NIRViz: 3D visualization software for multimodality optical imaging using visualization toolkit (VTK) and insight segmentation toolkit (ITK).

Optical imaging using near-infrared light is used for noninvasive probing of tissues to recover vascular and molecular status of healthy and diseased tissues using hemoglobin contrast arising due to absorption of light. While multimodality optical techniques exist, visualization techniques in this area are limited. Addressing this issue, we present a simple framework for image overlay of optical and magnetic resonance (MRI) or computerized tomographic images which is intuitive and easily usable, called NIRViz. NIRViz is a multimodality software platform for the display and navigation of Digital Imaging and Communications in Medicine (DICOM) MRI datasets and 3D optical image solutions geared toward visualization and coregistration of optical contrast in diseased tissues such as cancer. We present the design decisions undertaken during the design of the software, the libraries used in the implementation, and other implementation details as well as preliminary results from the software package. Our implementation uses the Visualization Toolkit library to do most of the work, with a Qt graphical user interface for the front end. Challenges encountered include reslicing DICOM image data and coregistration of image space and mesh space. The resulting software provides a simple and customized platform to display surface and volume meshes with optical parameters such as hemoglobin concentration, overlay them on magnetic resonance images, allow the user to interactively change transparency of different image sets, rotate geometries, clip through the resulting datasets, obtain mesh and optical solution information, and successfully interact with both functional and structural medical image information.

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 e(R)ect 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 14 mm 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 30 mm.

Rapid magnetic resonance-guided near-infrared mapping to image pulsatile hemoglobin in the breast.

A near-IR (NIR) tomography system with spectral-encoded sources was built to quantify the temporal contrast in human breast tissue using guidance from magnetic resonance imaging. The systems were integrated with a custom breast coil interface to provide simultaneous acquisition. The NIR signal was synchronized to simultaneous finger pulse oximeter plethysmogram, which offered a frequency reference. A 0.1 s temporal delay of the absorption pulse within adipose tissue relative to fibroglandular tissue was found, in an initial human study, showing the potential for novel contrast imaging of fast flow signals in deep tissue.

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.

Imaging of glioma tumor with endogenous fluorescence tomography.

Tomographic imaging of a glioma tumor with endogenous fluorescence is demonstrated using a noncontact single-photon counting fan-beam acquisition system interfaced with microCT imaging. The fluorescence from protoporphyrin IX (PpIX) was found to be detectable, and allowed imaging of the tumor from within the cranium, even though the tumor presence was not visible in the microCT image. The combination of single-photon counting detection and normalized fluorescence to transmission detection at each channel allowed robust imaging of the signal. This demonstrated use of endogenous fluorescence stimulation from aminolevulinic acid (ALA) and provides the first in vivo demonstration of deep tissue tomographic imaging with protoporphyrin IX.

Diagnostic detection of diffuse glioma tumors in vive with molecular fluorescent probe-based transmission spectroscopy.

The diffuse spread of glioma tumors leads to the inability to image and properly treat this disease. The optical spectral signature of targeted fluorescent probes provides molecular signals from the diffuse morphologies of glioma tumors, which can be a more effective diagnostic probe than standard morphology-based magnetic resonance imaging (MRI) sequences. Three orthotopic xenograft glioma models were used to examine the potential for transmitted optical fluorescence signal detection in vivo, using endogenously produced protoporphyrin IX (PpIX) and exogenously administered fluorescently labeled epidermal growth factor (EGF). Accurate quantification of the fluorescent signals required spectral filtering and signal normalization, and when optimized, it was possible to improve detection of sparse diffuse glioma tumor morphologies. The signal of endogenously produced PpIX provided similar sensitivity and specificity to MRI, while detection with fluorescently labeled EGF provided maximal specificity for tumors with high EGF receptor activity. Optical transmitted fluorescent signal may add significant benefit for clinical cases of diffuse infiltrative growth pattern glioma tumors given sufficient optimization of the signal acquisition for each patient.

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.

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.

Spectral tomography with diffuse near-infrared light: inclusion of broadband frequency domain spectral data.

Near-infrared (NIR) region-based spectroscopy is examined for accuracy with spectral recovery using frequency domain data at a discrete number of wavelengths, as compared to that with broadband continuous wave data. Data with more wavelengths in the frequency domain always produce superior quantitative spectroscopy results with reduced noise and error in the chromophore concentrations. Performance of the algorithm in the situation of doing region-guided spectroscopy within the MRI is also considered, and the issue of false positive prior regions being identified is examined to see the effect of added wavelengths. The results indicate that broadband frequency domain data are required for maximal accuracy. A broadband frequency domain experimental system was used to validate the predictions, using a mode-locked Ti:sapphire laser for the source between 690- and 850-nm wavelengths. The 80-MHz pulsed signal is heterodyned with photomultiplier tube detection, to lower frequency for data acquisition. Tissue-phantom experiments with known hemoglobin absorption and tissue-like scatter values are used to validate the system, using measurements every 10 nm. More wavelengths clearly provide superior quantification of total hemoglobin values. The system and algorithms developed here should provide an optimal way to quantify regions with the goal of image-guided breast tissue spectroscopy within the MRI.

