This conference presentation was prepared for SPIE BiOS, 2024.

This conference presentation was prepared for SPIE BiOS, 2024.

To be determined.

Diabetic nephropathy, a common diabetes complication, affects millions globally and requires precise biomarker detection without added surgical risks. Our emphasis on label-free multi-modal imaging removes the need for sample preparation and destruction, allowing analysis of smaller biopsies. This approach offers a comprehensive and accurate assessment of structural and biochemical changes in 2D and 3D, improving our understanding of kidney disease using a single microscopy setup. Crucially, it remains compatible with conventional methods, providing a holistic view without requiring extra tissue availability. Preserving this flexibility allows us to uncover hidden insights by visualizing previously quantified data.

A stand-alone single-impulse photoacoustic computed tomography (PACT) system has been built, which successfully mitigates these limitations by integrating high spatiotemporal resolution, deep penetration, and full-view fidelity, as well as anatomical, dynamical, and functional contrasts. Based on hemoglobin absorption contrast, the whole-body dynamics and large scale brain functions of rodents have been imaged in real time. The absorption contrast between cytochrome and lipid has enabled PACT to resolve MRI-like whole brain structures. Taking advantage of the distinct absorption signature of melanin, unlabeled circulating melanoma cells have been tracked in real time in vivo. Genetically encoded photochromic proteins benefit PACT in detection sensitivity and specificity. The unique photoswitching characteristics of different photochromic proteins allow quantitative multi-contrast imaging at depths. A split version of the photochromic protein has permitted PA detection of protein-protein interactions in deep-seated tumors. As a rapidly evolving imaging technique, multiscale multicontrast PACT promises pre-clinical applications and clinical translation.

Cellular function is governed by the molecular organization and interactions at the nanoscale. Here, I will present our 3D single-molecule imaging systems that combine light sheet illumination with point spread function engineering, microfluidics, and deep learning for improved 3D single-molecule tracking of dynamics and 3D super-resolution imaging of nanoscale structures within individual mammalian cells. Optical sectioning of the cells using light sheet illumination reduces fluorescence background, photobleaching, and the risk of photodamaging sensitive samples, while microfluidics allows for environmental control. I will demonstrate applications where we have utilized these platforms to provide real-time dynamic information about chromosomal loci in living cells and structural details of several cellular structures. These imaging platforms are versatile and can be utilized to study molecular dynamics, nanoscale architectures, and molecular mechanisms to address a wide range of biochemical, biophysical, and biomedical questions related to cellular function and pathogenesis.

This study aimed to clinically translate our previously proposed translational needle photoacoustic (PA) probe by integrating it with standard prostate biopsy procedures. The all-optical components, enclosed within an 18G clinical standard steel needle, included an optical fiber diffusor and a fiber hydrophone. During the biopsy, the needle PA probe was inserted into the prostate through a guide needle, monitored by real-time transrectal ultrasound imaging fused with pre-procedure magnetic resonance imaging (MRI). Tunable wavelengths were employed to target specific tissue components. For each patient, we focused on one normal area and one cancerous area, as identified by MRI. We then quantified the PA signals via PA spectral analysis and compared them with histology results. This ongoing study aims to demonstrate the effectiveness of our proposed method in differentiating between normal and cancerous tissues in the human prostate.

We present a fully integrated, clinical-compatible SRS imaging device giving access to the complete Raman spectrum during tumor surgeries. Leveraging the advantages of a compact and robust fiber laser, we have integrated the entire microscopy system into a clinical cart, facilitating deployment in diverse clinical environments. The laser provides rapid tunability within milliseconds across a broad spectral range of 700 to 3300 cm^-1, covering biomedically relevant resonances in the fingerprint region. For detailed examination of larger tissue samples, we have designed a high-speed, low-resolution imaging mode to quickly identify cancerous hot-spots, followed by a high-resolution imaging mode.

