European Radiology

Papers
(The median citation count of European Radiology is 10. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-05-01 to 2024-05-01.)
ArticleCitations
A deep learning algorithm using CT images to screen for Corona virus disease (COVID-19)519
Chest CT score in COVID-19 patients: correlation with disease severity and short-term prognosis482
Artificial intelligence in radiology: 100 commercially available products and their scientific evidence190
ESUR/ESUI consensus statements on multi-parametric MRI for the detection of clinically significant prostate cancer: quality requirements for image acquisition, interpretation and radiologists’ trainin186
CT in coronavirus disease 2019 (COVID-19): a systematic review of chest CT findings in 4410 adult patients152
Radiomics in predicting treatment response in non-small-cell lung cancer: current status, challenges and future perspectives141
A deep learning approach to characterize 2019 coronavirus disease (COVID-19) pneumonia in chest CT images136
Chest CT for detecting COVID-19: a systematic review and meta-analysis of diagnostic accuracy132
Implementation of artificial intelligence (AI) applications in radiology: hindering and facilitating factors128
The sensitivity and specificity of chest CT in the diagnosis of COVID-19117
Reliability and prognostic value of radiomic features are highly dependent on choice of feature extraction platform115
Multi-scale and multi-parametric radiomics of gadoxetate disodium–enhanced MRI predicts microvascular invasion and outcome in patients with solitary hepatocellular carcinoma ≤ 5 cm107
How can we combat multicenter variability in MR radiomics? Validation of a correction procedure96
To buy or not to buy—evaluating commercial AI solutions in radiology (the ECLAIR guidelines)93
An international survey on AI in radiology in 1,041 radiologists and radiology residents part 1: fear of replacement, knowledge, and attitude90
Quantitative chest CT analysis in COVID-19 to predict the need for oxygenation support and intubation88
Minimizing acquisition-related radiomics variability by image resampling and batch effect correction to allow for large-scale data analysis85
Radiographic findings in 240 patients with COVID-19 pneumonia: time-dependence after the onset of symptoms82
Initial chest radiographs and artificial intelligence (AI) predict clinical outcomes in COVID-19 patients: analysis of 697 Italian patients81
Chest X-ray for predicting mortality and the need for ventilatory support in COVID-19 patients presenting to the emergency department80
Acute pulmonary embolism in non-hospitalized COVID-19 patients referred to CTPA by emergency department79
Preoperative prediction for pathological grade of hepatocellular carcinoma via machine learning–based radiomics77
From community-acquired pneumonia to COVID-19: a deep learning–based method for quantitative analysis of COVID-19 on thick-section CT scans77
Imaging features and evolution on CT in 100 COVID-19 pneumonia patients in Wuhan, China75
A decade of radiomics research: are images really data or just patterns in the noise?74
COVID-19 pneumonia: CT findings of 122 patients and differentiation from influenza pneumonia73
Utility of sonoelastography for the evaluation of rotator cuff tendon and pertinent disorders: a systematic review and meta-analysis73
Automated detection of pulmonary embolism in CT pulmonary angiograms using an AI-powered algorithm72
Accelerate gas diffusion-weighted MRI for lung morphometry with deep learning71
Identifying normal mammograms in a large screening population using artificial intelligence71
CT iterative vs deep learning reconstruction: comparison of noise and sharpness71
Radiomics of MRI for pretreatment prediction of pathologic complete response, tumor regression grade, and neoadjuvant rectal score in patients with locally advanced rectal cancer undergoing neoadjuvan69
Staging, recurrence and follow-up of uterine cervical cancer using MRI: Updated Guidelines of the European Society of Urogenital Radiology after revised FIGO staging 201868
Prediction of breast cancer molecular subtypes on DCE-MRI using convolutional neural network with transfer learning between two centers68
Comparison of O-RADS, GI-RADS, and IOTA simple rules regarding malignancy rate, validity, and reliability for diagnosis of adnexal masses68
Can machine learning radiomics provide pre-operative differentiation of combined hepatocellular cholangiocarcinoma from hepatocellular carcinoma and cholangiocarcinoma to inform optimal treatment plan67
Machine learning for the identification of clinically significant prostate cancer on MRI: a meta-analysis66
Neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios as predictors of tumor response in hepatocellular carcinoma after DEB-TACE65
Ultra-low-dose chest CT imaging of COVID-19 patients using a deep residual neural network62
Clinically significant prostate cancer detection and segmentation in low-risk patients using a convolutional neural network on multi-parametric MRI61
Automated quantification of COVID-19 severity and progression using chest CT images61
Pancreas image mining: a systematic review of radiomics59
Chest CT practice and protocols for COVID-19 from radiation dose management perspective58
Radiomic machine learning for predicting prognostic biomarkers and molecular subtypes of breast cancer using tumor heterogeneity and angiogenesis properties on MRI58
Long-term outcomes of radiofrequency ablation for unifocal low-risk papillary thyroid microcarcinoma: a large cohort study of 414 patients57
Prediction of tumor response via a pretreatment MRI radiomics-based nomogram in HCC treated with TACE57
The Lisbon Agreement on Femoroacetabular Impingement Imaging—part 1: overview56
Fully automated body composition analysis in routine CT imaging using 3D semantic segmentation convolutional neural networks56
Interpretation of CT signs of 2019 novel coronavirus (COVID-19) pneumonia55
Deep learning radiomics of ultrasonography can predict response to neoadjuvant chemotherapy in breast cancer at an early stage of treatment: a prospective study55
Preoperative sarcopenia is associated with poor overall survival in pancreatic cancer patients following pancreaticoduodenectomy55
Radiomics analysis of 18F-Choline PET/CT in the prediction of disease outcome in high-risk prostate cancer: an explorative study on machine learning feature classification in 94 patients55
Radiologists with MRI-based radiomics aids to predict the pelvic lymph node metastasis in endometrial cancer: a multicenter study54
Incorporating radiomics into clinical trials: expert consensus endorsed by the European Society of Radiology on considerations for data-driven compared to biologically driven quantitative biomarkers54
Volumetric assessment of the periablational safety margin after thermal ablation of colorectal liver metastases53
Association of “initial CT” findings with mortality in older patients with coronavirus disease 2019 (COVID-19)53
Applications of artificial intelligence (AI) in diagnostic radiology: a technography study53
Deep learning–assisted prostate cancer detection on bi-parametric MRI: minimum training data size requirements and effect of prior knowledge51
Which role for chest x-ray score in predicting the outcome in COVID-19 pneumonia?51
COVIDiag: a clinical CAD system to diagnose COVID-19 pneumonia based on CT findings50
Opportunistic osteoporosis screening in multi-detector CT images using deep convolutional neural networks50
A systematic review of radiomics in osteosarcoma: utilizing radiomics quality score as a tool promoting clinical translation50
Automatic opportunistic osteoporosis screening in routine CT: improved prediction of patients with prevalent vertebral fractures compared to DXA50
Identification of high-risk carotid plaque with MRI-based radiomics and machine learning49
Outcome prediction of head and neck squamous cell carcinoma by MRI radiomic signatures49
MR image-based radiomics to differentiate type Ι and type ΙΙ epithelial ovarian cancers48
Radiomics signature of brain metastasis: prediction of EGFR mutation status48
Introducing the Node Reporting and Data System 1.0 (Node-RADS): a concept for standardized assessment of lymph nodes in cancer47
Preoperative classification of primary and metastatic liver cancer via machine learning-based ultrasound radiomics47
Identification of common and severe COVID-19: the value of CT texture analysis and correlation with clinical characteristics46
Gadoxetate-enhanced abbreviated MRI is highly accurate for hepatocellular carcinoma screening45
An international survey on AI in radiology in 1041 radiologists and radiology residents part 2: expectations, hurdles to implementation, and education45
Radiomics nomogram for the prediction of 2019 novel coronavirus pneumonia caused by SARS-CoV-245
A deep learning algorithm may automate intracranial aneurysm detection on MR angiography with high diagnostic performance45
Acute adrenal infarction as an incidental CT finding and a potential prognosis factor in severe SARS-CoV-2 infection: a retrospective cohort analysis on 219 patients44
Chest computed tomography findings of coronavirus disease 2019 (COVID-19) pneumonia44
Stakeholders’ perspectives on the future of artificial intelligence in radiology: a scoping review44
