Intraoperative fiducial-less patient registration using volumetric 3D ultrasound: a prospective series of 32 neurosurgical cases.

OBJECT: Fiducial-based registration (FBR) is used widely for patient registration in image-guided neurosurgery. The authors of this study have developed an automatic fiducial-less registration (FLR) technique to find the patient-to-image transformation by directly registering 3D ultrasound (3DUS) with MR images without incorporating prior information. The purpose of the study was to evaluate the performance of the FLR technique when used prospectively in the operating room and to compare it with conventional FBR. METHODS: In 32 surgical patients who underwent conventional FBR, preoperative T1-weighted MR images (pMR) with attached fiducial markers were acquired prior to surgery. After craniotomy but before dural opening, a set of 3DUS images of the brain volume was acquired. A 2-step registration process was executed immediately after image acquisition: 1) the cortical surfaces from pMR and 3DUS were segmented, and a multistart sum-of-squared-intensity-difference registration was executed to find an initial alignment between down-sampled binary pMR and 3DUS volumes; and 2) the alignment was further refined by a mutual information-based registration between full-resolution grayscale pMR and 3DUS images, and a patient-to-image transformation was subsequently extracted. RESULTS: To assess the accuracy of the FLR technique, the following were quantified: 1) the fiducial distance error (FDE); and 2) the target registration error (TRE) at anterior commissure and posterior commissure locations; these were compared with conventional FBR. The results showed that although the average FDE (6.42 ± 2.05 mm) was higher than the fiducial registration error (FRE) from FBR (3.42 ± 1.37 mm), the overall TRE of FLR (2.51 ± 0.93 mm) was lower than that of FBR (5.48 ± 1.81 mm). The results agreed with the intent of the 2 registration techniques: FBR is designed to minimize the FRE, whereas FLR is designed to optimize feature alignment and hence minimize TRE. The overall computational cost of FLR was approximately 4-5 minutes and minimal user interaction was required. CONCLUSIONS: Because the FLR method directly registers 3DUS with MR by matching internal image features, it proved to be more accurate than FBR in terms of TRE in the 32 patients evaluated in this study. The overall efficiency of FLR in terms of the time and personnel involved is also improved relative to FBR in the operating room, and the method does not require additional image scans immediately prior to surgery. The performance of FLR and these results suggest potential for broad clinical application.

Real-time electrical impedance variations in women with and without breast cancer.

The chaotic vascular network surrounding malignant tumors leads to pulsatile blood flow patterns that differ from those in benign regions of the breast. This study aimed to determine if high-speed electrical impedance tomography (EIT) is able to detect conductivity changes associated with cyclic blood-volume changes and to gauge the potential of using these signatures to differentiate malignant from benign regions within the breast. EIT imaging of pulsating latex membranes submerged in saline baths provided initial validation of its use for tracking temporally varying conductivities. Nineteen women (10 with cancer, nine without) were imaged with EIT over the course of several heartbeats in synchrony with pulse-oximetry acquisition. Eight parameters ( rs, ϕ(rt,max), rt,max, Plow:full, Phigh:full, Plow:high) relating the conductivity images and pulse-oximeter signatures were extracted and used as a means of comparing malignant and benign regions of the breast. Significant differences between malignant and benign regions of interest were noted in seven of the eight parameters. The maximum correlation between conductivity and pulse-oximeter signals, rt,max , was observed to be the optimal discriminating parameter with a receiver operating characteristic area under the curve of 0.8 and a specificity of 81% at a sensitivity of 77%. Assessing the dynamic conductivity of breast may provide additional clinical utility to that of standard imaging modalities, but further investigation is necessary to better understand the biophysical mechanisms leading to the observed conductivity changes.

Stereovision to MR image registration for cortical surface displacement mapping to enhance image-guided neurosurgery.

