Characterizing Accuracy of Total Hemoglobin Recovery Using Contrast-Detail Analysis in 3D Image-Guided Near Infrared Spectroscopy with the Boundary Element Method

The quantification of total hemoglobin concentration (HbT) obtained from multi-modality image-guided near infrared spectroscopy (IG-NIRS) was characterized using the boundary element method (BEM) for 3D image reconstruction. Multi-modality IG-NIRS systems use a priori information to guide the reconstruction process. While this has been shown to improve resolution, the effect on quantitative accuracy is unclear. Here, through systematic contrast-detail analysis, the fidelity of IG-NIRS in quantifying HbT was examined using 3D simulations. These simulations show that HbT could be recovered for medium sized (20mm in 100mm total diameter) spherical inclusions with an average error of 15%, for the physiologically relevant situation of 2:1 or higher contrast between background and inclusion. Using partial 3D volume meshes to reduce the ill-posed nature of the image reconstruction, inclusions as small as 14mm could be accurately quantified with less than 15% error, for contrasts of 1.5 or higher. This suggests that 3D IG-NIRS provides quantitatively accurate results for sizes seen early in treatment cycle of patients undergoing neoadjuvant chemotherapy when the tumors are larger than 30mm

Methodology Development for Three-Dimensional MR-Guided Near Infrared Spectroscopy of Breast Tumors

Combined Magnetic Resonance (MR) and Near Infrared Spectroscopy (NIRS) has been proposed as a unique method to quantify hemodynamics, water content, and cellular size and packing density of breast tumors, as these tissue constituents can be quantified with increased resolution and overlaid on the structural features identified by the MR. However, the choices in how to reconstruct and visualize this information can have a dramatic impact on the feasibility of implementing this modality in the clinic. This is especially true in 3 dimensions, as there is often limited optical sampling of the breast tissue, and methods need to accurately reflect the tissue composition. In this paper, the implementation and display of fully 3D MR image-guided NIRS is outlined and demonstrated using in vivo data from three healthy women and a volunteer undergoing neoadjuvant chemotherapy. Additionally, a display feature presented here scales the transparency of the optical images to the sensitivity of the measurements, providing a logical way to incorporate partial volume sets of optical images onto the MR volume. These concepts are demonstrated with 3D data sets using Volview software online

A Coupled Finite Element-Boundary Element Method for Modeling Diffusion Equation in 3d Multi-Modality Optical Imaging

Three dimensional image reconstruction for multi-modality optical spectroscopy systems needs computationally efficient forward solvers with minimum meshing complexity, while allowing the flexibility to apply spatial constraints. Existing models based on the finite element method (FEM) require full 3D volume meshing to incorporate constraints related to anatomical structure via techniques such as regularization. Alternate approaches such as the boundary element method (BEM) require only surface discretization but assume homogeneous or piece-wise constant domains that can be limiting. Here, a coupled finite element-boundary element method (coupled FE-BEM) approach is demonstrated for modeling light diffusion in 3D, which uses surfaces to model exterior tissues with BEM and a small number of volume nodes to model interior tissues with FEM. Such a coupled FE-BEM technique combines strengths of FEM and BEM by assuming homogeneous outer tissue regions and heterogeneous inner tissue regions. Results with FE-BEM show agreement with existing numerical models, having RMS differences of less than 0.5 for the logarithm of intensity and 2.5 degrees for phase of frequency domain boundary data. The coupled FE-BEM approach can model heterogeneity using a fraction of the volume nodes (4-22%) required by conventional FEM techniques. Comparisons of computational times showed that the coupled FE-BEM was faster than stand-alone FEM when the ratio of the number of surface to volume nodes in the mesh (Ns/Nv) was less than 20% and was comparable to stand-alone BEM ( ± 10%)

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

Video-Rate Near Infrared Tomography to Image Pulsatile Absorption Properties in Thick Tissue

A high frame-rate near-infrared (NIR) tomography system was created to allow transmission imaging of thick tissues with spectral encoding for parallel source implementation. The design was created to maximize tissue penetration through up to 10 cm of tissue, allowing eventual use in human imaging. Eight temperature-controlled laser diodes (LD) are used in parallel with 1.5 nm shifts in their lasing wavelengths. Simultaneous detection is achieved with eight high-resolution, CCD-based spectrometers that were synchronized to detect the intensities and decode their source locations from the spectrum. Static and dynamic imaging is demonstrated through a 64 mm tissue-equivalent phantom, with acquisition rates up to 20 frames per second. Imaging of pulsatile absorption changes through a 72 mm phantom was demonstrated with a 0.5 Hz varying object having only 1% effect upon the transmitted signal. This subtle signal change was used to show that while reconstructing the signal changes in a tissue may not be possible, image-guided recovery of the pulsatile change in broad regions of tissue was possible. The ability to image thick tissue and the capacity to image periodic changes in absorption makes this design well suited for tracking thick tissue hemodynamics in vivo during MR or CT imaging

Image-Guided Raman Spectroscopic Recovery of Canine Cortical Bone Contrast in Situ

