Optical imaging in medicine: I. Experimental techniques

Birefringence mapping of biological tissues based on polarization sensitive non-interferometric quantitative phase imaging technique

OBJECTIVE

Oral cancer is a leading cause of mortality globally, particularly affecting developing regions where oral hygiene is often overlooked. The optical properties of tissues are vital for diagnostics, with polarization imaging emerging as a label-free, contrast-enhancing technique widely employed in medical and scientific research over past few decades.

MATERIALS AND METHODS

We present a novel polarization sensitive quantitative phase imaging of biological tissues by incorporating the conventional polarization microscope and transport of intensity equation-based phase retrieval algorithm. This integration provides access to the birefringence mapping of biological tissues. The inherent optical anisotropy in biological tissues induces the polarization dependent refractive index variations which can provide the detailed insights into the birefringence characteristics of their extracellular constituents. Experimental investigations were conducted on both normal and cancerous oral tissue samples by recording a set of three polarization intensity images for each case with a step size of 2 μm.

RESULTS

A noteworthy increment in birefringence quantification was observed in cancerous as compared to the normal tissues, attributed to the proliferation of abnormal cells during cancer progression. The mean birefringence values were calculated for both normal and cancerous tissues, revealing a significant increase in birefringence of cancerous tissues (2.1 ± 0.2) × 10-2 compared to normal tissues (0.8 ± 0.2) × 10-2. Data were collected from 8 patients in each group under identical experimental conditions.

CONCLUSION

This polarization sensitive non-interferometric optical approach demonstrated effective discrimination between cancerous and normal tissues, with various parameters indicating elevated values in cancerous tissues.

Super-resolution reconstruction of underwater polarized images with a fused attention mechanism

The polarization imaging technique leverages the disparity between target and background polarization information to mitigate the impact of backward scattered light, thereby enhancing image quality. However, the imaging model of this method exhibits limitations in extracting inter-image features, resulting in less-than-optimal outcomes in turbid underwater environments. In recent years, machine learning methodologies, particularly neural networks, have gained traction. These networks, renowned for their superior fitting capabilities, can effectively extract information from multiple images. The incorporation of an attention mechanism significantly augments the capacity of neural networks to extract inter-image correlation attributes, thereby mitigating the constraints of polarization imaging methods to a certain degree. To enhance the efficacy of polarization imaging in complex underwater environments, this paper introduces a super-resolution network with an integrated attention mechanism, termed as SRGAN-DP. This network is a fusion of an enhanced SRGAN network and the high-performance deep pyramidal split attention (DPSA) module, also proposed in this paper. SRGAN-DP is employed to perform high-resolution reconstruction of the underwater polarimetric image dataset, constructed specifically for this study. A comparative analysis with existing algorithms demonstrates that our proposed algorithm not only produces superior images but also exhibits robust performance in real-world environments.

Gold nanoparticle-mediated photothermal therapy guidance with multi-wavelength photomagnetic imaging

Difficulty in heating tumors with high spatial selectivity while protecting surrounding healthy tissues from thermal harm is a challenge for cancer photothermal treatment (PTT). To mitigate this problem, PTT mediated by photothermal agents (PTAs) has been established as a potential therapeutic technique to boost selectivity and reduce damage to surrounding healthy tissues. Various gold nanoparticles (AuNP) have been effectively utilized as PTAs, mainly using strategies to target cancerous tissue and increase selective thermal damage. Meanwhile, imaging can be used in tandem to monitor the AuNP distribution and guide the PTT. Mainly, the parameters impacting the induced temperature can be determined using simulation tools before treatment for effective PTT. However, accurate simulations can only be performed if the amount of AuNPs accumulated in the tumor is known. This study introduces Photo-Magnetic Imaging (PMI), which can appropriately recover the AuNP concentration to guide the PTT. Using multi-wavelength measurements, PMI can provide AuNP concentration based on their distinct absorption spectra. Tissue-simulating phantom studies are conducted to demonstrate the potential of PMI in recovering AuNP concentration for PTT planning. The recovered AuNP concentration is used to model the temperature increase accurately in a small inclusion representing tumor using a multiphysics solver that takes into account the light propagation and heat diffusion in turbid media.

Custom Hyperspectral Imaging System Reveals Unique Spectral Signatures of Heart, Kidney, and Liver Tissues

The rapid advancement of diagnostic and therapeutic optical techniques for oncology demands a good understanding of the optical properties of biological tissues. This study explores the capabilities of hyperspectral (HS) cameras as a non-invasive and non-contact optical imaging system to distinguish and highlight spectral differences inbiological soft tissuesof three structures (kidney, heart, and liver) for use inendoscopic interventionoropen surgery. The study presents an optical system consisting of two individual setups, the transmission setup, and the reflection setup, both incorporating anHS camerawith apolychromatic light sourcewithin the range of 380 to 1050 nm to measure tissue's light transmission (Tr) and diffuse light reflectance (Rd), respectively. The optical system was calibrated with a customizedliquid optical phantom, then 30 samples from various organs were investigated fortissue characterizationby measuring both Tr and Rd at the visible and near infrared (VIS-NIR) band. We exploited the ANOVA test, subsequently by a Tukey's test on the created three independent clusters (kidney vs. heart: group I / kidney vs. liver: group II / heart vs. liver: group III) to identify the optimum wavelength for each tissue regarding their spectroscopic optical properties in the VIS-NIR spectrum. The optimum spectral span for the determined light Tr of the three groups was 640 ∼ 680 nm, and the ideal range was 720 ∼ 760 nm for the measured light Rd for mutual group I and group II. However, the group III range was different at a range of 520 ∼ 560 nm. Therefore, the investigation provides vital information concerning theoptimum spectral scalefor the computed light Tr and Rd of the investigatedbiological tissues(kidney, liver, and heart) to be employed in diagnostic andtherapeutic medical applications.