PURPOSE: A surface registration method is presented to align intraoperative stereovision (iSV) with preoperative magnetic resonance (pMR) images, which utilizes both geometry and texture information to extract tissue displacements as part of the overall process of compensating for intraoperative brain deformation in order to maintain accurate neuronavigational image guidance during surgery. METHODS: A sum-of-squared-difference rigid image registration was first executed to detect lateral shift of the cortical surface and was followed by a mutual-information-based block matching method to detect local nonrigid deformation caused by distention or collapse of the cortical surface. Ten (N = 10) surgical cases were evaluated in which an independent point measurement of a dominant cortical surface feature location was recorded with a tracked stylus in each case and compared to its surface-registered counterpart. The full three-dimensional (3D) displacement field was also extracted to drive a biomechanical brain deformation model, the results of which were reconciled with the reconstructed iSV surface as another form of evaluation. RESULTS: Differences between the tracked stylus coordinates of cortical surface features and their surface-registered locations were 1.94 ± 0.59 mm on average across the ten cases. When the complete displacement map derived from surface registration was utilized, the resulting images generated from mechanical model updates were consistent in terms of both geometry (1-2 mm of model misfit) and texture, and were generated with less than 10 min of computational time. Analysis of the surface-registered 3D displacements indicate that the magnitude of motion ranged from 4.03 to 9.79 mm in the ten patient cases, and the amount of lateral shift was not related statistically to the direction of gravity (p = 0.73 ≫ 0.05) or the craniotomy size (p = 0.48 ≫ 0.05) at the beginning of surgery. CONCLUSIONS: The iSV-pMR surface registration method utilizes texture and geometry information to extract both global lateral shift and local nonrigid movement of the cortical surface in 3D. The results suggest small differences exist in surface-registered locations when compared to positions measured independently with a coregistered stylus and when the full iSV surface was aligned with model-updated MR. The effectiveness and efficiency of the registration method is also minimally disruptive to surgical workflow.

Cortical surface shift estimation using stereovision and optical flow motion tracking via projection image registration.

Stereovision is an important intraoperative imaging technique that captures the exposed parenchymal surface noninvasively during open cranial surgery. Estimating cortical surface shift efficiently and accurately is critical to compensate for brain deformation in the operating room (OR). In this study, we present an automatic and robust registration technique based on optical flow (OF) motion tracking to compensate for cortical surface displacement throughout surgery. Stereo images of the cortical surface were acquired at multiple time points after dural opening to reconstruct three-dimensional (3D) texture intensity-encoded cortical surfaces. A local coordinate system was established with its z-axis parallel to the average surface normal direction of the reconstructed cortical surface immediately after dural opening in order to produce two-dimensional (2D) projection images. A dense displacement field between the two projection images was determined directly from OF motion tracking without the need for feature identification or tracking. The starting and end points of the displacement vectors on the two cortical surfaces were then obtained following spatial mapping inversion to produce the full 3D displacement of the exposed cortical surface. We evaluated the technique with images obtained from digital phantoms and 18 surgical cases - 10 of which involved independent measurements of feature locations acquired with a tracked stylus for accuracy comparisons, and 8 others of which 4 involved stereo image acquisitions at three or more time points during surgery to illustrate utility throughout a procedure. Results from the digital phantom images were very accurate (0.05 pixels). In the 10 surgical cases with independently digitized point locations, the average agreement between feature coordinates derived from the cortical surface reconstructions was 1.7-2.1mm relative to those determined with the tracked stylus probe. The agreement in feature displacement tracking was also comparable to tracked probe data (difference in displacement magnitude was <1mm on average). The average magnitude of cortical surface displacement was 7.9 ± 5.7 mm (range 0.3-24.4 mm) in all patient cases with the displacement components along gravity being 5.2 ± 6.0 mm relative to the lateral movement of 2.4 ± 1.6 mm. Thus, our technique appears to be sufficiently accurate and computationally efficiency (typically ∼15 s), for applications in the OR.

Transrectal electrical impedance tomography of the prostate: spatially coregistered pathological findings for prostate cancer detection.

PURPOSE: Prostate cancer ranks as one of the most common malignancies and currently represents the second leading cancer-specific cause of death in men. The current use of single modality transrectal ultrasound (TRUS) for biopsy guidance has a limited sensitivity and specificity for accurately identifying cancerous lesions within the prostate. This study introduces a novel prostate cancer imaging method that combines TRUS with electrical impedance tomography (EIT) and reports on initial clinical findings based on in vivo measurements. METHODS: The ultrasound system provides anatomic information, which guides EIT image reconstruction. EIT reconstructions are correlated with semiquantitative pathological findings. Thin plate spline warping transformations are employed to overlay electrical impedance images and pathological maps describing the spatial distribution of prostate cancer, with the latter used as reference for data analysis. Clinical data were recorded from a total of 50 men prior to them undergoing radical prostatectomy for prostate cancer treatment. Student's t-tests were employed to statistically examine the electrical property difference between cancerous tissue and benign tissue as defined through histological assessment of the excised gland. RESULTS: Example EIT reconstructions are presented along with a statistical analysis comparing EIT and pathology. An average transformation error of 1.67% is found when 381 spatially coregistered pathological images are compared with their target EIT reconstructed counterparts. At EIT signal frequencies of 0.4, 3.2, and 25.6 kHz, paired-testing demonstrated that the conductivity of cancerous regions is significantly greater than that of benign regions ( p < 0.0304). CONCLUSIONS: These preliminary clinical findings suggest the potential benefits electrical impedance measurements might have for prostate cancer detection.

