Frame rate required for speckle tracking echocardiography: A quantitative clinical study with open-source, vendor-independent software

Negoita, Madalina and Zolgharni, Massoud and Dadkho, Elham and Pernigo, Matteo and Mielewczik, Michael and Cole, Graham D. and Dhutia, Niti M. and Francis, Darrel P. (2016) Frame rate required for speckle tracking echocardiography: A quantitative clinical study with open-source, vendor-independent software. International Journal of Cardiology, 218 . pp. 31-36. ISSN 0167-5273

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Abstract

Background

Assessing left ventricular function with speckle tracking is useful in patient diagnosis but requires a temporal resolution that can follow myocardial motion. In this study we investigated the effect of different frame rates on the accuracy of speckle tracking results, highlighting the temporal resolution where reliable results can be obtained.

Material and methods

27 patients were scanned at two different frame rates at their resting heart rate. From all acquired loops, lower temporal resolution image sequences were generated by dropping frames, decreasing the frame rate by up to 10-fold.

Results

Tissue velocities were estimated by automated speckle tracking. Above 40 frames/s the peak velocity was reliably measured. When frame rate was lower, the inter-frame interval containing the instant of highest velocity also contained lower velocities, and therefore the average velocity in that interval was an underestimate of the clinically desired instantaneous maximum velocity.

Conclusions

The higher the frame rate, the more accurately maximum velocities are identified by speckle tracking, until the frame rate drops below 40 frames/s, beyond which there is little increase in peak velocity. We provide in an online supplement the vendor-independent software we used for automatic speckle-tracked velocity assessment to help others working in this field.

Keywords:Speckle tracking, Frame rate, Myocardial velocity, Sampling frequency, Tissue velocity imaging, NotOAChecked
Subjects:H Engineering > H673 Bioengineering
G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:College of Science > School of Computer Science
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ID Code:24899
Deposited On:04 Nov 2016 09:23

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