Tse ZTH, Dumoulin CL, Clifford GD, Schweitzer J, Qin L, Oster J, Jerosch-Herold M, Kwong RY, Michaud G, Stevenson WG, et al. A 1.5T MRI-conditional 12-lead Electrocardiogram for MRI and Intra-MR Intervention. Magn Reson Med. 2014;71 (3) :1336-47.Abstract

PURPOSE: High-fidelity 12-lead electrocardiogram (ECG) is important for physiological monitoring of patients during MR-guided intervention and cardiac MRI. Issues in obtaining noncorrupted ECGs inside MRI include a superimposed magneto-hydro-dynamic voltage, gradient switching-induced voltages, and radiofrequency heating. These problems increase with magnetic field. The aim of this study is to develop and clinically validate a 1.5T MRI-conditional 12-lead ECG system. METHODS: The system was constructed with transmission lines to reduce radiofrequency induction and switching circuits to remove induced voltages. Adaptive filters, trained by 12-lead measurements outside MRI and in two orientations inside MRI, were used to remove the magneto-hydro-dynamic voltage. The system was tested on 10 (one exercising) volunteers and four arrhythmia patients. RESULTS: Switching circuits removed most imaging-induced voltages (residual noise <3% of the R-wave). Magneto-hydro-dynamic voltage removal provided intra-MRI ECGs that varied by <3.8% from those outside the MRI, preserving the true S-wave to T-wave segment. In premature ventricular contraction (PVC) patients, clean ECGs separated premature ventricular contraction and sinus rhythm beats. Measured heating was <1.5°C. The system reliably acquired multiphase (steady-state free precession) wall-motion-cine and phase-contrast-cine scans, including subjects in whom 4-lead gating failed. The system required a minimum repetition time of 4 ms to allow robust ECG processing. CONCLUSION: High-fidelity intra-MRI 12-lead ECG is possible.

Gregory ST, Schmidt EJ, Zhang SH, Tse ZTH. 3DQRS: A Method to Obtain Reliable QRS Complex Detection within High Field MRI using 12-Lead Electrocardiogram Traces. Magn Reson Med. 2014;71 (4) :1374-80.Abstract

PURPOSE: To develop a technique that accurately detects the QRS complex in 1.5 Tesla (T), 3T, and 7T MRI scanners. METHODS: During early systole, blood is rapidly ejected into the aortic arch, traveling perpendicular to the MRI's main field, which produces a strong voltage (V(MHD)) that eclipses the QRS complex. Greater complexity arises in arrhythmia patients, since V(MHD) varies between sinus-rhythm and arrhythmic beats. The 3DQRS method uses a kernel consisting of 6 electrocardiogram (ECG) precordial leads (V1-V6), compiled from a 12-lead ECG performed outside the magnet. The kernel is cross-correlated with signals acquired inside the MRI to identify the QRS complex in real time. The 3DQRS method was evaluated against a vectorcardiogram (VCG)-based approach in two premature ventricular contraction (PVC) and two atrial fibrillation (AF) patients, a healthy exercising athlete, and eight healthy volunteers, within 1.5T and 3T MRIs, using a prototype MRI-conditional 12-lead ECG system. Two volunteers were recorded at 7T using a Holter recorder. RESULTS: For QRS complex detection, 3DQRS subject-averaged sensitivity levels, relative to VCG were: 1.5T (100% versus 96.7%), 3T (98.9% versus 92.2%), and 7T (96.2% versus 77.7%). CONCLUSION: The 3DQRS method was shown to be more effective in cardiac gating than a conventional VCG-based method.

