Characterizing optical properties and spatial heterogeneity of human ovarian tissue using spatial frequency domain imaging

Ultra-miniature dual-wavelength spatial frequency domain imaging for micro-endoscopy

Significance

There is a need for a cost-effective, quantitative imaging tool that can be deployed endoscopically to better detect early stage gastrointestinal cancers. Spatial frequency domain imaging (SFDI) is a low-cost imaging technique that produces near-real time, quantitative maps of absorption and reduced scattering coefficients, but most implementations are bulky and suitable only for use outside the body.

Aim

We aim to develop an ultra-miniature SFDI system comprising an optical fiber array (diameter 0.125 mm) and a micro camera (1 × 1    mm package) to displace conventionally bulky components, in particular, the projector.

Approach

First, we fabricated a prototype with an outer diameter of 3 mm, although the individual component dimensions could permit future packaging to a < 1.5    mm diameter. We developed a phase-tracking algorithm to rapidly extract images with fringe projections at three equispaced phase shifts to perform SFDI demodulation.

Results

To validate the performance, we first demonstrate comparable recovery of quantitative optical properties between our ultra-miniature system and a conventional bench-top SFDI system with an agreement of 15% and 6% for absorption and reduced scattering, respectively. Next, we demonstrate imaging of absorption and reduced scattering of tissue-mimicking phantoms providing enhanced contrast between simulated tissue types (healthy and tumour), done simultaneously at wavelengths of 515 and 660 nm. Using a support vector machine classifier, we estimate that sensitivity and specificity values of > 90 % are feasible for detecting simulated squamous cell carcinoma.

Conclusions

This device shows promise as a cost-effective, quantitative imaging tool to detect variations in optical absorption and scattering as indicators of cancer.

Monte Carlo simulations and phantom modeling for spatial frequency domain imaging of surgical wound monitoring

Significance

Postoperative surgical wound infection is a serious problem around the globe, including in countries with advanced healthcare systems, and a method for early detection of infection is urgently required.

Aim

We explore spatial frequency domain imaging (SFDI) for distinguishing changes in surgical wound healing based on the tissue scattering properties and surgical wound width measurements.

Approach

A comprehensive numerical method is developed by applying a three-dimensional Monte Carlo simulation to a vertical heterogeneous wound model. The Monte Carlo simulation results are validated using resin phantom imaging experiments.

Results

We report on the SFDI lateral resolution with varying reduced scattering value and wound width and discuss the partial volume effect at the sharp vertical boundaries present in a surgical incision. The detection sensitivity of this method is dependent on spatial frequency, wound reduced scattering coefficient, and wound width.

Conclusions

We provide guidelines for future SFDI instrument design and explanation for the expected error in SFDI measurements.

Ultrasound-enhanced Unet model for quantitative photoacoustic tomography of ovarian lesions

Quantitative photoacoustic tomography (QPAT) is a valuable tool in characterizing ovarian lesions for accurate diagnosis. However, accurately reconstructing a lesion's optical absorption distributions from photoacoustic signals measured with multiple wavelengths is challenging because it involves an ill-posed inverse problem with three unknowns: the Grüneisen parameter ( Γ ) , the absorption distribution, and the optical fluence ( ϕ ) . Here, we propose a novel ultrasound-enhanced Unet model (US-Unet) that reconstructs optical absorption distribution from PAT data. A pre-trained ResNet-18 extracts the US features typically identified as morphologies of suspicious ovarian lesions, and a Unet is implemented to reconstruct optical absorption coefficient maps, using the initial pressure and US features extracted by ResNet-18. To test this US-Unet model, we calculated the blood oxygenation saturation values and total hemoglobin concentrations from 655 regions of interest (ROIs) (421 benign, 200 malignant, and 34 borderline ROIs) obtained from clinical images of 35 patients with ovarian/adnexal lesions. A logistic regression model was used to compute the ROC, the area under the ROC curve (AUC) was 0.94, and the accuracy was 0.89. To the best of our knowledge, this is the first study to reconstruct quantitative PAT with PA signals and US-based structural features.