Intraoperative patient registration using volumetric true 3D ultrasound without fiducials.

PURPOSE: Accurate patient registration is crucial for effective image-guidance in open cranial surgery. Typically, it is accomplished by matching skin-affixed fiducials manually identified in the operating room (OR) with their counterparts in the preoperative images, which not only consumes OR time and personnel resources but also relies on the presence (and subsequent fixation) of the fiducials during the preoperative scans (until the procedure begins). In this study, the authors present a completely automatic, volumetric image-based patient registration technique that does not rely on fiducials by registering tracked (true) 3D ultrasound (3DUS) directly with preoperative magnetic resonance (MR) images. METHODS: Multistart registrations between binary 3DUS and MR volumes were first executed to generate an initial starting point without incorporating prior information on the US transducer contact point location or orientation for subsequent registration between grayscale 3DUS and MR via maximization of either mutual information (MI) or correlation ratio (CR). Patient registration was then computed through concatenation of spatial transformations. RESULTS: In ten (N = 10) patient cases, an average fiducial (marker) distance error (FDE) of 5.0 mm and 4.3 mm was achieved using MI or CR registration (FDE was smaller with CR vs MI in eight of ten cases), which are comparable to values reported for typical fiducial- or surface-based patient registrations. The translational and rotational capture ranges were found to be 24.0 mm and 27.0° for binary registrations (up to 32.8 mm and 36.4°), 12.2 mm and 25.6° for MI registrations (up to 18.3 mm and 34.4°), and 22.6 mm and 40.8° for CR registrations (up to 48.5 mm and 65.6°), respectively. The execution time to complete a patient registration was 12-15 min with parallel processing, which can be significantly reduced by confining the 3DUS transducer location to the center of craniotomy in MR before registration (an execution time of 5 min is achievable). CONCLUSIONS: Because common features deep in the brain and throughout the surgical volume of interest are used, intraoperative fiducial-less patient registration is possible on-demand, which is attractive in cases where preoperative patient registration is compromised (e.g., from loss∕movement of skin-affixed fiducials) or not possible (e.g., in cases of emergency when external fiducials were not placed in time). CR registration was more robust than MI (capture range about twice as big) and appears to be more accurate, although both methods are comparable to or better than fiducial-based registration in the patient cases evaluated. The results presented here suggest that 3DUS image-based patient registration holds promise for clinical application in the future.

Incorporating a biopsy needle as an electrode in transrectal electrical impedance imaging.

Previous studies have shown that prostate cancer may be detected by a combined transrectal ultrasound and electrical impedance tomography imaging system. However, the sensitivity of the imaging system is limited due to very little current established in the far field distant from the probe surface. Consequently, biopsy needles are introduced to the imaging system to provide current paths in the distal regions. This study demonstrates that image sensitivity can be improved by incorporating the needle electrodes. A phantom experiment is presented to show that contrast to the background is enhanced by 17.4% when imaging with needle electrodes. Simulated reconstructions and some preliminary clinical data also suggest the sensitivity improvement. In summary, TREIT with needle electrodes in the tissue may have great potential in future clinical prostate cancer detection.

Passive bioelectrical properties for assessing high- and low-grade prostate adenocarcinoma.

