Optimisation of ultrasound liver perfusion through a digital reference object and analysis tool View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-04-03

AUTHORS

Ángel Alberich-Bayarri, Jose Tomás-Cucarella, Alfredo Torregrosa-Lloret, Javier Sáiz Rodriguez, Luis Martí-Bonmatí

ABSTRACT

BackgroundConventional ultrasound (US) provides important qualitative information, although there is a need to evaluate the influence of the input parameters on the output signal and standardise the acquisition for an adequate quantitative perfusion assessment. The present study analyses how the variation in the input parameters influences the measurement of the perfusion parameters.MethodsA software tool with simulator of the conventional US signal was created, and the influence of the different input variables on the derived biomarkers was analysed by varying the image acquisition configuration. The input parameters considered were the dynamic range, gain, and frequency of the transducer. Their influence on mean transit time (MTT), the area under the curve (AUC), maximum intensity (MI), and time to peak (TTP) parameters as outputs of the quantitative perfusion analysis was evaluated. A group of 13 patients with hepatocarcinoma was analysed with both a commercial tool and an in-house developed software.ResultsThe optimal calculated inputs which minimise errors while preserving images’ readability consisted of gain of 15 dB, dynamic range of 60 dB, and frequency of 1.5 MHz. The comparison between the in-house developed software and the commercial software provided different values for MTT and AUC, while MI and TTP were highly similar.ConclusionInput parameter selection introduces variability and errors in US perfusion parameter estimation. Our results may add relevant insight into the current knowledge of conventional US perfusion and its use in lesions characterisation, playing in favour of optimised standardised parameter configuration to minimise variability. More... »

PAGES

15

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s41747-019-0086-5

DOI

http://dx.doi.org/10.1186/s41747-019-0086-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1113182401

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30945029


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