From Pixels to Pathology: Employing Computer Vision to Decode Chest Diseases in Medical Images

Radiology has been a pioneer in the healthcare industry's digital transformation, incorporating digital imaging systems like picture archiving and communication system (PACS) and teleradiology over the past thirty years. This shift has reshaped radiology services, positioning the field at a crucial junction for potential evolution into an integrated diagnostic service through artificial intelligence and machine learning. These technologies offer advanced tools for radiology's transformation. The radiology community has advanced computer-aided diagnosis (CAD) tools using machine learning techniques, notably deep learning convolutional neural networks (CNNs), for medical image pattern recognition. However, the integration of CAD tools into clinical practice has been hindered by challenges in workflow integration, unclear business models, and limited clinical benefits, despite development dating back to the 1990s. This comprehensive review focuses on detecting chest-related diseases through techniques like chest X-rays (CXRs), magnetic resonance imaging (MRI), nuclear medicine, and computed tomography (CT) scans. It examines the utilization of computer-aided programs by researchers for disease detection, addressing key areas: the role of computer-aided programs in disease detection advancement, recent developments in MRI, CXR, radioactive tracers, and CT scans for chest disease identification, research gaps for more effective development, and the incorporation of machine learning programs into diagnostic tools.

Structure functions for optical waves in a complex medium of turbulent biological tissues

Although optical wave propagation is investigated based on the absorption and scattering in biological tissues, the turbulence effect can also not be overlooked. Here, the closed-form expressions of the wave structure function (WSF) and phase structure function (PSF) of plane and spherical waves propagating in biological tissue are obtained to help with future research on imaging, intensity, and coherency in turbulent biological tissues. This paper presents the effect of turbulent biological tissue on optical wave propagation to give a perception of the performance of biomedical systems that use optical technologies. The behavior of optical waves in different types of turbulent biological tissues such as a liver parenchyma (mouse), an intestinal epithelium (mouse), a deep dermis (mouse), and an upper dermis (human) are investigated and compared. It is observed that turbulence becomes more effective with an increase in the characteristic length of heterogeneity, propagation distance, and the strength of the refractive index fluctuations. However, an increase in the fractal dimension, wavelength, and small length scale factor has a smaller turbulence effect on the propagating optical wave. We envision that our results may be used to interpret the performance of optical medical systems operating in turbulent biological tissues.

Nanotheranostic Strategies for Cancer Immunotherapy

Despite advancements in cancer immunotherapy, heterogeneity in tumor response impose barriers to successful treatments and accurate prognosis. Effective therapy and early outcome detection are critical as toxicity profiles following immunotherapies can severely affect patients' quality of life. Existing imaging techniques, including positron emission tomography, computed tomography, magnetic resonance imaging, or multiplexed imaging, are often used in clinics yet suffer from limitations in the early assessment of immune response. Conventional strategies to validate immune response mainly rely on the Response Evaluation Criteria in Solid Tumors (RECIST) and the modified iRECIST for immuno-oncology drug trials. However, accurate monitoring of immunotherapy efficacy is challenging since the response does not always follow conventional RECIST criteria due to delayed and variable kinetics in immunotherapy responses. Engineered nanomaterials for immunotherapy applications have significantly contributed to overcoming these challenges by improving drug delivery and dynamic imaging techniques. This review summarizes challenges in recent immune-modulation approaches and traditional imaging tools, followed by emerging developments in three-in-one nanoimmunotheranostic systems co-opting nanotechnology, immunotherapy, and imaging. In addition, a comprehensive overview of imaging modalities in recent cancer immunotherapy research and a brief outlook on how nanotheranostic platforms can potentially advance to clinical translations for the field of immuno-oncology is presented.

Framework for denoising Monte Carlo photon transport simulations using deep learning

SIGNIFICANCE

The Monte Carlo (MC) method is widely used as the gold-standard for modeling light propagation inside turbid media, such as human tissues, but combating its inherent stochastic noise requires one to simulate a large number photons, resulting in high computational burdens.

AIM

We aim to develop an effective image denoising technique using deep learning (DL) to dramatically improve the low-photon MC simulation result quality, equivalently bringing further acceleration to the MC method.

APPROACH

We developed a cascade-network combining DnCNN with UNet, while extending a range of established image denoising neural-network architectures, including DnCNN, UNet, DRUNet, and deep residual-learning for denoising MC renderings (ResMCNet), in handling three-dimensional MC data and compared their performances against model-based denoising algorithms. We also developed a simple yet effective approach to creating synthetic datasets that can be used to train DL-based MC denoisers.

RESULTS

Overall, DL-based image denoising algorithms exhibit significantly higher image quality improvements over traditional model-based denoising algorithms. Among the tested DL denoisers, our cascade network yields a 14 to 19 dB improvement in signal-to-noise ratio, which is equivalent to simulating 25  ×   to 78  ×   more photons. Other DL-based methods yielded similar results, with our method performing noticeably better with low-photon inputs and ResMCNet along with DRUNet performing better with high-photon inputs. Our cascade network achieved the highest quality when denoising complex domains, including brain and mouse atlases.

