ArticleCancers2022
Added Value of Viscoelasticity for MRI-Based Prediction of Ki-67 Expression of Hepatocellular Carcinoma Using a Deep Learning Combined Radiomics (DLCR) Model.
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.
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Who cites it
30 citing papers in PubMed, 2 syntheses or guidelines pooled it, 46 citations in OpenAlex.
- Changes in Tissue Fluidity Predict Tumor Aggressiveness In Vivo.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Pooled it
- Diagnostic value of radiomics in predicting Ki-67 and cytokeratin 19 expression in hepatocellular carcinoma: a systematic review and meta-analysis.Frontiers in oncology · 2023Pooled it
- [Research advances of magnetic resonance elastography for assessing the bioinvasiveness in hepatocellular carcinoma].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2026Review
- Ki-67 expression correlates with hepatocellular carcinoma recurrence and is predictable using radiomics features.Abdominal radiology (New York) · 2026Article
- Preliminary quantitative assessment of liver and spleen MR imaging and elastography in clinically significant portal hypertension.Scientific reports · 2026Article
- Predictive Efficacy of a Combined Triphasic CT Radiomics and Clinical Feature Model for Ki-67 Expression in Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2026Article
- CT-Based Radiomics for Non-Invasive Prediction of Ki-67 Expression in Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2026Article
- The relationship between serum levels of miR-342 and miR-148a and acute lung injury in sepsis patients.Open medicine (Warsaw, Poland) · 2026Article
- Preoperative Multifrequency MR Elastography for Stratifying Wnt/β-Catenin Pathway and Microvascular Invasion Phenotypes in Hepatocellular Carcinoma.Journal of magnetic resonance imaging : JMRI · 2025Article
- Preoperative model for predicting early recurrence in hepatocellular carcinoma patients using radiomics and deep learning: A multicenter study.World journal of gastrointestinal oncology · 2025Article
- Magnetic Resonance Elastography Combined With PI-RADS v2.1 for the Identification of Clinically Significant Prostate Cancer.Journal of magnetic resonance imaging : JMRI · 2025Article
- Impact of frailty on the long-term prognosis of the elderly with hepatocellular carcinoma treated with transarterial chemoembolization.Scientific reports · 2025Article
- Imaging-Based Prediction of Ki-67 Expression in Hepatocellular Carcinoma: A Retrospective Study.Cancer medicine · 2025Article
- Histogram analysis of multiple mathematical diffusion-weighted imaging models for preoperative prediction of Ki-67 expression in hepatocellular carcinoma.Frontiers in oncology · 2025Article
- Triphasic CT Radiomics Model for Preoperative Prediction of Hepatocellular Carcinoma Pathological Grading.Journal of hepatocellular carcinoma · 2025Article
- Radiomics predicting immunohistochemical markers in primary hepatic carcinoma: Current status and challenges.Heliyon · 2024Review
- Role of the Clinical Features and MRI Parameters on Ki-67 Expression in Hepatocellular Carcinoma Patients: Development of a Predictive Nomogram.Journal of gastrointestinal cancer · 2024Article
- [Research progress of radiomics in hepatocellular carcinoma].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2024Review
- Predicting Ki-67 expression in hepatocellular carcinoma: nomogram based on clinical factors and contrast-enhanced ultrasound radiomics signatures.Abdominal radiology (New York) · 2024Article
- Ultrasound-based deep learning radiomics model for differentiating benign, borderline, and malignant ovarian tumours: a multi-class classification exploratory study.BMC medical imaging · 2024Article
Corrections and comments
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Authors and funding
10 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aimed to explore the added value of viscoelasticity measured by magnetic resonance elastography (MRE) in the prediction of Ki-67 expression in hepatocellular carcinoma (HCC) using a deep learning combined radiomics (DLCR) model. This retrospective study included 108 histopathology-proven HCC patients (93 males; age, 59.6 ± 11.0 years) who underwent preoperative MRI and MR elastography. They were divided into training (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.