Ultrasound image has already been proved to be a useful tool for non-invasive strain quantifications in soft tissue.
While clinical applications only include cardiac imaging, the development of techniques suitable for musculoskeletal
system is an active area of research. On this study, a technique for speckle tracking on ultrasound images
using non-rigid image registration is presented. This approach is based on a single 2D+t registration procedure,
in which the temporal changes on the B-mode speckle patterns are locally assessed. This allows estimating
strain from ultrasound image sequences of tissues under deformation while imposing temporal smoothness in
the deformation field, originating smooth strain curves. METHODS: The tracking algorithm was systematically
tested on synthetic images and gelatin phantoms, under sinusoidal deformations with amplitudes between 0.5%
and 4.0%, at frequencies between 0.25Hz and 2.0Hz. Preliminary tests were also performed on Achilles tendons
isolated from human cadavers. RESULTS: The strain was estimated with deviations of -0.011%±0.053% on the
synthetic images and agreements of ±0.28% on the phantoms. Some tests with real tendons show good tracking
results. However, significant variability between the trials still exists. CONCLUSIONS: The proposed image
registration methodology constitutes a robust tool for motion and deformation tracking in both simulated and
real phantom data. Strain estimation in both cases reveals that the proposed method is accurate and provides
good precision. Although the ex-vivo results are still preliminary, the potential of the proposed algorithm is
promising. This suggests that further improvements, together with systematic testing, can lead to in-vivo and
clinical applications.
The quantitative assessment of regional myocardial function remains an important goal in clinical cardiology. As such,
tissue Doppler imaging and speckle tracking based methods have been introduced to estimate local myocardial strain.
Recently, volumetric ultrasound has become more readily available, allowing therefore the 3D estimation of motion and
myocardial deformation. Our lab has previously presented a method based on spatio-temporal elastic registration of
ultrasound volumes to estimate myocardial motion and deformation in 3D, overcoming the spatial limitations of the
existing methods. This method was optimized on simulated data sets in previous work and is currently tested in a clinical
setting. In this manuscript, 10 healthy volunteers, 10 patient with myocardial infarction and 10 patients with arterial hypertension were included. The cardiac strain values extracted with the proposed method were compared with the ones estimated with 1D tissue Doppler imaging and 2D speckle tracking in all patient groups. Although the absolute values of the 3D strain components assessed by this new methodology were not identical to the reference methods, the relationship between the different patient groups was similar.
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