Showing papers in "Magnetic Resonance Imaging in 2010"
TL;DR: It is demonstrated that the strength of the functional connection between the medial frontal cortex and the dorsolateral prefrontal cortex is related to cognitive function and that this relationship is not an artifact of global regression.
Abstract: Functional brain imaging studies have identified a set of brain areas typically activated during cognitive tasks (task-positive brain areas) and another set of brain areas typically deactivated during cognitive tasks (task-negative brain areas). Negative correlations, or anticorrelations, between task-positive and task-negative brain areas have been reported at rest. Furthermore, the strength of these anticorrelations appears to be related to cognitive function. However, studies examining anticorrelations have typically employed global regression or similar analysis steps that force anticorrelated relationships to exist between brain areas. Therefore the validity of these findings has been questioned. Here we examine anticorrelations between a task-negative region in the medial frontal gyrus/anterior cingulate cortex and dorsolateral prefrontal cortex, a classic task-positive area, using an analysis that does not include global regression. Instead, we control for whole-brain correlations in the group-level analysis. Using this approach, we demonstrate that the strength of the functional connection between the medial frontal cortex and the dorsolateral prefrontal cortex is related to cognitive function and that this relationship is not an artifact of global regression.
TL;DR: It is demonstrated that functional connectivity observed in the rat depends strongly on the type of anesthesia used and suggested that the mechanisms contributing to functional connectivity involve a complicated relationship between changes in neural activity, neurovascular coupling and vascular reactivity.
Abstract: Functional connectivity measures based upon low-frequency blood-oxygenation-level-dependent functional magnetic resonance imaging (BOLD fMRI) signal fluctuations have become a widely used tool for investigating spontaneous brain activity in humans. Still unknown, however, is the precise relationship between neural activity, the hemodynamic response and fluctuations in the MRI signal. Recent work from several groups had shown that correlated low-frequency fluctuations in the BOLD signal can be detected in the anesthetized rat — a first step toward elucidating this relationship. Building on this preliminary work, through this study, we demonstrate that functional connectivity observed in the rat depends strongly on the type of anesthesia used. Power spectra of spontaneous fluctuations and the cross-correlation-based connectivity maps from rats anesthetized with α-chloralose, medetomidine or isoflurane are presented using a high-temporal-resolution imaging sequence that ensures minimal contamination from physiological noise. The results show less localized correlation in rats anesthetized with isoflurane as compared with rats anesthetized with α-chloralose or medetomidine. These experiments highlight the utility of using different types of anesthesia to explore the fundamental physiological relationships of the BOLD signal and suggest that the mechanisms contributing to functional connectivity involve a complicated relationship between changes in neural activity, neurovascular coupling and vascular reactivity.
TL;DR: The left superior longitudinal fasciculus was found connecting the posterior language areas to the precentral gyrus and only marginally in some cases to the canonical Broca's area, consistent with reports describing lack of correlation between lateralization of the SLF and language areas.
Abstract: Purpose The left superior longitudinal fasciculus (SLF) has been felt to link receptive with expressive language areas. The latter is located in the pars opercularis (Broca's area) of the left inferior frontal gyrus. We report the findings with tractography of the SLF in a group of normal volunteers. Methods and materials The data and subsidiary results of 12 normal right-handed volunteers who participated in an institutional review board-approved diffusion tensor imaging study were evaluated. The SLF fibers were obtained bilaterally placing a region of interest at the triangular-shaped region lateral to each of the corticospinal tracts, in a coronal plane along the rostral aspect of the corpus callosum. A sagittal fractional anisotropy image was used to determine the rostral endpoint of the SLF fibers in the white matter pertaining to specific gyri or pars of the frontal lobe. The SLF projection to Broca's area was ranked qualitatively as none, minimal, most or all. Findings are presented in descriptive statistics. Results The SLF projection to Broca's areas was absent in seven subjects (58.3%) and minimal in five (41.6%). SLF's rostral end points were found uniquely or mainly in the precentral gyrus in 100% of cases. Conclusion The SLF was found connecting the posterior language areas to the precentral gyrus and only marginally in some cases to the canonical Broca's area. This finding is consistent with reports describing lack of correlation between lateralization of the SLF and language areas. The understanding of language circuitry is beginning to emerge with the use of tractography.
TL;DR: A wavelet-based bilateral filtering scheme for noise reduction in magnetic resonance images that has been adapted specifically to Rician noise and the visual and the diagnostic quality of the denoised image is well preserved.
Abstract: Feature-preserved denoising is of great interest in medical image processing. This article presents a wavelet-based bilateral filtering scheme for noise reduction in magnetic resonance images. Undecimated wavelet transform is employed to provide effective representation of the noisy coefficients. Bilateral filtering of the approximate coefficients improves the denoising efficiency and effectively preserves the edge features. Denoising is done in the square magnitude domain, where the noise tends to be signal independent and is additive. The proposed method has been adapted specifically to Rician noise. The visual and the diagnostic quality of the denoised image is well preserved. The quantitative and the qualitative measures used as the quality metrics demonstrate the ability of the proposed method for noise suppression.
