Troy O. McBride

SPATIALLY VARIANT REGULARIZATION IMPROVES DIFFUSE OPTICAL TOMOGRAPHY

Diffuse tomography with near-infrared light has biomedical application for imaging hemoglobin, water, lipids, cytochromes, or exogenous contrast agents and is being investigated for breast cancer diagnosis. A Newton-Raphson inversion algorithm is used for image reconstruction of tissue optical absorption and transport scattering coefficients from frequency-domain measurements of modulated phase shift and light intensity. A variant of Tikhonov regularization is examined in which radial variation is allowed in the value of the regularization parameter. This method minimizes high-frequency noise in the reconstructed image near the source-detector locations and can produce constant image resolution and contrast across the image field.

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.

A parallel-detection frequency-domain near-infrared tomography system for hemoglobin imaging of the breast in vivo

A novel near-infrared frequency-domain system designed for tomographic breast imaging is described. The setup utilizes five optical wavelengths, from 660 to 826 nm, and parallel detection with 16 photomultiplier tubes. Direct fiberoptic coupling with the tissue is achieved with a high precision positioning device using 16 motorized actuators (0.5 μm precision) arranged radially in a circular geometry. Images of breast tissue optical absorption and reduced scattering coefficients are obtained using a Newton-type reconstruction algorithm to solve for the optimal fit between the measurement data and predicted data from a finite element solution to the frequency-domain diffusion equation. The design, calibration, and performance of the tomographic imaging system are detailed. Data acquisition from the system requires under 30 s for a single tomographic slice at one optical wavelength with a measurement repeatability for a single phantom on average of 0.5% in ac intensity and 0.4° in phase. Absorbing and scatt...

Spectroscopic diffuse optical tomography for the quantitative assessment of hemoglobin concentration and oxygen saturation in breast tissue

Near-infrared (NIR) spectroscopic diffuse tomography has been used to map the hemoglobin concentration and the hemoglobin oxygen saturation quantitatively in tissuelike phantoms and to determine average values in vivo. A series of phantom calibrations were performed to achieve quantitatively accurate images of the absorption and the reduced scattering coefficients at multiple optical wavelengths. A least-squares fit was applied to absorption-coefficient images at multiple NIR wavelengths to obtain hemoglobin images of the concentration and the hemoglobin oxygen saturation. Objects of varying hemoglobin concentration and oxygen saturation within highly scattering media were localized and imaged to within 15% of their actual values. The average hemoglobin concentration and oxygen saturation of breast tissue was measured in vivo for two women volunteers. The potential application for the diagnosis of breast tumors is discussed.

Comparison of imaging geometries for diffuse optical tomography of tissue

Images produced in six different geometries with diffuse optical tomography simulations of tissue have been compared using a finite element-based algorithm with iterative refinement provided by the Newton-Raphson approach. The source-detector arrangements studied include (i) fan-beam tomography, (ii) full reflectance and transmittance tomography, as well as (iii) sub-surface imaging, where each of these three were examined in a circular and a flat slab geometry. The algorithm can provide quantitatively accurate results for all of the tomographic geometries investigated under certain circumstances. For example, quantitatively accurate results occur with sub-surface imaging only when the object to be imaged is fully contained within the diffuse projections. In general the diffuse projections must sample all regions around the target to be characterized in order for the algorithm to recover quantitatively accurate results. Not only is it important to sample the whole space, but maximal angular sampling is required for optimal image reconstruction. Geometries which do not maximize the possible sampling angles cause more noise artifact in the reconstructed images. Preliminary simulations using a mesh of the human brain confirm that optimal images are produced from circularly symmetric source-detector distributions, but that quantitatively accurate images can be reconstructed even with a sub-surface imaging, although spatial resolution is modest.

Three-dimensional simulation of near-infrared diffusion in tissue: boundary condition and geometry analysis for finite-element image reconstruction

Imaging of tissue with near-infrared spectral tomography is emerging as a practicable method to map hemoglobin concentrations within tissue. However, the accurate recovery of images by using modeling methods requires a good match between experiments and the model prediction of light transport in tissue. We illustrate the potential for a match between (i) three-dimensional (3-D) frequency-domain diffusion theory, (ii) two-dimensional diffusion theory, (iii) Monte Carlo simulations, and (iv) experimental data from tissue-simulating phantoms. Robin-type boundary conditions are imposed in the 3-D model, which can be implemented with a scalar coupling coefficient relating the flux through the surface to the diffuse fluence rate at the same location. A comparison of 3-D mesh geometries for breast imaging indicates that relative measurements are sufficiently similar when calculated on either cylindrical or female breast shapes, suggesting that accurate reconstruction may be achieved with the simpler cylindrical mesh. Simulation studies directly assess the effects from objects extending out of the image plane, with results suggesting that spherically shaped objects reconstruct at lower contrast when their diameters are less than 15-20 mm. The algorithm presented here illustrates that a 3-D forward diffusion model can be used with circular tomographic measurements to reconstruct two-dimensional images of the interior absorption coefficient.