Hyperspectral Imaging for Clinical Applications

Measuring morphological and biochemical features of tissue is crucial for disease diagnosis and surgical guidance, providing clinically significant information related to pathophysiology. Hyperspectral imaging (HSI) techniques obtain both spatial and spectral features of tissue without labeling molecules such as fluorescent dyes, which provides rich information for improved disease diagnosis and treatment. Recent advances in HSI systems have demonstrated its potential for clinical applications, especially in disease diagnosis and image-guided surgery. This review summarizes the basic principle of HSI and optical systems, deep-learning-based image analysis, and clinical applications of HSI to provide insight into this rapidly growing field of research. In addition, the challenges facing the clinical implementation of HSI techniques are discussed.

Perspective on the integration of optical sensing into orthopedic surgical devices

SIGNIFICANCE

Orthopedic surgery currently comprises over 1.5 million cases annually in the United States alone and is growing rapidly with aging populations. Emerging optical sensing techniques promise fewer side effects with new, more effective approaches aimed at improving patient outcomes following orthopedic surgery.

AIM

The aim of this perspective paper is to outline potential applications where fiberoptic-based approaches can complement ongoing development of minimally invasive surgical procedures for use in orthopedic applications.

APPROACH

Several procedures involving orthopedic and spinal surgery, along with the clinical challenge associated with each, are considered. The current and potential applications of optical sensing within these procedures are discussed and future opportunities, challenges, and competing technologies are presented for each surgical application.

RESULTS

Strong research efforts involving sensor miniaturization and integration of optics into existing surgical devices, including K-wires and cranial perforators, provided the impetus for this perspective analysis. These advances have made it possible to envision a next-generation set of devices that can be rigorously evaluated in controlled clinical trials to become routine tools for orthopedic surgery.

CONCLUSIONS

Integration of optical devices into surgical drills and burrs to discern bone/tissue interfaces could be used to reduce complication rates across a spectrum of orthopedic surgery procedures or to aid less-experienced surgeons in complex techniques, such as laminoplasty or osteotomy. These developments present both opportunities and challenges for the biomedical optics community.

Multimodal hyperspectral fluorescence and spatial frequency domain imaging for tissue health diagnostics of the oral cavity

A multimodal, hyperspectral imaging system was built for diagnostics of oral tissues. The system, termed Hyperspectral-Fluorescence-Spatial Frequency Domain Imaging (Hy-F-SFDI), combines the principles of spatial frequency domain imaging, quantitative light fluorescence, and CIELAB color measurement. Hy-F-SFDI employs a compact LED projector, excitation LED, and a 16 channel hyperspectral camera mounted on a custom platform for tissue imaging. A two layer Monte Carlo approach was used to generate a reference table for quick tissue analysis. To demonstrate the clinical capabilities of Hy-F-SFDI, we used the system to quantify gingival tissue hemoglobin volume fraction, detect caries, bacterial activity, and measure tooth color of a volunteer at different time points. Hy-F-SFDI was able to measure quantitative changes in tissue parameters.

A modified source-detector configuration for the discrimination between normal and diseased human breast based on the continuous-wave diffuse optical imaging approach: a simulation study

Breast tumors are among the most common types of tumors that can affect both genders. It may spread to the whole breast without any symptoms. Therefore, the early detection and accurate diagnosis of breast tumors are significantly important. Current approaches for breast cancer screening such as positron emission tomography (PET) and magnetic resonance imaging (MRI) have some limitations of being time and money-consuming. In addition, mammography screening is not recommended for women under forty. Consequently, optical techniques have been introduced as safe and functional alternatives. Diffuse optical imaging is a non-invasive imaging technique that utilizes near-infrared light to examine biological tissues based on measuring the optical transmission and/or reflection at various locations on the tissue surface. In this paper, we propose a modified arrangement between the laser source and the detectors for distinguishing tumors from normal breast tissue. A three-dimensional model of the normal human breast with three types of tumors is developed using a COMSOL simulation software based on the finite element solution of Helmholtz equation to estimate optical fluence distribution. The breast model consists of four layers: skin, fat, glandular, and muscle, where the tumor is included in the glandular layer. Different wavelengths were used to determine the most proper wavelength for the discrimination between the normal tissue and tumor. The obtained results were verified using the receiver operating characteristic (ROC) method. The resultant fluence images show different features between normal breast and breast with tumor especially using 600-nm incident laser as demonstrated by the obtained ROC curves.

