Frequency-domain Diffuse Optical Tomography Research Articles

Deep learning-enabled high-speed, multi-parameter diffuse optical tomography.

Frequency-domain diffuse optical tomography (FD-DOT) could enhance clinical breast tumor characterization. However, conventional diffuse optical tomography (DOT) image reconstruction algorithms require case-by-case expert tuning and are too computationally intensive to provide feedback during a scan. Deep learning (DL) algorithms front-load computational and tuning costs, enabling high-speed, high-fidelity FD-DOT. We aim to demonstrate a simultaneous reconstruction of three-dimensional absorption and reduced scattering coefficients using DL-FD-DOT, with a view toward real-time imaging with a handheld probe. A DL model was trained to solve the DOT inverse problem using a realistically simulated FD-DOT dataset emulating a handheld probe for human breast imaging and tested using both synthetic and experimental data. Over a test set of 300 simulated tissue phantoms for absorption and scattering reconstructions, the DL-DOT model reduced the root mean square error by and , increased the spatial similarity by and , increased the anomaly contrast accuracy by ( ), and reduced the crosstalk by and , respectively, compared with model-based tomography. The average reconstruction time was reduced from 3.8min to 0.02s for a single reconstruction. The model was successfully verified using two tumor-emulating optical phantoms. There is clinical potential for real-time functional imaging of human breast tissue using DL and FD-DOT.

Computationally-efficient linear scheme for overlap time-gating spatial frequency domain diffuse optical tomography using an analytical diffusion model.

Time-domain (TD) spatial frequency domain (SFD) diffuse optical tomography (DOT) potentially enables laminar tomography of both the absorption and scattering coefficients. Its full time-resolved-data scheme is expected to enhance performances of the image reconstruction but poses heavy computational costs and also susceptible signal-to-noise ratio (SNR) limits, as compared to the featured-data one. We herein propose a computationally-efficient linear scheme of TD-SFD-DOT, where an analytical solution to the TD phasor diffusion equation for semi-infinite geometry is derived and used to formulate the Jacobian matrices with regard to overlap time-gating data of the time-resolved measurement for improved SNR and reduced redundancy. For better contrasting the absorption and scattering and widely adapted to practically-available resources, we develop an algebraic-reconstruction-technique-based two-step linear inversion procedure with support of a balanced memory-speed strategy and multi-core parallel computation. Both simulations and phantom experiments are performed to validate the effectiveness of the proposed TD-SFD-DOT method and show an achieved tomographic reconstruction at a relative depth resolution of ∼4 mm.

Co-registered speckle contrast optical tomography and frequency domain-diffuse optical tomography for imaging of the fifth metatarsal.

A co-registered speckle contrast optical tomography and frequency domain-diffuse optical tomography system has been designed for imaging total hemoglobin concentration, blood oxygenation, and blood flow with the future aim of monitoring Jones fractures of the fifth metatarsal. Experimental validation was performed using both in vitro tissue-mimicking phantoms and in vivo cuff occlusion experiments. Results of these tissue phantom experiments ensure accurate recovery of three-dimensional distributions of optical properties and flow. Finally, cuff occlusion experiments performed on one healthy human subject demonstrate the system's ability to recover both decreasing tissue oxygenation and blood flow as caused by an arterial occlusion.

