A Pilot Study of the Impact of Microwave Ablation on the Dielectric Properties of Breast Tissue.

Percutaneous microwave ablation (MWA) is a promising technology for patients with breast cancer, as it may help treat individuals who have less aggressive cancers or do not respond to targeted therapies in the neoadjuvant or pre-surgical setting. In this study, we investigate changes to the microwave dielectric properties of breast tissue that are induced by MWA. While similar changes have been characterized for relatively homogeneous tissues, such as liver, those prior results are not directly translatable to breast tissue because of the extreme tissue heterogeneity present in the breast.

Assessing recurrent interactions in cortical networks: Modeling EEG response to transcranial magnetic stimulation.

Background: The basic mechanisms underlying the electroencephalograpy (EEG) response to transcranial magnetic stimulation (TMS) of the human cortex are not well understood.

New Method: A state-space modeling methodology is developed to gain insight into the network nature of the TMS/EEG response. Cortical activity is modeled using a multivariariate autoregressive model with exogenous stimulation parameters representing the effect of TMS.

Modeling Touch and Palpation Using Autoregressive Models.

Objective: The human haptic system uses a set of reproducible and subconscious hand maneuvers to identify objects. Similar subconscious maneuvers are used during medical palpation for screening and diagnosis. The goal of this work was to develop a mathematical model that can be used to describe medical palpation techniques.

Fetal QT Interval Estimation Using Sequential Hypothesis Testing.

: Recent studies utilizing fetal magnetocardiography have demonstrated the efficacy of corrected QT interval (QTc) measurement for in utero diagnosis and prognosis of long QT syndrome, a leading cause of sudden death in early life. The objective of the study was to formulate and test a novel statistical estimation method to detect the end of the fetal T-wave and thereby improve the accuracy of fetal QT interval measurement. : To detect the end of the T-wave, we apply a sequential composite hypothesis test to decide when the T-wave has returned to baseline.

A 3-D Level Set Method for Microwave Breast Imaging.

Objective: Conventional inverse-scattering algorithms for microwave breast imaging result in moderate resolution images with blurred boundaries between tissues. Recent 2-D numerical microwave imaging studies demonstrate that the use of a level set method preserves dielectric boundaries, resulting in a more accurate, higher resolution reconstruction of the dielectric properties distribution. Previously proposed level set algorithms are computationally expensive, and thus, impractical in 3-D.

Context-specific differences in fronto-parieto-occipital effective connectivity during short-term memory maintenance.

Although visual short-term memory (VSTM) performance has been hypothesized to rely on two distinct mechanisms, capacity and filtering, the two have not been dissociated using network-level causality measures. Here, we hypothesized that behavioral tasks challenging capacity or distraction filtering would both engage a common network of areas, namely dorsolateral prefrontal cortex (dlPFC), superior parietal lobule (SPL), and occipital cortex, but would do so according to dissociable patterns of effective connectivity. We tested this by estimating directed connectivity between areas using conditional Granger causality (cGC).

Characterizing touch using pressure data and auto regressive models.

Palpation plays a critical role in medical physical exams. Despite the wide range of exams, there are several reproducible and subconscious sets of maneuvers that are common to examination by palpation. Previous studies by our group demonstrated the use of manikins and pressure sensors for measuring and quantifying how physicians palpate during different physical exams.

Beamforming-Enhanced Inverse Scattering for Microwave Breast Imaging.

We present a focal-beamforming-enhanced formulation of the distorted Born iterative method (DBIM) for microwave breast imaging. Incorporating beamforming into the imaging algorithm has the potential to mitigate the effect of noise on the image reconstruction. We apply the focal-beamforming-enhanced DBIM algorithm to simulated array measurements from two MRI-derived, anatomically realistic numerical breast phantoms and compare its performance to that of the DBIM formulated with two non-focal schemes.

Disrupted directed connectivity along the cingulate cortex determines vigilance after sleep deprivation.

