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Improving blood vessel tortuosity measurements via highly sampled numerical integration of the Frenet-Serret equations

ORAL

Abstract

Measures of vascular tortuosity are associated with a variety of vascular diseases. Consequently, measurements of vessel tortuosity that are accurate and comparable across modality, resolution, and size are greatly needed. Yet in practice, precise and consistent measurements are problematic. Here, we present a new method of measuring vessel tortuosity that ensures improved accuracy. Our method relies on numerical integration of the Frenet-Serret equations. By reconstructing the three-dimensional vessel coordinates from tortuosity measurements, we explain how to identify and use a minimally-sufficient sampling rate based on vessel radius while avoiding errors associated with oversampling and overfitting. Our work identifies a key failing in current practices of filtering asymptotic measurements and highlights inconsistencies and redundancies between existing tortuosity metrics. We demonstrate our method by applying it to manually constructed vessel phantoms with known measures of tortuousity, and 9,000 vessels from medical image data spanning human cerebral, coronary, and pulmonary vascular trees, and the carotid, abdominal, renal, and iliac arteries.

Presenters

  • Alex Brummer

    University of California, Los Angeles, Department of Computational Medicine, University of California, Los Angeles

Authors

  • Alex Brummer

    University of California, Los Angeles, Department of Computational Medicine, University of California, Los Angeles

  • David Hunt

    Institute for Learning and Brain Sciences, University of Washington

  • Van Savage

    Department of Computational Medicine, University of California, Los Angeles