Improving image quality in diffuse optical tomography

Diffuse optical tomography (DOT) modality uses diffusion equation solution of low power laser distribution in the imaging tissue. DOT method has three main running mode and three geometric subbranches. Run modes are: Continuous Wave (CW), Time Resolved (TR) and Frequency Domain (FD) modes. These run modes might have transmission-through, back-reflected or ring geometry depend on the source and detector placements on tissue surface. In this work, we tested our novel imaging method on the frequency-domain back-reflected DOT simulation model. Our novelty is: selecting a great number of multi-frequency data in the wide frequency spectrum which was not tested before in the literature. Most of the literature works consist of narrow frequency band with the limited number of frequencies such as maximum 12 multi-frequency-data which cover from 100 up to 700 MHz. In our work, we tested and compared reconstructed inclusion images generated by our 500 wide spectrum multi-frequency data versus reconstructed inclusion images generated by 20 narrow band multi-frequency data which was generally used in FD DOT studies. We observed that our novel imaging method which used wide spectrum multi-frequency data is superior to the traditionally used narrow-band multi-frequency method based on the reconstructed inclusion image localization errors. Since most of the homogenous geometry consists of fat tissue, we selected background absorption coefficient µa = 0.2 cm−1 and tissue scattering coefficient $${\upmu }$$ s = 80 cm−1 for 800 nm laser source wavelength. Three-dimensional cubic imaging simulation media has 75-mm grid sizes in each direction. Two different imaging scenarios were tested. In the first scenario, one inclusion with absorption coefficient µa = 0.7 cm−1 was put inside the three-dimensional imaging geometry at 27 mm depth. In the second scenario one inclusion with absorption coefficient µa = 0.7 cm−1 was embedded in 48 mm depth location. Inclusions are cubic and they have 6 mm xyz length at each direction.

Imaging affective and non-affective touch processing in two-year-old children

Touch is an important component of early parent-child interaction and plays a critical role in the socio-emotional development of children. However, there are limited studies on touch processing amongst children in the age range from one to three years. The present study used frequency-domain diffuse optical tomography (DOT) to investigate the processing of affective and non-affective touch over left frontotemporal brain areas contralateral to the stimulated forearm in two-year-old children. Affective touch was administered by a single stroke with a soft brush over the child's right dorsal forearm at 3 cm/s, while non-affective touch was provided by multiple brush strokes at 30 cm/s. We found that in the insula, the total haemoglobin (HbT) response to slow brushing was significantly greater than the response to fast brushing (slow > fast). Additionally, a region in the postcentral gyrus, Rolandic operculum and superior temporal gyrus exhibited greater response to fast brushing than slow brushing (fast > slow). These findings confirm that an adult-like pattern of haemodynamic responses to affective and non-affective touch can be recorded in two-year-old subjects using DOT. To improve the accuracy of modelling light transport in the two-year-old subjects, we used a published age-appropriate atlas and deformed it to match the exterior shape of each subject's head. We estimated the combined scalp and skull, and grey matter (GM) optical properties by fitting simulated data to calibrated and coupling error corrected phase and amplitude measurements. By utilizing a two-compartment cerebrospinal fluid (CSF) model, the accuracy of estimation of GM optical properties and the localization of activation in the insula was improved. The techniques presented in this paper can be used to study neural development of children at different ages and illustrate that the technology is well-tolerated by most two-year-old children and not excessively sensitive to subject movement. The study points the way towards exciting possibilities in functional imaging of deeper functional areas near sulci in small children.

Frequency shifting model for diffuse optical tomography

The Diffuse Optical Tomography (DOT) imaging modality is an interesting research field for researchers since it has uncertainties in the solution space. DOT imaging modality is an unsolved scientific problem. Inverse problem solution and image reconstruction have never been of their best quality. Reconstructed images have low spatial resolution. The scattering nature of low-energized diffusive light is the obscuring effect for DOT modality. DOT has 3 functional sub-branches which are Continuous Wave, Time-Resolved, and Frequency-Domain. In this work, one new approach to Frequency Domain Diffuse Optical Tomography (FDDOT) biomedical optic imaging modality is presented to the readers. Frequency shifting data were added to the forward model problem which has source-detector couplings and several imaging voxels. 100 MHz center core light modulation frequency was selected as modulation frequency. 169 source-detector matches were used on back-reflected imaging geometry. Absorption coefficient µa was selected 0.1 cm−1. Scattering coefficient µs was selected 100 cm−1. 1-µm x, y, z cartesian grid coordinates were used in each direction for imaging tissue-like simulation media. A total of 100 frequency shifts were added to the forward model problem which has 5 Hz frequency step. 2 inclusion objects were embedded inside the imaging simulation phantom to be reconstructed. Their optical absorption coefficient µa = 0.7 cm−1. Two inclusion images were successfully reconstructed with the low contrast to noise ratio (CNR) and position error. The frequency shifting technique is first applied for FDDOT here in this work. This technique increased the total number of equations in the forward model problem; hence it is helping to solve the inverse problem more accurately. In this work, the positive effect of using frequency shifting methodology was observed. Differentiation of 2 embedded inclusions was completed and illustrated in this work. Two different scenarios were compared with each other. In the first scenario, only 100 MHz center core frequency was used for one source-detector match. In the second scenario, 100 additional shifted frequencies over 100 MHz center core frequency were added. It was seen that the second scenario which has more frequency shifts is superior to the general concept FDDOT methodology. This work shows that the frequency shift technique might be used for future FDDOT devices.

