Hemoglobin signal network mapping reveals novel indicators for precision medicine

Precision medicine currently relies on a mix of deep phenotyping strategies to guide more individualized healthcare. Despite being widely available and information-rich, physiological time-series measures are often overlooked as a resource to extend insights gained from such measures. Here we have explored resting-state hemoglobin measures applied to intact whole breasts for two subject groups - women with confirmed breast cancer and control subjects - with the goal of achieving a more detailed assessment of the cancer phenotype from a non-invasive measure. Invoked is a novel ordinal partition network method applied to multivariate measures that generates a Markov chain, thereby providing access to quantitative descriptions of short-term dynamics in the form of several classes of adjacency matrices. Exploration of these and their associated co-dependent behaviors unexpectedly reveals features of structured dynamics, some of which are shown to exhibit enzyme-like behaviors and sensitivity to recognized molecular markers of disease. Thus, findings obtained strongly indicate that despite the use of a macroscale sensing method, features more typical of molecular-cellular processes can be identified. Discussed are factors unique to our approach that favor a deeper depiction of tissue phenotypes, its extension to other forms of physiological time-series measures, and its expected utility to advance goals of precision medicine.

Endurance Exercise Enhances Emotional Valence and Emotion Regulation

Acute exercise consistently benefits both emotion and cognition, particularly cognitive control. We evaluated acute endurance exercise influences on emotion, domain-general cognitive control and the cognitive control of emotion, specifically cognitive reappraisal. Thirty-six endurance runners, defined as running at least 30 miles per week with one weekly run of at least 9 miles (21 female, age 18-30 years) participated. In a repeated measures design, participants walked at 57% age-adjusted maximum heart rate (HRmax; range 51%-63%) and ran at 70% HRmax (range 64%-76%) for 90 min on two separate days. Participants completed measures of emotional state and the Stroop test of domain-general cognitive control before, every 30 min during and 30 min after exercise. Participants also completed a cognitive reappraisal task (CRT) after exercise. Functional near-infrared spectroscopy (fNIRS) tracked changes in oxygenated and deoxygenated hemoglobin (O2Hb and dHb) levels in the prefrontal cortex (PFC). Results suggest that even at relatively moderate intensities, endurance athletes benefit emotionally from running both during and after exercise and task-related PFC oxygenation reductions do not appear to hinder prefrontal-dependent cognitive control.

Hemoglobin state-flux: A finite-state model representation of the hemoglobin signal for evaluation of the resting state and the influence of disease

SUMMARY

In this report we introduce a weak-model approach for examination of the intrinsic time-varying properties of the hemoglobin signal, with the aim of advancing the application of functional near infrared spectroscopy (fNIRS) for the detection of breast cancer, among other potential uses. The developed methodology integrates concepts from stochastic network theory with known modulatory features of the vascular bed, and in doing so provides access to a previously unrecognized dense feature space that is shown to have promising diagnostic potential. Notable features of the methodology include access to this information solely from measures acquired in the resting state, and analysis of these by treating the various components of the hemoglobin (Hb) signal as a co-varying interacting system.

APPROACH

The principal data-transform kernel projects Hb state-space trajectories onto a coordinate system that constitutes a finite-state representation of covariations among the principal elements of the Hb signal (i.e., its oxygenated (ΔoxyHb) and deoxygenated (ΔdeoxyHb) forms and the associated dependent quantities: total hemoglobin (ΔtotalHb = ΔoxyHb + ΔdeoxyHb), hemoglobin oxygen saturation (ΔHbO2Sat = 100Δ(oxyHb/totalHb)), and tissue-hemoglobin oxygen exchange (ΔHbO2Exc = ΔdeoxyHb-ΔoxyHb)). The resulting ten-state representation treats the evolution of this signal as a one-space, spatiotemporal network that undergoes transitions from one state to another. States of the network are defined by the algebraic signs of the amplitudes of the time-varying components of the Hb signal relative to their temporal mean values. This assignment produces several classes of coefficient arrays, most with a dimension of 10×10.

BIOLOGICAL MOTIVATION

Motivating our approach is the understanding that effector mechanisms that modulate blood delivery to tissue operate on macroscopic scales, in a spatially and temporally varying manner. Also recognized is that this behavior is sensitive to nonlinear actions of these effectors, which include the binding properties of hemoglobin. Accessible phenomenology includes measures of the kinetics and probabilities of network dynamics, which we treat as surrogates for the actions of feedback mechanisms that modulate tissue-vascular coupling.

FINDINGS

Qualitative and quantitative features of this space, and their potential to serve as markers of disease, have been explored by examining continuous-wave fNIRS 3D tomographic time series obtained from the breasts of women who do and do not have breast cancer. Inspection of the coefficient arrays reveals that they are governed predominantly by first-order rate processes, and that each array class exhibits preferred structure that is mainly independent of the others. Discussed are strategies that may serve to extend evaluation of the accessible feature space and how the character of this information holds potential for development of novel clinical and preclinical uses.

