1,721,104 research outputs found
Editorial Comment: LI-RADS Provides High Accuracy for Liver Transplant Eligibility in High-Risk Patients
No full textCombined quantitative and radiomics model can predict outcomes in patients with initially unresectable colorectal liver metastases treated with chemotherapy
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Hepatocellular carcinoma: Diagnostic imaging criteria
No full textThe diagnosis of hepatocellular carcinoma (HCC) can be reached noninvasively on imaging in patients at high risk as discussed in chapter “Hepatocellular carcinoma: Diagnostic Guidelines.” In this chapter, we describe the CT and MR imaging criteria more commonly used in the guidelines for the diagnosis and management of patients with HCC, including arterial phase hyperenhancement, washout, capsule, growth, and hypointensity on hepatobiliary phase MR imaging. The provided definitions are based on the latest version (v2018) of the liver imaging reporting and data system (LI-RADS) document (American College of Radiology 2018, https://www.acr.org/Clinical-Resources/Reporting-and-Data-Systems/LI-RADS)
ESR Essentials: diagnosis of hepatocellular carcinoma—practice recommendations by ESGAR
Full text linkHepatocellular carcinoma (HCC) is the most common primary hepatic malignancy and a leading cause of cancer related death worldwide. Current guidelines for the noninvasive diagnosis of HCC are provided by the European Association for the Study of the Liver (EASL), the American Association for the Study of Liver Diseases (AASLD) which endorsed the Liver Imaging Reporting and Data System (LI-RADS) algorithm, the Korean Liver Cancer Association-National Cancer Center (KLCA-NCC), and the Asian-Pacific Association for the Study of the Liver (APASL). These allow the diagnosis of HCC in high-risk patients in the presence of typical imaging features on contrast-enhanced CT, MRI, or contrast-enhanced ultrasound. Size, non-rim arterial phase hyperenhancement, non-peripheral washout, enhancing capsule, and growth are major imaging features and they should be combined for the diagnosis of HCC. This article provides concise and relevant practice recommendations aimed at general radiologist audience, summarizing the best practice and informing on the essential imaging criteria for the diagnosis of HCC, while also discussing the high-risk population criteria, imaging modalities, and imaging features according to the current guidelines
Reply to “Standardizing diffusion-weighted imaging in LI-RADS for diagnosis of hepatocellular carcinoma”
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LI-RADS v2018 category and imaging features: inter-modality agreement between contrast-enhanced CT, gadoxetate disodium-enhanced MRI, and extracellular contrast-enhanced MRI
No full textPurpose: To perform an intra-individual comparison of LI-RADS category and imaging features in patients at high risk of hepatocellular carcinoma (HCC) on contrast-enhanced CT, gadoxetate disodium-enhanced MRI (EOB-MRI), and extracellular agent-enhanced MRI (ECA-MRI) and to analyze the diagnostic performance of each imaging modality. Method: This retrospective study included cirrhotic patients with at least one LR-3, LR-4, LR-5, LR-M or LR-TIV observation imaged with at least two imaging modalities among CT, EOB-MRI, or ECA-MRI. Two radiologists evaluated the observations using the LI-RADS v2018 diagnostic algorithm. Reference standard included pathologic confirmation and imaging criteria according to LI-RADS v2018. Imaging features were compared between different exams using the McNemar test. Inter-modality agreement was calculated by using the weighted Cohen's kappa (k) test. Results: A total of 144 observations (mean size 34.0 ± 32.4 mm) in 96 patients were included. There were no significant differences in the detection of major and ancillary imaging features between the three imaging modalities. When considering all the observations, inter-modality agreement for category assignment was substantial between CT and EOB-MRI (k 0.60; 95%CI 0.44, 0.75), moderate between CT and ECA-MRI (k 0.46; 95%CI 0.22, 0.69) and substantial between EOB-MRI and ECA-MRI (k 0.72; 95%CI 0.59, 0.85). In observations smaller than 20 mm, inter-modality agreement was fair between CT and EOB-MRI (k 0.26; 95%CI 0.05, 0.47), moderate between CT and ECA-MRI (k 0.42; 95%CI -0.02, 0.88), and substantial between EOB-MRI and ECA-MRI (k 0.65; 95%CI 0.47, 0.82). ECA-MRI demonstrated the highest sensitivity (70%) and specificity (100%) when considering LR-5 as predictor of HCC. Conclusions: Inter-modality agreement between CT, ECA-MRI, and EOB-MRI decreases in observations smaller than 20 mm. ECA-MRI has the provided higher sensitivity for the diagnosis of HCC
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