The cingulate cortex is regarded as the backbone of structural and functional connectivity of the brain. While its functional connectivity has been intensively studied, little is known about its effective connectivity, its modulation by behavioral states, and its involvement in cognitive performance. Given the previously reported effects on cingulate functional connectivity, we investigated how eye-closure and sleep deprivation changed cingulate effective connectivity, estimated from resting-state high-density electroencephalography (EEG) using a novel method to calculate Granger Causality directly in source space.

Detection of T-wave alternans in fetal magnetocardiography using the generalized likelihood ratio test.

T-wave alternans (TWA) is an indicator of cardiac instability and is associated with life-threatening ventricular arrhythmias. Detection of TWA in the adult has been widely investigated and is used routinely for cardiac risk assessment. Detection of TWA in the fetus, however, is much more difficult due to the low amplitude and variable configuration of the signal, the presence of strong interferences, and the brevity of fetal TWA episodes.

Multivariate autoregressive models with exogenous inputs for intracerebral responses to direct electrical stimulation of the human brain.

A multivariate autoregressive (MVAR) model with exogenous inputs (MVARX) is developed for describing the cortical interactions excited by direct electrical current stimulation of the cortex. Current stimulation is challenging to model because it excites neurons in multiple locations both near and distant to the stimulation site. The approach presented here models these effects using an exogenous input that is passed through a bank of filters, one for each channel.

Interhemispheric effective and functional cortical connectivity signatures of spina bifida are consistent with callosal anomaly.

The impact of the posterior callosal anomalies associated with spina bifida on interhemispheric cortical connectivity is studied using a method for estimating cortical multivariable autoregressive models from scalp magnetoencephalography data. Interhemispheric effective and functional connectivity, measured using conditional Granger causality and coherence, respectively, is determined for the anterior and posterior cortical regions in a population of five spina bifida and five control subjects during a resting eyes-closed state. The estimated connectivity is shown to be consistent over the randomly selected subsets of the data for each subject.

Quantitative Microwave Imaging of Realistic Numerical Breast Phantoms Using an Enclosed Array of Multiband, Miniaturized Patch Antennas.

We present a 3-D microwave breast imaging study in which we reconstruct the dielectric profiles of MRI-derived numerical breast phantoms from simulated array measurements using an enclosed array of multiband, miniaturized patch antennas. The array is designed to overcome challenges relating to the ill-posed nature of the inverse scattering system. We use a multifrequency formulation of the distorted Born iterative method to image four normal-tissue breast phantoms, each corresponding to a different density class.

MRI-Derived 3-D-Printed Breast Phantom for Microwave Breast Imaging Validation.

We propose a 3-D-printed breast phantom for use in preclinical experimental microwave imaging studies. The phantom is derived from an MRI of a human subject; thus, it is anthropomorphic, and its interior is very similar to an actual distribution of fibroglandular tissues. Adipose tissue in the breast is represented by the solid plastic (printed) regions of the phantom, while fibroglandular tissue is represented by liquid-filled voids in the plastic.

A TSVD analysis of microwave inverse scattering for breast imaging.

A variety of methods have been applied to the inverse scattering problem for breast imaging at microwave frequencies. While many techniques have been leveraged toward a microwave imaging solution, they are all fundamentally dependent on the quality of the scattering data. Evaluating and optimizing the information contained in the data are, therefore, instrumental in understanding and achieving optimal performance from any particular imaging method.

Cross validation for selection of cortical interaction models from scalp EEG or MEG.

A cross-validation (CV) method based on state-space framework is introduced for comparing the fidelity of different cortical interaction models to the measured scalp electroencephalogram (EEG) or magnetoencephalography (MEG) data being modeled. A state equation models the cortical interaction dynamics and an observation equation represents the scalp measurement of cortical activity and noise. The measured data are partitioned into training and test sets.

Causal Network Inference Via Group Sparse Regularization.

