Biomedical subjects

Alex Hartov

Publications and source records attributed to Alex Hartov.

17 recordsLinked to original sources

PubMed2006

Data-guided brain deformation modeling: evaluation of a 3-D adjoint inversion method in porcine studies.

Biomechanical models of brain deformation are useful tools for estimating parenchymal shift that results during open cranial procedures. Intraoperative data is likely to improve model estimates, but incorporation of such data into the model is not trivial. This study tests the adjoint equations method (AEM) for data assimilation as a viable approach for integrating displacement data into a brain deformation model. AEM was applied to two porcine experiments. AEM-based estimates were compared both to measured displacement data [from computed tomography (CT) scans] and to model solutions obtained without the guidance of sparse data, which we term the best prior estimate (BPE). Additionally, the sensitivity of the AEM solution to inverse parameter selection was investigated. The results suggest that it is most important to estimate the size of the variance in the measurement error correctly, make the correlation length long and estimate displacement (over stress) boundary conditions. Application of AEM shows an average 33% improvement over BPE. This paper represents the first evidence of successful use of the AEM technique in three dimensions with experimental data validation. The guidelines established for selection of model parameters are starting points for further optimization of the method under clinical conditions.

Algorithms↗

PubMed2006

Finite element implementation of Maxwell's equations for image reconstruction in electrical impedance tomography.

Traditionally, image reconstruction in electrical impedance tomography (EIT) has been based on Laplace's equation. However, at high frequencies the coupling between electric and magnetic fields requires solution of the full Maxwell equations. In this paper, a formulation is presented in terms of the Maxwell equations expressed in scalar and vector potentials. The approach leads to boundary conditions that naturally align with the quantities measured by EIT instrumentation. A two-dimensional implementation for image reconstruction from EIT data is realized. The effect of frequency on the field distribution is illustrated using the high-frequency model and is compared with Laplace solutions. Numerical simulations and experimental results are also presented to illustrate image reconstruction over a range of frequencies using the new implementation. The results show that scalar/vector potential reconstruction produces images which are essentially indistinguishable from a Laplace algorithm for frequencies below 1 MHz but superior at frequencies reaching 10 MHz.

Algorithms↗

PubMed2005

Excitation patterns in three-dimensional electrical impedance tomography.

Electrical impedance tomography (EIT) is a non-invasive technique that aims to reconstruct images of internal electrical properties of a domain, based on electrical measurements on the periphery. Improvements in instrumentation and numerical modeling have led to three-dimensional (3D) imaging. The availability of 3D modeling and imaging raises the question of identifying the best possible excitation patterns that will yield to data, which can be used to produce the best image reconstruction of internal properties. In this work, we describe our 3D finite element model of EIT. Through singular value decomposition as well as examples of reconstructed images, we show that for a homogenous female breast model with four layers of electrodes, a driving pattern where each excitation plane is a sinusoidal pattern out-of-phase with its neighboring plane produces better qualitative images. However, in terms of quantitative imaging an excitation pattern where all electrode layers are in phase produces better results.

Algorithms↗

PubMed2005

Assimilating intraoperative data with brain shift modeling using the adjoint equations.

Biomechanical models of brain deformation are increasingly being used to nonrigidly register preoperative MR (pMR) images of the brain to the surgical scene. These model estimates can potentially be improved by incorporating sparse displacement data available in the operating room (OR), but integrating the intraoperative information with model calculations is a nontrivial problem. We present an inverse method to estimate the unknown boundary and volumetric forces necessary to achieve a least-squares fit between the model and the data that is formulated in terms of the adjoint equations, which are solved directly by the method of representers. The scheme is illustrated in a 2D simulation and in a 2D approximation based on a patient case using actual OR data.

Algorithms↗

PubMed2005

On optimal current patterns for electrical impedance tomography.

We develop a statistical criterion for optimal patterns in planar circular electrical impedance tomography. These patterns minimize the total variance of the estimation for the resistance or conductance matrix. It is shown that trigonometric patterns (Isaacson, 1986), originally derived from the concept of distinguishability, are a special case of our optimal statistical patterns. New optimal random patterns are introduced. Recovering the electrical properties of the measured body is greatly simplified when optimal patterns are used. The Neumann-to-Dirichlet map and the optimal patterns are derived for a homogeneous medium with an arbitrary distribution of the electrodes on the periphery. As a special case, optimal patterns are developed for a practical EIT system with a finite number of electrodes. For a general nonhomogeneous medium, with no a priori restriction, the optimal patterns for the resistance and conductance matrix are the same. However, for a homogeneous medium, the best current pattern is the worst voltage pattern and vice versa. We study the effect of the number and the width of the electrodes on the estimate of resistivity and conductivity in a homogeneous medium. We confirm experimentally that the optimal patterns produce minimum conductivity variance in a homogeneous medium. Our statistical model is able to discriminate between a homogenous agar phantom and one with a 2 mm air hole with error probability (p-value) 1/1000.

