterior circulation. We aimed to examine the association of baseline multiparametric CT imaging and clinical factors with the course of neurologic symptom severity in the first 24 h after endovascular treatment (EVT). Methods: Patients with LVO stroke of the anterior circulation were selected from a prospectively acquired consecutive cohort of patients who underwent multiparametric CT, including non-contrast CT, CT angiography and CT perfusion before EVT. The symptom severity was assessed on admission and after 24 h using the 42-point National Institutes of Health Stroke Scale (NIHSS). Clinical and imaging data were compared between patients with and without early neurological deterioration (END). END was defined as an increase in ≥4 points, and a significant clinical improvement as a decrease in ≥4 points, compared to NIHSS on admission. Multivariate regression analyses were used to determine independent associations of imaging and clinical parameters with NIHSS score increase or decrease in the first 24 h. Results: A total of 211 patients were included, of whom 38 (18.0%) had an END. END was significantly associated with occlusion of the internal carotid artery (odds ratio (OR), 4.25; 95% CI, 1.90–9.47) and the carotid T (OR, 6.34; 95% CI, 2.56–15.71), clot burden score (OR, 0.79; 95% CI, 0.68–0.92) and total ischemic volume (OR, 1.01; 95% CI, 1.00–1.01). In a comprehensive multivariate analysis model including periprocedural parameters and complications after EVT, carotid T occlusion remained independently associated with END, next to reperfusion status and intracranial hemorrhage. Favorable reperfusion status and small ischemic core volume were associated with clinical improvement after 24 h. Conclusions: The use of imaging parameters as a surrogate for early NIHSS progression in an acute LVO stroke after EVT reached limited performance with only carotid T occlusion as an independent predictor of END. Reperfusion status and early complications in terms of intracranial hemorrhage are critical factors that influence patient outcome in the acute stroke phase after EVT.

Die radiologische sowie nuklearmedizinische Diagnostik nimmt einen bedeutenden Stellenwert im diagnostischen Algorithmus, insbesondere zur Diagnosefindung sowie auch zur Staging-Untersuchung von gastroenteropankreatischen neuroendokrinen Tumoren (GEP-NET) dar. Die sonographische – einschlieslich der kontrastverstarkten – Untersuchung stellt eine wichtige initiale Modalitat dar, um bei anamnestischem und klinischem Verdacht nach NET zu suchen. Der vorliegende Artikel beschreibt das sonomorphologische Verhalten von Ileum- sowie Pankreas-NET und von neuroendokrinen Lebermetastasen. Sonographische Evaluation von Dunndarm‑, Pankreas-NET sowie neuroendokriner Leberfiliae. Kontrastverstarkte Computertomographie (CT) oder Magnetresonanztomographie (MRT), native Sonographie. Kontrastverstarkter Ultraschall (CEUS). Der CEUS unterstutzt die native Sonographie bei der Suche nach NET und der Differenzialdiagnose fokaler Lasionen und ist sensitiver fur Lebermetastasen (Sensitivitat nach der Literatur 99 % vs. 68 %). Der CEUS bietet eine Suchmethode, um nach eventuellen Tumoren bei positiver Anamnese bzw. positiven klinischen Ergebnissen und Laborwerten zu suchen. Er erlaubt eine nahere Differenzierung zwischen Benignitat und Malignitat. Auf schnittbildgebende Verfahren kann jedoch bzgl. Staging-Diagnostik nicht verzichtet werden.

IntroductionAs white matter hyperintensities (WMHs) of the brain are associated with an increased risk of stroke, cognitive decline, and depression, elucidating the associated risk factors is important. In addition to age and hypertension, pre-diabetes and diabetes may play important roles in the development of WMHs. Previous studies have, however, shown conflicting results. We aimed to investigate the effect of diabetes status and quantitative markers of glucose metabolism on WMH volume in a population-based cohort without prior cardiovascular disease.Research design and methods400 participants underwent 3 T MRI. WMHs were manually segmented on 3D fluid-attenuated inversion recovery images. An oral glucose tolerance test (OGTT) was administered to all participants not previously diagnosed with diabetes to assess 2-hour serum glucose concentrations. Fasting glucose concentrations and glycated hemoglobin (HbA1c) levels were measured. Zero-inflated negative binomial regression analyses of WMH volume and measures of glycemic status were performed while controlling for cardiovascular risk factors and multiple testing.ResultsThe final study population comprised 388 participants (57% male; age 56.3±9.2 years; n=98 with pre-diabetes, n=51 with diabetes). Higher WMH volume was associated with pre-diabetes (p=0.001) and diabetes (p=0.026) compared with normoglycemic control participants after adjustment for cardiovascular risk factors. 2-hour serum glucose (pConclusionOur results indicate that high 2-hour serum glucose concentration in OGTT, but not fasting glucose levels, may be an independent risk factor for the development of WMHs, with the potential to inform intensified prevention strategies in individuals at risk of WMH-associated morbidity.

BACKGROUND/AIM Intraarterial Technetium-99m-Macroaggregated Albumin (99mTc-MAA) administration is an established method to predict particle distribution prior to radioembolization. This study aimed to analyse the impact of intraarterial administration of 99mTc-MAA on changes in liver-specific laboratory parameters and to assess whether such changes are associated with post-radioembolization hepatotoxicity. PATIENTS AND METHODS A total of 202 patients treated with radioembolization received prior mapping angiography with 99mTc-MAA administration. All patients underwent clinical and laboratory examinations, including liver-specific parameters at certain times before and after mapping angiography/99mTc-MAA administration, as well as before radioembolization and during follow-up. RESULTS Bilirubin increased temporarily after 99mTc-MAA administration (p

To identify the most important factors that impact brain volume, while accounting for potential collinearity, we used a data-driven machine-learning approach. Gray Matter Volume (GMV) was derived from magnetic resonance imaging (3T, FLAIR) and adjusted for intracranial volume (ICV). 93 potential determinants of GMV from the categories sociodemographics, anthropometric measurements, cardio-metabolic variables, lifestyle factors, medication, sleep, and nutrition were obtained from 293 participants from a population-based cohort from Southern Germany. Elastic net regression was used to identify the most important determinants of ICV-adjusted GMV. The four variables age (selected in each of the 1000 splits), glomerular filtration rate (794 splits), diabetes (323 splits) and diabetes duration (122 splits) were identified to be most relevant predictors of GMV adjusted for intracranial volume. The elastic net model showed better performance compared to a constant linear regression (mean squared error = 1.10 vs. 1.59, p

Objectives To determine a cut-off apparent diffusion coefficient (ADC) value distinguishing local recurrence from scar tissue in patients with rectal cancer treated with complete surgical tumour removal. Methods 72 patients were retrospectively included. Patients underwent 1.5T MRI including multiplanar T2-weighted turbo-spin-echo sequences (TSE) and axial single-shot epi-diffusion-weighted sequences (EPSE). Two independent observers measured mean tumour and scar tissue ADCs by manually drawing regions of interest (ROIs). The t -test and ROC analysis were used for comparison and determining an optimal discrimination threshold. As reference standard histopathological results were used in 23 patients (32%) and clinical follow-up in 49 patients (68%). Results Recurrent rectal cancer was found in 30 patients (4 female, 26 male, median age 63.13 years) and treatment related changes such as scar tissue in 42 patients (11 female, 31 male, median age 63.67 years). The mean ADC value of tumour recurrence was 1.02×10 −3 mm 2 /s (0.63–1.44×10 −3 mm 2 /s) and of scar tissue 1.77×10 −3 mm 2 /s (1.11–2.41×10 −3 mm 2 /s) showing a statistically significant difference (p −3 mm 2 /s with a sensitivity, specificity, and accuracy of 93%, 91%, and 92% respectively. Conclusions Diffusion weighted MRI allows for the differentiation of tumour recurrence from scar tissue after surgical resection of rectal cancer.

Objective Hepatocellular carcinoma (HCC) is the most common cause of primary liver cancer. A major part of diagnostic HCC work-up is based on imaging findings from sonography, computed tomography (CT), or magnetic resonance imaging (MRI) scans. Contrast-enhanced ultrasound (CEUS) allows for the dynamic assessment of the microperfusion pattern of suspicious liver lesions. This study aimed to evaluate the diagnostic value of CEUS compared with CT scans for assessing HCC. Methods We performed a retrospective, single-center study between 2004 and 2018 on 234 patients with suspicious liver lesions who underwent CEUS and CT examinations. All patients underwent native B-mode, color Doppler and CEUS after providing informed consent. Every CEUS examination was performed and interpreted by a single experienced radiologist (European Federation of Societies for Ultrasound in Medicine and Biology level 3). Results CEUS was performed on all included patients without occurrence of any adverse effects. CEUS showed a sensitivity of 94%, a specificity of 70%, a positive predictive value of 93% and a negative predictive value of 72% for analyzing HCC compared with CT as the diagnostic gold standard. Conclusions CEUS has an excellent safety profile and shows a high diagnostic accuracy in assessing HCC compared with corresponding results from CT scans.

We present the case of splenogonadal fusion in a 53-year-old male patient assessed by ultrasound and MRI, confirmed by pathologic examination. In addition to B-mode and colour-coded Doppler ultrasound, shear wave elastography and CEUS were performed and are presented in detail. Splenogonadal fusion is a rare congenital anomaly presumably caused by an abnormal attachment of splenic tissue to the gonad during gestation. Diagnosis is challenging for clinicians and in unclear cases splenogonadal fusion might cause unnecessary orchiectomies with benign pathologic results. Ultrasound is the first-line imaging modality in the diagnosis of testicular pathologies. This case report summarizes all available modern ultrasound imagingtechnologies and highlights the possibilities for the diagnosis of splenogonadal fusion.