Subhadra Srinivasan

Interpreting hemoglobin and water concentration, oxygen saturation, and scattering measured in vivo by near-infrared breast tomography

Near-infrared spectroscopic tomography was used to measure the properties of 24 mammographically normal breasts to quantify whole-breast absorption and scattering spectra and to evaluate which tissue composition characteristics can be determined from these spectra. The absorption spectrum of breast tissue allows quantification of (i) total hemoglobin concentration, (ii) hemoglobin oxygen saturation, and (iii) water concentration, whereas the scattering spectrum provides information about the size and number density of cellular components and structural matrix elements. These property data were tested for correlation to demographic information, including subject age, body mass index, breast size, and radiographic density. Total hemoglobin concentration correlated inversely to body mass index, likely because lower body mass indicates proportionately less fat and more glandular tissue, and glandular tissue contains greater vascularity, hence, more total hemoglobin. Optical scattering was correlated to breast diameter, subject age, and radiographic density. In the radiographic density, fatty breasts had low scattering power and extremely dense breasts had higher values. This observation is consistent with low attenuation of conventional x-rays with fat and higher attenuation in glandular tissues. Optically, fatty tissues have large scatterers leading to a low scattering power, whereas glandular or fibrous tissues have more cellular and collagen-based structures that lead to high scattering power. The study presents correlative data supporting the hypothesis that optical measurements of absorption and scattering can provide physiologically relevant information about breast tissue composition. These breast constituents vary significantly between individuals and can be altered because of changes in breast physiology or pathological state.

Characterization of hemoglobin, water, and NIR scattering in breast tissue: analysis of intersubject variability and menstrual cycle changes.

Near-infrared imaging was used to quantify typical values of hemoglobin concentration, oxygen saturation, water fraction, scattering power, and scattering amplitude within the breast tissue of volunteer subjects. A systematic study of the menstrual variations in these parameters was carried out by measuring a group of seven premenopausal normal women (aged 41 to 47 years) in the follicular (days 7 to 14 of the cycle) and secretory phases (days 21 to 28) of the cycle, for two complete menstrual cycles. An average increase in hemoglobin concentration of 2.6 microM or 13% of the background breast values was observed in the secretory phase relative to the follicular phase (p<0.0001), but no other average near-infrared parameter changes were significant. While repeatable and systematic changes were observed in all parameters for individual subjects, large intersubject variations were present in all parameters. In a survey of thirty-nine normal subjects, the total hemoglobin varied from 9 to 45 microM, with a systematic correlation observed between total hemoglobin concentration and breast radiographic density. Scattering power and scattering amplitude were also correlated with radiographic density, but oxygen saturation and water fraction were not. Images of breast lesions indicate that total hemoglobin-based contrast can be up to 200% relative to the background in the same breast. Yet, since the background hemoglobin values vary considerably among breasts, the maximum hemoglobin concentrations observed in cancer tumors may vary considerably as well. In light of these observations, it may be important to use hemoglobin contrast values relative to the background for a given breast, rather than absolute hemoglobin contrast when trying to compare the features of breast lesions among subjects.

Numerical modelling and image reconstruction in diffuse optical tomography

The development of diffuse optical tomography as a functional imaging modality has relied largely on the use of model-based image reconstruction. The recovery of optical parameters from boundary measurements of light propagation within tissue is inherently a difficult one, because the problem is nonlinear, ill-posed and ill-conditioned. Additionally, although the measured near-infrared signals of light transmission through tissue provide high imaging contrast, the reconstructed images suffer from poor spatial resolution due to the diffuse propagation of light in biological tissue. The application of model-based image reconstruction is reviewed in this paper, together with a numerical modelling approach to light propagation in tissue as well as generalized image reconstruction using boundary data. A comprehensive review and details of the basis for using spatial and structural prior information are also discussed, whereby the use of spectral and dual-modality systems can improve contrast and spatial resolution.

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.

Noninvasive Raman tomographic imaging of canine bone tissue.

