Carotid artery wall motion and strain analysis using tracking

Carotid artery wall motion and strain analysis using tracking

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In this chapter, a number of speckle-tracking-based methodologies are outlined, suitable for the estimation of motion and strain of the carotid artery from ultrasound images. Various versions of intensity- and phase-based techniques have been suggested and validated mostly in phantoms, in in silico and in vitro data. Waveforms showing displacements, velocities and accelerations can be obtained from these methods, and a number of indices can then be calculated. Spatial mapping (imaging) of tissue strains can be achieved with elastography, a major application of motion analysis. Through their application in real data, these methods are promising for revealing valuable quantitative in vivo information about arterial mechanics. Compared to other ultrasound-based indices, a major advantage of motion-derived indices is that they provide functional, rather than mere anatomical, information, which is more sensitive to early wall changes. Their full potential in predicting, diagnosing and monitoring carotid-related disorders, such as cerebrovascular events, as well as in characterising the burden of other diseases, remains to be confirmed in large clinical trials, towards an integrated personalised approach for disease management and increased patient safety.

Chapter Contents:

  • Abstract
  • 24.1 Introduction
  • 24.2 Methods for motion and strain analysis
  • 24.3 Estimation of motion and strain of the carotid artery in health and disease
  • 24.4 Discussion and future perspectives
  • References

Inspec keywords: biomechanics; blood vessels; diseases; motion estimation; medical image processing; patient monitoring; medical disorders; object tracking; biomedical ultrasonics; phantoms

Other keywords: arterial mechanics; disease management; elastography; carotid artery wall motion; carotid-related disorder monitoring; in vitro data; strain analysis; phantoms; spatial mapping; cerebrovascular events; motion estimation; in silico data; ultrasound images; motion analysis; patient safety; phase-based techniques; speckle-tracking-based methodology; tissue strains; carotid-related disorder diagnosis; intensity-based techniques

Subjects: Sonic and ultrasonic radiation (biomedical imaging/measurement); Biology and medical computing; Computer vision and image processing techniques; Sonic and ultrasonic radiation (medical uses); Patient diagnostic methods and instrumentation; Optical, image and video signal processing; Mechanical properties of tissues and organs; Sonic and ultrasonic applications

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