CONCLUSIONS

Incorporating state-of-the-art DL denoising techniques can equivalently reduce the computation time of MC simulations by one to two orders of magnitude. Our open-source MC denoising codes and data can be freely accessed at http://mcx.space/.

Automatic Segmentation and Cardiac Mechanics Analysis of Evolving Zebrafish Using Deep Learning

Background: In the study of early cardiac development, it is essential to acquire accurate volume changes of the heart chambers. Although advanced imaging techniques, such as light-sheet fluorescent microscopy (LSFM), provide an accurate procedure for analyzing the heart structure, rapid, and robust segmentation is required to reduce laborious time and accurately quantify developmental cardiac mechanics. Methods: The traditional biomedical analysis involving segmentation of the intracardiac volume occurs manually, presenting bottlenecks due to enormous data volume at high axial resolution. Our advanced deep-learning techniques provide a robust method to segment the volume within a few minutes. Our U-net-based segmentation adopted manually segmented intracardiac volume changes as training data and automatically produced the other LSFM zebrafish cardiac motion images. Results: Three cardiac cycles from 2 to 5 days postfertilization (dpf) were successfully segmented by our U-net-based network providing volume changes over time. In addition to understanding each of the two chambers' cardiac function, the ventricle and atrium were separated by 3D erode morphology methods. Therefore, cardiac mechanical properties were measured rapidly and demonstrated incremental volume changes of both chambers separately. Interestingly, stroke volume (SV) remains similar in the atrium while that of the ventricle increases SV gradually. Conclusion: Our U-net-based segmentation provides a delicate method to segment the intricate inner volume of the zebrafish heart during development, thus providing an accurate, robust, and efficient algorithm to accelerate cardiac research by bypassing the labor-intensive task as well as improving the consistency in the results.

Improving vascular imaging with co-planar mutually guided photoacoustic and diffuse optical tomography: a simulation study

Diffuse optical tomography (DOT) and photoacoustic tomography (PAT) are functional imaging modalities that provide absorption coefficient maps of the tissue. Spatial resolution of DOT is relatively low due to light scattering characteristics of the tissue. On the other hand, although PAT can resolve regions of different absorptions with a high spatial resolution, measuring the absolute value of optical absorptions using PAT is challenging due to unknown light fluence distribution in the tissue. Development of image guidance techniques using a priori information of imaging target structure has been shown to increase the accuracy of DOT. PAT is one such method that can be used as a complementary modality to serve as a guide for DOT image reconstruction. On the other hand, estimated fluence map provided by DOT can be used to quantitatively correct PAT images. In this study we introduce a mutually-guided imaging system for fast and simultaneous optical and photoacoustic measurements of tissue absorption map, where DOT is guided by the PAT image and vice versa. Using the obtained absorption map of the tissue, we then estimate the tissue scattering map. We conducted this study using a series of simulations on digital phantoms and demonstrated the effectiveness of the proposed method.

Waveguiding and focusing in a bio-medium with an optofluidic cell chain

Long-distance waveguiding and submicron focusing of light in a bio-medium are crucial for biomedical sensing and imaging. Disordered bio-mediums usually exhibit high scattering and absorption, which limits effective waveguiding and focusing. Here, we demonstrate an optofluidic cell chain, assembled via an optical trapping force from an optical fiber probe, to achieve long-distance waveguiding and submicron light focusing in a disordered bio-medium. By applying a trapping light at 980 nm to generate an optical force, stable binding of E. faecalis cells was achieved in a fluid to assemble cell chains of different lengths. The length could reach up to 360 µm and the incident light (at 675, 532 and 473 nm) could be focused into a beam with a waist radius of 400 nm. As a potential practical application, backscattered signals from human red blood cells were detected using the cell chains, which is expected to benefit biomedical sensing and single cell analysis. STATEMENT OF SIGNIFICANCE: With the assistance of optofluidic techniques, we assembled an E. faecalis cell chain with a length up to 360 µm to achieve long-distance waveguiding and submicron focusing at a propagation loss of 0.03 dB/µm in the bio-medium. Visible lights were launched into the cell chain and the incident lights can converge into a beam with a waist radius of 400 nm. The cell chain was further used to detect the backscattering signals from human red blood cells (RBCs), and the results indicate that the cell chain can be applied as a fully biocompatible extension of the probe for the real-time detection of RBCs in healthy and pathological states.

Fluorescence Imaging as a Tool in Preclinical Evaluation of Polymer-Based Nano-DDS Systems Intended for Cancer Treatment

Targeted drug delivery using nano-sized carrier systems with targeting functions to malignant and inflammatory tissue and tailored controlled drug release inside targeted tissues or cells has been and is still intensively studied. A detailed understanding of the correlation between the pharmacokinetic properties and structure of the nano-sized carrier is crucial for the successful transition of targeted drug delivery nanomedicines into clinical practice. In preclinical research in particular, fluorescence imaging has become one of the most commonly used powerful imaging tools. Increasing numbers of suitable fluorescent dyes that are excitable in the visible to near-infrared (NIR) wavelengths of the spectrum and the non-invasive nature of the method have significantly expanded the applicability of fluorescence imaging. This chapter summarizes non-invasive fluorescence-based imaging methods and discusses their potential advantages and limitations in the field of drug delivery, especially in anticancer therapy. This chapter focuses on fluorescent imaging from the cellular level up to the highly sophisticated three-dimensional imaging modality at a systemic level. Moreover, we describe the possibility for simultaneous treatment and imaging using fluorescence theranostics and the combination of different imaging techniques, e.g., fluorescence imaging with computed tomography.

