# Mechanical characterization of cells and microspheres sorted by acoustophoresis with in-line resistive pulse sensing

## TL;DR

This study introduces a novel method combining acoustophoresis and resistive pulse sensing to measure cell and particle mechanical properties, enabling label-free, high-precision phenotyping potentially useful for cancer research and nanoscale object analysis.

## Contribution

The paper develops and validates a linear and a statistical model for inferring cell compressibility using acoustic radiation pressure combined with resistive pulse sensing, advancing label-free cell phenotyping.

## Key findings

- High-precision linear model for cell compressibility
- Robust statistical model for datasets with fewer particles
- Potential for point-of-care acoustic phenotyping

## Abstract

Resistive Pulse Sensing (RPS) is a key label-free technology to measure particles and single-cell size distribution. As a growing corpus of evidence supports that cancer cells exhibit distinct mechanical phenotypes from healthy cells, expanding the method from size to mechanical sensing could represent a pertinent and innovative tool for cancer research. In this paper, we infer the cells compressibility by using acoustic radiation pressure to deflect flowing cells in a microchannel, and use RPS to sense the subpopulations of cells and particles at each acoustic power level. We develop and validate a linear model to analyze experimental data from a large number of particles. This high-precision linear model is complemented by a more robust (yet less detailed) statistical model to analyze datasets with fewer particles. Compared to current acoustic cell phenotyping apparatus based on video cameras, the proposed approach is not limited by the optical diffraction, frame rate, data storage or processing speed, and may ultimately constitute a step forward towards point-of-care acousto-electrical phenotyping and acoustic phenotyping of nanoscale objects such as exosomes and viruses.