Therapeutic ultrasound guided by MRI is a noninvasive treatment that potentially reduces mortality, lowers medical costs, and widens accessibility of treatments for patients. Recent developments in the design and fabrication of capacitive micromachined ultrasonic transducers (CMUTs) have made them competitive with piezoelectric transducers for use in therapeutic ultrasound applications. In this paper, we present the first designs and prototypes of an eight-element, concentric-ring, CMUT array to treat upper abdominal cancers. This array was simulated and designed to focus 30-50 mm into tissue, and ablate a 2- to 3-cm-diameter tumor within 1 h. Assuming a surface acoustic output pressure of 1 MPa peak-to-peak (8.5 W/cm (2)) at 2.5 MHz, we simulated an array that produced a focal intensity of 680 W/cm (2) when focusing to 35 mm. CMUT cells were then designed to meet these frequency and surface acoustic intensity specifications. These cell designs were fabricated as 2.5 mm x 2.5 mm test transducers and used to verify our models. The test transducers were shown to operate at 2.5 MHz with an output pressure of 1.4 MPa peak-to-peak (16.3 W/cm (2)). With this CMUT cell design, we fabricated a full eight-element array. Due to yield issues, we only developed electronics to focus the four center elements of the array. The beam profile of the measured array deviated from the simulated one because of the crosstalk effects; the beamwidth matched within 10% and sidelobes increased by two times, which caused the measured gain to be 16.6 compared to 27.4.
A software system to provide intuitive navigation for MRI-guided robotic transperineal prostate therapy is presented. In the system, the robot control unit, the MRI scanner, and the open-source navigation software are connected together via Ethernet to exchange commands, coordinates, and images using an open network communication protocol, OpenIGTLink. The system has six states called "workphases" that provide the necessary synchronization of all components during each stage of the clinical workflow, and the user interface guides the operator linearly through these workphases. On top of this framework, the software provides the following features for needle guidance: interactive target planning; 3D image visualization with current needle position; treatment monitoring through real-time MR images of needle trajectories in the prostate. These features are supported by calibration of robot and image coordinates by fiducial-based registration. Performance tests show that the registration error of the system was 2.6mm within the prostate volume. Registered real-time 2D images were displayed 1.97 s after the image location is specified.
Low-frequency transcranial ultrasound (<1 MHz) is being investigated for a number of brain therapies, including stroke, tumor ablation, and localized opening of the blood-brain barrier. However, lower frequencies have been associated with the production of undesired standing waves and cavitation in the brain. Presently, we examine an approach to suppress standing waves during continuous-wave (CW) transcranial application. The investigation uses a small randomization in the frequency content of the signal for suppressing standing waves. The approach is studied in an ex-vivo human skull and a plastic-walled chamber, representing idealized conditions. The approach is compared to single-frequency CW operation as well as to a swept-frequency input. Acoustic field scans demonstrate that the swept-frequency method can suppress standing waves in the plastic chamber and skull by 3.4 and 1.6 times, respectively, compared to single-frequency CW excitation. With random modulation, standing waves were reduced by 5.6 and 2 times, respectively, in the plastic chamber and skull. It is expected that the process may play a critical role in providing a safer application of the ultrasound field in the brain and may have application in other areas where standing waves may be created.
As the number and complexity of partially sampled dynamic imaging methods continue to increase, reliable strategies to evaluate performance may prove most useful. In the present work, an analytical framework to evaluate given reconstruction methods is presented. A perturbation algorithm allows the proposed evaluation scheme to perform robustly without requiring knowledge about the inner workings of the method being evaluated. A main output of the evaluation process consists of a two-dimensional modulation transfer function, an easy-to-interpret visual rendering of a method's ability to capture all combinations of spatial and temporal frequencies. Approaches to evaluate noise properties and artifact content at all spatial and temporal frequencies are also proposed. One fully sampled phantom and three fully sampled cardiac cine datasets were subsampled (R = 4 and 8) and reconstructed with the different methods tested here. A hybrid method, which combines the main advantageous features observed in our assessments, was proposed and tested in a cardiac cine application, with acceleration factors of 3.5 and 6.3 (skip factors of 4 and 8, respectively). This approach combines features from methods such as k-t sensitivity encoding, unaliasing by Fourier encoding the overlaps in the temporal dimension-sensitivity encoding, generalized autocalibrating partially parallel acquisition, sensitivity profiles from an array of coils for encoding and reconstruction in parallel, self, hybrid referencing with unaliasing by Fourier encoding the overlaps in the temporal dimension and generalized autocalibrating partially parallel acquisition, and generalized autocalibrating partially parallel acquisition-enhanced sensitivity maps for sensitivity encoding reconstructions.