Raman spectroscopic diffuse tomographic imaging has been demonstrated for the first time. It provides a noninvasive, label-free modality to image the chemical composition of human and animal tissue and other turbid media. This technique has been applied to image the composition of bone tissue within an intact section of a canine limb. Spatially distributed 785-nm laser excitation was employed to prevent thermal damage to the tissue. Diffuse emission tomography reconstruction was used, and the location that was recovered has been confirmed by micro-computed tomography (micro-CT) images.

Spectral priors improve near-infrared diffuse tomography more than spatial priors

We compare the benefits of spatial and spectral priors in near-infrared diffuse tomography image reconstruction. Although previous studies that incorporated anatomical spatial priors have shown improvement in algorithm convergence and resolution, our results indicate that functional parameter quantification by this approach can be suboptimal. The incorporation of a priori spectral information significantly improves the accuracy observed in recovered images. Specifically, phantom results show that the maximum total hemoglobin concentration ([Hb(T)]) in a region of heterogeneity reached 91% of the true value compared to 63% using spatial priors. The combination of both priors produced results accurate to 98% of the true [Hb(T)]. When both spatial and spectral priors were applied in a healthy volunteer, glandular tissue showed a higher [Hb(T)], water fraction, and scattering power compared to adipose tissue.

A boundary element approach for image-guided near-infrared absorption and scatter estimation

Multimodality NIR spectroscopy systems offer the possibility of region-based vascular and molecular characterization of tissue in vivo. However, computationally efficient 3D image reconstruction algorithms specific to these image-guided systems currently do not exist. Image reconstruction is often based on finite-element methods (FEMs), which require volume discretization. Here, a boundary element method (BEM) is presented using only surface discretization to recover the optical properties in an image-guided setting. The reconstruction of optical properties using BEM was evaluated in a domain containing a 30 mm inclusion embedded in two layer media with different noise levels and initial estimates. For 5% noise in measurements, and background starting values for reconstruction, the optical properties were recovered to within a mean error of 6.8%. When compared with FEM for this case, BEM showed a 28% improvement in computational time. BEM was also applied to experimental data collected from a gelatin phantom with a 25 mm inclusion and could recover the true absorption to within 6% of expected values using less time for computation compared with FEM. When applied to a patient-specific breast mesh generated using MRI, with a 2 cm ductal carcinoma, BEM showed successful recovery of optical properties with less than 5% error in absorption and 1% error in scattering, using measurements with 1% noise. With simpler and faster meshing schemes required for surface grids as compared with volume grids, BEM offers a powerful and potentially more feasible alternative for high-resolution 3D image-guided NIR spectroscopy.

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.

Image reconstruction of effective Mie scattering parameters of breast tissue in vivo with near-infrared tomography

A method for image reconstruction of the effective size and number density of scattering particles is discussed within the context of interpreting near-infrared (NIR) tomography images of breast tissue. An approach to use Mie theory to estimate the effective scattering parameters is examined and applied, given some assumptions about the index of refraction change expected in lipid membrane-bound scatterers. When using a limited number of NIR wavelengths in the reduced scattering spectra, the parameter extraction technique is limited to representing a continuous distribution of scatterer sizes, which is modeled as a simple exponentially decreasing distribution function. In this paper, image formation of effective scatterer size and number density is presented based on the estimation method. The method was evaluated with Intralipid phantom studies to demonstrate particle size estimation to within 9% of the expected value. Then the method was used in NIR patient images, and it indicates that for a cancer tumor, the effective scatterer size is smaller than the background breast values and the effective number density is higher. In contrast, for benign tumor patients, there is not a significant difference in effective scatterer size or number density between tumor and normal tissues. The method was used to interpret magnetic resonance imaging-coupled NIR images of adipose and fibroglandular tissues, and it indicated that the fibroglandular tissue has smaller effective scatterer size and larger effective number density than the adipose tissue does.

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 x 10(-5) s(-1)), as compared to the normal pancreas (3.4 x 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.