Near Infrared Fluorescence Imaging of Intraperitoneal Ovarian Tumors in Mice Using Erythrocyte-Derived Optical Nanoparticles and Spatially-Modulated Illumination

Simple Summary

Ovarian cancer has a greater mortality rate than all gynecological malignancies combined. While cytoreductive surgery remains the primary therapeutic approach, its success is limited by the inability to visualize all tumor nodules for resection. We developed light activated nano-sized particles derived from red blood cells as potential imaging probes for near infrared fluorescence imaging of tumors during cytoreductive surgery. We present the first demonstration of the use of these nanoparticles in conjunction a spatially-modulated illumination (SMI) modality to image ovarian intraperitoneal tumors in mice. Our findings indicate that, at 24 h post-administration, these nanoparticles accumulated at higher levels in tumors as compared to organs, and that use of SMI enhances the image contrast.

Abstract

Ovarian cancer is the deadliest gynecological cancer. Cytoreductive surgery to remove primary and intraperitoneal tumor deposits remains as the standard therapeutic approach. However, lack of an intraoperative image-guided approach to enable the visualization of all tumors can result in incomplete cytoreduction and recurrence. We engineered nano-sized particles derived from erythrocytes that encapsulate the near infrared (NIR) fluorochrome, indocyanine green, as potential imaging probes for tumor visualization during cytoreductive surgery. Herein, we present the first demonstration of the use of these nanoparticles in conjunction with spatially-modulated illumination (SMI), at spatial frequencies in the range of 0–0.5 mm⁻¹, to fluorescently image intraperitoneal ovarian tumors in mice. Results of our animal studies suggest that the nanoparticles accumulated at higher levels within tumors 24 h post-intraperitoneal injection as compared to various other organs. We demonstrate that, under the imaging specifications reported here, use of these nanoparticles in conjunction with SMI enhances the fluorescence image contrast between intraperitoneal tumors and liver, and between intraperitoneal tumors and spleen by nearly 2.1, and 3.0 times, respectively, at the spatial frequency of 0.2 mm⁻¹ as compared to the contrast values at spatially-uniform (non-modulated) illumination. These results suggest that the combination of erythrocyte-derived NIR nanoparticles and structured illumination provides a promising approach for intraoperative fluorescence imaging of ovarian tumor nodules at enhanced contrast.

Spatial-Frequency Domain Imaging: An Emerging Depth-Varying and Wide-Field Technique for Optical Property Measurement of Biological Tissues

Measurement of optical properties is critical for understanding light-tissue interaction, properly interpreting measurement data, and gaining better knowledge of tissue physicochemical properties. However, conventional optical measuring techniques are limited in point measurement, which partly hinders the applications on characterizing spatial distribution and inhomogeneity of optical properties of biological tissues. Spatial-frequency domain imaging (SFDI), as an emerging non-contact, depth-varying and wide-field optical imaging technique, is capable of measuring the optical properties in a wide field-of-view on a pixel-by-pixel basis. This review first describes the typical SFDI system and the principle for estimating optical properties using the SFDI technique. Then, the applications of SFDI in the fields of biomedicine, as well as food and agriculture, are reviewed, including burn assessment, skin tissue evaluation, tumor tissue detection, brain tissue monitoring, and quality evaluation of agro-products. Finally, a discussion on the challenges and future perspectives of SFDI for optical property estimation is presented.

Virus-Mimicking Nanoparticles for Targeted Near Infrared Fluorescence Imaging of Intraperitoneal Ovarian Tumors in Mice

