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Updated: Jun 29, 2025

Guidelines and Experience Using Imaging Biomarker Explorer IBEX for Radiomics
Published on: January 8, 2018
Radiomics for clinical decision support in radiation oncology.
L Russo1, D Charles-Davies2, S Bottazzi2
1Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy; Dipartimento di Scienze Radiologiche ed Ematologiche. Università Cattolica Del Sacro Cuore, Rome, Italy.
Radiomics offers quantitative biomarkers for personalized cancer care, improving treatment response prediction in radiation oncology. Challenges in standardization and reproducibility hinder its clinical translation.
Area of Science:
- Medical imaging analysis
- Quantitative imaging biomarkers
- Radiation oncology
Background:
- Radiomics extracts quantitative features from medical images.
- It shows potential for predicting treatment response and outcomes.
- Personalized medicine in radiation oncology is a key application area.
Purpose of the Study:
- To review radiomics principles and applications in cancer management.
- To analyze the integration of radiomics into clinical decision support systems.
- To identify challenges and propose solutions for clinical translation.
Main Methods:
- Review of radiomics principles and applications.
- Analysis of radiomics integration into decision support systems.
- Discussion of challenges and potential solutions.
Main Results:
- Radiomics can enhance treatment response prediction and optimize radiation therapy.
- Standardization, reproducibility, and interpretability remain significant challenges.
- Clinical translation requires addressing these limitations.
Conclusions:
- Radiomics holds promise for personalized cancer treatment and improved outcomes.
- Standardized methodologies and improved interpretability are crucial for clinical adoption.
- Addressing current challenges will facilitate the integration of radiomics into routine clinical practice.
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