Objectives: This study aimed to investigate the influence of microvascular impairment on myocardial characteristic alterations in remote myocardium at multiple time points, and its prognostic significance after acute ST-segment elevation myocardial infarction (STEMI). Methods: Patients were enrolled prospectively and performed CMR at baseline, 30 days, and 6 months. The primary endpoint was major adverse cardiac events (MACE): death, myocardial reinfarction, malignant arrhythmia, and hospitalization for heart failure. Cox proportional hazards regression modeling was analyzed to estimate the correlation between T1 mapping of remote myocardium and MACE in patients with and without microvascular obstruction (MVO). Results: A total of 135 patients (mean age 60.72 years; 12.70% female, median follow-up 510 days) were included, of whom 86 (63.70%) had MVO and 26 (19.26%) with MACE occurred in patients. Native T1 values of remote myocardium changed dynamically. At 1 week and 30 days, T1 values of remote myocardium in the group with MVO were higher than those without MVO (p = 0.030 and p = 0.001, respectively). In multivariable cox regression analysis of 135 patients, native_1w T1 (HR 1.03, 95%CI 1.01–1.04, p = 0.002), native_30D T1 (HR 1.05, 95%CI 1.03–1.07, p < 0.001) and LGE (HR 1.10, 95%CI 1.05–1.15, p < 0.001) were joint independent predictors of MACE. In multivariable cox regression analysis of 86 patients with MVO, native_30D T1 (HR 1.05, 95%CI 1.04–1.07, p < 0.001) and LGE (HR 1.10, 95%CI 1.05–1.15, p < 0.001) were joint independent predictors of MACE. Conclusions: The evolution of native T1 in remote myocardium was associated with the extent of microvascular impairment after reperfusion injury. In patients with MVO, native_30D T1 and LGE were joint independent predictors of MACE.

Objectives: This study compared the accuracy of predicting transarterial chemoembolization (TACE) outcomes for hepatocellular carcinoma (HCC) patients in the four different classifiers, and comprehensive models were constructed to improve predictive performance. Methods: The subjects recruited for this study were HCC patients who had received TACE treatment from April 2016 to June 2021. All participants underwent enhanced MRI scans before and after intervention, and pertinent clinical information was collected. Registry data for the 144 patients were randomly assigned to training and test datasets. The robustness of the trained models was verified by another independent external validation set of 28 HCC patients. The following classifiers were employed in the radiomics experiment: machine learning classifiers k-nearest neighbor (KNN), support vector machine (SVM), the least absolute shrinkage and selection operator (Lasso), and deep learning classifier deep neural network (DNN). Results: DNN and Lasso models were comparable in the training set, while DNN performed better in the test set and the external validation set. The CD model (Clinical & DNN merged model) achieved an AUC of 0.974 (95% CI: 0.951–0.998) in the training set, superior to other models whose AUCs varied from 0.637 to 0.943 (p < 0.05). The CD model generalized well on the test set (AUC = 0.831) and external validation set (AUC = 0.735). Conclusions: DNN model performs better than other classifiers in predicting TACE response. Integrating with clinically significant factors, the CD model may be valuable in pre-treatment counseling of HCC patients who may benefit the most from TACE intervention.

Background: Magnetic resonance elastography (MRE) has been used to stage liver fibrosis in adults. We aimed to assess the agreement between the Ishak scoring system and magnetic resonance elastography-measured liver stiffness (MRE-LS) in children. This study included all the children who underwent abdominal MRE and liver biopsies between February 2018 and January 2021. The correlation between MRE-LS and Ishak fibrosis stage, MRE parameters, and clinical and biochemical markers affecting this relationship was investigated. Results: A total of 52 patients (31 male; a median age of 11.8 years) were included in the study. The MRE-LS values were significantly different between Ishak fibrosis stages (p = 0.036). With a cut-off value of 2.97 kilopascals, MRE-LS had sensitivity, specificity, PPV, NPV and accuracy values of 90.9%, 82.9%, 58.8%, 97.1%, and 84.6%, respectively, for differentiating mild/moderate fibrosis (F0, 1, 2, 3) from severe fibrosis (F ≥ 4). Although MRE-LS was moderately correlated with Ishak fibrosis score and histological activity index and weakly correlated with aspartate aminotransferase, hepatic steatosis, and R2*, only Ishak fibrosis score was a significant predictor of MRE-LS. MRE-measured spleen stiffness was weakly correlated with the Ishak fibrosis score. Conclusions: MRE has high sensitivity and specificity for evaluating liver fibrosis in children. MRE may be used to evaluate liver fibrosis in pediatric patients.

