Publications

2015
Patil VD, Gupta R, San José Estépar R, Lacson R, Cheung A, Wong JM, Popp JA, Golby AJ, Ogilvy C, Vosburgh KG. Smart Stylet: The Development and Use of a Bedside External Ventricular Drain Image-Guidance System. Stereotact Funct Neurosurg. 2015;93 (1) :50-8.Abstract

BACKGROUND: Placement accuracy of ventriculostomy catheters is reported in a wide and variable range. Development of an efficient image-guidance system may improve physician performance and patient safety. OBJECTIVE: We evaluate the prototype of Smart Stylet, a new electromagnetic image-guidance system for use during bedside ventriculostomy. METHODS: Accuracy of the Smart Stylet system was assessed. System operators were evaluated for their ability to successfully target the ipsilateral frontal horn in a phantom model. RESULTS: Target registration error across 15 intracranial targets ranged from 1.3 to 4.6 mm (mean 3.1 mm). Using Smart Stylet guidance, a test operator successfully passed a ventriculostomy catheter to a shifted ipsilateral frontal horn 20/20 (100%) times from the frontal approach in a skull phantom. Without Smart Stylet guidance, the operator was successful 4/10 (40%) times from the right frontal approach and 6/10 (60%) times from the left frontal approach. In a separate experiment, resident operators were successful 2/4 (50%) times when targeting the shifted ipsilateral frontal horn with Smart Stylet guidance and 0/4 (0%) times without image guidance using a skull phantom. CONCLUSIONS: Smart Stylet may improve the ability to successfully target the ventricles during frontal ventriculostomy.

Arvanitis CD, Clement GT, McDannold N. Transcranial Assessment and Visualization of Acoustic Cavitation: Modeling and Experimental Validation. IEEE Trans Med Imaging. 2015;34 (6) :1270-81.Abstract
The interaction of ultrasonically-controlled microbubble oscillations with tissues and biological media has been shown to induce a wide range of bioeffects that may have significant impact on therapy and diagnosis of brain diseases and disorders. However, the inherently non-linear microbubble oscillations combined with the micrometer and microsecond scales involved in these interactions and the limited methods to assess and visualize them transcranially hinder both their optimal use and translation to the clinics. To overcome these challenges, we present a framework that combines numerical simulations with multimodality imaging to assess and visualize the microbubble oscillations transcranially. In the present work, microbubble oscillations were studied with an integrated US and MR imaging guided clinical FUS system. A high-resolution brain CT scan was also co-registered to the US and MR images and the derived acoustic properties were used as inputs to two- and three-dimensional Finite Difference Time Domain simulations that matched the experimental conditions and geometry. Synthetic point sources by either a Gaussian function or the output of a microbubble dynamics model were numerically excited and propagated through the skull towards a virtual US imaging array. Using passive acoustic mapping (PAM) that was refined to incorporate variable speed of sound, we were able to correct the aberrations introduced by the skull and substantially improve the PAM resolution. The good agreement between the simulations incorporating microbubble emissions and experimentally-determined PAMs suggest that this integrated approach can provide a clinically-relevant framework and more control over this nonlinear and dynamic process.
Penzkofer T, Tuncali K, Fedorov A, Song S-E, Tokuda J, Fennessy FM, Vangel MG, Kibel AS, Mulkern RV, Wells WM, et al. Transperineal In-Bore 3-T MR Imaging-guided Prostate Biopsy: A Prospective Clinical Observational Study. Radiology. 2015;274 (1) :170-80.Abstract

PURPOSE: To determine the detection rate, clinical relevance, Gleason grade, and location of prostate cancer ( PCa prostate cancer ) diagnosed with and the safety of an in-bore transperineal 3-T magnetic resonance (MR) imaging-guided prostate biopsy in a clinically heterogeneous patient population. MATERIALS AND METHODS: This prospective retrospectively analyzed study was HIPAA compliant and institutional review board approved, and informed consent was obtained. Eighty-seven men (mean age, 66.2 years ± 6.9) underwent multiparametric endorectal prostate MR imaging at 3 T and transperineal MR imaging-guided biopsy. Three subgroups of patients with at least one lesion suspicious for cancer were included: men with no prior PCa prostate cancer diagnosis, men with PCa prostate cancer who were undergoing active surveillance, and men with treated PCa prostate cancer and suspected recurrence. Exclusion criteria were prior prostatectomy and/or contraindication to 3-T MR imaging. The transperineal MR imaging-guided biopsy was performed in a 70-cm wide-bore 3-T device. Overall patient biopsy outcomes, cancer detection rates, Gleason grade, and location for each subgroup were evaluated and statistically compared by using χ(2) and one-way analysis of variance followed by Tukey honestly significant difference post hoc comparisons. RESULTS: Ninety biopsy procedures were performed with no serious adverse events, with a mean of 3.7 targets sampled per gland. Cancer was detected in 51 (56.7%) men: 48.1% (25 of 52) with no prior PCa prostate cancer , 61.5% (eight of 13) under active surveillance, and 72.0% (18 of 25) in whom recurrence was suspected. Gleason pattern 4 or higher was diagnosed in 78.1% (25 of 32) in the no prior PCa prostate cancer and active surveillance groups. Gleason scores were not assigned in the suspected recurrence group. MR targets located in the anterior prostate had the highest cancer yield (40 of 64, 62.5%) compared with those for the other parts of the prostate (P < .001). CONCLUSION: In-bore 3-T transperineal MR imaging-guided biopsy, with a mean of 3.7 targets per gland, allowed detection of many clinically relevant cancers, many of which were located anteriorly.

