Design, Implementation, and Evaluation of a Fluorescence Laminar Optical Tomography Scanner for Brain Imaging

Implementation of new instrumentation and techniques for neuroscience research in recent years has opened new avenues in the study of the dynamics of large-scale neural networks such as the brain. In many of these techniques, including fluorescence recordings and optogenetic stimulation, a combination of photonics and molecular genetic methods are exploited to manipulate and monitor neural activities. Such techniques have been proven to be highly efficient in unraveling the mysteries of data processing in the micro circuits of the brain and as a result these techniques are widely used nowadays in most neuroscience labs. In optogenetics, cell-types of interest are genetically modified by expressing light-sensitive proteins adapted from microbial opsin. Once these proteins are expressed, we are able to use light of appropriate wavelengths to manipulate, increase or suppress neural activity of specific neurons on command. With a high temporal resolution (in the order of milliseconds) and cell-type-specific precision, optogenetics is able to probe how the nervous system functions in real-time, even in freely-moving animals. Currently, whenever genetic modifications are employed in the study of nervous systems, fluorescence proteins are also co-expressed in the same cells as biological markers to visualize the induced changes in the targeted cells. Despite its importance to trace the signal of such markers in-vivo, capabilities of the developed fluorescence tomography instrumentation are still limited and researchers mostly document the fluorescence distribution and expression of proteins of interest after euthanizing the animal and dissection of the tissue. In this project, we present our effort in implementing a fluorescence laminar optical tomography (FLOT) system which is specifically designed for non-invasive three dimensional imaging of fluorescence proteins within the brain of rodents. The application of the developed technology is not limited to optogenetics, but it can be used as a powerful tool to help improving the precision and accuracy of neuroscience and optogenetic experiments. In this design, a set of galvanometer mirrors are employed for realization of a fast and flexible scanner while a highly sensitive camera records the produced fluorescence signals. Fluorescence laminar optical tomography (FLOT) scanner has shown promising results in imaging superficial areas up to 2mm deep from the surface, with the resolution of ~200µm. Details of the design of the hardware and reconstruction algorithms are discussed and samples of experimental results are presented

Simulating photodynamic therapy for the treatment of glioblastoma using Monte Carlo radiative transport

Funding: LF acknowledges financial support from the UK Research and Innovation (UKRI) Engineering and Physical Sciences Research Council (EPSRC) Centre for Doctoral Training in Applied Photonics (Grant No. EP/S022821/1) and the Laser Research and Therapy Fund (Grant No. SC030850).Significance Glioblastoma (GBM) is a rare but deadly form of brain tumor with a low median survival rate of 14.6 months, due to its resistance to treatment. An independent simulation of the INtraoperative photoDYnamic therapy for GliOblastoma (INDYGO) trial, a clinical trial aiming to treat the GBM resection cavity with photo- dynamic therapy (PDT) via a laser coupled balloon device, is demonstrated. Aim To develop a framework providing increased understanding for the PDT treatment, its parameters, and their impact on the clinical outcome. Approach We use Monte Carlo radiative transport techniques within a computational brain model containing a GBM to simulate light path and PDT effects. Treatment parameters (laser power, photosensitizer concentration, and irradiation time) are considered, as well as PDT’s impact on brain tissue temperature.  Results The simulation suggests that 39% of post-resection GBM cells are killed at the end of treatment when using the standard INDYGO trial protocol (light fluence = 200 J∕cm2 at balloon wall) and assuming an initial photosensitizer concentration of 5 μM. Increases in treatment time and light power (light fluence = 400 J∕cm2 at balloon wall) result in further cell kill but increase brain cell temperature, which potentially affects treatment safety. Increasing the p hotosensitizer concentration produces the most significant increase in cell kill, with 61% of GBM cells killed when doubling concentration to 10 μM and keeping the treatment time and power the same. According to these simulations, the standard trial protocol is reasonably well optimized with improvements in cell kill difficult to achieve without potentially dangerous increases in temperature. To improve treatment outcome, focus should be placed on improving the photosensitizer.  Conclusions With further development and optimization, the simulation could have potential clinical benefit and be used to help plan and optimize intraoperative PDT treatment for GBM.Peer reviewe

ValoMC: a Monte Carlo software and MATLAB toolbox for simulating light transport in biological tissue

A Monte Carlo method for photon transport has gained wide popularity in biomedical optics for studying light behaviour in tissue. Nowadays, typical computation times range from a few minutes to hours. Although various implementations of the Monte Carlo algorithm exist, there is only a limited number of free software available. In addition, these packages may require substantial learning efforts. To address these issues, we present a new Monte Carlo software with a user-friendly interface. The simulation geometry is defined using an unstructured (triangular or tetrahedral) mesh. The program solves the photon fluence in the computation domain and the exitance at the domain boundary. It is capable of simulating complex measurement geometries with spatially varying optical parameter distributions and supports several types of light sources as well as intensity modulated light. Furthermore, attention is given to ease of use and fast problem set up with a MATLAB (The MathWorks Inc., Natick, MA) interface. The simulation code is written in C++ and parallelized using OpenMP. The simulation code has been validated against analytical and numerical solutions of radiative transfer equation and other Monte Carlo software in good agreement. The software is available for download from the homepage https://inverselight.github.io/ValoMC/ and the source code from GitHub https://github.com/InverseLight/ValoMC