Using dual-modality imaging, we can detect with this system the molecular composition of tissues on a 1 cm² area. Visible light imaging is done in real-time through an RGB camera, while the Raman modality uses a line-scanning system for surface imaging and has a spatial resolution of 250 μm² as well as a spectral resolution of 8 cm-1 for measurements just under 10 seconds. This system is used for ex-vivo measurements, where in a recent study, this system differentiated invasive breast cancer from normal breast tissues based on an SVM classification model.

We present a novel approach utilizing non-invasive near-infrared spectroscopy (NIRS) to assess disease severity in Extracorporeal Membrane Oxygenation (ECMO) patients. By monitoring lower limb microcirculation, our real-time assessment enables informed adjustments to ECMO settings and cardiovascular drug dosages, potentially mitigating complications and improving patient outcomes. Through machine learning, we classified VV-ECMO and VA-ECMO patient populations into high and low disease severity groups with an accuracy of 80%. The NIRS and support vector machine(SVM) combination demonstrate promising potential for clinically distinguishing disease severity in ECMO patients, providing valuable treatment insights and predictive tools for patient conditions and prognoses.

Atrial fibrillation is a common and potentially lethal arrhythmia, yet catheter radiofrequency ablation (RFA), a mainstay of treatment, frequently fails to provide long-term remission. We present a catheter capable of near-infrared diffuse reflectance spectroscopy, with a source fiber delivering broadband light and a detection fiber whose light is sent to a spectrometer. Separate catheters have been fabricated with different source-detection separations, yielding spectra sensitive to different optical properties of the underlying tissue. Optical indices have been developed from benchtop measurements to distinguish the spectral signatures of different cardiac substrates. These measurements will equip clinicians with intraprocedural feedback to improve RFA effectiveness.

Photonic technologies have seen revolutionary developments in the past decades leading from conventional optics to on-chip photonic devices. Mid-infrared (3-15 μm; MIR) sensor technology has nowadays evolved into a state-of-the-art tool for the selective and sensitive quantification of trace analytes in liquid, solid, and gaseous state in a wide variety of sensing scenarios. In this presentation, we will discuss the unique combination of mid-infrared photonics sensors with electronic nose systems for the analysis of biomarker panels in exhaled breath that are indicative of gastric cancer. Within a multi-national initiative, six so-called VOGAS analyzers were deployed around the world for screening patients establishing the utility of this innovative method.

Endometrial cancer is the sixth most common cancer and the fourth leading cause of death amongst women worldwide. Currently there are no screening strategies successfully implemented in clinical practice for the general population. Present diagnostic approaches are invasive, costly and time consuming. Here, we present results of a simple blood test showing promise for endometrial cancer detection. Both Raman and FtIR-ATR (Fourier transform Infrared Attenuated Total Reflection) spectroscopies, of blood plasma taken from patients with and without endometrial cancer, as ascertained by histopathology, are shown to yield discrimination of endometrial cancer. Spectral data classification is performed using Quasar open-source software.

The COVID-19 pandemic remains a global challenge now with the long-COVID arising. Mitigation measures focused on case counting, assessment and determination of variants and their likely targets of infection and transmission, the pursuit of drug treatments, use and enhancement of masks, social distancing, vaccination, post-infection rehabilitation, and mass screening. The latter is of utmost importance given the current scenario of infections, reinfections, and long-term health effects. Mid-infrared photonics screening platforms appear ideally suited to provide more sensitive, specific, and reliable tests that are accessible to the entire population and can be used to assess the prognosis of the disease as well as the subsequent health follow-up of patients suffering from long-COVID.

Patients with oral cavity cancer are often treated with surgery. The goal is to remove the tumor with a margin of > 5 mm of surrounding healthy tissue. Unfortunately, this is only achieved in about 15% to 26% of cases. Intraoperative assessment of tumor resection margins can dramatically improve surgical results. However, current methods are laborious, subjective, and logistically demanding. This hinders broad adoption of IOARM, to the detriment of patients. Therefore, an objective easy-to-use technique is needed, to accurately assess all resection margins intraoperatively. The role of photonic techniques in general will be discussed and the development of a high-wavenumber Raman spectroscopic technology, for quick and objective intraoperative measurement of resection margins will be presented.

Bioimaging techniques with molecular specific information will provide important insights into diagnosis, treatment, and understanding of disease pathology. To obtain molecular information, it is important to have high multiplexity and high specificity hyperspectral imaging, together with analysis techniques to interpret spectral signatures. This talk introduces pioneering discoveries and novel approaches to achieve these goals. I will introduce a new bioimaging mechanism, Raman imaging enhanced through 2D materials, an enhancement effect of molecular Raman fingerprints on the atomically-flat 2D material surfaces. It offers a new paradigm of biochemical sensing with high specificity, high multiplexity, and low noise. The selection rule for the 2D material substrates has been revealed, which is critical for device design. Hyperspectral imaging examples for brain tissues with Alzheimer’s disease will be discussed, where interpretable machine learning was further applied for new knowledge discovery. The works presented offer important guidelines to design high-performance biosensing and imaging devices, and are significant in fundamental material science and quantum science.

Quality control in molecular optical sectioning microscopy is indispensable for transforming acquired digital images from qualitative descriptions to quantitative data. Although numerous tools, metrics, and phantoms have been developed, accurate quantitative comparisons of data from different microscopy systems with diverse acquisition conditions remains a challenge. Here, we develop a simple tool based on an absolute measurement of bulk fluorophore solutions with related Poisson photon statistics, to overcome this obstacle. Demonstrated in a prototypical multiphoton microscope, our tool unifies the unit of pixelated measurement to enable objective comparison of imaging performance across different modalities, microscopes, components/settings, and molecular targets. The application of this tool in live specimens identifies an attractive methodology for quantitative imaging, which rapidly acquires low signal-to-noise frames with either gentle illumination or low-concentration fluorescence labeling.

Most diffuse imaging techniques work in the regime around 10 transport mean free path lengths (e.g., 1cm of human tissue). To realise the potential of non-invasive diffuse optical imaging modalities requires a focused effort to develop techniques in regimes beyond 100 transport mean free paths. The work presented shows evidence that there is imaging information at these extreme scattering regimes in the spatiotemporal distribution of diffuse photons, and information can be enhanced by considering key experimental parameters. Furthermore, we show numerical evidence that there is enough information to reconstruct images of absorbing shapes embedded in highly diffuse materials when using machine learning inverse retrieval algorithms. This work explores the use of highly diffuse light to enable imaging through scattering media well beyond currently accepted limits.

Recently, phasor approach has emerged as a powerful tool for extracting fluorescence lifetime and has been utilized as a biochemical component analyzing tool without complicated fitting algorithms. In this study, we propose the new method to obtain phasors from directly sampled waveforms. With deconvolution using optically obtained instrumental response function (IRF), fluorescence lifetime can be successfully measured with high precision (~ 40 psec). Cells under the various metabolic conditions were imaged through label-free fluorescence lifetime imaging microscopy with targeting nicotinamide adenine dinucleotide (NADH) and their phasors exhibited distinct clusters on phasor plots corresponding to different culturing conditions.

A smart optical probe that enables in vivo tissue type identification and the measurement of the force applied to the needle during epidural procedures is presented. This probe is meant to reduce the adverse risk associated with needle misplacement. It combines a Bragg sensor with low coherence interferometry (LCI) to measure the force applied by the operator on the standard epidural needle and differentiate tissue type presented at the tip of the epidural needle. The probe enables differentiation between different layers of tissue in the spinal region by making use of a machine-learning algorithm, which was trained on animal spinal cord tissue specimens.

Optical Photothermal Infrared (O-PTIR) is a rapidly emerging technique for super-resolution infrared spectroscopy that uses a short wavelength visible probe beam to detect infrared absorption by a sample with 10-30X better spatial resolution than conventional infrared spectroscopy. O-PTIR has been used in biomedical applications including cancer, neurodegenerative disease, cellular metabolism research, and other areas. O-PTIR has recently been combined fluorescence imaging to provide targeted IR spectroscopic analysis of fluorescently labeled regions of cells and tissue and also to rapidly detect IR absorption over a wide sample area. This presentation will overview O-PTIR technology and survey a variety of applications.