Tissue Optics and Photonics III

The current study aims at evaluating if absorption and scattering coefficients measurements combined to automatic classification based on machine-learning methods could be of interest in assisting urologists with kidney stones characterization. Absorption and scattering coefficients were measured using the inverse adding doubling method (IAD). This method based on solving inverse problem takes as input data measurements acquired on a double integrating spheres optical bench developed in the CRAN laboratory. The dataset is made of absorption and scattering coefficients measured every 10 nm from 535 to 845 nm on 16 kidney stones: 4 kidney stones in each diagnostic class under consideration (1a, 3a, 4c and 5a). Class 3a (5a respectively) kidney stones display the highest (lowest resp.) absorption and scattering coefficients: 3 and 30 mm-1 (1 and 10 mm-1 respectively) at 650 nm. Support-vector machine (SVM) and k-nearest neighbors (k-NN) methods were used to perform automatic classification: k-NN reached 98%-accuracy in the four-class confusion matrix when considering both absorption and scattering coefficients.

The present work shows design, development, and testing of the multimodal optical setup for simultaneous auto-fluorescence imaging, spectroscopy and quantitative phase microscopy (SAF-QPM) from same field of view(FOV). The SAF-QPM combines the capabilities of autofluorescence, offering molecular insights into metabolic activities, with quantitative phase imaging, providing nanometres-level sensitivity to cellular morphology and refractive index distribution. The autofluorescence serves as a biomarker for abnormal cellular changes associated with cancer development. Simultaneous incorporation of quantitative phase microscopy of the same tissue section probes the refractive index-dependent changes in the cellular morphology associated with cancer development. Non-interferometric QPI technique is used to retrieve the phase information of the sample, which overcomes the limitations of instability and coherent noise associated with interferometric QPI techniques. The incorporation of simultaneous AF and QPM from the same field of view enhances the accuracy and specificity of label-free cancer diagnosis.

Non-invasive pulse wave monitoring is now widely used in health and wellness applications. Very often, the use of this measurement to trace physiological parameters is indirect. We propose here a bench for synchronized acquisition of optical and ultrasound signals at high rates (over 100 Hz). Optical acquisition is performed with an in-house system enabling us to perform multispectral PPG. We report here the description of the bench, the performances obtained, and the first bimodal acquisitions made on dynamic phantoms.

We present comprehensive studies of terahertz time-domain spectroscopy (THz-TDS) imaging of biomedical materials, specifically, pancreatic ductal adenocarcinoma (PDAC) in genetically modified mouse tissue samples. PDAC is a lethal malignancy in humans that, presently, poses very significant challenges in therapeutic intervention. We propose THz TDS imaging as a novel approach to map and measure the cytotoxic responsivity of PDAC to neoadjuvant therapies like stereotactic body radiation. Our high-resolution imaging, employing as biomarkers the index of refraction and the absorption coefficient, provides valuable insights into tissue changes post-therapy, offering a promising avenue for assessing treatment efficacy.

Each year, about 30% of all newly diagnosed cancer cases in women worldwide are breast cancers. One of the most common techniques for breast cancer diagnosis is mammography. However, this technique provides limited functional information regarding breast tissue morphology. In the cases of suspected malignancy invasive techniques such as biopsy are implemented. In this work an optical deep tissue imaging technique called ultrasound optical tomography (UOT) which combines laser light and ultrasound is implemented for a non-invasive lesion characterization in a breast tissue. The experiments were performed using 794 nm wavelength, 6 MHz ultrasound frequency and the narrowband spectral filter material Tm3+: LiNbO3. The measurements were carried out in 5 cm thick agar phantoms using a range of tumor mimicking inclusions of 3 different sizes. Based on the literature, the optical scattering and absorption properties of the inclusions were consistent with breast tumors. This work is the first deep tissue imaging demonstration using UOT at tissue relevant wavelengths.

The ex vivo porcine lung tissue exposure to nicotine-flavour free e-liquid was examined in-depth using confocal Raman micro-spectroscopy. It was found that the lung-related Raman bands and autofluorescence intensities were enhanced after exposure to e-liquid for all depths and treatment time (first and second treatments) due to the optical clearing effect of glycerol and propylene glycol as an OC agent. The nicotine-flavour free e-liquids that contain glycerol and propylene glycol could potentially be used in clinical protocols for lung disease discrimination in-depth using Raman-based in vivo bronchoscopy due to light scattering reduction as an optical clearing agent.

Perceiving the depth of flat and thin adenomas and the extent of invasion is vital in staging, diagnosis, treatment planning, and surgical precision. Here, we utilize fiber-optic Raman spectroscopy to simultaneously predict the depth and thickness of thin sub-surface tumors using multi-layer phantoms. Silicone phantoms incorporating Hydroxyapatite are used as a Raman scatterer to indicate malignant calcifications. The signal intensity for varied tumor depths and thicknesses is numerically simulated and verified using experiments. The high-wavenumber Raman spectrum is captured using a fiber-optic low-resolution spectrometer. Partial Least Squares Regression (PLSR) analysis is carried out on the acquired dataset for predicting the tumor depth and thickness with a Root Mean Square Error (RMSE) of 0.268 mm and 0.120 mm, respectively.

Fatty liver disease, or steatosis, is a pathology characterized by the presence of fat droplets in the cytoplasm of hepatocytes. This common and potentially severe condition can result in liver damage and various health complications. The current gold standard method to assess steatosis involves an invasive biopsy and a subjective anatomopathological analysis. In this study, we introduce a novel non-invasive approach based on near infrared diffuse reflectance spectroscopy. Currently, NIR DRS methods are often use to quantify fat fraction but our method provides a way to quantify a fraction of hepatocytes affected by steatosis and thus can be directly compared to anatomopathological analysis. The results obtained from this method demonstrate a strong correlation with the gold standard.

