Background: The accurate staging of liver fibrosis is crucial for managing chronic liver disease (CLD). Although magnetic resonance elastography (MRE) is the reference standard for noninvasive fibrosis assessment, its cost, specialized hardware, and operational demands restrict accessibility. In contrast, two-dimensional shear-wave elastography (2D-SWE) is more affordable, accessible, and widely integrated into routine ultrasound systems. Objective: Our aim was to determine the optimal 2D-SWE cut-offs for detecting significant fibrosis (≥F2) and evaluate its diagnostic performance across fibrosis stages. Methods: In this prospective study, 71 patients with suspected CLD underwent same-day MRE and 2D-SWE. MRE-defined cut-offs categorized fibrosis stages (≥3.5 kPa for significant fibrosis). Sensitivity, specificity, area under the receiver operating characteristic curve (AUROC), and likelihood ratios were calculated for various 2D-SWE thresholds. Results: At a 2D-SWE cut-off of 7.0 kPa, sensitivity for detecting ≥F2 fibrosis was 100% with a specificity of 85.7% and a positive likelihood ratio (LR+) of 7.0. Increasing the threshold to 8.0 kPa improved specificity to 91.8% while maintaining a sensitivity of 86.4% and achieving an AUROC of 0.89. For cirrhosis, a cut-off of 11.0 kPa achieved 100% sensitivity and 96.9% specificity. A 5.0 kPa cut-off reliably excluded abnormal stiffness with 89.1% sensitivity. Conclusions: Two-dimensional SWE is a reliable method for staging liver fibrosis. Thresholds of 7.0 kPa for screening significant fibrosis, 8.0 kPa for confirmation, and 11.0 kPa for diagnosing cirrhosis demonstrate high diagnostic accuracy. A 5.0 kPa cut-off effectively excludes abnormal liver stiffness.

Background/Objective: Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are the most common primary liver cancer. Computed tomography (CT) is the imaging modality used to evaluate liver nodules and differentiate HCC from ICC. Artificial intelligence (AI), machine learning (ML), and deep learning (DL) have been used in multiple studies in the field of radiology. The purpose of this study was to determine potential CT features for the differentiation of hepatocellular carcinoma and intrahepatic cholangiocarcinoma. Methods: Patients with radiological and pathologically confirmed diagnosis of HCC and ICC between January 2013 and December 2015 were included in this retrospective study. Two board-certified diagnostic radiologists independently reviewed multiphase CT images on a picture archiving and communication system (PACS). Arterial hyperenhancement, portal vein thrombosis, lymph node enlargement, and cirrhosis appearance were evaluated. We then calculated sensitivity, specificity, the likelihood ratio for diagnosis of HCC and ICC. Inter-observed agreement of categorical data was evaluated using Cohen’s kappa statistic (k). Results: A total of 74 patients with a pathologically confirmed diagnosis, including 48 HCCs and 26 ICC, were included in this study. Most of HCC patients showed arterial hyperenhancement at 95.8%, and interobserver agreement was moderate (k = 0.47). Arterial enhancement in ICC was less frequent, ranging from 15.4% to 26.9%, and agreement between readers was substantial (k = 0.66). The two readers showed a moderate agreement of cirrhosis appearance in both the HCC and ICC groups, k = 0.43 and k = 0.48, respectively. Cirrhosis appeared in the HCC group more frequently than the ICC group. Lymph node enlargement was more commonly seen in ICC than HCC, and agreement between the readers was almost perfect (k = 0.84). Portal vein invasion in HCC was seen in 14.6% by both readers with a substantial agreement (k = 0.66). Portal vein invasion in ICC was seen in 11.5% to 19.2% of the patients. The diagnostic performance of the two radiologists was satisfactory, with a corrected diagnosis of 87.8% and 94.6%. The two radiologists had high sensitivity in diagnosing HCCs (95.8% to 97.9%) and specificity in diagnosing ICCs (95.8% to 97.9%). Conclusions: Cirrhosis and lymph node metastasis could be ancillary and adopted in future AI training algorithms.

