AIMC Topic: Ki-67 Antigen

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Digital quantification of Ki67 and PRAME in challenging melanocytic lesions - A novel diagnostic tool.

Pathology, research and practice Mar 31, 2025
The interpretation of immunohistochemical markers in melanocytic lesions possesses difficulties due to expression in non-melanocytic cells and the time-consuming, non-reproducible nature of manual assessment. A digital tool that accurately quantifies...
Humans Biomarkers, Tumor Male Middle Aged Antigens, Neoplasm Immunohistochemistry Female Melanoma Skin Neoplasms Adult Ki-67 Antigen SOXE Transcription Factors
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Toward Accurate Deep Learning-Based Prediction of Ki67, ER, PR, and HER2 Status From H&E-Stained Breast Cancer Images.

Applied immunohistochemistry & molecular morphology : AIMM Mar 27, 2025
Despite improvements in machine learning algorithms applied to digital pathology, only moderate accuracy, to predict molecular information from histology alone, has been achieved so far. One of the obstacles is the lack of large data sets to properly...
Staining and Labeling Immunohistochemistry Receptor, ErbB-2 Receptors, Estrogen Female Receptors, Progesterone Ki-67 Antigen Breast Neoplasms Humans Biomarkers, Tumor Deep Learning Image Processing, Computer-Assisted
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Multi-center study: ultrasound-based deep learning features for predicting Ki-67 expression in breast cancer.

Scientific reports Mar 25, 2025
Applying deep learning algorithms to mine ultrasound features of breast cancer and construct a machine learning model that accurately predicts Ki-67 expression level. This multi-center retrospective study analyzed clinical and ultrasound data from 92...
Ultrasonography, Mammary Ki-67 Antigen Middle Aged Deep Learning Ultrasonography Support Vector Machine Female Aged Adult Breast Neoplasms Humans Algorithms Retrospective Studies
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Preoperative Assessment of Ki-67 Labeling Index in Pituitary Adenomas Using Delta-Radiomics Based on Dynamic Contrast-Enhanced MRI.

Journal of magnetic resonance imaging : JMRI Mar 17, 2025
BACKGROUND: Ki-67 labeling index (Ki-67 LI) is a proliferation marker that is correlated with aggressive behavior and prognosis of pituitary adenomas (PAs). Dynamic contrast-enhanced MRI (DCE-MRI) may potentially contribute to the preoperative assess...
Male Female Humans Magnetic Resonance Imaging Reproducibility of Results Middle Aged Retrospective Studies Pituitary Neoplasms Aged ROC Curve Adenoma Adult Contrast Media Preoperative Care Radiomics Ki-67 Antigen
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DCE-MRI based deep learning analysis of intratumoral subregion for predicting Ki-67 expression level in breast cancer.

Magnetic resonance imaging Mar 13, 2025
OBJECTIVE: To evaluate whether deep learning (DL) analysis of intratumor subregion based on dynamic contrast-enhanced MRI (DCE-MRI) can help predict Ki-67 expression level in breast cancer.
Breast Image Interpretation, Computer-Assisted Ki-67 Antigen Dynamic Contrast Enhanced Magnetic Resonance Imaging Middle Aged Deep Learning Contrast Media Magnetic Resonance Imaging Humans Algorithms Retrospective Studies Female Aged Adult Breast Neoplasms
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CT-based machine learning radiomics predicts Ki-67 expression level and its relationship with overall survival in resectable pancreatic ductal adenocarcinoma.

Abdominal radiology (New York) Jan 22, 2025
BACKGROUND: The prognostic prediction of pancreatic ductal adenocarcinoma (PDAC) remains challenging. This study aimed to develop a radiomics model to predict Ki-67 expression status in PDAC patients using radiomics features from dual-phase enhanced ...
Tomography, X-Ray Computed Female Aged Aged, 80 and over Adult Humans Machine Learning Prognosis Retrospective Studies Nomograms Pancreatic Neoplasms Predictive Value of Tests Carcinoma, Pancreatic Ductal Ki-67 Antigen Survival Rate Radiomics Male Middle Aged
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Interpretable CT Radiomics-based Machine Learning Model for Preoperative Prediction of Ki-67 Expression in Clear Cell Renal Cell Carcinoma.

Academic radiology Jan 9, 2025
RATIONALE AND OBJECTIVES: To develop and externally validate interpretable CT radiomics-based machine learning (ML) models for preoperative Ki-67 expression prediction in clear cell renal cell carcinoma (ccRCC).
Kidney Neoplasms Retrospective Studies Carcinoma, Renal Cell Tomography, X-Ray Computed Ki-67 Antigen Female Aged Radiomics Adult Male Humans Middle Aged Machine Learning Radiographic Image Interpretation, Computer-Assisted
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The value of multiparametric MRI radiomics and machine learning in predicting preoperative Ki-67 expression level in breast cancer.

BMC medical imaging Jan 7, 2025
OBJECTIVE: This study was to develop a multi-parametric MRI radiomics model to predict preoperative Ki-67 status.
Machine Learning Algorithms Retrospective Studies Female Aged Adult Sensitivity and Specificity Breast Neoplasms Radiomics Humans Middle Aged Ki-67 Antigen Multiparametric Magnetic Resonance Imaging
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Prediction of gene expression-based breast cancer proliferation scores from histopathology whole slide images using deep learning.

BMC cancer Dec 11, 2024
BACKGROUND: In breast cancer, several gene expression assays have been developed to provide a more personalised treatment. This study focuses on the prediction of two molecular proliferation signatures: an 11-gene proliferation score and the MKI67 pr...
Biomarkers, Tumor Middle Aged Cell Proliferation Gene Expression Profiling Humans Female Ki-67 Antigen Deep Learning Prognosis Aged Adult Gene Expression Regulation, Neoplastic Breast Neoplasms
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Interpretable machine learning model based on CT semantic features and radiomics features to preoperatively predict Ki-67 expression in gastrointestinal stromal tumors.

Scientific reports Nov 26, 2024
To develop and validate a machine learning (ML) model which combined computed tomography (CT) semantic and radiomics features to preoperatively predict Ki-67 expression in gastrointestinal stromal tumors (GISTs) patients. We retrospectively collected...
Male Female Semantics Humans Middle Aged Aged Gastrointestinal Stromal Tumors Machine Learning ROC Curve Ki-67 Antigen Adult Retrospective Studies Gastrointestinal Neoplasms Radiomics Tomography, X-Ray Computed
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