Corneal crosslinking (CXL) with UVA light is the primary treatment for keratoconus, a disease that affects cornea's stability, transparency and shape. UVA-CXL has limitations in penetration depth and unwanted irradiation on healthy tissue. As an alternative, a near-infrared femtosecond laser was used for targeted corneal crosslinking of fresh pigs’ corneas. Brillouin microscopy was implemented as a non-destructive method to determine the viscoelastic properties, by measuring the Brillouin shift. We compared the Brillouin shifts measured for UVA-CXL and fs-CXL treated corneas. Measurements were also performed on UVA-CXL pure bovine collagen I in order to correlate the changes observed in CXL cornea. An increase in Brillouin shift before and after crosslinking, for both UVA and femtosecond-CXL are measurable. We demonstrate the precision and efficacy of using femtosecond CXL in spatial targeted CXL at depth in corneal tissues.

In this work we investigate the correlation between cell stiffness and viscoelastic parameters, mainly determined by the actin cortex, and plasma membrane microviscosity, mainly determined by its lipid profile, in cancer cells, as these are key to their migratory ability. These data clearly indicate that mechanical parameters, determined by two different cellular structures, are interconnected in cells and play a role in their intrinsic migratory potential.

Photobiomodulation (PBM) utilizes light to stimulate cellular responses in medical and therapeutic fields. This study investigates how light probe design influences tissue penetration. Factors like spot size, geometry, and materials were explored. Monte Carlo simulations were performed in tissue phantoms.Results reveal how probe design optimization can enhance PBM's safety and efficacy, providing insights for personalized treatment protocols. Understanding light interactions in biological tissues is vital for tailoring therapy to individual patients and specific equipment.

Photothermal therapy is a well-established method for cancer treatment, which is based on the incorporation of photoresponsive materials into the tumor area and their further irradiation by a laser for light-to-heat conversion. However, overheating of cells can affect various cellular functions and mechanisms, thus it is crucial to monitor the temperature during optical hyperthermia. One of the possible approaches of nanothermometry is a Stokes shift of Raman response, which is inherent in silicon nanoparticles. To apply silicon nanoparticles as optical heaters, they should possess a narrow size distribution to meet the critical coupling conditions. Silicon nanoparticles are usually fabricated using laser ablation, but this approach suffers from polydispersity. To overcome these limitations, we integrated plasmonic (gold) and dielectric (silicon) nanostructures in a single platform to develop hybrid nanomaterials with outstanding optical performances and real-time temperature monitoring inside cells. It allows the implementation of polydisperse hybrid nanoparticles as efficient nanoscale heaters and thermometers instead of monodisperse pure silicon ones.

Thermo-plasmonics is an emerging field where plasmonic nanoparticles are used as nano sources of heat. This simple phenomenon is the basis of numerous biomedical applications such as cancer therapies and targeted drug delivery. Here, we present an experimental and computational analysis of the heating characteristics of a thermo-plasmonic optical fiber probe. It consists of an optical fiber decorated with densely packed gold nanoislands fabricated by a solid-state dewetting process on the fiber facet. The simulation results are validated by the steady-state and transient temperature measurements taken in the air with a high-resolution thermal camera. We further used the numerical simulations to estimate the temperature gradients in liquid environments and brain tissue where such probes are intended to be used. Based on simulations and experimental results obtained in this work, we foresee that our thermo-plasmonic optical fiber probe can be exploited in several biomedical applications.

The laser safety standard IEC 60825-1:2014 is based on retinal damage thresholds of symmetrical exposure scenarios or retinal images. In reality, retinal exposure scenarios of laser systems feature aberration-afflicted, asymmetrical retinal images, for example resulting from optical aberrations such as coma and astigmatism. In terms of safety and performance of the laser systems, it is important to consider asymmetrical retinal images. For this consideration, a computer model for asymmetrical retinal images is recommended. A computer model for symmetrical retinal geometries exists, which is validated on experimental data of non-human primates and solves the heat transfer equation. The retinal damage thresholds are calculated by inserting the temperature behavior into the Arrhenius equation. The focus of the work presented here is the extension and further development of the computer model and elaborates the difficulties to simulate retinal damage thresholds of asymmetrical exposure scenarios while maintaining validation.

Carbon-based nanoparticles (CNPs), owing to their abundance and excellent optical and electronic properties, along with their small size and high surface area-to-volume ratio, are widely used in various fields of health applications. Green synthesis procedures have emerged as promising approaches for the toxic alternatives serving in the biomedical and plant health industries to produce nanoparticles. Despite their numerous benefits, the use of nanoparticles also raises concerns about their potential health and environmental impacts. This work showcases a cheap and toxic-free synthesis of CNPs from pink and white petal extracts of Catharanthus roseus flower and studies the surface, size, chemical composition, and optical behavior. The results from two different colored sources were explored, compared, and reported This paper also highlights the future scope of using these nanoparticles in various medical and plant health domains.

Optical cavities with nonlinear elements and delayed self-coupling are widely explored candidates for photonic reservoir computing (RC). For time series prediction applications that appear in many real-world problems, energy efficiency, robustness and performance are key indicators. With this contribution I want to clarify the role of internal dynamic coupling and timescales on the performance of a photonic RC system and discuss routes for optimization. By numerically comparing various delay-based RC systems e.g., quantum-dot lasers, spin-VCSEL (vertically emitting semiconductor lasers), and semiconductor amplifiers regarding their performance on different time series prediction tasks, to messages are emphasized: First, a concise understanding of the nonlinear dynamic response (bifurcation structure) of the chosen dynamical system is necessary in order to use its full potential for RC and prevent operation with unsuitable parameters. Second, the input scheme (optical injection, current modulation etc.) crucially changes the outcome as it changes the direction of the perturbation and therewith the nonlinearity. The input can be further utilized to externally add a memory timescale that is needed for the chosen task and thus offers an easy tunability of RC systems.