Ovarian cancer is the most lethal malignancy affecting the female reproductive system. Identification and removal of all ovarian intraperitoneal tumor deposits during the intraoperative surgery is important towards preventing cancer recurrence and ultimately improving patient survival. Herein, we investigate the effectiveness of virus mimicking nanoparticles, derived from genome-depleted plant-infecting brome mosaic virus, and doped with near infrared (NIR) brominated cyanine dye BrCy106-NHS, for targeted NIR fluorescence imaging of intraperitoneal ovarian tumors. We refer to these nanoparticles as optical viral ghosts (OVGs). We functionalized the OVGs with antibodies against HER2 receptor, a biomarker over-expressed in ovarian cancers. We injected functionalized OVGs, non-functionalized OVGs, and non-encapsulated BrCy106-NHS intravenously in mice implanted with ovarian intraperitoneal tumors. Tumors were extracted at 2, 6, and 24 h post-injection, and quantitatively analyzed using NIR fluorescence imaging. Fluorescence emission from tumors associated with the injection of the functionalized OVGs continued to increase between 2 and 24 h post-injection. At 24 h timepoint, the average spectrally-integrated fluorescence emission from homogenized tumors containing functionalized-OVGs was about 3.5 and 19.5 times higher than those containing non-functionalized OVGs or non-encapsulated BrCy106-NHS, respectively. Similarly, by using the functionalized-OVGs, the imaging signal-to-noise ratio at 24 h timepoint was enhanced by approximately threefold and sevenfold as compared to non-functionalized OVGs and the non-encapsulated dye, respectively. These functionalized virus-mimicking NIR nano-constructs could potentially be used for intraoperative visualization of ovarian tumors implants.

Spatial frequency domain imaging for the longitudinal monitoring of vascularization during mouse femoral graft healing

Allograft is the current gold standard for treating critical-sized bone defects. However, allograft healing is usually compromised partially due to poor host-mediated vascularization. In the efforts towards developing new methods to enhance allograft healing, a non-terminal technique for monitoring the vascularization is needed in pre-clinical mouse models. In this study, we developed a non-invasive instrument based on spatial frequency domain imaging (SFDI) for longitudinal monitoring of the mouse femoral graft healing. SFDI technique provided total hemoglobin concentration (THC) and oxygen saturation (StO2) of the graft and the surrounding soft tissues. SFDI measurements were performed from 1 day before to 44 days after graft transplantation. Autograft, another type of bone graft with higher vascularization potential was also measured as a comparison to allograft. For both grafts, the overall temporal changes of the measured THC agreed with the physiological expectations of vascularization timeline during bone healing. A significantly greater increase in THC was observed in the autograft group compared to the allograft group, which agreed with the expectation that allografts have more compromised vascularization.

A Review on Advances in Intra-operative Imaging for Surgery and Therapy: Imagining the Operating Room of the Future

With the advent of Minimally Invasive Surgery (MIS), intra-operative imaging has become crucial for surgery and therapy guidance, allowing to partially compensate for the lack of information typical of MIS. This paper reviews the advancements in both classical (i.e. ultrasounds, X-ray, optical coherence tomography and magnetic resonance imaging) and more recent (i.e. multispectral, photoacoustic and Raman imaging) intra-operative imaging modalities. Each imaging modality was analyzed, focusing on benefits and disadvantages in terms of compatibility with the operating room, costs, acquisition time and image characteristics. Tables are included to summarize this information. New generation of hybrid surgical room and algorithms for real time/in room image processing were also investigated. Each imaging modality has its own (site- and procedure-specific) peculiarities in terms of spatial and temporal resolution, field of view and contrasted tissues. Besides the benefits that each technique offers for guidance, considerations about operators and patient risk, costs, and extra time required for surgical procedures have to be considered. The current trend is to equip surgical rooms with multimodal imaging systems, so as to integrate multiple information for real-time data extraction and computer-assisted processing. The future of surgery is to enhance surgeons eye to minimize intra- and after-surgery adverse events and provide surgeons with all possible support to objectify and optimize the care-delivery process.

Adaptive Boosting (AdaBoost)-based multiwavelength spatial frequency domain imaging and characterization for ex vivo human colorectal tissue assessment

The current gold standard diagnostic test for colorectal cancer remains histological inspections of endoluminal neoplasia in biopsy specimens. However, biopsy site selection requires visual inspection of the bowel, typically with a white-light endoscope. Therefore, this technique is poorly suited to detect small or innocuous-appearing lesions. We hypothesize that an alternative modality-multiwavelength spatial frequency domain imaging (SFDI)-would be able to differentiate various colorectal neoplasia from normal tissue. In this ex vivo study of human colorectal tissues, we report the optical absorption and scattering signatures of normal, adenomatous polyp and cancer specimens. An abnormal vs. normal adaptive boosting (AdaBoost) classifier is trained to dichotomize tissue based on SFDI imaging characteristics, and an area under the receiver operating characteristic (ROC) curve (AUC) of 0.95 is achieved. We conclude that AdaBoost-based multiwavelength SFDI can differentiate abnormal from normal colorectal tissues, potentially improving endoluminal screening of the distal gastrointestinal tract in the future.