Madore B, Chiou J-yuan G, Chu R, Chao T-C, Maier SE. Accelerated Multi-shot Diffusion Imaging. Magn Reson Med. 2014;72 (2) :324-36.Abstract

PURPOSE: To reduce image distortion in MR diffusion imaging using an accelerated multi-shot method. METHODS: The proposed method exploits the fact that diffusion-encoded data tend to be sparse when represented in the kb-kd space, where kb and kd are the Fourier transform duals of b and d, the b-factor and the diffusion direction, respectively. Aliasing artifacts are displaced toward under-used regions of the kb-kd plane, allowing nonaliased signals to be recovered. A main characteristic of the proposed approach is how thoroughly the navigator information gets used during reconstruction: The phase of navigator images is used for motion correction, while the magnitude of the navigator signal in kb-kd space is used for regularization purposes. As opposed to most acceleration methods based on compressed sensing, the proposed method reduces the number of ky lines needed for each diffusion-encoded image, but not the total number of images required. Consequently, it tends to be most effective at reducing image distortion rather than reducing total scan time. RESULTS: Results are presented for three volunteers with acceleration factors ranging from 4 to 8, with and without the inclusion of parallel imaging. CONCLUSION: An accelerated motion-corrected diffusion imaging method was introduced that achieves good image quality at relatively high acceleration factors.

Calligaris D, Caragacianu D, Liu X, Norton I, Thompson CJ, Richardson AL, Golshan M, Easterling ML, Santagata S, Dillon DA, et al. Application of Desorption Electrospray Ionization Mass Spectrometry Imaging in Breast Cancer Margin Analysis. Proc Natl Acad Sci U S A. 2014;111 (42) :15184-9.Abstract

Distinguishing tumor from normal glandular breast tissue is an important step in breast-conserving surgery. Because this distinction can be challenging in the operative setting, up to 40% of patients require an additional operation when traditional approaches are used. Here, we present a proof-of-concept study to determine the feasibility of using desorption electrospray ionization mass spectrometry imaging (DESI-MSI) for identifying and differentiating tumor from normal breast tissue. We show that tumor margins can be identified using the spatial distributions and varying intensities of different lipids. Several fatty acids, including oleic acid, were more abundant in the cancerous tissue than in normal tissues. The cancer margins delineated by the molecular images from DESI-MSI were consistent with those margins obtained from histological staining. Our findings prove the feasibility of classifying cancerous and normal breast tissues using ambient ionization MSI. The results suggest that an MS-based method could be developed for the rapid intraoperative detection of residual cancer tissue during breast-conserving surgery.

Fedorov A, Wells WM, Kikinis R, Tempany CM, Vangel MG. Application of Tolerance Limits to the Characterization of Image Registration Performance. IEEE Trans Med Imaging. 2014;33 (7) :1541-50.Abstract

Deformable image registration is used increasingly in image-guided interventions and other applications. However, validation and characterization of registration performance remain areas that require further study. We propose an analysis methodology for deriving tolerance limits on the initial conditions for deformable registration that reliably lead to a successful registration. This approach results in a concise summary of the probability of registration failure, while accounting for the variability in the test data. The (β, γ) tolerance limit can be interpreted as a value of the input parameter that leads to successful registration outcome in at least 100β% of cases with the 100γ% confidence. The utility of the methodology is illustrated by summarizing the performance of a deformable registration algorithm evaluated in three different experimental setups of increasing complexity. Our examples are based on clinical data collected during MRI-guided prostate biopsy registered using publicly available deformable registration tool. The results indicate that the proposed methodology can be used to generate concise graphical summaries of the experiments, as well as a probabilistic estimate of the registration outcome for a future sample. Its use may facilitate improved objective assessment, comparison and retrospective stress-testing of deformable.