BACKGROUND: The electrical properties of prostate tissues are dependent on cellular morphology and have been demonstrated to distinguish between benign and malignant formations. Because Gleason grading is also based on tissue architecture we explored the hypothesis that the electrical properties might also provide discriminating power between high- and low-Gleason grade cancers. METHODS: Electrical properties (σ, ε, Δσ, σ(∞) , f(c) , and α) were gauged from 546 prostate tissue samples and correlated with histopathological assessment. Primary and secondary Gleason grades and a Gleason score were assigned to the tissues identified as cancer. We evaluated how well differently graded cancers were separable from benign tissues and from each other on the basis of these properties using ROC curves. RESULTS: Of the 546 prostate tissue samples, 71 were identified as cancer and 465 as benign. ε, Δσ, σ(∞) , and f(c) provided the most discriminatory power with area under the curves (AUCs) ranging from 0.77-0.82 for detecting any cancer, 0.72-0.8 for low-grade cancer, and increasing to 0.87-0.9 for detecting high-grade cancer. Further, ε, Δσ, and σ(∞) , provided AUCs ranging from 0.74 to 0.75 for discriminating between low- and high-grade cancers. CONCLUSIONS: Using the electrical properties to identify prostate cancer is improved when high-grade cancers are sought. These electrical properties can also discriminate between different grades of tumors. These findings suggest that technologies being developed to sense and image these properties in vivo may discriminate between aggressive and indolent lesions.

Statistical estimation of EIT electrode contact impedance using magic Toeplitz matrix.

The goal of the paper is to propose a fast and reliable method of simultaneous estimation of conductivity and electrode contact impedances for a homogeneous 2D disk. Magic Toeplitz matrix as the Neumann-to-Dirichlet map with finite width electrodes plays the central role in our linear model, called the gapZ model. This model enables testing of various hypotheses using the F-test, such as the uniformity of electrode impedances and their statistical significance. The gapZ model is compared with the finite element approximation, and illustrated and validated with a phantom tank experiment filled with saline. Further this model was illustrated with the patient breast EIT data to identify bad contact electrodes.

Quantitative fluorescence in intracranial tumor: implications for ALA-induced PpIX as an intraoperative biomarker.

OBJECT: Accurate discrimination between tumor and normal tissue is crucial for optimal tumor resection. Qualitative fluorescence of protoporphyrin IX (PpIX), synthesized endogenously following δ-aminolevulinic acid (ALA) administration, has been used for this purpose in high-grade glioma (HGG). The authors show that diagnostically significant but visually imperceptible concentrations of PpIX can be quantitatively measured in vivo and used to discriminate normal from neoplastic brain tissue across a range of tumor histologies. METHODS: The authors studied 14 patients with diagnoses of low-grade glioma (LGG), HGG, meningioma, and metastasis under an institutional review board-approved protocol for fluorescence-guided resection. The primary aim of the study was to compare the diagnostic capabilities of a highly sensitive, spectrally resolved quantitative fluorescence approach to conventional fluorescence imaging for detection of neoplastic tissue in vivo. RESULTS: A significant difference in the quantitative measurements of PpIX concentration occurred in all tumor groups compared with normal brain tissue. Receiver operating characteristic (ROC) curve analysis of PpIX concentration as a diagnostic variable for detection of neoplastic tissue yielded a classification efficiency of 87% (AUC = 0.95, specificity = 92%, sensitivity = 84%) compared with 66% (AUC = 0.73, specificity = 100%, sensitivity = 47%) for conventional fluorescence imaging (p < 0.0001). More than 81% (57 of 70) of the quantitative fluorescence measurements that were below the threshold of the surgeon's visual perception were classified correctly in an analysis of all tumors. CONCLUSIONS: These findings are clinically profound because they demonstrate that ALA-induced PpIX is a targeting biomarker for a variety of intracranial tumors beyond HGGs. This study is the first to measure quantitative ALA-induced PpIX concentrations in vivo, and the results have broad implications for guidance during resection of intracranial tumors.

Real-time interpolation for true 3-dimensional ultrasound image volumes.

We compared trilinear interpolation to voxel nearest neighbor and distance-weighted algorithms for fast and accurate processing of true 3-dimensional ultrasound (3DUS) image volumes. In this study, the computational efficiency and interpolation accuracy of the 3 methods were compared on the basis of a simulated 3DUS image volume, 34 clinical 3DUS image volumes from 5 patients, and 2 experimental phantom image volumes. We show that trilinear interpolation improves interpolation accuracy over both the voxel nearest neighbor and distance-weighted algorithms yet achieves real-time computational performance that is comparable to the voxel nearest neighbor algrorithm (1-2 orders of magnitude faster than the distance-weighted algorithm) as well as the fastest pixel-based algorithms for processing tracked 2-dimensional ultrasound images (0.035 seconds per 2-dimesional cross-sectional image [76,800 pixels interpolated, or 0.46 ms/1000 pixels] and 1.05 seconds per full volume with a 1-mm(3) voxel size [4.6 million voxels interpolated, or 0.23 ms/1000 voxels]). On the basis of these results, trilinear interpolation is recommended as a fast and accurate interpolation method for rectilinear sampling of 3DUS image acquisitions, which is required to facilitate subsequent processing and display during operating room procedures such as image-guided neurosurgery.