JP, Austin W, Tabassum SM, Aguénounon E, Tilbury K, Saager RB, Gioux S, Roblyer D. OpenSFDI: an open-source guide for constructing a spatial frequency domain imaging system

Significance: Spatial frequency domain imaging (SFDI) is a diffuse optical measurement technique that can quantify tissue optical absorption (μ_a) and reduced scattering (<inline-formula>μs'</inline-formula>) on a pixel-by-pixel basis. Measurements of μ_a at different wavelengths enable the extraction of molar concentrations of tissue chromophores over a wide field, providing a noncontact and label-free means to assess tissue viability, oxygenation, microarchitecture, and molecular content. We present here openSFDI: an open-source guide for building a low-cost, small-footprint, three-wavelength SFDI system capable of quantifying μ_a and <inline-formula>μs'</inline-formula> as well as oxyhemoglobin and deoxyhemoglobin concentrations in biological tissue. The companion website provides a complete parts list along with detailed instructions for assembling the openSFDI system.<p> Aim: We describe the design of openSFDI and report on the accuracy and precision of optical property extractions for three different systems fabricated according to the instructions on the openSFDI website.</p> <p> Approach: Accuracy was assessed by measuring nine tissue-simulating optical phantoms with a physiologically relevant range of μ_a and <inline-formula>μs'</inline-formula> with the openSFDI systems and a commercial SFDI device. Precision was assessed by repeatedly measuring the same phantom over 1 h.</p> <p> Results: The openSFDI systems had an error of 0  ±  6  %   in μ_a and -2  ±  3  %   in <inline-formula>μs'</inline-formula>, compared to a commercial SFDI system. Bland-Altman analysis revealed the limits of agreement between the two systems to be   ±  0.004  mm^-  1 for μ_a and -0.06 to 0.1  mm^-  1 for <inline-formula>μs'</inline-formula>. The openSFDI system had low drift with an average standard deviation of 0.0007  mm^-  1 and 0.05  mm^-  1 in μ_a and <inline-formula>μs'</inline-formula>, respectively.</p>,<p> Conclusion: The openSFDI provides a customizable hardware platform for research groups seeking to utilize SFDI for quantitative diffuse optical imaging.</p>

Histogram analysis of en face scattering coefficient map predicts malignancy in human ovarian tissue

Ovarian cancer is a heterogeneous disease at the molecular and histologic level. Optical coherence tomography (OCT) is able to map ovarian tissue optical properties and heterogeneity, which has been proposed as a feature to aid in diagnosis of ovarian cancer. In this manuscript, depth-resolved en face scattering maps of malignant ovaries, benign ovaries, and benign fallopian tubes obtained from 20 patients are provided to visualize the heterogeneity of ovarian tissues. Six features are extracted from histograms of scattering maps. All features are able to statistically distinguish benign from malignant ovaries. Two prediction models were constructed based on these features: a logistic regression model (LR) and a support vector machine (SVM). The optimal set of features is mean scattering coefficient and scattering map entropy. The LR achieved a sensitivity and specificity of 97.0% and 97.8%, and SVM demonstrated a sensitivity and specificity of 99.6% and 96.4%. Our initial results demonstrate the feasibility of using OCT as an "optical biopsy tool" for detecting the microscopic scattering changes associated with neoplasia in human ovarian tissue.

