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Objectives: Adenomatous colorectal polyps require endoscopic resection, as opposed to non-adenomatous hyperplastic colorectal polyps. This study aims to evaluate the effect of artificial intelligence (AI)-assisted differentiation of adenomatous and non-adenomatous colorectal polyps at CT colonography on radiologists' therapy management., Materials and Methods: Five board-certified radiologists evaluated CT colonography images with colorectal polyps of all sizes and morphologies retrospectively and decided whether the depicted polyps required endoscopic resection. After a primary unassisted reading based on current guidelines, a second reading with access to the classification of a radiomics-based random-forest AI-model labelling each polyp as "non-adenomatous" or "adenomatous" was performed. Performance was evaluated using polyp histopathology as the reference standard., Results: 77 polyps in 59 patients comprising 118 polyp image series (47% supine position, 53% prone position) were evaluated unassisted and AI-assisted by five independent board-certified radiologists, resulting in a total of 1180 readings (subsequent polypectomy: yes or no). AI-assisted readings had higher accuracy (76% +/- 1% vs. 84% +/- 1%), sensitivity (78% +/- 6% vs. 85% +/- 1%), and specificity (73% +/- 8% vs. 82% +/- 2%) in selecting polyps eligible for polypectomy (p < 0.001). Inter-reader agreement was improved in the AI-assisted readings (Fleiss' kappa 0.69 vs. 0.92)., Conclusion: AI-based characterisation of colorectal polyps at CT colonography as a second reader might enable a more precise selection of polyps eligible for subsequent endoscopic resection. However, further studies are needed to confirm this finding and histopathologic polyp evaluation is still mandatory., Key Points: Question This is the first study evaluating the impact of AI-based polyp classification in CT colonography on radiologists' therapy management. Findings Compared with unassisted reading, AI-assisted reading had higher accuracy, sensitivity, and specificity in selecting polyps eligible for polypectomy. Clinical relevance Integrating an AI tool for colorectal polyp classification in CT colonography could further improve radiologists' therapy recommendations., Competing Interests: Compliance with ethical standards. Guarantor: The scientific guarantor of this publication is Sergio Grosu. Conflict of interest: C.C. is a member of the Scientific Editorial Board (section: Nuclear Medicine and Molecular Imaging) for European Radiology. As such, they did not participate in the selection nor review processes for this article. The remaining authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article. Statistics and biometry: One of the authors has significant statistical expertise. Informed consent: Written informed consent was waived by the Institutional Review Board. Ethical approval: Institutional Review Board approval was obtained. Study subjects or cohorts overlap: Some study subjects or cohorts have been previously reported in https://doi.org/10.1148/radiol.2021202363 and https://doi.org/10.1007/s00330-021-08532-2 . Methodology: Retrospective Diagnostic or prognostic study Performed at one institution, (© 2025. The Author(s).)

