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Shear-Wave Dispersion Slope (SWDS) is a new ultrasound parameter to detect liver inflammation

https://doi.org/10.24835/1607-0763-1513

Abstract

Background: one of the most pressing problems of ultrasound shear wave elastometry of the liver is the lack of distinct digital differential diagnostic criteria for the presence and severity of fibrosis in inflammation.

Purpose. To evaluate the possibility of a new ultrasonic parameter – the shear wave dispersion slope (SWDS) in solving this problem.

Materials and methods. 156 patients with various liver pathologies were examined. Depending on the absence or presence of fibrosis, as well as inflammatory changes in the liver (according to biopsy and serological blood tests), the examined patients were divided into three groups. The control group consisted of 10 healthy donors. Measurements of the shear wave velocity (SWS), shear wave dispersion slope (SWDS) and the assessment of ultrasound attenuation (ATI) in the liver were performed using the Canon Medical Aplio i800 ultrasound diagnostic system (Tokyo, Japan) using a standard convex transducer.

Results. The indicators of SWS, SWDS and ATI (Median and 95% CI) in the control group were Me 1.2 (95% CI 1.1–1.6) m/s, Me 10.1 (95% CI 9.7–14.3) m/s/kHz and Me 0.54 (95% CI 0.41–0.63) dB/cm/MHz, respectively. The study of the main group showed that there is a close correlation between SWS and SWDS (Spearman's rho = 0.74). At the same time, patients in the subgroup with inflammation had significantly (p < 0.01) higher SWDS values compared with the control group and the subgroup without inflammation – Me 16.4 (95% CI 15.3–17.9) m/s/kHz versus Me 10.1 (95% CI 9.7–14.3) m/s/kHz and Me 12.7 (95%CI 12.1–14.3) m/s/kHz. In patients of the subgroup with fibrosis, but without inflammation, there was also a significant (p < 0.01) increase in SWDS from Me 12,0 (95% CI 11.4–12.8) m/s/kHz at F0-1 to Me 16,5 (95% CI 12.9–20.3) m/s/kHz at F3–4 METAVIR.

Conclusion. The use of absolute SWDS values did not contribute to the achievement of the purpose of this study – the detection of criteria for the differential diagnosis of the presence and severity of liver fibrosis in patients with hepatitis. Nevertheless, the results of the study provide grounds for making a fairly confident conclusion that the assessment of the relationship between SWDS and SWS using the binary logistic regression formula (logit(p) = 0, 4152 SWDS (м/с/кГц) 0,1344 SWS (м/с) – 6,5115) can become a valuable additional method for ultrasound diagnostics of inflammatory changes in the liver.

About the Authors

B. I. Zykin
Federal Medical Biophysical Center named after A.I. Burnazyan Russia's Federal Medical-Biological Agency
Russian Federation

Boris I. Zykin – Doct. of Sci. (Med.), professor, Department of radiology, Medical and Biological University of innovation and continuing education of Federal Medical Biophysical Center named after A.I. Burnazyan Russia's Federal Medical-Biological Agency, Moscow.
https://orcid.org/0000-0002-8871-1434



E. A. Ionova
Federal Medical Biophysical Center named after A.I. Burnazyan Russia's Federal Medical-Biological Agency
Russian Federation

Elena A. Ionova – Doct. of Sci. (Med.), Head of Department of radiology, Medical and Biological University of innovation and continuing education of Federal Medical Biophysical Center named after A.I. Burnazyan Russia's Federal Medical-Biological Agency, Moscow. https://orcid.org/0000-0002-6084-2061



T. A. Anosova
Federal Medical Biophysical Center named after A.I. Burnazyan Russia's Federal Medical-Biological Agency
Russian Federation

Tatyana A. Anosova – Cand. of Sci. (Med.), Assistant professor, Department of radiology, Medical and Biological University of innovation and continuing education of Federal Medical Biophysical Center named after A.I. Burnazyan Russia's Federal Medical-Biological Agency, Moscow.
https://orcid.org/0009-0000-9014-2165



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Review

For citations:


Zykin B.I., Ionova E.A., Anosova T.A. Shear-Wave Dispersion Slope (SWDS) is a new ultrasound parameter to detect liver inflammation. Medical Visualization. 2025;29(1):41-50. (In Russ.) https://doi.org/10.24835/1607-0763-1513

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