Can artificial intelligence reduce the interval cancer rate in mammography screening?44
Percutaneous microwave ablation of bone tumors: a systematic review43
Radiomics-based prediction model for outcomes of PD-1/PD-L1 immunotherapy in metastatic urothelial carcinoma43
Prospective comparison of the diagnostic accuracy of 18F-FDG PET/MRI, MRI, CT, and bone scintigraphy for the detection of bone metastases in the initial staging of primary breast cancer patients43
Artificial intelligence for prediction of COVID-19 progression using CT imaging and clinical data43
MRI-Based radiomics nomogram for differentiation of benign and malignant lesions of the parotid gland43
A predictive model and scoring system combining clinical and CT characteristics for the diagnosis of COVID-1943
MRI-derived PRECISE scores for predicting pathologically-confirmed radiological progression in prostate cancer patients on active surveillance43
Diagnostic performance of conventional and advanced imaging modalities for assessing newly diagnosed cervical cancer: systematic review and meta-analysis42
Differentiation of renal cell carcinoma subtypes through MRI-based radiomics analysis42
Pulmonary embolism in patients with COVID-19 and value of D-dimer assessment: a meta-analysis42
Radiomics analysis of dual-energy CT-derived iodine maps for diagnosing metastatic cervical lymph nodes in patients with papillary thyroid cancer42
Natural history of prostate cancer on active surveillance: stratification by MRI using the PRECISE recommendations in a UK cohort42
Lung and kidney perfusion deficits diagnosed by dual-energy computed tomography in patients with COVID-19-related systemic microangiopathy42
CT-based radiomics to predict the pathological grade of bladder cancer42
Clinical value of radiomics and machine learning in breast ultrasound: a multicenter study for differential diagnosis of benign and malignant lesions42
Preoperative prediction of axillary sentinel lymph node burden with multiparametric MRI-based radiomics nomogram in early-stage breast cancer41
Current status and quality of radiomics studies in lymphoma: a systematic review41
Clinical characteristics and chest CT imaging features of critically ill COVID-19 patients41
COVID-19 classification of X-ray images using deep neural networks41
Comparison of the computed tomography findings in COVID-19 and other viral pneumonia in immunocompetent adults: a systematic review and meta-analysis41
MRI index lesion radiomics and machine learning for detection of extraprostatic extension of disease: a multicenter study40
Challenges and solutions for introducing artificial intelligence (AI) in daily clinical workflow40
Chest CT–derived pulmonary artery enlargement at the admission predicts overall survival in COVID-19 patients: insight from 1461 consecutive patients in Italy40
Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study40
Radiomics signature on dynamic contrast-enhanced MR images: a potential imaging biomarker for prediction of microvascular invasion in mass-forming intrahepatic cholangiocarcinoma40
Shape and texture-based radiomics signature on CT effectively discriminates benign from malignant renal masses40
The validity, reliability, and reviewer acceptance of VI-RADS in assessing muscle invasion by bladder cancer: a multicenter prospective study40
Diagnosis of left atrial appendage thrombus in patients with atrial fibrillation: delayed contrast-enhanced cardiac CT40
Deep learning with convolutional neural network in the assessment of breast cancer molecular subtypes based on US images: a multicenter retrospective study40
Imaging assessment of children presenting with suspected or known juvenile idiopathic arthritis: ESSR-ESPR points to consider40
Dynamic evolution of COVID-19 on chest computed tomography: experience from Jiangsu Province of China39
Diagnostic accuracy of spleen stiffness to evaluate portal hypertension and esophageal varices in chronic liver disease: a systematic review and meta-analysis39
Deep learning–based reconstruction may improve non-contrast cerebral CT imaging compared to other current reconstruction algorithms39
Deep learning–based metal artefact reduction in PET/CT imaging39
Advanced gastric cancer: CT radiomics prediction and early detection of downstaging with neoadjuvant chemotherapy38
Radiomics nomogram of contrast-enhanced spectral mammography for prediction of axillary lymph node metastasis in breast cancer: a multicenter study38
CT-like images based on T1 spoiled gradient-echo and ultra-short echo time MRI sequences for the assessment of vertebral fractures and degenerative bone changes of the spine38
