Radiomics-based aortic flow profile characterization with 4D phase-contrast MRI

Markus Huellebrand; Lina Jarmatz; Chiara Manini; Ann Laube; Matthias Ivantsits; Jeanette Schulz-Menger; Sarah Nordmeyer; Andreas Harloff; Jochen Hansmann; Sebastian Kelle; Anja Hennemuth

doi:10.3389/fcvm.2023.1102502

Radiomics-based aortic flow profile characterization with 4D phase-contrast MRI

Front Cardiovasc Med. 2023 Apr 3:10:1102502. doi: 10.3389/fcvm.2023.1102502. eCollection 2023.

Authors

Markus Huellebrand^{1

2

3}, Lina Jarmatz^{1

2}, Chiara Manini^{1

2}, Ann Laube^{1

2

4}, Matthias Ivantsits^{1

2}, Jeanette Schulz-Menger^{5

4

6}, Sarah Nordmeyer^{1

2

4}, Andreas Harloff^{7

8}, Jochen Hansmann⁹, Sebastian Kelle^{1

2

4}, Anja Hennemuth^{1

2

3

4

10}

Affiliations

¹ Deutsches Herzzentrum der Charité, Berlin, Germany.
² Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany.
³ Fraunhofer Institute for Digital Medicine MEVIS, Berlin, Germany.
⁴ DZHK (German Centre for Cardiovascular Research), partner site Berlin, Berlin, Germany.
⁵ Charité Universitätsmedizin Berlin, Working Group on Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, a joint cooperation between the Charité Universitätsmedizin Berlin and the Max-Delbrück-Center for Molecular Medicine, Berlin, Germany.
⁶ Helios Hospital Berlin-Buch, Department of Cardiology and Nephrology, Berlin, Germany.
⁷ Department of Neurology, University Medical Center Freiburg, Freiburg, Germany.
⁸ Faculty of Medicine, University of Freiburg, Freiburg, Germany.
⁹ Department of Radiology, Theresienkrankenhaus und St. Hedwig-Klinik, Mannheim, Germany.
¹⁰ Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

Abstract

4D PC MRI of the aorta has become a routinely available examination, and a multitude of single parameters have been suggested for the quantitative assessment of relevant flow features for clinical studies and diagnosis. However, clinically applicable assessment of complex flow patterns is still challenging. We present a concept for applying radiomics for the quantitative characterization of flow patterns in the aorta. To this end, we derive cross-sectional scalar parameter maps related to parameters suggested in literature such as throughflow, flow direction, vorticity, and normalized helicity. Derived radiomics features are selected with regard to their inter-scanner and inter-observer reproducibility, as well as their performance in the differentiation of sex-, age- and disease-related flow properties. The reproducible features were tested on user-selected examples with respect to their suitability for characterizing flow profile types. In future work, such signatures could be applied for quantitative flow assessment in clinical studies or disease phenotyping.

Keywords: 4D PC-MRI; Radiomics; aortic valve stenosis; flow profile; population; reproduciblity; travelling volunteers.

Grants and funding

This work was partially funded by the BMBF project “Berlin Institute for the Foundations of Learning and Data” (grant number 01IS18037E) and by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - SFB-1470 - B06. AH received funding from Berta-Ottenstein-Programme for Advanced Clinician Scientists, Medical Faculty, University of Freiburg, Germany. We acknowledge financial support from the Open Access Publication Fund of Charité – Universitätsmedizin Berlin and the German Research Foundation (DFG).