Purpose/objectives: Advancements in transcatheter mitral and tricuspid valve repair have resulted in growing demands in preprocedural computed tomography (CT) imaging. Due to the introduction of multidetector CT (MDCT), shorter acquisition times as well as high rates of heart failure and arrhythmias in this specific patient population, optimal synchronization between the passage of contrast agent and data acquisition is mandatory. There is no consensus on which acquisition technique should be used in this patient population. We aimed to optimize our preprocedural CT protocol comparing bolus tracking (BT) and test bolus (TB) techniques., Materials and Methods: We performed a retrospective analysis on 151 patients referred for full-cycle MDCT evaluation for transcatheter tricuspid valve repair comparing BT with TB (BT n=75 TB n=75). Contrast-to-noise ratios (CNR) were obtained. Demographic data, laboratory, electrocardiographic, and transthoracic echocardiography/transoesophageal echocardiography parameters were collected from electronic health records. Also, the volume of contrast agent and saline chaser and radiation dose length product and milliampere seconds were collected., Results: BT and TB resulted in comparable CNR (BT: 0.47 [0.34 to 0.98]; TB: 0.51 [0.41 to 1.40]; P =0.1). BT was associated with a shorter scan duration (BT: 8.3 min [4.1 to 24.4]; TB: 13.9 min [6.2 to 41.4]; P <0.001), less radiation in terms of dose length product (BT: 1186±585; TB: 1383±679, P =0.04), and lower total volume administration (BT: 101 mL [63 to 16]; TB: 114 mL [71 to 154]; P <0.001). In patients with severely impaired ejection fraction (left ventricular ejection fraction [LVEF] ≤35%; n=65 [TB n=31; BT n=34]) using the TB technique yielded significantly better image quality in terms of CNR (TB=0.57 [0.41 to 1.07); BT=0.41 [0.34 to 0.65]; P =0.02)., Conclusion: In patients with impaired LVEF (LVEF≤35%), the TB technique yielded significantly superior image quality and may be the preferred approach in this specific patient population. BT showed advantages in terms of shorter duration, less radiation, and lower contrast agent volume., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Large-bore arteriotomy for transcatheter aortic valve implantation (TAVI) requires percutaneous vascular closure devices, but real-world data comparing different closure strategies are limited., Aims: We sought to compare a dual ProGlide strategy vs a combination of one ProGlide and one FemoSeal for vascular closure after TAVI., Methods: We retrospectively analysed 874 propensity score-matched patients undergoing TAVI at the Munich University Hospital from August 2018 to October 2020. From August 2018 to August 2019, a dual ProGlide strategy was used for vascular closure. From October 2019 to October 2020, a combination of one ProGlide and one FemoSeal was used. The primary endpoint was defined as access-related major vascular complications or bleeding ≥Type 2 according to Valve Academic Research Consortium 3 criteria., Results: Patients in the dual ProGlide group (n=437) had a higher incidence of the primary endpoint than patients treated with one ProGlide and one FemoSeal (n=437; 11.4% vs 3.0%; p<0.001). Furthermore, they had a higher rate of closure device failure (2.7% vs 0.9%; p=0.044) and more often required unplanned surgery or endovascular treatment (3.9% vs 0.9%; p=0.004). The incidence of death did not differ significantly between groups (3.4% vs 1.6%; p=0.08)., Conclusions: A combined ProGlide and FemoSeal strategy might have the potential to reduce access-related vascular complications following TAVI.

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., (© 2022. The Author(s).)

The spleen is often involved in malignant lymphoma, which manifests on CT as either splenomegaly or focal, hypodense lymphoma lesions. This study aimed to investigate the diagnostic value of radiomics features of the spleen in classifying malignant lymphoma against non-lymphoma as well as the determination of malignant lymphoma subtypes in the case of disease presence-in particular Hodgkin lymphoma (HL), diffuse large B-cell lymphoma (DLBCL), mantle-cell lymphoma (MCL), and follicular lymphoma (FL). Spleen segmentations of 326 patients (139 female, median age 54.1 +/- 18.7 years) were generated and 1317 radiomics features per patient were extracted. For subtype classification, we created four different binary differentiation tasks and addressed them with a Random Forest classifier using 10-fold cross-validation. To detect the most relevant features, permutation importance was analyzed. Classifier results using all features were: malignant lymphoma vs. non-lymphoma AUC = 0.86 ( p < 0.01); HL vs. NHL AUC = 0.75 ( p < 0.01); DLBCL vs. other NHL AUC = 0.65 ( p < 0.01); MCL vs. FL AUC = 0.67 ( p < 0.01). Classifying malignant lymphoma vs. non-lymphoma was also possible using only shape features AUC = 0.77 ( p < 0.01), with the most important feature being sphericity. Based on only shape features, a significant AUC could be achieved for all tasks, however, best results were achieved combining shape and textural features. This study demonstrates the value of splenic imaging and radiomic analysis in the diagnostic process in malignant lymphoma detection and subtype classification.

Finding prognostic biomarkers with high accuracy in patients with pancreatic cancer (PC) remains a challenging problem. To improve the prediction of survival and to investigate the relevance of quantitative imaging biomarkers (QIB) we combined QIB with established clinical parameters. In this retrospective study a total of 75 patients with metastatic PC and liver metastases were analyzed. Segmentations of whole liver tumor burden (WLTB) from baseline contrast-enhanced CT images were used to derive QIBs. The benefits of QIBs in multivariable Cox models were analyzed in comparison with two clinical prognostic models from the literature. To discriminate survival, the two clinical models had concordance indices of 0.61 and 0.62 in a statistical setting. Combined clinical and imaging-based models achieved concordance indices of 0.74 and 0.70 with WLTB volume, tumor burden score (TBS), and bilobar disease being the three WLTB parameters that were kept by backward elimination. These combined clinical and imaging-based models have significantly higher predictive performance in discriminating survival than the underlying clinical models alone ( p < 0.003). Radiomics and geometric WLTB analysis of patients with metastatic PC with liver metastases enhances the modeling of survival compared with models based on clinical parameters alone.