We introduce a mathematical framework for computing geometrical properties of white matter fibers directly from diffusion tensor fields. The key idea is to isolate the portion of the gradient of the tensor field corresponding to local variation in tensor orientation, and to project it onto a coordinate frame of tensor eigenvectors. The resulting eigenframe-centered representation then makes it possible to define scalar indices (or measures) that describe the local white matter geometry directly from the diffusion tensor field and its gradient, without requiring prior tractography. We derive new scalar indices of (1) fiber dispersion and (2) fiber curving, and we demonstrate them on synthetic and in vivo data. Finally, we illustrate their applicability to a group study on schizophrenia.
MR imaging-guided interventions are well established in routine patient care in many parts of the world. There are many approaches, depending on magnet design and clinical need, based on MR imaging providing excellent inherent tissue contrast without ionizing radiation risk for patients. MR imaging-guided minimally invasive therapeutic procedures have advantages over conventional surgical procedures. In the genitourinary tract, MR imaging guidance has a role in tumor detection, localization, and staging and can provide accurate image guidance for minimally invasive procedures. The advent of molecular and metabolic imaging and use of higher strength magnets likely will improve diagnostic accuracy and allow targeted therapy to maximize disease control and minimize side effects.
The present study examined the relationship between hand preference degree and direction, functional language lateralization in Broca's and Wernicke's areas, and structural measures of the arcuate fasciculus. Results revealed an effect of degree of hand preference on arcuate fasciculus structure, such that consistently-handed individuals, regardless of the direction of hand preference, demonstrated the most asymmetric arcuate fasciculus, with larger left versus right arcuate, as measured by DTI. Functional language lateralization in Wernicke's area, measured via fMRI, was related to arcuate fasciculus volume in consistent-left-handers only, and only in people who were not right hemisphere lateralized for language; given the small sample size for this finding, future investigation is warranted. Results suggest handedness degree may be an important variable to investigate in the context of neuroanatomical asymmetries.
Often considered benign, meningiomas represent 32% of intracranial tumors with three grades of malignancy defined by the World Health Organization (WHO) histology based classification. Malignant meningiomas are associated with less than 2 years median survival. The inability to predict recurrence and progression of meningiomas induces significant anxiety for patients and limits physicians in implementing prophylactic treatment approaches. This report presents an analytical approach to tissue characterization based on matrix-assisted laser desorption ionization time-of-flight (MALDI TOF) mass spectrometry imaging (MSI) which is introduced in an attempt to develop a reference database for predictive classification of brain tumors. This pilot study was designed to evaluate the potential of such an approach and to begin to address limitations of the current methodology. Five recurrent and progressive meningiomas for which surgical specimens were available from the original and progressed grades were selected and tested against nonprogressive high-grade meningiomas, high-grade gliomas, and nontumor brain specimens. The common profiling approach of data acquisition was compared to imaging and revealed significant benefits in spatially resolved acquisition for improved spectral definition. A preliminary classifier based on the support vector machine showed the ability to distinguish meningioma image spectra from the nontumor brain and from gliomas, a different type of brain tumor, and to enable class imaging of surgical tissue. Although the development of classifiers was shown to be sensitive to data preparation parameters such as recalibration and peak picking criteria, it also suggested the potential for maturing into a predictive algorithm if provided with a larger series of well-defined cases.
We present a shape optimization approach to compute patient-specific models in customized prototyping applications. We design a coupled shape prior to model the transformation between a related pair of surfaces, using a nonparametric joint probability density estimation. The coupled shape prior forces with the help of application-specific data forces and smoothness forces drive a surface deformation towards a desired output surface. We demonstrate the usefulness of the method for generating customized shape models in applications of hearing aid design and pre-operative to intra-operative anatomic surface estimation.