Hyperspectral imaging in the spatial frequency domain with a supercontinuum source

We introduce a method for quantitative hyperspectral optical imaging in the spatial frequency domain (hs-SFDI) to image tissue absorption (μa) and reduced scattering (μs') parameters over a broad spectral range. The hs-SFDI utilizes principles of spatial scanning of the spectrally dispersed output of a supercontinuum laser that is sinusoidally projected onto the tissue using a digital micromirror device. A scientific complementary metal-oxide-semiconductor camera is used for capturing images that are demodulated and analyzed using SFDI computational models. The hs-SFDI performance is validated using tissue-simulating phantoms over a range of μa and μs' values. Quantitative hs-SFDI images are obtained from an ex-vivo beef sample to spatially resolve concentrations of oxy-, deoxy-, and met-hemoglobin, as well as water and fat fractions. Our results demonstrate that the hs-SFDI can quantitatively image tissue optical properties with 1000 spectral bins in the 580- to 950-nm range over a wide, scalable field of view. With an average accuracy of 6.7% and 12.3% in μa and μs', respectively, compared to conventional methods, hs-SFDI offers a promising approach for quantitative hyperspectral tissue optical imaging.

Spatial frequency domain imaging in 2019: principles, applications, and perspectives

Spatial frequency domain imaging (SFDI) has witnessed very rapid growth over the last decade, owing to its unique capabilities for imaging optical properties and chromophores over a large field-of-view and in a rapid manner. We provide a comprehensive review of the principles of this imaging method as of 2019, review the modeling of light propagation in this domain, describe acquisition methods, provide an understanding of the various implementations and their practical limitations, and finally review applications that have been published in the literature. Importantly, we also introduce a group effort by several key actors in the field for the dissemination of SFDI, including publications, advice in hardware and implementations, and processing code, all freely available online.

Spatial frequency domain imaging in 2019: principles, applications, and perspectives

Spatial frequency domain imaging (SFDI) has witnessed very rapid growth over the last decade, owing to its unique capabilities for imaging optical properties and chromophores over a large field-of-view and in a rapid manner. We provide a comprehensive review of the principles of this imaging method as of 2019, review the modeling of light propagation in this domain, describe acquisition methods, provide an understanding of the various implementations and their practical limitations, and finally review applications that have been published in the literature. Importantly, we also introduce a group effort by several key actors in the field for the dissemination of SFDI, including publications, advice in hardware and implementations, and processing code, all freely available online.

Single snapshot imaging of optical properties using a single-pixel camera: a simulation study

We present the effects of using a single-pixel camera approach to extract optical properties with the single-snapshot spatial frequency-domain imaging method. We acquired images of a human hand for spatial frequencies ranging from 0.1 to 0.4  mm  -  1 with increasing compression ratios using adaptive basis scan wavelet prediction strategy. In summary, our findings indicate that the extracted optical properties remained usable up to 99% of compression rate at a spatial frequency of 0.2  mm  -  1 with errors of 5% in reduced scattering and 10% in absorption.

Low-cost compact multispectral spatial frequency domain imaging prototype for tissue characterization

We present a low-cost, compact, and multispectral spatial frequency domain imaging prototype. Illumination components, including 9 LEDs (660 nm - 950 nm) placed on a custom-designed printed circuit board, linear and rotational motors, a printed sinusoidal pattern, and collimation and projection optics as well as the detection components are incorporated in a compact custom-designed 3D-printed probe. Reconstruction of absorption and reduced scattering coefficients is evaluated via imaging tissue mimicking phantoms and potentials of the probe for biological tissue imaging are evaluated via imaging human ovarian tissue ex vivo.

Review of structured light in diffuse optical imaging

Diffuse optical imaging probes deep living tissue enabling structural, functional, metabolic, and molecular imaging. Recently, due to the availability of spatial light modulators, wide-field quantitative diffuse optical techniques have been implemented, which benefit greatly from structured light methodologies. Such implementations facilitate the quantification and characterization of depth-resolved optical and physiological properties of thick and deep tissue at fast acquisition speeds. We summarize the current state of work and applications in the three main techniques leveraging structured light: spatial frequency-domain imaging, optical tomography, and single-pixel imaging. The theory, measurement, and analysis of spatial frequency-domain imaging are described. Then, advanced theories, processing, and imaging systems are summarized. Preclinical and clinical applications on physiological measurements for guidance and diagnosis are summarized. General theory and method development of tomographic approaches as well as applications including fluorescence molecular tomography are introduced. Lastly, recent developments of single-pixel imaging methodologies and applications are reviewed.