Adaptive spatial calibration of a 3D ultrasound system.

PURPOSE: The authors present a method devised to calibrate the spatial relationship between a 3D ultrasound scanhead and its tracker completely automatically and reliably. The user interaction is limited to collecting ultrasound data on which the calibration is based. METHODS: The method of calibration is based on images of a fixed plane of unknown location with respect to the 3D tracking system. This approach has, for advantage, to eliminate the measurement of the plane location as a source of error. The devised method is sufficiently general and adaptable to calibrate scanheads for 2D images and 3D volume sets using the same approach. The basic algorithm for both types of scanheads is the same and can be run unattended fully automatically once the data are collected. The approach was devised by seeking the simplest and most robust solutions for each of the steps required. These are the identification of the plane intersection within the images or volumes and the optimization method used to compute a calibration transformation matrix. The authors use adaptive algorithms in these two steps to eliminate data that would otherwise prevent the convergence of the procedure, which contributes to the robustness of the method. RESULTS: The authors have run tests amounting to 57 runs of the calibration on two a scanhead that produce 3D imaging volumes, at all the available scales. The authors evaluated the system on two criteria: Robustness and accuracy. The program converged to useful values unattended for every one of the tests (100%). Its accuracy, based on the measured location of a reference plane, was estimated to be 0.7 +/- 0.6 mm for all tests combined. CONCLUSIONS: The system presented is robust and allows unattended computations of the calibration parameters required for freehand tracked ultrasound based on either 2D or 3D imaging systems.

Electrical properties of prostatic tissues: II. Spectral admittivity properties.

PURPOSE: The electrical properties of prostate tissues gauged at discrete frequencies provide sufficient contrast to discriminate malignant from benign prostatic tissues. The frequency dependence of these properties is also a function of tissue morphology. We evaluated the potential of this spectral dependence to provide additional diagnostic information for prostate cancer detection. MATERIALS AND METHODS: Electrical conductivity and permittivity were recorded from 50 ex vivo prostates at 31 logarithmically spaced frequencies of 100 Hz to 100 kHz. We used a well established, 4 parameter (sigma(infinity), Delta sigma, f(c) and alpha) model to describe individual spectra with each model parameter influenced by tissue morphology. We evaluated these parameters in terms of discriminatory power using ROC curves. RESULTS: Of the 4 spectral parameters sigma(infinity) and f(c) were significantly greater in cancer than in benign tissues and Delta sigma was significantly more negative in cancer than in benign tissues (each p <0.0001). f(c) provided the maximum discriminating power with an ROC AUC of 0.821 and 81.5% specificity at 70% sensitivity. Also, sigma(infinity) and Delta sigma provided high levels of discrimination with an AUC of 0.770 and 0.782, respectively. CONCLUSIONS: Spectral electrical admittivity properties provide sufficient levels of ex vivo cancer discrimination that may potentially enhance disease localization when prostate cancer is suspected. The development of novel technologies gauging these properties in vivo has the potential to provide new tissue characterizing tools for prostate cancer detection and identification.

Electrical properties of prostatic tissues: I. Single frequency admittivity properties.

PURPOSE: Electrical properties of the prostate may provide sufficient contrast for distinguishing malignant and benign formations in the gland. We evaluated how well these electrical properties discriminate cancer from noncancer tissues in the prostate. MATERIALS AND METHODS: Electrical admittivity (conductivity and permittivity) was recorded at 31 discrete frequencies of 0.1 to 100 kHz from each of 50 ex vivo human prostates. A specifically designed admittivity probe was used to gauge these electrical properties from sectioned prostate specimens. The specific tissue area probed was marked to provide precise colocalization between tissue histological assessment and recorded admittivity spectra. RESULTS: Adenocarcinoma, benign prostatic hyperplasia, nonhyperplastic glandular tissue and stromal tissue were the primary tissue types probed. Mean cancer conductivity was significantly less than that of glandular and stromal tissues at all frequencies (p <0.05), while mean cancer permittivity was significantly greater than that of all benign tissues at 100 kHz (p <0.0001). ROC curves showed that permittivity at 100 kHz was optimal for discriminating cancer from all benign tissues. This parameter had 77% specificity at 70% sensitivity and an ROC AUC of 0.798. CONCLUSIONS: The contrast in electrical admittivity properties of different prostate tissues shows promise for distinguishing cancer from benign tissues. Sensitivity and specificity exceed those reported for current prostate specific antigen screening practices at low prostate specific antigen, making this an attractive addition to the clinical armamentarium for identifying prostate cancer.

