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A radiomics pipeline dedicated to Breast MRI: validation on a multi-scanner phantom study



Quantitative analysis in MRI is challenging due to variabilities in intensity distributions across patients, acquisitions and scanners and suffers from bias field inhomogeneity. Radiomic studies are impacted by these effects that affect radiomic feature values. This paper describes a dedicated pipeline to increase reproducibility in breast MRI radiomic studies.

Materials and methods

T1, T2, and T1-DCE MR images of two breast phantoms were acquired using two scanners and three dual breast coils. Images were retrospectively corrected for bias field inhomogeneity and further normalised using Z score or histogram matching. Extracted radiomic features were harmonised between coils by the ComBat method. The whole pipeline was assessed qualitatively and quantitatively using statistical comparisons on two series of radiomic feature values computed in the gel mimicking the normal breast tissue or in dense lesions.


Intra and inter-acquisition variabilities were strongly reduced by the standardisation pipeline. Harmonisation by ComBat lowered the percentage of radiomic features significantly different between the three coils from 87% after bias field correction and MR normalisation to 3% in the gel, while preserving or improving performance of lesion classification in the phantoms.


A dedicated standardisation pipeline was developed to reduce variabilities in breast MRI, which paves the way for robust multi-scanner radiomic studies but needs to be assessed on patient data.

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We thank Sophie Lassalle, radiographer manager, for her help in acquiring the data. We are grateful to the anonymous reviewers for their helpful comments.


Pia Akl was funded by ‘Bourse Curie M2 2018’ by Institut Curie.

Author information




Saint Martin: Conception and study design, Analysis and interpretation of data, Drafting of manuscript, Critical revision; Orlhac: Conception and study design, Analysis and interpretation of data, Critical revision; Akl: Acquisition of data, Analysis and interpretation of data, Critical revision; Khalid: Acquisition of data, Analysis and interpretation of data, Critical revision; Nioche: Analysis and interpretation of data, Critical revision; Buvat: Analysis and interpretation of data, Critical revision; Malhaire: Conception and study design, Acquisition of data, Critical revision; Frouin: Conception and study design, Analysis and interpretation of data, Critical revision.

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Correspondence to Marie-Judith Saint Martin.

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Saint Martin, MJ., Orlhac, F., Akl, P. et al. A radiomics pipeline dedicated to Breast MRI: validation on a multi-scanner phantom study. Magn Reson Mater Phy 34, 355–366 (2021).

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  • Breast
  • MRI
  • Reproducibility
  • Radiologic phantom
  • Image processing