Water diffusion in nerve fibers is strongly influenced by axon architecture. In this study, fractional diffusion anisotropy and transverse and longitudinal diffusion coefficients were measured in excised human cervical spinal cord with MR line-scan diffusion imaging, at 625 microm in-plane resolution and 3 mm slice thickness. A pixel-based comparison of fractional diffusion anisotropy, transverse diffusion coefficient, and longitudinal diffusion coefficient data with axon packing parameters derived from corresponding stained histological sections was performed for four slices. The axon packing parameters, axon density, axon area-fraction, and average axon size for entire specimen cross-sections were calculated by computerized segmentation of optical microscopy data obtained at 0.53 microm resolution. Salient features could be recognized on fractional diffusion anisotropy, transverse diffusion coefficient, axon density, axon area fraction, and average axon size maps. For white matter regions only, the average correlation coefficients for fractional diffusion anisotropy compared to histology-based parameters axon density and axon area fraction were 0.37 and 0.21, respectively. For transverse diffusion coefficient compared to axon density and axon area fraction, they were -0.40 and -0.36, and for longitudinal diffusion coefficient compared to axon density and axon area fraction, -0.14 and -0.30. All average correlation coefficients for average axon size were low. Correlation coefficients for collectively analyzed white and gray matter regions were significantly higher than correlation coefficients derived from analysis of white matter regions only.
PURPOSE: To demonstrate reduced field-of-view (RFOV) single-shot fast spin echo (SS-FSE) imaging based on the use of two-dimensional spatially selective radiofrequency (2DRF) pulses.
MATERIALS AND METHODS: The 2DRF pulses were incorporated into an SS-FSE sequence for RFOV imaging in both phantoms and the human brain on a 1.5 Tesla (T) whole-body MR system with the aim of demonstrating improvements in terms of shorter scan time, reduced blurring, and higher spatial resolution compared with full FOV imaging.
RESULTS: For phantom studies, scan time gains of up to 4.2-fold were achieved as compared to the full FOV imaging. For human studies, the spatial resolution was increased by a factor of 2.5 (from 1.7 mm/pixel to 0.69 mm/pixel) for RFOV imaging within a scan time (0.7 s) similar to full FOV imaging. A 2.2-fold shorter scan time along with a significant reduction of blurring was demonstrated in RFOV images compared with full FOV images for a target spatial resolution of 0.69 mm/pixel.
CONCLUSION: RFOV SS-FSE imaging using a 2DRF pulse shows advantages in scan time, blurring, and specific absorption rate reduction along with true spatial resolution increase compared with full FOV imaging. This approach is promising to benefit fast imaging applications such as image guided therapy.
Conventional spatial-spectral radiofrequency pulses excite the water or the fat spins in a whole slice or slab. While such pulses prove useful in a number of applications, their applicability is severely limited in sequences with short pulse repetition time due to the relatively long duration of the pulses. In the present work, we demonstrate that, by manipulating the parameters of a two-dimensional spartially-selective (2DRF) pulse designed to excite a two-dimensional spatial profile, the chemical-shift sensitivity of the pulse can be exploited to obtain potentially useful spatially varying fat-water excitation patterns.
The quantification of brain asymmetries may provide biomarkers for presurgical localization of language function and can improve our understanding of neural structure-function relationships in health and disease. We propose a new method for studying the asymmetry of the white matter tracts in the entire brain, and we apply it to a preliminary study of normal subjects across the handedness spectrum. Methods for quantifying white matter asymmetry using diffusion MRI tractography have thus far been based on comparing numbers of fibers or volumes of a single fiber tract across hemispheres. We propose a generalization of such methods, where the "number of fibers" laterality measurement is extended to the entire brain using a soft fiber comparison metric. We summarize the distribution of fiber laterality indices over the whole brain in a histogram, and we measure properties of the distribution such as its skewness, median, and inter-quartile range. The whole-brain fiber laterality histogram can be measured in an exploratory fashion without hypothesizing asymmetries only in particular structures. We demonstrate an overall difference in white matter asymmetry in consistent- and inconsistent-handers: the skewness of the fiber laterality histogram is significantly different across handedness groups.
