ArticleEuropean radiology2020
Role of baseline volumetric functional MRI in predicting histopathologic grade and patients' survival in hepatocellular carcinoma.
Article in European radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 23 citations in OpenAlex.
- Interpretable machine learning based on CT-derived extracellular volume fraction to predict pathological grading of hepatocellular carcinoma.Abdominal radiology (New York) · 2024Article
- CT-based radiomics for predicting pathological grade in hepatocellular carcinoma.Frontiers in oncology · 2024Article
- Response Assessment of Primary Liver Tumors to Novel Therapies: an Imaging Perspective.Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract · 2023Review
- Non-invasive preoperative prediction of Edmondson-Steiner grade of hepatocellular carcinoma based on contrast-enhanced ultrasound using ensemble learning.Frontiers in oncology · 2023Article
- Magnetic Resonance Imaging Predictors of Hepatocellular Carcinoma Progression and Dropout in Patients in Liver Transplantation Waiting List.Transplantation direct · 2022Article
- Role of MRI-Derived Radiomics Features in Determining Degree of Tumor Differentiation of Hepatocellular Carcinoma.Diagnostics (Basel, Switzerland) · 2022Article
- Clinical and imaging features preoperative evaluation of histological grade and microvascular infiltration of hepatocellular carcinoma.BMC gastroenterology · 2022Article
- Noninvasively predict the micro-vascular invasion and histopathological grade of hepatocellular carcinoma with CT-derived radiomics.European journal of radiology open · 2022Article
- Whole tumor volumetric ADC analysis: relationships with histopathological differentiation of hepatocellular carcinoma.Abdominal radiology (New York) · 2021Article
- Current updates in machine learning in the prediction of therapeutic outcome of hepatocellular carcinoma: what should we know?Insights into imaging · 2021Review
- Integrating baseline MR imaging biomarkers into BCLC and CLIP improves overall survival prediction of patients with hepatocellular carcinoma (HCC).European radiology · 2021Article
- Post-TACE changes in ADC histogram predict overall and transplant-free survival in patients with well-defined HCC: a retrospective cohort with up to 10 years follow-up.European radiology · 2021Article
- A Reliable Prognostic Model for HCC Using Histological Grades and the Expression Levels of Related Genes.Journal of oncology · 2021Article
- Initial Incomplete Thermal Ablation Is Associated With a High Risk of Tumor Progression in Patients With Hepatocellular Carcinoma.Frontiers in oncology · 2021Article
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11 authors at 1 institution in 1 country.
Funding
Abstract
objectivesWe aimed to evaluate the role of volumetric ADC (vADC) and volumetric venous enhancement (vVE) in predicting the grade of tumor differentiation in hepatocellular carcinoma (HCC).
methodsThe study population included 136 HCC patients (188 lesions) who had baseline MR imaging and histopathological report. Measurements of vVE and vADC were performed on baseline MRI. Tumors were histologically classified into low-grade and high-grade groups. The parameters between the two groups were compared using Mann-Whitney U and chi-square tests for continuous and categorical parameters, respectively. Area under receiver operating characteristic (AUROC) was calculated to investigate the accuracy of vADC and vVE. Logistic regression and multivariable Cox regression were used to unveil the potential parameters associated with high-grade HCC and patient's survival, respectively.
resultsLesions with higher vADC values and a higher absolute vADC skewness were more likely to be high grade on histopathology assessment (p = 0.001 and p = 0.0291, respectively). Also, vVE showed a trend to be higher in low-grade lesions (p = 0.079). Adjusted multivariable model including vADC, vVE, and vADC skewness could strongly predict HCC degree of differentiation (AUROC = 83%). Additionally, a higher Child-Pugh score (HR = 2.39 [p = 0.02] for score 2 and HR = 3.47 [p = 0.001] for score 3), vADC skewness (HR = 1.52, p = 0.02; per increments in skewness), and tumor volume (HR = 1.1, p = 0.001; per 100 cm
conclusionsvADC and vVE have the potential to accurately predict HCC differentiation. Additionally, some imaging features in combination with patients' clinical characteristics can predict patient survival. KEY POINTS: • Volumetric functional MRI metrics can be considered as non-invasive measures for determining tumor histopathology in HCC. • Estimating patient survival based on clinical and imaging parameters can be used for modifying management approach and preventing unnecessary adverse events.
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