Multivariate discrimination of heat shock proteins using a fiber optic Raman setup for in situ analysis of human perilymph

Raman spectroscopy has proven to be an effective tool for molecular analysis in different applications. In clinical diagnostics, its application has enabled nondestructive investigation of biological tissues and liquids. The human perilymph, for example, is an inner ear liquid, essential for the hearing sensation. The composition of this liquid is correlated with pathophysiological parameters and was analyzed by extraction and mass spectrometry so far. In this work, we present a fiber optic probe setup for the Raman spectroscopic sampling of inner ear proteins in solution. Multivariate data analysis is applied for the discrimination of individual proteins (heat shock proteins) linked to a specific type of hearing impairment. This proof-of-principle is a first step toward a system for sensitive and continuous in vivo perilymph investigation in the future.

Amphiphilic Nanoaggregates with Bimodal MRI and Optical Properties Exhibiting Magnetic Field Dependent Switching from Positive to Negative Contrast Enhancement

Mixed micelles based on amphiphilic gadolinium(III)-DOTA and europium(III)-DTPA complexes were synthesized and evaluated for their paramagnetic and optical properties as potential bimodal contrast agents. Amphiphilic folate molecule for targeting the folate receptor protein, which is commonly expressed on the surface of many human cancer cells, was used in the self-assembly process in order to create nanoaggregates with targeting properties. Both targeted and nontargeted nanoaggregates formed monodisperse micelles having distribution maxima of 10 nm. The micelles show characteristic europium(III) emission with quantum yields of 2% and 1.1% for the nontargeted and targeted micelles, respectively. Fluorescence microscopy using excitation at 405 nm and emission at 575-675 nm was employed to visualize the nanoaggregates in cultured HeLa cells. The uptake of folate-targeted and nontargeted micelles is already visible after 5 h of incubation and was characterized with the europium(III) emission, which is clearly observable in the cytoplasm of the cells. The very fast longitudinal relaxivity r₁ of ca. 26 s^-1 mM^-1 per gadolinium(III) ion was observed for both micelles at 60 MHz and 310 K. Upon increasing the magnetic field to 300 MHz, the nanoaggregates exhibited a large switching to transversal relaxivity with r₂ value of ca. 52 s^-1 mM^-1 at 310 K. Theoretical fitting of the ¹H NMRD profiles indicate that the efficient T₁ and T₂ relaxations are sustained by the favorable magnetic and electron-configuration properties of the gadolinium(III) ion, rotational correlation time, and coordinated water molecule. These nanoaggregates could have versatile application as a positive contrast agent at the currently used magnetic imaging field strengths and a negative contrast agent in higher field applications, while at the same time offering the possibility for the loading of hydrophobic therapeutics or targeting molecules.

Unbiased estimation of an optical loss at the ultimate quantum limit with twin-beams

Loss measurements are at the base of spectroscopy and imaging, thus permeating all the branches of science, from chemistry and biology to physics and material science. However, quantum mechanics laws set the ultimate limit to the sensitivity, constrained by the probe mean energy. This can be the main source of uncertainty, for example when dealing with delicate systems such as biological samples or photosensitive chemicals. It turns out that ordinary (classical) probe beams, namely with Poissonian photon number distribution, are fundamentally inadequate to measure small losses with the highest sensitivity. It is known that quantum-correlated pair of beams, named “twin-beam state”, allows surpassing this classical limit. Here we demonstrate they can reach the ultimate sensitivity for all energy regimes (even less than one photon per mode) with the simplest measurement strategy. One beam of the pair addresses the sample, while the second one is used as a reference to compensate both for classical drifts and for fluctuation at the most fundamental quantum level. This capability of selfcompensating for unavoidable instability of the sources and detectors allows also to strongly reduce the bias in practical measurement. Moreover, we report the best sensitivity per photon ever achieved in loss estimation experiments.

Amphiphilic complexes of Ho(iii), Dy(iii), Tb(iii) and Eu(iii) for optical and high field magnetic resonance imaging

Amphiphilic lanthanide(iii) complexes self-assemble into monodisperse micelles with favourable properties for optical and high field magnetic resonance imaging.

Ex vivo validation of photo-magnetic imaging

We recently introduced a new high-resolution diffuse optical imaging technique termed photo-magnetic imaging (PMI), which utilizes magnetic resonance thermometry (MRT) to monitor the 3D temperature distribution induced in a medium illuminated with a near-infrared light. The spatiotemporal temperature distribution due to light absorption can be accurately estimated using a combined photon propagation and heat diffusion model. High-resolution optical absorption images are then obtained by iteratively minimizing the error between the measured and modeled temperature distributions. We have previously demonstrated the feasibility of PMI with experimental studies using tissue simulating agarose phantoms. In this Letter, we present the preliminary ex vivo PMI results obtained with a chicken breast sample. Similarly to the results obtained on phantoms, the reconstructed images reveal that PMI can quantitatively resolve an inclusion with a 3 mm diameter embedded deep in a biological tissue sample with only 10% error. These encouraging results demonstrate the high performance of PMI in ex vivo biological tissue and its potential for in vivo imaging.

