Despite the technological evolutions that transform the operating rooms nowadays, a major clinical need remains: surgeons need to distinguish healthy from diseased tissues while performing a procedure. Tissue status assessment procedures such as blood perfusion monitoring require objective input that can potentially be obtained with fluorescence imaging and oxygenation imaging. We developed a multimodal imaging platform for performing widefield quantitative oxygenation imaging and fluorescence imaging in a clinical environment. We demonstrate in-vivo the impact of widefield quantitative oxygenation imaging on blood perfusion assessment. Fluorescence imaging provided by the system is used in complement to confirm the outcome of oxygenation imaging.
Quantitative diffuse optical imaging has the potential to provide valuable functional information about tissue status, such as oxygen saturation or blood content to healthcare practitioners in real time. However, significant technical challenges have so far prevented such tools from being deployed in the clinic. Toward achieving this goal, prior research introduced methods based on spatial frequency domain imaging (SFDI) that allow real-time (within milliseconds) wide-field imaging of optical properties but at a single wavelength. However, for this technology to be useful to clinicians, images must be displayed in terms of metrics related to the physiological state of the tissue, hence interpretable to guide decision-making. For this purpose, recent developments introduced multispectral SFDI methods for rapid imaging of oxygenation parameters up to 16 frames per seconds (fps). We introduce real-time, wide-field, and quantitative blood parameters imaging using spatiotemporal modulation of light. Using this method, we are able to quantitatively obtain optical properties at 100 fps at two wavelengths (665 and 860 nm), and therefore oxygenation, oxyhemoglobin, and deoxyhemoglobin, using a single camera with, at most, 4.2% error in comparison with standard SFDI acquisitions.
Most surgeries are currently performed subjectively, with outcomes that are largely dependent on the experience of the surgeon. Providing objective information about tissue that need to be resected or avoided could reduce the variability in surgical outcomes. Spatial Frequency Domain Imaging (SFDI) is a novel diffuse optical imaging method that has the potential to identify tissue viability over a large field of view. In this method, a spatial sinusoidal pattern is projected onto the tissue to get the optical properties of the tissue at each pixel. More recently, Single Snapshot of Optical Properties (SSOP) hase been developed to provide such image feedback in real-time within the specific constraints of surgery. However, while SSOP has been shown to provide information about tissues at a single wavelength in real-time, during surgical applications, it is critical to obtain spectrally-resolved functional information that can be easily interpreted by the surgeons. Optical properties at multiple wavelengths are therefore needed to correlate the absorption and scattering coefficients with the tissue functional and structural information.
In this work, we propose a novel method relying on spatio-temporal modulation of light to obtain multispectral optical properties in real time. A temporal-encoding method is used to distinguish different wavelengths by modulating each wavelength at a one particular chosen frequency. The temporally-modulated light is then used to project sinusoidal patterns onto the tissues for SSOP processing. The scene is then recorded with a fast camera to get multiple information in 3 dimensions: two spatial dimensions for SSOP and the third temporal dimension for wavelength. Discrete Fourier Transform (DFT) is used to separate the modulation frequencies pixels by pixels, and each 2D image obtained for every wavelength is processed using SSOP to obtain absorption and scattering coefficients. Finally, the optical properties at each wavelength are used to provide functional and structural information about tissues. We validated this proof of concept using 2 wavelengths (665 and 860nm) during phantom measurements and in vivo by obtaining real-time oxygenation videos. This work lays the foundation for the clinical translation of real-time quantitative multispectral imaging.
KEYWORDS: Photons, Scattering, 3D modeling, Diffuse optical tomography, Sensors, Absorption, Diffusion, Finite element methods, Optical fibers, Chemical elements
We developed a time-resolved diffuse optical tomography system that enables performing noncontact 3D-DOT
measurements of irregular shapes which is appropriate for small animal imaging. To retrieve the surface mesh, a
noncontact holographic setup using a sensor and an XY optical scanning system was used. We present a noncontact
modeling approach that consists in computing the temporal intensity distribution of detected photons taking into account
the free space propagation from, and to, the fibers disposed around the studied object at some distance from its surface.
The optimization was performed once on the time-weighted moments then on some points of the temporal profiles.