Multispectral near-infrared tomography: a case study in compensating for water and lipid content in hemoglobin imaging of the breast.

Images of hemoglobin concentration and oxygen saturation are presented from multispectral near-infrared tomographic measurements in the breast of a woman with an invasive cancer. Images of the absorption coefficient and reduced scattering coefficient are recovered from the measured data using a finite element reconstruction algorithm based on the frequency-domain diffusion equation. Three methods of recovering the hemoglobin concentration and oxygen saturation images are presented which compensate for water and lipid absorption in different ways: (1) an assumed bulk content of water and lipids is used, (2) four chromophores are imaged, and (3) scattering power data are applied to deduce water and lipid images. In all three cases, a large increase in the hemoglobin concentration (3:1) is observed at the location of the cancer while a maximum of 15% difference is observed in the hemoglobin images between each of these methods for water and lipid compensation.

Initial studies of in vivo absorbing and scattering heterogeneity in near-infrared tomographic breast imaging

Simultaneously recovered absorption and scattering images that separate these optical property features within the female breast are demonstrated from frequency-domain measurements. A study of known absorbing and scattering objects is presented as a foundation for interpreting these in vivo images once the contrast space has been fully characterized. No measurable influence of absorbing-object contrast appears in the scattering images, whereas localized scattering contrast enhances the corresponding region within the absorption image by approximately 30% (e.g., a 2:1 scatterer also reconstructs as an approximately 1.3:1 absorber). Scattering and absorption images of a female volunteer with a 3.4-cm fibroadenoma show a clear 2:1 localized increase in absorption coefficient with little or no evidence of scattering enhancement in the lesion.

Contrast‐detail analysis for detection and characterization with near‐infrared diffuse tomography

Near-infrared (NIR) diffuse tomography is emerging as a medical imaging modality for obtaining information related to tissue hemoglobin concentration and oxygen saturation and may be used for characterizing diseased tissues such as breast cancer. The optimal methodology for NIR image reconstruction remains an ongoing research problem with several new approaches being demonstrated in recent years. However, a comparison of reconstruction methods is problematic because tools for the objective assessment of image quality have yet to be clearly defined for this type of nonlinear reconstruction problem. Contrast-detail analysis has become an accepted assessment tool to quantify x-ray mammography image quality, and in this study it has been applied to a prototype NIR diffuse tomography system that is being evaluated for breast cancer characterization. The minimum detectable levels of contrast have been defined for different sizes of objects, and the minimum contrasts which can be accurately reconstructed have also been determined for the same object sizes. In general, objects 8 mm and larger in diameter can be accurately reconstructed and detected for most absorption contrasts which are observed in human tissues (i.e., greater than 1% contrast in absorption). Objects as small as 2 mm can be detected with high contrast (i.e., near 100%), but cannot be accurately reconstructed. Within the size range of 2 mm to 8 mm, there is an inverse correlation between contrast and detail size which is characteristic of the total noise in the system. This analysis provides an objective method for assessing detection and characterization limits and can be applied to future improvements in hardware system architecture as well as reconstruction algorithms.

Quantitative analysis of near-infrared tomography: sensitivity to the tissue-simulating precalibration phantom

A near-infrared (NIR) imaging system is evaluated as a diagnostic clinical tool to image total hemoglobin concentration and oxygen saturation within tissue. Calibration of this type of system requires measurement of the response at each detector and source location from a homogeneous tissue-simulating phantom. The effect of using calibration phantoms of varying composition, size, and optical properties is examined to determine how it affects the overall image accuracy. All of the calibration phantoms investigated result in accurate reconstruction of absorbing heterogeneities due to increased blood concentration with less than 4% standard deviation. Images from a patient with a biopsy-confirmed ductal carcinoma are also evaluated and found to be insensitive to the choice of calibration object, with only 1% variation between images generated with different calibration objects. The tumor total hemoglobin contrast is approximately 240% higher than the average total hemoglobin concentration in contralateral breast. Soft calibration phantoms, which mimic the elastic properties of human breast tissue, are also considered and found to diminish positioning errors in the fibers relative to the actual breast exam, thereby reducing the artifacts in the periphery of the reconstructed image.