D.V. Leonov1, T.V. Yakovleva2, N.S. Kulberg3, O.V. Omelyanskaya4, Yu.A. Vasiliev5
1,2,4,5 Scientific and practical clinical center for diagnostics and telemedicine technologies Moscow Health Department (Moscow, Russia)
1 National Research University MPEI (Moscow, Russia)
1,2 Federal Research Center “Informatics and Management” RAS (Moscow, Russia)
3 Bauman Moscow State Technical University (National Research University) (Moscow, Russia)
1 strat89@mail.ru, 2YakovlevaTV7@zdrav.mos.ru, 3 kulberg@yandex.ru, 4 OmelyanskayaOV@zdrav.mos.ru, 5 VasilevYA1@zdrav.mos.ru
A number of diseases, such as breast, thyroid, and liver steatosis cancers, are characterized by changes in the size of the body's cells. Such changes are difficult to diagnose with current medical imaging tools, and the biopsies required to make a definitive diagnosis are expensive for the health care system and painful for the patient. At the same time, ultrasound imaging stands out from other diagnostic methods due to its prevalence, absence of harmful radiation and the possibility of real-time operation. Therefore, the development of methods for estimating the size of scatterers based on the principles of ultrasound imaging is relevant. It is known that the statistics of ultrasonic signals is described by the Rice distribution. However, until recently the estimation of parameters of the Rice distribution was difficult because of the necessity to calculate the Bessel function.
To develop a new method for estimation of scatterer sizes in ultrasound imaging based on the calculation of the parameters of the Rice distribution without calculating the Bessel function.
The developed method of scatterers size estimation was tested by numerical simulation of ultrasonic oscillation propagation in the medium. The simulations showed that estimating the ratio of the parameters σ and A of the Rice distribution while varying the scatterer size allows us to identify a decreasing linear trend that can be used to estimate the scatterer size. In an experiment using a signal at a carrier frequency of 5 MHz and a duration of 0.7 μs, it was possible to perform size estimation in the range from 41 to 706 μm, which is 4 to 69 % with respect to the duration of the probing pulse. The operation of the method is possible with the size of a square sliding window with side up to 2 mm.
The results of the study can be used in the development of ultrasonic medical diagnostic systems with the mode of scatterer size estimation.
Leonov D.V., Yakovleva T.V., Kulberg N.S., Omelyanskaya O.V., Vasiliev Yu.A. A method for estimating the size of scatterers in ultrasound imaging. Biomedicine Radioengineering. 2025. V. 28. № 3. P. 5–13. DOI: https:// doi.org/10.18127/j15604136-202503-08 (In Russian)
- Zhou Z., Gao R., Wu S., Ding Q., Bin G., Tsui P.-H. Scatterer size estimation for ultrasound tissue characterization: A survey. Measurement. 2024. V. 225. P.114046,https://doi.org/10.1016/j.measurement.2023.114046.
- Cloutier G., Destrempes F., Yu F., Tang A. Quantitative ultrasound imaging of soft biological tissues: a primer for radiologists and medical physicists. Insights into Imaging. 2021. V. 12. P. 1–20.
- Fan Y., Chen K., Zhao Q., Yin H., Zhu Y. Xu H. Quantitative ultrasound analysis for non-invasive assessment of hepatic steatosis in metabolic dysfunction-associated steatotic liver disease. Clinical Hemorheology and Microcirculation. 2025. 13860291241304057.
- Taleghamar H., Jalalifar S.A., Czarnota G.J., Sadeghi-Naini A. Deep learning of quantitative ultrasound multi-parametric images at pre-treatment to predict breast cancer response to chemotherapy. Scientific reports. 2022. V. 12(1). P. 2244.
- Li X., Jia X., Shen T., Wang M., Yang G., Wang H., Sun Q., Wan M., Zhang S. Ultrasound entropy imaging for detection and monitoring of thermal lesion during microwave ablation of liver. IEEE Journal of Biomedical and Health Informatics. 2022. V. 26(8). P. 4056–4066.
- Tai H., Song J., Li J., Reddy S., Khairalseed M., Hoyt K. Three-dimensional H-scan ultrasound imaging of early breast cancer response to neoadjuvant therapy in a murine model. Investigative radiology. 2022. V. 57(4). P. 222–232.
- Baek J., Qin S.S., Prieto P.A., Parker K.J. H-Scan Discrimination for Tumor Microenvironmental Heterogeneity in Melanoma. Ultrasound in medicine & biology. 2024. V. 50(2). P. 268–276.
- Khairalseed M., Hoyt K. High-resolution ultrasound characterization of local scattering in cancer tissue. Ultrasound in medicine & biology. 2023. V. 49(4). P. 951–960.
- Yakovleva T.V., Kulberg N.S., Leonov D.V. Estimation of the size of structural formations in ultrasound imaging through statistical analysis of the echo signal. In Doklady Mathematics. 2023. V. 107. № 1. P. 72–76.