CT diagnostic reference levels based on clinical indications: results of a large-scale European survey38
Nomogram based on radiomics analysis of primary breast cancer ultrasound images: prediction of axillary lymph node tumor burden in patients38
Pre-treatment CT-based radiomics nomogram for predicting microsatellite instability status in colorectal cancer38
Prediction of HCC microvascular invasion with gadobenate-enhanced MRI: correlation with pathology38
Prospective performance of clear cell likelihood scores (ccLS) in renal masses evaluated with multiparametric magnetic resonance imaging37
Improved coronary calcification quantification using photon-counting-detector CT: an ex vivo study in cadaveric specimens37
Intimate partner violence crisis in the COVID-19 pandemic: how can radiologists make a difference?37
The Kaiser score reliably excludes malignancy in benign contrast-enhancing lesions classified as BI-RADS 4 on breast MRI high-risk screening exams36
Imaging alternatives to colonoscopy: CT colonography and colon capsule. European Society of Gastrointestinal Endoscopy (ESGE) and European Society of Gastrointestinal and Abdominal Radiology (ESGAR) G36
Automated segmentation of kidney and renal mass and automated detection of renal mass in CT urography using 3D U-Net-based deep convolutional neural network36
Towards reference values of pericoronary adipose tissue attenuation: impact of coronary artery and tube voltage in coronary computed tomography angiography36
MR imaging of epithelial ovarian cancer: a combined model to predict histologic subtypes36
CT-based radiomics stratification of tumor grade and TNM stage of clear cell renal cell carcinoma36
Comparison of chest CT findings between COVID-19 pneumonia and other types of viral pneumonia: a two-center retrospective study36
Unnecessary thyroid nodule biopsy rates under four ultrasound risk stratification systems: a systematic review and meta-analysis36
Deep learning in breast radiology: current progress and future directions36
T1 mapping and cardiac magnetic resonance feature tracking in mitral valve prolapse36
Coronary calcium scoring potential of large field-of-view spectral photon-counting CT: a phantom study36
Deep learning shows good reliability for automatic segmentation and volume measurement of brain hemorrhage, intraventricular extension, and peripheral edema35
ESUR/ESUI position paper: developing artificial intelligence for precision diagnosis of prostate cancer using magnetic resonance imaging35
Early detection of ovarian cancer35
AI-based improvement in lung cancer detection on chest radiographs: results of a multi-reader study in NLST dataset35
[18F]FDG uptake of axillary lymph nodes after COVID-19 vaccination in oncological PET/CT: frequency, intensity, and potential clinical impact35
COVID-19 pneumonia imaging follow-up: when and how? A proposition from ESTI and ESR35
Solitary solid pulmonary nodules: a CT-based deep learning nomogram helps differentiate tuberculosis granulomas from lung adenocarcinomas35
Deep learning in interstitial lung disease—how long until daily practice35
MRI-based radiomics signature for pretreatment prediction of pathological response to neoadjuvant chemotherapy in osteosarcoma: a multicenter study35
Smart chest X-ray worklist prioritization using artificial intelligence: a clinical workflow simulation35
Deep learning–assisted differentiation of pathologically proven atypical and typical hepatocellular carcinoma (HCC) versus non-HCC on contrast-enhanced MRI of the liver35
Fully automated prediction of liver fibrosis using deep learning analysis of gadoxetic acid–enhanced MRI35
Evaluation of a convolutional neural network for ovarian tumor differentiation based on magnetic resonance imaging34
MRI radiomics features of mesorectal fat can predict response to neoadjuvant chemoradiation therapy and tumor recurrence in patients with locally advanced rectal cancer34
Diagnostic value of deep learning reconstruction for radiation dose reduction at abdominal ultra-high-resolution CT34
Multiparametric functional MRI and 18F-FDG-PET for survival prediction in patients with head and neck squamous cell carcinoma treated with (chemo)radiation34
4D flow MRI applications in congenital heart disease34
Radiomics derived from dynamic contrast-enhanced MRI pharmacokinetic protocol features: the value of precision diagnosis ovarian neoplasms34
Radiomics-based differentiation between glioblastoma and primary central nervous system lymphoma: a comparison of diagnostic performance across different MRI sequences and machine learning techniques33
