Back to search

Article

Prediction of Ki-67 expression in invasive breast cancer with dual-modality radiomics

2025-12-01

Abstract excerpt

<title>Abstract</title> <p> <bold>Background</bold> Ki-67 expression, a critical biomarker for tumor aggressiveness and proliferation in invasive breast cancer, is traditionally assessed via invasive biopsies, which suffer from sampling variability and limit serial monitoring. This study aimed to develop radiomics models using ultrasound (US) and mammography (MG) features to predict Ki-67 expression, hypothesiz...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
c8ab691e-a9ba-5e4c-92f5-1a2be3c05515
DOI
10.21203/rs.3.rs-7771373/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Prediction of Ki-67 expression in invasive breast cancer with dual-modality radiomicsDOI 10.21203/rs.3.rs-7771373/v1
The Ki67 index of preoperative breast cancer puncture is correlated with lymph node metastasis, ER, PR and AR expression: A retrospective study of real world dataSemantic proximity
Integrating clinical data and ultrasonographic imaging for non-invasive prediction of HER2 status in breast cancerSemantic proximity
Development and Validation of a CEUS-Based Intratumoral–Peritumoral Radiomics Nomogram for Preoperative Prediction of HER2-Low Breast CancerSemantic proximity
Multiparametric MRI-based radiomics combined with machine learning for preoperative differentiation of luminal A and luminal B breast cancer: a multicenter studySemantic proximity
Value of intratumoral combined with peritumoral radiomics model in the prediction of Ki-67 expression in lung adenocarcinoma: a multi-center studySemantic proximity
A nomogram model combining ultrasound-based radiomics features and clinicopathological factors to identify germline BRCA1/2 mutation in invasive breast cancer patientsSemantic proximity
Prediction of clinical phenotypes in invasive breast carcinomas from the integration of radiomics and genomics dataSemantic proximity
Radiomic Features Based on Multi-sequence MRI Predict Immunohistochemical Biomarkers of Endometrial CancerSemantic proximity
Multi-omics investigation on the prognostic and predictive factors in metastatic breast cancer using data from Phase III ribociclib clinical trials: A statistical and machine learning analysis planSemantic proximity
Development and validation of a multimodal interpretable machine learning model with SHAP for malignancy risk prediction in Bethesda III thyroid nodules: a dual-center retrospective cohort studySemantic proximity
A Nomogram for Predicting Mammaprint Results in Women with T1-3N0-1M0 Hormone Receptor-Positive and Human Epidermal Growth Factor Receptor-2-Negative Breast CancerSemantic proximity
Ultrasound Characteristics in Predicting Molecular Subtypes of Breast Cancer: A Retrospective AnalysisSemantic proximity
Select a neighboring publication to make it the new centre.