Full-field noise-correlation elastography for in-plane mechanical anisotropy imaging.

Elastography contrast imaging has great potential for the detection and characterization of abnormalities in soft biological tissues to help physicians in diagnosis. Transient shear-waves elastography has notably shown promising results for a range of clinical applications. In biological soft tissues such as muscle, high mechanical anisotropy implies different stiffness estimations depending on the direction of the measurement. In this study, we propose the evolution of a noise-correlation elastography approach for in-plane anisotropy mapping. This method is shown to retrieve anisotropy from simulation images before being validated on agarose anisotropic tissue-mimicking phantoms, and the first results on in-vivo biological fibrous tissues are presented.

Time-of-flight and noise-correlation-inspired algorithms for full-field shear-wave elastography using digital holography.

SIGNIFICANCE: Quantitative stiffness information can be a powerful aid for tumor or fibrosis diagnosis. Currently, very promising elastography approaches developed for non-contact biomedical imaging are based on transient shear-waves imaging. Transient elastography offers quantitative stiffness information by tracking the propagation of a wave front. The most common method used to compute stiffness from the acquired propagation movie is based on shear-wave time-of-flight calculations. AIM: We introduce an approach to transient shear-wave elastography with spatially coherent sources, able to yield full-field quantitative stiffness maps with reduced artifacts compared to typical artifacts observed in time-of-flight. APPROACH: A noise-correlation algorithm developed for passive elastography is adapted to spatially coherent narrow or any band sources. This noise-correlation-inspired (NCi) method is employed in parallel with a classic time-of-flight approach. Testing is done on simulation images, experimental validation is conducted with a digital holography setup on controlled homogeneous samples, and full-field quantitative stiffness maps are presented for heterogeneous samples and ex-vivo biological tissues. RESULTS: The NCi approach is first validated on simulations images. Stiffness images processed by the NCi approach on simulated inclusions display significantly less artifacts than with a time-of-flight reconstruction. The adaptability of the NCi algorithm to narrow or any band shear-wave sources was tested successfully. Experimental testing on homogeneous samples demonstrates similar values for both the time-of-flight and the NCi approach. Soft inclusions in agarose sample could be resolved using the NCi method and feasibility on ex-vivo biological tissues is presented. CONCLUSIONS: The presented NCi approach was successful in computing quantitative full-field stiffness maps with narrow and broadband source signals on simulation and experimental images from a digital holography setup. Results in heterogeneous media show that the NCi approach could provide stiffness maps with less artifacts than with time-of-flight, demonstrating that a NCi algorithm is a promising approach for shear-wave transient elastography with spatially coherent sources.

Full-field passive elastography using digital holography.

Off-axis digital holography is an imaging technique that allows direct measurement of phase and amplitude from one image. We utilize this technique to capture displacements induced by a diffuse shear wave field with high sensitivity. A noise-correlation-based algorithm is then used to measure mechanical properties of samples. This approach enables full-field quantitative passive elastography without the need of contact or a synchronized source of a mechanical wave. This passive elastography method is first validated on agarose test samples mimicking biological tissues, and first results on an ex vivo biological sample are presented.