Data assimilation using a gradient descent method for estimation of intraoperative brain deformation.

Biomechanical models that simulate brain deformation are gaining attention as alternatives for brain shift compensation. One approach, known as the "forced-displacement method", constrains the model to exactly match the measured data through boundary condition (BC) assignment. Although it improves model estimates and is computationally attractive, the method generates fictitious forces and may be ill-advised due to measurement uncertainty. Previously, we have shown that by assimilating intraoperatively acquired brain displacements in an inversion scheme, the Representer algorithm (REP) is able to maintain stress-free BCs and improve model estimates by 33% over those without data guidance in a controlled environment. However, REP is computationally efficient only when a few data points are used for model guidance because its costs scale linearly in the number of data points assimilated, thereby limiting its utility (and accuracy) in clinical settings. In this paper, we present a steepest gradient descent algorithm (SGD) whose computational complexity scales nearly invariantly with the number of measurements assimilated by iteratively adjusting the forcing conditions to minimize the difference between measured and model-estimated displacements (model-data misfit). Solutions of full linear systems of equations are achieved with a parallelized direct solver on a shared-memory, eight-processor Linux cluster. We summarize the error contributions from the entire process of model-updated image registration compensation and we show that SGD is able to attain model estimates comparable to or better than those obtained with REP, capturing about 74-82% of tumor displacement, but with a computational effort that is significantly less (a factor of 4-fold or more reduction relative to REP) and nearly invariant to the amount of sparse data involved when the number of points assimilated is large. Based on five patient cases, an average computational cost of approximately 2 min for estimating whole-brain deformation has been achieved with SGD using 100 sparse data points, suggesting the new algorithm is sufficiently fast with adequate accuracy for routine use in the operating room (OR).

The correlation of in vivo and ex vivo tissue dielectric properties to validate electromagnetic breast imaging: initial clinical experience.

Electromagnetic (EM) breast imaging provides low-cost, safe and potentially a more specific modality for cancer detection than conventional imaging systems. A primary difficulty in validating these EM imaging modalities is that the true dielectric property values of the particular breast being imaged are not readily available on an individual subject basis. Here, we describe our initial experience in seeking to correlate tomographic EM imaging studies with discrete point spectroscopy measurements of the dielectric properties of breast tissue. The protocol we have developed involves measurement of in vivo tissue properties during partial and full mastectomy procedures in the operating room (OR) followed by ex vivo tissue property recordings in the same locations in the excised tissue specimens in the pathology laboratory immediately after resection. We have successfully applied all of the elements of this validation protocol in a series of six women with cancer diagnoses. Conductivity and permittivity gauged from ex vivo samples over the frequency range 100 Hz-8.5 GHz are found to be similar to those reported in the literature. A decrease in both conductivity and permittivity is observed when these properties are gauged from ex vivo samples instead of in vivo. We present these results in addition to a case study demonstrating how discrete point spectroscopy measurements of the tissue can be correlated and used to validate EM imaging studies.

Brain-skull contact boundary conditions in an inverse computational deformation model.

Biomechanical models simulating brain motion under loading and boundary conditions in the operating room (OR) are gaining attention as alternatives for brain shift compensation during open cranial neurosurgeries. Although the significance of brain-skull boundary conditions (BCs) in these models has been explored in dynamic simulations, it has not been fully investigated in models representing the quasi-static brain motion that prevails during neurosurgery. In this study, we extend the application of a brain-skull contact BC by incorporating it into an inversion estimation scheme for the deformation field using the steepest gradient descent (SGD) framework. The technique allows parenchymal surface motion normal to the skull while maintaining stress-free BCs at the craniotomy and minimizing the effect of measurement noise. Application of the algorithm in five clinical cases using sparse data generated at the tumor boundary confirms the significance of brain-skull BCs in the model response. Specifically, the results demonstrate that the contact BC enhances model flexibility and achieves improved or comparable performance at the tumor boundary (recovering about 85% of the deformation) relative to that obtained when normal motion of the parenchymal surface is not allowed. It also significantly improves model estimation accuracy at the craniotomy (1.6mm on average), especially when the normal motion is large. The importance of the method is that model performance significantly improves when brain-skull contact influences the deformation field but does not degrade when the contact is less critical and simpler BCs would suffice. The computational cost of the technique is currently 3.9 min on average, but may be further reduced by applying an iterative solver to the linear systems of equations involved and/or by local refinement of the mesh in regions of interest.

