Effects of lipid composition on photothermal optical coherence tomography signals

Artificial neural network for enhancing signal-to-noise ratio and contrast in photothermal optical coherence tomography

Optical coherence tomography (OCT) is a medical imaging method that generates micron-resolution 3D volumetric images of tissues in-vivo. Photothermal (PT)-OCT is a functional extension of OCT with the potential to provide depth-resolved molecular information complementary to the OCT structural images. PT-OCT typically requires long acquisition times to measure small fluctuations in the OCT phase signal. Here, we use machine learning with a neural network to infer the amplitude of the photothermal phase modulation from a short signal trace, trained in a supervised fashion with the ground truth signal obtained by conventional reconstruction of the PT-OCT signal from a longer acquisition trace. Results from phantom and tissue studies show that the developed network improves signal to noise ratio (SNR) and contrast, enabling PT-OCT imaging with short acquisition times and without any hardware modification to the PT-OCT system. The developed network removes one of the key barriers in translation of PT-OCT (i.e., long acquisition time) to the clinic.

Machine Learning-Assisted Short-Wave InfraRed (SWIR) Techniques for Biomedical Applications: Towards Personalized Medicine

Personalized medicine transforms healthcare by adapting interventions to individuals' unique genetic, molecular, and clinical profiles. To maximize diagnostic and/or therapeutic efficacy, personalized medicine requires advanced imaging devices and sensors for accurate assessment and monitoring of individual patient conditions or responses to therapeutics. In the field of biomedical optics, short-wave infrared (SWIR) techniques offer an array of capabilities that hold promise to significantly enhance diagnostics, imaging, and therapeutic interventions. SWIR techniques provide in vivo information, which was previously inaccessible, by making use of its capacity to penetrate biological tissues with reduced attenuation and enable researchers and clinicians to delve deeper into anatomical structures, physiological processes, and molecular interactions. Combining SWIR techniques with machine learning (ML), which is a powerful tool for analyzing information, holds the potential to provide unprecedented accuracy for disease detection, precision in treatment guidance, and correlations of complex biological features, opening the way for the data-driven personalized medicine field. Despite numerous biomedical demonstrations that utilize cutting-edge SWIR techniques, the clinical potential of this approach has remained significantly underexplored. This paper demonstrates how the synergy between SWIR imaging and ML is reshaping biomedical research and clinical applications. As the paper showcases the growing significance of SWIR imaging techniques that are empowered by ML, it calls for continued collaboration between researchers, engineers, and clinicians to boost the translation of this technology into clinics, ultimately bridging the gap between cutting-edge technology and its potential for personalized medicine.

Photothermal optical coherence tomography for 3D live cell detection and mapping

Imaging cells in their 3D environment with molecular specificity is important to cell biology study. Widely used microscopy techniques, such as confocal microscopy, have limited imaging depth when probing cells in optically scattering media. Optical coherence tomography (OCT) can provide millimeter-level depth for imaging of highly scattering media but lacks the contrast to distinguish cells from extracellular matrix or to distinguish between different types of cells. Photothermal OCT (PT-OCT) is a promising technique to obtain molecular contrast at the imaging scale of OCT. Here, we report PT-OCT imaging of live, nanoparticle-labeled cells in 3D. In particular, we demonstrate detection and mapping of single cell in 3D without causing call death, and show the feasibility of 3D cell mapping through optical scattering media. This work presents live cell detection and mapping at an imaging scale that complements the major microscopy techniques, which is potentially useful to study cells in their 3D native or culture environment.

Bond-selective full-field optical coherence tomography

Optical coherence tomography (OCT) is a label-free, non-invasive 3D imaging tool widely used in both biological research and clinical diagnosis. Conventional OCT modalities can only visualize specimen tomography without chemical information. Here, we report a bond-selective full-field OCT (BS-FF-OCT), in which a pulsed mid-infrared laser is used to modulate the OCT signal through the photothermal effect, achieving label-free bond-selective 3D sectioned imaging of highly scattering samples. We first demonstrate BS-FF-OCT imaging of 1 µm PMMA beads embedded in agarose gel. Next, we show 3D hyperspectral imaging of up to 75 µm of polypropylene fiber mattress from a standard surgical mask. We then demonstrate BS-FF-OCT imaging on biological samples, including cancer cell spheroids and C. elegans. Using an alternative pulse timing configuration, we finally demonstrate the capability of BS-FF-OCT on imaging a highly scattering myelinated axons region in a mouse brain tissue slice.

Immersion optical clearing of adipose tissue in rats: ex vivo and in vivo studies

Optical clearing (OC) of adipose tissue has not been studied enough, although it can be promising in medical applications, including surgery and cosmetology, for example, to visualize blood vessels or increase the permeability of tissues to laser beams. The main objective of this work is to develop technology for OC of abdominal adipose tissue in vivo using hyperosmotic optical clearing agents (OCAs). The maximum OC effect (77%) was observed for ex vivo rat adipose tissue samples exposed to OCA on fructose basis for 90 minutes. For in vivo studies, the maximum effect of OC (65%) was observed when using OCA based on diatrizoic acid and dimethylsulfoxide for 120 minutes. Histological analysis showed that in vivo application of OCAs may induce a limited local necrosis of fat cells. The efficiency of OC correlated with local tissue damage through cell necrosis due to accompanied cell lipolysis.