Programmable photonic circuits manipulate the flow of light on a chip by electrically controlling a set of tunable analog gates connected by optical waveguides. Light is distributed and spatially rerouted to implement various linear functions by interfering signals along different paths. A general-purpose photonic processor can be built by integrating this flexible hardware in a technology stack comprising an electronic monitoring and controlling layer and a software layer for resource control and programming. This processor can leverage the unique properties of photonics in terms of ultra-high bandwidth, high-speed operation, and low power consumption while operating in a complementary and synergistic way with electronic processors. This talk will review the recent advances in the field and it will also delve into the potential application fields for this technology including, communications, 6G systems, interconnections, switching for data centers and computing.

Information on skin phototype and ages of cosmetic and medical interest in some procedures like objective evaluation of cosmetic treatments effectiveness, laser wavelength choice, risk of skin cancer recurrence and skin evaluation before cosmetic surgeries [1-3]. However, all existing methods for determining these parameters are not very accurate and cannot always be applied in dermatological practice. Optical spectroscopy combining autofluorescence (AF) and diffuse reflectance (DR) may be a promising and non-invasive alternative to these tests. In the current study, a bimodal spectroscopic device was used to obtain in vivo spatially resolved AF and DR spectra of skin in the visible range. Five LEDs featuring wavelength peaks at 365, 385, 395, 400 and 415 nm and a xenon lamp featuring a 350-800 nm spectral emission were used as light sources. Four source-detector separation (SDS) were used: 400, 600, 800, and 1000 μm. Spectra were taken in different anatomical sites on 131 patients of different age and gender during a clinical study. Spectra were analysed using different classification and regression methods.

Wide-field diffuse optical tomography (DOT) offers a compelling approach to reveal the functional and structural states of tissue in clinical and preclinical studies since it allows rapid and non-invasive imaging of tissue optical properties. The spatial frequency domain (SFD) imaging is a simple and robust implementation of the wide-field strategy. We present here a wide-field illumination time-domain (TD) DOT for three-dimensional reconstruction within a shallow region under the illuminated surface of the turbid medium. The methodologically fundamental is laid on the single-pixel SFD imaging that facilitates the adoption of the well-established time-correlation single-photon counting (TCSPC)-based time-resolved detection and generalized pulse spectrum techniques (GPST)-based reconstruction. We proposed a model based on the δ-P1 approximation to enhance the accuracy in the near-field. Additionally, we have developed a single-pixel TD-SFD-DOT system that embeds the TCSPC time-resolved detection in the SFD imaging framework.

This study investigates the use of Resonant Raman (RR) spectroscopy as a non-invasive method to measure carotenoid levels in human skin, which are indicators of dietary richness in fruits and vegetables and overall antioxidant status. Traditional methods require invasive tissue removal, but RR spectroscopy offers a non-invasive alternative. The study compares two excitation wavelengths and incorporates a feedback system to adjust for laser power variations. It also examines the impact of water-filtered Infrared-A (wIRA) irradiation on carotenoid levels and background fluorescence in the skin, finding that wIRA decreases both, thereby improving the signal-to-background ratio.

Introduction: Presently, the diagnosis of cataracts relies upon the utilization of a slit lamp. This method of examination is inherently subjective, contingent upon the level of expertise possessed by the attending ophthalmologist. That is why our aim was to evaluate lens thickness parameter's utility for cataract diagnoses. Method: We investigated 1750 patients (age 40 till 75) which were separated in two groups: cataract patients (n=750) and control group (n = 1000). The lens thickness parameter (LT) and anterior chamber depth (ACD) were measured with IOLMaster® 700 (Zeiss) and analyzes with ANOVA test, The IOLMaster® 700 is a frequently used device which is utilized for intraocular lens (IOL) measurements. Results. Overall results demonstrates that the cataract groups lens thickness parameter (mean 4.89 ± 0.11mm) was greater than control groups (mean 4.69 ± 0.17mm) and there was a statistically significance between the results (p = 0,01). Control groups ACD results showed similarities with cortical cataract results and there were overlapping (p = 0.15). Conclusion. Lens thickness parameter can be used as an additional criteria to differentiate cataract diagnoses.

In this study, we present an integrated Raman fiber laser thermal therapy surveillance system coupled with multifunctional optical coherence tomography (OCT). The bench-top swept-source OCT (SS-OCT) system, featuring a dynamic algorithm (D-OCT), is utilized to monitor the real-time laser-induced dynamic processes in tissue. Moreover, the results from OCT angiography (OCTA) illustrate the impact of laser surgery on vascular distribution, which can be further corroborated by D-OCT thermal delivery data. Furthermore, we introduce a classification method to delineate the various zones affected by thermal changes in tissue during laser surgery, thereby improving the visualization of the thermal dynamic processes.

We present the development of optical phantoms for the evaluation of biomedical optics in the spectral range from 400 to 1400 nm. A set of 9 phantoms are produced, which cover the expected optical range of tissue. Silicone was used as the substrate, a black pigment as the absorber and zirconium oxide particles were used to adjust the scattering. A standardised manufacturing process was developed to ensure reproducibility of the scattering. An integrating sphere was applied as a reference system to determine the optical properties. Different scattering particles were investigated for their scattering behaviour. The particles with the most spectrally constant scattering behaviour were used in order to be able to apply the phantoms over a wide range of wavelengths. This allows us to use the phantoms in the VIS and NIR.