Jayender J, Chikarmane S, Jolesz FA, Gombos E. Automatic Segmentation of Invasive Breast Carcinomas from Dynamic Contrast-Enhanced MRi using Time Series Analysis. J Magn Reson Imaging. 2014;40 (2) :467-75.Abstract

PURPOSE: To accurately segment invasive ductal carcinomas (IDCs) from dynamic contrast-enhanced MRI (DCE-MRI) using time series analysis based on linear dynamic system (LDS) modeling. MATERIALS AND METHODS: Quantitative segmentation methods based on black-box modeling and pharmacokinetic modeling are highly dependent on imaging pulse sequence, timing of bolus injection, arterial input function, imaging noise, and fitting algorithms. We modeled the underlying dynamics of the tumor by an LDS and used the system parameters to segment the carcinoma on the DCE-MRI. Twenty-four patients with biopsy-proven IDCs were analyzed. The lesions segmented by the algorithm were compared with an expert radiologist's segmentation and the output of a commercial software, CADstream. The results are quantified in terms of the accuracy and sensitivity of detecting the lesion and the amount of overlap, measured in terms of the Dice similarity coefficient (DSC). RESULTS: The segmentation algorithm detected the tumor with 90% accuracy and 100% sensitivity when compared with the radiologist's segmentation and 82.1% accuracy and 100% sensitivity when compared with the CADstream output. The overlap of the algorithm output with the radiologist's segmentation and CADstream output, computed in terms of the DSC was 0.77 and 0.72, respectively. The algorithm also shows robust stability to imaging noise. Simulated imaging noise with zero mean and standard deviation equal to 25% of the base signal intensity was added to the DCE-MRI series. The amount of overlap between the tumor maps generated by the LDS-based algorithm from the noisy and original DCE-MRI was DSC = 0.95. CONCLUSION: The time-series analysis based segmentation algorithm provides high accuracy and sensitivity in delineating the regions of enhanced perfusion corresponding to tumor from DCE-MRI.

Maier SE, Mitsouras D, Mulkern RV. Avian Egg Latebra as Brain Tissue Water Diffusion Model. Magn Reson Med. 2014;72 (2) :501-9.Abstract

PURPOSE: Simplified models of non-monoexponential diffusion signal decay are of great interest to study the basic constituents of complex diffusion behavior in tissues. The latebra, a unique structure uniformly present in the yolk of avian eggs, exhibits a non-monoexponential diffusion signal decay. This model is more complex than simple phantoms based on differences between water and lipid diffusion, but is also devoid of microscopic structures with preferential orientation or perfusion effects. METHODS: Diffusion scans with multiple b-values were performed on a clinical 3 Tesla system in raw and boiled chicken eggs equilibrated to room temperature. Diffusion encoding was applied over the ranges 5-5,000 and 5-50,000 s/mm(2). A low read-out bandwidth and chemical shift was used for reliable lipid/water separation. Signal decays were fitted with exponential functions. RESULTS: The latebra, when measured over the 5-5,000 s/mm(2) range, exhibited independent of preparation clearly biexponential diffusion, with diffusion parameters similar to those typically observed in in vivo human brain. For the range 5-50,000 s/mm(2), there was evidence of a small third, very slow diffusing water component. CONCLUSION: The latebra of the avian egg contains membrane structures, which may explain a deviation from a simple monoexponential diffusion signal decay, which is remarkably similar to the deviation observed in brain tissue.

Fedorov A, Fluckiger J, Ayers GD, Li X, Gupta SN, Tempany C, Mulkern R, Yankeelov TE, Fennessy FM. A Comparison of Two Methods for Estimating DCE-MRI Parameters via Individual and Cohort Based AIFs in Prostate Cancer: A Step towards Practical Implementation. Magn Reson Imaging. 2014;32 (4) :321-9.Abstract

