Purpose Quantitative ultrasound (QUS) infers properties about tissue microstructure from backscattered radio-frequency ultrasound data. This paper describes how to implement the most practical QUS parameters using an ultrasound research system for tissue differentiation. Methods This study first validated chicken liver and gizzard muscle as suitable acoustic phantoms for human brain and brain tumour tissues via measurement of the speed of sound and acoustic attenuation. A total of thirteen QUS parameters were estimated from twelve samples, each using data obtained with a transducer with a frequency of 5–11 MHz. Spectral parameters, i.e., effective scatterer diameter and acoustic concentration, were calculated from the backscattered power spectrum of the tissue, and echo envelope statistics were estimated by modelling the scattering inside the tissue as a homodyned K-distribution, yielding the scatterer clustering parameter α and the structure parameter κ. Standard deviation and higher-order moments were calculated from the echogenicity value assigned in conventional B-mode images. Results The k-nearest neighbours algorithm was used to combine those parameters, which achieved 94.5% accuracy and 0.933 F1-score. Conclusion We were able to generate classification parametric images in near-real-time speed as a potential diagnostic tool in the operating room for the possible use for human brain tissue characterisation.

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A two-and-a-half-year-old Friesian cow and a five-year-old Charolais cow developed severe respiratory distress and palpable swellings to the left of the larynx as a result of a dissecting aneurysm of the common carotid artery. Neither cow responded to medical treatment. The underlying pathogenesis of the condition was uncertain, but direct trauma to the carotid artery was a possible contributory factor. Aneurysms of the common carotid artery should be considered when swelling occurs in the region of the larynx or when respiratory distress is due to laryngeal compression.

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