Background: Education in radiology should be an integral aspect of undergraduate medical training given the essential role of imaging in patient management. Since the introduction of the European Society of Radiology undergraduate curriculum a decade ago, radiology education has evolved. Objectives: This survey aimed to assess the current status of undergraduate radiology education in Europe. Methods: An electronic survey on undergraduate teaching was distributed by the European Society of Radiology to delegates of the European Society of Radiology education committee and presidents of national radiological societies from April 1 to May 31, 2022. Data from the twenty questions were summarized using descriptive statistics. Results: There were 72 respondents from 36 countries. Radiology was taught to undergraduates in 95% (68/72), with a national or local curriculum informing radiology education in 93% (67/72). Radiology teaching was delivered by radiologists in 98% (58/59), across all years of medical school but most commonly in the fourth year of medical training (63%, 44/70), through various means including lectures, workshops, radiology department placements, online resources and simulation. Teaching hours were variable, with a minimum of 10 h reported. Conclusion: This survey’s findings suggest an improvement over the last decade in the engagement of radiologists in the delivery of undergraduate radiology education in European countries affiliated with the European Society of Radiology.

Objectives: Although diffusion tensor imaging (DTI) may facilitate the identification of cytoarchitectural changes associated with focal cortical dysplasia (FCD), the predominant aetiology of paediatric structural epilepsy, its potential has thus far remained unexplored in this population. Here, we investigated whether DTI indices can differentiate FCD from contralateral brain parenchyma (CBP) and whether clinical features affect these indices. Methods: In this single-centre, retrospective study, we considered children and adolescents with FCD-associated epilepsy who underwent brain magnetic resonance (MRI), including DTI. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity, and radial diffusivity, were calculated in both FCD and CBP. The DTI indices best discriminating between FCD and CBP were subsequently used to assess the link between DTI and selected clinical and lesion-related parameters. Results: We enrolled 32 patients (20 male; median age at MRI 4 years), including 15 with histologically confirmed FCD. FA values were lower (p = 0.03), whereas MD values were higher in FCD than in CBP (p = 0.04). The difference in FA values between FCD and CBP was more pronounced for a positive vs. negative history of status epilepticus (p = 0.004). Among histologically confirmed cases, the difference in FA values between FCD and CBP was more pronounced for type IIb versus type I FCD (p = 0.03). Conclusions: FA and MD discriminate between FCD and CBP, while FA differentiates between FCD types. Status epilepticus increases differences in FA, potentially reflecting changes induced in the brain. Our findings support the potential of DTI to serve as a non-invasive biomarker to characterise FCD in the paediatric population.

Objectives: Different noninvasive imaging methods to predict the chance of malignancy of ovarian tumors are available. However, their predictive value is limited due to subjectivity of the reviewer. Therefore, more objective prediction models are needed. Computer-aided diagnostics (CAD) could be such a model, since it lacks bias that comes with currently used models. In this study, we evaluated the available data on CAD in predicting the chance of malignancy of ovarian tumors. Methods: We searched for all published studies investigating diagnostic accuracy of CAD based on ultrasound, CT and MRI in pre-surgical patients with an ovarian tumor compared to reference standards. Results: In thirty-one included studies, extracted features from three different imaging techniques were used in different mathematical models. All studies assessed CAD based on machine learning on ultrasound, CT scan and MRI scan images. Per imaging method, subsequently ultrasound, CT and MRI, sensitivities ranged from 40.3 to 100%; 84.6–100% and 66.7–100% and specificities ranged from 76.3–100%; 69–100% and 77.8–100%. Results could not be pooled, due to broad heterogeneity. Although the majority of studies report high performances, they are at considerable risk of overfitting due to the absence of an independent test set. Conclusion: Based on this literature review, different CAD for ultrasound, CT scans and MRI scans seem promising to aid physicians in assessing ovarian tumors through their objective and potentially cost-effective character. However, performance should be evaluated per imaging technique. Prospective and larger datasets with external validation are desired to make their results generalizable.

Objective: The relatively long scan time has hampered the clinical use of whole-heart noncontrast coronary magnetic resonance angiography (NCMRA). The compressed sensitivity encoding (SENSE) technique, also known as the CS technique, has been found to improve scan times. This study aimed to identify the optimal CS acceleration factor for NCMRA. Methods: Thirty-six participants underwent four NCMRA sequences: three sequences using the CS technique with acceleration factors of 4, 5, and 6, and one sequence using the conventional SENSE technique with the acceleration factor of 2. Coronary computed tomography angiography (CCTA) was considered as a reference sequence. The acquisition times of the four NCMRA sequences were assessed. The correlation and agreement between the visible vessel lengths obtained via CCTA and NCMRA were also assessed. The image quality scores and contrast ratio (CR) of eight coronary artery segments from the four NCMRA sequences were quantitatively evaluated. Results: The mean acquisition time of the conventional SENSE was 343 s, while that of CS4, CS5, and CS6 was 269, 215, and 190 s, respectively. The visible vessel length from the CS4 sequence showed good correlation and agreement with CCTA. The image quality score and CR from the CS4 sequence were not statistically significantly different from those in the other groups (p > 0.05). Moreover, the image score and CR showed a decreasing trend with the increase in the CS factor. Conclusions: The CS technique could significantly shorten the acquisition time of NCMRA. The CS sequence with an acceleration factor of 4 was generally acceptable for NCMRA in clinical settings to balance the image quality and acquisition time.

