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

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.

Automated summary

4D PC MRI of the aorta has become a routine method for quantitative assessment of flow patterns, but the clinical application of complex flow patterns still poses challenges. This study presents a concept of applying radiomics to quantitatively characterize flow patterns in the aorta and selects reproducible parameters for differentiation of flow properties related to sex, age, and disease. The suitability of these reproducible features for characterizing different flow profile types is evaluated using user-selected examples. In the future, these signatures could be used for quantitative flow assessment in clinical studies or disease phenotyping.