This study presents an innovative method for creating optical phantoms of small animals with a focus on brain hemodynamics. Leveraging 3D printing technology, the approach produces long-lasting, flexible phantoms with high accuracy in mimicking various tissue types. The organ blocks, replicating structural and optical properties, facilitate experiments simulating real-life scenarios. The mouse model, which replicates the size and shape of real animals, increases the accuracy and reliability of the research. Rigorous confirmation of optical properties makes the phantom an ideal tool for evaluating and calibrating optical imaging systems. Its versatility enables researchers to explore diverse optical and physiological parameters in a controlled environment, providing a cost-effective solution for studying brain hemodynamics and tissue-specific optical interactions. Validation against living animals using advanced imaging techniques, such as Diffusion Correlation Spectroscopy and Laser Speckle Contrast, confirms the phantom's accuracy in replicating blood flow characteristics in a mouse brain.

In today's world, where food security and safety are key issues, perishable food preservation is a big challenge. Food preservation techniques have advanced significantly throughout time, with traditional methods like canning, drying, and salting giving way to more modern methods like refrigeration and freezing. However, as the global population grows and the demand for fresh, safe, and nutritious food grows, so does the demand for novel, sustainable, and effective food preservation technology. According to the research, food prices have risen by 24.1% in the previous year, and food supply has begun to decrease. Another big issue is food waste. The globe creates 931 million tonnes of food waste each year. Light technologies of various wavelengths are being researched to discover solutions to these problems, as are attempts to ensure that foods can be preserved for longer periods of time.

Ultrasound Optical Tomography (UOT) combines ultrasound and near-infrared optical imaging to offer a non-invasive method for characterizing biological tissues. By analyzing only the light that has been frequency-shifted by the ultrasound, it provides the optical contrast of light with the spatial resolution of ultrasound. To assess the technique’s utility, Monte Carlo simulations are performed on realistic computational tissue phantoms that mimic the complexity of breast tissue, including adipose and glandular compartments and skin. We examine how tumor properties affect the UOT signal, with the aim of distinguishing between benign glandular tissue and malignant tumors. The results indicate that UOT reliably can distinguish 1 cm^3 tumors from glandular tissue at a level of two standard deviations, assuming the tumor has a roughly 45% increased optical absorption compared to benign lesions due to increased hemoglobin levels or reduced oxygenation. This abstract presents the current development and optimization of UOT, while underscoring its significance as a non-invasive tool that may revolutionize breast tumor diagnosis and monitoring.

The guiding or focusing of light, crucial in many applications, often relies on bulky optical elements that are difficult to place in delicate mediums like biological tissue. In current systems, the optical components are located outside the sample, limiting possibilities due to geometric constraints. Scattering further complicates the control of light within non-homogeneous media, restricting operating beyond 1 mm of depth. A promising solution involves shaped ultrasound to induce refractive index gradients within the tissue, acting as embedded lenses or waveguides. However, existing methods rely on bulky ultrasonic transducers, introducing invasiveness and fixing the ultrasound geometry. The proposed approach uses photoacoustic generation of pressure waves within the medium, allowing light guiding without geometrical constraints. As it is successfully demonstrated in tissue phantoms with different scattering coefficients, this method offers a promising solution in conditions not feasable with traditional external optical elements.

A characteristic feature of diabetes mellitus is an increase in blood glucose levels and the development of hyperglycemia, which provokes the development of metabolic changes at the level of cells and tissues of the body. The dysfunction of pancreatic beta cells with impaired insulin secretion and a decrease in their mass is the main sign of the development of both types of diabetes. Thus, beta cells are the main target in the development of new therapeutic approaches. In this work, using a model of pancreatic beta cells (RINm5F), the effect of photosensitizer-free laser-induced singlet oxygen (SO) on the bioenergetics of this type of cells was studied. It was found that laser exposure affects a number of parameters characterizing the bioenergetics of cells: mitochondrial membrane potential, NADH, FAD and ATP levels. The totality of the results obtained may indicate the potential possibility of using laser-induced SO in the regulation of beta cell functions.

Transcranial photobiomodulation (tPBM) has emerged as a promising economical point-of-care tool to enhance mitochondrial dynamics, mitigate neuroinflammation, improve sleep and cognitive functions in various CNS disorders. Its propensity to modulate cerebrovascular tone can potentially alter the cerebral hemodynamics. We set out to investigate whether tPBM can influence the brain oxygenation as assessed by fNIRS in healthy subjects with a body positional challenge.

Photopletysmographic methods for cardiovascular parameters monitoring have been extensively investigated. Yet, there is still a lack of consensus on the signals origins and sensors are designed based on qualitative intuitions. We present the radiometric calibration of a versatile optical workbench that allows quantitative multi-spectral measurements on several distances source/detector simultaneously. We propose here a method to retrieve both incident and outgoing radiant fluxes on the studied medium, thus allowing diffuse reflectance quantitative measurements

In this work, ablation of clinically relevant mammalian brain tissue was demonstrated using 200-fs laser pulses at 205 nm wavelength. The ablated region depth could be controlled by adjusting the pulse energy and pulse spatial separation; using low-energy deep ultraviolet laser pulses allowed for the removal of very fine layers of tissue. Histopathological analysis revealed minimal thermal damage to the tissue regions adjacent to the ablation craters. Optical coherence tomography was used for surface profile measurements of the laser-processed tissue. The presented deep ultraviolet ultrashort laser ablation technique could be utilised in surgical procedures that require precise tissue removal, for example to facilitate more complete resection of tumour margins located close to brain critical structures where use of conventional surgery tools might cause irreparable damage.

Collagen type I is extensively employed in 3D cell culture and tissue engineering.This research investigates the impact of embedded microbeads of different types on the fibrillogenesis process in collagen type I hydrogels. Our findings reveal that the presence of microbeads within the collagen matrix alters the fibrillogenesis dynamics. Specifically, carboxylated fluorescent microbeads accelerate gelation by 3.6 times, while silica microbeads decelerate collagen fibril formation by a factor of 1.9, in comparison to pure collagen hydrogels. These observations suggest that carboxylate microbeads serve as nucleation sites, influencing the binding of early collagen fibrils to the microbeads.