Combining multiple true 3D ultrasound image volumes through re-registration and rasterization.

We present an accurate and efficient technique to combine and rasterize multiple 3D ultrasound (3DUS) image volumes originally presented in spherical coordinates into a single, 3D Cartesian image that uniformly samples the total field of view. To ensure the consistency of merged image content in overlapping regions, image re-registration was performed by maximizing mutual information (MI). The technique was applied to 22 3DUS image volumes obtained during five neurosurgical patient cases. The computational cost of the approach increases linearly with the number of images involved (average time to combine and rasterize one pair of 3DUS images was 1.5 sec). Interpolation was approximately 20% more accurate in overlapping regions when reregistration was performed before rasterization and minimized feature loss and/or blurring that was evident without re-registration. In addition, we report the average translational (35.2 mm) and rotational (38.5 degrees) capture ranges for the MI re-registration of two volumetric 3DUS images. The technique is applicable in any clinical application in which volumetric true 3DUS is acquired.

Mutual-information-based image to patient re-registration using intraoperative ultrasound in image-guided neurosurgery.

An image-based re-registration scheme has been developed and evaluated that uses fiducial registration as a starting point to maximize the normalized mutual information (nMI) between intraoperative ultrasound (iUS) and preoperative magnetic resonance images (pMR). We show that this scheme significantly (p<0.001) reduces tumor boundary misalignment between iUS pre-durotomy and pMR from an average of 2.5 mm to 1.0 mm in six resection surgeries. The corrected tumor alignment before dural opening provides a more accurate reference for assessing subsequent intraoperative tumor displacement, which is important for brain shift compensation as surgery progresses. In addition, we report the translational and rotational capture ranges necessary for successful convergence of the nMI registration technique (5.9 mm and 5.2 deg, respectively). The proposed scheme is automatic, sufficiently robust, and computationally efficient (<2 min), and holds promise for routine clinical use in the operating room during image-guided neurosurgical procedures.

Genetic and least squares algorithms for estimating spectral EIS parameters of prostatic tissues.

We employed electrical impedance spectroscopy (EIS) to evaluate the electrical properties of prostatic tissues. We collected freshly excised prostates from 23 men immediately following radical prostatectomy. The prostates were sectioned into 3 mm slices and electrical property measurements of complex resistivity were recorded from each of the slices using an impedance probe over the frequency range of 100 Hz to 100 kHz. The area probed was marked so that following tissue fixation and slide preparation, histological assessment could be correlated directly with the recorded EIS spectra. Prostate cancer (CaP), benign prostatic hyperplasia (BPH), non-hyperplastic glandular tissue and stroma were the primary prostatic tissue types probed. Genetic and least squares parameter estimation algorithms were implemented for fitting a Cole-type resistivity model to the measured data. The four multi-frequency-based spectral parameters defining the recorded spectrum (rho(infinity), Deltarho, f(c) and alpha) were determined using these algorithms and statistically analyzed with respect to the tissue type. Both algorithms fit the measured data well, with the least squares algorithm having a better average goodness of fit (95.2 mOmega m versus 109.8 mOmega m) and a faster execution time (80.9 ms versus 13 637 ms) than the genetic algorithm. The mean parameters, from all tissue samples, estimated using the genetic algorithm ranged from 4.44 to 5.55 Omega m, 2.42 to 7.14 Omega m, 3.26 to 6.07 kHz and 0.565 to 0.654 for rho(infinity), Deltarho, f(c) and alpha, respectively. These same parameters estimated using the least squares algorithm ranged from 4.58 to 5.79 Omega m, 2.18 to 6.98 Omega m, 2.97 to 5.06 kHz and 0.621 to 0.742 for rho(infinity), Deltarho, f(c) and alpha, respectively. The ranges of these parameters were similar to those reported in the literature. Further, significant differences (p < 0.01) were observed between CaP and BPH for the spectral parameters Deltarho and f(c); this is especially important since current prostate cancer screening methods do not reliably differentiate between these two tissue types.