ESR Essentials: radiomics-practice recommendations by the European Society of Medical Imaging Informatics

Joao Santinha*, Daniel Pinto dos Santos, Fabian Laqua, Jacob J. Visser, Kevin B. W. Groot Lipman, Matthias Dietzel, Michail E. Klontzas, Renato Cuocolo, Salvatore Gitto, Tugba Akinci D'Antonoli

*Corresponding author for this work

Research output: Contribution to journalReview articleAcademicpeer-review

2 Citations (Scopus)
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Abstract

Radiomics is a method to extract detailed information from diagnostic images that cannot be perceived by the naked eye. Although radiomics research carries great potential to improve clinical decision-making, its inherent methodological complexities make it difficult to comprehend every step of the analysis, often causing reproducibility and generalizability issues that hinder clinical adoption. Critical steps in the radiomics analysis and model development pipeline-such as image, application of image filters, and selection of feature extraction parameters-can greatly affect the values of radiomic features. Moreover, common errors in data partitioning, model comparison, fine-tuning, assessment, and calibration can reduce reproducibility and impede clinical translation. Clinical adoption of radiomics also requires a deep understanding of model explainability and the development of intuitive interpretations of radiomic features. To address these challenges, it is essential for radiomics model developers and clinicians to be well-versed in current best practices. Proper knowledge and application of these practices is crucial for accurate radiomics feature extraction, robust model development, and thorough assessment, ultimately increasing reproducibility, generalizability, and the likelihood of successful clinical translation. In this article, we have provided researchers with our recommendations along with practical examples to facilitate good research practices in radiomics.
Original languageEnglish
Number of pages11
JournalEuropean Radiology
DOIs
Publication statusPublished - 25 Oct 2024

Bibliographical note

This paper was endorsed by the Executive Council of the European Society of Radiology (ESR) and the European Society of Medical Imaging Informatics (EuSoMII) in September 2024.

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