883 resultados para Radiographic Image Interpretation, Computer-Assisted


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We investigated the neural basis for spontaneous chemo-stimulated increases in ventilation in awake, healthy humans. Blood oxygen level dependent (BOLD) functional MRI was performed in nine healthy subjects using T2 weighted echo planar imaging. Brain volumes (52 transverse slices, cortex to high spinal cord) were acquired every 3.9 s. The 30 min paradigm consisted of six, 5-min cycles, each cycle comprising 45 s of hypoxic-isocapnia, 45 s of isooxic-hypercapnia and 45 s of hypoxic-hypercapnia, with 55 s of non-stimulatory hyperoxic-isocapnia (control) separating each stimulus period. Ventilation was significantly (p<0.001) increased during hypoxic-isocapnia, isooxic-hypercapnia and hypoxic-hypercapnia (17.0, 13.8, 24.9 L/min respectively) vs. control (8.4 L/min) and was associated with significant (p<0.05, corrected for multiple comparisons) signal increases within a bilateral network that included the basal ganglia, thalamus, red nucleus, cerebellum, parietal cortex, cingulate and superior mid pons. The neuroanatomical structures identified provide evidence for the spontaneous control of breathing to be mediated by higher brain centres, as well as respiratory nuclei in the brainstem.

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At least 10% of glioblastoma relapses occur at distant and even contralateral locations. This disseminated growth limits surgical intervention and contributes to neurological morbidity. Preclinical data pointed toward a role for temozolomide (TMZ) in reducing radiotherapy-induced glioma cell invasiveness. Our objective was to develop and validate a new analysis tool of MRI data to examine the clinical recurrence pattern of glioblastomas. MRIcro software was used to map the location and extent of initial preoperative and recurrent tumors on MRI of 63 patients in the European Organisation for Research and Treatment of Cancer (EORTC) 26981/22981/National Cancer Institute of Canada (NCIC) CE.3 study into the same stereotaxic space. This allowed us to examine changes of site and distance between the initial and the recurrent tumor on the group level. Thirty of the 63 patients were treated using radiotherapy, while the other patients completed a radiotherapy-plus-TMZ treatment. Baseline characteristics (median age, KPS) and outcome data (progression-free survival, overall survival) of the patients included in this analysis resemble those of the general study cohort. The patient groups did not differ in the promoter methylation status of methyl guanine methyltransferase (MGMT). Overall frequency of distant recurrences was 20%. Analysis of recurrence patterns revealed no difference between the groups in the size of the recurrent tumor or in the differential effect on the distance of the recurrences from the preoperative tumor location. The data show the feasibility of groupwise recurrence pattern analysis. An effect of TMZ treatment on the recurrence pattern in the EORTC 26981/22981/NCIC CE.3 study could not be demonstrated.

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Diffusion-weighted spin-echo imaging of the spine has been successfully implemented for differentiation of benign fracture edema and tumor infiltration of the vertebral body. Nevertheless, this technique still suffers from insufficient image quality in numerous patients due to motion artifacts. The aim of this study was to investigate the impact of variable respiratory motion artifact suppression techniques on image quality in diffusion-weighted spin-echo imaging of the spine. In addition to phase-encoding reordering, a newly implemented right hemi-diaphragmaitc navigator for respiratory gating was used. Subjective and objective image quality parameters were compared. Respiratory motion artifact suppression has a major impact on image quality in diffusion-weighted imaging of the spine. Phase-encoding reordering does not enhance image quality while right hemi-diaphragmatic respiratory navigator gating significantly improves image quality at the cost of data acquisition time. Navigator gating should be used if standard spin-echo diffusion-weighted imaging demonstrates insufficient image quality.