Optical properties of the human round window membrane

Optical techniques are effective tools for diagnostic applications in medicine and are particularly attractive for the noninvasive analysis of biological tissues and fluids in vivo. Noninvasive examinations of substances via a fiber optic probe need to consider the optical properties of biological tissues obstructing the optical path. This applies to the analysis of the human perilymph, which is located behind the round window membrane. The composition of this inner ear liquid is directly correlated to inner ear hearing loss. In this work, experimental methods for studying the optical properties of the human round window membrane ex vivo are presented. For the first time, a comprehensive investigation of this tissue is performed, including optical transmission, forward scattering, and Raman scattering. The results obtained suggest the application of visible wavelengths (>400  nm) for investigating the perilymph behind the round window membrane in future.

Primal-dual approach to optical tomography with discretized path integral with efficient formulations

We propose an efficient optical tomography with discretized path integral. We first introduce the primal-dual approach to solve the inverse problem formulated as a constraint optimization problem. Next, we develop efficient formulations for computing Jacobian and Hessian of the cost function of the constraint nonlinear optimization problem. Numerical experiments show that the proposed formulation is faster ([Formula: see text]) than the previous work with the log-barrier interior point method ([Formula: see text]) for the Shepp-Logan phantom with a grid size of [Formula: see text], while keeping the quality of the estimation results (root-mean-square error increasing by up to 12%).

Probe for evaluating the absorbing and transport scattering properties of turbid fluids using low-cost time-of-flight technology

A probe is described that when immersed into a highly scattering fluid provides a measurement of its scattering and absorbing properties at a single optical wavelength. It uses recently available low-cost proximity sensor modules to estimate the mean flight times of photons diffusely transmitted between near-infrared sources and detectors at two different separations. The probe has been designed with a specific application for enabling the rapid and efficient production of fluids, which mimic the optical properties of biological tissues. The potential of the device is demonstrated using precalibrated solutions of intralipid, an intravenous nutrient, and absorbing dye. It is shown that a combination of time-of-flight measurements at two source–detector separations can uniquely specify the absorption coefficient and the transport scattering coefficient.

Combined diffuse optical tomography and photoacoustic tomography for enhanced functional imaging of small animals: a methodological study on phantoms

Hybrid imaging methods combining diffuse optical tomography (DOT) and other anatomical or nonoptical functional modalities have been widely investigated to improve imaging performance degraded by the strong optical scattering of biological tissues, through constraining the reconstruction process by prior structures. However, these modalities with different contrast mechanisms may be ineffective in revealing early-staged lesions with high optical contrast but no morphological changes. Photoacoustic tomography (PAT) is particularly useful for visualizing light-absorbing structures embedded in soft tissues with high spatial resolution. Although it is still challenging for PAT to quantitatively disclose the absorption distribution, the modality does provide reliable and specific a priori information differentiating light-absorbing structures of soft tissues and might be more appropriate to guide DOT in lesion diagnosis, as compared with other anatomical or nonoptical functional modalities. In this study, a PAT-guided DOT approach is introduced with both soft- and hard-prior regularizations. The methodology is experimentally validated on small-animal-sized phantoms using a computed-tomography-analogous (CT-analogous) PAT/DOT dual-modality system, focusing on future whole-body applications. The results show that the proposed scheme is capable of effectively improving the quantitative accuracy and spatial resolution of DOT reconstruction.

An accelerated photo-magnetic imaging reconstruction algorithm based on an analytical forward solution and a fast Jacobian assembly method

We previously introduced photo-magnetic imaging (PMI), an imaging technique that illuminates the medium under investigation with near-infrared light and measures the induced temperature increase using magnetic resonance thermometry (MRT). Using a multiphysics solver combining photon migration and heat diffusion, PMI models the spatiotemporal distribution of temperature variation and recovers high resolution optical absorption images using these temperature maps. In this paper, we present a new fast non-iterative reconstruction algorithm for PMI. This new algorithm uses analytic methods during the resolution of the forward problem and the assembly of the sensitivity matrix. We validate our new analytic-based algorithm with the first generation finite element method (FEM) based reconstruction algorithm previously developed by our team. The validation is performed using, first synthetic data and afterwards, real MRT measured temperature maps. Our new method accelerates the reconstruction process 30-fold when compared to a single iteration of the FEM-based algorithm.

Real-time photo-magnetic imaging

We previously introduced a new high resolution diffuse optical imaging modality termed, photo-magnetic imaging (PMI). PMI irradiates the object under investigation with near-infrared light and monitors the variations of temperature using magnetic resonance thermometry (MRT). In this paper, we present a real-time PMI image reconstruction algorithm that uses analytic methods to solve the forward problem and assemble the Jacobian matrix much faster. The new algorithm is validated using real MRT measured temperature maps. In fact, it accelerates the reconstruction process by more than 250 times compared to a single iteration of the FEM-based algorithm, which opens the possibility for the real-time PMI.

Fluorescence optical imaging in anticancer drug delivery

In the past several decades, nanosized drug delivery systems with various targeting functions and controlled drug release capabilities inside targeted tissues or cells have been intensively studied. Understanding their pharmacokinetic properties is crucial for the successful transition of this research into clinical practice. Among others, fluorescence imaging has become one of the most commonly used imaging tools in pre-clinical research. The development of increasing numbers of suitable fluorescent dyes excitable in the visible to near-infrared wavelengths of the spectrum has significantly expanded the applicability of fluorescence imaging. This paper focuses on the potential applications and limitations of non-invasive imaging techniques in the field of drug delivery, especially in anticancer therapy. Fluorescent imaging at both the cellular and systemic levels is discussed in detail. Additionally, we explore the possibility for simultaneous treatment and imaging using theranostics and combinations of different imaging techniques, e.g., fluorescence imaging with computed tomography.

