Literature DB >> 17804889

Performance of ultrasound based measurement of 3D displacement using a curvilinear probe for organ motion tracking.

Emma J Harris1, Naomi R Miller, Jeffrey C Bamber, Phillip M Evans, J Richard N Symonds-Tayler.   

Abstract

Three-dimensional (3D) soft tissue tracking is of interest for monitoring organ motion during therapy. Our goal is to assess the tracking performance of a curvilinear 3D ultrasound probe in terms of the accuracy and precision of measured displacements. The first aim was to examine the depth dependence of the tracking performance. This is of interest because the spatial resolution varies with distance from the elevational focus and because the curvilinear geometry of the transducer causes the spatial sampling frequency to decrease with depth. Our second aim was to assess tracking performance as a function of the spatial sampling setting (low, medium or high sampling). These settings are incorporated onto 3D ultrasound machines to allow the user to control the trade-off between spatial sampling and temporal resolution. Volume images of a speckle-producing phantom were acquired before and after the probe had been moved by a known displacement (1, 2 or 8 mm). This allowed us to assess the optimum performance of the tracking algorithm, in the absence of motion. 3D speckle tracking was performed using 3D cross-correlation and sub-voxel displacements were estimated. The tracking performance was found to be best for axial displacements and poorest for elevational displacements. In general, the performance decreased with depth, although the nature of the depth dependence was complex. Under certain conditions, the tracking performance was sufficient to be useful for monitoring organ motion. For example, at the highest sampling setting, for a 2 mm displacement, good accuracy and precision (an error and standard deviation of <0.4 mm) were observed at all depths and for all directions of displacement. The trade-off between spatial sampling, temporal resolution and size of the field of view (FOV) is discussed.

Mesh:

Year:  2007        PMID: 17804889     DOI: 10.1088/0031-9155/52/18/014

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  5 in total

1.  [Ultrasound motion tracking for radiation therapy].

Authors:  J Jenne; J Schwaab
Journal:  Radiologe       Date:  2015-11       Impact factor: 0.635

2.  Robust model-based quantification of global ventricular torsion from spatially sparse three-dimensional time series data by orthogonal distance regression: evaluation in a canine animal model under different pacing regimes.

Authors:  Sven Zenker; Hyung Kook Kim; Gilles Clermont; Michael R Pinsky
Journal:  Pacing Clin Electrophysiol       Date:  2012-08-16       Impact factor: 1.976

3.  Histotripsy cardiac therapy system integrated with real-time motion correction.

Authors:  Ryan M Miller; Yohan Kim; Kuang-Wei Lin; Charles A Cain; Gabe E Owens; Zhen Xu
Journal:  Ultrasound Med Biol       Date:  2013-09-21       Impact factor: 2.998

Review 4.  The road to clinical use of high-intensity focused ultrasound for liver cancer: technical and clinical consensus.

Authors:  Jean-Francois Aubry; Kim Butts Pauly; Chrit Moonen; Gail Ter Haar; Mario Ries; Rares Salomir; Sham Sokka; Kevin Michael Sekins; Yerucham Shapira; Fangwei Ye; Heather Huff-Simonin; Matt Eames; Arik Hananel; Neal Kassell; Alessandro Napoli; Joo Ha Hwang; Feng Wu; Lian Zhang; Andreas Melzer; Young-Sun Kim; Wladyslaw M Gedroyc
Journal:  J Ther Ultrasound       Date:  2013-08-01

5.  Systematic analysis of volumetric ultrasound parameters for markerless 4D motion tracking.

Authors:  Johanna Sprenger; Marcel Bengs; Stefan Gerlach; Maximilian Neidhardt; Alexander Schlaefer
Journal:  Int J Comput Assist Radiol Surg       Date:  2022-05-21       Impact factor: 3.421

  5 in total

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