Objectives: The purpose of our study was to objectively and subjectively assess optimal monoenergetic image (MEI (+)) characteristics from dual-energy CT (DECT) and the diagnostic performance for the T staging in patients with thoracic esophageal cancer (EC). Methods: In this retrospective study, patients with histopathologically confirmed EC who underwent DECT from September 2019 to December 2020 were enrolled. One standard polyenergetic image (PEI) and five MEI (+) were reconstructed. Two readers independently assessed the lesion conspicuity subjectively and calculated the contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR) of EC. Two readers independently assessed the T stage on the optimal MEI (+) and PEI subjectively. Multiple quantitative parameters were measured to assess the diagnostic performance to identify T1-2 from T3-4 in EC patients. Results: The study included 68 patients. Subjectively, primary tumor delineation received the highest ratings in MEI (+) _40 keV of the venous phase. Objectively, MEI (+) images showed significantly higher SNR compared with PEI (p < 0.05), peaking at MEI (+) _40 keV in the venous phase. CNR of tumor (MEI (+) _{40 keV -80 keV}) was all significantly higher than PEI in arterial and venous phases (p < 0.05), peaking at MEI (+) _40 keV in venous phases. The agreement between MEI (+) _40 keV and pathologic T categories was 81.63% (40/49). Rho values in venous phases had excellent diagnostic efficiency for identifying T1-2 from T3-4 (AUC = 0.84). Conclusions: MEI (+) reconstructions at low keV in the venous phase improved the assessment of lesion conspicuity and also have great potential for preoperative assessment of T staging in patients with EC.

Background: To evaluate the inter-observer and inter-vendor reliability of diffusion tensor imaging parameters in the musculoskeletal system. Methods: This prospective study included six healthy volunteers three men (mean age: 42; range: 31–52 years) and three women (mean age: 36; range: 30–44 years). Each subject was scanned using different 3 Tesla magnetic resonance scanners from three different vendors at three different sites bilaterally. First, the intra-class correlation coefficient was used to determine between-observers agreement for overall measurements and clinical sites. Next, between-group comparisons were made through the nonparametric Friedman’s test. Finally, the Bland–Altman method was used to determine agreement among the three scanner measurements, comparing them two by two. Results: A total of 792 measurement were calculated. ICC reported high levels of agreement between the two observers. ICC related to MD, FA, and RD measurements ranged from 0.88 (95% CI 0.85–0.90) to 0.95 (95% CI 0.94–0.96), from 0.85 (95% CI 0.81–0.88) to 0.95 (95% CI 0.93–0.96), and from 0.89 (0.85–0.90) to 0.92 (0.90–0.94). No statistically significant inter-vendor differences were observed. The Bland–Altmann method confirmed a high correlation between parameter values. Conclusion: An excellent inter-observer and inter-vendor reliability was found in our study.

Purpose: To investigate the reproducibility of radiomics features extracted from two-dimensional regions of interest (2D ROIs) versus whole lung (3D) ROIs in repeated in-vivo fetal magnetic resonance imaging (MRI) acquisitions. Methods: Thirty fetal MRI scans including two axial T2-weighted acquisitions of the lungs were analysed. 2D (lung at the level of the carina) and 3D (whole lung) ROIs were manually segmented using ITK-Snap. Ninety-five radiomics features were extracted from 2 and 3D ROIs in initial and repeat acquisitions using Pyradiomics. Radiomics feature intra-class correlation coefficients (ICC) were calculated between 2 and 3D ROIs in the initial acquisition, and between 2 and 3D ROIs in repeated acquisitions, respectively. Results: MRI data of 11 (36.7%) female and 19 (63.3%) male fetuses acquired at a median 25 + 0 gestational weeks plus days (GW) (interquartile range [IQR] 23 + 4 − 27 + 0 GW) were assessed. Median radiomics feature ICC between 2 and 3D ROIs in the initial MRI acquisition was 0.733 (IQR 0.313–0.814, range 0.018–0.970). ICCs between radiomics features extracted using 3D ROIs in initial and repeat acquisitions (median 0.908 [IQR 0.824–0.929, range 0.335–0.996]) were significantly higher compared to 2D ROIs (0.771 [0.699–0.835, 0.048–0.965]) (p < 0.001). Conclusion: Fetal MRI radiomics features extracted from 3D whole lung segmentation masks showed significantly higher reproducibility across repeat acquisitions compared to 2D ROIs. Therefore, fetal MRI whole lung radiomics features are robust diagnostic and potentially prognostic tools in the image-based in-vivo quantitative assessment of lung development.