Purpose: Coronavirus 2019 disease (COVID-19) has been shown to affect the myocardium, resulting in a worse clinical outcome. In this registry study, we aimed to identify differences in cardiac magnetic resonance imaging (CMRI) between COVID-19 and all-cause myocarditis., Materials and Methods: We examined CMRI of patients with COVID-19 and elevated high-sensitivity serum troponin levels performed between March 31st and May 5th and compared them to CMRI of patients without SARS-CoV-2 infection with suspected myocarditis in the same time period. For this purpose, we evaluated Lake-Louise Criteria for myocarditis by determining nonischemic myocardial injury via T1-mapping, extracellular volume, late gadolinium enhancement, and myocardial edema (ME) by T2-mapping and fat-saturated T2w imaging (T2Q)., Results: A total of 15 of 18 (89%) patients with COVID-19 had abnormal findings. The control group consisted of 18 individuals. There were significantly fewer individuals with COVID-19 who had increased T2 (5 vs. 10; P=0.038) and all-cause ME (7 vs. 15; P=0.015); thus, significantly fewer patients with COVID-19 fulfilled Lake-Louise Criteria (6 vs. 17; P<0.001). In contrast, nonischemic myocardial injury was not significantly different. In the COVID-19 group, indexed end-diastolic volume of the left ventricle showed a significant correlation to the extent of abnormal T1 (R2=0.571; P=0.017) and extracellular volume (R2=0.605; P=0.013) and absolute T1, T2, and T2Q (R2=0.644; P=0.005, R2=0.513; P=0.035 and R2=0.629; P=0.038, respectively); in the control group, only extracellular volume showed a weak correlation (R2=0.490; P=0.046)., Conclusions: Cardiac involvement in COVID-19 seems to show less ME than all-cause myocarditis. Abnormal CMRI markers correlated to left ventricle dilation only in the COVID-19 group. Larger comparative studies are needed to verify our findings., Competing Interests: A.C. declares a nonmonetary scientific cooperation with Siemens-Healthineers. The remaining authors declare no conflicts of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

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.

Objective: To evaluate the performance of 1.5 T true fast imaging with steady state precession (TrueFISP) magnetic resonance imaging (MRI) sequences for the detection and characterization of pulmonary abnormalities caused by coronavirus disease 2019 (COVID-19)., Materials and Methods: In this retrospective single-center study, computed tomography (CT) and MRI scans of 20 patients with COVID-19 pneumonia were evaluated with regard to the distribution, opacity, and appearance of pulmonary lesions, as well as bronchial changes, pleural effusion, and thoracic lymphadenopathy. McNemar's test was used in order to compare the COVID-19-associated alterations seen on CT with those seen on MRI., Results: Ground-glass opacities were better visualized on CT than on MRI ( p = 0.031). We found no statistically significant differences between CT and MRI regarding the visualization/characterization of the following: consolidations; interlobular/intralobular septal thickening; the distribution or appearance of pulmonary abnormalities; bronchial pathologies; pleural effusion; and thoracic lymphadenopathy., Conclusion: Pulmonary abnormalities caused by COVID-19 pneumonia can be detected on TrueFISP MRI sequences and correspond to the patterns known from CT. Especially during the current pandemic, the portions of the lungs imaged on cardiac or abdominal MRI should be carefully evaluated to promote the identification and isolation of unexpected cases of COVID-19, thereby curbing further spread of the disease.