Photon phase shift imaging research on frequency domain diffuse optic tomography

Diffuse optic imaging is an important biomedical optic research tool. Diffuse optic tomography (DOT) modality needs progressive philosophical approaches for scientific contribution. Technological developments and philosophical approaches should both go forward. Phase-shift based frequency domain diffuse optical tomography (FDDOT) method was well established in the literature. The instruments were tested for brain neurofunctional imaging. A mixture of AC laser intensity and phase data were used at these works. According to those works, deep tissue resolution was improved by only using phase data. Because phase data is only related to the photon mean free path in imaging tissue media. Besides this advantage, laser intensity data is also affected by noisy background light and electrical artifacts. Another most important advantage of only using phase data can be explained as time-resolved temporal change which can be directly related to the phase shift of modulated frequency source. In this work, the FDDOT imaging method which uses phase shift data were tested for simulation. Laser source-driven forward model problem weight matrix simulation data was given to the simple pseudo-inverse-based inverse problem solution algorithm for one inclusion example. The inclusion image was reconstructed and demonstrated successfully. Forward model problem weight functions inside the tissue simulation media were calculated and used based on the phase shifts at the same core modulation frequency. 100 MHz modulation frequency was selected due to its FDDOT standard. 13 sources and 13 detectors were placed on the back-reflected imaging surface. 40 x, y, z cartesian coordinate grid elements were used in the image reconstruction algorithm. Photon absorption coefficient: μa = 0.1 cm−1, and scattering coefficient: μs = 100 cm−1 values were set for simulation background. One inclusion object was embedded inside the background imaging tissue simulation environment. x, y, z cartesian coordinate grid sizes were selected for 1 μm for each direction. Photon phase shift fluencies were added to the forward model problem. The forward model problem was built according to the frequency domain photon migration diffusion equation (DE) approximation. The pseudoinverse mathematical inverse problem solution function was applied to test the results. The embedded inclusion object was reconstructed successfully with the high-resolution image quality. The philosophical approach has future promising DOT imaging capability. The phase shift version of the FDDOT modality has an important advantage for future purposes.

Signal regression in frequency-domain diffuse optical tomography to remove superficial signal contamination

.Significance: Signal contamination is a major hurdle in functional near-infrared spectroscopy (fNIRS) of the human head as the NIR signal is contaminated with the changes corresponding to superficial tissue, therefore occluding the functional information originating from the cerebral region. For continuous wave, this is generally handled through linear regression of the shortest source-detector (SD) distance intensity measurement from all of the signals. Although phase measurements utilizing frequency domain (FD) provide deeper tissue sampling, the use of the shortest SD distance phase measurement for regression of superficial signal contamination can lead to misleading results, therefore suppressing cortical signals.Aim: An approach for FD fNIRS that utilizes a short-separation intensity signal directly to regress both intensity and phase measurements, providing a better regression of superficial signal contamination from both data-types, is proposed.Approach: Simulated data from realistic models of the human head are used, and signal regression using both intensity and phase-based components of the FD fNIRS is evaluated.Results: Intensity-based phase regression achieves a suppression of superficial signal contamination by 68% whereas phase-based phase regression is only by 13%. Phase-based phase regression is also shown to generate false-positive signals from the cortex, which are not desirable.Conclusions: Intensity-based phase regression provides a better methodology for minimizing superficial signal contamination in FD fNIRS.