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We present a method for segmenting white matter tracts from high angular resolution diffusion MR. images by representing the data in a 5 dimensional space of position and orientation. Whereas crossing fiber tracts cannot be separated in 3D position space, they clearly disentangle in 5D position-orientation space. The segmentation is done using a 5D level set method applied to hyper-surfaces evolving in 5D position-orientation space. In this paper we present a methodology for constructing the position-orientation space. We then show how to implement the standard level set method in such a non-Euclidean high dimensional space. The level set theory is basically defined for N-dimensions but there are several practical implementation details to consider, such as mean curvature. Finally, we will show results from a synthetic model and a few preliminary results on real data of a human brain acquired by high angular resolution diffusion MRI.

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INTRODUCTION Functional imaging studies of addiction following protracted abstinence have not been systematically conducted to look at the associations between severity of use of different drugs and brain dysfunction. Findings from such studies may be relevant to implement specific interventions for treatment. The aim of this study was to examine the association between resting-state regional brain metabolism (measured with 18F-fluorodeoxyglucose Positron Emission Tomography (FDG-PET) and the severity of use of cocaine, heroin, alcohol, MDMA and cannabis in a sample of polysubstance users with prolonged abstinence from all drugs used. METHODS Our sample consisted of 49 polysubstance users enrolled in residential treatment. We conducted correlation analyses between estimates of use of cocaine, heroin, alcohol, MDMA and cannabis and brain metabolism (BM) (using Statistical Parametric Mapping voxel-based (VB) whole-brain analyses). In all correlation analyses conducted for each of the drugs we controlled for the co-abuse of the other drugs used. RESULTS The analysis showed significant negative correlations between severity of heroin, alcohol, MDMA and cannabis use and BM in the dorsolateral prefrontal cortex (DLPFC) and temporal cortex. Alcohol use was further associated with lower metabolism in frontal premotor cortex and putamen, and stimulants use with parietal cortex. CONCLUSIONS Duration of use of different drugs negatively correlated with overlapping regions in the DLPFC, whereas severity of cocaine, heroin and alcohol use selectively impact parietal, temporal, and frontal-premotor/basal ganglia regions respectively. The knowledge of these associations could be useful in the clinical practice since different brain alterations have been associated with different patterns of execution that may affect the rehabilitation of these patients.

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PURPOSE: To assess the diagnostic performance of respiratory self-navigation for whole-heart coronary magnetic resonance (MR) angiography in a patient cohort referred for diagnostic cardiac MR imaging. MATERIALS AND METHODS: Written informed consent was obtained from all participants for this institutional review board-approved study. Self-navigated coronary MR angiography was performed after administration of a contrast agent in 78 patients (mean age, 48.5 years ± 20.7 [standard deviation]; 53 male patients) referred for cardiac MR imaging because of coronary artery disease (n = 40), cardiomyopathy (n = 14), congenital anomaly (n = 17), or "other" (n = 7). Examination duration was recorded, and the image quality for each coronary segment was assessed with consensus reading. Vessel sharpness, length, and diameter were measured. Quantitative values in proximal, middle, and distal segments were compared by using analysis of variance and t tests. A double-blinded comparison with the results of x-ray angiography was performed when such results were available. RESULTS: When patients with different indications for cardiac MR imaging were examined with self-navigated postcontrast coronary MR angiography, whole-heart data sets with 1.15-mm isotropic spatial resolution were acquired in an average of 7.38 minutes ± 1.85. The main and proximal coronary segments could be visualized in 92.3% of cases, while the middle and distal segments could be visualized in 84.0% and 55.8% of cases, respectively. Subjective scores and vessel sharpness were significantly higher in the proximal segments than in the middle and distal segments (P < .05). Anomalies of the coronary arteries could be confirmed or excluded in all cases. Per-vessel sensitivity and specificity for stenosis detection were 64.7% and 85.0%, respectively, in the 31 patients for whom reference standard x-ray coronary angiography results were available. CONCLUSION: The self-navigated coronary MR angiography sequence shows promise for coronary imaging. However, technical improvements are needed to improve image quality, especially in the more distal coronary segments.

