[HTML][HTML] Introduction to radiomics for a clinical audience

C McCague, S Ramlee, M Reinius, I Selby, D Hulse… - Clinical Radiology, 2023 - Elsevier
Radiomics is a rapidly developing field of research focused on the extraction of quantitative
features from medical images, thus converting these digital images into minable, high …

MRI‐based radiomics and deep learning in biological characteristics and prognosis of hepatocellular carcinoma: Opportunities and challenges

T Xia, B Zhao, B Li, Y Lei, Y Song… - Journal of Magnetic …, 2024 - Wiley Online Library
Hepatocellular carcinoma (HCC) is the fifth most common malignancy and the third leading
cause of cancer‐related death worldwide. HCC exhibits strong inter‐tumor heterogeneity …

Deep learning nomogram based on Gd-EOB-DTPA MRI for predicting early recurrence in hepatocellular carcinoma after hepatectomy

M Yan, X Zhang, B Zhang, Z Geng, C Xie, W Yang… - European …, 2023 - Springer
Objectives The accurate prediction of post-hepatectomy early recurrence in patients with
hepatocellular carcinoma (HCC) is crucial for decision-making regarding postoperative …

Diagnostic evaluation and ablation treatments assessment in hepatocellular carcinoma

V Granata, R Grassi, R Fusco, A Belli, C Cutolo… - Infectious Agents and …, 2021 - Springer
This article provides an overview of diagnostic evaluation and ablation treatment
assessment in Hepatocellular Carcinoma (HCC). Only studies, in the English language from …

Application of radiomics in the efficacy evaluation of transarterial chemoembolization for hepatocellular carcinoma: a systematic review and meta-analysis

Y Wang, M Li, Z Zhang, M Gao, L Zhao - Academic radiology, 2024 - Elsevier
Rationale and Objectives This meta-analysis was aimed at evaluating the predictive value of
radiomics in the context of transarterial chemoembolization (TACE) therapeutic response …

Radiomics analysis of pretreatment MRI in predicting tumor response and outcome in hepatocellular carcinoma with transarterial chemoembolization: a two-center …

QP Liu, KL Yang, X Xu, XS Liu, JR Qu, YD Zhang - Abdominal Radiology, 2022 - Springer
Background and objective To develop a machine-learning model by integrating clinical and
imaging modalities for predicting tumor response and survival of hepatocellular carcinoma …

The role of radiomics and AI technologies in the segmentation, detection, and management of hepatocellular carcinoma

D Fahmy, A Alksas, A Elnakib, A Mahmoud, H Kandil… - Cancers, 2022 - mdpi.com
Simple Summary As a primary hepatic tumor, hepatocellular carcinoma (HCC) is the most
prevalent kind. Recent developments in magnetic resonance imaging (MRI) and computed …

Progress of MRI radiomics in hepatocellular carcinoma

XQ Gong, YY Tao, YK Wu, N Liu, X Yu, R Wang… - Frontiers in …, 2021 - frontiersin.org
Background Hepatocellular carcinoma (HCC) is the sixth most common cancer in the world
and the third leading cause of cancer-related death. Although the diagnostic scheme of HCC …

[HTML][HTML] Current status and future perspectives of radiomics in hepatocellular carcinoma

J Miranda, N Horvat, GM Fonseca… - World journal of …, 2023 - ncbi.nlm.nih.gov
Given the frequent co-existence of an aggressive tumor and underlying chronic liver
disease, the management of hepatocellular carcinoma (HCC) patients requires experienced …

Analysis of the correlation and prognostic significance of tertiary lymphoid structures in breast cancer: a radiomics‐clinical integration approach

K Li, J Ji, S Li, M Yang, Y Che, Z Xu… - Journal of Magnetic …, 2024 - Wiley Online Library
Background Tertiary lymphoid structures (TLSs) are potential prognostic indicators.
Radiomics may help reduce unnecessary invasive operations. Purpose To analyze the …