This paper addresses the problem of inferring sparse causal networks modeled by multivariate autoregressive (MAR) processes. Conditions are derived under which the Group Lasso (gLasso) procedure consistently estimates sparse network structure. The key condition involves a "false connection score" ψ.

Dielectric characterization of PCL-based thermoplastic materials for microwave diagnostic and therapeutic applications.

We propose the use of a polycaprolactone (PCL)-based thermoplastic mesh as a tissue-immobilization interface for microwave imaging and microwave hyperthermia treatment. An investigation of the dielectric properties of two PCL-based thermoplastic materials in the frequency range of 0.5-3.

Microwave beamforming for non-invasive patient-specific hyperthermia treatment of pediatric brain cancer.

We present a numerical study of an array-based microwave beamforming approach for non-invasive hyperthermia treatment of pediatric brain tumors. The transmit beamformer is designed to achieve localized heating-that is, to achieve constructive interference and selective absorption of the transmitted electromagnetic waves at the desired focus location in the brain while achieving destructive interference elsewhere. The design process takes into account patient-specific and target-specific propagation characteristics at 1 GHz.

Time-multiplexed beamforming for noninvasive microwave hyperthermia treatment.

A noninvasive microwave beamforming strategy is proposed for selective localized heating of biological tissue. The proposed technique is based on time multiplexing of multiple beamformers. We investigate the effectiveness of the time-multiplexed beamforming in the context of brain hyperthermia treatment by using a high-fidelity numerical head phantom of an adult female from the Virtual Family (IT'IS Foundation) as our testbed.

Three-dimensional microwave imaging of realistic numerical breast phantoms via a multiple-frequency inverse scattering technique.

Purpose: Breast density measurement has the potential to play an important role in individualized breast cancer risk assessment and prevention decisions. Routine evaluation of breast density will require the availability of a low-cost, nonionizing, three-dimensional (3-D) tomographic imaging modality that exploits a strong properties contrast between dense fibroglandular tissue and less dense adipose tissue. The purpose of this computational study is to investigate the performance of 3-D tomography using low-power microwaves to reconstruct the spatial distribution of breast tissue dielectric properties and to evaluate the modality for application to breast density characterization.

3D computational study of non-invasive patient-specific microwave hyperthermia treatment of breast cancer.

Non-invasive microwave hyperthermia treatment of breast cancer is investigated using three-dimensional (3D) numerical breast phantoms with anatomical and dielectric-properties realism. 3D electromagnetic and thermal finite-difference time-domain simulations are used to evaluate the focusing and selective heating efficacy in four numerical breast phantoms with different breast tissue densities. Beamforming is used to design and focus the signals transmitted by an antenna array into the breast.

Estimation of cortical connectivity from EEG using state-space models.

A state-space formulation is introduced for estimating multivariate autoregressive (MVAR) models of cortical connectivity from noisy, scalp-recorded EEG. A state equation represents the MVAR model of cortical dynamics, while an observation equation describes the physics relating the cortical signals to the measured EEG and the presence of spatially correlated noise. We assume that the cortical signals originate from known regions of cortex, but the spatial distribution of activity within each region is unknown.

A Sparsity Regularization Approach to the Electromagnetic Inverse Scattering Problem.

We investigate solving the electromagnetic inverse scattering problem using the distorted Born iterative method (DBIM) in conjunction with a variable-selection approach known as the elastic net. The elastic net applies both ℓ1 and ℓ2 penalties to regularize the system of linear equations that result at each iteration of the DBIM. The elastic net thus incorporates both the stabilizing effect of the ℓ2 penalty with the sparsity encouraging effect of the ℓ1 penalty.

State-space multivariate autoregressive models for estimation of cortical connectivity from EEG.

We propose using a state-space model to estimate cortical connectivity from scalp-based EEG recordings. A state equation describes the dynamics of the cortical signals and an observation equation describes the manner in which the cortical signals contribute to the scalp measurements. The state equation is based on a multivariate autoregressive (MVAR) process model for the cortical signals.