Guidelines and Experience Using Imaging Biomarker Explorer (IBEX) for Radiomics

作者： Rachel B. Ger1,2, Carlos E. Cardenas1,2, Brian M. Anderson1,2, Jinzhong Yang1,2, Dennis S. Mackin1, Lifei Zhang1, Laurence E. Court1,2,3 1Department of Radiation Physics,The University of Texas MD Anderson Cancer Center, 2UTHealth Graduate School of Biomedical Sciences,The University of Texas MD Anderson Cancer Center, 3Department of Imaging Physics,The University of Texas MD Anderson Cancer Center

简介：

Overview

IBEX is an open-source tool designed for medical imaging radiomics studies, enabling the extraction of quantitative image features related to shape and texture. This tool facilitates uncertainty analysis and model building in radiomics research.

Key Study Components

Area of Science

• Medical Imaging
• Radiomics
• Quantitative Analysis

Background

• Radiomics involves extracting features from medical images to predict patient outcomes.
• IBEX is user-friendly and has a history of application in prognostic models.
• The tool supports research in understanding tumor responses to treatments.
• It can quantify changes in tissue throughout treatment.

Purpose of Study

• To provide a comprehensive tool for extracting image features in radiomics.
• To enhance the understanding of correlations between image features and patient outcomes.
• To support uncertainty analysis in model building.

Methods Used

• Extraction of quantitative image features using IBEX.
• Analysis of shape and texture features through gray level co-occurrence matrix categories.
• Application of radiomics in assessing tumor treatment responses.
• Showcasing published works utilizing IBEX for uncertainty analysis.

Main Results

• IBEX facilitates the extraction of relevant image features for prognostic modeling.
• Demonstrated potential for providing insights into tumor phenotypes.
• Highlighted the tool's ease of use and open-source nature.
• Showcased successful applications in clinical research.

Conclusions

• IBEX is a valuable resource for researchers in the field of radiomics.
• The tool enhances the ability to analyze and interpret medical imaging data.
• It supports the development of models that can inform treatment decisions.

Frequently Asked Questions