Neighborhood resonance phenomenon for cell imaging via scanning probe acoustic microscope

Xiaoqing Li; Wenjie Deng; Mingyue Ding

doi:10.1117/12.2509007

15 March 2019 Neighborhood resonance phenomenon for cell imaging via scanning probe acoustic microscope

Xiaoqing Li, Wenjie Deng, Mingyue Ding

Proceedings Volume 10955, Medical Imaging 2019: Ultrasonic Imaging and Tomography; 109551C (2019) https://doi.org/10.1117/12.2509007
Event: SPIE Medical Imaging, 2019, San Diego, California, United States

Abstract

The methods for nondestructive subcellular imaging of cancer cells have attracted lots of interests. Scanning probe acoustic microscope (SPAM) has broad potential for such imaging, which could acquire information of the morphology as well as the internal structure signals. Neighborhood resonance imaging (NRI) could provide depth information in a high spatial resolution at nano-scale. However, the observations of breast cancer MDA-MB-231 cell via NRI are few. In this paper, we utilized SPAM to perform NRI for mapping MDA-MB-231 cells for specified characterization of the morphology and the internal structures. We verified the feasibility of applying NRI on cell imaging theoretically and experimentally. The simulation experiment demonstrated that NRI could succeed to image the cells with high-resolution. The experimental results illustrated that images acquired by NRI showed clear cell edges and complicated internal structure, compared to the traditional scanning acoustic imaging mode. NRI would build an important and solid basis for studying the morphology and internal structures of the cancer cells in a non-destructive way. In addition, our proposed method could be used to obtain the morphology and internal information in both solid and soft material wafers with the nano-resolution.

Citation Download Citation

Xiaoqing Li, Wenjie Deng, and Mingyue Ding "Neighborhood resonance phenomenon for cell imaging via scanning probe acoustic microscope", Proc. SPIE 10955, Medical Imaging 2019: Ultrasonic Imaging and Tomography, 109551C (15 March 2019); https://doi.org/10.1117/12.2509007

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