Multi-parametric Magnetic Resonance Imaging, and specifically Dynamic Contrast Enhanced (DCE) MRI, play increasingly important roles in detection and staging of prostate cancer (PCa). One of the actively investigated approaches to DCE MRI analysis involves pharmacokinetic (PK) modeling to extract quantitative parameters that may be related to microvascular properties of the tissue. It is well-known that the prescribed arterial blood plasma concentration (or Arterial Input Function, AIF) input can have significant effects on the parameters estimated by PK modeling. The purpose of our study was to investigate such effects in DCE MRI data acquired in a typical clinical PCa setting. First, we investigated how the choice of a semi-automated or fully automated image-based individualized AIF (iAIF) estimation method affects the PK parameter values; and second, we examined the use of method-specific averaged AIF (cohort-based, or cAIF) as a means to attenuate the differences between the two AIF estimation methods. Two methods for automated image-based estimation of individualized (patient-specific) AIFs, one of which was previously validated for brain and the other for breast MRI, were compared. cAIFs were constructed by averaging the iAIF curves over the individual patients for each of the two methods. Pharmacokinetic analysis using the Generalized kinetic model and each of the four AIF choices (iAIF and cAIF for each of the two image-based AIF estimation approaches) was applied to derive the volume transfer rate (K(trans)) and extravascular extracellular volume fraction (ve) in the areas of prostate tumor. Differences between the parameters obtained using iAIF and cAIF for a given method (intra-method comparison) as well as inter-method differences were quantified. The study utilized DCE MRI data collected in 17 patients with histologically confirmed PCa. Comparison at the level of the tumor region of interest (ROI) showed that the two automated methods resulted in significantly different (p<0.05) mean estimates of ve, but not of K(trans). Comparing cAIF, different estimates for both ve, and K(trans) were obtained. Intra-method comparison between the iAIF- and cAIF-driven analyses showed the lack of effect on ve, while K(trans) values were significantly different for one of the methods. Our results indicate that the choice of the algorithm used for automated image-based AIF determination can lead to significant differences in the values of the estimated PK parameters. K(trans) estimates are more sensitive to the choice between cAIF/iAIF as compared to ve, leading to potentially significant differences depending on the AIF method. These observations may have practical consequences in evaluating the PK analysis results obtained in a multi-site setting.

Parisot S, Wells W, Chemouny S, Duffau H, Paragios N. Concurrent Tumor Segmentation and Registration with Uncertainty-based Sparse Non-uniform Graphs. Med Image Anal. 2014;18 (4) :647-59.Abstract

In this paper, we present a graph-based concurrent brain tumor segmentation and atlas to diseased patient registration framework. Both segmentation and registration problems are modeled using a unified pairwise discrete Markov Random Field model on a sparse grid superimposed to the image domain. Segmentation is addressed based on pattern classification techniques, while registration is performed by maximizing the similarity between volumes and is modular with respect to the matching criterion. The two problems are coupled by relaxing the registration term in the tumor area, corresponding to areas of high classification score and high dissimilarity between volumes. In order to overcome the main shortcomings of discrete approaches regarding appropriate sampling of the solution space as well as important memory requirements, content driven samplings of the discrete displacement set and the sparse grid are considered, based on the local segmentation and registration uncertainties recovered by the min marginal energies. State of the art results on a substantial low-grade glioma database demonstrate the potential of our method, while our proposed approach shows maintained performance and strongly reduced complexity of the model.

Langs G, Sweet A, Lashkari D, Tie Y, Rigolo L, Golby AJ, Golland P. Decoupling Function and Anatomy in Atlases of Functional Connectivity patterns: Language Mapping in Tumor Patients. Neuroimage. 2014;103 :462-75.Abstract

In this paper we construct an atlas that summarizes functional connectivity characteristics of a cognitive process from a population of individuals. The atlas encodes functional connectivity structure in a low-dimensional embedding space that is derived from a diffusion process on a graph that represents correlations of fMRI time courses. The functional atlas is decoupled from the anatomical space, and thus can represent functional networks with variable spatial distribution in a population. In practice the atlas is represented by a common prior distribution for the embedded fMRI signals of all subjects. We derive an algorithm for fitting this generative model to the observed data in a population. Our results in a language fMRI study demonstrate that the method identifies coherent and functionally equivalent regions across subjects. The method also successfully maps functional networks from a healthy population used as a training set to individuals whose language networks are affected by tumors.

