Near-infrared fluorescence optical imaging and tomography

The advent of recent advances in near-infrared laser diodes and fast electro-optic detection has spawned a new research field of diagnostic spectroscopy and imaging based on targeting and reporting exogenous fluorescent agents. This review seeks to concisely address the physics, instrumentation, advancements in tomography, and near-infrared fluorescent contrast agent development that promises selective and specific molecular targeting of diseased tissues. As an example of one area of the field, recent work focusing on pharmacokinetic analysis of fluorophores targeting the epidermal growth factor receptor (EGFR) is presented in a human breast cancer xenograft mouse model to demonstrate specificity of molecularly targeted contrast agents. Finally, a critical evaluation of the limitations and the opportunities for future translation of fluorescence-enhanced optical imaging of deep tissues is presented.     

Mesh-based enhancement schemes in diffuse optical tomography

Two mesh-based methods including dual meshing and adaptive meshing are developed to improve the finite element-based reconstruction of both absorption and scattering images of heterogeneous turbid media. The idea of dual meshing scheme is to use a fine mesh for the solution of photon propagation and a coarse mesh for the inversion of optical property distributions. The adaptive meshing method is accomplished by the automatic mesh refinement in the region of heterogeneity during reconstruction. These schemes are validated using tissue-like phantom measurements. Our results demonstrate the capabilities of the dual meshing and adaptive meshing in both qualitative and quantitative improvement of optical image reconstruction.     

Image analysis methods for diffuse optical tomography

Three major analytical tools in imaging science are summarized and demonstrated relative to optical imaging in vivo. Standard resolution testing is optimal when infinite contrast is used and hardware evaluation is the goal. However, deep tissue imaging of absorption or fluorescent contrast agents in vivo often presents a different problem, which requires contrast-detail analysis. This analysis shows that the minimum detectable sizes are in the range of 1/10 the outer diameter, whereas minimum detectable contrast values are in the range of 10 to 20% relative to the continuous background values. This is estimated for objects being in the center of the domain being imaged, and as the heterogeneous region becomes closer to the surface, the lower limit on size and contrast can become arbitrarily low and more dictated by hardware specifications. Finally, if human observer detection of abnormalities in the images is the goal, as is standard in most radiological practice, receiver operating characteristic (ROC) curve and location receiver operating characteristic curve (LROC) are used. Each of these three major areas of image interpretation and analysis are reviewed in the context of medical imaging as well as how they are used to quantify the performance of diffuse optical imaging of tissue.     

Fundamental study on diffuse reflective optical tomography

We report a simulation study on diffuse reflective optical computed tomography, in which continuous-wave sources and detectors are placed on the plane surface of a semi-infinite body. We adopted a simple Tikhonov regularization in the inverse problem and demonstrated the feasibility of three-dimensional reconstruction of the absorption coefficient change. The spatial resolution of the reconstructed image was shown to be degrading markedly with the depth. The regularization parameter should be chosen appropriately considering the trade-off between the reconstructed image noise and the spatial resolution. We analysed the dependence of the spatial resolution of the reconstructed image on the regularization parameter and the depth, and also the behaviour of the reconstructed image noise on the regularization parameter and the depth.     

Three-dimensional diffuse optical tomography of bones and joints

We present for the first time full three-dimensional (3D) volumetric reconstruction of absorption images of in vitro and in vivo bones and joints from near-infrared tomographic measurements. Imaging experiments were conducted on human finger and chicken bones embedded in cylindrical scattering media using a Clemson multichannel diffuse optical imager. The volumetric optical images were recovered with our 3D finite element based reconstruction algorithm. Our results show that 3D imaging methods can provide details of the joint structure/composition that would be impossible from two-dimensional imaging methods.     

Contrast-detail analysis characterizing diffuse optical fluorescence tomography image reconstruction

Contrast-detail analysis is used to evaluate the imaging performance of diffuse optical fluorescence tomography (DOFT), characterizing spatial resolution limits, signal-to-noise limits, and the trade-off between object contrast and size. Reconstructed images of fluorescence yield from simulated noisy data were used to determine the contrast-to-noise ratio (CNR). A threshold of CNR=3 was used to approximate a lowest acceptable noise level in the image, as a surrogate measure for human detection of objects. For objects 0.5 cm inside the edge of a simulated tissue region, the smallest diameter that met this criteria was approximately 1.7 mm, regardless of contrast level, and test field diameter had little impact on this limit. Object depth had substantial impact on object CNR, leading to a limit of 4 mm for objects near the center of a 51-mm test field and 8.5 mm for an 86-mm test field. Similarly, large objects near the edge of both test fields required a minimum contrast of 50% to achieve acceptable image CNR. The minimum contrast for large, centered objects ranged between 50% and 100%. Contrast-detail analysis using human detection of lower contrast limits provides fundamentally important information about the performance of reconstruction algorithms, and can be used to compare imaging performance of different systems.     