We introduce a fibre tractography framework based on a particle filter which estimates a local geometrical model of the underlying white matter tract, formulated as a 'streamline flow' using generalized helicoids. The method is not dependent on the diffusion model, and is applicable to diffusion tensor (DT) data as well as to high angular resolution reconstructions. The geometrical model allows for a robust inference of local tract geometry, which, in the context of the causal filter estimation, guides tractography through regions with partial volume effects. We validate the method on synthetic data and present results on two types in vivo data: diffusion tensors and a spherical harmonic reconstruction of the fibre orientation distribution function (fODF).
Nyquist ghosts are an inherent artifact in echo planar imaging acquisitions. An approach to robustly eliminate Nyquist ghosts is presented that integrates two previous Nyquist ghost correction techniques: temporal domain encoding (phase labeling for additional coordinate encoding: PLACE and spatial domain encoding (phased array ghost elimination: PAGE). Temporal encoding modulates the echo planar imaging acquisition trajectory from frame to frame, enabling one to interleave data to remove inconsistencies that occur between sampling on positive and negative gradient readouts. With PLACE, one can coherently combine the interleaved data to cancel residual Nyquist ghosts. If the level of ghosting varies significantly from image to image, however, the signal cancellation that occurs with PLACE can adversely affect SNR-sensitive applications such as perfusion imaging with arterial spin labeling. This work proposes integrating PLACE into a PAGE-based reconstruction process to yield significantly better Nyquist ghost correction that is more robust than PLACE or PAGE alone. The robustness of this method is demonstrated in the presence of magnetic field drift with an in-vivo arterial spin labeling perfusion experiment.
MRI offers a tremendous armamentarium of different methods that can be employed in brain tumor characterization. MR diffusion imaging has become a widely accepted method to probe for the presence of fluid pools and molecular tissue water mobility. For most clinical applications of diffusion imaging, it is assumed that the diffusion signal vs diffusion weighting factor b decays monoexponentially. Within this framework, the measurement of a single diffusion coefficient in brain tumors permits an approximate categorization of tumor type and, for some tumors, definitive diagnosis. In most brain tumors, when compared with normal brain tissue, the diffusion coefficient is elevated. The presence of peritumoral edema, which also exhibits an elevated diffusion coefficient, often precludes the delineation of the tumor on the basis of diffusion information alone. Serially obtained diffusion data are useful to document and even predict the cellular response to drug or radiation therapy. Diffusion measurements in tissues over an extended range of b factors have clearly shown that the monoparametric description of the MR diffusion signal decay is incomplete. Very high diffusion weighting on clinical systems requires substantial compromise in spatial resolution. However, after suitable analysis, superior separation of malignant brain tumors, peritumoral edema and normal brain tissue can be achieved. These findings are also discussed in the light of tissue-specific differences in membrane structure and the restrictions exerted by membranes on diffusion. Finally, measurement of the directional dependence of diffusion permits the assessment of white matter integrity and dislocation. Such information, particularly in conjunction with advanced post-processing, is considered to be immensely useful for therapy planning. Diffusion imaging, which permits monoexponential analysis and provides directional diffusion information, is performed routinely in brain tumor patients. More advanced methods require improvement in acquisition speed and spatial resolution to gain clinical acceptance.
Frontal-subcortical cognitive and limbic feedback loops modulate higher cognitive functioning. The final step in these feedback loops is the thalamo-cortical projection through the anterior limb of the internal capsule (AL-IC). Using diffusion tensor imaging (DTI), we evaluated abnormalities in the AL-IC fiber tract in schizophrenia. Participants comprised 16 chronic schizophrenia patients and 19 male, normal controls, who were group matched for handedness, age, and parental socioeconomic status, and underwent DTI on a 1.5 Tesla GE system. We measured the diffusion indices, fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD), and manually segmented, based on FA maps, AL-IC volume, normalized for intracranial contents (ICC). The results showed a significant reduction in the ICC-corrected volume of the AL-IC in schizophrenia, but did not show diffusion measure group differences in the AL-IC in FA, MD, RD or AD. In addition, in the schizophrenia patients, AL-IC FA correlated positively with performance on measures of spatial and verbal declarative/episodic memory, and right AL-IC ICC-corrected volume correlated positively with more perseverative responses on the Wisconsin Card Sort Test (WCST). We found a reduction in AL-IC ICC-corrected volume in schizophrenia, without FA, MD, RD or AD group differences, implicating the presence of a structural abnormality in schizophrenia in this subcortical white matter region which contains important cognitive, and limbic feedback pathways that modulate prefrontal cortical function. Despite not demonstrating a group difference in FA, we found that AL-IC FA was a good predictor of spatial and verbal declarative/episodic memory performance in schizophrenia.