Tie Y, Rigolo L, Norton IH, Huang RY, Wu W, Orringer D, Mukundan S, Golby AJ. Defining Language Networks from Resting-state fMRI for Surgical Planning: A Feasibility Study. Hum Brain Mapp. 2014;35 (3) :1018-30.Abstract

Presurgical language mapping for patients with lesions close to language areas is critical to neurosurgical decision-making for preservation of language function. As a clinical noninvasive imaging technique, functional MRI (fMRI) is used to identify language areas by measuring blood-oxygen-level dependent (BOLD) signal change while patients perform carefully timed language vs. control tasks. This task-based fMRI critically depends on task performance, excluding many patients who have difficulty performing language tasks due to neurologic deficits. On the basis of recent discovery of resting-state fMRI (rs-fMRI), we propose a "task-free" paradigm acquiring fMRI data when patients simply are at rest. This paradigm is less demanding for patients to perform and easier for technologists to administer. We investigated the feasibility of this approach in right-handed healthy control subjects. First, group independent component analysis (ICA) was applied on the training group (14 subjects) to identify group level language components based on expert rating results. Then, four empirically and structurally defined language network templates were assessed for their ability to identify language components from individuals' ICA output of the testing group (18 subjects) based on spatial similarity analysis. Results suggest that it is feasible to extract language activations from rs-fMRI at the individual subject level, and two empirically defined templates (that focuses on frontal language areas and that incorporates both frontal and temporal language areas) demonstrated the best performance. We propose a semi-automated language component identification procedure and discuss the practical concerns and suggestions for this approach to be used in clinical fMRI language mapping.

Anand M, King F, Ungi T, Lasso A, Rudan J, Jayender J, Fritz J, Carrino JA, Jolesz FA, Fichtinger G. Design and Development of a Mobile Image Overlay System for Needle Interventions. Conf Proc IEEE Eng Med Biol Soc. 2014;2014 :6159-62.Abstract

Previously, a static and adjustable image overlay systems were proposed for aiding needle interventions. The system was either fixed to a scanner or mounted over a large articulated counterbalanced arm. Certain drawbacks associated with these systems limited the clinical translation. In order to minimize these limitations, we present the mobile image overlay system with the objective of reduced system weight, smaller dimension, and increased tracking accuracy. The design study includes optimal workspace definition, selection of display device, mirror, and laser source. The laser plane alignment, phantom design, image overlay plane calibration, and system accuracy validation methods are discussed. The virtual image is generated by a tablet device and projected into the patient by using a beamsplitter mirror. The viewbox weight (1.0 kg) was reduced by 8.2 times and image overlay plane tracking precision (0.21 mm, STD = 0.05) was improved by 5 times compared to previous system. The automatic self-calibration of the image overlay plane was achieved in two simple steps and can be done away from patient table. The fiducial registration error of the physical phantom to scanned image volume registration was 1.35 mm (STD = 0.11). The reduced system weight and increased accuracy of optical tracking should enable the system to be hand held by the physician and explore the image volume over the patient for needle interventions.

Fennessy FM, McKay RR, Beard CJ, Taplin M-E, Tempany CM. Dynamic Contrast-enhanced Magnetic Resonance Imaging in Prostate Cancer Clinical Trials: Potential Roles and Possible Pitfalls. Transl Oncol. 2014;7 (1) :120-9.Abstract

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) evaluates the tissue microvasculature and may have a role in assessing and predicting therapeutic response in prostate cancer (PCa). In this review, we review principles of DCE-MRI and present the potential quantitative information that can be obtained. We discuss how it may be used as a biomarker for treatment with antiangiogenic and antivascular agents and potentially identify patients with PCa who may benefit from this form of therapy. Likewise, DCE-MRI may play a role in assessing response to combined androgen deprivation therapy and radiation therapy and theoretically could be a prognostic biomarker in evaluating second-generation hormone therapies. We also address the challenges of using DCE-MRI in PCa clinical trials and discuss the difficulties with standardization of this methodology to allow for biomarker validation, with particular reference to PCa.