Algorithms↗

PubMed2005

Stereopsis-guided brain shift compensation.

Brain deformation models have proven to be a powerful tool in compensating for soft tissue deformation during image-guided neurosurgery. The accuracy of these models can be improved by incorporating intraoperative measurements of brain motion. We have designed and implemented a passive intraoperative stereo vision system capable of estimating the three-dimensional shape of the surgical scene in near real-time. This intraoperative shape is compared with the cortical surface in the co-registered preoperative magnetic resonance (MR) volume for the estimation of the cortical motion resulting from the open cranial surgery. The estimated cortical motion is then used to guide a full brain model, which updates a preoperative MR volume. We have found that the stereo vision system is accurate to within approximately 1 mm. Based on data from two representative clinical cases, we show that stereopsis guidance improves the accuracy of brain shift compensation both at and below the cortical surface.

Algorithms↗

PubMed2005

Cortical surface tracking using a stereoscopic operating microscope.

OBJECTIVE: To measure and compensate for soft tissue deformation during image-guided neurosurgery, we have developed a novel approach to estimate the three-dimensional (3-D) topology of the cortical surface and track its motion over time. METHODS: We use stereopsis to estimate the 3-D cortical topology during neurosurgical procedures. To facilitate this process, two charge-coupled device cameras have been attached to the binocular optics of a stereoscopic operating microscope. Before surgery, this stereo imaging system is calibrated to obtain the extrinsic and intrinsic camera parameters. During surgery, the 3-D shape of the cortical surface is automatically estimated from a stereo pair of images and registered to the preoperative image volume to provide navigational guidance. This estimation requires robust matching of features between the images, which, when combined with the camera calibration, yields the desired 3-D coordinates. After the 3-D cortical surface has been estimated from stereo pairs, its motion is tracked by comparing the current surface with its previous locations. RESULTS: We are able to estimate the 3-D topology of the cortical surface with an average error of less than 1.2 mm. Executing on a 1.1-GHz Pentium machine, the 3-D estimation from a stereo pair of 1024 x 768 resolution images requires approximately 60 seconds of computation. By applying stereopsis over time, we are able to track the motion of the cortical surface, including the pulsatile movement of the cortical surface, gravitational sag, tissue bulge as a result of increased intracranial pressure, and the parenchymal shape changes associated with tissue resection. The results from 10 surgical patients are reported. CONCLUSION: We have demonstrated that a stereo vision system coupled to the operating microscope can be used to efficiently estimate the dynamic topology of the cortical surface during surgery. The 3-D surface can be coregistered to the preoperative image volume. This unique intraoperative imaging technique expands the capability of the current navigational system in the operating room and increases the accuracy of anatomic correspondence with preoperative images through compensation for brain deformation.

Adult↗

PubMed2004

Multi-frequency electrical impedance tomography of the breast: new clinical results.

Electrical impedance tomography (EIT) has been used in the recent past for a number of clinical applications. In this work we present recent tomographic and spectroscopic findings for breast imaging from clinical exams completed at Dartmouth. The results presented here are based on 18 normal and 24 abnormal subjects. The participants were classified as normal or abnormal using the American College of Radiology (ACR) indexing system for mammograms. The EIT data were collected for ten discrete frequencies in the range 10 kHz-1 MHz using a single array of 16 electrodes. The finite element method was used to reconstruct the images. The images were examined visually and were compared with mammograms. The results were also analyzed based on zonal averages of property values and breast tissue radiodensities. Statistical analysis showed a significance difference between the mean conductivity and permittivity values of normal and abnormal subjects for various zones defined on the reconstructed images. Tissues with high radiodensity also had increased conductivity and permittivity.

Breast↗

PubMed2004

Design and implementation of a high frequency electrical impedance tomography system.

Electrical impedance tomography is an imaging modality being investigated for use in detection of breast cancer. Use of higher frequencies than have typically been employed may benefit the detection processes. In this current work we discuss the design and initial implementation of a system having a bandwidth of 10 MHz. Previous investigations into high frequency designs have proven more difficult than anticipated and shown that careful selection of systems architecture is critical to achieving broadband performance above 1 MHz. The design for this new system is based on a digital signal processor (DSP) which is used for control, signal generation and signal processing. Signal generation and detection, software design and preliminary system specifications are discussed.

