Super-Resolution Electrochemical Impedance Imaging with a 100 × 100 CMOS Sensor Array

This paper presents a 100 × 100 super-resolution integrated sensor array for microscale electrochemical impedance spectroscopy (EIS) imaging. The system is implemented in 180 nm CMOS with 10 μm × 10 μm pixels. Rather than treating each electrode independently, the sensor is designed to measure the mutual capacitance between programmable sets of pixels. Multiple spatially-resolved measurements can then be computationally combined to produce super-resolution impedance images. Experimental measurements of sub-cellular permittivity distributions within single algae cells demonstrate the potential of this new approach.

Ultra-high frequency acoustic impedance imaging of cancer cells

Acoustic impedance maps of cells can be used to gain insight into its microstructures and physiological state. Information about the cell’s microstructures can be acquired from the acoustic impedance map fluctuations. The maps can also help identify the dominant scattering source in cells. Furthermore, the cell’s physiological state can be inferred from the average acoustic impedance values as many physiological changes in the cell are linked to the alteration in the mechanical properties. A method called acoustic impedance imaging has been used to measure the impedance of biological tissues. We used an acoustic microscope attached to a transducer with a center frequency of 375MHz to acquire acoustic impedance images of breast cancer cells. The generated images suggest that the nucleus has an acoustic impedance similar to the surrounding cytoplasm. Fluorescence and confocal microscopy were used to correlate acoustic impedance images with the cell microstructure (the nucleus). Simulation results demonstrate the system’s capability in detecting cell microstructures close to the substrate. The average acoustic impedance were used to differentiate between single-live, clustered-live and clustered-fixed cancer cells with a measured values of 1.60±0.01 MRayl, 1.61±0.02 MRayl and 1.55±0.02 MRayl respectively.

Ultra-high frequency acoustic impedance imaging of cancer cells

Acoustic impedance maps of cells can be used to gain insight into its microstructures and physiological state. Information about the cell’s microstructures can be acquired from the acoustic impedance map fluctuations. The maps can also help identify the dominant scattering source in cells. Furthermore, the cell’s physiological state can be inferred from the average acoustic impedance values as many physiological changes in the cell are linked to the alteration in the mechanical properties. A method called acoustic impedance imaging has been used to measure the impedance of biological tissues. We used an acoustic microscope attached to a transducer with a center frequency of 375MHz to acquire acoustic impedance images of breast cancer cells. The generated images suggest that the nucleus has an acoustic impedance similar to the surrounding cytoplasm. Fluorescence and confocal microscopy were used to correlate acoustic impedance images with the cell microstructure (the nucleus). Simulation results demonstrate the system’s capability in detecting cell microstructures close to the substrate. The average acoustic impedance were used to differentiate between single-live, clustered-live and clustered-fixed cancer cells with a measured values of 1.60±0.01 MRayl, 1.61±0.02 MRayl and 1.55±0.02 MRayl respectively.

Stability of current density impedance imaging II

<p style='text-indent:20px;'>This paper is a continuation of the authors earlier work on stability of Current Density Impedance Imaging (CDII) [R. Lopez, A. Moradifam, Stability of Current Density Impedance Imaging, SIAM J. Math. Anal. (2020).] We show that CDII is stable with respect to errors in both measurement of the magnitude of the current density vector field in the interior and the measurement of the voltage potential on the boundary. This completes the authors study of the stability of Current Density Independence Imaging which was previously shown only by numerical simulations.</p>