Online object oriented Monte Carlo computational tool for the needs of biomedical optics

Conceptual engineering design and optimization of laser-based imaging techniques and optical diagnostic systems used in the field of biomedical optics requires a clear understanding of the light-tissue interaction and peculiarities of localization of the detected optical radiation within the medium. The description of photon migration within the turbid tissue-like media is based on the concept of radiative transfer that forms a basis of Monte Carlo (MC) modeling. An opportunity of direct simulation of influence of structural variations of biological tissues on the probing light makes MC a primary tool for biomedical optics and optical engineering. Due to the diversity of optical modalities utilizing different properties of light and mechanisms of light-tissue interactions a new MC code is typically required to be developed for the particular diagnostic application. In current paper introducing an object oriented concept of MC modeling and utilizing modern web applications we present the generalized online computational tool suitable for the major applications in biophotonics. The computation is supported by NVIDEA CUDA Graphics Processing Unit providing acceleration of modeling up to 340 times

Noninvasive optical estimation of CSF thickness for brain-atrophy monitoring

Dementia disorders are increasingly becoming sources of a broad range of problems, strongly interfering with normal daily tasks of a growing number of individuals. Such neurodegenerative diseases are often accompanied with progressive brain atrophy that, at late stages, leads to drastically reduced brain dimensions. At the moment, this structural involution can be followed with XCT or MRI measurements that share numerous disadvantages in terms of usability, invasiveness and costs. In this work, we aim to retrieve information concerning the brain atrophy stage and its evolution, proposing a novel approach based on non-invasive time-resolved Near Infra-Red (tr-NIR) measurements. For this purpose, we created a set of human-head atlases, in which we eroded the brain as it would happen in a clinical brain-atrophy progression. With these realistic meshes, we reproduced a longitudinal tr-NIR study exploiting a Monte-Carlo photon propagation algorithm to model the varying cerebral spinal fluid (CSF). The study of the time-resolved reflectance curve at late photon arrival times exhibited peculiar slope-changes upon CSF layer increase that were confirmed under several measurement conditions. The performance of the technique suggests good sensitivity to CSF variation, useful for a fast and non-invasive observation of the dementia progression.Comment: 32 pages, double spaced, 11 figure

Multi-spectral light interaction modeling and imaging of skin lesions

Nevoscope as a diagnostic tool for melanoma was evaluated using a white light source with promising results. Information about the lesion depth and its structure will further improve the sensitivity and specificity of melanoma diagnosis. Wavelength-dependent variable penetration power of monochromatic light in the trans-illumination imaging using the Nevoscope can be used to obtain this information. Optimal selection of wavelengths for multi-spectral imaging requires light-tissue interaction modeling. For this, three-dimensional wavelength dependent voxel-based models of skin lesions with different depths are proposed. A Monte Carlo simulation algorithm (MCSVL) is developed in MATLAB and the tissue models are simulated using the Nevoscope optical geometry. 350-700nm optical wavelengths with an interval of 5nm are used in the study. A correlation analysis between the lesion depth and the diffuse reflectance is then used to obtain wavelengths that will produce diffuse reflectance suitable for imaging and give information related to the nevus depth and structure. Using the selected wavelengths, multi-spectral trans-illumination images of the skin lesions are collected and analyzed. An adaptive wavelet transform based tree-structure classification method (ADWAT) is proposed to classify epi-illuminance images of the skin lesions obtained using a white light source into melanoma and dysplastic nevus images classes. In this method, tree-structure models of melanoma and dysplastic nevus are developed and semantically compared with the tree-structure of the unknown image for classification. Development of the tree-structure is dependent on threshold selections obtained from a statistical analysis of the feature set. This makes the classification method adaptive. The true positive value obtained for this classifier is 90% with a false positive of 10%. The Extended ADWAT method and Fuzzy Membership Functions method using combined features from the epi-illuminance and multi-spectral images further improve the sensitivity and specificity of melanoma diagnosis. The combined feature set with the Extended-ADWAT method gives a true positive of 93.33% with a false positive of 8.88%. The Gaussian Membership Functions give a true positive of 100% with a false positive of 17.77% while the Bell Membership Functions give a true positive of 100% with a false positive of 4.44%