TL;DR: The results indicate that the origin of the BOLD signal variability between subjects was predominantly vascular during the motor task while being principally a consequence of neural variability during the cognitive task, and in addition to gray matter differences, the type of task performed can have different vascular variability weighting that can influence age-related differences in brain functional response.
Abstract: Neural, vascular and structural variables contributing to the blood oxygen level-dependent (BOLD) signal response variability were investigated in younger and older humans. Twelve younger healthy human subjects (six male and six female; mean age: 24 years; range: 19–27 years) and 12 older healthy subjects (five male and seven female; mean age: 58 years; range: 55–71 years) with no history of head trauma and neurological disease were scanned. Functional magnetic resonance imaging measurements using the BOLD contrast were made when participants performed a motor, cognitive or a breath hold (BH) task. Activation volume and the BOLD response amplitude were estimated for the younger and older at both group and subject levels. Mean activation volume was reduced by 45%, 40% and 38% in the elderly group during the motor, cognitive and BH tasks, respectively, compared to the younger. Reduction in activation volume was substantially higher compared to the reduction in the gray matter volume of 14% in the older compared to the younger. A significantly larger variability in the intersubject BOLD signal change occurred during the motor task, compared to the cognitive task. BH-induced BOLD signal change between subjects was significantly less-variable in the motor task-activated areas in the younger compared to older whereas such a difference between age groups was not observed during the cognitive task. Hemodynamic scaling using the BH signal substantially reduced the BOLD signal variability during the motor task compared to the cognitive task. The results indicate that the origin of the BOLD signal variability between subjects was predominantly vascular during the motor task while being principally a consequence of neural variability during the cognitive task. Thus, in addition to gray matter differences, the type of task performed can have different vascular variability weighting that can influence age-related differences in brain functional response.
TL;DR: MRI may provide a volumetric measure more representative of breast composition than mammography, particularly in groups of women with dense breasts, and could potentially be quantified and used for a better assessment of breast cancer risk in these populations.
Abstract: A quantitative measure of three-dimensional breast density derived from noncontrast magnetic resonance imaging (MRI) was investigated in 35 women at high-risk for breast cancer. A semiautomatic segmentation tool was used to quantify the total volume of the breast and to separate volumes of fibroglandular and adipose tissue in noncontrast MRI data. The MRI density measure was defined as the ratio of breast fibroglandular volume over total volume of the breast. The overall correlation between MRI and mammographic density measures was R2=.67. However the MRI/mammography density correlation was higher in patients with lower breast density (R2=.73) than in patients with higher breast density (R2=.26). Women with mammographic density higher than 25% exhibited very different magnetic resonance density measures spread over a broad range of values. These results suggest that MRI may provide a volumetric measure more representative of breast composition than mammography, particularly in groups of women with dense breasts. Magnetic resonance imaging density could potentially be quantified and used for a better assessment of breast cancer risk in these populations.
TL;DR: Results indicated that GSH was significantly higher in GM relative to WM in normal subjects, and this preliminary investigation demonstrates the potential of this marker to probe oxidative state in MS.
Abstract: Detection of glutathione (GSH) is technically challenging at clinical field strengths of 1.5 or 3 T due to its low concentration in the human brain coupled with the fact that conventional single-echo acquisitions, typically used for magnetic resonance (MR) spectroscopy acquisitions, cannot be used to resolve GSH given its overlap with other resonances. In this study, an MR spectral editing scheme was used to generate an unobstructed detection of GSH at 7 T. This technique was used to obtain normative white (WM) and gray matter (GM) GSH concentrations over a two-dimensional region. Results indicated that GSH was significantly higher (P<.001) in GM relative to WM in normal subjects. This finding is consistent with previous radionuclide experiments and histochemical staining and validates this 7 T MR spectroscopy technique. To our knowledge, this is the first study to report normative differences in WM and GM glutathione concentrations in the human brain. Glutathione is a biomarker for oxidative status and this non-invasive in vivo measurement of GSH was used to explore its sensitivity to oxidative state in multiple sclerosis (MS) patients. There was a significant reduction (P<.001) of GSH between the GM in MS patients and normal controls. No statistically significant GSH differences were found between the WM in controls and MS patients. Reduced GSH was also observed in a MS WM lesion. This preliminary investigation demonstrates the potential of this marker to probe oxidative state in MS.
TL;DR: The proposed stochastic resonance (SR)-based transform in Fourier space for the enhancement of magnetic resonance images of brain lesions can restore the original image from noisy image and optimally enhance the edges or boundaries of the tissues, and enables improved diagnosis over conventional methods.