A soft deformable tissue-equivalent phantom for diffuse optical tomography

A recipe is presented for the manufacture of highly compressible phantoms for diffuse optical tomography. The recipe is based on polyvinyl alcohol (PVA) slime, a viscoelastic fluid which readily deforms under moderate pressure. Scattering particles and absorbing compounds can be added to provide a uniform material with stable and reproducible optical properties. A linear relationship between the concentration of scattering particles (either titanium dioxide or microspheres) and the transport scatter coefficient is demonstrated. Phantoms of an arbitrary size and shape may be produced by containing the slime within a thin latex shell, and a stability over a period of at least 3 months has been established. The deformable phantoms may be used to test and calibrate optical tomography systems designed for use on patients with irregular or variable geometries.     

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.     

Improved quantification of small objects in near-infrared diffuse optical tomography

Diffuse optical tomography allows quantification of hemoglobin, oxygen saturation, and water in tissue, and the fidelity in this quantification is dependent on the accuracy of optical properties determined during image reconstruction. In this study, a three-step algorithm is proposed and validated that uses the standard Newton minimization with Levenberg-Marquardt regularization as the first step. The second step is a modification to the existing algorithm using a two-parameter regularization to allow lower damping in a region of interest as compared to background. This second stage allows the recovery of the actual size of an inclusion. A region-based reconstruction is the final third step, which uses the estimated size and position information from step 2 to yield quantitatively accurate average values for the optical parameters. The algorithm is tested on simulated and experimental data and is found to be insensitive to object contrast and position. The percentage error between the true and the average recovered value for the absorption coefficient in test images is reduced from 47 to 27% for a 10-mm inclusion, from 38 to 13% for a 15-mm anomaly, and from 28 to 5.5% for a 20-mm heterogeneity. Simulated data with absorbing and scattering heterogeneities of 15 mm diam located in different positions show recovery with less than 15% error in absorption and 6% error in reduced scattering coefficients. The algorithm is successfully applied to clinical data from a subject with a breast abnormality to yield quantitatively increased absorption coefficients, which enhances the contrast to 3.8 compared to 1.23 previously.     

A haemodynamic response function model in spatio-temporal diffuse optical tomography

Diffuse optical tomography (DOT) is a new and effective technique for functional brain imaging. It can detect local changes in both oxygenated and deoxygenated haemoglobin concentrations in tissue based on differential absorption at multiple wavelengths. Traditional methods in spatio-temporal analysis of haemoglobin concentrations in diffuse optical tomography first reconstruct the spatial distribution at different time instants independently, then look at the temporal dynamics on each pixel, without incorporating any temporal information as a prior in the image reconstruction. In this work, we present a temporal haemodynamic response function model described by a basis function expansion, in a joint spatio-temporal DOT reconstruction of haemoglobin concentration changes during simulated brain activation. In this joint framework, we simultaneously employ spatial regularization, spectral information and temporal assumptions. We also present an efficient algorithm for solving the associated large-scale systems. The expected improvements in spatial resolution and contrast-to-noise ratio are illustrated with simulations of human brain activation.     

Experimental measurement of time-dependent photon scatter for diffuse optical tomography

Time-resolved measurement of early arriving photons through diffusive media has been shown to effectively reduce the high degree of light scatter in biological tissue. However, the experimentally achievable reduction in photon scatter and the impact of time-gated detection on instrument noise performance is not well understood. We measure time-dependent photon density sensitivity functions (PDSFs) between a pulsed laser source and a photomultiplier tube operating in time-correlated single-photon-counting mode. Our data show that with our system, measurement of early arriving photons reduces the full width half maximum of PDSFs on average by about 40 to 60% versus quasicontinuous wave photons over a range of experimental conditions similar to those encountered in small animal tomography, corresponding to a 64 to 84% reduction in PDSF volume. Factoring in noise considerations, the optimal operating point of our instrument is determined to be about the 10% point on the rising edge of the transmitted intensity curve. Time-dependent Monte Carlo simulations and the time-resolved diffusion approximation are used to model photon propagation and are evaluated for agreement with experimental data.     

In vivo mice lung tumor follow-up with fluorescence diffuse optical tomography

We present in vivo experiments conducted with a new fluorescence diffuse optical tomographic (fDOT) system on cancerous mice bearing mammary murine tumors. We first briefly present this new system that has been developed and its associated reconstruction method. Its main specificity is its ability to reconstruct the fluorescence yield even in heterogeneous and highly attenuating body regions such as lungs and to enable mouse inspection without immersion in optical index matching liquid (Intralipid and ink). Some phantom experiments validate the performance of this new system for heterogeneous media inspection. Its use for a mice study is then related. It consists in the follow-up of the lungs at different stages of tumor development after injection of RAFT-(cRGD)4-Alexa700. As expected, the reconstructed fluorescence increases along with the tumor stage. These results validate the use of our system for biological studies of small animals.     