Breast Neoplasms↗

PubMed2004

Statistical estimation of resistance/conductance by electrical impedance tomography measurements.

This paper is built upon the assumption that in electrical impedance tomography, vectors of voltages and currents are linearly dependent through a resistance matrix. This linear relationship was confirmed experimentally and may be derived analytically under certain assumptions regarding electrodes (Isaacson, 1991). Given measurement data consisting of voltages and currents, we treat this relationship as a linear statistical model. Thus, our goal is not to reconstruct the image but directly estimate its electromagnetic properties reflected in the resistance and/or conductance matrix using electrical impedance tomography (EIT) measurements of voltages and currents on the periphery of the body. Since no inverse problem is involved the algorithm for estimation merely reduces to one matrix inversion. We estimate the impedance resistance matrix using well established statistical inference techniques for linear regression models. We provide a comprehensive treatment for a two-dimensional homogeneous body of a circular shape, by which many concepts of electrical impedance tomography, such as width of electrodes, the difference between voltage-current and current-voltage systems are illustrated. Our theory may be applied to various tests including EIT hardware calibration and whether the medium is homogeneous. These tests are illustrated on phantom agar data.

Agar↗

PubMed2003

A novel data calibration scheme for electrical impedance tomography.

In electrical impedance tomography surface measurements of voltages and currents are recorded and the image reconstruction algorithm uses this set of boundary data to estimate internal electrical properties of the region under investigation. Therefore correct and accurate modelling of the current and voltage distributions (forward model) is an essential part of any reconstruction method. In this paper, we explored the root cause of a boundary layer effect in the reconstructed conductivity map and found it to be an artefact arising from 2D to 3D data-model mismatch within the imaging algorithm. We propose a data calibration scheme that improves the reconstruction results by removing these boundary or edge effects. We present both two-dimensional and three-dimensional images for agar phantoms using this data calibration scheme which are markedly better than their counterparts recovered when the measurement data are not calibrated with the procedure outlined herein.

Agar↗

PubMed2003

Displacement estimation with co-registered ultrasound for image guided neurosurgery: a quantitative in vivo porcine study.

Brain shift during open cranial surgery presents a challenge for maintaining registration with image-guidance systems. Ultrasound (US) is a convenient intraoperative imaging modality that may be a useful tool in detecting tissue shift and updating preoperative images based on intraoperative measurements of brain deformation. We have quantitatively evaluated the ability of spatially tracked freehand US to detect displacement of implanted markers in a series of three in vivo porcine experiments, where both US and computed tomography (CT) image acquisitions were obtained before and after deforming the brain. Marker displacements ranged from 0.5 to 8.5 mm. Comparisons between CT and US measurements showed a mean target localization error of 1.5 mm, and a mean vector error for displacement of 1.1 mm. Mean error in the magnitude of displacement was 0.6 mm. For one of the animals studied, the US data was used in conjunction with a biomechanical model to nonrigidly re-register a baseline CT to the deformed brain. The mean error between the actual and deformed CT's was found to be on average 1.2 and 1.9 mm at the marker locations depending on the extent of the deformation induced. These findings indicate the potential accuracy in coregistered freehand US displacement tracking in brain tissue and suggest that the resulting information can be used to drive a modeling re-registration strategy to comparable levels of agreement.

Algorithms↗

PubMed2003

A noncontacting 3-D digitizer for use in image-guided neurosurgery.

Current neuronavigational systems face two primary challenges: (1) automatic and robust registration between preoperative images and the operating room space, and (2) compensation for brain deformations that compromise the accuracy of the initial registration. To contend with these difficulties, we firstly estimate the three-dimensional (3-D) structure of the cortical surface using a noncontacting 3-D digitizer. This 3-D structure is then used to establish the initial registration, and to update the preoperative MR volume as the brain deforms. We show that this approach improves the accuracy of registration in a phantom study, and demonstrate the ability to capture cortical motion in six clinical cases.

Cerebral Cortex↗

PubMed2002

Imaging the breast with EIS: an initial study of exam consistency.