Forgacs PB, Sarkis R, Folkerth R, Golby AJ, Hsu L, Bubrick EJ, Dworetzky BA. Focal Cortical Dysplasia IIb Presenting as Slowly Progressive Aphasia Mimicking a Brain Tumor. Seizure. 2014;23 (2) :161-3.
Wachinger C, Golland P, Reuter M, Wells III WM. Gaussian Process Interpolation for Uncertainty Estimation in Image Registration. Med Image Comput Comput Assist Interv. 2014;17 (Pt 1) :267-74.Abstract

Intensity-based image registration requires resampling images on a common grid to evaluate the similarity function. The uncertainty of interpolation varies across the image, depending on the location of resampled points relative to the base grid. We propose to perform Bayesian inference with Gaussian processes, where the covariance matrix of the Gaussian process posterior distribution estimates the uncertainty in interpolation. The Gaussian process replaces a single image with a distribution over images that we integrate into a generative model for registration. Marginalization over resampled images leads to a new similarity measure that includes the uncertainty of the interpolation. We demonstrate that our approach increases the registration accuracy and propose an efficient approximation scheme that enables seamless integration with existing registration methods.

Santagata S, Eberlin LS, Norton I, Calligaris D, Feldman DR, Ide JL, Liu X, Wiley JS, Vestal ML, Ramkissoon SH, et al. Intraoperative Mass Spectrometry Mapping of an Onco-metabolite to Guide Brain Tumor Surgery. Proc Natl Acad Sci U S A. 2014;111 (30) :11121-6.Abstract

For many intraoperative decisions surgeons depend on frozen section pathology, a technique developed over 150 y ago. Technical innovations that permit rapid molecular characterization of tissue samples at the time of surgery are needed. Here, using desorption electrospray ionization (DESI) MS, we rapidly detect the tumor metabolite 2-hydroxyglutarate (2-HG) from tissue sections of surgically resected gliomas, under ambient conditions and without complex or time-consuming preparation. With DESI MS, we identify isocitrate dehydrogenase 1-mutant tumors with both high sensitivity and specificity within minutes, immediately providing critical diagnostic, prognostic, and predictive information. Imaging tissue sections with DESI MS shows that the 2-HG signal overlaps with areas of tumor and that 2-HG levels correlate with tumor content, thereby indicating tumor margins. Mapping the 2-HG signal onto 3D MRI reconstructions of tumors allows the integration of molecular and radiologic information for enhanced clinical decision making. We also validate the methodology and its deployment in the operating room: We have installed a mass spectrometer in our Advanced Multimodality Image Guided Operating (AMIGO) suite and demonstrate the molecular analysis of surgical tissue during brain surgery. This work indicates that metabolite-imaging MS could transform many aspects of surgical care.

Gregory ST, Schmidt EJ, Zhang SH, Kwong RY, Stevenson WG, Murrow JR, Tse ZTH. Left-ventricular Mechanical Activation and Aortic-arch Orientation Recovered from Magneto-hydrodynamic Voltages Observed in 12-lead ECGs Obtained Inside MRIs: A Feasibility Study. Ann Biomed Eng. 2014;42 (12) :2480-9.Abstract

To explore use of the Magnetohydrodynamic Voltage (VMHD), observed in intra-MRI 12-lead electrocardiograms (ECG), to indicate the timing of the onset of left-ventricular mechanical activation (LVMA) and the orientation of the aortic-arch (AAO). Blood flow through the aortic arch during systole, in the presence of the MRI magnetic field (B 0), generates VMHD. Since the magnitude and direction of VMHD are determined by the timing and directionality of blood flow relative to B 0, we hypothesized that clinically useful measures, LVMA and AAO, could be extracted from temporal and vectorial VMHD characteristics. VMHD signals were extracted from 12-lead ECG traces by comparing traces obtained inside and outside the MRI scanner. VMHD was converted into the Vectorcardiogram frame of reference. LVMA was quantified in 1 subject at 1.5T and 3 subjects at 3T, and the result compared to CINE MRI. AAO was inferred for 4 subjects at 3T and compared to anatomical imaging of the aortic arch orientation in the transverse plane. A < 10% error was observed in LVMA measurements, while a < 3° error was observed in aortic arch orientation measurements. The temporal and vectorial nature of VMHD is useful in estimating these clinically relevant parameters.