Enhanced resting-state dynamics of the hemoglobin signal as a novel biomarker for detection of breast cancer

PURPOSE

The work presented here demonstrates an application of diffuse optical tomography (DOT) to the problem of breast-cancer diagnosis. The potential for using spatial and temporal variability measures of the hemoglobin signal to identify useful biomarkers was studied.

METHODS

DOT imaging data were collected using two instrumentation platforms the authors developed, which were suitable for exploring tissue dynamics while performing a simultaneous bilateral exam. For each component of the hemoglobin signal (e.g., total, oxygenated), the image time series was reduced to eight scalar metrics that were affected by one or more dynamic properties of the breast microvasculature (e.g., average amplitude, amplitude heterogeneity, strength of spatial coordination). Receiver-operator characteristic (ROC) analyses, comparing groups of subjects with breast cancer to various control groups (i.e., all noncancer subjects, only those with diagnosed benign breast pathology, and only those with no known breast pathology), were performed to evaluate the effect of cancer on the magnitudes of the metrics and of their interbreast differences and ratios.

RESULTS

For women with known breast cancer, simultaneous bilateral DOT breast measures reveal a marked increase in the resting-state amplitude of the vasomotor response in the hemoglobin signal for the affected breast, compared to the contralateral, noncancer breast. Reconstructed 3D spatial maps of observed dynamics also show that this behavior extends well beyond the tumor border. In an effort to identify biomarkers that have the potential to support clinical aims, a group of scalar quantities extracted from the time series measures was systematically examined. This analysis showed that many of the quantities obtained by computing paired responses from the bilateral scans (e.g., interbreast differences, ratios) reveal statistically significant differences between the cancer-positive and -negative subject groups, while the corresponding measures derived from individual breast scans do not. ROC analyses yield area-under-curve values in the 77%-87% range, depending on the metric, with sensitivity and specificity values ranging from 66% to 91%. An interesting result is the initially unexpected finding that the hemodynamic-image metrics are only weakly dependent on the tumor burden, implying that the DOT technique employed is sensitive to tumor-induced changes in the vascular dynamics of the surrounding breast tissue as well. Computational modeling studies serve to identify which properties of the vasomotor response (e.g., average amplitude, amplitude heterogeneity, and phase heterogeneity) principally determine the values of the metrics and their codependences. Findings from the modeling studies also serve to clarify the influence of spatial-response heterogeneity and of system-design limitations, and they reveal the impact that a complex dependence of metric values on the modeled behaviors has on the success in distinguishing between cancer-positive and -negative subjects.

CONCLUSIONS

The authors identified promising hemoglobin-based biomarkers for breast cancer from measures of the resting-state dynamics of the vascular bed. A notable feature of these biomarkers is that their spatial extent encompasses a large fraction of the breast volume, which is mainly independent of tumor size. Tumor-induced induction of nitric oxide synthesis, a well-established concomitant of many breast cancers, is offered as a plausible biological causal factor for the reported findings.

On the geometry dependence of differential pathlength factor for near-infrared spectroscopy. I. Steady-state with homogeneous medium

This work analytically examines some dependences of the differential pathlength factor (DPF) for steady-state photon diffusion in a homogeneous medium on the shape, dimension, and absorption and reduced scattering coefficients of the medium. The medium geometries considered include a semi-infinite geometry, an infinite-length cylinder evaluated along the azimuthal direction, and a sphere. Steady-state photon fluence rate in the cylinder and sphere geometries is represented by a form involving the physical source, its image with respect to the associated extrapolated half-plane, and a radius-dependent term, leading to simplified formula for estimating the DPFs. With the source-detector distance and medium optical properties held fixed across all three geometries, and equal radii for the cylinder and sphere, the DPF is the greatest in the semi-infinite and the smallest in the sphere geometry. When compared to the results from finite-element method, the DPFs analytically estimated for 10 to 25 mm source–detector separations on a sphere of 50 mm radius with μa=0.01  mm(−1) and μ′s=1.0  mm(−1) are on average less than 5% different. The approximation for sphere, generally valid for a diameter≥20 times of the effective attenuation pathlength, may be useful for rapid estimation of DPFs in near-infrared spectroscopy of an infant head and for short source–detector separation.

A programmable laboratory testbed in support of evaluation of functional brain activation and connectivity

An important determinant of the value of quantitative neuroimaging studies is the reliability of the derived information, which is a function of the data collection conditions. Near infrared spectroscopy (NIRS) and electroencelphalography are independent sensing domains that are well suited to explore principal elements of the brain's response to neuroactivation, and whose integration supports development of compact, even wearable, systems suitable for use in open environments. In an effort to maximize the translatability and utility of such resources, we have established an experimental laboratory testbed that supports measures and analysis of simulated macroscopic bioelectric and hemodynamic responses of the brain. Principal elements of the testbed include 1) a programmable anthropomorphic head phantom containing a multisignal source array embedded within a matrix that approximates the background optical and bioelectric properties of the brain, 2) integrated translatable headgear that support multimodal studies, and 3) an integrated data analysis environment that supports anatomically based mapping of experiment-derived measures that are directly and not directly observable. Here, we present a description of system components and fabrication, an overview of the analysis environment, and findings from a representative study that document the ability to experimentally validate effective connectivity models based on NIRS tomography.