A comparative study of the value of amide proton transfer-weighted imaging and diffusion kurtosis imaging in the diagnosis and evaluation of breast cancer33
Deep learning reconstruction for contrast-enhanced CT of the upper abdomen: similar image quality with lower radiation dose in direct comparison with iterative reconstruction33
Hypoxia and perfusion in breast cancer: simultaneous assessment using PET/MR imaging33
Validation of the revised 2018 AAST-OIS classification and the CT severity index for prediction of operative management and survival in patients with blunt spleen and liver injuries33
Performance of machine learning algorithms for glioma segmentation of brain MRI: a systematic literature review and meta-analysis33
Any unique image biomarkers associated with COVID-19?33
Predicting the molecular subtype of breast cancer and identifying interpretable imaging features using machine learning algorithms32
Improved characterization of sub-centimeter enhancing breast masses on MRI with radiomics and machine learning in BRCA mutation carriers32
Differential diagnosis of benign and malignant vertebral fracture on CT using deep learning32
Bladder cancer: do we need contrast injection for MRI assessment of muscle invasion? A prospective multi-reader VI-RADS approach32
Radiomics model based on shear-wave elastography in the assessment of axillary lymph node status in early-stage breast cancer32
A clinically practical radiomics-clinical combined model based on PET/CT data and nomogram predicts EGFR mutation in lung adenocarcinoma32
Inter-reader agreement of the PI-QUAL score for prostate MRI quality in the NeuroSAFE PROOF trial32
Improvement of late gadolinium enhancement image quality using a deep learning–based reconstruction algorithm and its influence on myocardial scar quantification32
Five-year follow-up results of thermal ablation for low-risk papillary thyroid microcarcinomas: systematic review and meta-analysis31
Intramesenteric dynamic contrast pediatric MR lymphangiography: initial experience and comparison with intranodal and intrahepatic MR lymphangiography31
Cardiac CT and MRI radiomics: systematic review of the literature and radiomics quality score assessment31
Impact of coronavirus disease 2019 (COVID-19) emergency on Italian radiologists: a national survey31
Diagnostic accuracy and interobserver variability of CO-RADS in patients with suspected coronavirus disease-2019: a multireader validation study31
Radiomics using CT images for preoperative prediction of futile resection in intrahepatic cholangiocarcinoma31
Robust performance of deep learning for automatic detection and segmentation of brain metastases using three-dimensional black-blood and three-dimensional gradient echo imaging31
Combined hepatocellular-cholangiocarcinoma: which preoperative clinical data and conventional MRI characteristics have value for the prediction of microvascular invasion and clinical significance?31
Quantitative evaluation of passive muscle stiffness by shear wave elastography in healthy individuals of different ages31
Quantitative CT radiomics-based models for prediction of haematoma expansion and poor functional outcome in primary intracerebral haemorrhage31
Comparison of machine learning algorithms to predict clinically significant prostate cancer of the peripheral zone with multiparametric MRI using clinical assessment categories and radiomic features31
Molecular subtyping of diffuse gliomas using magnetic resonance imaging: comparison and correlation between radiomics and deep learning31
How to read and review papers on machine learning and artificial intelligence in radiology: a survival guide to key methodological concepts31
Radiofrequency ablation versus repeat resection for recurrent hepatocellular carcinoma (≤ 5 cm) after initial curative resection31
Clinical and chest CT features as a predictive tool for COVID-19 clinical progress: introducing a novel semi-quantitative scoring system30
MRI-based radiomics signature for localized prostate cancer: a new clinical tool for cancer aggressiveness prediction? Sub-study of prospective phase II trial on ultra-hypofractionated radiotherapy (A30
An MRI-based radiomics signature as a pretreatment noninvasive predictor of overall survival and chemotherapeutic benefits in lower-grade gliomas30
Repeatability and reproducibility of ADC measurements: a prospective multicenter whole-body-MRI study30
The combination of hepatobiliary phase with Gd-EOB-DTPA and DWI is highly accurate for the detection and characterization of liver metastases from neuroendocrine tumor30
Application of the amide proton transfer-weighted imaging and diffusion kurtosis imaging in the study of cervical cancer30
