A methodology for the assessment of cell concentration, in the range 5-100 cells/ μL, suitable for in vivo analysis of serous body fluids is presented in this work. This methodology is based on the quantitative analysis of ultrasound images obtained from cell suspensions and considers applicability criteria, such as short analysis times, moderate frequency, and absolute concentration estimation, all necessary to deal with the variability of tissues among different patients. Numerical simulations provided the framework to analyze the impact of echo overlapping and the polydispersion of scatterer sizes on the cell concentration estimation. The cell concentration range that can be analyzed as a function of the transducer and emitted waveform used was also discussed. Experiments were conducted to evaluate the performance of the method using 7- μm and 12- μm polystyrene particles in water suspensions in the 5-100 particles/ μL range. A single scanning focused transducer working at a central frequency of 20 MHz was used to obtain ultrasound images. The method proposed to estimate the concentration proved to be robust for different particle sizes and variations of gain acquisition settings. The effect of tissues placed in the ultrasound path between the probe and the sample was also investigated using 3-mm-thick tissue mimics. Under this situation, the algorithm was robust for the concentration analysis of 12 μm particle suspensions, yet significant deviations were obtained for the smallest particles.
Funding
This work was supported in part by the Instituto de Salud Carlos III under Project PI16/00738 and PI16/01822, in part by FEDER (European Regional Development Fund) resources, and in part by the Spanish Ministry of Science and Innovation under Project PID2019-111392RB-I00. The work of Alba Fernández was supported in part by the Comunidad de Madrid and Alicia Pose through the JAEINTRO Programme under Contract PEJD-2018-PRE/IND-9090 and in part by the Consejo Superior de Investigaciones Científicas (CSIC) under Grant JAEINT_18_01152. The work of Quique Bassat was supported in part by the Spanish Ministry of Science and Innovation through the Centro de Excelencia Severo Ochoa 2019-2023 Program under Grant CEX2018-000806-S, in part by the Generalitat de Catalunya through the CERCA Program, in part by the Government of Mozambique, and in part by the Spanish Agency for International Development (AECID).
