Key result
Automated speckle tracking matches specialist consensus on echo image quality in ~85% of cases.
Why the study?
Obtaining correct echocardiographic views is subjective and lacks a reliable real-time objective index for image alignment to assist less experienced operators.
May aid novice echocardiographers in view optimization; leaves open prospective validation of clinical impact.
Obtaining a "correct" view in echocardiography is a subjective process in which an operator attempts to obtain images conforming to consensus standard views. Real-time objective quantification of image alignment may assist less experienced operators, but no reliable index yet exists. We present a fully automated algorithm for detecting incorrect medial/lateral translation of an ultrasound probe by image analysis. The ability of the algorithm to distinguish optimal from sub-optimal four-chamber images was compared to that of specialists-the current "gold-standard." The orientation assessments produced by the automated algorithm correlated well with consensus visual assessments of the specialists ([Formula: see text]) and compared favourably with the correlation between individual specialists and the consensus, [Formula: see text]. Each individual specialist's assessments were within the consensus of other specialists, [Formula: see text] of the time, and the algorithm's assessments were within the consensus of specialists 85% of the time. The mean discrepancy in probe translation values between individual specialists and their consensus was [Formula: see text], and between the automated algorithm and specialists' consensus was [Formula: see text]. This technology could be incorporated into hardware to provide real-time guidance for image optimisation-a potentially valuable tool both for training and quality control.
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Dhutia et al. (2014) studied Echocardiography imaging alignment. Automated speckle tracking algorithm vs. Consensus visual assessments by specialists was evaluated on Agreement with consensus visual assessments of optimal versus sub-optimal four-chamber images. An automated speckle tracking algorithm's orientation assessments were within the consensus of specialists 85% of the time, indicating its potential to provide real-time guidance for image optimization.
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