There is a growing interest in imaging fluorescence contrast at depth within living tissues over wide fields of view and in real time. Most methods used to date to improve depth detection of fluorescence information involve acquisition of multiple images, postprocessing of the data using a light propagation model, and are capable of providing either depth-sectioned or tomographic fluorescence information. We introduce a method, termed masked detection of structured illumination, that allows the enhancement of fluorescence imaging at depth without postprocessing. This method relies on the scanning of a collimated beam onto a turbid medium and the physical masking of the point spread function on the detection arm before acquisition on a CCD camera. By preferentially collecting diffuse photons at a chosen source-detector range, this method enhances fluorescence information at depth and has the potential to form images without postprocessing and in real time.
We report the design, characterization, and validation of an optimized simultaneous color and near-infrared (NIR) fluorescence rigid endoscopic imaging system for minimally invasive surgery. This system is optimized for illumination and collection of NIR wavelengths allowing the simultaneous acquisition of both color and NIR fluorescence at frame rates higher than 6.8 fps with high sensitivity. The system employs a custom 10-mm diameter rigid endoscope optimized for NIR transmission. A dual-channel light source compatible with the constraints of an endoscope was built and includes a plasma source for white light illumination and NIR laser diodes for fluorescence excitation. A prism-based 2-CCD camera was customized for simultaneous color and NIR detection with a highly efficient filtration scheme for fluorescence imaging of both 700- and 800-nm emission dyes. The performance characterization studies indicate that the endoscope can efficiently detect fluorescence signal from both indocyanine green and methylene blue in dimethyl sulfoxide at the concentrations of 100 to 185 nM depending on the background optical properties. Finally, we performed the validation of this imaging system in vivo during a minimally invasive procedure for thoracic sentinel lymph node mapping in a porcine model.
Time-resolved imaging has been well-established as the most powerful imaging paradigm in optical tomography by providing rich information datasets for both functional and fluorescence tomography. The practical implementations of time-resolved imaging platforms however are limited by lengthy acquisition times and demand highly stable instrumentation for collection of robust datasets. In recent years, wide-field imaging strategies have been implemented for time-resolved imaging allowing a fast acquisition of spatially- and temporally- rich datasets within short acquisition times. In this work, we present wide-field illumination and processing strategies which significantly improve the signal-to-noise ratio of time-resolved measurements. First, we demonstrate the impact of temporal and photon noise on timeresolved measurements and compare the performance of various born-normalization schemes designed to improve the robustness of the time-resolved data-types used for reconstruction. Secondly, we present a de-noising algorithm design for time-gated data types which reduce errors arising due to noise and conclude with experimental validation of the approach. The adoption of these strategies alleviates some of the limitations associated with time-resolved imaging, especially when using more advanced data types such as early gates, thus allowing the wider acceptance of timeresolved methods for biomedical applications.
Current methodologies for obtaining depth-sensitive contrast information from an optically diffusive medium involve complex hardware and software implementations. In turn, such methods typically lead to long acquisition and long reconstruction times, rendering them impractical for real-time use. In this work, we report preliminary proof-of-concept for a hardware-only method capable of providing depth sensitive contrast information without requiring post acquisition image reconstruction and with rapid acquisition. This method, termed Masked Detection of Structured Illumination (MDSI), relies on physically masking, in the detection arm, the point spread function from a collimated beam illuminating a diffusive medium, to isolate the contribution of the photon path lengths of interest. By continuously scanning and integrating the obtained images, MDSI allows, for the first time, optical depth sectioning of a diffusive medium without any processing.
Lung cancer is the leading cause of cancer death in the United States, accounting for 28% of all cancer deaths. Standard of care for potentially curable lung cancer involves preoperative radiographic or invasive staging, followed by surgical resection. With recent adjuvant chemotherapy and radiation studies showing a survival advantage in nodepositive patients, it is crucial to accurately stage these patients surgically in order to identify those who may benefit. However, lymphadenectomy in lung cancer is currently performed without guidance, mainly due to the lack of tools permitting real-time, intraoperative identification of lymph nodes. In this study we report the design and validation of a novel, clinically compatible near-infrared (NIR) fluorescence thoracoscope for real-time intraoperative guidance during lymphadenectomy. A novel, NIR-compatible, clinical rigid endoscope has been designed and fabricated, and coupled to a custom source and a dual channel camera to provide simultaneous color and NIR fluorescence information to the surgeon. The device has been successfully used in conjunction with a safe, FDA-approved fluorescent tracer to detect and resect mediastinal lymph nodes during thoracic surgery on Yorkshire pigs. Taken together, this study lays the foundation for the clinical translation of endoscopic NIR fluorescence intraoperative guidance and has the potential to profoundly impact the management of lung cancer patients.