Conventional histopathological methods, being time-consuming and resource-intensive, leave room for improvement with label-free optical techniques. In this study, our novel metasurface-based polarimeter has been verified for imaging of unstained histological tissue blocks and benchmarked against industrially calibrated polarization measurement systems. The novel system is based on a specifically designed metamaterial grating enabling movement/rotation-free characterization of the light polarization state, ensuring reduced measurement noise in the obtained polarimetric data. The demonstrated potential suggests a transformative, affordable, and scalable standalone system, enhancing accessibility for researchers and clinicians in polarization-based biotissue imaging.

The challenging task of precisely delineating neoplastic brain tissue during neurosurgery finds a promising solution in imaging Mueller polarimetry. This method shows great potential for real-time tumor border visualization. In this work, we evaluated for the first time the polarimetric properties of various brain tumor types in fresh thick brain specimens. A novel neuropathology protocol was developed to enable precise mapping between histological and polarimetric data, allowing histological data to serve as a reliable ground truth for tissue characterization. We then quantified and correlated the polarimetric parameters between healthy and neoplastic brain tissue samples. The main finding of this study is the detection of randomization of the azimuth of the optical axis in neoplastic regions. Thus, this research has significant potential in improving brain tumor segmentation and paves the way for guiding intraoperative tumor resections, supporting decision making, and improving patient prognosis.

During neurooncological surgery the intraoperative visual differentiation of healthy and diseased tissue is often challenging. In our prior work we demonstrated that imaging Mueller polarimetry is a promising tool for both ex- and in-vivo brain tissue differentiation and diagnosis. Apart from the superficial 2D-polarimetric maps of brain fiber tracts that can be generated with IMP, the knowledge of the probing tissue volume is crucial for the estimation of residual tumor thickness and the proximity of underlying fiber tracts. Here, we quantified the penetration depth of a probing light beam by evaluating the polarimetric maps of formalin-fixed (FF) human cerebral corpus callosum sections of different thicknesses measured in reflection, and we extended the analysis to FF gray matter brain sections of different thicknesses. Finally, we evaluated the light penetration depth at different wavelengths. Our findings allow us to define different thresholds of light penetration depth for white and gray brain matter.

In this study, we harnessed the capabilities of Multispectral Mueller Matrix Imaging (MMI) at six distinct wavelengths in the visible range to analyze the intricate structures of the brain using lamb cerebral samples. The imaging of several brain sections revealed that white matter (WM) exhibits pronounced depolarization and retardance when contrasted with grey matter (GM), a phenomenon likely attributed to the elevated scattering and anisotropic nature of WM. More precisely, with an increase in wavelength, both depolarization and retardance also exhibit an increase, suggesting enhanced penetration into deeper tissue layers. Additionally, employing various wavelengths enabled us to trace the dynamic shifts in the optical axis of retardance within the brain tissue, offering insights into the morphological changes in WM beneath the cortical surface. The consistency observed in our results underscores the promise of Multispectral Wide-Field MMI as a non-intrusive, efficacious modality for probing brain architecture.

Investigating optical properties (OPs) is crucial in the field of biophotonics. Various techniques are available for deriving OPs, with inverse Monte Carlo simulations (IMCS) being the most advanced for ex-vivo contexts. However, identifying the spectral behavior of each microscopic absorber and scatterer responsible for generating these OPs requires further experimentation. To tackle this issue, a customized autoencoder neural network (ANN) is suggested. The ANN computes optical properties (OPs) from measurements, where the bottleneck corresponds to the number of absorbers and scatterers. The presented ANN functions asymmetrically and computes the final OPs using a linear combination of absorbers and scatterers. Consequently, the decoder's weight corresponds to the constituent's OPs spectral behavior. Validation was conducted by utilizing intralipid as a scatterer and ink as an absorber. The employment of the decoder weights facilitated the successful extraction of the spectral shape of every constituent.

Fluorescence spectroscopy is a technique proposed to improve the detection of tumor boundaries during fluorescence-guided neurosurgery. More sensitive than fluorescence microscopy, this technique can provide spectral measurements of fluorescence that are post-processed to extract qualitative or even quantitative information on fluorophores present in the tissue probed. To obtain quantitative information, this technique requires modeling the propagation of radiation in the brain, considering the optical properties of the tissue as well as the fluorescence phenomenon. The present work is devoted to the development and application of Monte Carlo methods including the fluorescence phenomenon, enabling us to study the effects of optical properties on the measured signal and, consequently, on biomarker quantification. Symbolic Monte Carlo method based on orthogonal polynomial sequences is developed to express a physical observable as a function of the fluorophore concentration in a single simulation. The results obtained for the case of a brain composed of grey matter and different fluorophore concentrations are studied and show good agreement with standard Monte Carlo approaches.

Artifacts and noise hamper the signal quality of functional near-infrared spectroscopy (fNIRS) signals. As fNIRS measurement data collection is time consuming and expensive, and the low-quality data affects the analysis results, reliable early detection of poor-quality signals is crucial. In this human brain study, we utilized previously developed deep learning approach with short-time Fourier transform to evaluate the quality of raw fNIRS signals with wavelengths 690 nm, 810 nm, 830 nm and 980 nm measured during breath hold protocol. The results show the high potential of using deep learning approach for fNIRS signal quality assessment.