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.

Developments in quantitative oxygen-saturation imaging of breast tissue in vivo using multispectral near-infrared tomography.

Imaging of oxygen saturation provides a spatial map of the tissue metabolic activity and has potential in diagnosis and treatment monitoring of breast cancer. Oxygen-saturation imaging is possible through near-infrared (NIR) tomography, but has low signal-to-noise ratio (SNR). This can be augmented by using NIR tomography as an add-on to MRI. Presented are results from a free-standing NIR system and a hybrid MR-guided system for breast imaging. In results from imaging 60 healthy volunteers in the initial NIR system, oxygen saturation was a significant discriminator between the BIRADS classifications of adipose tissue, heterogeneously dense, and extremely dense tissue. By using the MR-guided NIR system, more accurate tissue-specific data were obtained on adipose and fibroglandular volumes, with 11 healthy volunteers. In these data, oxygen saturation in the adipose tissue correlated with percentage of adipose tissue. In two case studies of infiltrating ductal carcinomas, oxygen saturation was reduced at the site of the tumor, as compared with the surrounding healthy tissue, agreeing with conventional thought that hypoxia exists in larger solid tumors. The MRI-guided NIR images of oxygen saturation provide higher resolution and superior SNR and will likely be used in the future to study and characterize specific tissue volumes.

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.

Data subset algorithm for computationally efficient reconstruction of 3-D spectral imaging in diffuse optical tomography.

Three-dimensional (3-D) models of light propagation in diffuse optical tomography provide an accurate representation of scattering in tissue. Here the use of spectral priors, shown to improve quantification of functional parameters in 2-D, has been extended to 3-D. To make 3-D spectral imaging computationally tractable, a novel technique is presented to deal with the large data set. The basic principle consists of using a dynamic criterion to select optimal data subsets that capture the major changes in the imaging domain. Results from three test cases showed comparable image quality and accuracy with less than 4% difference between the uses of data subset approach versus the entire dataset. Tested on simulated data from two different models, the algorithm was able to discern multiple objects successfully with an average error of 30% in quantifying multiple regions and less than 1% in quantifying the background.

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.

In vivo hemoglobin and water concentrations, oxygen saturation, and scattering estimates from near-infrared breast tomography using spectral reconstruction.

RATIONALE AND OBJECTIVES: Near-infrared (NIR) imaging has its niche in quantifying and characterizing functional changes in tissue relating to vascularity and metabolic status. Here, NIR tomography was applied to study mammographically normal breast tissue in vivo by evaluating relationships between functional parameters so obtained to clinical representers in an effort to understand factors influencing tissue compositional changes. MATERIALS AND METHODS: A new spectral reconstruction method that is considered to provide the most accurate estimates of hemoglobin level, oxygen saturation, water fraction, scattering power, and amplitude was used to assess healthy breast tissue imaged in vivo by means of NIR tomography. The approach directly recovers functional parameters with inherent inclusion of spectral behavior enforced through the incorporation of a priori model assumptions. Sixty subjects were imaged by using a frequency-domain instrument followed by spectral image reconstruction and statistical analysis for significant correlations. RESULTS: The new analysis shows statistically significant inverse correlations between body mass index and breast total hemoglobin and water fractions. Water fraction also correlated inversely with age and separated certain categories of breast density. Average scatter power was indicative of breast radiographic density composition, whereas scatter amplitude varied inversely with breast diameter. Total hemoglobin correlated with water fraction, whereas water correlated with scatter power. CONCLUSION: The changes observed here are attributable to volume fraction alterations and provide some of the most comprehensive data on breast composition variations with demographic factors.

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.

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.

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.

3-D Image-guided diffuse optical tomography using boundary element method and MPI implementation.

Boundary elements provide an attractive method for image-guided multi-modality near infrared spectroscopy in three dimensions using only surface discretization. This method operates under the assumption that the underlying tissue contains piece-wise constant domains whose boundaries are known a priori from an alternative imaging modality such as MRI or microCT. This significantly simplifies the meshing process providing both speed-up and accuracy in the forward solution. Challenges with this method are in solving dense matrices, and working with complex heterogeneous domains. Solutions to these problems are presented here, with applications in breast cancer imaging and small - animal molecular imaging.

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 (N(s)/N(v)) was less than 20% and was comparable to stand-alone BEM ( ± 10%).