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<0.05). In multivariate analyses, Basilar artery on CTA score, posterior-circulation Acute Stroke Prognosis Early Computed Tomography Score (odds ratio range, 1.31–2.10 [95% CI, 1.00–7.24]), and perfusion deficit volumes on all CTP maps (odds ratio range, 0.77–0.98 [95% CI, 0.63–1.00]) remained as independent outcome predictors. Cerebral blood flow deficit volume yielded the best performance for the classification of good clinical outcome with an area under the curve of 0.92 (95% CI, 0.84–0.99). Age and admission National Institutes of Health Stroke Scale had lower discriminatory power (area under the curve, <0.7)., 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 and Purpose: Acute ischemic stroke of the anterior circulation due to large vessel occlusion (LVO) is a multifactorial process, which causes neurologic symptoms of different degree. Our aim was to examine the impact of neuromorphologic and vascular correlates as well as clinical factors on acute symptom severity in LVO stroke. Methods: We selected LVO stroke patients with known onset time from a consecutive cohort which underwent multiparametric CT including non-contrast CT, CT angiography and CT perfusion (CTP) before thrombectomy. Software-based quantification was used to calculate CTP total ischemic and ischemic core volume. Symptom severity was assessed using the National Institutes of Health Stroke Scale (NIHSS) upon admission. Multivariable regression analysis was performed to determine independent associations of admission NIHSS with imaging and clinical parameters. Receiver operating characteristics (ROC) analyses were used to examine performance of imaging parameters to classify symptom severity. Results: We included 142 patients. Linear and ordinal regression analyses for NIHSS and NIHSS severity groups identified significant associations for total ischemic volume [β = 0.31, p = 0.01; Odds ratio (OR) = 1.11, 95%-confidence-interval (CI): 1.02-1.19], clot burden score (β = -0.28, p = 0.01; OR = 0.76, 95%-CI: 0.64-0.90) and age (β = 0.17, p = 0.04). No association was found for ischemic core volume, stroke side, collaterals and time from onset. Stroke topography according to the Alberta Stroke Program CT Score template did not display significant influence after correction for multiple comparisons. AUC for classification of the NIHSS threshold ≥6 by total ischemic volume was 0.81 ( p < 0.001). Conclusions: We determined total ischemic volume, clot burden and age as relevant drivers for baseline NIHSS in acute LVO stroke. This suggests that not only mere volume but also degree of occlusion influences symptom severity. Use of imaging parameters as surrogate for baseline NIHSS reached limited performance underlining the need for combined clinical and imaging assessment in acute stroke management., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Stueckelschweiger, Tiedt, Puhr-Westerheide, Fabritius, Mueller, Kellert, Maurus, Grosu, Rueckel, Herzberg, Liebig, Ricke, Dimitriadis, Kunz and Reidler.)

Objectives: To investigate the prediction of 1-year survival (1-YS) in patients with metastatic colorectal cancer with use of a systematic comparative analysis of quantitative imaging biomarkers (QIBs) based on the geometric and radiomics analysis of whole liver tumor burden (WLTB) in comparison to predictions based on the tumor burden score (TBS), WLTB volume alone, and a clinical model., Methods: A total of 103 patients (mean age: 61.0 ± 11.2 years) with colorectal liver metastases were analyzed in this retrospective study. Automatic segmentations of WLTB from baseline contrast-enhanced CT images were used. Established biomarkers as well as a standard radiomics model building were used to derive 3 prognostic models. The benefits of a geometric metastatic spread (GMS) model, the Aerts radiomics prior model of the WLTB, and the performance of TBS and WLTB volume alone were assessed. All models were analyzed in both statistical and predictive machine learning settings in terms of AUC., Results: TBS showed the best discriminative performance in a statistical setting to discriminate 1-YS (AUC = 0.70, CI: [0.56, 0.90]). For the machine learning-based prediction for unseen patients, both a model of the GMS of WLTB (0.73, CI: [0.60, 0.84]) and the Aerts radiomics prior model (0.76, CI: [0.65, 0.86]) applied on the WLTB showed a numerically higher predictive performance than TBS (0.68, CI: [0.54, 0.79]), radiomics (0.65, CI: [0.55, 0.78]), WLTB volume alone (0.53, CI: [0.40. 0.66]), or the clinical model (0.56, CI: [0.43, 0.67])., Conclusions: The imaging-based GMS model may be a first step towards a more fine-grained machine learning extension of the TBS concept for risk stratification in mCRC patients without the vulnerability to technical variance of radiomics., Key Points: • CT-based geometric distribution and radiomics analysis of whole liver tumor burden in metastatic colorectal cancer patients yield prognostic information. • Differences in survival are possibly attributable to the spatial distribution of metastatic lesions and the geometric metastatic spread analysis of all liver metastases may serve as robust imaging biomarker invariant to technical variation. • Imaging-based prediction models outperform clinical models for 1-year survival prediction in metastatic colorectal cancer patients with liver metastases.