This work provides a model for tubular structures, and devises an algorithm to automatically extract tubular anatomical structures from medical imagery. Our model fits many anatomical structures in medical imagery, in particular, various fiber bundles in the brain (imaged through diffusion-weighted magnetic resonance (DW-MRI)) such as the cingulum bundle, and blood vessel trees in computed tomography angiograms (CTAs). Extraction of the cingulum bundle is of interest because of possible ties to schizophrenia, and extracting blood vessels is helpful in the diagnosis of cardiovascular diseases. The tubular model we propose has advantages over many existing approaches in literature: fewer degrees-of-freedom over a general deformable surface hence energies defined on such tubes are less sensitive to undesirable local minima, and the tube (in 3-D) can be naturally represented by a 4-D curve (a radius function and centerline), which leads to computationally less costly algorithms and has the advantage that the centerline of the tube is obtained without additional effort. Our model also generalizes to tubular trees, and the extraction algorithm that we design automatically detects and evolves branches of the tree. We demonstrate the performance of our algorithm on 20 datasets of DW-MRI data and 32 datasets of CTA, and quantify the results of our algorithm when expert segmentations are available.
Patient-mounted needle guide devices for percutaneous ablation are vulnerable to patient motion. The objective of this study is to develop and evaluate a software system for an MRI-compatible patient-mounted needle guide device that can adaptively compensate for displacement of the device due to patient motion using a novel image-based automatic device-to-image registration technique. We have developed a software system for an MRI-compatible patient-mounted needle guide device for percutaneous ablation. It features fully-automated image-based device-to-image registration to track the device position, and a device controller to adjust the needle trajectory to compensate for the displacement of the device. We performed: (a) a phantom study using a clinical MR scanner to evaluate registration performance; (b) simulations using intraoperative time-series MR data acquired in 20 clinical cases of MRI-guided renal cryoablations to assess its impact on motion compensation; and (c) a pilot clinical study in three patients to test its feasibility during the clinical procedure. FRE, TRE, and success rate of device-to-image registration were [Formula: see text] mm, [Formula: see text] mm, and 98.3% for the phantom images. The simulation study showed that the motion compensation reduced the targeting error for needle placement from 8.2 mm to 5.4 mm (p < 0.0005) in patients under general anesthesia (GA), and from 14.4 mm to 10.0 mm ([Formula: see text]) in patients under monitored anesthesia care (MAC). The pilot study showed that the software registered the device successfully in a clinical setting. Our simulation study demonstrated that the software system could significantly improve targeting accuracy in patients treated under both MAC and GA. Intraprocedural image-based device-to-image registration was feasible.
PURPOSE: To develop and evaluate an approach to estimate the respiratory-induced motion of lesions in the chest and abdomen. MATERIALS AND METHODS: The proposed approach uses the motion of an initial reference needle inserted into a moving organ to estimate the lesion (target) displacement that is caused by respiration. The needles position is measured using an inertial measurement unit (IMU) sensor externally attached to the hub of an initially placed reference needle. Data obtained from the IMU sensor and the target motion are used to train a learning-based approach to estimate the position of the moving target. An experimental platform was designed to mimic respiratory motion of the liver. Liver motion profiles of human subjects provided inputs to the experimental platform. Variables including the insertion angle, target depth, target motion velocity and target proximity to the reference needle were evaluated by measuring the error of the estimated target position and processing time. RESULTS: The mean error of estimation of the target position ranged between 0.86 and 1.29 mm. The processing maximum training and testing time was 5 ms which is suitable for real-time target motion estimation using the needle position sensor. CONCLUSION: The external motion of an initially placed reference needle inserted into a moving organ can be used as a surrogate, measurable and accessible signal to estimate in real-time the position of a moving target caused by respiration; this technique could then be used to guide the placement of subsequently inserted needles directly into the target.