Computational image reconstruction for multi-frequency diffuse optical tomography

Diffuse optical tomography (DOT) is promising to investigate functional and structural information in biological tissue by involving the forward problem and inverse solution. The work within this study develops an image reconstruction algorithm based on frequency-domain DOT using multi-frequency. In the forward problem, numerical simulation performs a diffusion equation to compute the light radiance distribution inside the model geometry with the assumed light intensity and optical properties. While in inverse solution, the absorption and reduced scattering coefficients are reconstructed utilizing light boundary data. To test the algorithm, several simulation cases, such as different contrast ratios between background and inclusion, inclusion size, as well as single and multi-frequency using one to three frequencies each and simultaneously are implemented. For verifying the image reconstruction results of multi-frequency, an objective numerical assessment, namely contrast and size detail is applied with a threshold value to specify the visible inclusion inside the geometry. Reconstructed images indicate that the effectivity of two frequencies in multi-frequency with 100 and 150 MHz has similar results as in single-frequency with 200 MHz. Therefore, the more number of frequencies may not enhance the contrast and image quality.

Multi-wavelength spatial frequency domain diffuse optical tomography using single-pixel imaging based on lock-in photon counting.

We present a spatial frequency domain (SFD) diffuse optical tomography for simultaneous acquisition of multi-wavelength tomographic images of turbid media. We propose a highly sensitive single-pixel SFD imaging system for simultaneously collecting multi-wavelength spatially modulated reflectance images, instead of using the expensive electron-multiplying charge-coupled device camera that requires switching between the multi-wavelength collections. The single-pixel SFD imaging system using three low-power light sources (455, 532 and 660 nm) that were intensity-modulated by square waves with three different frequencies for frequency encoding, and all the light sources were focused onto one digital micromirror device (DMD) for generating wide-field sinusoidal illumination patterns. Reflected light from the surface of the turbid media was modulated by the other DMD with many sampling patterns before being spatially integrated. Spatially integrated light signals were frequency decoded with a novel highly sensitive lock-in photon counting detection, then multi-wavelength spatially modulated reflectance images were recovered with the single-pixel imaging (SPI) method. We incorporated the two-dimensional discrete cosine transform (DCT) into the SPI method to reduce the number of sampling patterns, and, thereby, the proposed DCT-SPI scheme achieved a fast acquisition of SFD reflectance images that is desired for a dynamic SFD imaging application. Direct current (DC) and alternating current (AC) amplitudes at all the locations on the media surface were extracted from the recovered images. Multi-wavelength tomographic images were reconstructed with an inversion algorithm based on the first-order Rytov approximation of the diffusion equation, using both the extracted DC and AC amplitudes. We performed experiments using a series of tissue simulating phantoms to verify the performances of the proposed approach and compared the experimental results with those using a conventional camera-based SFD imaging system. The results demonstrate that our DCT-SPI based SFD-DOT approach is well suited for simultaneous reconstruction of multi-wavelength tomographic images to pave the way for many SFD imaging applications.

Nondestructive detection of underlying moldy lesions of apple using frequency domain diffuse optical tomography

Nondestructive tomographic identification of underlying moldy lesions of apple is demonstrated experimentally, for the first time, by using frequency domain diffuse optical tomography (FD-DOT). The custom applicator-probe had 18 optodes distributed on a spheroid apple-size imaging domain. The 12 source channels were time-multiplexed to a laser source modulated at 110 MHz, and the 6 detector channels were individually conditioned for parallel heterodyning at 10 kHz. The iterative image reconstruction was performed without priors in an open-source finite-element-method (FEM) package with custom meshing of the imaging domain. Cylindrical moldy lesions in apple at controlled center depths ranging from 10 mm to 35 mm were established using 10 mm diameter cylinder inclusions harvested from mildew flesh, and freeform lesions in apple were developed by injecting colonies of Alternaria alternate. The moldy lesions not deeper than 20 mm from the peel were resolvable on the absorption images. The moldy lesions were unremarkable on the reduced scattering images. Contrast-detail-analysis is also performed in simulation to assess the condition of identifying a moldy-core lesion by FD-DOT.

