Phase-shifting optothermal microscopy enables live-cell mid-infrared hyperspectral imaging of large cell populations at high confluency.

Rapid live-cell hyperspectral imaging at large fields of view (FOVs) and high cell confluency remains challenging for conventional vibrational spectroscopy-based microscopy technologies. At the same time, imaging at high cell confluency and large FOVs is important for proper cell function and statistical significance of measurements, respectively. Here, we introduce phase-shifting mid-infrared optothermal microscopy (PSOM), which interprets molecular-vibrational information as the optical path difference induced by mid-infrared absorption and can take snapshot vibrational images over broad excitation areas at high live-cell confluency. By means of phase-shifting, PSOM suppresses noise to a quarter of current optothermal microscopy modalities to allow capturing live-cell vibrational images at FOVs up to 50 times larger than state of the art. PSOM also reduces illumination power flux density (PFD) down to four orders of magnitude lower than other conventional vibrational microscopy methods, such as coherent anti-Stokes Raman scattering (CARS), thus considerably decreasing the risk of cell photodamage.

Enabling the autofocus approach for parameter optimization in planar measurement geometry clinical optoacoustic imaging.

In optoacoustic (photoacoustic) tomography, several parameters related to tissue and detector features are needed for image formation, but they may not be known a priori. An autofocus (AF) algorithm is generally used to estimate these parameters. However, the algorithm works iteratively and is therefore impractical for clinical imaging with planar geometry systems due to the long reconstruction times. We have developed a fast autofocus (FAF) algorithm for 3D optoacoustic systems with planar geometry. Such an algorithm exploits the symmetries of the planar geometry and a virtual source concept to reduce the dimensionality of the parameter estimation problem. The dimensionality reduction makes FAF much simpler computationally than the conventional AF algorithm. We show that the FAF algorithm required about 5 s to provide accurate estimates of the speed of sound in simulated data and experimental data obtained using an imaging system that is poised to enter the clinic. The applicability of FAF for estimating other image formation parameters is discussed. We expect the FAF algorithm to contribute decisively to the clinical use of optoacoustic tomography systems with planar geometry.

Low-cost single-point optoacoustic sensor for spectroscopic measurement of local vascular oxygenation.

Optical sensors developed for the assessment of oxygen in tissue microvasculature, such as those based on near-infrared spectroscopy, are limited in application by light scattering. Optoacoustic methods are insensitive to light scattering, and therefore, they can provide higher specificity and accuracy when quantifying local vascular oxygenation. However, currently, to the best of our knowledge, there is no low-cost, single point, optoacoustic sensor for the dedicated measurement of oxygen saturation in tissue microvasculature. This work introduces a spectroscopic optoacoustic sensor (SPOAS) for the non-invasive measurement of local vascular oxygenation in real time. SPOAS employs continuous wave laser diodes and measures at a single point, which makes it low-cost and portable. The SPOAS performance was benchmarked using blood phantoms, and it showed excellent linear correlation (R2=0.98) with a blood gas analyzer. Subsequent measurements of local vascular oxygenation in living mice during an oxygen stress test correlated well with simultaneous readings from a reference instrument.

Software-defined optoacoustic tomography.

In this work we present what we believe is the first application of software-defined optoelectronics (SDO) for bidimensional optoacoustic tomography (OAT). The SDO concept refers to optoelectronic systems where the functionality associated with the conditioning and processing of optical and electrical signals are digitally implemented and controlled by software. This paradigm takes advantage of the flexibility of software-defined hardware platforms to develop adaptive instrumentation systems. We implement an OAT system based on a heterodyne interferometer in a Mach-Zehnder configuration and a commercial software-defined radio platform (SDR). Here the SDR serves as a function generator and oscilloscope, while at the same time providing perfect carrier synchronization between its transmitter and receiver in a coherent baseband modulator scheme. This carrier synchronization enables us to have much better phase recovery. We study the performance of the OAT SDO system using different bidimensional phantoms and carry out an analysis of the reconstructed images.