This paper presents detailed computational aspects of a new 3D modeling for solving the direct problem in a no-contact
time-resolved Fluorescent Diffuse Optical Tomography (FDOT) method that rely on near-infrared scattered and
fluorescent photons to image the optical properties and distribution of fluorescent probes in small laboratory animals. An
optical scanner allowing performing in-vivo measurements in no-contact scheme was built in our laboratory and is
presented. We use the three-dimensional Finite Element Method (FEM) to solve the coupled diffusion equations of
excitation and fluorescence photons in highly scattering objects. The computed results allowed yielding photon density
maps and the temporal profiles of photons on the surface of the small animal. Our 3D modeling of propagation of
photons in the void space between the surface of the object and the detectors allows calculating the quantity of photons
reaching the optodes. Simulations were carried-out on two test objects: a resin cylinder and a mouse phantom. The
results demonstrate the potential applications of the method to pre-clinical imaging.
We describe a method to increase the speed of convergence for the simultaneous reconstruction of absorption and scattering images in Diffuse Optical Tomography (DOT). We used the diffusion approximation of the radiative transfer equation and the Finite Element Method (FEM) to solve the forward problem. The absorption and reduced scattering images are reconstructed by inverting the distribution of the moments of the time-dependent detected light flux. The inverse problem is solved with an optimization algorithm like ART or Conjugate Gradient. This ill-posed inverse problem can be simplified by using a priori knowledge of the studied objects.
In this paper, we consider that DOT is a functional imaging technique that can be complemented by an anatomical imaging technique like Magnetic Resonance Imaging (MRI). We used anatomic information obtained from MRI as prior knowledge to compute optical absorption and scattering images. In a first step, MRI segmented images were only
used to mesh our phantoms, with a finer resolution around boundaries. In a second step, we computed optical images with homogeneous properties from the segmented MRI image, in order to initialise our optimisation process. These two initialisations yield better reconstructed images. Reconstruction from simulated and experimental data will be presented.
We describe a method to increase the convergence speed for simultaneous reconstruction of absorption and scattering images in Diffuse Optical Tomography (DOT). We used the diffusion approximation of the radiative tranfer equation and the Finite Element Method (FEM) to solve the forward problem. The absorption and reduced scattering images were reconstructed by inverting the distribution of the moments of the time-dependent detected light flux. The inverse problem is solved with an optimization algorithm such as ART or Conjugate Gradient. This ill-posed inverse problem can be simplified by using a priori knowledge of the objects studied.
In this paper, we consider that DOT is a functional imaging technique that can be complemented by an anatomical imaging technique such as Magnetic Resonance Imaging (MRI). The algorithm is built as follows: the first step consists in to dividing the observed zone into regions, thanks to another imaging technique such as MRI. In practice, this allows to adapt the mesh to the internal geometry. Then, supposing that each region is homogeneous absorption- and scattering-wise, a few parameters are reconstructed with an optimization technique. With a few iterative steps, well-averaged parameters can be obtained, which could be used to initialize the first stage of a global process. This process could reconstruct smaller inhomogeneities. We compare this method with direct global reconstruction, beginning with homogeneous parameters.
Two experimental setups for time-resolved diffuse optical tomography (DOT) are described. The first involves a titanium-sapphire laser and a streak camera in a synchroscan mode. A multiple-arm light guide allows to measure simultaneously the temporal profiles of photons re-emitted at different boundary sites of the objects studied. The second one uses picosecond laser diodes and a multiple-anode micro-channel plate photomultiplier tube followed by parallel time-correlated single photon counting channels. The two instruments are described and their main specifications compared: instrument response and time resolution, sweep time, temporal stability, sensitivity and its inter-channel variation, cross-talk between adjacent channels. We will also discuss detector-specific data analysis prior to image reconstruction. Both instruments have been tested with phantoms simulating tissues and the absorption and reduced scattering images obtained have been compared.
A near-infrared optical tomograph has been developed to obtain 3-dimensional images of scattering phantoms with optical properties similar to those of biological tissues. This experimental setup uses a femtosecond laser and a synchroscan streak camera. Thanks to three stepping motors, the phantom to be imaged is scanned in a parallel-beam mode. The time resolved detection of scattered photons is performed in the transmission mode, for different phantom positions obtained by two translations and one rotation stages. Regarding the data processing, we have developed a nonlinear image reconstruction algorithm based on the Newton-Raphson iterative method. It executes absorption and scattering mapping on the basis of characteristic data extracted from the recorded temporal point spread function of light transmitted through the studied object, such as the mean flight time of photon, the related variance or the integral intensity. First, 2D images using absolute or differential imaging schemes have been obtained for different scattering cylindrical phantoms possessing one or two more absorbing and/or more scattering inclusions. Reconstructed images have been compared to simulated and expected values. The results demonstrate that this system is a reliable and valuable platform for research on time-resolved optical tomography.
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