Trial reportCancer immunology, immunotherapy : CII2022
Imaging features of gadoxetic acid-enhanced MR imaging for evaluation of tumor-infiltrating CD8 cells and PD-L1 expression in hepatocellular carcinoma.
Trial report in Cancer immunology, immunotherapy : CII, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 30 citations in OpenAlex.
- A Computed Tomography Radiomics Approach for Assessing the T Cell-Inflamed Gene Expression Profile in Hepatocellular Carcinoma and Its Association With Immunotherapy Response.Health care science · 2026Article
- Artificial intelligence and personalised medicine in liver cancer.Journal of hepatology · 2026Review
- Gd-EOB-DTPA-Enhanced Magnetic Resonance Imaging for Predicting Immunotherapy Response in Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis.Liver cancer · 2026Review
- Noninvasive prediction of the clinical benefit of immunotherapy in hepatocellular carcinoma.Journal of gastroenterology · 2025Review
- Prognostic and predictive imaging markers of hepatocellular carcinoma: a pictorial essay.Insights into imaging · 2025Article
- Prediction of PD-L1 expression and prognosis of mass-forming intrahepatic cholangiocarcinoma based on preoperative magnetic resonance imaging.Quantitative imaging in medicine and surgery · 2025Article
- Gadoxetic Acid-Enhanced Magnetic Resonance Imaging Features Can Predict Immune-Excluded Phenotype of Hepatocellular Carcinoma.Liver cancer · 2025Article
- Application of Intravoxel Incoherent Motion in the Prediction of Intra-Tumoral Tertiary Lymphoid Structures in Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2025Article
- Article
- Hepatobiliary-phase gadolinium ethoxybenzyl-diethylenetriaminepentaacetic acid MRI for pretreatment prediction of efficacy-to-standard-therapies based on Barcelona Clinic Liver Cancer algorithm: an up-to-date review.European radiology · 2023Review
- Reproducibility and usefulness of quantitative apparent diffusion coefficient measurements for predicting program death-ligand 1 expression in nasopharyngeal carcinoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2023Article
- 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
- The Era of Immunotherapy in Hepatocellular Carcinoma: The New Mission and Challenges of Magnetic Resonance Imaging.Cancers · 2023Review
- Novel Computed-Tomography-Based Transformer Models for the Noninvasive Prediction of PD-1 in Pre-Operative Settings.Cancers · 2023Article
- Preoperative prediction of glypican-3 positive expression in solitary hepatocellular carcinoma on gadoxetate-disodium enhanced magnetic resonance imaging.Frontiers in immunology · 2022Article
- Systemic therapies in hepatocellular carcinoma: Existing and emerging biomarkers for treatment response.Frontiers in oncology · 2022Review
- Assessing PD-L1 Expression Level via Preoperative MRI in HCC Based on Integrating Deep Learning and Radiomics Features.Diagnostics (Basel, Switzerland) · 2021Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
backgroundTumor-infiltrating CD8 cells and expression of programmed cell death ligand 1 (PD-L1) are immune checkpoint markers in patients with hepatocellular carcinoma (HCC). We aimed to determine the ability of preoperative gadoxetic acid-enhanced magnetic resonance imaging (MRI) findings to predict CD8 cell density and PD-L1 expression in HCC.
methodsA total of 120 patients with HCC who underwent 3.0-T gadoxetic acid-enhanced MRI before curative resection from January 2016 to June 2020 were enrolled and divided into a training set (n = 84) and a testing set (n = 36). Thirty-four patients with advanced stage HCC who received anti-PD-1 inhibitor between January 2017 and April 2020 and underwent pretreated gadoxetic acid-enhanced MRI scans were enrolled in an independent validation set. PD-L1 expression and CD8 cell infiltration were assessed with immunohistochemical staining, respectively. Two radiologists blinded to pathology results evaluated the pretreated MR features in consensus. Logistic regression and the receiver operating characteristic curve (ROC) analyses were used to determine the value of image features to predict high CD8 cell density, PD-L1 positivity and the combination of high CD8 cell density and PD-L1 positivity in HCC in the training set and validated the findings in the testing set. The associations of MRI predictors with the objective response to immunotherapy were assessed in the independent validation.
resultsIn the training set, the independent MRI predictors were irregular tumor margin (ITM, P = 0.008) and peritumoral low signal intensity (PLSI) on hepatobiliary phase (HBP) images (P < 0.001) for PD-L1 positivity, absence of an enhancing capsule (AEC, P = 0.001) and PLSI on HBP images (P = 0.025) for high CD8 cell density, and PLSI on HBP images (P = 0.001) and ITM (P = 0.023) for the both. The area under the curves (AUCs) of the predictive models for evaluating PD-L1 positivity, high CD8 cell density and the combination of high CD8 cell density and PD-L1 positivity were 0.810 and 0.809, 0.740 and 0.728, and 0.809 and 0.874 in the training and testing set, respectively. The objective response was demonstrated to be associated with the combination of PLSI on HBP images and ITM (PHI, P = 0.004), and the combination of PLSI on HBP images and AEC (PHA, P = 0.012) in the independent validation set.
conclusionsPretreated MRI features have the potential to identify patients with HCC in an immune-activated state and predict outcomes of immunotherapy. Trial registration The study was retrospectively registered on March 5, 2020 with registration no. [2020] 02-012-01.
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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.