Magnetofluorescent micelles incorporating Dy(III)-DOTA as potential bimodal agents for optical and high field magnetic resonance imaging

Dysprosium(iii) was coordinated to four 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) bisamide derivatives functionalized with amphiphilic p-dodecylaniline and p-tetradecylaniline in a differing cis- and trans-orientation. The complexes were assembled into mono-disperse micelles having size distribution maxima ranging from 10 to 15 nm and the magnetic and optical properties of the micelles were examined in detail. The micelles show characteristic Dy(iii) emission with quantum yields reaching 0.8%. The transverse relaxivity r2 per Dy(iii) ion at 500 MHz and 310 K reaches maximum values of ca. 20 s(-1) mM(-1) which is a large increase when compared to a value of 0.8 s(-1) mM(-1) observed for Dy(III)-DTPA. The micelles were stable in water when incubated at 37 °C for 1 week and showed no relaxivity decrease when measured in the presence of 4% (w/v) human serum albumin. The efficient T2 relaxation, especially at strong magnetic fields, is sustained by the high magnetic moment of the dysprosium(iii) ion, the coordination of water molecules and long rotational correlation times.

Experimental validation of a high-resolution diffuse optical imaging modality: photomagnetic imaging

We present experimental results that validate our imaging technique termed photomagnetic imaging (PMI). PMI illuminates the medium under investigation with a near-infrared light and measures the induced temperature increase using magnetic resonance imaging. A multiphysics solver combining light and heat propagation is used to model spatiotemporal distribution of temperature increase. Furthermore, a dedicated PMI reconstruction algorithm has been developed to reveal high-resolution optical absorption maps from temperature measurements. Being able to perform measurements at any point within the medium, PMI overcomes the limitations of conventional diffuse optical imaging. We present experimental results obtained on agarose phantoms mimicking biological tissue with inclusions having either different sizes or absorption contrasts, located at various depths. The reconstructed images show that PMI can successfully resolve these inclusions with high resolution and recover their absorption coefficient with high-quantitative accuracy. Even a 1-mm inclusion located 6-mm deep is recovered successfully and its absorption coefficient is underestimated by only 32%. The improved PMI system presented here successfully operates under the maximum skin exposure limits defined by the American National Standards Institute, which opens up the exciting possibility of its future clinical use for diagnostic purposes.

Quantitative multi-spectral oxygen saturation measurements independent of tissue optical properties

Imaging of tissue oxygenation is important in several applications associated with patient care. Optical sensing is commonly applied for assessing oxygen saturation but is often restricted to local measurements or else it requires spectral and spatial information at the expense of time. Many methods proposed so far require assumptions on the properties of measured tissue. In this study we investigated a computational method that uses only multispectral information and quantitatively computes tissue oxygen saturation independently of tissue optical properties. The method is based on linear transformations of measurements in three isosbestic points. We investigated the ideal isosbestic point combination out of six isosbestic points available for measurement in the visible and near-infrared region that enable accurate oxygen saturation computation. We demonstrate this method on controlled tissue mimicking phantoms having different optical properties and validated the measurements using a gas analyzer. A mean error of 2.9 ± 2.8% O2 Sat was achieved. Finally, we performed pilot studies in tissues in-vivo by measuring dynamic changes in fingers subjected to vascular occlusion, the vasculature of mouse ears and exposed mouse organs.

A fast SPAD-based small animal imager for early-photon diffuse optical tomography

Photon scatter is the dominant light transport process in biological tissue and is well understood to degrade imaging performance in near-infrared diffuse optical tomography. Measurement of photons arriving at early times following a short laser pulse is considered to be an effective method to improve this limitation, i.e. by systematically selecting photons that have experienced fewer scattering events. Previously, we tested the performance of single photon avalanche photodiode (SPAD) in measurement of early transmitted photons through diffusive media and showed that it outperformed photo-multiplier tube (PMT) systems in similar configurations, principally due to its faster temporal response. In this paper, we extended this work and developed a fast SPAD-based time-resolved diffuse optical tomography system. As a first validation of the instrument, we scanned an optical phantom with multiple absorbing inclusions and measured full time-resolved data at 3240 scan points per axial slice. We performed image reconstruction with very early-arriving photon data and showed significant improvements compared to time-integrated data. Extension of this work to mice in vivo and measurement of time-resolved fluorescence data is the subject of ongoing research.

Optical tomography with discretized path integral

We present a framework for optical tomography based on a path integral. Instead of directly solving the radiative transport equations, which have been widely used in optical tomography, we use a path integral that has been developed for rendering participating media based on the volume rendering equation in computer graphics. For a discretized two-dimensional layered grid, we develop an algorithm to estimate the extinction coefficients of each voxel with an interior point method. Numerical simulation results are shown to demonstrate that the proposed method works well.

Improvement of the chemical content prediction of a model powder system by reducing multiple scattering using polarized light spectroscopy

Near-infrared spectroscopy (NIRS) is a powerful non-destructive analytical method used to analyze major compounds in bulk materials and products and requiring no sample preparation. It is widely used in routine analysis and also in line in industries, in vivo with biomedical applications, or in field for agricultural and environmental applications. However, highly scattering samples subvert Beer-Lambert law's linear relationship between spectral absorbance and the concentration. Instead of spectral pre-processing, which is commonly used by NIR spectroscopists to mitigate the scattering effect, we put forward an optical method, i.e., coupling polarized light with NIR spectrometry, to free spectra from scattering effect. This should allow us to retrieve linear and steady conditions for spectral analysis. When tested in visible-NIR (Vis-NIR) range (400-800 nm) on model media, mixtures of scattering and absorbing particles, the setup provided significant improvements in absorber concentration estimation precision as well as in the quality and robustness of the calibration model.