Raman scattering provides valuable biochemical and molecular markers for studying bone tissue composition with use in predicting fracture risk in osteoporosis. Raman tomography can image through a few centimeters of tissue but is limited by low spatial resolution. X-ray computed tomography (CT) imaging can provide high-resolution image-guidance of the Raman spectroscopic characterization, which enhances the quantitative recovery of the Raman signals, and this technique provides additional information to standard imaging methods. This hypothesis was tested in data measured from Teflon tissue phantoms and from a canine limb. Image-guided Raman spectroscopy (IG-RS) of the canine limb using CT images of the tissue to guide the recovery recovered a contrast of 145:1 between the cortical bone and background. Considerably less contrast was found without the CT image to guide recovery. This study presents the first known IG-RS results from tissue and indicates that intrinsically high contrasts (on the order of a hundred fold) are available

Imaging Targeted-Agent Binding In Vivo with Two Probes

An approach to quantitatively image targeted-agent binding rate in vivo is demonstrated with dual-probe injection of both targeted and nontargeted fluorescent dyes. Images of a binding rate constant are created that reveal lower than expected uptake of epidermal growth factor in an orthotopic xenograft pancreas tumor (2.3×10−5 s−1), as compared to the normal pancreas (3.4×10−5 s−1). This approach allows noninvasive assessment of tumor receptor targeting in vivo to determine the expected contrast, spatial localization, and efficacy in therapeutic agent delivery. Targeting therapeutic drugs to tumors based on their overexpression of cellular receptors is widely researched and has important clinical success.1, 2 Yet there are essentially no good tools to assess the in vivo receptor expression contrast between tumor as compared to normal surrounding tissue.3, 4 In tumors with very high molecular signaling such as in the pancreas,4, 5 it is not obvious when a particular receptor is actually up-regulated as compared to the surrounding normal tissue versus upregulated without biopsy. Imaging of receptor status in vivo is problematic, because the majority of any targeted agent in vivo is often not cell-associated yet. Thus, any single image simply provides a measure of the whole tissue concentration rather than the bound concentration. Delivery from the vascular supply to tumor cells requires transvascular leakage, followed by diffusion through the interstitial space, and binding to the targeted receptor followed by possible internalization.6 As such, imaging concentration values in vivo usually do not provide information about binding,7 since most of the agent is in the interstitial space. In this work, we demonstrate a new methodology for quantitative imaging of effective binding rate in vivo, using the difference in fluorescence signal between a targeted and untargeted agent. We use this to demonstrate that a tumor known to have high EGFR expression in vitro 5 actually has lower EGF activity than the surrounding normal pancreas in vivo. Most contrast agent imaging has been interpreted with a simple pharmacokinetic model that is designed with as few compartments and rate constants as possible to not overinterpret the data. A three compartment model [Fig. 1 ] can be used effectively to model targeted agent delivery in the tumor, which includes compartments for 1. the concentration of drug in the plasma within the vasculature, 2. the concentration in the interstitial space of the tissue, and 3. the cellular-associated fraction of drug.7 The dominant fast rates in this model are transvascular delivery of contrast agent through rate constantK12 role= presentation \u3eK12 , and then cell-associating rate constant due to binding and uptake, K23 role= presentation \u3eK23 . The dominant clearance from the plasma is given by excretion mechanisms, such as those in the liver and kidneys, through rate constant Ke role= presentation \u3eKe . Then the slowest rates tend to be those involved in backflow from the interstitial space to the vasculature K21 role= presentation \u3eK21 , and from the cell-associated space to the interstitial space K32 role= presentation \u3eK32 . Each of these is shown in the illustration of the model in Fig. 1

Near-Infrared Characterization of Breast Tumors In Vivo using Spectrally-Constrained Reconstruction

Multi-wavelength Near-Infrared (NIR) Tomography was utilized in this study to non-invasively quantify physiological parameters of breast tumors using direct spectral reconstruction. Frequency domain NIR measurements were incorporated with a new spectrally constrained direct chromophore and scattering image reconstruction algorithm, which was validated in simulations and experimental phantoms. Images of total hemoglobin, oxygen saturation, water, and scatter parameters were obtained with higher accuracy than previously reported. Using this spectral approach, in vivo NIR images are presented and interpreted through a series of case studies (n=6 subjects) having differing abnormalities. The corresponding mammograms and ultrasound images are also evaluated. Three of six cases were malignant (infiltrating ductal carcinomas) and showed higher hemoglobin (34–86% increase), a reduction in oxygen saturation, an increase in water content as well as scatter changes relative to surrounding normal tissue. Three of six cases were benign, two of which were diagnosed with fibrocystic disease and showed a dominant contrast in water, consistent with fluid filled cysts. Scatter amplitude was the main source of contrast in the volunteer with the benign condition fibrosis, which typically contains denser collagen tissue. The changes monitored correspond to physiological changes associated with angiogenesis, hypoxia and cell proliferation anticipated in cancers. These changes represent potential diagnostic indicators, which can be assessed to characterize breast tumors