Quantitative multispectral ex vivo optical evaluation of human ovarian tissue using spatial frequency domain imaging

About 85-90% of all ovarian cancers are carcinomas; these manifest clinically as mass-forming epithelial proliferations involving the ovary. In this study, a visible light spatial frequency domain imaging (SFDI) system was used for multispectral ex vivo imaging and quantitative evaluation of freshly excised benign and malignant human ovarian tissues. A total of 14 ovaries from 11 patients undergoing oophorectomy were investigated. Using a logistic regression model with seven significant spectral and spatial features extracted from SFDI images, a sensitivity of 94.06% and specificity of 93.53% were achieved for prediction of histologically confirmed invasive carcinoma.

Determination of the complex refractive index segments of turbid sample with multispectral spatially modulated structured light and models approximation

Spectral data enabling the derivation of a biological tissue sample's complex refractive index (CRI) can provide a range of valuable information in the clinical and research contexts. Specifically, changes in the CRI reflect alterations in tissue morphology and chemical composition, enabling its use as an optical marker during diagnosis and treatment. In the present work, we report a method for estimating the real and imaginary parts of the CRI of a biological sample using Kramers-Kronig (KK) relations in the spatial frequency domain. In this method, phase-shifted sinusoidal patterns at single high spatial frequency are serially projected onto the sample surface at different near-infrared wavelengths while a camera mounted normal to the sample surface acquires the reflected diffuse light. In the offline analysis pipeline, recorded images at each wavelength are converted to spatial phase maps using KK analysis and are then calibrated against phase-models derived from diffusion approximation. The amplitude of the reflected light, together with phase data, is then introduced into Fresnel equations to resolve both real and imaginary segments of the CRI at each wavelength. The technique was validated in tissue-mimicking phantoms with known optical parameters and in mouse models of ischemic injury and heat stress. Experimental data obtained indicate variations in the CRI among brain tissue suffering from injury. CRI fluctuations correlated with alterations in the scattering and absorption coefficients of the injured tissue are demonstrated. This technique for deriving dynamic changes in the CRI of tissue may be further developed as a clinical diagnostic tool and for biomedical research applications. To the best of our knowledge, this is the first report of the estimation of the spectral CRI of a mouse head following injury obtained in the spatial frequency domain.

Reference-free determination of tissue absorption coefficient by modulation transfer function characterization in spatial frequency domain

Background

Spatial frequency domain (SFD) measurement allows rapid and non-contact wide-field imaging of the tissue optical properties, thus has become a potential tool for assessing physiological parameters and therapeutic responses during photodynamic therapy of skin diseases. The conventional SFD measurement requires a reference measurement within the same experimental scenario as that for a test one to calibrate mismatch between the real measurements and the model predictions. Due to the individual physical and geometrical differences among different tissues, organs and patients, an ideal reference measurement might be unavailable in clinical trials. To address this problem, we present a reference-free SFD determination of absorption coefficient that is based on the modulation transfer function (MTF) characterization.

Methods

Instead of the absolute amplitude that is used in the conventional SFD approaches, we herein employ the MTF to characterize the propagation of the modulated lights in tissues. With such a dimensionless relative quantity, the measurements can be naturally corresponded to the model predictions without calibrating the illumination intensity. By constructing a three-dimensional database that portrays the MTF as a function of the optical properties (both the absorption coefficient μ_a and the reduced scattering coefficient \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu^{\prime}_{s}$$\end{document}μs′) and the spatial frequency, a look-up table approach or a least-square curve-fitting method is readily applied to recover the absorption coefficient from a single frequency or multiple frequencies, respectively.

Results

Simulation studies have verified the feasibility of the proposed reference-free method and evaluated its accuracy in the absorption recovery. Experimental validations have been performed on homogeneous tissue-mimicking phantoms with μ_a ranging from 0.01 to 0.07 mm⁻¹ and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu^{\prime}_{s}$$\end{document}μs′ = 1.0 or 2.0 mm⁻¹. The results have shown maximum errors of 4.86 and 7% for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu^{\prime}_{s}$$\end{document}μs′ = 1.0 mm⁻¹ and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu^{\prime}_{s}$$\end{document}μs′ = 2.0 mm⁻¹, respectively. We have also presented quantitative ex vivo imaging of human lung cancer in a subcutaneous xenograft mouse model for further validation, and observed high absorption contrast in the tumor region.