Real-time tissue viability assessment using near-infrared light

Despite significant advances in medical imaging technologies, there currently exist no tools to effectively assist healthcare professionals during surgical procedures. In turn, procedures remain subjective and dependent on experience, resulting in avoidable failure and significant quality of care disparities across hospitals. Optical techniques are gaining popularity in clinical research because they are low cost, non-invasive, portable, and can retrieve both fluorescence and endogenous contrast information, providing physiological information relative to perfusion, oxygenation, metabolism, hydration, and sub-cellular content. Near-infrared (NIR) light is especially well suited for biological tissue and does not cause tissue damage from ionizing radiation or heat. My dissertation has been focused on developing rapid imaging techniques for mapping endogenous tissue constituents to aid surgical guidance. These techniques allow, for the first time, video-rate quantitative acquisition over a large field of view (> 100 cm2) in widefield and endoscopic implementations. The optical system analysis has been focused on the spatial-frequency domain for its ease of quantitative measurements over large fields of view and for its recent development in real-time acquisition, single snapshot of optical properties (SSOP) imaging. Using these methods, this dissertation provides novel improvements and implementations to SSOP, including both widefield and endoscopic instrumentations capable of video-rate acquisition of optical properties and sample surface profile maps. In turn, these measures generate profile-corrected maps of hemoglobin concentration that are highly beneficial for perfusion and overall tissue viability. Also utilizing optical property maps, a novel technique for quantitative fluorescence imaging was also demonstrated, showing large improvement over standard and ratiometric methods. To enable real-time feedback, rapid processing algorithms were designed using lookup tables that provide a 100x improvement in processing speed. Finally, these techniques were demonstrated in vivo to investigate their ability for early detection of tissue failure due to ischemia. Both pre-clinical studies show endogenous contrast imaging can provide early measures of future tissue viability. The goal of this work has been to provide the foundation for real-time imaging systems that provide tissue constituent quantification for tissue viability assessments.2018-01-09T00:00:00

Theoretical and Experimental Tools for Clinical Translation of Quantitative Tissue Optical Sensing.

Quantitative tissue optical spectroscopy has been considered as a promising method for clinical diagnosis, owing to its ability to non-invasively give an objective assessment of biological tissues at cellular and sub-cellular levels. In spite of recent advances in optics and the computational power, not many quantitative tissue optical sensing technologies have been translated into clinical practice. In order to translate this technology in the clinics, we need to further improve the technology. To name a few, we need accurate and rapid quantification method for a real-time diagnostic feedback. Next, we need computational methods for complex tissue-optics problems. Also, we need a novel approach in probe design for the inaccessible organs. This dissertation focuses on the development, verification and validation of theoretical (mathematical and computational) and experimental (instrumental) tool set to promote the translation of quantitative tissue optical spectroscopy into clinical diagnostic applications. For the mathematical tool, a direct-fit photon tissue interaction (DF-PTI) model that could rapidly and accurately extract the parameters associated biophysical features was developed and validated to characterize the precursor lesions of pancreatic cancer. A rapid scattering model on pancreatic tissue reflectance based on principal components analysis (PCA) results was also developed. The diagnostic capability of scattering properties obtained was demonstrated on an 18-patient data set using a rigorous statistical method, which implied the potential of reflectance spectroscopy for real-time detection of pancreatic cancer. For the computational tool, a ray-traced Monte Carlo (RTMC) simulation for the design of fluorescence spectroscopy or imaging system utilizing complex optics to probe turbid biological tissues was devised. This new method was verified computationally with epithelial tissue models and experimentally using tissue-simulating optical phantoms. For the instrumental tool, the design and development of minimally-invasive diagnostic technologies employing optoelectronic components were discussed. In this dissertation, we focused on detection of pancreatic cancer, which has the worst prognosis among other major cancers. Pancreatic tissues were employed as our model system to validate our developed tools. The developed technology and tools can be applied to a variety of other human tissue sites to help in the translation of quantitative tissue optical sensing in a clinical setting.PhDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111401/1/paulslee_1.pd

Patient-oriented simulation based on Monte Carlo algorithm by using MRI data

<p>Abstract</p> <p>Background</p> <p>Although Monte Carlo simulations of light propagation in full segmented three-dimensional MRI based anatomical models of the human head have been reported in many articles. To our knowledge, there is no patient-oriented simulation for individualized calibration with NIRS measurement. Thus, we offer an approach for brain modeling based on image segmentation process with <it>in vivo </it>MRI T1 three-dimensional image to investigate the individualized calibration for NIRS measurement with Monte Carlo simulation.</p> <p>Methods</p> <p>In this study, an individualized brain is modeled based on <it>in vivo </it>MRI 3D image as five layers structure. The behavior of photon migration was studied for this individualized brain detections based on three-dimensional time-resolved Monte Carlo algorithm. During the Monte Carlo iteration, all photon paths were traced with various source-detector separations for characterization of brain structure to provide helpful information for individualized design of NIRS system.</p> <p>Results</p> <p>Our results indicate that the patient-oriented simulation can provide significant characteristics on the optimal choice of source-detector separation within 3.3 cm of individualized design in this case. Significant distortions were observed around the cerebral cortex folding. The spatial sensitivity profile penetrated deeper to the brain in the case of expanded CSF. This finding suggests that the optical method may provide not only functional signal from brain activation but also structural information of brain atrophy with the expanded CSF layer. The proposed modeling method also provides multi-wavelength for NIRS simulation to approach the practical NIRS measurement.</p> <p>Conclusions</p> <p>In this study, the three-dimensional time-resolved brain modeling method approaches the realistic human brain that provides useful information for NIRS systematic design and calibration for individualized case with prior MRI data.</p