There is a pressing clinical need to provide image guidance during surgery. Currently, assessment of tissue that needs to be resected or avoided is performed subjectively, leading to a large number of failures, patient morbidity, and increased healthcare costs. Because near-infrared (NIR) optical imaging is safe, noncontact, inexpensive, and can provide relatively deep information (several mm), it offers unparalleled capabilities for providing image guidance during surgery. These capabilities are well illustrated through the clinical translation of fluorescence imaging during oncologic surgery. In this work, we introduce a novel imaging platform that combines two complementary NIR optical modalities: oxygenation imaging and fluorescence imaging. We validated this platform during facial reconstructive surgery on large animals approaching the size of humans. We demonstrate that NIR fluorescence imaging provides identification of perforator arteries, assesses arterial perfusion, and can detect thrombosis, while oxygenation imaging permits the passive monitoring of tissue vital status, as well as the detection and origin of vascular compromise simultaneously. Together, the two methods provide a comprehensive approach to identifying problems and intervening in real time during surgery before irreparable damage occurs. Taken together, this novel platform provides fully integrated and clinically friendly endogenous and exogenous NIR optical imaging for improved image-guided intervention during surgery.
Over the last few years, fluorescence imaging for biomedical applications has experienced very rapid growth. An application triggering significant interest is the use of fluorescence for image guidance during surgical interventions. A custom 15x broadband (400-900 nm) macro-zoom objective has been designed, manufactured, and tested for use in image-guided surgery that employs near-infrared (NIR) fluorescence imaging. The lens has been incorporated into the novel FLARE™ imaging system for NIR fluorescence image-guided surgery.
We describe a wide-field optical tomography technique, which allows the measurement-guided optimization of illumination patterns for enhanced reconstruction performances. The iterative optimization of the excitation pattern aims at reducing the dynamic range in photons transmitted through biological tissue. It increases the number of measurements collected with high photon counts resulting in a dataset with improved tomographic information. Herein, this imaging technique is applied to time-resolved fluorescence molecular tomography for preclinical studies. First, the merit of this approach is tested by in silico studies in a synthetic small animal model for typical illumination patterns. Second, the applicability of this approach in tomographic imaging is validated in vitro using a small animal phantom with two fluorescent capillaries occluded by a highly absorbing inclusion. The simulation study demonstrates an improvement of signal transmitted (∼2 orders of magnitude) through the central portion of the small animal model for all patterns considered. A corresponding improvement in the signal at the emission wavelength by 1.6 orders of magnitude demonstrates the applicability of this technique for fluorescence molecular tomography. The successful discrimination and localization (∼1 mm error) of the two objects with higher resolution using the optimized patterns compared with nonoptimized illumination establishes the improvement in reconstruction performance when using this technique.
Proc. SPIE. 7892, Multimodal Biomedical Imaging VI
KEYWORDS: Near infrared, Data modeling, Magnetic resonance imaging, Luminescence, Molecules, Quantum efficiency, 3D modeling, Optical tomography, Fluorescence resonance energy transfer, Animal model studies
We investigate the feasibility of 3-D localization of Foerster resonance energy transfer (FRET) between two NIR
fluorophores (Alexa Fluor 700 and Alexa Fluor 750) in small animal models. Specifically, the decrease in donor
lifetime upon FRET is used as the contrast mechanism to isolate donor-acceptor pairs undergoing FRET. The
optical tomography system uses a femtosecond tunable laser coupled with a micro-mirror device based digital
light processor as the source to generate wide-field patterns. The time-resolved detection is achieved using a gated
intensified CCD camera. The wide-field excitation scheme described herein provides an experimental advantage
by reducing the time of acquisition of temporally dense datasets. In this study, anatomical information obtained
using MR imaging is used in the computation of the Monte Carlo (MC) based forward model. The MC model
reconstructs the 3D distribution of the quantum yield of the donor fluorophore and the FRET complex using
the time-gate data type allowing the estimation of fractional distribution (D) of donor molecules undergoing
FRET and unquenched donor molecules. The performance of this approach in the estimation of D using the
position of fluorophores obtained using the MRI is investigated.
We propose the use of Time-Resolved Diffuse Optical Tomography in a multispectral scheme with anatomical constraints supplied by MR imaging to reconstruct functional parameters of the animal model with greater accuracy and resolution. The tomographic imaging system described is capable of acquiring temporal measurements
in multiple-views using a gated ICCD camera. A tunable Ti-Sapphire pulsed laser at wavelengths between 700nm - 1000nm is used as the source. Anatomical distribution is determined using MRI in a non-concurrent setting. Time-resolved measurements at multiple wavelengths in the NIR window combined with the anatomical constraints
is used to determine a 3D distribution of the functional parameters in vivo. Multispectral spectroscopy measurements on homogenous tissue simulating phantoms are used to demonstrate the accuracy of the system
in determining optical parameters in thin tissues. We show that temporal measurements combined with MRI data can be used to accurately quantify optical properties in heterogeneous tissues.
Diffuse optical tomography using perturbation Monte Carlo method can overcome the drawback inherent to the classical model based on the diffusion equation for pre-clinical applications. The combined use of information from different time gates enables image reconstruction with accurate quantification and reducing the crosstalk between the absorption and the scattering coefficients. In this work, we apply this approach to solve an inverse problem of a 3D mouse model, and investigate the benefit to incorporate the time-resolved data into the optical reconstruction for quantitative functional imaging.