Colorectal cancer is the second most common cancer and the second with the highest associated deaths in the world. Methods used in clinical practice for colon cancer diagnosis are fairly effective but quite unpleasant and not always applicable in situations where the patient has symptoms of colonic obstruction. This problem can be solved by the use of optical methods that can be applied less invasively. This study presents the results of classification of cancerous and healthy colon tissue absorption coefficient spectra. The absorption coefficient was measured using direct calculations from the total reflectance and total transmittance spectra obtained ex vivo. Classification was performed using support vector machine, multilayer perceptron and linear discriminant analysis

This study analyses intraoperative multispectral images taken from 47 brain tumour surgeries to investigate the diagnostic and surgical guidance potential of MSI. The research enrolled patients with various tumour types and introduces a hybrid model, uniting a transformer-coupled convolutional neural network (CNN), tailored for multispectral brain image segmentation. Leveraging MSI, the model was preliminarily assessed on ten meningioma and thirty-three glioma cases, each categorized into seven distinct classes. The model demonstrated a promising overall accuracies of 88.14% for meningioma and 85.64% for glioma. These initial results highlight the potential of the proposed hybrid architecture in multispectral brain image segmentation, laying the foundation for future research to optimize the model's performance with a larger patient cohort.

Spatial light distribution prediction is highly useful but challenging; no imaging method is currently capable of measuring it at different depths. This study introduces a novel technique for fluence quantification within blood vessels through the ratio of photoacoustic fluctuation imaging (PAFI) and ultrasound power Doppler (USPD). However, their direct coupling fails in accurately estimating the fluence due to differences in the Point Spread Functions (PSFs), leading to varying image resolution and amplitude dependence over vessel sizes. To address this, we propose a model-based matrix approach to apply a non-stationary PSF filter to USPD. Validation through 3D simulations and experiments with tissue-mimicking phantoms demonstrates accurate fluence recovery. Results indicate a robust correlation with the Monte Carlo-simulated ground truth, even in unresolved vessels. This direct imaging technique uniquely offers precise measurement of light distribution in ubiquitous blood vessels, showing great potential for clinical applications and quantitative photoacoustic inverse problems.

Optical imaging is a marker-free, contactless, and non-invasive technique that is able to monitor hemodynamic and metabolic brain response following neuronal activation during neurosurgery. However, a robust quantification is complicated to perform during neurosurgery due to the critical context of the operating room, which makes the calibration and adjustment of optical devices more complex. To overcome this issue, tissue-simulating objects that mimic the properties of biological tissues are required for the development of detection or diagnostic imaging systems. In this study, we developed a digital instrument simulator to optimize the development of a novel hyperspectral system for application in brain/cortex imaging. This digital phantom is based on white Monte Carlo simulations of the light propagation in tissues. The output of the Monte Carlo simulations are integrated with the key instrument parameters in order to produce realistic images. The results can be beneficial and useful within the framework of our EU-funded HyperProbe project, which aims at transforming neuronavigation during glioma resection using novel hyperspectral imaging technology.

In the field of Biomedical Optics, understanding how transparent layers affect light propagation in tissue is crucial for optimizing therapeutic and diagnostic applications. We employed Monte Carlo simulation to analyze changes in light behavior when introducing a transparent layer onto a multilayer optical skin phantom. Our study revealed that adding a transparent layer alters the illuminated volume, with changes influenced by the refractive index and thickness of the layer. This insight emphasizes the significance of both composition and thickness of transparent materials in influencing light propagation within the skin model. Such knowledge is fundamental for improving light-based therapies and diagnostics in Biomedical Optics.

Photoplethysmography (PPG) is a high-speed measurement technique that resolves fast physiological phenomena and offers promising applications in the medical field. In order to have a better understanding of the cardiovascular dynamics through the PPG signal, we propose a comprehensive multilayered and optical biophysical skin model from the wrist that is able to simulate some characteristic physiological properties and the complex cardiovascular dynamics. Thanks to this dynamic optical model, we are able to identify and disentangle the microvascular, arterial and venous contributions retrieved from the PPG signal signature.

Epithelial cancers, constituting the majority of human cancer cases, can be identified by alterations in the biochemical and structural morphological characteristics of the thin epithelial layer (ranging from 100μm to 500μm), serving as an initial indication of the disease. Many researchers have utilised spatially resolved fiber optic probes and fluorescence spectroscopy technique to detect subtle variations in the optical properties of the epithelium layer of tissue. This study explores the impact of different incidence and collection configurations on epithelium layer sensitivity for spatially resolved fluorescence using Monte Carlo simulation. It reveals that a fiber probe with illumination-collection at 45-degree beveled angle in parallel configuration provides maximum fluorescence from the epithelium layer. The efficacy of the 45-degree beveled angle fiber probe for measuring spatially resolved sensitivity has also been validated experimentally using two layer solid tissue-mimicking phantoms which demonstrates strong agreement with the results generated from Monte Carlo simulation.

3D laser nanoprinting based on multi-photon absorption (or multi-step absorption) has become an established commercially available and widespread technology. Here, we focus on recent progress concerning increasing print speed, improving the accessible spatial resolution beyond the diffraction limit, increasing the palette of available materials, and reducing instrument cost.

Biological discovery is a driving force of biomedical progress. With rapidly advancing technology to collect and analyze information from cells and tissues, we generate biomedical knowledge at rates never before attainable to science. Nevertheless, conversion of this knowledge to patient benefits remains a slow process. To accelerate the process of reaching solutions for healthcare, it would be important to complement this culture of discovery with a culture of problem-solving in healthcare. The talk focuses on recent progress with optical and optoacoustic technologies, as well as computational methods, which open new paths for solutions in biology and medicine. Particular attention is given on the use of these technologies for early detection and monitoring of disease evolution. The talk further shows new classes of imaging systems and sensors for assessing biochemical and pathophysiological parameters of systemic diseases, complement knowledge from –omic analytics and drive integrated solutions for improving healthcare.