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BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

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BACKGROUND To compare outcomes for patients with recurrent or persistent papillary thyroid cancer (PTC) who had metastatic tumors that were fluorodeoxyglucose-positron emission tomography (FDG-PET) positive or negative, and to determine whether the FDG-PET scan findings changed the outcome of medical and surgical management. METHODS From a prospective thyroid cancer database, we retrospectively identified patients with recurrent or persistent PTC and reviewed data on demographics, initial stage, location and extent of persistent or recurrent disease, clinical management, disease-free survival and outcome. We further identified subsets of patients who had an FDG-PET scan or an FDG-PET/CT scan and whole-body radioactive iodine scans and categorized them by whether they had one or more FDG-PET-avid (PET-positive) lesions or PET-negative lesions. The medical and surgical treatments and outcome of these patients were compared. RESULTS Between 1984 and 2008, 41 of 141 patients who had recurrent or persistent PTC underwent FDG-PET (n = 11) or FDG-PET/CT scans (n = 30); 22 patients (54%) had one or more PET-positive lesion(s), 17 (41%) had PET-negative lesions, and two had indeterminate lesions. Most PET-positive lesions were located in the neck (55%). Patients who had a PET-positive lesion had a significantly higher TNM stage (P = 0.01), higher age (P = 0.03), and higher thyroglobulin (P = 0.024). Only patients who had PET-positive lesions died (5/22 vs. 0/17 for PET-negative lesions; P = 0.04). In two of the seven patients who underwent surgical resection of their PET-positive lesions, loco-regional control was obtained without evidence of residual disease. CONCLUSION Patients with recurrent or persistent PTC and FDG-PET-positive lesions have a worse prognosis. In some patients loco-regional control can be obtained without evidence of residual disease by reoperation if the lesion is localized in the neck or mediastinum.

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Methods are presented to map complex fiber architectures in tissues by imaging the 3D spectra of tissue water diffusion with MR. First, theoretical considerations show why and under what conditions diffusion contrast is positive. Using this result, spin displacement spectra that are conventionally phase-encoded can be accurately reconstructed by a Fourier transform of the measured signal's modulus. Second, studies of in vitro and in vivo samples demonstrate correspondence between the orientational maxima of the diffusion spectrum and those of the fiber orientation density at each location. In specimens with complex muscular tissue, such as the tongue, diffusion spectrum images show characteristic local heterogeneities of fiber architectures, including angular dispersion and intersection. Cerebral diffusion spectra acquired in normal human subjects resolve known white matter tracts and tract intersections. Finally, the relation between the presented model-free imaging technique and other available diffusion MRI schemes is discussed.

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During the last decade, we have been developing new therapeutic strategies for the treatment of renal cancer, based on knowledge derived from molecular biology. We report a case of long-term renal metastatic cancer progression despite therapy with sunitinib and interleukin, which are the most active drugs in renal cancer. Disease stabilization for 58 weeks was achieved upon sequential use of temsirolimus, following the occurrence of disease progression during angiogenic therapy. The patient demonstrated excellent tolerance without marked symptoms for 10 months. Hypothyroidism and mumps-related adverse events were present. The survival time from diagnosis to lung metastasis was 8 years. Thus, this case demonstrates promising therapeutic effects of the sequential use of tyrosine kinase inhibitors (TKIs) and mammalian target of rapamycin (mTOR) inhibitors during different stages of the disease.

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PURPOSE: To investigate magnetization transfer (MT) effects as a new source of contrast for imaging and tracking of peripheral foot nerves. MATERIALS AND METHODS: Two sets of 3D spoiled gradient-echo images acquired with and without a saturation pulse were used to generate MT ratio (MTR) maps of 260 μm in-plane resolution for eight volunteers at 3T. Scan parameters were adjusted to minimize signal loss due to T2 dephasing, and a dedicated coil was used to improve the inherently low signal-to-noise ratio of small voxels. Resulting MTR values in foot nerves were compared with those in surrounding muscle tissue. RESULTS: Average MTR values for muscle (45.5 ± 1.4%) and nerve (21.4 ± 3.1%) were significantly different (P < 0.0001). In general, the difference in MTR values was sufficiently large to allow for intensity-based segmentation and tracking of foot nerves in individual subjects. This procedure was termed MT-based 3D visualization. CONCLUSION: The MTR serves as a new source of contrast for imaging of peripheral foot nerves and provides a means for high spatial resolution tracking of these structures. The proposed methodology is directly applicable on standard clinical MR scanners and could be applied to systemic pathologies, such as diabetes.

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To enhance the clinical value of coronary magnetic resonance angiography (MRA), high-relaxivity contrast agents have recently been used at 3T. Here we examine a uniform bilateral shadowing artifact observed along the coronary arteries in MRA images collected using such a contrast agent. Simulations were performed to characterize this artifact, including its origin, to determine how best to mitigate this effect, and to optimize a data acquisition/injection scheme. An intraluminal contrast agent concentration model was used to simulate various acquisition strategies with two profile orders for a slow-infusion of a high-relaxivity contrast agent. Filtering effects from temporally variable weighting in k-space are prominent when a centric, radial (CR) profile order is applied during contrast infusion, resulting in decreased signal enhancement and underestimation of vessel width, while both pre- and postinfusion steady-state acquisitions result in overestimation of the vessel width. Acquisition during the brief postinfusion steady-state produces the greatest signal enhancement and minimizes k-space filtering artifacts.

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The use of self-calibrating techniques in parallel magnetic resonance imaging eliminates the need for coil sensitivity calibration scans and avoids potential mismatches between calibration scans and subsequent accelerated acquisitions (e.g., as a result of patient motion). Most examples of self-calibrating Cartesian parallel imaging techniques have required the use of modified k-space trajectories that are densely sampled at the center and more sparsely sampled in the periphery. However, spiral and radial trajectories offer inherent self-calibrating characteristics because of their densely sampled center. At no additional cost in acquisition time and with no modification in scanning protocols, in vivo coil sensitivity maps may be extracted from the densely sampled central region of k-space. This work demonstrates the feasibility of self-calibrated spiral and radial parallel imaging using a previously described iterative non-Cartesian sensitivity encoding algorithm.

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To be diagnostically useful, structural MRI must reliably distinguish Alzheimer's disease (AD) from normal aging in individual scans. Recent advances in statistical learning theory have led to the application of support vector machines to MRI for detection of a variety of disease states. The aims of this study were to assess how successfully support vector machines assigned individual diagnoses and to determine whether data-sets combined from multiple scanners and different centres could be used to obtain effective classification of scans. We used linear support vector machines to classify the grey matter segment of T1-weighted MR scans from pathologically proven AD patients and cognitively normal elderly individuals obtained from two centres with different scanning equipment. Because the clinical diagnosis of mild AD is difficult we also tested the ability of support vector machines to differentiate control scans from patients without post-mortem confirmation. Finally we sought to use these methods to differentiate scans between patients suffering from AD from those with frontotemporal lobar degeneration. Up to 96% of pathologically verified AD patients were correctly classified using whole brain images. Data from different centres were successfully combined achieving comparable results from the separate analyses. Importantly, data from one centre could be used to train a support vector machine to accurately differentiate AD and normal ageing scans obtained from another centre with different subjects and different scanner equipment. Patients with mild, clinically probable AD and age/sex matched controls were correctly separated in 89% of cases which is compatible with published diagnosis rates in the best clinical centres. This method correctly assigned 89% of patients with post-mortem confirmed diagnosis of either AD or frontotemporal lobar degeneration to their respective group. Our study leads to three conclusions: Firstly, support vector machines successfully separate patients with AD from healthy aging subjects. Secondly, they perform well in the differential diagnosis of two different forms of dementia. Thirdly, the method is robust and can be generalized across different centres. This suggests an important role for computer based diagnostic image analysis for clinical practice.