2014
Kapur T, Tempany CM, Jolesz FA. Proceedings of the 7th Image Guided Therapy Workshop. Image Guided Therapy Workshop. 2014;7 :1-60. 2014 IGT Workshop Proceedings
Phillips JG, Aizer AA, Chen M-H, Zhang D, Hirsch MS, Richie JP, Tempany CM, Williams S, Hegde JV, Loffredo MJ, et al. The Effect of Differing Gleason Scores at Biopsy on the Odds of Upgrading and the Risk of Death from Prostate Cancer. Clin Genitourin Cancer. 2014;12 (5) :e181-7.Abstract

INTRODUCTION/BACKGROUND: The GS is an established prostate cancer prognostic factor. Whether the presence of differing GSs at biopsy (eg, 4+3 and 3+3), which we term ComboGS, improves the prognosis that would be predicted based on the highest GS (eg, 4+3) because of decreased upgrading is unknown. Therefore, we evaluated the odds of upgrading at time of radical prostatectomy (RP) and the risk of PCSM when ComboGS was present versus absent. PATIENTS AND METHODS: Logistic and competing risks regression were performed to assess the effect that ComboGS had on the odds of upgrading at time of RP in the index (n = 134) and validation cohorts (n = 356) and the risk of PCSM after definitive therapy in a long-term cohort (n = 666), adjusting for known predictors of these end points. We calculated and compared the area under the curve using a receiver operating characteristic analysis when ComboGS was included versus excluded from the upgrading models. RESULTS: ComboGS was associated with decreased odds of upgrading (index: adjusted odds ratio [AOR], 0.14; 95% confidence interval [CI], 0.04-0.50; P = .003; validation: AOR, 0.24; 95% CI, 0.11-0.51; P < .001) and added significantly to the predictive value of upgrading for the in-sample index (P = .02), validation (P = .003), and out-of-sample prediction models (P = .002). ComboGS was also associated with a decreased risk of PCSM (adjusted hazard ratio, 0.40; 95% CI, 0.19-0.85; P = .02). CONCLUSION: Differing biopsy GSs are associated with a lower odds of upgrading and risk of PCSM. If validated, future randomized noninferiority studies evaluating deescalated treatment approaches in men with ComboGS could be considered.

Mehrtash A, Damato A, Pernelle G, Barber L, Farhat N, Viswanathan A, Cormack R, Kapur T. EM-Navigated Catheter Placement for Gynecologic Brachytherapy: An Accuracy Study. Proc SPIE Int Soc Opt Eng. 2014;9036 :90361F.Abstract
Gynecologic malignancies, including cervical, endometrial, ovarian, vaginal and vulvar cancers, cause significant mortality in women worldwide. The standard care for many primary and recurrent gynecologic cancers consists of chemoradiation followed by brachytherapy. In high dose rate (HDR) brachytherapy, intracavitary applicators and/or interstitial needles are placed directly inside the cancerous tissue so as to provide catheters to deliver high doses of radiation. Although technology for the navigation of catheters and needles is well developed for procedures such as prostate biopsy, brain biopsy, and cardiac ablation, it is notably lacking for gynecologic HDR brachytherapy. Using a benchtop study that closely mimics the clinical interstitial gynecologic brachytherapy procedure, we developed a method for evaluating the accuracy of image-guided catheter placement. Future bedside translation of this technology offers the potential benefit of maximizing tumor coverage during catheter placement while avoiding damage to the adjacent organs, for example bladder, rectum and bowel. In the study, two independent experiments were performed on a phantom model to evaluate the targeting accuracy of an electromagnetic (EM) tracking system. The procedure was carried out using a laptop computer (2.1GHz Intel Core i7 computer, 8GB RAM, Windows 7 64-bit), an EM Aurora tracking system with a 1.3mm diameter 6 DOF sensor, and 6F (2 mm) brachytherapy catheters inserted through a Syed-Neblett applicator. The 3D Slicer and PLUS open source software were used to develop the system. The mean of the targeting error was less than 2.9mm, which is comparable to the targeting errors in commercial clinical navigation systems.
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.

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