¹⁹F MRI radiomic features: in vitro and in vivo repeatability

KEY POINTS: We analyzed 194 ¹⁹F MRI scans and 772 segments obtained in phantoms at 7 T. Cross-agent stability identified 466 radiomic features meeting concordance correlation coefficient ≥ 0.85 and normalized dynamic range ≥ 0.90. Of these phantom-stable features, 401 of 466 remained stable in vivo in a tumor mouse model. Intensity features were most repeatable, while shape features were least stable across sessions. Median concordance correlation coefficient dropped from 0.886 intrasession to 0.683 intersession.

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Publication Details

Journal
European Radiology Experimental
Published
2026-03-16
DOI
https://doi.org/10.1186/s41747-026-00694-2
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
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article

¹⁹F MRI radiomic features: in vitro and in vivo repeatability

Mariah R. R. Daal, Mangala Srinivas, Manon Boeije, Leila Akkari et al.
European Radiology Experimental
Radiomics and Machine Learning in Medical Imaging
article

¹⁹F MRI radiomic features: in vitro and in vivo repeatability

Mariah R. R. Daal, Mangala Srinivas, Manon Boeije, Leila Akkari, Serena Vegna, Sajjad Rostami, Zuhir Bodalal, Olga Maxouri, Diana Ivonne Rodríguez Sánchez, R.G.H. Beets-Tan, Natalie Proost, Stephan Ursprung, Marieke van de Ven
article en

Abstract

KEY POINTS: We analyzed 194 ¹⁹F MRI scans and 772 segments obtained in phantoms at 7 T. Cross-agent stability identified 466 radiomic features meeting concordance correlation coefficient ≥ 0.85 and normalized dynamic range ≥ 0.90. Of these phantom-stable features, 401 of 466 remained stable in vivo in a tumor mouse model. Intensity features were most repeatable, while shape features were least stable across sessions. Median concordance correlation coefficient dropped from 0.886 intrasession to 0.683 intersession.

European Radiology ExperimentalVol. 10(1)
University of Southern Denmark (DK), Maastricht University Medical Centre (NL), The Netherlands Cancer Institute (NL), Maastricht University (NL), Oncode Institute (NL), Cancer Genomics Centre (NL), University of Tübingen (DE), Wageningen University & Research (NL)
Openalex Percentile: Top 21%
Radiomics and Machine Learning in Medical Imaging
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