Glykys J, Dzhala V, Egawa K, Balena T, Saponjian Y, Kuchibhotla KV, Bacskai BJ, Kahle KT, Zeuthen T, Staley KJ. Local Impermeant Anions Establish the Neuronal Chloride Concentration. Science. 2014;343 (6171) :670-5.Abstract

Neuronal intracellular chloride concentration [Cl(-)](i) is an important determinant of γ-aminobutyric acid type A (GABA(A)) receptor (GABA(A)R)-mediated inhibition and cytoplasmic volume regulation. Equilibrative cation-chloride cotransporters (CCCs) move Cl(-) across the membrane, but accumulating evidence suggests factors other than the bulk concentrations of transported ions determine [Cl(-)](i). Measurement of [Cl(-)](i) in murine brain slice preparations expressing the transgenic fluorophore Clomeleon demonstrated that cytoplasmic impermeant anions ([A](i)) and polyanionic extracellular matrix glycoproteins ([A](o)) constrain the local [Cl(-)]. CCC inhibition had modest effects on [Cl(-)](i) and neuronal volume, but substantial changes were produced by alterations of the balance between [A](i) and [A](o). Therefore, CCCs are important elements of Cl(-) homeostasis, but local impermeant anions determine the homeostatic set point for [Cl(-)], and hence, neuronal volume and the polarity of local GABA(A)R signaling.

Jolesz FA, McDannold NJ. Magnetic Resonance-guided Focused Ultrasound: A New Technology for Clinical Neurosciences. Neurol Clin. 2014;32 (1) :253-69.Abstract

Transcranial MRI-guided focused ultrasound (TcMRgFUS) is an old idea but a new technology that may change the entire clinical field of the neurosciences. TcMRgFUS has no cumulative effect, and it is applicable for repeatable treatments, controlled by real-time dosimetry, and capable of immediate tissue destruction. Most importantly, it has extremely accurate targeting and constant monitoring. It is potentially more precise than proton beam therapy and definitely more cost effective. Neuro-oncology may be the most promising area of future TcMRgFUS applications.

Garlapati RR, Roy A, Joldes GR, Wittek A, Mostayed A, Doyle B, Warfield SK, Kikinis R, Knuckey N, Bunt S, et al. More Accurate Neuronavigation Data Provided by Biomechanical Modeling Instead of Rigid Registration. J Neurosurg. 2014;120 (6) :1477-83.Abstract

It is possible to improve neuronavigation during image-guided surgery by warping the high-quality preoperative brain images so that they correspond with the current intraoperative configuration of the brain. In this paper, the accuracy of registration results obtained using comprehensive biomechanical models is compared with the accuracy of rigid registration, the technology currently available to patients. This comparison allows investigation into whether biomechanical modeling provides good-quality image data for neuronavigation for a larger proportion of patients than rigid registration. Preoperative images for 33 neurosurgery cases were warped onto their respective intraoperative configurations using both the biomechanics-based method and rigid registration. The Hausdorff distance-based evaluation process, which measures the difference between images, was used to quantify the performance of both registration methods. A statistical test for difference in proportions was conducted to evaluate the null hypothesis that the proportion of patients for whom improved neuronavigation can be achieved is the same for rigid and biomechanics-based registration. The null hypothesis was confidently rejected (p < 10(-4)). Even the modified hypothesis that fewer than 25% of patients would benefit from the use of biomechanics-based registration was rejected at a significance level of 5% (p = 0.02). The biomechanics-based method proved particularly effective in cases demonstrating large craniotomy-induced brain deformations. The outcome of this analysis suggests that nonlinear biomechanics-based methods are beneficial to a large proportion of patients and can be considered for use in the operating theater as a possible means of improving neuronavigation and surgical outcomes.