Background/aim: Intraarterial Technetium-99m-Macroaggregated Albumin ( 99m Tc-MAA) administration is an established method to predict particle distribution prior to radioembolization. This study aimed to analyse the impact of intraarterial administration of 99m Tc-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 99m Tc-MAA administration. All patients underwent clinical and laboratory examinations, including liver-specific parameters at certain times before and after mapping angiography/ 99m Tc-MAA administration, as well as before radioembolization and during follow-up., Results: Bilirubin increased temporarily after 99m Tc-MAA administration (p<0.001), but was not clinically relevant, and returned close to the initial value before radioembolization. These changes showed no association with subsequent postradioembolic hepatotoxicity or shortened overall survival., Conclusion: 99m Tc-MAA administration results in a significant, however, not clinically relevant transient increase in bilirubin levels, which does not provide a predictive value for subsequent radioembolization outcome or postradioembolic hepatotoxicity., (Copyright© 2021, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Background: Myocardial injury, defined by elevated troponin levels, is associated with adverse outcome in patients with coronavirus disease 2019 (COVID-19). The frequency of cardiac injury remains highly uncertain and confounded in current publications; myocarditis is one of several mechanisms that have been proposed., Methods: We prospectively assessed patients with myocardial injury hospitalized for COVID-19 using transthoracic echocardiography, cardiac magnetic resonance imaging, and endomyocardial biopsy., Results: Eighteen patients with COVID-19 and myocardial injury were included in this study. Echocardiography revealed normal to mildly reduced left ventricular ejection fraction of 52.5% (46.5%-60.5%) but moderately to severely reduced left ventricular global longitudinal strain of -11.2% (-7.6% to -15.1%). Cardiac magnetic resonance showed any myocardial tissue injury defined by elevated T1, extracellular volume, or late gadolinium enhancement with a nonischemic pattern in 16 patients (83.3%). Seven patients (38.9%) demonstrated myocardial edema in addition to tissue injury fulfilling the Lake-Louise criteria for myocarditis. Combining cardiac magnetic resonance with speckle tracking echocardiography demonstrated functional or morphological cardiac changes in 100% of investigated patients. Endomyocardial biopsy was conducted in 5 patients and revealed enhanced macrophage numbers in all 5 patients in addition to lymphocytic myocarditis in 1 patient. SARS-CoV-2 RNA was not detected in any biopsy by quantitative real-time polymerase chain reaction. Finally, follow-up measurements of left ventricular global longitudinal strain revealed significant improvement after a median of 52.0 days (-11.2% [-9.2% to -14.7%] versus -15.6% [-12.5% to -19.6%] at follow-up; P =0.041)., Conclusions: In this small cohort of COVID-19 patients with elevated troponin levels, myocardial injury was evidenced by reduced echocardiographic left ventricular strain, myocarditis patterns on cardiac magnetic resonance, and enhanced macrophage numbers but not predominantly lymphocytic myocarditis in endomyocardial biopsies.

Flow coefficients v&#95;{n} of the orders n=1-6 are measured with the High-Acceptance DiElectron Spectrometer (HADES) at GSI for protons, deuterons, and tritons as a function of centrality, transverse momentum, and rapidity in Au+Au collisions at sqrt[s&#95;{NN}]=2.4  GeV. Combining the information from the flow coefficients of all orders allows us to construct for the first time, at collision energies of a few GeV, a multidifferential picture of the angular emission pattern of these particles. It reflects the complicated interplay between the effect of the central fireball pressure on the emission of particles and their subsequent interaction with spectator matter. The high precision information on higher order flow coefficients is a major step forward in constraining the equation of state of dense baryonic matter.