Accelerated single-shot T2-weighted fat-suppressed (FS) MRI of the liver with deep learning–based image reconstruction: qualitative and quantitative comparison of image quality with conventional T2-we30
CT and COVID-19: Chinese experience and recommendations concerning detection, staging and follow-up30
Myocardial injury detected by T1 and T2 mapping on CMR predicts subsequent cancer therapy–related cardiac dysfunction in patients with breast cancer treated by epirubicin-based chemotherapy or left-si30
Deep learning analysis using FDG-PET to predict treatment outcome in patients with oral cavity squamous cell carcinoma30
Deep learning algorithm for detection of aortic dissection on non-contrast-enhanced CT29
Cumulative effective dose from recurrent CT examinations in Europe: proposal for clinical guidance based on an ESR EuroSafe Imaging survey29
Small single perivascular hepatocellular carcinoma: comparisons of radiofrequency ablation and microwave ablation by using propensity score analysis29
Deep learning for the rapid automatic quantification and characterization of rotator cuff muscle degeneration from shoulder CT datasets29
Machine learning–based MRI texture analysis to predict occult lymph node metastasis in early-stage oral tongue squamous cell carcinoma29
Prognostic value of myocardial extracellular volume fraction evaluation based on cardiac magnetic resonance T1 mapping with T1 long and short in hypertrophic cardiomyopathy29
Clinical utility of the Vesical Imaging-Reporting and Data System for muscle-invasive bladder cancer between radiologists and urologists based on multiparametric MRI including 3D FSE T2-weighted acqui29
Comparative performance of MRI-derived PRECISE scores and delta-radiomics models for the prediction of prostate cancer progression in patients on active surveillance29
Use of dental MRI for radiation-free guided dental implant planning: a prospective, in vivo study of accuracy and reliability29
Diffusion and perfusion MRI may predict EGFR amplification and the TERT promoter mutation status of IDH-wildtype lower-grade gliomas29
Overall survival and local recurrence following RFA, MWA, and cryoablation of very early and early HCC: a systematic review and Bayesian network meta-analysis29
Magnetic resonance imaging before breast cancer surgery: results of an observational multicenter international prospective analysis (MIPA)29
3D cephalometry on reduced FOV CBCT: skeletal class assessment through AF-BF on Frankfurt plane—validity and reliability through comparison with 2D measurements29
Noise reduction approach in pediatric abdominal CT combining deep learning and dual-energy technique29
Implementation of eHealth and AI integrated diagnostics with multidisciplinary digitized data: are we ready from an international perspective?29
Why did European Radiology reject my radiomic biomarker paper? How to correctly evaluate imaging biomarkers in a clinical setting28
The use of imaging in COVID-19—results of a global survey by the International Society of Radiology28
Deep learning–based automated detection algorithm for active pulmonary tuberculosis on chest radiographs: diagnostic performance in systematic screening of asymptomatic individuals28
Prediction of acute coronary syndrome within 3 years using radiomics signature of pericoronary adipose tissue based on coronary computed tomography angiography28
Automatic detection and classification of rib fractures based on patients’ CT images and clinical information via convolutional neural network28
Image quality of ultralow-dose chest CT using deep learning techniques: potential superiority of vendor-agnostic post-processing over vendor-specific techniques28
Convolutional neural network for discriminating nasopharyngeal carcinoma and benign hyperplasia on MRI28
Structured reporting in radiology: a systematic review to explore its potential28
A deep learning model integrating mammography and clinical factors facilitates the malignancy prediction of BI-RADS 4 microcalcifications in breast cancer screening28
Quantitation of bladder cancer for the prediction of muscle layer invasion as a complement to the vesical imaging-reporting and data system28
Preoperative prediction of postsurgical outcomes in mass-forming intrahepatic cholangiocarcinoma based on clinical, radiologic, and radiomics features28
CT-determined resectability of borderline resectable and unresectable pancreatic adenocarcinoma following FOLFIRINOX therapy28
Training opportunities of artificial intelligence (AI) in radiology: a systematic review28
A fully automatic artificial intelligence–based CT image analysis system for accurate detection, diagnosis, and quantitative severity evaluation of pulmonary tuberculosis28