Optomechanical imaging system for breast cancer detection

Imaging studies of the breast comprise three principal sensing domains: structural, mechanical, and functional. Combinations of these domains can yield either additive or wholly new information, depending on whether one domain interacts with the other. In this report, we describe a new approach to breast imaging based on the interaction between controlled applied mechanical force and tissue hemodynamics. Presented is a description of the system design, performance characteristics, and representative clinical findings for a second-generation dynamic near-infrared optical tomographic breast imager that examines both breasts simultaneously, under conditions of rest and controlled mechanical provocation. The expected capabilities and limitations of the developed system are described in relation to the various sensing domains for breast imaging.

Heritable cardiac conduction and myocardial disease: from the clinic to the basic science laboratory and back to the clinic

A close collaboration between the physicians-scientists of the Division of Cardiology, The Ohio State University and the basic scientists of the Department of Genetics, Harvard Medical School was essential to define the multiple phenotypic expressions and the genetic abnormalities in the heritable conduction and myocardial disease in a family from central Ohio (Family OSU). The Family OSU presents evidence of sequential hierarchical progression through multiple cardiac phenotypes (sinus bradycardia, atrioventricular conduction defects requiring pacemaker, supraventricular arrhythmias including atrial fibrillation, heart failure, and sudden cardiac death) on a decade-to-decade basis. In this setting, each phenotype may be mistakenly considered as a specific diagnosis by physicians working without a pedigree or long-term follow-up. Genetic analysis, however, confirms lamin A/C mutation. The role of the physician-scientist and the basic scientist for the study of heritable disorders is equally important but different. Only the physician-scientist, however, who is in constant contact with the patient understands the complexity of the disease. The physician-scientist with an interest in a particular disease can guide the basic scientist to define molecular mechanisms of that disease and by extension learn important lessons for other diseases.

Using co-variations in the Hb signal to detect visual activation: a near infrared spectroscopic imaging study

The premise of this report is that functional Near Infrared Spectroscopy (fNIRS) imaging data contain valuable physiological information that can be extracted by using analysis techniques that simultaneously consider the components of the measured hemodynamic response [i.e., levels of oxygenated, deoxygenated and total hemoglobin (oxyHb, deoxyHb and totalHb, respectively)]. We present an algorithm for examining the spatiotemporal co-variations among the Hb components, and apply it to the data obtained from a demonstrational study that employed a well-established visual stimulation paradigm: a contrast-reversing checkerboard. Our results indicate that the proposed method can identify regions of tissue that participate in the hemodynamic response to neuronal activation, but are distinct from the areas identified by conventional analyses of the oxyHb, deoxyHb and totalHb data. A discussion is provided that compares these findings to other recent studies using fNIRS techniques.

Image correction scheme applied to functional diffuse optical tomography scattering images

We have extended our investigation on the use of a linear algorithm for enhancing the accuracy of diffuse optical tomography (DOT) images, to include spatial maps of the diffusion coefficient. The results show that the corrected images are markedly improved in terms of estimated size, spatial resolution, two-object resolving power, and quantitative accuracy. These image-enhancing effects are significant at expected levels of diffusion-coefficient contrast in tissue and noise levels typical of experimental DOT data. Overall, the types and magnitudes of image-enhancing effects obtained here are qualitatively similar to those seen in previous studies on mu(a) perturbations. The implications for practical implementations of DOT time-series imaging are discussed.

Image correction algorithm for functional three-dimensional diffuse optical tomography brain imaging

We outline a computationally efficient image correction algorithm, which we have applied to diffuse optical tomography (DOT) image time series derived from a magnetic resonance imaging (MRI)-based brain model. Results show that the algorithm increases spatial resolution, decreases spatial bias, and only modestly reduces temporal accuracy for noise levels typically seen in experiment, and produces results comparable to image reconstructions that incorporate information from MRI priors. We demonstrate that this algorithm has robust performance in the presence of noise, background heterogeneity, irregular external and internal boundaries, and error in the initial guess. However, the algorithm introduces artifacts when the absorption and scattering coefficients of the reference medium are overestimated--a situation that is easily avoided in practice. The considered algorithm offers a practical approach to improving the quality of images from time-series DOT, even without the use of MRI priors.

Image quality improvement via spatial deconvolution in optical tomography: time-series imaging

We present the fourth in a series of studies devoted to the issue of improving image quality in diffuse optical tomography (DOT) by using a spatial deconvolution operation that seeks to compensate for the information-blurring property of first-order perturbation algorithms. Our earlier reports consider only static target media. Here we report spatial deconvolution applied to media with time-varying optical properties, as a model of tissue dynamics resulting from varying metabolic demand and modulation of the vascular bed. Issues under study include the influence of deconvolution on the accuracy of the recovered temporal and spatial information. The impact of noise is also explored, and techniques for ameliorating its information-degrading effects are examined. At low noise levels (i.e, < or = 5% of the time-varying signal amplitude), spatial deconvolution markedly improves the accuracy of recovered information. Temporal information is more seriously degraded by noise than is spatial information, and the impact of noise increases with the complexity of the time-varying signal. These effects, however, can be significantly reduced using simple noise suppression techniques (e.g., low-pass filtering). Results suggest that the deconvolution scheme should provide considerable enhancement of the quality of spatiotemporal information recovered from dynamic DOT techniques applied to tissue studies.

Improved accuracy of reconstructed diffuse optical tomographic images by means of spatial deconvolution: two-dimensional quantitative characterization

Systematic characterization studies are presented, relating to a previously reported spatial deconvolution operation that seeks to compensate for the information-blurring property of first-order perturbation algorithms for diffuse optical tomography (DOT) image reconstruction. In simulation results that are presented, this deconvolution operation has been applied to two-dimensional DOT images reconstructed by solving a first-order perturbation equation. Under study was the effect on algorithm performance of control parameters in the measurement (number and spatial distribution of sources and detectors, presence of noise, and presence of systematic error), target (medium shape; and number, location, size, and contrast of inclusions), and computational (number of finite-element-method mesh nodes, length of filter-generating linear system, among others) parameter spaces associated with computation and the use of the deconvolution operators. Substantial improvements in reconstructed image quality, in terms of recovered inclusion location, size, and contrast, are found in all cases. A finding of practical importance is that the method is robust to appreciable differences between the optical coefficients of the media used for filter generation and those of the target media to which the filters are subsequently applied.

Design and implementation of dynamic near-infrared optical tomographic imaging instrumentation for simultaneous dual-breast measurements

Dynamic near-infrared optical tomographic measurement instrumentation capable of simultaneous bilateral breast imaging, having a capability of four source wavelengths and 32 source-detector fibers for each breast, is described. The system records dynamic optical data simultaneously from both breasts, while verifying proper optical fiber contact with the tissue through implementation of automatic schemes for evaluating data integrity. Factors influencing system complexity and performance are discussed, and experimental measurements are provided to demonstrate the repeatability of the instrumentation. Considerations in experimental design are presented, as well as techniques for avoiding undesirable measurement artifacts, given the high sensitivity and dynamic range (1:10(9)) of the system. We present exemplary clinical results comparing the measured physiologic response of a healthy individual and of a subject with breast cancer to a Valsalva maneuver.

Spatial deconvolution technique to improve the accuracy of reconstructed three-dimensional diffuse optical tomographic images

A straightforward spatial deconvolution operation is presented that seeks to invert the information-blurring property of first-order perturbation algorithms for diffuse optical tomography (DOT) image reconstruction. The method that was developed to generate these deconvolving operators, or filters, was conceptually based on the frequency-encoding process used in magnetic resonance imaging. The computation of an image-correcting filter involves the solution of a large system of linear equations, in which known true distributions and the corresponding recovered distributions are compared. Conversely, application of a filter involves only a simple matrix multiplication. Simulation results show that application of this deconvolution operation to three-dimensional DOT images reconstructed by the solution of a first-order perturbation equation (Born approximation) can yield marked enhancement of image quality. In the examples considered, use of image-correcting filters produces obvious improvements in image quality, in terms of both location and mirco(a) of the inclusions. The displacements between the true and recovered locations of an inclusion's centroid location are as small as 1 mm, in an 8-cm-diameter medium with 1.5-cm-diameter inclusions, and the peak value of the recovered micro(a) for the inclusions deviates from the true value by as little as 5%.

Imaging of spatiotemporal coincident states by DC optical tomography

The utility of optical tomography as a practical imaging modality has, thus far, been limited by its intrinsically low spatial resolution and quantitative accuracy. Recently, we have argued that a broad range of physiological phenomena might be accurately studied by adopting this technology to investigate dynamic states (Schmitz et al., 2000; Barbour et al., 2000; Graber et al., 2000; Barbour et aL, 2001; and Barbour et aL, 1999). One such phenomenon holding considerable significance is the dynamics of the vasculature, which has been well characterized as being both spatially and temporally heterogeneous. In this paper, we have modeled such heterogeneity in the limiting case of spatiotemporal coincident behavior involving optical contrast features, in an effort to define the expected limits with which dynamic states can be characterized using two newly described reconstruction methods that evaluate normalized detector data: the normalized difference method (NDM) and the normalized constraint method (NCM). Influencing the design of these studies is the expectation that spatially coincident temporal variations in both the absorption and scattering properties of tissue can occur in vivo. We have also chosen to model dc illumination techniques, in recognition of their favorable performance and cost for practical systems. This choice was made with full knowledge of theoretical findings arguing that separation of the optical absorption and scattering coefficients under these conditions is not possible. Results obtained show that the NDM algorithm provides for good spatial resolution and excellent characterization of the temporal behavior of optical properties but is subject to interparameter crosstalk. The NCM algorithm, while also providing excellent characterization of temporal behavior, provides for improved spatial resolution, as well as for improved separation of absorption and scattering coefficients. A discussion is provided to reconcile these findings with theoretical expectations.

Optical tomographic imaging of dynamic features of dense-scattering media

Methods used in optical tomography have thus far proven to produce images of complex target media (e.g., tissue) having, at best, relatively modest spatial resolution. This presents a challenge in differentiating artifact from true features. Further complicating such efforts is the expectation that the optical properties of tissue for any individual are largely unknown and are likely to be quite variable due to the occurrence of natural vascular rhythms whose amplitudes are sensitive to a host of autonomic stimuli that are easily induced. We recognize, however, that rather than frustrating efforts to validate the accuracy of image features, the time-varying properties of the vasculature can be exploited to aid in such efforts, owing to the known structure-dependent frequency response of the vasculature and to the fact that hemoglobin is a principal contrast feature of the vasculature at near-infrared wavelengths. To accomplish this, it is necessary to generate a time series of image data. In this report we have tested the hypothesis that through analysis of time-series data, independent contrast features can be derived that serve to validate, at least qualitatively, the accuracy of imaging data, in effect establishing a self-referencing scheme. A significant finding is the observation that analysis of such data can produce high-contrast images that reveal features that are mainly obscured in individual image frames or in time-averaged image data. Given the central role of hemoglobin in tissue function, this finding suggests that a wealth of new features associated with vascular dynamics can be identified from the analysis of time-series image data.

Influence of Systematic Errors in Reference States on Image Quality and on Stability of Derived Information for dc Optical Imaging

Optical measurements of tissue can be performed in discrete, time-averaged, and time-varying data collection modes. This information can be evaluated to yield estimates of either absolute optical coefficient values or some relative change in these values compared with a defined state. In the case of time-varying data, additional analysis can be applied to define various dynamic features. Here we have explored the accuracy with which such information can be recovered from dense scattering media using linear perturbation theory, as a function of the accuracy of the reference medium that serves as the initial guess. Within the framework of diffusion theory and a first-order solution, we have observed the following inequality regarding the sensitivity of computed measures to inaccuracy in the reference medium: Absolute measures ? relative measures > dynamic measures. In fact, the fidelity of derived dynamic measures was striking; we observed that accurate measures of dynamic behavior could be defined even if the quality of the image data from which these measures were derived was comparatively modest. In other studies we identified inaccuracy in the estimates of the reference detector values, and not to corresponding errors in the image operators, as the primary factor responsible for instability of absolute measures. The significance of these findings for practical imaging studies of tissue is discussed.

Instrumentation and calibration protocol for imaging dynamic features in dense-scattering media by optical tomography

Instrumentation is described that is suitable for acquiring multisource, multidetector, time-series optical data at high sampling rates (up to 150 Hz) from tissues having arbitrary geometries. The design rationale, calibration protocol, and measured performance features are given for both a currently used, CCD-camera-based instrument and a new silicon-photodiode-based system under construction. Also shown are representative images that we reconstructed from data acquired in laboratory studies using the described CCD-based instrument.

Clinical characteristics of sudden death victims in heritable (chromosome 1p1-1q1) conduction and myocardial disease

OBJECTIVES

The purpose of this study was to identify the clinical characteristics of family members at risk of sudden death.

BACKGROUND

The significance of sudden death in heritable cardiac disorders with delayed expression is incompletely understood. Additional insights come from a four-decade experience of seven generations of a family of German origin with autosomal dominant (chromosome 1p1-1q1) cardiac conduction and myocardial disease.

METHODS AND RESULTS

A total of 38 family members (20 males; 18 females) were identified with sudden death. Twenty-eight family members (mean age 48+/-8 years) from earlier generations had no pacemaker at the time of sudden death. In this group, 15 subjects were asymptomatic prior to sudden death. Ten family members with sudden death, from later generations, had chronically implanted pacemakers for high grade atrioventricular block. This group was older (mean age 57+/-2 years), with decreased functional status (New York Heart Association class II to IV), enlarged left atria, dilated left ventricles with reduced systolic function and documented ventricular fibrillation in three members. Twenty-eight family members with sudden death were descendants of sib lineages 2 or 6; 21 family members with sudden death were offspring of a parent who also suffered sudden death.

CONCLUSION

Sudden death is an important late outcome in heritable (chromosome 1p1-1q1) cardiac conduction and myocardial disease. Pacemaker therapy is important for the treatment of symptomatic bradycardia, but it does not prevent sudden death. Family members who are beyond the third decade of life with reduced functional capacity, left ventricular dysfunction, pacemakers and who are the offspring of a parent with sudden death appear to be at greatest risk

Improved Reconstruction Algorithm for Luminescence Optical Tomography when Background Lumiphore is Present

We examine the impact of background lumiphore on image quality in luminescence optical tomography. A modification of a previously described algorithm [J. Chang, H. L. Graber, and R. L. Barbour, J. Opt. Soc. Am. A 14, 288-299 (1997); J. Chang, H. L. Graber, and R. L. Barbour, IEEE Trans. Biomed. Eng. 44, 810-822 (1997)] that estimates the background luminescence directly from the detector readings is developed. Numerical simulations were performed to calculate the diffusion-regime limiting form of forward-problem solutions for a specific test medium. We performed image reconstructions with and without white noise added to the detector readings, using both the original and the improved versions of the algorithm. The results indicate that the original version produces unsatisfactory reconstructions when background lumiphore is present, whereas the improved algorithm yields qualitatively better images, especially for small target-to-background luminescence yield ratios.

Dependence of image quality on image operator and noise for optical diffusion tomography

By applying linear perturbation theory to the radiation transport equation, the inverse problem of optical diffusion tomography can be reduced to a set of linear equations, Wμ=R, where W is the weight function, μ are the cross-section perturbations to be imaged, and R is the detector readings perturbations. We have studied the dependence of image quality on added systematic error and/or random noise in W and R. Tomographic data were collected from cylindrical phantoms, with and without added inclusions, using Monte Carlo methods. Image reconstruction was accomplished using a constrained conjugate gradient descent method. Results show that accurate images containing few artifacts are obtained when W is derived from a reference state whose optical thickness matches that of the unknown test medium. Comparable image quality was also obtained for unmatched W, but the location of the target becomes more inaccurate as the mismatch increases. Results of the noise study show that image quality is much more sensitive to noise in W than in R, and the impact of noise increases with the number of iterations. Images reconstructed after pure noise was substituted for R consistently contain large peaks clustered about the cylinder axis, which was an initially unexpected structure. In other words, random input produces a nonrandom output. This finding suggests that algorithms sensitive to the evolution of this feature could be developed to suppress noise effects. © 1998 Society of Photo-Optical Instrumentation Engineers.

Nonlinear effects of localized absorption perturbations on the light distribution in a turbid medium

A theoretical model of photon propagation in a scattering medium is presented, from which algebraic formulas for the detector-reading perturbations (delta R) produced by one or two localized perturbations in the macroscopic absorption cross section (delta mu a) are derived. Examination of these shows that when delta mu a is titrated from very small to large magnitudes in one voxel, the curve traced by the corresponding delta R values is a rectangular hyperbola. Furthermore, while delta Rinfinity identical to lim delta mu a-->infinity delta R is dependent on the location of the detector with respect to the source and the voxel, the ratio delta R/ delta Rinfinity is independent of the detector location. We also find that when delta mu a is varied in two voxels simultaneously, the quantity delta R (delta mu a,1 [symbol: see text] delta mu a,2) is a bilinear rational function of the delta mu aS. These results apply not only in the case of steady-state illumination and detection but to time-harmonic measurements as well. The validity of the theoretical formulas is demonstrated by applying them to the results of selected numerical diffusion computations. Potential applications of the derived expressions to image-reconstruction problems are discussed.

Imaging of fluorescence in highly scattering media

Two one-speed radiation transport equations coupled by a dynamic equation for the distribution of fluorophore electronic states are used to model the migration of excitation photons and emitted fluorescence photons. The conditions for producing appreciable levels of fluorophore in the excited state are studied, with the conclusion that minimal saturation occurs under the conditions applicable to tissue imaging. This simplifies the derivation of the frequency response and of the imaging operator for a time-harmonic excitation source. Several factors known to influence the fluorescence response-the concentration, mean lifetime and quantum yield of the fluorophore, and the modulation frequency of the excitatory source-are examined. Optimal sensitivity conditions are obtained by analyzing the fluorescence source strength as a function of the mean lifetime and modulation frequency. The dependence of demodulation of the fluorescent signal on the above factors is also examined. In complementary studies, transport-theory-based operators for imaging fluorophore distributions in a highly scattering medium are derived. Experimental data were collected by irradiating a cylindrical phantom containing one or two fluorophore-filled balloons with continuous wave laser light. The reconstruction results show that qualitatively and quantitatively good images can be obtained, with embedded objects accurately located and the fluorophore concentration correctly determined.

Iterative total least-squares image reconstruction algorithm for optical tomography by the conjugate gradient method

We present an iterative total least-squares algorithm for computing images of the interior structure of highly scattering media by using the conjugate gradient method. For imaging the dense scattering media in optical tomography, a perturbation approach has been described previously [Y. Wang et al., Proc. SPIE 1641, 58 (1992); R. L. Barbour et al., in Medical Optical Tomography: Functional Imaging and Monitoring (Society of Photo-Optical Instrumentation Engineers, Bellingham, Wash., 1993), pp. 87-120], which solves a perturbation equation of the form W delta x = delta I. In order to solve this equation, least-squares or regularized least-squares solvers have been used in the past to determine best fits to the measurement data delta I while assuming that the operator matrix W is accurate. In practice, errors also occur in the operator matrix. Here we propose an iterative total least-squares (ITLS) method that minimizes the errors in both weights and detector readings. Theoretically, the total least-squares (TLS) solution is given by the singular vector of the matrix [W/ delta I] associated with the smallest singular value. The proposed ITLS method obtains this solution by using a conjugate gradient method that is particularly suitable for very large matrices. Simulation results have shown that the TLS method can yield a significantly more accurate result than the least-squares method.

Optical imaging of anatomical maps derived from magnetic resonance images using time-independent optical sources

We present a model suitable for computing images of absorption cross sections of thick tissue structures illuminated at near infrared (NIR) wavelengths from tomographic projection data. Image reconstruction is accomplished by solving a system of linear equations derived from transport theory. Reconstruction results using different algebraic solvers are shown for anatomical maps of the breast, derived from magnetic resonance imaging data, containing two simulated pathologies, in which case qualitatively good reconstructions were obtained. Evaluation of magnetic resonance (MR) data to optimize NIR optical tomographic imaging methods and to assess the feasibility of a combined MR-optical measurement scheme is discussed.

Regularized progressive expansion algorithm for recovery of scattering media from time-resolved data

Reconstructions of the absorption cross sections of dense scattering media from time-resolved data are presented. A progressive expansion (PE) algorithm, similar to a layer-stripping, is developed to circumvent the underdeterminedness of the inverse problem. An overlapping scheme, which used detector readings from several consecutive time intervals, is introduced to reduce the propagation of reconstruction errors that occur at shallower depths. To reduce the sensitivity of the PE algorithm to noise a regularized progressive expansion (RPE) algorithm is proposed, which incorporates regularization techniques into the PE algorithm. The PE and the RPE algorithms are applied to the problem of image reconstruction from time-resolved data. The test media were isotropically scattering slabs containing one or two compact absorbers at different depths below the surface. The data were corrupted by additive white Gaussian noise with various strengths. The reconstruction results show that the PE and the RPE algorithms, when they are combined by proper overlapping, can effectively overcome the underdeterminedness of the inverse problem. The RPE algorithm yields reconstructions that are more accurate and more stable under the same noise level.

Luminescence optical tomography of dense scattering media

Using a set of coupled radiation transport equations, we derive image operators for luminescence optical tomography with which it is possible to reconstruct concentration and mean lifetime distribution from information obtained from dc and time-harmonic optical sources. Weight functions and detector readings were computed from analytic solutions of the diffusion equation and from numerical solutions of the transport equation by Monte Carlo methods. Detector readings were also obtained from experiments on vessels containing a balloon filled with dye embedded in an Intralipid suspension with dye in the background. Image reconstructions were performed by the conjugate gradient descent method and the simultaneous algebraic reconstruction technique with a positivity constraint. A concentration correction was developed in which the reconstructed concentration information is used in the mean-lifetime reconstruction. The results show that the target can be accurately located in both the simulated and the experimental cases, but quantitative inaccuracies are present. Observed errors include a shadowing effect in regions that have the lowest weight within the inclusion. Application of the concentration correction can significantly improve computational efficiency and reduce error in the mean-lifetime reconstructions.

Recovery of optical cross-section perturbations in dense-scattering media by transport-theory-based imaging operators and steady-state simulated data

We present a useful strategy for imaging perturbations of the macroscopic absorption cross section of dense-scattering media using steady-state light sources. A perturbation model based on transport theory is derived, and the inverse problem is simplified to a system of linear equations, WΔμ = ΔR, where W is the weight matrix, Δμ is a vector of the unknown perturbations, and ΔR is the vector of detector readings. Monte Carlo simulations compute the photon flux across the surfaces of phantoms containing simple or complex inhomogeneities. Calculation of the weight matrix is also based on the results of Monte Carlo simulations. Three reconstruction algorithms-conjugate gradient descent, projection onto convex sets, and the simultaneous algebraic reconstruction technique, with or without imposed positivity constraints-are used for image reconstruction. A rescaling technique that improves the conditioning of the weight matrix is also developed. Results show that the analysis of time-independent data by a perturbation model is capable of resolving the internal structure of a dense-scattering medium. Imposition of positivity constraints improves image quality at the cost of a reduced convergence rate. Use of the rescaling technique increases the initial rate of convergence, resulting in accurate images in a smaller number of iterations.

Sensitivity studies for imaging a spherical object embedded in a spherically symmetric, two-layer turbid medium with photon-density waves

We present analytic expressions for the amplitude and phase of photon-density waves in strongly scattering, spherically symmetric, two-layer media containing a spherical object. This layered structure is a crude model of multilayered tissues whose absorption and scattering coefficients lie within a range reported in the literature for most tissue types. The embedded object simulates a pathology, such as a tumor. The normal-mode-series method is employed to solve the inhomogeneous Helmholtz equation in spherical coordinates, with suitable boundary conditions. By comparing the total field at points in the outer layer at a fixed distance from the origin when the object is present and when it is absent, we evaluate the potential sensitivity of an optical imaging system to inhomogeneities in absorption and scattering. For four types of background media with different absorption and scattering properties, we determine the modulation frequency that achieves an optimal compromise between signal-detection reliability and sensitivity to the presence of an object, the minimum detectable object radius, and the smallest detectable change in the absorption and scattering coefficients for a fixed object size. Our results indicate that (l) enhanced sensitivity to the object is achieved when the outer layer is more absorbing or scattering than the inner layer; (2) sensitivity to the object increases with the modulation frequency, except when the outer layer is the more absorbing; (3) amplitude measurements are proportionally more sensitive to a change in absorption, phase measurements are proportionally more sensitive to a change in scattering, and phase measurements exhibit a much greater capacity for distinguishing an absorption perturbation from a scattering perturbation.

A gene defect that causes conduction system disease and dilated cardiomyopathy maps to chromosome 1p1-1q1

Longitudinal evaluation of a seven generation kindred with an inherited conduction system defect and dilated cardiomyopathy demonstrated autosomal dominant transmission of a progressive disorder that both perturbs atrioventricular conduction and depresses cardiac contractility. To elucidate the molecular genetic basis for this disorder, a genome-wide linkage analysis was performed. Polymorphic loci near the centromere of chromosome 1 demonstrated linkage to the disease locus (maximum multipoint lod score = 13.2 in the interval between D1S305 and D1S176). Based on the disease phenotype and map location we speculate that gap junction protein connexin 40 is a candidate for mutations that result in conduction system disease and dilated cardiomyopathy.

Evolution of a hereditary cardiac conduction and muscle disorder: a study involving a family with six generations affected

This study describes six generations of a family with autosomal dominant cardiac conduction system and myocardial disease with recognizable clinical stages. A 20 year follow-up of nine family members, a medical questionnaire of 196, electrocardiographic screening of 91, noninvasive testing of 20, and catheterization with endomyocardial biopsy of six are the basis of this report. The clinical stages are as follows: Stage I occurs in the second and third decades of life and is characterized by an absence of symptoms, normal heart size, sinus bradycardia, and premature atrial contractions. Stage II is marked by first-degree atrioventricular block in the third and fourth decades. Stage III occurs in the fourth and fifth decades and is accompanied by chest pain, fatigue, lightheadedness, and advanced atrioventricular block followed by the development of atrial fibrillation or flutter. Stage IV, in the fifth and sixth decades of life, is characterized by congestive heart failure and recurrent ventricular arrhythmias. Light microscopy of right ventricular endomyocardial biopsy specimens from patients in stage II revealed very mild fibrosis; electron microscopy of the specimens demonstrated mild dilatation of tubules, mitochondrial swelling, and minimal myofibrillar loss. Biopsy specimens from patients with stage III disease were similar to those from patients with stage II disease except for an increase of myofibrillar loss. The stage IV specimens had diffuse fibrosis and more severe tubular dilatation, mitochondrial cristolysis, and myofibrillar loss. At autopsy in the proband, the atrial changes were more severe than the ventricular and were especially marked in the sinoatrial and atrial myocardium. Early recognition of the disease and use of pacemakers and antiarrhythmic agents have proved beneficial for affected family members. Thorough family studies of patients with conduction system disease and/or dilated cardiomyopathy are necessary to better understand the hereditary basis and natural course of this category of disease.

Calcification of the mitral annulus: etiology, clinical associations, complications and therapy

This report reviews the clinical features of 80 patients with roentgenographically proved mitral annular calcification. The mean age of the group was 73 years, and there was a 2.5 to 1 female to male ratio. Evaluation for underlying cardiovascular disease revealed six patients with severe calcific valvular aortic stenosis; five patients with hypertrophic cardiomyopathy, 11 with mitral prolapse and 33 with significant arterial hypertension (blood pressure greater or equal to 150/96 mm Hg). Eighty-five per cent of the group (68 of 80 patients) had an underlying cardiac disorder associated with either chronically increased left ventricular systolic pressure or abnormal leaflet motion. Other cardiovascular abnormalities occurring as complications secondary to the mitral ring calcification included subacute bacterial endocarditis (three cases), arterial emboli (five episodes) and high grade atrioventricular block (16 cases). Twelve patients had severe mitral regurgitation; successful mitral valve replacement was carried out in four patients (all with myxomatous mitral tissue). Evidence of diffuse conduction system disease, not limited to the area of the cardiac fibrous skeleton, was found frequently (44 patients). Nine patients had sinus node dysfunction and 35 patients had electrocardiographic evidence of distal intraventricular (fascicular) block. Twenty-one patients eventually required pacemakers for management of symptomatic bradyarrhythmias. Atrial fibrillation was present in 23 patients. In this review it was found that calcification of the mitral annulus is frequently associated with or induces serious cardiovascular disease. Since some of these disorders may be modified by appropriate therapy, calcification of the mitral annulus should no longer be ignored as a benign marker of the elderly heart.