Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

An MRI-Based Intratumoral and Peritumoral 2.5D Deep Learning Model for Predicting P53-Mutated Hepatocellular Carcinoma: A Two-Center Study.

Technology in cancer research & treatment - 1 Jan 2026

Weng Jingfei, Li Pinxiong, Yao Dinghua, He Yuqing, Yang Chun, Yang Bin

Abstract excerpt

IntroductionHepatocellular carcinoma (HCC) is the most common primary liver cancer with high mortality. TP53 is the most frequently mutated tumor-suppressor gene in HCC, and P53 mutations are associated with poor differentiation, vascular invasion, and lower survival. Preoperative noninvasive detection of P53-mutated HCC is critical for treatment planning and prognostic assessment. This study aimed to develop and...

Read the complete abstract on PubMed

Topics

Adult
Aged
Female
Humans
Male
Middle Aged
Carcinoma, Hepatocellular

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Deep Learning

Dynamic Contrast Enhanced Magnetic Resonance Imaging

Liver Neoplasms

Magnetic Resonance Imaging

Mutation

Predictive Learning Models

Prognosis

Radiomics

Retrospective Studies

ROC Curve

Tumor Suppressor Protein p53

Source

Open in PubMed Open full text

Identifiers

PMID: 42712103
DOI: 10.1177/15330338261488956
PMCID: PMC13558934

Genes

TP53

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 25 Oct 2026.

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

An MRI-Based Intratumoral and Peritumoral 2.5D Deep Learning Model for Predicting P53-Mutated Hepatocellular Carcinoma: A Two-Center Study.PMID 42712103Read ↗

Deep learning-based MRI model for predicting P53-mutated hepatocellular carcinoma.Semantic proximity Read ↗

An Intra- and Inter-Modality Fusion Model Using MR Images for Prediction of Glioma Isocitrate Dehydrogenase (IDH) Mutation.Semantic proximity Read ↗

Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics.Semantic proximity Read ↗

Transformer-based Deep Learning Model Using Contrast-enhanced US for Predicting Malignancy in Breast Nodules: A Two-center StudySemantic proximity Read ↗

Prediction of p53 Expression in Intrahepatic Mass-forming Cholangiocarcinoma Using a Union Model Based on Intra- and Peritumoral MRI RadiomicsSemantic proximity Read ↗

A multimodal ConvNeXt-Tiny deep learning model for simultaneous prediction of IDH mutation and Ki-67 expression in gliomas.Semantic proximity Read ↗

Brain metastasis magnetic resonance imaging-based deep learning for predicting epidermal growth factor receptor (EGFR) mutation and subtypes in metastatic non-small cell lung cancerSemantic proximity Read ↗

Preoperative Diagnosis of Dual-Phenotype Hepatocellular Carcinoma Using Enhanced MRI Radiomics Models.Semantic proximity Read ↗

[Diagnostic value of Gd-EOB-DTPA-enhanced MRI radiomics models for dual-phenotype hepatocellular carcinoma].Semantic proximity Read ↗

A multitask classification framework based on vision transformer for predicting molecular expressions of glioma.Semantic proximity Read ↗

Machine Learning Model Integrating Clinical Features, CT Radiomics, and Transfer Learning for Predicting Aggressive Recurrence of Hepatocellular CarcinomaSemantic proximity Read ↗

Preoperative Prediction of Microvascular Invasion in small hepatocellular carcinoma (≤3 cm) by leveraging cross-phase variations of MRI contrast phasesSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.