Automatic measurement of the sinus of Valsalva by image analysis

Comput Methods Programs Biomed. 2017 Sep:148:123-135. doi: 10.1016/j.cmpb.2017.06.014. Epub 2017 Jun 30.

Abstract

Background and objectives: Despite the importance of the morphology of the sinus of Valsalva in the behavior of heart valves and the proper irrigation of coronary arteries, the study of these sinuses from medical imaging is still limited to manual radii measurements. This paper aims to present an automatic method to measure the sinuses of Valsalva on medical images, more specifically on cine MRI and Xray CT.

Methods: This paper introduces an enhanced method to automatically localize and extract each sinus of Valsalva edge and its relevant points. Compared to classical active contours, this new image approach enhances the edge extraction of the Sinus of Valsalva. Our process not only allows image segmentation but also a complex study of the considered region including morphological classification, metrological characterization, valve tracking and 2D modeling.

Results: The method was successfully used on single or multiplane cine MRI and aortic CT angiographies. The localization is robust and the proposed edge extractor is more efficient than the state-of-the-art methods (average success rate for MRI examinations=84% ± 24%, average success rate for CT examinations=89% ± 11%). Moreover, deduced measurements are close to manual ones.

Conclusions: The software produces accurate measurements of the sinuses of Valsalva. The robustness and the reproducibility of results will help for a better understanding of sinus of Valsalva pathologies and constitutes a first step to the design of complex prostheses adapted to each patient.

Keywords: Computed tomography; Image analysis; Magnetic resonance imaging; Valsalva sinuses.

MeSH terms

  • Aorta / diagnostic imaging*
  • Computed Tomography Angiography
  • Humans
  • Image Processing, Computer-Assisted*
  • Magnetic Resonance Imaging, Cine
  • Reproducibility of Results
  • Sinus of Valsalva / diagnostic imaging*