In this paper we will discuss a noninvasive photonic sensing of presence of glucose in the blood stream. The sensing mechanism is based upon analyzing the temporal-spatial changes occurring in back or forward scattered photonic speckle field that is generated while coherent photons (coming from a laser illuminating source) are interacting with glucose molecules in the presence of externally applied alternating magnetic field. Due to the magneto-optic effect specific to glucose, high sensitivity and high specificity results were obtained both during in-vitro as well as in-vivo measurements. The results were further enhanced by artificial intelligence analysis that includes machine learning and deep neural networks. The in-vivo measurements were performed both in free space sensing (of glucose in blood stream in a finger) as well as by using a multi-mode fiber sensor (that was touching the skin of a finger) while applying the same sensing methodology.

Multiple Laser Speckle contrast Imaging (MESI) is a well established method that provides relative blood flow maps from the statistical analysis of the dynamic speckle patterns observed when a coherent source is used to illuminate a tissue that contains moving scatterers. Analysis of MESI data is done by pixelwise regression of the experimental images to a theoretical function of the contrast K as a function of the exposure time T. This approach is computer intensive and the duration required to obatin a single flow map is too long for "real-time" analysis of in vivo hemodynamics. We have evaluated as an alternative a method based on convolutional neural networks. This approach is model-free and delivers blod flow maps several ordres of magnitude faster than the classical pixelwise non linear regression. Here we have created two different datasets to train the neural networks. One is composed of simulated time integrated speckle while the other one is composed of experimental data acquired for microfluidic channesl with controlled geometries and flows. We will discuss the assets and limits of both approaches.

In this study, we addressed the pressing challenge of cancer treatment by focusing on tumor vasculature as a potential therapeutic target. We employed a combination of hyperspectral imaging (HSI) and laser speckle contrast imaging (LSCI) to non-invasively monitor the growth of 4T1 murine mammary carcinomas and their vasculature over a span of two weeks and the response to electroporation-based therapy. Following gene electrotransfer, we observed an immediate reduction in blood flow within tumor vessels due to induced vasoconstriction from the electrical pulses. Furthermore, tumor perfusion decreased and gradually recovered in the following days after therapy, while an untreated control tumor exhibited a substantial increase in blood flow. Our findings highlight the effectiveness of HSI and LSCI in monitoring vascular changes after electroporation-based therapy, offering valuable insights for improving cancer treatment strategies.

In spectral-domain optical coherence tomography (SDOCT), traditional spectrometers with a grating and line-scan camera yield nonlinear wavenumber responses, affecting OCT signal sensitivity and resolution. This necessitates post-processing for spectral interferogram remapping, but it's limited in short-wavelength ranges due to uneven pixel frequency spacing. To overcome these challenges, we introduce a cost-effective, simple linear-wavenumber spectrometer using a dual-prism and reflector setup, significantly enhancing spectral dispersion linearity, vital for ultra-high resolution SDOCT. Our method employs iterative calculations with global stochastic gradient descent for higher-order dispersion linearization. This results in a substantial increase in wavenumber linearity, from 99.9714% to 99.9998% for 80 nm at 850 nm wavelength, and 99.6828% to 99.9861% for 260 nm bandwidth. Our design eliminates resampling needs for up to 260 nm bandwidth, with nonlinearity-induced wavenumber mismatch under one pixel. This innovation marks a significant advancement in SDOCT spectrometer design, enhancing performance and resolution beyond traditional system limitations.

Over the past few decades, a multitude of optical imaging techniques have emerged. Among them, full-field optical coherence tomography (FF-OCT) has gained significant importance in various biomedical applications. Indeed, FF-OCT stands out as a noninvasive and label-free imaging method capable of generating high-resolution 3D microscopic images of light-scattering biological specimens. However, FF-OCT approach is limited for in-vivo imaging and images from FF-OCT lack the specificity required for accurate diagnosis. Hence, there is a need to have access to in-vivo imaging and to incorporate additional contrast modalities, such as elastography, into the FF-OCT technique. Indeed, the combination of FF-OCT with shear wave elastography enables the quantitative assessment of tissue stiffness at a resolution of a few micrometers. In this context, we present a novel FF-OCT approach that enables single-shot acquisitions, making it well-suited for both in-vivo imaging and transient shear wave elastography.

Elasticity of blood vessels make them contract or dilate in regulating the body temperature to changes in external temperature changes such as air-conditioning. However, aging makes them gradually lose elasticity, making it difficult for blood vessels to make adjustments. In this study, we propose the use of biospeckle Optical Coherence Tomography to visualize the dynamic changes within the skin. Five subjects in their 20’s and two subjects in their 30’s or older subjected to heating of the palmar forearm of their dominant hand by a USB hot pad (40°C) for five minutes. Biospeckle OCT contrasts calculated from OCT structural images obtained before and after heating were compared. Increased contrast corresponds to larger change within and a comparison between the subjects’ ages revealed a clear dependence with increasing age lesser the contrast. Currently we are conducting experiments to increase the reliability of the results.

Throughout the history of medicine, assessing stiffness through palpation has served as an indicator to gauge tissue health. Within our research team, we are advancing an innovative approach for full-field optical elastography, rooted in noise correlation analysis. This method leverages the relationship between the correlation function of a diffuse shear wave field and the time reversal of the shear wave field. By examining the correlation function, we then have access to an estimation of the shear wave speed, directly linked to tissue stiffness. Recent findings using this approach have shown great promise. However, in most cases, only the elasticity is quantified, despite the availability of additional information, such as viscosity, also present in the correlation function. In this paper, we introduce our initial outcomes in integrating noise correlation with artificial intelligence. More specifically, we employ a U-NET-based architecture to process noise correlation data.