Monitoring early tumor response to drug therapy with diffuse optical tomography

Although anti-angiogenic agents have shown promise as cancer therapeutics, their efficacy varies between tumor types and individual patients. Providing patient-specific metrics through rapid noninvasive imaging can help tailor drug treatment by optimizing dosages, timing of drug cycles, and duration of therapy-thereby reducing toxicity and cost and improving patient outcome. Diffuse optical tomography (DOT) is a noninvasive three-dimensional imaging modality that has been shown to capture physiologic changes in tumors through visualization of oxygenated, deoxygenated, and total hemoglobin concentrations, using non-ionizing radiation with near-infrared light. We employed a small animal model to ascertain if tumor response to bevacizumab (BV), an anti-angiogenic agent that targets vascular endothelial growth factor (VEGF), could be detected at early time points using DOT. We detected a significant decrease in total hemoglobin levels as soon as one day after BV treatment in responder xenograft tumors (SK-NEP-1), but not in SK-NEP-1 control tumors or in non-responder control or BV-treated NGP tumors. These results are confirmed by magnetic resonance imaging T2 relaxometry and lectin perfusion studies. Noninvasive DOT imaging may allow for earlier and more effective control of anti-angiogenic therapy.     

Design and implementation of a multifrequency near-infrared diffuse optical tomography system

The design and implementation of a multifrequency and multispectral diffuse optical tomography system is described. Four wavelengths are utilized: 665, 785, 808, and 830 nm. The system is based on a network analyzer, which provides rf modulation signals for the laser diodes, as well as measures the amplitude and the phase of the detected signals. Six different modulation frequencies ranging from 110 to 280 MHz are used. The details of instrumentation, calibration, data acquisition, and performance of the system are given. 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. Data acquisition for one wavelength is completed in less than 2.5 min for a single modulation frequency. The measurement repeatability is 0.5% in ac intensity and 0.2 deg in phase. The performance of the system is evaluated with phantom studies. A multifrequency reconstruction algorithm is used, in which a single absorption and scattering image pair is obtained using the whole dataset obtained at different modulation frequencies. It is shown that the multifrequency reconstruction approach provides superior image quality compared to the single frequency counterpart.     

Projection access order in algebraic reconstruction technique for diffuse optical tomography

Algebraic reconstruction technique (ART) is one of the popular image reconstruction techniques used in diffuse optical tomography (DOT). We investigate in this note the influence of the order in which data are accessed in ART. Simulations mimicking breast tissues in transmission geometry with contrast agent tumour enhancement were used to evaluate the image quality of the diverse projection access investigated. We show that by selecting proper projection access order, the convergence speed can be significantly improved when ART is used to perform DOT. Moreover, low-contrast detection is improved.     

Comparison of diffuse optical tomography of human breast with whole-body and breast-only positron emission tomography

We acquire and compare three-dimensional tomographic breast images of three females with suspicious masses using diffuse optical tomography (DOT) and positron emission tomography (PET). Co-registration of DOT and PET images was facilitated by a mutual information maximization algorithm. We also compared DOT and whole-body PET images of 14 patients with breast abnormalities. Positive correlations were found between total hemoglobin concentration and tissue scattering measured by DOT, and fluorodeoxyglucose (18F-FDG) uptake. In light of these observations, we suggest potential benefits of combining both PET and DOT for characterization of breast lesions.     

Target detection and quantification using a hybrid hand-held diffuse optical tomography and photoacoustic tomography system

We present a photoacoustic tomography-guided diffuse optical tomography approach using a hand-held probe for detection and characterization of deeply-seated targets embedded in a turbid medium. Diffuse optical tomography guided by coregistered ultrasound, MRI, and x ray has demonstrated a great clinical potential to overcome lesion location uncertainty and to improve light quantification accuracy. However, due to the different contrast mechanisms, some lesions may not be detectable by a nonoptical modality but yet have high optical contrast. Photoacoustic tomography utilizes a short-pulsed laser beam to diffusively penetrate into tissue. Upon absorption of the light by the target, photoacoustic waves are generated and used to reconstruct, at ultrasound resolution, the optical absorption distribution that reveals optical contrast. However, the robustness of optical property quantification of targets by photoacoustic tomography is complicated because of the wide range of ultrasound transducer sensitivity, the orientation and shape of the targets relative to the ultrasound array, and the uniformity of the laser beam. We show in this paper that the relative optical absorption map provided by photoacoustic tomography can potentially guide the diffuse optical tomography to accurately reconstruct target absorption maps.     

Depth-correction algorithm that improves optical quantification of large breast lesions imaged by diffuse optical tomography

Optical quantification of large lesions imaged with diffuse optical tomography in reflection geometry is depth dependence due to the exponential decay of photon density waves. We introduce a depth-correction method that incorporates the target depth information provided by coregistered ultrasound. It is based on balancing the weight matrix, using the maximum singular values of the target layers in depth without changing the forward model. The performance of the method is evaluated using phantom targets and 10 clinical cases of larger malignant and benign lesions. The results for the homogenous targets demonstrate that the location error of the reconstructed maximum absorption coefficient is reduced to the range of the reconstruction mesh size for phantom targets. Furthermore, the uniformity of absorption distribution inside the lesions improve about two times and the median of the absorption increases from 60 to 85% of its maximum compared to no depth correction. In addition, nonhomogenous phantoms are characterized more accurately. Clinical examples show a similar trend as the phantom results and demonstrate the utility of the correction method for improving lesion quantification.