Image reconstruction for frequency-domain diffuse optical tomography

Image reconstruction for frequency-domain diffuse optical tomography

Indocyanine green enhanced co-registered diffuse optical tomography and photoacoustic tomography

To overcome the intensive light scattering in biological tissue, diffuse optical tomography (DOT) in the near-infrared range for breast lesion detection is usually combined with other imaging modalities, such as ultrasound, x-ray, and magnetic resonance imaging, to provide guidance. However, these guiding imaging modalities may depend on different contrast mechanisms compared to the optical contrast in the DOT. As a result, they cannot provide reliable guidance for DOT because some lesions may not be detectable by a nonoptical modality but may have a high optical contrast. An imaging modality that relies on optical contrast to provide guidance is desirable for DOT. We present a system that combines a frequency-domain DOT and real-time photoacoustic tomography (PAT) systems to detect and characterize deeply seated targets embedded in a turbid medium. To further improve the contrast, the exogenous contrast agent, indocyanine green (ICG), is used. Our experimental results show that the combined system can detect a tumor-mimicking phantom, which is immersed in intralipid solution with the concentrations ranging from 100 to 10 μM and with the dimensions of 0.8 cm × 0.8 cm × 0.6 cm, up to 2.5 cm in depth. Mice experiments also confirmed that the combined system can detect tumors and monitor the ICG uptake and washout in the tumor region. This method can potentially improve the accuracy to detect small breast lesions as well as lesions that are sensitive to background tissue changes, such as the lesions located just above the chest wall.

Implementation of edge-preserving regularization for frequency-domain diffuse optical tomography

In this study, we first propose the use of edge-preserving regularization in optimizing an ill-conditioned problem in the reconstruction procedure for diffuse optical tomography to prevent unwanted edge smoothing, which usually degrades the attributes of images for distinguishing tumors from background tissues when using Tikhonov regularization. In the edge-preserving regularization method presented here, a potential function with edge-preserving properties is introduced as a regularized term in an objective function. With the minimization of this proposed objective function, an iterative method to solve this optimization problem is presented in which half-quadratic regularization is introduced to simplify the minimization task. Both numerical and experimental data are employed to justify the proposed technique. The reconstruction results indicate that edge-preserving regularization provides a superior performance over Tikhonov regularization.

Lock-in 증폭기를 채용한 주파수영역 확산 광단층촬영 시스템

In this paper, we developed a frequency-domain diffuse optical tomography(DOT) system for non-invasively imaging in vivo. The system uses near-infrared(NIR) light sources and detectors for which the photon propagation in human tissue is dominated by scattering rather than by absorption. We present the experimental reconstruction images of absorption and scattering coefficients using a liquid tissue phantom, and we obtain the location and shape of an anomaly which has different optical properties than the phantom.

Reduction of image artifacts induced by change in the optode coupling in time-resolved diffuse optical tomography

Tomographic images of the optical properties can be reconstructed using inversion algorithms for diffuse optical tomography (DOT); however, changes in the optode coupling that occurs while obtaining an object's measurements may often lead to the presence of artifacts in the reconstructed images. To reduce the number of artifacts induced by optode coupling, previous studies have introduced (unknown) coupling coefficients in reconstruction algorithms, which were found to be effective for continuous wave- and frequency-domain DOT. This study aims to investigate the effects of optode calibration on the reconstructed images of time-domain DOT. Here, coupling coefficients are incorporated into the time-domain DOT algorithm based on a modified generalized pulse spectrum technique. The images of the absorption coefficient are reconstructed in various numerical simulations, phantom experiments, and in vivo experiments of time-domain DOT. As a result, the artifacts resulting from changes in optode coupling are reduced in the reconstructed images of the absorption coefficient, thereby demonstrating that introduction of coupling coefficients is effective in time-domain DOT. Moreover, numerical simulations, phantom experiments, and in vivo studies have validated this algorithm.

