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

Identification of Predominant Histopathological Growth Patterns of Colorectal Liver Metastasis by Multi-Habitat and Multi-Sequence Based Radiomics Analysis

14 Aug 2020

Abstract excerpt

Purpose: Developing an MRI-based radiomics model to effectively and accurately predict the predominant histopathologic growth patterns (HGPs) of colorectal liver metastases (CRLMs). Materials and Methods: In this study, 182 resected and histopathological proven CRLMs of chemotherapy-naive patients from two institutions, including 123 replacement CRLMs and 59 desmoplastic CRLMs, were retrospectively analyzed....

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Hepatocellular Carcinoma Treatment and Prognosis
Share to Radiomics and Machine Learning in Medical Imaging

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 32923388
DOI: 10.3389/fonc.2020.01363

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Identification of Predominant Histopathological Growth Patterns of Colorectal Liver Metastasis by Multi-Habitat and Multi-Sequence Based Radiomics AnalysisPMID 32923388Read ↗

MRI T2WI-based radiomics combined with KRAS gene mutation constructed models for predicting liver metastasis in rectal cancer.Semantic proximity Read ↗

Prognostic value and spatial transcriptomic landscape of histopathological growth patterns in synchronous colorectal liver metastases.Semantic proximity Read ↗

Prediction of Key Pathological Features in Colorectal Cancer Using a CT-derived Intratumoral Heterogeneity Score (ITHscore)Semantic proximity Read ↗

Radiological and pathological integration predicts the efficacy of bevacizumab with chemotherapy in colorectal cancer liver metastasesSemantic proximity Read ↗

Magnetic resonance imaging based radiomics for predicting pathogenetic features and survival in rectal cancer.Semantic proximity Read ↗

Histopathological growth patterns of liver metastases - a retrospective, consecutive, single- center, pilot study and literature review of non-colorectal carcinoma metastasis studiesSemantic proximity Read ↗

Radiomics and Machine Learning for prediction of two-year disease-specific mortality and KRAS mutation status in metastatic colorectal cancer.Semantic proximity Read ↗

Prognostic Value of Multiparametric MRI-Based Radiomics model: Potential Role for Chemotherapeutic Benefits in Locally Advanced Rectal CancerSemantic proximity Read ↗

Comprehensive Overview of Molecular, Imaging, and Therapeutic Challenges in Rectal Mucinous AdenocarcinomaSemantic proximity Read ↗

Histopathological growth patterns determines the outcomes of colorectal cancer liver metastasis that have undergone liver resectionSemantic proximity Read ↗

The adiposity of CRLM before targeted therapy initiation may serve as a marker to distinguish KRAS mutation status：A retrospective studySemantic proximity Read ↗

MRI-based Delta-Radiomic Features for Prediction of Local Control in Liver Lesions Treated with Stereotactic Body Radiation TherapySemantic proximity Read ↗

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