Background: We aimed to investigate the clinical value of a 3D-T1w turbo-spin-echo (TSE) sequence and [18F]fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG-PET/CT) for the diagnosis of active large vessel vasculitis (LVV) and single-organ vasculitis (SOV) of the aorta., Methods: Twenty-four patients with suspected vasculitis who underwent MRI and PET/CT were retrospectively evaluated. MRI was analyzed for concentric contrast enhancement and wall thickening, and flow artifact intensity (4-point-scales). PET/CT analysis comprised qualitative, quantitative and semiquantitative methods. Imaging findings were correlated with final diagnosis derived from the clinical follow-up data., Results: Fifteen of 24 patients had a clinically confirmed active vasculitis, two had inactive vasculitis and 7 no vasculitis. [18F]FDG-PET/CT and 3D-T1w TSE-MRI revealed both a high diagnostic accuracy of 88% and 83%, respectively. In patients in whom both PET/CT and MRI showed concordant findings (19 patients), the accuracy increased to 95% with a high positive predictive value (92%) and negative predictive value (100%); thus, a correct diagnosis was obtained in 18 of 19 patients. Among the five patients with discordant findings PET/CT correctly identified the two patients without active vasculitis while rated false positive on MRI. Of the three remaining patients with active vasculitis, two were correctly identified by MRI and one by PET/CT., Conclusions: 3D-T1w TSE-MRI and [18F]FDG-PET/CT are both useful in the diagnosis of active vasculitis with high diagnostic accuracies. The diagnostic accuracy was even optimized by combining the two analysis methods. Therefore, there might be substantial potential for the application of whole-body hybrid PET/MRI in the evaluation of vasculitis in future studies.

Objectives: To assess the value of a T1-3D black-blood turbo spin echo (TSE) sequence for the diagnosis of abdominal large vessel vasculitis (LVV)., Materials and Methods: The study included 20 patients with abdominal LVV and 17 controls, who underwent a 3T-MRI scan using a modified T1-3D volumetric isotropic TSE acquisition and a segmented T1-3D turbo field echo sequence (T1-mVISTA/T1-eTHRIVE). Two radiologists independently analyzed the aorta for concentric contrast enhancement, concentric wall thickening, image quality, and flow artifact intensity (CCE/CWT/IQ/FAI; 4-point scales). The mean aortic wall thickness (MAWT) in post-contrast T1-mVISTA was compared between patients and controls., Results: IQ of T1-mVISTA was rated good to excellent in 91.5% of 282 evaluated vessel segments with no or minor FAI present in 85.5%. The inter-observer reproducibility for the identification of CCE/CWT on T1-mVISTA was 0.92 and 0.93 (p < 0.001). The distribution of segmental inflammation in T1-mVISTA significantly correlated with T1-eTHRIVE (CCE, κ = 0.768; CWT, κ = 0.715; p < 0.001), resulting in a sensitivity, specificity, and positive predictive value of 100%, 81.3%, and 83.3%. The MAWT significantly differed between patients and controls (3.29 ± 0.81 vs. 2.24 ± 0.45 mm; p < 0.001)., Conclusions: T1-mVISTA enables the evaluation of the MAWT and allows the detection of abdominal LVV., Key Points: • 3D T1w-mVISTA accurately depicted the large abdominal vessels. • 3D T1w-mVISTA enables accurate measurements of the abdominal aortic wall thickness. • 3D T1w-mVISTA is useful for the detection of abdominal LVV.

The goal of radiomics is to convert medical images into a minable data space by extraction of quantitative imaging features for clinically relevant analyses, e.g. survival time prediction of a patient. One problem of radiomics from computed tomography is the impact of technical variation such as reconstruction kernel variation within a study. Additionally, what is often neglected is the impact of inter-patient technical variation, resulting from patient characteristics, even when scan and reconstruction parameters are constant. In our approach, measurements within 3D regions-of-interests (ROI) are calibrated by further ROIs such as air, adipose tissue, liver, etc. that are used as control regions (CR). Our goal is to derive general rules for an automated internal calibration that enhance prediction, based on the analysed features and a set of CRs. We define qualification criteria motivated by status-quo radiomics stability analysis techniques to only collect information from the CRs which is relevant given a respective task. These criteria are used in an optimisation to automatically derive a suitable internal calibration for prediction tasks based on the CRs. Our calibration enhanced the performance for centrilobular emphysema prediction in a COPD study and prediction of patients' one-year-survival in an oncological study.