Near Infrared Diffuse Optical Tomography: Improving the Quality of Care in Chronic Wounds of Patients With Diabetes

A frequency domain diffuse optical tomography instrument operating in the Near Infrared region (680-830nm) has been designed and used to monitor healing in diabetic wounds in a rat animal model. Instrument design and calibration are described and preliminary data of the in vivo experiment are reported. Excellent discrimination capability between the control and the diabetic population is possible, while the time course of impaired healing in diabetic animals appears to have different optical coefficients from the normal healing in the control group.

Combined Diffuse Optical Tomography (DOT) and MRI System for Cancer Imaging in Small Animals

Recently, there has been a great amount of interest in developing multi-modality imaging techniques for oncologic research and clinical studies with the aim of obtaining complementary information and, thus, improving the detection and characterization of tumors. In this present work, the details of a combined MR-diffuse optical imaging system for dual-modality imaging of small animals are given. As a part of this effort, a multi-spectral frequency domain diffuse optical tomography system is integrated with an MRI system. Here, a network analyzer provides the rf modulation signal for the laser diodes and measures the amplitude and the phase of the detected signals. Photomultiplier tubes are utilized to measure low-level signals. The integration of this optical imaging system with the 4T MRI system is realized by incorporating a fiber adaptive interface inside the MR magnet. Coregistration is achieved by a special probe design utilizing fiducial markers. A finite element algorithm is used to solve the diffusion equation and an inverse solver based on this forward solver is implemented to calculate the absorption and scattering maps from the acquired data. The MR a priori information is used to guide the optical reconstruction algorithm. Phantom studies show that the absorption coefficient of a 7 mm inclusion in an irregular object located in 64 mm phantom is recovered with 11% error when MR a priori information is used. ENU induced tumor model is used to test the performance of the system in vivo.

Gauss–Newton method for image reconstruction in diffuse optical tomography

We present a regularized Gauss–Newton method for solving the inverse problem of parameter reconstruction from boundary data in frequency-domain diffuse optical tomography. To avoid the explicit formation and inversion of the Hessian which is often prohibitively expensive in terms of memory resources and runtime for large-scale problems, we propose to solve the normal equation at each Newton step by means of an iterative Krylov method, which accesses the Hessian only in the form of matrix–vector products. This allows us to represent the Hessian implicitly by the Jacobian and regularization term. Further we introduce transformation strategies for data and parameter space to improve the reconstruction performance. We present simultaneous reconstructions of absorption and scattering distributions using this method for a simulated test case and experimental phantom data.

Instrumentation and design of a frequency-domain diffuse optical tomography imager for breast cancer detection

The instrument development and design of a prototype frequency-domain optical imaging device for breast cancer detection is described in detail. This device employs radio-frequency intensity modulated near-infrared light to image quantitatively both the scattering and absorption coefficients of tissue. The functioning components of the system include a laser diode and a photomultiplier tube, which are multiplexed automatically through 32 large core fiber optic bundles using high precision linear translation stages. Image reconstruction is based on a finite element solution of the diffusion equation. This tool for solving the forward problem of photon migration is coupled to an iterative optical property estimation algorithm, which uses a Levenberg-Marquardt routine with total variation minimization. The result of this development is an automated frequency-domain optical imager for computed tomography which produces quantitatively accurate images of the test phantoms used to date. This paper is a description and characterization of an automated frequency-domain computed tomography scanner, which is more quantitative than earlier systems used in diaphanography because of the combination of intensity modulated signal detection and iterative image reconstruction.