- Carvajal R., Orellana R., Coronel M., Agüero J.C. Channel Modeling Using Rayleigh and Rice Sum Approximation. In 2024 IEEE International Conference on Automation/XXVI Congress of the Chilean Association of Automatic Control (ICA-ACCA). IEEE. 2024. P. 1–6.
- Yakovleva T.V. Matematicheskie metody analiza dannyh v usloviyah primenimosti statisticheskoj modeli Rajsa: Dis. … dokt. fiz.-mat. nauk / Federal'noe gosudarstvennoe byudzhetnoe uchrezhdenie nauki Vychislitel'nyj centr im. A.A. Dorodnicyna Rossijskoj akademii nauk. 2015 (In Russian).
- Chen C., Pertijs M.A. Integrated transceivers for emerging medical ultrasound imaging devices: A review. IEEE Open Journal of the Solid-State Circuits Society. 2021. V. 1. P. 104–114.
- Ginzberg M.B., Kafri R., Kirschner M. On being the right (cell) size. Science. 2015. V. 348(6236). P. 1245075.
- Leonov D., Nasibullina A., Grebennikova V., Vlasova O., Bulgakova Yu., Belyakova E., Shestakova D., Costa-Júnior J.F.S., Omelianskaya O., Vasilev Yu. Design and evaluation of an anthropomorphic neck phantom for improved ultrasound diagnostics of thyroid gland tumors. International Journal of Computer Assisted Radiology and Surgery. 2024 Aug; 19(8). P. 1637–1645. DOI: 10.1007/s11548-024-03130-1.
- Kim D.S., Paltiel H.J., White P.J., Sassaroli E. Ultrasound Imaging Techniques and Artifacts. Pediatric Ultrasound. 2021. P. 1–49.
- Pirmoazen A.M., Khurana A., El Kaffas A., Kamaya A. Quantitative ultrasound approaches for diagnosis and monitoring hepatic steatosis in nonalcoholic fatty liver disease. Theranostics. 2020. V. 10(9). P. 4277.
- Fang J., Lai M.W., Cheng H.T., Cristea A., Zhou Z., Tsui P.H. Imaging the Effects of Whole-Body Vibration on the Progression of Hepatic Steatosis by Quantitative Ultrasound Based on Backscatter Envelope Statistics. Pharmaceutics. 2022. V. 14(4). P. 741.
- Osipov L.V., Kul'berg N.S., Leonov D.V., Morozov S.P. Trekhmernoe ul'trazvukovoe issledovanie: osobennosti vizualizacii ob"emnyh dannyh Medicinskaya tekhnika. 2020. № 2 (320). S. 51–55 (In Russian).
- Tai H., Khairalseed M., Hoyt K. 3-D H-scan ultrasound imaging and use of a convolutional neural network for scatterer size estimation. Ultrasound in medicine & biology. 2020. V. 46(10). P. 2810–2818.
- Tai H., Khairalseed M., Hoyt K. 3D H-scan ultrasound imaging system and method for acoustic scatterer size estimation: Preliminary studies using phantom materials. In 2019 IEEE International Ultrasonics Symposium (IUS). IEEE. 2019. P. 1515–1518.
- Osipov L.V., Kul'berg N.S., Leonov D.V., Morozov S.P. Trekhmernoe ul'trazvukovoe issledovanie: tekhnologii, tendencii razvitiya // Medicinskaya tekhnika. 2018. № 3 (309). S. 39–43 (In Russian).
- Vasil'ev Yu.A., Omelyanskaya O.V., Nasibullina A.A., Lejchenko D.V., Leonov D.V., SHestakova D.Yu., Vetsheva N.N., Lyhin V.N. Ispol'zovanie fantomov v processe obucheniya ul'trazvukovoj diagnostike: metodicheskie rekomendacii. Ser.: Luchshie praktiki luchevoj i instrumental'noj diagnostiki. Vyp. 137. M.: GBUZ «NPKC DiT DZM». 2023. 61 s. (In Russian)
- Patent na izobretenie RU 2747253 C1. Biofantom dlya otrabotki prakticheskih navykov pri vypolnenii miniinvazivnyh vmeshatel'stv i intraoperacionnyh issledovanij pod ul'trazvukovym kontrolem / N.N. Vetsheva, E.P. Fisenko, E.A. Kostenko. 2020 (In Russian).
- Vasil'ev Yu.A., Omelyanskaya O.V., Nasibullina A.A., Leonov D.V., Bulgakova Yu.V., Ahmedzyanova D.A., Shumskaya Yu.F., Reshetnikov R.V. Antropomorfnye fantomy molochnoj zhelezy dlya luchevoj diagnostiki: nauchnyj obzor. Digital Diagnostics. 2023. T. 4. № 4. S. 569–592 (In Russian).