Monte Carlo simulation of in vivo Raman spectral measurements of human skin with a multi-layered tissue optical model

Raman photon generation inside human skin and escaping to skin surface were modeled in an eight-layered skin optical model. Intrinsic Raman spectra of different skin layers were determined by microscopy measurements of excised skin tissue sections. Monte Carlo simulation was used to study the excitation light distribution and intrinsic Raman signal distortion caused by tissue reabsorption and scattering during in vivo measurements. The simulation results demonstrated how different skin layers contributed to the observed in vivo Raman spectrum. Using the strongest Raman peak at 1445 cm(-1) as an example, the simulation suggested that the integrated contributions of the stratum corneum layer is 1.3%, the epidermis layer 28%, the dermis layer 70%, and the subcutaneous fat layer 1.1%. Reasonably good matching between the calculated spectrum and the measured in vivo Raman spectra was achieved, thus demonstrated great utility of our modeling method and approaches for help understanding the clinical measurements.

High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System

We have developed a graphics processor unit (GPU-) based high-speed fully 3D system for diffuse optical tomography (DOT). The reduction in execution time of 3D DOT algorithm, a severely ill-posed problem, is made possible through the use of (1) an algorithmic improvement that uses Broyden approach for updating the Jacobian matrix and thereby updating the parameter matrix and (2) the multinode multithreaded GPU and CUDA (Compute Unified Device Architecture) software architecture. Two different GPU implementations of DOT programs are developed in this study: (1) conventional C language program augmented by GPU CUDA and CULA routines (C GPU), (2) MATLAB program supported by MATLAB parallel computing toolkit for GPU (MATLAB GPU). The computation time of the algorithm on host CPU and the GPU system is presented for C and Matlab implementations. The forward computation uses finite element method (FEM) and the problem domain is discretized into 14610, 30823, and 66514 tetrahedral elements. The reconstruction time, so achieved for one iteration of the DOT reconstruction for 14610 elements, is 0.52 seconds for a C based GPU program for 2-plane measurements. The corresponding MATLAB based GPU program took 0.86 seconds. The maximum number of reconstructed frames so achieved is 2 frames per second.

MONSTIR II: a 32-channel, multispectral, time-resolved optical tomography system for neonatal brain imaging

We detail the design, construction and performance of the second generation UCL time-resolved optical tomography system, known as MONSTIR II. Intended primarily for the study of the newborn brain, the system employs 32 source fibres that sequentially transmit picosecond pulses of light at any four wavelengths between 650 and 900 nm. The 32 detector channels each contain an independent photo-multiplier tube and temporally correlated photon-counting electronics that allow the photon transit time between each source and each detector position to be measured with high temporal resolution. The system's response time, temporal stability, cross-talk, and spectral characteristics are reported. The efficacy of MONSTIR II is demonstrated by performing multi-spectral imaging of a simple phantom.

Three-dimensional transillumination image reconstruction for small animal with new scattering suppression technique

To realize three-dimensional (3D) optical imaging of the internal structure of an animal body, we have developed a new technique to reconstruct optical computed tomography (optical CT) images from two-dimensional (2D) transillumination images. In transillumination imaging of an animal body using near-infrared light, the image is blurred because of the strong scattering in the tissue. To overcome this problem, we propose a novel technique to apply the point spread function (PSF) for a light source located inside the medium to the transilluminated image of light-absorbing structure. The problem of the depth-dependence of PSF was solved in the calculation of the projection image in the filtered back-projection method. The effectiveness of the proposed technique was assessed in the experiments with a model phantom and a mouse. These analyses verified the feasibility of the practical 3D imaging of the internal light-absorbing structure of a small animal.

Ultrasound-stimulated drug delivery for treatment of residual disease after incomplete resection of head and neck cancer

Microbubbles triggered with localized ultrasound (US) can improve tumor drug delivery and retention. Termed US-stimulated drug delivery, this strategy was applied to head and neck cancer (HNC) in a post-surgical tumor resection model. Luciferase-positive HNC squamous cell carcinoma (SCC) was implanted in the flanks of nude athymic mice (N = 24) that underwent various degrees of surgical tumor resection (0%, 50% or 100%). After surgery, animals received adjuvant therapy with cetuximab-IRDye alone, or cetuximab-IRDye in combination with US-stimulated drug delivery or saline injections (control) on days 4, 7 and 10. Tumor drug delivery was assessed on days 0, 4, 7, 10, 14 and 17 with an in vivo fluorescence imaging system, and tumor viability was evaluated at the same times with in vivo bioluminescence imaging. Tumor caliper measurements occurred two times per week for 24 d. Optical imaging revealed that in the 50% tumor resection group, US-stimulated drug delivery resulted in a significant increase in cetuximab delivery compared with administration of drug alone on day 10 (day of peak fluorescence) (p = 0.03). Tumor viability decreased in all groups that received cetuximab-IRDye in combination with US-stimulated drug delivery, compared with the group that received only the drug. After various degrees of surgical resection, this novel study reports positive improvements in drug uptake in the residual cancer cells when drug delivery is stimulated with US.

