ArticleChinese journal of cancer research = Chung-kuo yen cheng yen chiu2019
Texture analysis on gadoxetic acid enhanced-MRI for predicting Ki-67 status in hepatocellular carcinoma: A prospective study.
Article in Chinese journal of cancer research = Chung-kuo yen cheng yen chiu, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
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30 citing papers in PubMed, 1 synthesis or guideline pooled it, 51 citations in OpenAlex.
- 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
- Habitat analysis and other AI technologies for Ki-67 prediction in hepatocellular carcinoma: a multi-center study.BMC cancer · 2026Article
- From texture analysis to artificial intelligence: global research landscape and evolutionary trajectory of radiomics in hepatocellular carcinoma.Discover oncology · 2025Article
- Prediction of Ki-67 expression in hepatocellular carcinoma with machine learning models based on intratumoral and peritumoral radiomic features.World journal of gastrointestinal oncology · 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
- 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 and prospects of the application of radiographic imaging in the precise diagnosis and treatment of hepatocellular carcinoma].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2024Review
- Current status of magnetic resonance imaging radiomics in hepatocellular carcinoma: A quantitative review with Radiomics Quality Score.World journal of gastroenterology · 2024Review
- A gadoxetic acid-enhanced MRI-based model using LI-RADS v2018 features for preoperatively predicting Ki-67 expression in hepatocellular carcinoma.BMC medical imaging · 2024Article
- Multiparametric MRI-based radiomics approach with deep transfer learning for preoperative prediction of Ki-67 status in sinonasal squamous cell carcinoma.Frontiers in oncology · 2024Article
- Added value of CE-CT radiomics to predict high Ki-67 expression in hepatocellular carcinoma.BMC medical imaging · 2023Article
- Development and validation of combined Ki67 status prediction model for intrahepatic cholangiocarcinoma based on clinicoradiological features and MRI radiomics.La Radiologia medica · 2023Article
- Current status and future perspectives of radiomics in hepatocellular carcinoma.World journal of gastroenterology · 2023Review
- Gadoxetic acid-enhanced MRI combined with T1 mapping and clinical factors to predict Ki-67 expression of hepatocellular carcinoma.Frontiers in oncology · 2023Article
- Role of Machine Learning in Precision Oncology: Applications in Gastrointestinal Cancers.Cancers · 2022Review
- Prediction of Histological Grades and Ki-67 Expression of Hepatocellular Carcinoma Based on Sonazoid Contrast Enhanced Ultrasound Radiomics Signatures.Diagnostics (Basel, Switzerland) · 2022Article
- Prediction of the Ki-67 expression level and prognosis of gastrointestinal stromal tumors based on CT radiomics nomogram.International journal of computer assisted radiology and surgery · 2022Article
- Radiomics signature: A potential biomarker for β-arrestin1 phosphorylation prediction in hepatocellular carcinoma.World journal of gastroenterology · 2022Article
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10 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
objectiveTo investigate the value of whole-lesion texture analysis on preoperative gadoxetic acid enhanced magnetic resonance imaging (MRI) for predicting tumor Ki-67 status after curative resection in patients with hepatocellular carcinoma (HCC).
methodsThis study consisted of 89 consecutive patients with surgically confirmed HCC. Texture features were extracted from multiparametric MRI based on whole-lesion regions of interest. The Ki-67 status was immunohistochemical determined and classified into low Ki-67 (labeling index ≤15%) and high Ki-67 (labeling index >15%) groups. Least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were applied for generating the texture signature, clinical nomogram and combined nomogram. The discrimination power, calibration and clinical usefulness of the three models were evaluated accordingly. Recurrence-free survival (RFS) rates after curative hepatectomy were also compared between groups.
resultsA total of 13 texture features were selected to construct a texture signature for predicting Ki-67 status in HCC patients (C-index: 0.878, 95% confidence interval: 0.791-0.937). After incorporating texture signature to the clinical nomogram which included significant clinical variates (AFP, BCLC-stage, capsule integrity, tumor margin, enhancing capsule), the combined nomogram showed higher discrimination ability (C-index: 0.936
conclusionsTexture analysis on gadoxetic acid enhanced MRI can serve as a noninvasive approach to preoperatively predict Ki-67 status of HCC after curative resection. The combination of texture signature and clinical factors demonstrated the potential to further improve the prediction performance.
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