Use of electrical impedance spectroscopy (EIS) to image the breasts of women with both normal and abnormal conditions requires the ability to deliver a consistent and repeatable exam. To investigate the degree to which our current imaging system can meet this requirement we conducted an initial study of exam consistency. The trial involved the imaging of 25 breasts stratified into four separate substudies with increasing levels of electrode placement uncertainty. The degree of complexity ranged from single-placement single-session imaging to multiple-placement single-session imaging to multiple-placement multiple-session imaging. Both visual analysis and quantitative comparisons using mean squared difference (MSD) measures between pairs of permittivity and conductivity images were performed. A new breast interface with the improved vertical and radial electrode array positioning capability required to complete this study is described. Not surprisingly, the results show a dominant trend of increased image variability with increased electrode placement uncertainty. Importantly, quantitative levels of image consistency are reported through MSD analysis. On average across all frequencies analysed, MSDs for single placements are well below 1%, near 2-3% for repositioned breasts during the same session and approximately 15% for re-examined breasts in multiple sessions conducted over time. Overall, these results suggest that EIS breast exams are consistent provided the electrode placement is well controlled, typically with better than 1 cm accuracy.

Algorithms↗

PubMed2002

In vivo quantification of retraction deformation modeling for updated image-guidance during neurosurgery.

The use of coregistered preoperative anatomical scans to provide navigational information in the operating room has greatly benefited the field of neurosurgery. Nonetheless, it has been widely acknowledged that significant errors between the operating field and the preoperative images are generated as surgery progresses. Quantification of tissue shift can be accomplished with volumetric intraoperative imaging; however, more functional, lower cost alternative solutions to this challenge are desirable. We are developing the strategy of exploiting a computational model driven by sparse data obtained from intraoperative ultrasound and cortical surface tracking to warp preoperative images to reflect the current state of the operating field. This paper presents an initial quantification of the predictive capability of the current model to computationally capture tissue deformation during retraction in the porcine brain. Performance validation is achieved through comparisons of displacement and pressure predictions to experimental measurements obtained from computed tomographic images and pressure sensor recordings. Group results are based upon a generalized set of boundary conditions for four subjects that, on average, account for at least 75% of tissue motion generated during interhemispheric retraction. Individualized boundary conditions can improve the degree of data-model match by 10% or more but warrant further study. Overall, the level of quantitative agreement achieved in these experiments is encouraging for updating preoperative images to reflect tissue deformation resulting from retraction, especially since model improvements are likely as a result of the intraoperative constraints that can be applied through sparse data collection.

Animals↗

PubMed2002

Electrical impedance spectroscopy of the breast: clinical imaging results in 26 subjects.

Electrical impedance spectroscopy (EIS) is a potential, noninvasive technique to image women for breast cancer. Studies have shown characteristic frequency dispersions in the electrical conductivity and permittivity of malignant versus normal tissue. Using a multifrequency EIS system, we imaged the breasts of 26 women. All patients had mammograms ranked using the American College of Radiology (ACR) BIRADS system. Of the 51 individual breasts imaged, 38 were ACR 1 negative, six had ACR 4-5 suspicious lesions, and seven had ACR 2 benign findings such as fibroadenomas or calcifications. A radially translatable circular array of 16 Ag/AgCl electrodes was placed around the breast while the patient lay prone. We applied trigonometric voltage patterns at ten frequencies between 10 and 950 kHz. Anatomically coronal images were reconstructed from this data using nonlinear partial differential equation methods. Typically, ACR 1-rated breasts were interrogated in a single central plane whereas ACR 2-5-rated breasts were imaged in multiple planes covering the region of suspicion. In general, a characteristic homogeneous image emerged for mammographically normal cases while focal inhomogeneities were observed in images from women with malignancies. Using a specific visual criterion, EIS images identified 83% of the ACR 4-5 lesions while 67% were detected using a numerical criterion. Overall, multifrequency electrical impedance imaging appears promising for detecting breast malignancies, but improvements must be made before the method reaches its full potential.

Adult↗

PubMed2002

Using multiple-electrode impedance measurements to monitor cryosurgery.

We outfitted cryoprobes with electrodes and used them in conjunction with a multiple channel electrical impedance tomography (EIT) system to record data during freezing experiments in a shallow saline tank. We made measurements using electrodes mounted on the probes and the tank's periphery. Reconstructed images based on both sets of electrodes indicate a significant improvement in the appearance of the ice ball over using tank electrodes alone. The size of the ice balls was varied by deliberately altering the cooling rate. We found a positive correlation between the measured size of the ice ball and the sizes of isocontour lines in the reconstructed impedance maps. Similarly, the shape of the ice balls was altered by circulating the saline about the probe. Two-dimensional reconstructed impedance contours indicated a deformation in agreement with the shape of the ice ball during the experiments. These findings suggest that using multielectrode impedance sensing may constitute a means for monitoring cryosurgery.

Biophysical Phenomena↗