Background: Existing non-invasive tests (NITs) for liver fibrosis offer moderate precision and accessibility but are often limited by complexity, reducing their practicality in routine clinical use. This study aimed to evaluate the diagnostic performance of current fibrosis assessment methods and develop a novel, simplified scoring system—the Aspartate Aminotransferase (AST)-Thrombocytopenia-Albumin (ATA) score—to enhance ease of use and clinical applicability. Methods: This study examined past cases of patients with chronic liver disease (CLD) by using magnetic resonance elastography (MRE) to evaluate fibrosis stages. Serum biomarkers were collected, and common fibrosis scores were calculated. Logistic regression identified potential predictors of significant fibrosis, forming the ATA score. Diagnostic performance was assessed, and internal validation was conducted via bootstrap resampling. Results: Among 70 patients, 31.4% had significant fibrosis. Hepatitis B was the most common cause (60.0%), followed by hepatitis C (18.6%) and nonalcoholic fatty liver disease (NAFLD, 15.7%). The ATA score demonstrated an area under the receiver operating characteristic curve (AUROC) of 0.872, comparable to the AST-to-platelet ratio index (APRI; 0.858) and fibrosis-4 index (FIB-4; 0.847). The recommended cut-offs for identifying high-risk patients were ATA score ≥ 2 (specificity 95.8%, sensitivity 50.0%), APRI ≥ 0.50 (specificity 89.6%, sensitivity 68.2%), and FIB-4 ≥ 1.3 (specificity 58.3%, sensitivity 90.9%). Internal validation confirmed model robustness, with an optimism-corrected AUROC of 0.8551. Conclusions: The ATA score offers a straightforward and efficient method for detecting significant fibrosis, demonstrating comparable diagnostic capability to APRI and FIB-4, while being more user-friendly in clinical practice. A score of 0–1 indicates low risk, suitable for clinical follow-up, whereas a score of ≥2 suggests high risk, warranting further evaluation. Integrating the ATA score into clinical workflows can enhance early detection, optimize resource utilization, and improve patient care.

Purpose To evaluate the frequency and independent risk factors associated with transient severe motion artifact (TSM) during the arterial phase of gadoxetic acid–enhanced liver MRI in a Southeast Asian population. Materials and methods This retrospective study included 836 consecutive studies who underwent gadoxetic acid–enhanced MRI between October 2022 and October 2024 at a tertiary academic hospital. Two abdominal radiologists reviewed arterial phase images and graded motion artifacts using a validated 5-point scale; grades 4 and 5 were classified as TSM. Clinical and laboratory data were extracted from the electronic medical record. Univariable and multivariable logistic regression analyses were performed to identify predictors of TSM. Subgroup analyses were conducted based on age and body mass index (BMI). Results TSM artifacts were observed in 43 of 836 studies (5.14%). In multivariable analysis, older age (> 65 years) (adjusted OR 4.59; 95% CI 1.268–16.710; p = 0.021) and lower serum albumin (adjusted OR 0.33; 95% CI 0.143–0.761; p = 0.009) were independent predictors of TSM. Subgroup analyses demonstrated higher TSM incidence in patients aged ≥ 65 years (7.07% vs. 3.41%; p = 0.019) and in those with BMI > 30 kg/m² (11.11% vs. 4.73%; p = 0.052). Other variables, including sex, comorbidities, liver disease etiology, and fluid overload, were not significantly associated with TSM. Conclusion TSM during gadoxetic acid–enhanced liver MRI occurs in approximately 5% of patients and is independently associated with older age and lower serum albumin. Awareness of these risk factors can guide protocol optimization and personalized imaging strategies to improve arterial phase image quality.

To evaluate survival rates of hepatocellular carcinoma (HCC), the Chiang Mai Cancer Registry provided characteristics data of 6276 HCC patients diagnosed between 1998-2020 based on evolution of imaging diagnosis. Evolution can be separated into four cohorts, namely, cohort 1 (1990-2005) when we had ultrasound (US) and single-phase computed tomography (CT), cohort 2 (2006-2009) when one multi-phase CT and one magnetic resonance imaging (MRI) were added, cohort 3 (2010-2015) when MRI with LI-RADS was added, and finally, cohort 4 (2016-2020) when two upgraded MRIs with LI-RADS were added. Cox proportional hazard models were used to determine the relation between death and risk factors including methods of imagining diagnosis, gender, age of diagnosis, tumor stages, history of smoking and alcohol-use, while Kaplan-Meier curves were used to calculate survival rates. The median age of diagnosis was 57.0 years (IQR: 50.0-65.0) and the median survival time was 5.8 months (IQR: 1.9-26.8) during the follow-up period. In the univariable analysis, all factors were all associated with a higher risk of death in HCC patients except age of diagnosis. In a multivariable analysis, elderly age at diagnosis, regional and metastatic stages and advanced methods of imagining diagnosis during cohorts 2 and 3 were independently associated with the risk of death in HCC patients. The survival rate of patients diagnosed during cohort 4 was significantly higher than the other cohorts. As a significantly increasing survival rate of HCC patients in cohort 4, advanced methods of diagnostic imaging can be a part of the recommendation to diagnose HCC.