Three-dimensional opto-thermo-mechanical model for predicting photo-thermal optical coherence tomography responses in multilayer geometries

Photothermal optical coherence tomography (PT-OCT) is a functional extension of OCT with the ability to generate qualitative maps of molecular absorptions co-registered with the micron-resolution structural tomograms of OCT. Obtaining refined insight into chemical information from PT-OCT images, however, requires solid understanding of the multifactorial physics behind generation of PT-OCT signals and their dependence on system and sample parameters. Such understanding is needed to decouple the various physical effects involved in the PT-OCT signal to obtain more accurate insight into sample composition. In this work, we propose an analytical model that considers the opto-thermo-mechanical properties of multi-layered samples in 3-D space, eliminating several assumptions that have been limiting previous PT-OCT models. In parametric studies, the model results are compared with experimental signals to investigate the effect of sample and system parameters on the acquired signals. The proposed model and the presented findings open the door for: 1) better understanding of the effects of system parameters and tissue opto-thermo-mechanical properties on experimental signals; 2) informed optimization of experimentation strategies based on sample and system parameters; 3) guidance of downstream signal processing for predicting tissue molecular composition.

Spectroscopic thermo-elastic optical coherence tomography for tissue characterization

Optical imaging techniques that provide free space, label free imaging are powerful tools in obtaining structural and biochemical information in biological samples. To date, most of the optical imaging technologies create images with a specific contrast and require multimodality integration to add additional contrast. In this study, we demonstrate spectroscopic Thermo-elastic Optical Coherence Tomography (TE-OCT) as a potential tool in tissue identification. TE-OCT creates images based on two different forms of contrast: optical reflectance and thermo-elastic deformation. TE-OCT uses short laser pulses to induce thermo-elastic tissue deformation and measures the resulting surface displacement using phase-sensitive OCT. In this work we characterized the relation between thermo-elastic displacement and optical absorption, excitation, fluence and illumination area. The experimental results were validated with a 2-dimensional analytical model. Using spectroscopic TE-OCT, the thermo-elastic spectra of elastic phantoms and tissue components in coronary arteries were extracted. Specific tissue components, particularly lipid, an important biomarker for identifying atherosclerotic lesions, can be identified in the TE-OCT spectral response. As a label-free, free-space, dual-contrast, all-optical imaging technique, spectroscopic TE-OCT holds promise for biomedical research and clinical pathology diagnosis.

Transient-mode photothermal optical coherence tomography

Photothermal optical coherence tomography (PT-OCT) is an emerging extension of OCT, which forms images based on both scattering and absorption of light. The speed of PT-OCT, however, has been limited by the necessity for lock-in detection with extensive temporal sampling of the sample's PT response. Here, we demonstrate transient-mode PT-OCT (TM-PT-OCT), which increases the effective A-line rate by orders of magnitude from 10-100 Hz to 1.5-7.5 kHz, by interrogating the sample's transient thermal response to a single diode laser pulse. Functional imaging of moving samples with TM-PT-OCT at video rate is also presented. This significant improvement in imaging speed is expected to open the door for downstream integration of PT-OCT in clinical systems for in vivo imaging.

Handheld Thermo-Photonic Device for Rapid, Low-Cost, and On-Site Detection and Quantification of Anti-SARS-CoV-2 Antibody

With the emergence of vaccines and antibody therapeutics, rapid and scalable platforms are needed to quantify the antibody response of individuals. Lateral flow immunoassay (LFA) based test strips provide a rapid, low-cost, and point-of-care approach to antibody testing against the SARS-CoV-2 virus. These convenient and scalable tests, however, are qualitative in nature and cannot quantify the immune response of the infected and/or vaccinated individuals. This study reports on the development of a rapid, low cost and portable thermo-photonic device that enables sensitive detection and quantification of antibody levels using commercially available COVID-19 Antibody LFAs. Unlike conventional LFA readers, the developed technology is based on sensing the infrared thermal radiation of tag gold nanoparticles following laser excitation (aka photothermal response). Our proof-of-concept results with humanized monoclonal anti-SARS-CoV-2 Spike receptor-binding domain (RBD) IgG demonstrate that the thermo-photonic technology can detect and quantify antibody concentrations within the clinically relevant range and with a limit of detection of [Formula: see text]/ml. The reader in conjunction with antibody LFAs offers a low-cost, portable, and scalable solution for assessment of the degree of immunity in populations, quality control of convalescent plasma donations for antibody therapeutics, and monitoring the immune response of infected individuals and vaccine recipients.