We present the first observation of K^{-} and ϕ absorption within nuclear matter by means of π^{-}-induced reactions on C and W targets at an incident beam momentum of 1.7  GeV/c studied with HADES at SIS18/GSI. The double ratio (K^{-}/K^{+})&#95;{W}/(K^{-}/K^{+})&#95;{C} is found to be 0.319±0.009(stat)&#95;{-0.012}^{+0.014}(syst) indicating a larger absorption of K^{-} in heavier targets as compared to lighter ones. The measured ϕ/K^{-} ratios in π^{-}+C and π^{-}+W reactions within the HADES acceptance are found to be equal to 0.55±0.04(stat)&#95;{-0.07}^{+0.06}(syst) and to 0.63±0.06(stat)&#95;{-0.11}^{+0.11}(syst), respectively. The similar ratios measured in the two different reactions demonstrate for the first time experimentally that the dynamics of the ϕ meson in nuclear medium is strongly coupled to the K^{-} dynamics. The large difference in the ϕ production off C and W nuclei is discussed in terms of a strong ϕN in-medium coupling. These results are relevant for the description of heavy-ion collisions and the structure of neutron stars.

A HTS campaign identified compound 1, an excellent hit-like molecule to initiate medicinal chemistry efforts to optimize a dual ROCK1 and ROCK2 inhibitor. Substitution (2-Cl, 2-NH 2 , 2-F, 3-F) of the pyridine hinge binding motif or replacement with pyrimidine afforded compounds with a clean CYP inhibition profile. Cocrystal structures of an early lead compound were obtained in PKA, ROCK1, and ROCK2. This provided critical structural information for medicinal chemistry to drive compound design. The structural data indicated the preferred configuration at the central benzylic carbon would be ( R), and application of this information to compound design resulted in compound 16. This compound was shown to be a potent and selective dual ROCK inhibitor in both enzyme and cell assays and efficacious in the retinal nerve fiber layer model after oral dosing. This tool compound has been made available through the AbbVie Compound Toolbox. Finally, the cocrystal structures also identified that aspartic acid residues 176 and 218 in ROCK2, which are glutamic acids in PKA, could be targeted as residues to drive both potency and kinome selectivity. Introduction of a piperidin-3-ylmethanamine group to the compound series resulted in compound 58, a potent and selective dual ROCK inhibitor with excellent predicted drug-like properties.

Objectives: To evaluate the feasibility of T1w-3D black-blood turbo spin echo (TSE) sequence with variable flip angles for the diagnosis of thoracic large vessel vasculitis (LVV)., Methods: Thirty-five patients with LVV, diagnosed according to the current standard of reference, and 35 controls were imaged at 3.0T using 1.2 × 1.3 × 2.0 mm 3 fat-suppressed, T1w-3D, modified Volumetric Isotropic TSE Acquisition (mVISTA) pre- and post-contrast. Applying a navigator and peripheral pulse unit triggering (PPU), the total scan time was 10-12 min. Thoracic aorta and subclavian and pulmonary arteries were evaluated for image quality (IQ), flow artefact intensity, diagnostic confidence, concentric wall thickening and contrast enhancement (CWT, CCE) using a 4-point scale., Results: IQ was good in all examinations (3.25 ± 0.72) and good to excellent in 342 of 408 evaluated segments (83.8 %), while 84.1 % showed no or minor flow artefacts. The interobserver reproducibility for the identification of CCE and CWT was 0.969 and 0.971 (p < 0.001) with an average diagnostic confidence of 3.47 ± 0.64. CCE and CWT were strongly correlated (Cohen's k = 0.87; P < 0.001) and significantly more frequent in the LVV-group (52.8 % vs. 1.0 %; 59.8 % vs. 2.4 %; P < 0.001)., Conclusions: Navigated fat-suppressed T1w-3D black-blood MRI with PPU-triggering allows diagnosis of thoracic LVV., Key Points: • Cross-sectional imaging is frequently applied in the diagnosis of LVV. • Navigated, PPU-triggered, T1w-3D mVISTA pre- and post contrast takes 10-12 min. • In this prospective, single-centre study, T1w-3D mVISTA accurately depicted large thoracic vessels. • T1w-3D mVISTA visualized CWT/CCW as correlates of mural inflammation in LVV. • T1w-3D mVISTA might be an alternative diagnostic tool without ionizing radiation.