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Proceedings Paper

Rotation elastogram: a novel method to visualize local rigid body rotation under quasi-static compression
Author(s): Sowmiya C.; Ali Arshad Kothawala; Arun K. Thittai
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Paper Abstract

During manual palpation of breast masses, the perception of its stiffness and slipperiness are the two commonly used information by the physician. In order to reliably and quantitatively obtain this information several non-invasive elastography techniques have been developed that seek to provide an image of the underlying mechanical properties, mostly stiffness-related. Very few approaches have visualized the "slip" at the lesion-background boundary that only occurs for a loosely-bonded benign lesion. It has been shown that axial-shear strain distribution provides information about underlying slip. One such feature, referred to as "fill-in" was interpreted as a surrogate of the rotation undergone by an asymmetrically-oriented-loosely bonded-benign-lesion under quasi-static compression. However, imaging and direct visualization of the rotation itself has not been addressed yet. In order to accomplish this, the quality of lateral displacement estimation needs to be improved. In this simulation study, we utilize spatial compounding approach and assess the feasibility to obtain good quality rotation elastogram. The angular axial and lateral displacement estimates were obtained at different insonification angles from a phantom containing an elliptical inclusion oriented at 45°, subjected to 1% compression from the top. A multilevel 2D-block matching algorithm was used for displacement tracking and 2D-least square compounding of angular axial and lateral displacement estimates was employed. By varying the maximum steering angle and incremental angle, the improvement in the lateral motion tracking accuracy and its effects on the quality of rotational elastogram were evaluated. Results demonstrate significantly-improved rotation elastogram using this technique.

Paper Details

Date Published: 1 April 2016
PDF: 8 pages
Proc. SPIE 9790, Medical Imaging 2016: Ultrasonic Imaging and Tomography, 97901E (1 April 2016); doi: 10.1117/12.2216828
Show Author Affiliations
Sowmiya C., Indian Institute of Technology Madras (India)
Ali Arshad Kothawala, Indian Institute of Technology Madras (India)
Arun K. Thittai, Indian Institute of Technology Madras (India)

Published in SPIE Proceedings Vol. 9790:
Medical Imaging 2016: Ultrasonic Imaging and Tomography
Neb Duric; Brecht Heyde, Editor(s)

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