Optical coherence elastography (OCE) provides mechanical contrast on the micro-scale and has shown promise in a number of clinical applications. In the majority of OCE methods, local homogeneity is inherently assumed in the mechanical models, which results in low accuracy in complex tissues. Here, we present a novel compression OCE method that exploits tissue heterogeneity to generate mechanical contrast in human breast tissue by mapping the full strain tensor. We used the strain tensor to map mechanical parameters such as Euler angle of principal compression. We also demonstrate a new form of quantitative OCE by mapping local Poisson’s ratio.

The engineering of artificial human tissue became a routing technique in molecular biology. DLP bioprinter is usually employed to print a 3D matrix incorporating cell type or short-living spheroids/organoids. Complex neuronal brain-like or innerved tissue models require high-precision fs laser-printing with nano and micrometre resolution. To engineer human models hi-PSC-derived cell lines are often used making the whole process elaborate and expensive. Therefore, we used the MEA non-distractable functionality 3D neuronal network of neural progenitor efficiency in differentiation into functionally active post-mitotic neurons and custom-built dual-mode fluorescence spectroscopy (FS) and optical coherence tomography (OCT) system for metabolism and morphology assessment of full-thickness skin equivalent (FSE) cultivated on the laser-printed 3D scaffolds. Both calcium imaging and FS-OCT systems can monitor the functionality, morphology, and metabolism in developing human brain-like and FSE models. Thus, 3D laser-printed scaffolds are feasible to engineer human tissue models where dual-mode FS/OCT and MEA systems capable of non-distractive monitor their development.

There is rising interest in how nanomaterials interact with plants. Therefore, techniques to monitor the response of plants to nanoparticles (NPs) are crucial. In this study, we proposed Biospeckle Optical Coherence Tomography (bOCT), a highly sensitive, real-time, non-invasive technique, to investigate the size effects of Zinc Oxide (ZnO) nano and microparticles, which have recently been used in agriculture, on the internal activity of lentil seeds. The bOCT results revealed that smaller ZnO NPs of <50 nm size had a toxic effect on the internal activity of lentil seed at both low and high doses while larger NPs (45µm) had significantly positive effects even with higher concentrations. The proposed method was able to detect the response of Lentil seed activities to different concentrations and sizes of ZnO NPs at an early stage just after 5 hours of exposure before the germination.

Elastography is an emerging imaging technique that has already proved its clinical usefulness with MRI and ultrasound methods. In the last years, elastography methods have also been adapted to optical setups, expending its applications to new possibilities. In this presentation, we propose a generalization of the NCi method to partially coherent mechanical wave field. The method is first validated finite difference simulations and a proof of concept using optical, ultrasound and MRI commercial systems is presented.

Ultrasound waveguiding of light is a recently introduced technique aiding light transport in scattering media, effectively reducing scattering strength. This technique locally, transiently, reversibly modifies the refractive index of the medium, recollecting and guiding some of the scattered photons to increase light intensity in depth. Here we use transient transversal ultrasound light waveguiding to increase the strength of the signal received from fluorescent target hidden behind a 3 mm thick scattering phantom. We use a common linear array transducer and transmission geometry and show waveguiding-induced increase of fluorescence, excited by a pulsed 532 nm light, typical for photoacoustic imaging setting.

Detection of inclusions in biological tissue by optical imaging is often challenging, since the image becomes blurred due to strong scattering in the turbid tissue medium. This scattering-blur increases with the distance between the object and the focal plane of the imaging system, which can be utilised to determine the position of the object. Here, we present the proof of concept of a deep-learning based method of determining the location of such an object inside a turbid medium, from a stack of blurred epi-illuminated microscopy images captured at varying focal planes. A U-Net regression model was trained and tested with such 3D image datasets under simplified conditions. It gives a 2D matrix of depth values as output. The predicted results from the trained model show good agreement with the ground truth for testing data.

In this work, we address the challenge of noise dominance in synthesized photoacoustic (PA) fundus retinal images, which is a constraint for accurate diagnosis. By using the NIRFAST and K-wave MATLAB toolboxes, we simulate the PA images of the chosen fundus dataset i.e., both normal and abnormal (glaucoma-affected) images. During reconstruction, finer details such as tissue information are lost, beyond a certain depth, due to the noise dominance. To alleviate this, we propose to apply a dictionary learning-based denoising technique, known as the K-Singular Value Decomposition (K-SVD) algorithm. Results show that KSVD denoising is an effective method for abnormal and normal retinal PA images which effectively removes the noise and aids in better image reconstruction.

Skin cancer, a prevalent global health concern, necessitates accurate diagnostic tools. Fourier Domain Optical Coherence Tomography (FD-OCT) provides non-invasive, high-resolution imaging for early skin cancer detection. Our study emphasizes the modeling of FD-OCT, capturing subtle tissue variations and enabling precise differentiation between benign and malignant skin lesions based on features like epidermal thickness and dermal-epidermal junction integrity. The non-invasive nature of proposed FD-OCT's allows real-time assessment, reducing the need for biopsies and improving patient comfort. Our findings highlighted the FD-OCT's potential to enhance skin cancer diagnosis, facilitate timely treatment strategies and improving patient outcomes.

Photodynamic therapy is an effective modality for treating advanced melanoma. However, melanoma's inherent resistance to laser radiation hinders its widespread clinical application. The near-infrared laser radiation range of 1264-1270 nm offers unique properties: firstly, its ability to penetrate melanin-producing cells, and secondly, its capability to generate singlet oxygen without xenobiotics. We assess the impact of continuous wave 1265 nm laser radiation on an antioxidant defense system in melanoma B16-F10 and normal CHO-K1 cells. We observe a time-dependent increase in superoxide dismutase and glutathione-S-transferase activities, fluctuations in reduced glutathione levels, as well as a simultaneous increase in melanoma cell proliferation and cell death. We hypothesize that the differential activation of cellular antioxidant defense mechanisms contributes to melanoma cells' resilience to laser radiation.