Towards non-invasive characterization of breast cancer and cancer metabolism with diffuse optics

We review recent developments in diffuse optical imaging and monitoring of breast cancer, i.e. optical mammography. Optical mammography permits non-invasive, safe and frequent measurement of tissue hemodynamics oxygen metabolism and components (lipids, water, etc.), the development of new compound indices indicative of the risk and malignancy, and holds potential for frequent non-invasive longitudinal monitoring of therapy progression.

Optical tomography reconstruction algorithm based on the radiative transfer equation considering refractive index: Part 2. Inverse model

This paper is the second part of the study of optical tomography based on radiative transfer equation considering refractive index, namely the inverse model which reconstruct the image from the data obtained from the forward model in the first part of this study. In the forward model, we divided the problem into two cases: one is the uniform refractive index and the other is the gradient refractive index. We also use the human brain phantom which contains void-like region to test the forward model, the experiment result shows that the simulation agrees well with the theoretical model. Similarly, in the inverse model, we also consider the reconstruct scheme in two cases as above. In the case of uniform refractive index, we use the adjoint difference method to calculate the gradient of the objective function. In the case of gradient refractive index, we use Lagrangian formalism method to obtain the formula of the gradient. In order to test the reconstruct algorithm, we use the image which was used in the forward model as the predicted data. From the reconstruct image, we can see the case of gradient refractive index agrees with the original image more closer. This shows that the reconstruct algorithm we used is robust and effective.

Optical tomography reconstruction algorithm based on the radiative transfer equation considering refractive index--Part 1: Forward model

The present study consists of two parts. The overall goal is to introduce and experimentally test the optical tomographic imaging algorithm based on the radiative transfer equation considering the refractive index. Considering that the high scattering medium with void-like regions has very low absorption and scattering coefficients, we use the radiative transfer equation to describe the optical parameters of the medium. In the process of photo propagation, not only the absorption and scattering coefficients have impact on the light radiance, but also the refractive index affect the light radiance. Therefore, we focus on the impact of the refractive index in this present study. We divide the refractive index into two cases: the uniform refractive index and the gradient refractive index. The paper is the first part of the present study, namely the forward model. We calculate the derivative of the fluency with the optical parameters by upwind-difference method, and a simpler mathematical framework is obtained in our study. In order to verify the accuracy of the forward model, we select the human brain phantom image with a void-like region and tumor as the experimental data. We found that the experimental measurements are in good agreement with the theoretical predictions of the measurements.

Optical fluorescent imaging to monitor temporal effects of microbubble-mediated ultrasound therapy

Microbubble-mediated ultrasound therapy can noninvasively enhance drug delivery to localized regions in the body. This technique can be beneficial in cancer therapy, but currently there are limitations to tracking the therapeutic effects. The purpose of this experiment was to investigate the potential of fluorescent imaging for monitoring the temporal effects of microbubble-mediated ultrasound therapy. Mice were implanted with 2LMP breast cancer cells. The animals underwent microbubble-mediated ultrasound therapy in the presence of Cy5.5 fluorescent-labeled IgG antibody (large molecule) or Cy5.5 dye (small molecule) and microbubble contrast agents. Control animals were administered fluorescent molecules only. Animals were transiently imaged in vivo at 1, 10, 30, and 60 min post therapy using a small animal optical imaging system. Tumors were excised and analyzed ex vivo. Tumors were homogenized and emulsion imaged for Cy5.5 fluorescence. Monitoring in vivo results showed significant influx of dye into the tumor (p < 0.05) using the small molecule, but not in the large molecule group (p > 0.05). However, after tumor emulsion, significantly higher dye concentration was detected in therapy group tumors for both small and large molecule groups in comparison to their control counterparts (p <0.01). This paper explores a noninvasive optical imaging method for monitoring the effects of microbubble-mediated ultrasound therapy in a cancer model. It provides temporal information following the process of increasing extravasation of molecules into target tumors.

Using near infrared measurement of water content as a cue for detecting biological materials

This paper uses the spectral characteristics of water as a cue to detect biological materials in a scene. The spectra of a wide variety of materials were measured; most of the biological materials showed a spectral feature corresponding to the absorption peak of water at 962 nm. A machine vision system that used two narrowband near infrared light sources and a conventional CCD camera is described. The ability of the system to detect biological material is demonstrated in a series of examples. Water content is not an infallible indicator that a material is biological-wet inanimate surfaces will give a false positive, and some tissues are surrounded by highly scattering, impermeable layers that conceal internal water. Nonetheless, in this paper, we will show that many tissues do give a strong response to this feature and dry, nonbiological materials do not.

Near-Infrared Center-of-Intensity Time Gated Imaging for Detection of a Target in a Highly Scattering Turbid Medium

A near-infrared optical imaging approach for locating a target embedded in a turbid medium is introduced. The target localization is based on an analysis of the spatial variation of the transmitted-light intensity distribution for illumination at different positions on the sample boundary. The approach is used to detect, locate and generate images of absorbing targets embedded inside model scattering media of thickness approximately 50 times the transport mean free path of the medium, as well as, of ex vivo biological tissue specimens.

Diffuse Optical Monitoring of the Neoadjuvant Breast Cancer Therapy

Recent advances in the use of diffuse optical techniques for monitoring the hemodynamic, metabolic and physiological signatures of the neoadjuvant breast cancer therapy effectiveness is critically reviewed. An extensive discussion of the state-of-theart diffuse optical mammography is presented alongside a discussion of the current approaches to breast cancer therapies. Overall, the diffuse optics field is growing rapidly with a great deal of promise to fill an important niche in the current approaches to monitor, predict and personalize neoadjuvant breast cancer therapies.