Dataset Information

Optical coherence tomography detection of shear wave propagation in inhomogeneous tissue equivalent phantoms and ex-vivo carotid artery samples.

ABSTRACT: In this work, we explored the potential of measuring shear wave propagation using optical coherence elastography (OCE) in an inhomogeneous phantom and carotid artery samples based on a swept-source optical coherence tomography (OCT) system. Shear waves were generated using a piezoelectric transducer transmitting sine-wave bursts of 400 μs duration, applying acoustic radiation force (ARF) to inhomogeneous phantoms and carotid artery samples, synchronized with a swept-source OCT (SS-OCT) imaging system. The phantoms were composed of gelatin and titanium dioxide whereas the carotid artery samples were embedded in gel. Differential OCT phase maps, measured with and without the ARF, detected the microscopic displacement generated by shear wave propagation in these phantoms and samples of different stiffness. We present the technique for calculating tissue mechanical properties by propagating shear waves in inhomogeneous tissue equivalent phantoms and carotid artery samples using the ARF of an ultrasound transducer, and measuring the shear wave speed and its associated properties in the different layers with OCT phase maps. This method lays the foundation for future in-vitro and in-vivo studies of mechanical property measurements of biological tissues such as vascular tissues, where normal and pathological structures may exhibit significant contrast in the shear modulus.

SUBMITTER: Razani M

PROVIDER: S-EPMC3959849 | biostudies-other | 2014 Mar

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:Thromboembolism in a cerebral blood vessel is associated with high morbidity and mortality. Mechanical thrombectomy (MT) is one of the emergenc proceduresperformed to remove emboli. However, the interventional approaches such as aspiration catheters or stent retriever are empirically selected. An inappropriate selection of surgical devices can influence the success rate during embolectomy, which can lead to an increase in brain damage. There has been growing interest in the study of clot composition and using a priori knowledge of clot composition to provide guidance for an appropriate treatment strategy for interventional physicians. Developing imaging tools which can allow interventionalists to understand clot composition could affect management and device strategy. In this study, we investigated how clots of different compositions can be characterized by using acoustic radiation force optical coherence elastography (ARF-OCE) and compared with ultrasound shear wave elastography (SWE). Five different clots compositions using human blood were fabricated into cylindrical forms from fibrin-rich (21% red blood cells, RBCs) to RBC-rich (95% RBCs). Using the ARF-OCE and SWE, we characterized the wave velocities measured in the time-domain. In addition, the semi-analytical finite element model was used to explore the relationship between the phase velocities with various frequency ranges and diameters of the clots. The study demonstrated that the wave group velocities generally decrease as RBC content increases in ARF-OCE and SWE. The correlation of the group velocities from the OCE and SWE methods represented a good agreement as RBC composition is larger than 39%. Using the phase velocity dispersion analysis applied to ARF-OCE data, we estimated the shear wave velocities decoupling the effects of the geometry and material properties of the clots. The study demonstrated that the composition of the clots can be characterized by elastographic methods using ARF-OCE and SWE, and OCE demonstrated better ability to discriminate between clots of different RBC compositions, compared to the ultrasound-based approach, especially in clots with low RBC compositions.

Dataset Information

Optical coherence tomography detection of shear wave propagation in inhomogeneous tissue equivalent phantoms and ex-vivo carotid artery samples.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets