Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction

What are the true volumes of SEGA tumors? Reliability of planimetric and popular semi-automated image segmentation methods

OBJECTIVE

To evaluate the reliability of the standard planimetric methodology of volumetric analysis and three different open-source semi-automated approaches of brain tumor segmentation.

MATERIALS AND METHODS

The volumes of subependymal giant cell astrocytomas (SEGA) examined by 30 MRI studies of 10 patients from a previous everolimus-related trial (EMINENTS study) were estimated using four methods: planimetric method (modified MacDonald ellipsoid method), ITK-Snap (pixel clustering, geodesic active contours, region competition methods), 3D Slicer (level-set thresholding), and NIRFast (k-means clustering, Markov random fields). The methods were compared, and a trial simulation was performed to determine how the choice of approach could influence the final decision about progression or response.

RESULTS

Intraclass correlation coefficient was high (0.95; 95% CI 0.91-0.98). The planimetric method always overestimated the size of the tumor, while virtually no mean difference was found between ITK-Snap and 3D Slicer (P = 0.99). NIRFast underestimated the volume and presented a proportional bias. During the trial simulation, a moderate level of agreement between all the methods (kappa 0.57-0.71, P < 0.002) was noted.

CONCLUSION

Semi-automated segmentation can ease oncological follow-up but the moderate level of agreement between segmentation methods suggests that the reference standard volumetric method for SEGA tumors should be revised and chosen carefully, as the selection of volumetry tool may influence the conclusion about tumor progression or response.

Cerenkov luminescence imaging: physics principles and potential applications in biomedical sciences

Cerenkov luminescence imaging (CLI) is a novel imaging modality to study charged particles with optical methods by detecting the Cerenkov luminescence produced in tissue. This paper first describes the physical processes that govern the production and transport in tissue of Cerenkov luminescence. The detectors used for CLI and their most relevant specifications to optimize the acquisition of the Cerenkov signal are then presented, and CLI is compared with the other optical imaging modalities sharing the same data acquisition and processing methods. Finally, the scientific work related to CLI and the applications for which CLI has been proposed are reviewed. The paper ends with some considerations about further perspectives for this novel imaging modality.

Mixed Total Variation and L1 Regularization Method for Optical Tomography Based on Radiative Transfer Equation

Optical tomography is an emerging and important molecular imaging modality. The aim of optical tomography is to reconstruct optical properties of human tissues. In this paper, we focus on reconstructing the absorption coefficient based on the radiative transfer equation (RTE). It is an ill-posed parameter identification problem. Regularization methods have been broadly applied to reconstruct the optical coefficients, such as the total variation (TV) regularization and the L¹ regularization. In order to better reconstruct the piecewise constant and sparse coefficient distributions, TV and L¹ norms are combined as the regularization. The forward problem is discretized with the discontinuous Galerkin method on the spatial space and the finite element method on the angular space. The minimization problem is solved by a Jacobian-based Levenberg-Marquardt type method which is equipped with a split Bregman algorithms for the L¹ regularization. We use the adjoint method to compute the Jacobian matrix which dramatically improves the computation efficiency. By comparing with the other imaging reconstruction methods based on TV and L¹ regularizations, the simulation results show the validity and efficiency of the proposed method.

Systematic study of target localization for bioluminescence tomography guided radiation therapy

PURPOSE

To overcome the limitation of CT/cone-beam CT (CBCT) in guiding radiation for soft tissue targets, the authors developed a spectrally resolved bioluminescence tomography (BLT) system for the small animal radiation research platform. The authors systematically assessed the performance of the BLT system in terms of target localization and the ability to resolve two neighboring sources in simulations, tissue-mimicking phantom, and in vivo environments.

METHODS

Multispectral measurements acquired in a single projection were used for the BLT reconstruction. The incomplete variables truncated conjugate gradient algorithm with an iterative permissible region shrinking strategy was employed as the optimization scheme to reconstruct source distributions. Simulation studies were conducted for single spherical sources with sizes from 0.5 to 3 mm radius at depth of 3-12 mm. The same configuration was also applied for the double source simulation with source separations varying from 3 to 9 mm. Experiments were performed in a standalone BLT/CBCT system. Two self-illuminated sources with 3 and 4.7 mm separations placed inside a tissue-mimicking phantom were chosen as the test cases. Live mice implanted with single-source at 6 and 9 mm depth, two sources at 3 and 5 mm separation at depth of 5 mm, or three sources in the abdomen were also used to illustrate the localization capability of the BLT system for multiple targets in vivo.

RESULTS

For simulation study, approximate 1 mm accuracy can be achieved at localizing center of mass (CoM) for single-source and grouped CoM for double source cases. For the case of 1.5 mm radius source, a common tumor size used in preclinical study, their simulation shows that for all the source separations considered, except for the 3 mm separation at 9 and 12 mm depth, the two neighboring sources can be resolved at depths from 3 to 12 mm. Phantom experiments illustrated that 2D bioluminescence imaging failed to distinguish two sources, but BLT can provide 3D source localization with approximately 1 mm accuracy. The in vivo results are encouraging that 1 and 1.7 mm accuracy can be attained for the single-source case at 6 and 9 mm depth, respectively. For the 2 sources in vivo study, both sources can be distinguished at 3 and 5 mm separations, and approximately 1 mm localization accuracy can also be achieved.

CONCLUSIONS

This study demonstrated that their multispectral BLT/CBCT system could be potentially applied to localize and resolve multiple sources at wide range of source sizes, depths, and separations. The average accuracy of localizing CoM for single-source and grouped CoM for double sources is approximately 1 mm except deep-seated target. The information provided in this study can be instructive to devise treatment margins for BLT-guided irradiation. These results also suggest that the 3D BLT system could guide radiation for the situation with multiple targets, such as metastatic tumor models.

Diffuse optical tomography for breast cancer imaging guided by computed tomography: A feasibility study

Diffuse optical tomography (DOT) has attracted attentions in the last two decades due to its intrinsic sensitivity in imaging chromophores of tissues such as hemoglobin, water, and lipid. However, DOT has not been clinically accepted yet due to its low spatial resolution caused by strong optical scattering in tissues. Structural guidance provided by an anatomical imaging modality enhances the DOT imaging substantially. Here, we propose a computed tomography (CT) guided multispectral DOT imaging system for breast cancer imaging. To validate its feasibility, we have built a prototype DOT imaging system which consists of a laser at the wavelength of 650 nm and an electron multiplying charge coupled device (EMCCD) camera. We have validated the CT guided DOT reconstruction algorithms with numerical simulations and phantom experiments, in which different imaging setup parameters, such as projection number of measurements and width of measurement patch, have been investigated. Our results indicate that an air-cooling EMCCD camera is good enough for the transmission mode DOT imaging. We have also found that measurements at six angular projections are sufficient for DOT to reconstruct the optical targets with 2 and 4 times absorption contrast when the CT guidance is applied. Finally, we have described our future research plan on integration of a multispectral DOT imaging system into a breast CT scanner.

Raman spectroscopy detects distant invasive brain cancer cells centimeters beyond MRI capability in humans

Surgical treatment of brain cancer is limited by the inability of current imaging capabilities such as magnetic resonance imaging (MRI) to detect the entirety of this locally invasive cancer. This results in residual cancer cells remaining following surgery, leading to recurrence and death. We demonstrate that intraoperative Raman spectroscopy can detect invasive cancer cells centimeters beyond pathological T1-contrast-enhanced and T2-weighted MRI signals. This intraoperative optical guide can be used to detect invasive cancer cells and minimize post-surgical cancer burden. The detection of distant invasive cancer cells beyond MRI signal has the potential to increase the effectiveness of surgery and directly lengthen patient survival.

Evaluation of On- and Off-Line Bioluminescence Tomography System for Focal Irradiation Guidance

In response to the limitations of computed tomography (CT) and cone-beam CT (CBCT) in irradiation guidance, especially for soft-tissue targets without the use of contrast agents, our group developed a solution that implemented bioluminescence tomography (BLT) as the image-guidance modality for preclinical radiation research. However, adding such a system to existing small animal irradiators is no small task. A potential solution is to utilize an off-line BLT system in close proximity to the irradiator, with stable and effective animal transport between the two systems. In this study, we investigated the localization accuracy of an off-line BLT system when used for the small animal radiation research platform (SARRP) and compared the results with those of an on-line system. The CBCT was equipped on both the off-line BLT system and the SARRP, with a distance of 5 m between them. To evaluate the setup error during animal transport between the two systems, the mice underwent CBCT imaging on the SARRP and were then transported to the off-line system for a second CBCT imaging session. The normalized intensity difference of the two images and the corresponding histogram and correlation were computed to evaluate if the transport process perturbed animal positioning. Strong correlation (correlation coefficients >0.95) between the SARRP and the off-line mouse CBCT was observed. The offset of the implanted light source center can be maintained within 0.2 mm during transport. To compare the target localization accuracy using the on-line SARRP BLT and the off-line system, a self-illuminated bioluminescent source was implanted in the abdomen of anesthetized mice. In addition to the application for dose calculation, CBCT imaging was also employed to generate the mesh grid of the imaged mouse for BLT reconstruction. Two scenarios were devised and compared, which involved localization of the luminescence source based on either: 1. on-line SARRP bioluminescence image and CBCT; or 2. off-line bioluminescence image and SARRP CBCT. The first scenario is assumed to have the least setup error, because no animal transport was involved. The second scenario examines if an off-line BLT system, with the mesh generated from the SARRP CBCT, can be used to guide SARRP irradiation when there is minimal target contrast in CBCT. Stability during animal transport between the two systems was maintained. The center of mass (CoM) of the light source reconstructed by the off-line BLT had an offset of 1.0 ± 0.4 mm from the true CoM derived from the SARRP CBCT. These results are comparable to the offset of 1.0 ± 0.2 mm using on-line BLT. With CBCT information provided by the SARRP and effective animal immobilization during transport, these findings support the utilization of an off-line BLT-guided system, in close proximity to the SARRP, for accurate soft-tissue target localization. In addition, a dedicated standalone BLT system for our partner site at the University of Pennsylvania was introduced in this study.

Development of a multi-wavelength diffuse optical tomography system for early diagnosis of rheumatoid arthritis: simulation, phantoms and healthy human studies

A multi-wavelength diffuse optical tomography (DOT) system has been developed to directly extract physiological information, such as total haemoglobin concentration, from tissue in human hand joints. Novel methods for 3D surface imaging and spectrally constrained image reconstruction are introduced and their potential application to imaging of rheumatoid arthritis is discussed. Results are presented from simulation studies as well as experiments using phantoms and data from imaging of three healthy volunteers. The image features are recovered partially for phantom data using transmission measurements only. Images that reveal joint regions and surrounding features within the hand are shown to co-register with co-acquired ultrasound images which are shown to be related to total haemoglobin concentration.

Joint blood flow is more sensitive to inflammatory arthritis than oxyhemoglobin, deoxyhemoglobin, and oxygen saturation

Joint hypoxia plays a central role in the progression and perpetuation of rheumatoid arthritis (RA). Thus, optical techniques that can measure surrogate markers of hypoxia such as blood flow, oxyhemoglobin, deoxyhemoglobin, and oxygen saturation are being developed to monitor RA. The purpose of the current study was to compare the sensitivity of these physiological parameters to arthritis. Experiments were conducted in a rabbit model of RA and the results revealed that joint blood flow was the most sensitive to arthritis and could detect a statistically significant difference (p<0.05, power = 0.8) between inflamed and healthy joints with a sample size of only four subjects. Considering that this a quantitative technique, the high sensitivity to arthritis suggests that joint perfusion has the potential to become a potent tool for monitoring disease progression and treatment response in RA.

Quantitative photoacoustic image reconstruction improves accuracy in deep tissue structures

Photoacoustic imaging (PAI) is emerging as a potentially powerful imaging tool with multiple applications. Image reconstruction for PAI has been relatively limited because of limited or no modeling of light delivery to deep tissues. This work demonstrates a numerical approach to quantitative photoacoustic image reconstruction that minimizes depth and spectrally derived artifacts. We present the first time-domain quantitative photoacoustic image reconstruction algorithm that models optical sources through acoustic data to create quantitative images of absorption coefficients. We demonstrate quantitative accuracy of less than 5% error in large 3 cm diameter 2D geometries with multiple targets and within 22% error in the largest size quantitative photoacoustic studies to date (6cm diameter). We extend the algorithm to spectral data, reconstructing 6 varying chromophores to within 17% of the true values. This quantitiative PA tomography method was able to improve considerably on filtered-back projection from the standpoint of image quality, absolute, and relative quantification in all our simulation geometries. We characterize the effects of time step size, initial guess, and source configuration on final accuracy. This work could help to generate accurate quantitative images from both endogenous absorbers and exogenous photoacoustic dyes in both preclinical and clinical work, thereby increasing the information content obtained especially from deep-tissue photoacoustic imaging studies.

Automated data selection method to improve robustness of diffuse optical tomography for breast cancer imaging

Imaging-guided near infrared diffuse optical tomography (DOT) has demonstrated a great potential as an adjunct modality for differentiation of malignant and benign breast lesions and for monitoring treatment response of breast cancers. However, diffused light measurements are sensitive to artifacts caused by outliers and errors in measurements due to probe-tissue coupling, patient and probe motions, and tissue heterogeneity. In general, pre-processing of the measurements is needed by experienced users to manually remove these outliers and therefore reduce imaging artifacts. An automated method of outlier removal, data selection, and filtering for diffuse optical tomography is introduced in this manuscript. This method consists of multiple steps to first combine several data sets collected from the same patient at contralateral normal breast and form a single robust reference data set using statistical tests and linear fitting of the measurements. The second step improves the perturbation measurements by filtering out outliers from the lesion site measurements using model based analysis. The results of 20 malignant and benign cases show similar performance between manual data processing and automated processing and improvement in tissue characterization of malignant to benign ratio by about 27%.

Time resolved diffuse optical spectroscopy with geometrically accurate models for bulk parameter recovery

A novel straightforward, accessible and efficient approach is presented for performing hyperspectral time-domain diffuse optical spectroscopy to determine the optical properties of samples accurately using geometry specific models. To allow bulk parameter recovery from measured spectra, a set of libraries based on a numerical model of the domain being investigated is developed as opposed to the conventional approach of using an analytical semi-infinite slab approximation, which is known and shown to introduce boundary effects. Results demonstrate that the method improves the accuracy of derived spectrally varying optical properties over the use of the semi-infinite approximation.

Non-invasive diffuse correlation tomography reveals spatial and temporal blood flow differences in murine bone grafting approaches

Longitudinal blood flow during murine bone graft healing was monitored non-invasively using diffuse correlation tomography. The system utilized spatially dense data from a scanning set-up, non-linear reconstruction, and micro-CT anatomical information. Weekly in vivo measurements were performed. Blood flow changes in autografts, which heal successfully, were localized to graft regions and consistent across mice. Poor healing allografts showed heterogeneous blood flow elevation and high inter-subject variabilities. Allografts with tissue-engineered periosteum showed responses intermediate to both autografts and allografts, consistent with healing observed. These findings suggest that spatiotemporal blood flow changes can be utilized to differentiate the degree of bone graft healing.

Improving the quantitative accuracy of cerebral oxygen saturation in monitoring the injured brain using atlas based Near Infrared Spectroscopy models

The application of Near Infrared Spectroscopy (NIRS) for the monitoring of the cerebral oxygen saturation within the brain is well established, albeit using temporal data that can only measure relative changes of oxygenation state of the brain from a baseline. The focus of this investigation is to demonstrate that hybridisation of existing near infrared probe designs and reconstruction techniques can pave the way to produce a system and methods that can be used to monitor the absolute oxygen saturation in the injured brain. Using registered Atlas models in simulation, a novel method is outlined by which the quantitative accuracy and practicality of NIRS for specific use in monitoring the injured brain, can be improved, with cerebral saturation being recovered to within 10.1 ± 1.8% of the expected values.

Portable, parallel 9-wavelength near-infrared spectral tomography (NIRST) system for efficient characterization of breast cancer within the clinical oncology infusion suite

A portable near-infrared spectral tomography (NIRST) system was developed with simultaneous frequency domain (FD) and continuous-wave (CW) optical measurements for efficient characterization of breast cancer in a clinical oncology setting. Simultaneous FD and CW recordings were implemented to speed up acquisition to 3 minutes for all 9 wavelengths, spanning a range from 661nm to 1064nm. An adjustable interface was designed to fit various breast sizes and shapes. Spatial images of oxy- and deoxy-hemoglobin, water, lipid, and scattering components were reconstructed using a 2D FEM approach. The system was tested on a group of 10 normal subjects, who were examined bilaterally and the recovered optical images were compared to radiographic breast density. Significantly higher total hemoglobin and water were estimated in the high density relative to low density groups. One patient with invasive ductal carcinoma was also examined and the cancer region was characterized as having a contrast ratio of 1.4 in total hemoglobin and 1.2 in water.

Speckle contrast diffuse correlation tomography of complex turbid medium flow

PURPOSE

Developed herein is a three-dimensional (3D) flow contrast imaging system leveraging advancements in the extension of laser speckle contrast imaging theories to deep tissues along with our recently developed finite-element diffuse correlation tomography (DCT) reconstruction scheme. This technique, termed speckle contrast diffuse correlation tomography (scDCT), enables incorporation of complex optical property heterogeneities and sample boundaries. When combined with a reflectance-based design, this system facilitates a rapid segue into flow contrast imaging of larger, in vivo applications such as humans.

METHODS

A highly sensitive CCD camera was integrated into a reflectance-based optical system. Four long-coherence laser source positions were coupled to an optical switch for sequencing of tomographic data acquisition providing multiple projections through the sample. This system was investigated through incorporation of liquid and solid tissue-like phantoms exhibiting optical properties and flow characteristics typical of human tissues. Computer simulations were also performed for comparisons. A uniquely encountered smear correction algorithm was employed to correct point-source illumination contributions during image capture with the frame-transfer CCD and reflectance setup.

RESULTS

Measurements with scDCT on a homogeneous liquid phantom showed that speckle contrast-based deep flow indices were within 12% of those from standard DCT. Inclusion of a solid phantom submerged below the liquid phantom surface allowed for heterogeneity detection and validation. The heterogeneity was identified successfully by reconstructed 3D flow contrast tomography with scDCT. The heterogeneity center and dimensions and averaged relative flow (within 3%) and localization were in agreement with actuality and computer simulations, respectively.

CONCLUSIONS

A custom cost-effective CCD-based reflectance 3D flow imaging system demonstrated rapid acquisition of dense boundary data and, with further studies, a high potential for translatability to real tissues with arbitrary boundaries. A requisite correction was also found for measurements in the fashion of scDCT to recover accurate speckle contrast of deep tissues.

Dimensionality Reduction Based Optimization Algorithm for Sparse 3-D Image Reconstruction in Diffuse Optical Tomography

Diffuse optical tomography (DOT) is a relatively low cost and portable imaging modality for reconstruction of optical properties in a highly scattering medium, such as human tissue. The inverse problem in DOT is highly ill-posed, making reconstruction of high-quality image a critical challenge. Because of the nature of sparsity in DOT, sparsity regularization has been utilized to achieve high-quality DOT reconstruction. However, conventional approaches using sparse optimization are computationally expensive and have no selection criteria to optimize the regularization parameter. In this paper, a novel algorithm, Dimensionality Reduction based Optimization for DOT (DRO-DOT), is proposed. It reduces the dimensionality of the inverse DOT problem by reducing the number of unknowns in two steps and thereby makes the overall process fast. First, it constructs a low resolution voxel basis based on the sensing-matrix properties to find an image support. Second, it reconstructs the sparse image inside this support. To compensate for the reduced sensitivity with increasing depth, depth compensation is incorporated in DRO-DOT. An efficient method to optimally select the regularization parameter is proposed for obtaining a high-quality DOT image. DRO-DOT is also able to reconstruct high-resolution images even with a limited number of optodes in a spatially limited imaging set-up.

Radiative transfer equation modeling by streamline diffusion modified continuous Galerkin method

Optical tomography has a wide range of biomedical applications. Accurate prediction of photon transport in media is critical, as it directly affects the accuracy of the reconstructions. The radiative transfer equation (RTE) is the most accurate deterministic forward model, yet it has not been widely employed in practice due to the challenges in robust and efficient numerical implementations in high dimensions. Herein, we propose a method that combines the discrete ordinate method (DOM) with a streamline diffusion modified continuous Galerkin method to numerically solve RTE. Additionally, a phase function normalization technique was employed to dramatically reduce the instability of the DOM with fewer discrete angular points. To illustrate the accuracy and robustness of our method, the computed solutions to RTE were compared with Monte Carlo (MC) simulations when two types of sources (ideal pencil beam and Gaussian beam) and multiple optical properties were tested. Results show that with standard optical properties of human tissue, photon densities obtained using RTE are, on average, around 5% of those predicted by MC simulations in the entire/deeper region. These results suggest that this implementation of the finite element method-RTE is an accurate forward model for optical tomography in human tissues.

Combining energy and Laplacian regularization to accurately retrieve the depth of brain activity of diffuse optical tomographic data

Diffuse optical tomography (DOT) provides data about brain function using surface recordings. Despite recent advancements, an unbiased method for estimating the depth of absorption changes and for providing an accurate three-dimensional (3-D) reconstruction remains elusive. DOT involves solving an ill-posed inverse problem, requiring additional criteria for finding unique solutions. The most commonly used criterion is energy minimization (energy constraint). However, as measurements are taken from only one side of the medium (the scalp) and sensitivity is greater at shallow depths, the energy constraint leads to solutions that tend to be small and superficial. To correct for this bias, we combine the energy constraint with another criterion, minimization of spatial derivatives (Laplacian constraint, also used in low resolution electromagnetic tomography, LORETA). Used in isolation, the Laplacian constraint leads to solutions that tend to be large and deep. Using simulated, phantom, and actual brain activation data, we show that combining these two criteria results in accurate (error <2 mm) absorption depth estimates, while maintaining a two-point spatial resolution of <24 mm up to a depth of 30 mm. This indicates that accurate 3-D reconstruction of brain activity up to 30 mm from the scalp can be obtained with DOT.

Fast multislice fluorescence molecular tomography using sparsity-inducing regularization

Fluorescence molecular tomography (FMT) is a rapidly growing imaging method that facilitates the recovery of small fluorescent targets within biological tissue. The major challenge facing the FMT reconstruction method is the ill-posed nature of the inverse problem. In order to overcome this problem, the acquisition of large FMT datasets and the utilization of a fast FMT reconstruction algorithm with sparsity regularization have been suggested recently. Therefore, the use of a joint L1/total-variation (TV) regularization as a means of solving the ill-posed FMT inverse problem is proposed. A comparative quantified analysis of regularization methods based on L1-norm and TV are performed using simulated datasets, and the results show that the fast composite splitting algorithm regularization method can ensure the accuracy and robustness of the FMT reconstruction. The feasibility of the proposed method is evaluated in an in vivo scenario for the subcutaneous implantation of a fluorescent-dye-filled capillary tube in a mouse, and also using hybrid FMT and x-ray computed tomography data. The results show that the proposed regularization overcomes the difficulties created by the ill-posed inverse problem.

Bioluminescence Tomography-Guided Radiation Therapy for Preclinical Research

PURPOSE

In preclinical radiation research, it is challenging to localize soft tissue targets based on cone beam computed tomography (CBCT) guidance. As a more effective method to localize soft tissue targets, we developed an online bioluminescence tomography (BLT) system for small-animal radiation research platform (SARRP). We demonstrated BLT-guided radiation therapy and validated targeting accuracy based on a newly developed reconstruction algorithm.

METHODS AND MATERIALS

The BLT system was designed to dock with the SARRP for image acquisition and to be detached before radiation delivery. A 3-mirror system was devised to reflect the bioluminescence emitted from the subject to a stationary charge-coupled device (CCD) camera. Multispectral BLT and the incomplete variables truncated conjugate gradient method with a permissible region shrinking strategy were used as the optimization scheme to reconstruct bioluminescent source distributions. To validate BLT targeting accuracy, a small cylindrical light source with high CBCT contrast was placed in a phantom and also in the abdomen of a mouse carcass. The center of mass (CoM) of the source was recovered from BLT and used to guide radiation delivery. The accuracy of the BLT-guided targeting was validated with films and compared with the CBCT-guided delivery. In vivo experiments were conducted to demonstrate BLT localization capability for various source geometries.

RESULTS

Online BLT was able to recover the CoM of the embedded light source with an average accuracy of 1 mm compared to that with CBCT localization. Differences between BLT- and CBCT-guided irradiation shown on the films were consistent with the source localization revealed in the BLT and CBCT images. In vivo results demonstrated that our BLT system could potentially be applied for multiple targets and tumors.

CONCLUSIONS

The online BLT/CBCT/SARRP system provides an effective solution for soft tissue targeting, particularly for small, nonpalpable, or orthotopic tumor models.

Non-Invasive Monitoring of Temporal and Spatial Blood Flow during Bone Graft Healing Using Diffuse Correlation Spectroscopy

Vascular infiltration and associated alterations in microvascular blood flow are critical for complete bone graft healing. Therefore, real-time, longitudinal measurement of blood flow has the potential to successfully predict graft healing outcomes. Herein, we non-invasively measure longitudinal blood flow changes in bone autografts and allografts using diffuse correlation spectroscopy in a murine femoral segmental defect model. Blood flow was measured at several positions proximal and distal to the graft site before implantation and every week post-implantation for a total of 9 weeks (autograft n = 7 and allograft n = 10). Measurements of the ipsilateral leg with the graft were compared with those of the intact contralateral control leg. Both autografts and allografts exhibited an initial increase in blood flow followed by a gradual return to baseline levels. Blood flow elevation lasted up to 2 weeks in autografts, but this duration varied from 2 to 6 weeks in allografts depending on the spatial location of the measurement. Intact contralateral control leg blood flow remained at baseline levels throughout the 9 weeks in the autograft group; however, in the allograft group, blood flow followed a similar trend to the graft leg. Blood flow difference between the graft and contralateral legs (ΔrBF), a parameter defined to estimate graft-specific changes, was elevated at 1–2 weeks for the autograft group, and at 2–4 weeks for the allograft group at the proximal and the central locations. However, distal to the graft, the allograft group exhibited significantly greater ΔrBF than the autograft group at 3 weeks post-surgery (p < 0.05). These spatial and temporal differences in blood flow supports established trends of delayed healing in allografts versus autografts.

Evaluating real-time image reconstruction in diffuse optical tomography using physiologically realistic test data

In diffuse optical tomography (DOT), real-time image reconstruction of oxy- and deoxy-haemoglobin changes occurring in the brain could give valuable information in clinical care settings. Although non-linear reconstruction techniques could provide more accurate results, their computational burden makes them unsuitable for real-time applications. Linear techniques can be employed under the assumption that the expected change in absorption is small. Several approaches exist, differing primarily in their handling of regularization and the noise statistics. In real experiments, it is impossible to compute the true noise statistics, because of the presence of physiological oscillations in the measured data. This is even more critical in real-time applications, where no off-line filtering and averaging can be performed to reduce the noise level. Therefore, many studies substitute the noise covariance matrix with the identity matrix. In this paper, we examined two questions: does using the noise model with realistic, imperfect data yield an improvement in image quality compared to using the identity matrix; and what is the difference in quality between online and offline reconstructions. Bespoke test data were created using a novel process through which simulated changes in absorption were added to real resting-state DOT data. A realistic multi-layer head model was used as the geometry for the reconstruction. Results validated our assumptions, highlighting the validity of computing the noise statistics from the measured data for online image reconstruction, which was performed at 2 Hz. Our results can be directly extended to a real application where real-time imaging is required.

Calibration and optimization of 3D digital breast tomosynthesis guided near infrared spectral tomography

Calibration of a three-dimensional multimodal digital breast tomosynthesis (DBT) x-ray and non-fiber based near infrared spectral tomography (NIRST) system is challenging but essential for clinical studies. Phantom imaging results yielded linear contrast recovery of total hemoglobin (HbT) concentration for cylindrical inclusions of 15 mm, 10 mm and 7 mm with a 3.5% decrease in the HbT estimate for each 1 cm increase in inclusion depth. A clinical exam of a patient's breast containing both benign and malignant lesions was successfully imaged, with greater HbT was found in the malignancy relative to the benign abnormality and fibroglandular regions (11 μM vs. 9.5 μM). Tools developed improved imaging system characterization and optimization of signal quality, which will ultimately improve patient selection and subsequent clinical trial results.

Comprehensive analytical model for CW laser induced heat in turbid media

In this work, we present a new analytical approach to model continuous wave laser induced temperature in highly homogeneous turbid media. First, the diffusion equation is used to model light transport and a comprehensive solution is derived analytically by obtaining a special Greens' function. Next, the time-dependent bio-heat equation is used to describe the induced heat increase and propagation within the medium. The bio-heat equation is solved analytically utilizing the separation of variables technique. Our theoretical model is successfully validated using numerical simulations and experimental studies with agarose phantoms and ex-vivo chicken breast samples. The encouraging results show that our method can be implemented as a simulation tool to determine important laser parameters that govern the magnitude of temperature rise within homogenous biological tissue or organs.

Fast and efficient image reconstruction for high density diffuse optical imaging of the human brain

Real-time imaging of human brain has become an important technique within neuroimaging. In this study, a fast and efficient sensitivity map generation based on Finite Element Models (FEM) is developed which utilises a reduced sensitivitys matrix taking advantage of sparsity and parallelisation processes. Time and memory efficiency of these processes are evaluated and compared with conventional method showing that for a range of mesh densities from 50000 to 320000 nodes, the required memory is reduced over tenfold and computational time fourfold allowing for near real-time image recovery.

Alignment of sources and detectors on breast surface for noncontact diffuse correlation tomography of breast tumors

Noncontact diffuse correlation tomography (ncDCT) is an emerging technology for 3D imaging of deep tissue blood flow distribution without distorting hemodynamic properties. To adapt the ncDCT for imaging in vivo breast tumors, we designed a motorized ncDCT probe to scan over the breast surface. A computer-aided design (CAD)-based approach was proposed to create solid volume mesh from arbitrary breast surface obtained by a commercial 3D camera. The sources and detectors of ncDCT were aligned on the breast surface through ray tracing to mimic the ncDCT scanning with CAD software. The generated breast volume mesh along with the boundary data of ncDCT at the aligned source and detector pairs were used for finite-element-method-based flow image reconstruction. We evaluated the accuracy of source alignments on mannequin and human breasts; largest alignment errors were less than 10% in both tangential and radial directions of scanning. The impact of alignment errors (assigned 10%) on the tumor reconstruction was estimated using computer simulations. The deviations of simulated tumor location and blood flow contrast resulted from the alignment errors were 0.77 mm (less than the node distance of 1 mm) and 1%, respectively, which result in minor impact on flow image reconstruction. Finally, a case study on a human breast tumor was conducted and a tumor-to-normal flow contrast was reconstructed, demonstrating the feasibility of ncDCT in clinical application.

Laser line illumination scheme allowing the reduction of background signal and the correction of absorption heterogeneities effects for fluorescence reflectance imaging

Intraoperative fluorescence imaging in reflectance geometry is an attractive imaging modality as it allows to noninvasively monitor the fluorescence targeted tumors located below the tissue surface. Some drawbacks of this technique are the background fluorescence decreasing the contrast and absorption heterogeneities leading to misinterpretations concerning fluorescence concentrations. We propose a correction technique based on a laser line scanning illumination scheme. We scan the medium with the laser line and acquire, at each position of the line, both fluorescence and excitation images. We then use the finding that there is a relationship between the excitation intensity profile and the background fluorescence one to predict the amount of signal to subtract from the fluorescence images to get a better contrast. As the light absorption information is contained both in fluorescence and excitation images, this method also permits us to correct the effects of absorption heterogeneities. This technique has been validated on simulations and experimentally. Fluorescent inclusions are observed in several configurations at depths ranging from 1 mm to 1 cm. Results obtained with this technique are compared with those obtained with a classical wide-field detection scheme for contrast enhancement and with the fluorescence by an excitation ratio approach for absorption correction.

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.

Direct regularization from co-registered anatomical images for MRI-guided near-infrared spectral tomographic image reconstruction

Combining anatomical information from high resolution imaging modalities to guide near-infrared spectral tomography (NIRST) is an efficient strategy for improving the quality of the reconstructed spectral images. A new approach for incorporating image information directly into the inversion matrix regularization was examined using Direct Regularization from Images (DRI), which encodes the gray-scale data into the NIRST image reconstruction problem. This process has the benefit of eliminating user intervention such as image segmentation of distinct regions. Specifically, the Dynamic Contrast Enhanced Magnetic Resonance (DCE-MR) image intensity value differences within the anatomical image were used to implement an exponentially-weighted regularization function between the image pixels. The algorithm was validated using simulated reconstructions with noise, and the results showed that spatial resolution and robustness of the reconstructed images were significantly improved by appropriate choice of the regularization weight parameters. The proposed approach was also tested on in vivo breast data acquired in a recent clinical trial combining NIRST / MRI for cancer tumor characterization. Relative to the standard "no priors" diffuse recovery, the contrast of the tumor to the normal surrounding tissue increased from 2.4 to 3.6, and the difference between the tumor size segmented from DCE-MR images and reconstructed optical images decreased from 18% to 6%, while there was an overall decrease in surface artifacts.

Noncontact diffuse correlation tomography of human breast tumor

Our first step to adapt our recently developed noncontact diffuse correlation tomography (ncDCT) system for three-dimensional (3-D) imaging of blood flow distribution in human breast tumors is reported. A commercial 3-D camera was used to obtain breast surface geometry, which was then converted to a solid volume mesh. An ncDCT probe scanned over a region of interest on the mesh surface and the measured boundary data were combined with a finite element framework for 3-D image reconstruction of blood flow distribution. This technique was tested in computer simulations and in vivo human breasts with low-grade carcinoma. Results from computer simulations suggest that relatively high accuracy can be achieved when the entire tumor is within the sensitive region of diffuse light. Image reconstruction with a priori knowledge of the tumor volume and location can significantly improve the accuracy in recovery of tumor blood flow contrasts. In vivo imaging results from two breast carcinomas show higher average blood flow contrasts (5.9- and 10.9-fold) in the tumor regions compared to the surrounding tissues, which are comparable with previous findings using diffuse correlation spectroscopy. The ncDCT system has the potential to image blood flow distributions in soft and vulnerable tissues without distorting tissue hemodynamics

Brain activation during neurocognitive testing using functional near-infrared spectroscopy in patients following concussion compared to healthy controls

There is no accepted clinical imaging modality for concussion, and current imaging modalities including fMRI, DTI, and PET are expensive and inaccessible to most clinics/patients. Functional near-infrared spectroscopy (fNIRS) is a non-invasive, portable, and low-cost imaging modality that can measure brain activity. The purpose of this study was to compare brain activity as measured by fNIRS in concussed and age-matched controls during the performance of cognitive tasks from a computerized neurocognitive test battery. Participants included nine currently symptomatic patients aged 18-45 years with a recent (15-45 days) sport-related concussion and five age-matched healthy controls. The participants completed a computerized neurocognitive test battery while wearing the fNIRS unit. Our results demonstrated reduced brain activation in the concussed subject group during word memory, (spatial) design memory, digit-symbol substitution (symbol match), and working memory (X's and O's) tasks. Behavioral performance (percent-correct and reaction time respectively) was lower for concussed participants on the word memory, design memory, and symbol match tasks than controls. The results of this preliminary study suggest that fNIRS could be a useful, portable assessment tool to assess reduced brain activation and augment current approaches to assessment and management of patients following concussion.

Evaluation of rigid registration methods for whole head imaging in diffuse optical tomography

Functional brain imaging has become an important neuroimaging technique for the study of brain organization and development. Compared to other imaging techniques, diffuse optical tomography (DOT) is a portable and low-cost technique that can be applied to infants and hospitalized patients using an atlas-based light model. For DOT imaging, the accuracy of the forward model has a direct effect on the resulting recovered brain function within a field of view and so the accuracy of the spatially normalized atlas-based forward models must be evaluated. Herein, the accuracy of atlas-based DOT is evaluated on models that are spatially normalized via a number of different rigid registration methods on 24 subjects. A multileveled approach is developed to evaluate the correlation of the geometrical and sensitivity accuracies across the full field of view as well as within specific functional subregions. Results demonstrate that different registration methods are optimal for recovery of different sets of functional brain regions. However, the "nearest point to point" registration method, based on the EEG 19 landmark system, is shown to be the most appropriate registration method for image quality throughout the field of view of the high-density cap that covers the whole of the optically accessible cortex.

Non-contact scanning diffuse correlation tomography system for three-dimensional blood flow imaging in a murine bone graft model

A non-contact galvanometer-based optical scanning system for diffuse correlation tomography was developed for monitoring bone graft healing in a murine femur model. A linear image reconstruction algorithm for diffuse correlation tomography was tested using finite-element method based simulated data and experimental data from a femur or a tube suspended in a homogeneous liquid phantom. Finally, the non-contact system was utilized to monitor in vivo blood flow changes prior to and one week after bone graft transplantation within murine femurs. Localized blood flow changes were observed in three mice, demonstrating a potential for quantification of longitudinal blood flow associated with bone graft healing.

Multigrid-based reconstruction algorithm for quantitative photoacoustic tomography

This paper proposes a multigrid inversion framework for quantitative photoacoustic tomography reconstruction. The forward model of optical fluence distribution and the inverse problem are solved at multiple resolutions. A fixed-point iteration scheme is formulated for each resolution and used as a cost function. The simulated and experimental results for quantitative photoacoustic tomography reconstruction show that the proposed multigrid inversion can dramatically reduce the required number of iterations for the optimization process without loss of reliability in the results.

Experimental Comparison of Continuous-Wave and Frequency-Domain Fluorescence Tomography in a Commercial Multi-Modal Scanner

The performance evaluation of a variety of small animal tomography measurement approaches and algorithms for recovery of fluorescent absorption cross section has not been conducted. Herein, we employed an intensified CCD system installed in a commercial small animal CT (Computed Tomography) scanner to compare image reconstructions from time-independent, continuous wave (CW) measurements and from time-dependent, frequency domain (FD) measurements in a series of physical phantoms specifically designed for evaluation. Comparisons were performed as a function of (1) number of projections, (2) the level of preprocessing filters used to improve the signal-to-noise ratio (SNR), (3) endogenous heterogeneity of optical properties, as well as in the cases of (4) two fluorescent targets and (5) a mouse-shaped phantom. Assessment of quantitative recovery of fluorescence absorption cross section was performed using a fully parallel, regularization-free, linear reconstruction algorithm with diffusion approximation (DA) and high order simplified spherical harmonics ( SPN) approximation to the radiative transport equation (RTE). The results show that while FD measurements may result in superior image reconstructions over CW measurements, data acquisition times are significantly longer, necessitating further development of multiple detector/source configurations, improved data read-out rates, and detector technology. FD measurements with SP3 reconstructions enabled better quantitative recovery of fluorescent target strength, but required increased computational expense. Despite the developed parallel reconstruction framework being able to achieve more than 60 times speed increase over sequential implementation, further development in faster parallel acceleration strategies for near-real time and real-time image recovery and more precise forward solution is necessary.

Mapping cortical responses to speech using high-density diffuse optical tomography

The functional neuroanatomy of speech processing has been investigated using positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) for more than 20years. However, these approaches have relatively poor temporal resolution and/or challenges of acoustic contamination due to the constraints of echoplanar fMRI. Furthermore, these methods are contraindicated because of safety concerns in longitudinal studies and research with children (PET) or in studies of patients with metal implants (fMRI). High-density diffuse optical tomography (HD-DOT) permits presenting speech in a quiet acoustic environment, has excellent temporal resolution relative to the hemodynamic response, and provides noninvasive and metal-compatible imaging. However, the performance of HD-DOT in imaging the brain regions involved in speech processing is not fully established. In the current study, we use an auditory sentence comprehension task to evaluate the ability of HD-DOT to map the cortical networks supporting speech processing. Using sentences with two levels of linguistic complexity, along with a control condition consisting of unintelligible noise-vocoded speech, we recovered a hierarchically organized speech network that matches the results of previous fMRI studies. Specifically, hearing intelligible speech resulted in increased activity in bilateral temporal cortex and left frontal cortex, with syntactically complex speech leading to additional activity in left posterior temporal cortex and left inferior frontal gyrus. These results demonstrate the feasibility of using HD-DOT to map spatially distributed brain networks supporting higher-order cognitive faculties such as spoken language.

MR-Guided Near-Infrared Spectral Tomography Increases Diagnostic Performance of Breast MRI

PURPOSE

The purpose of this study was to determine the diagnostically most important molecular biomarkers quantified by magnetic resonance-guided (MR) near-infrared spectral tomography (NIRST) that distinguish malignant breast lesions from benign abnormalities when combined with outcomes from clinical breast MRI.

EXPERIMENTAL DESIGN

The study was HIPAA compliant and approved by the Dartmouth Institutional Review Board, the NIH, the United States State Department, and Xijing Hospital. MR-guided NIRST evaluated hemoglobin, water, and lipid content in regions of interest defined by concurrent dynamic contrast-enhanced MRI (DCE-MRI) in the breast. MRI plus NIRST was performed in 44 subjects (median age, 46, age range, 20-81 years), 28 of whom had subsequent malignant pathologic diagnoses, and 16 had benign conditions. A subset of 30 subject examinations yielded optical data that met minimum sensitivity requirements to the suspicious lesion and were included in the analyses of diagnostic performance.

RESULTS

In the subset of 30 subject examinations meeting minimum optical data sensitivity criterion, the MR-guided NIRST separated malignant from benign lesions using total hemoglobin (HbT; P < 0.01) and tissue optical index (TOI; P < 0.001). Combined MRI plus TOI data caused one false positive and 1 false negative, and produced the best diagnostic performance, yielding an AUC of 0.95, sensitivity of 95%, specificity of 89%, positive predictive value of 95%, and negative predictive value of 89%, respectively.

CONCLUSIONS

MRI plus NIRST results correlated well with histopathologic diagnoses and could provide additional information to reduce the number of MRI-directed biopsies.

Improved sparse reconstruction for fluorescence molecular tomography with L1/2 regularization

Fluorescence molecular tomography (FMT) is a promising imaging technique that allows in vivo visualization of molecular-level events associated with disease progression and treatment response. Accurate and efficient 3D reconstruction algorithms will facilitate the wide-use of FMT in preclinical research. Here, we utilize L1/2-norm regularization for improving FMT reconstruction. To efficiently solve the nonconvex L1/2-norm penalized problem, we transform it into a weighted L1-norm minimization problem and employ a homotopy-based iterative reweighting algorithm to recover small fluorescent targets. Both simulations on heterogeneous mouse model and in vivo experiments demonstrated that the proposed L1/2-norm method outperformed the comparative L1-norm reconstruction methods in terms of location accuracy, spatial resolution and quantitation of fluorescent yield. Furthermore, simulation analysis showed the robustness of the proposed method, under different levels of measurement noise and number of excitation sources.

Near-Infrared Spectroscopy in the Monitoring of Adult Traumatic Brain Injury: A Review

Cerebral near-infrared spectroscopy (NIRS) has long represented an exciting prospect for the noninvasive monitoring of cerebral tissue oxygenation and perfusion in the context of traumatic brain injury (TBI), although uncertainty still exists regarding the reliability of this technology specifically within this field. We have undertaken a review of the existing literature relating to the application of NIRS within TBI. We discuss current "state-of-the-art" NIRS monitoring, provide a brief background of the technology, and discuss the evidence regarding the ability of NIRS to substitute for established invasive monitoring in TBI.

Mesh Optimization for Monte Carlo-Based Optical Tomography

Mesh-based Monte Carlo techniques for optical imaging allow for accurate modeling of light propagation in complex biological tissues. Recently, they have been developed within an efficient computational framework to be used as a forward model in optical tomography. However, commonly employed adaptive mesh discretization techniques have not yet been implemented for Monte Carlo based tomography. Herein, we propose a methodology to optimize the mesh discretization and analytically rescale the associated Jacobian based on the characteristics of the forward model. We demonstrate that this method maintains the accuracy of the forward model even in the case of temporal data sets while allowing for significant coarsening or refinement of the mesh.

Systematic calibration of an integrated x-ray and optical tomography system for preclinical radiation research

PURPOSE

The cone beam computed tomography (CBCT) guided small animal radiation research platform (SARRP) has been developed for focal tumor irradiation, allowing laboratory researchers to test basic biological hypotheses that can modify radiotherapy outcomes in ways that were not feasible previously. CBCT provides excellent bone to soft tissue contrast, but is incapable of differentiating tumors from surrounding soft tissue. Bioluminescence tomography (BLT), in contrast, allows direct visualization of even subpalpable tumors and quantitative evaluation of tumor response. Integration of BLT with CBCT offers complementary image information, with CBCT delineating anatomic structures and BLT differentiating luminescent tumors. This study is to develop a systematic method to calibrate an integrated CBCT and BLT imaging system which can be adopted onboard the SARRP to guide focal tumor irradiation.

METHODS

The integrated imaging system consists of CBCT, diffuse optical tomography (DOT), and BLT. The anatomy acquired from CBCT and optical properties acquired from DOT serve as a priori information for the subsequent BLT reconstruction. Phantoms were designed and procedures were developed to calibrate the CBCT, DOT/BLT, and the entire integrated system. Geometrical calibration was performed to calibrate the CBCT system. Flat field correction was performed to correct the nonuniform response of the optical imaging system. Absolute emittance calibration was performed to convert the camera readout to the emittance at the phantom or animal surface, which enabled the direct reconstruction of the bioluminescence source strength. Phantom and mouse imaging were performed to validate the calibration.

RESULTS

All calibration procedures were successfully performed. Both CBCT of a thin wire and a euthanized mouse revealed no spatial artifact, validating the accuracy of the CBCT calibration. The absolute emittance calibration was validated with a 650 nm laser source, resulting in a 3.0% difference between simulated and measured signal. The calibration of the entire system was confirmed through the CBCT and BLT reconstruction of a bioluminescence source placed inside a tissue-simulating optical phantom. Using a spatial region constraint, the source position was reconstructed with less than 1 mm error and the source strength reconstructed with less than 24% error.

CONCLUSIONS

A practical and systematic method has been developed to calibrate an integrated x-ray and optical tomography imaging system, including the respective CBCT and optical tomography system calibration and the geometrical calibration of the entire system. The method can be modified and adopted to calibrate CBCT and optical tomography systems that are operated independently or hybrid x-ray and optical tomography imaging systems.

Next-generation Raman tomography instrument for non-invasive in vivo bone imaging

Combining diffuse optical tomography methods with Raman spectroscopy of tissue provides the ability for in vivo measurements of chemical and molecular characteristics, which have the potential for being useful in diagnostic imaging. In this study a system for Raman tomography was developed and tested. A third generation microCT coupled system was developed to combine 10 detection fibers and 5 excitation fibers with laser line filtering and a Cytop reference signal. Phantom measurements of hydroxyapatite concentrations from 50 to 300 mg/ml had a linear response. Fiber placement and experiment design was optimized using cadaver animals with live animal measurements acquired to validate the systems capabilities. Promising results from the initial animal experiments presented here, pave the way for a study of longitudinal measurements during fracture healing and the scaling of the Raman tomography system towards human measurements.

Dynamic causal modelling for functional near-infrared spectroscopy

Functional near-infrared spectroscopy (fNIRS) is an emerging technique for measuring changes in cerebral hemoglobin concentration via optical absorption changes. Although there is great interest in using fNIRS to study brain connectivity, current methods are unable to infer the directionality of neuronal connections. In this paper, we apply Dynamic Causal Modelling (DCM) to fNIRS data. Specifically, we present a generative model of how observed fNIRS data are caused by interactions among hidden neuronal states. Inversion of this generative model, using an established Bayesian framework (variational Laplace), then enables inference about changes in directed connectivity at the neuronal level. Using experimental data acquired during motor imagery and motor execution tasks, we show that directed (i.e., effective) connectivity from the supplementary motor area to the primary motor cortex is negatively modulated by motor imagery, and this suppressive influence causes reduced activity in the primary motor cortex during motor imagery. These results are consistent with findings of previous functional magnetic resonance imaging (fMRI) studies, suggesting that the proposed method enables one to infer directed interactions in the brain mediated by neuronal dynamics from measurements of optical density changes.