Conclusions

The proposed method can be applied to the rapid and accurate determination of the absorption coefficient, and better yet, in a reference-free way. We believe this reference-free strategy will facilitate the clinical translation of the SFD measurement to achieve enhanced intraoperative hemodynamic monitoring and personalized treatment planning in photodynamic therapy.

Finite element simulation of light transfer in turbid media under structured illumination

The spatial-frequency domain (SFD) imaging technique allows us to estimate the optical properties of biological tissues in a wide field of view. The technique is, however, prone to error in measurement because the two crucial assumptions used for deriving the analytical solution to the diffusion approximation cannot be met perfectly in practical applications. This research mainly focused on modeling light transfer in turbid media under the normal incidence of structured illumination using the finite element method (FEM). Finite element simulations were performed for 50 simulation samples with different combinations of optical absorption and scattering coefficients for varying spatial frequencies, and the results were then compared with the analytical method and Monte Carlo simulation. Relationships between diffuse reflectance and dimensionless absorption and dimensionless scattering coefficients were investigated. The results indicated that the FEM provided reasonable results for diffuse reflectance, compared with the analytical method. Both the FEM and the analytical method overestimated the reflectance for μ_tr/f_x values of greater than 2 and underestimated the reflectance for μ_tr/f_x values of smaller than 2. Larger values of μs'/μ_a yielded better diffuse reflectance estimations than did those of smaller than 10. The reflectance increased nonlinearly with the dimensionless scattering, whereas the reflectance decreased linearly with the dimensionless absorption. It was also observed that diffuse reflectance was relatively stable and insensitive to μs' when the dimensionless scattering was larger than 50. Overall results demonstrate that the FEM is effective for modeling light transfer in turbid media and can be used to explore the effects of crucial parameters for the SFD imaging technique.

Multimodal optical setup based on spectrometer and cameras combination for biological tissue characterization with spatially modulated illumination

The application of optical techniques as tools for biomedical research has generated substantial interest for the ability of such methodologies to simultaneously measure biochemical and morphological parameters of tissue. Ongoing optimization of optical techniques may introduce such tools as alternative or complementary to conventional methodologies. The common approach shared by current optical techniques lies in the independent acquisition of tissue’s optical properties (i.e., absorption and reduced scattering coefficients) from reflected or transmitted light. Such optical parameters, in turn, provide detailed information regarding both the concentrations of clinically relevant chromophores and macroscopic structural variations in tissue. We couple a noncontact optical setup with a simple analysis algorithm to obtain absorption and scattering coefficients of biological samples under test. Technically, a portable picoprojector projects serial sinusoidal patterns at low and high spatial frequencies, while a spectrometer and two independent CCD cameras simultaneously acquire the reflected diffuse light through a single spectrometer and two separate CCD cameras having different bandpass filters at nonisosbestic and isosbestic wavelengths in front of each. This configuration fills the gaps in each other’s capabilities for acquiring optical properties of tissue at high spectral and spatial resolution. Experiments were performed on both tissue-mimicking phantoms as well as hands of healthy human volunteers to quantify their optical properties as proof of concept for the present technique. In a separate experiment, we derived the optical properties of the hand skin from the measured diffuse reflectance, based on a recently developed camera model. Additionally, oxygen saturation levels of tissue measured by the system were found to agree well with reference values. Taken together, the present results demonstrate the potential of this integrated setup for diagnostic and research applications.

Classification and analysis of human ovarian tissue using full field optical coherence tomography

In this study, a full field optical coherence tomography (FFOCT) system was used to analyze and classify normal and malignant human ovarian tissue. 14 ovarian tissue samples (7 normal, 7 malignant) were imaged with the FFOCT system and five features were extracted by analyzing the normalized image histogram from 56 FFOCT images, based on the differences in the morphology of the normal and malignant tissue samples. A generalized linear model (GLM) classifier was trained using 36 images, and sensitivity of 95.3% and specificity of 91.1% was obtained. 20 images were used to test the model, and a sensitivity of 91.6% and specificity of 87.7% was obtained.