Brain shift during tumor resection compromises the spatial validity of registered preoperative imaging data that is critical to image-guided procedures. One current clinical solution to mitigate the effects is to reimage using intraoperative magnetic resonance (iMR) imaging. Although iMR has demonstrated benefits in accounting for preoperative-to-intraoperative tissue changes, its cost and encumbrance have limited its widespread adoption. While iMR will likely continue to be employed for challenging cases, a cost-effective model-based brain shift compensation strategy is desirable as a complementary technology for standard resections. We performed a retrospective study of [Formula: see text] tumor resection cases, comparing iMR measurements with intraoperative brain shift compensation predicted by our model-based strategy, driven by sparse intraoperative cortical surface data. For quantitative assessment, homologous subsurface targets near the tumors were selected on preoperative MR and iMR images. Once rigidly registered, intraoperative shift measurements were determined and subsequently compared to model-predicted counterparts as estimated by the brain shift correction framework. When considering moderate and high shift ([Formula: see text], [Formula: see text] measurements per case), the alignment error due to brain shift reduced from [Formula: see text] to [Formula: see text], representing [Formula: see text] correction. These first steps toward validation are promising for model-based strategies.
OBJECTIVE: The purpose of this article is to report our intermediate to long-term outcomes with image-guided percutaneous hepatic tumor cryoablation and to evaluate its technical success, technique efficacy, local tumor progression, and adverse event rate. MATERIALS AND METHODS: Between 1998 and 2014, 299 hepatic tumors (243 metastases and 56 primary tumors; mean diameter, 2.5 cm; median diameter, 2.2 cm; range, 0.3-7.8 cm) in 186 patients (95 women; mean age, 60.9 years; range, 29-88 years) underwent cryoablation during 236 procedures using CT (n = 126), MRI (n = 100), or PET/CT (n = 10) guidance. Technical success, technique efficacy at 3 months, local tumor progression (mean follow-up, 2.5 years; range, 2 months to 14.6 years), and adverse event rates were calculated. RESULTS: The technical success rate was 94.6% (279/295). The technique efficacy rate was 89.5% (231/258) and was greater for tumors smaller than 4 cm (93.4%; 213/228) than for larger tumors (60.0%; 18/30) (p < 0.0001). Local tumor progression occurred in 23.3% (60/258) of tumors and was significantly more common after the treatment of tumors 4 cm or larger (63.3%; 19/30) compared with smaller tumors (18.0%; 41/228) (p < 0.0001). Adverse events followed 33.8% (80/236) of procedures and were grade 3-5 in 10.6% (25/236) of cases. Grade 3 or greater adverse events more commonly followed the treatment of larger tumors (19.5%; 8/41) compared with smaller tumors (8.7%; 17/195) (p = 0.04). CONCLUSION: Image-guided percutaneous cryoablation of hepatic tumors is efficacious; however, tumors smaller than 4 cm are more likely to be treated successfully and without an adverse event.
OBJECTIVE: We report nine consecutive percutaneous image-guided cryoablation procedures of head and neck tumors in seven patients (four men and three women; mean age, 68 years; age range, 50-78 years). Ablation of the entire tumor for local control or ablation of a region of tumor for pain relief or preservation of function was achieved in eight of nine procedures. One patient experienced intraprocedural bradycardia, and another developed a neopharyngeal abscess. There were no deaths, permanent neurologic or functional deficits, vascular complications, or adverse cosmetic sequelae due to the procedures. CONCLUSION: Percutaneous image-guided cryoablation offers a potentially less morbid minimally invasive treatment option than salvage head and neck surgery. The complications that we encountered may be avoidable with increased experience. Further work is needed to continue improving the safety and efficacy of cryoablation of head and neck tumors and to continue expanding the use of cryoablation in patients with head and neck tumors that cannot be treated surgically.