Development and validation of a preoperative CT-based radiomic nomogram to predict pathology invasiveness in patients with a solitary pulmonary nodule: a machine learning approach, multicenter, diagno27
LI-RADS category 5 hepatocellular carcinoma: preoperative gadoxetic acid–enhanced MRI for early recurrence risk stratification after curative resection27
Efficacy and safety of prostatic artery embolization for benign prostatic hyperplasia: a systematic review and meta-analysis of randomized controlled trials27
Static 18F-FET PET and DSC-PWI based on hybrid PET/MR for the prediction of gliomas defined by IDH and 1p/19q status27
The diagnostic performance of CT and MRI for detecting extranodal extension in patients with head and neck squamous cell carcinoma: a systematic review and diagnostic meta-analysis27
Clinical outcomes of radiofrequency ablation for multifocal papillary thyroid microcarcinoma versus unifocal papillary thyroid microcarcinoma: a propensity-matched cohort study27
Distinguishing pancreatic cancer and autoimmune pancreatitis with in vivo tomoelastography27
Reporting standards for primary sclerosing cholangitis using MRI and MR cholangiopancreatography: guidelines from MR Working Group of the International Primary Sclerosing Cholangitis Study Group27
Development and validation of an 18F-FDG PET radiomic model for prognosis prediction in patients with nasal-type extranodal natural killer/T cell lymphoma27
Diagnostic value of ultrasonography in acute lateral and syndesmotic ligamentous ankle injuries27
Clinical and radiological changes of hospitalised patients with COVID-19 pneumonia from disease onset to acute exacerbation: a multicentre paired cohort study27
Prognostic relevance of temporal muscle thickness as a marker of sarcopenia in patients with glioblastoma at diagnosis27
Survival outcomes for surgical resection versus CT-guided percutaneous ablation for stage I non-small cell lung cancer (NSCLC): a systematic review and meta-analysis26
Chest CT for rapid triage of patients in multiple emergency departments during COVID-19 epidemic: experience report from a large French university hospital26
Performance of different Dixon-based methods for MR liver iron assessment in comparison to a biopsy-validated R2* relaxometry method26
Radiomics based on multisequence magnetic resonance imaging for the preoperative prediction of peritoneal metastasis in ovarian cancer26
Radiation dose management systems—requirements and recommendations for users from the ESR EuroSafe Imaging initiative26
Bosniak Classification version 2019: validation and comparison to original classification in pathologically confirmed cystic masses26
Late recurrence of hepatocellular carcinoma after radiofrequency ablation: a multicenter study of risk factors, patterns, and survival26
Quantification of myocardial strain assessed by cardiovascular magnetic resonance feature tracking in healthy subjects—influence of segmentation and analysis software26
Contrast agent dose reduction in computed tomography with deep learning using a conditional generative adversarial network26
Diagnostic performance of adult-based ATA and ACR-TIRADS ultrasound risk stratification systems in pediatric thyroid nodules: a systematic review and meta-analysis26
Diagnostic value of diffusion-weighted imaging with synthetic b-values in breast tumors: comparison with dynamic contrast-enhanced and multiparametric MRI26
Efficacy and safety of thermal ablation for autonomously functioning thyroid nodules: a systematic review and meta-analysis26
Accuracy of CT in a cohort of symptomatic patients with suspected COVID-19 pneumonia during the outbreak peak in Italy26
Gd-EOB-DTPA-enhanced MRI radiomics to predict vessels encapsulating tumor clusters (VETC) and patient prognosis in hepatocellular carcinoma26
Deep learning image reconstruction algorithm for pancreatic protocol dual-energy computed tomography: image quality and quantification of iodine concentration26
Skeletal muscle mass and sarcopenia can be determined with 1.5-T and 3-T neck MRI scans, in the event that no neck CT scan is performed26
MR 4D flow-based mean pulmonary arterial pressure tracking in pulmonary hypertension25
Diffusion and perfusion MRI radiomics obtained from deep learning segmentation provides reproducible and comparable diagnostic model to human in post-treatment glioblastoma25
Machine learning–based CT texture analysis to predict HPV status in oropharyngeal squamous cell carcinoma: comparison of 2D and 3D segmentation25
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