Abstract: Objective In general, low-field MRI scanners such as the 0.5- and 1-T ones produce images that are poor in quality. The motivation of this study was to lessen the noise and enhance the signal such that the image quality is improved. Here, we propose a new approach using stochastic resonance (SR)-based transform in Fourier space for the enhancement of magnetic resonance images of brain lesions, by utilizing an optimized level of Gaussian fluctuation that maximizes signal-to-noise ratio (SNR). Materials and Methods We acquired the T1-weighted MR image of the brain in DICOM format. We processed the original MR image using the proposed SR procedure. We then tested our approach on about 60 patients of different age groups with different lesions, such as arteriovenous malformation, benign lesion and malignant tumor, and illustrated the image enhancement by using just-noticeable difference visually as well as by utilizing the relative enhancement factor quantitatively. Results Our method can restore the original image from noisy image and optimally enhance the edges or boundaries of the tissues, clarify indistinct structural brain lesions without producing ringing artifacts, as well as delineate the edematous area, active tumor zone, lesion heterogeneity or morphology, and vascular abnormality. The proposed technique improves the enhancement factor better than the conventional techniques like the Wiener- and wavelet-based procedures. Conclusions The proposed method can readily enhance the image fusing a unique constructive interaction of noise and signal, and enables improved diagnosis over conventional methods. The approach well illustrates the novel potential of using a small amount of Gaussian noise to improve the image quality.
TL;DR: In this article, the relative CBF (rCBF) was proposed to detect inter-subject variations in global CBF, which are associated with non-neural factors and may contribute to the noise in the across-group comparison.
Abstract: Arterial-spin-labeling (ASL) magnetic resonance imaging (MRI) provides a noninvasive tool to measure cerebral blood flow (CBF) and is increasingly used as a surrogate for baseline neural activity. However, the power of ASL MRI in detecting CBF differences between patient and control subjects is hampered by inter-subject variations in global CBF, which are associated with non-neural factors and may contribute to the noise in the across-group comparison. Here, we investigated the sensitivity of this technique and proposed a normalization strategy to better detect such a difference. A "model" situation was employed in which two visual stimuli (i.e. cross fixation and flashing checkerboard) were presented to two groups of subjects to mimic "control" and "patient" groups (N=7 for each group), respectively. It was found that absolute CBF (aCBF) in the occipital lobe in the checkerboard group was 26.0% greater compared to the fixation group, but the level of significance was modest (P=.03). In contrast, when normalizing the CBF with whole-brain CBF or CBF in a reference region [termed relative CBF (rCBF)], the statistical significance was improved considerably (P<.003). For voxel-based analysis, the rCBF indices correctly detected CBF differences in the occipital lobe in the across-group comparison, while aCBF failed to detect any significant cluster using the same statistical threshold. We also performed Monte Carlo simulation to confirm the experimental findings and found that the power improvement was most pronounced when signal-to-noise-ratio is moderate and the underlying CBF difference was small. The simulation also showed that, with the proposed normalization, a detection power of 80% can be achieved using a sample size of about 20. In summary, rCBF is a more sensitive index to detect small differences in CBF, rather than the much-sought-after aCBF, since it reduces data noise caused by inter-subject variations in global CBF.
TL;DR: The DTI normalization methodology presented here enables automatic delineation of ROIs within the heads of individual subjects (or in a group).
Abstract: Purpose: To develop and apply diffusion tensor imaging (DTI)-based normalization methodology for the detection and quantification of sites of traumatic brain injury (TBI) and the impact of injury along specific brain pathways in (a) individual TBI subjects and (b) a TBI group. Materials and Methods: Normalized DTI tractography was conducted in the native space of 12 TBI and 10 age-matched control subjects using the same number of seeds in each subject, distributed at anatomically equivalent locations. Whole-brain tracts from the control group were mapped onto the head of each TBI subject. Differences in the fractional anisotropy (FA) maps between each TBI subject and the control group were computed in a common space using a t test, transformed back to the individual TBI subject's head space, and thresholded to form regions of interest (ROIs) that were used to sort tracts from the control group and the individual TBI subject. Tract counts for a given ROI in each TBI subject were compared to group mean for the same ROI to quantify the impact of injury along affected pathways. The same procedure was used to compare the TBI group to the control group in a common space. Results: Sites of injury within individual TBI subjects and affected pathways included hippocampal/fornix, inferior fronto-occipital, inferior longitudinal fasciculus, corpus callosum (genu and splenium), cortico-spinal tracts and the uncinate fasciculus. Most of these regions were also detected in the group study. Conclusions: The DTI normalization methodology presented here enables automatic delineation of ROIs within the heads of individual subjects (or in a group). These ROIs not only localize and quantify the extent of injury, but also quantify the impact of injury on affected pathways in an individual or in a group of TBI subjects.
TL;DR: It is argued that state-of-the-art methods from pattern recognition and machine learning, such as classifier ensembles, offer more accurate classification.
Abstract: Functional magnetic resonance imaging (fMRI) is becoming a forefront brain–computer interface tool. To decipher brain patterns, fast, accurate and reliable classifier methods are needed. The support vector machine (SVM) classifier has been traditionally used. Here we argue that state-of-the-art methods from pattern recognition and machine learning, such as classifier ensembles, offer more accurate classification. This study compares 18 classification methods on a publicly available real data set due to Haxby et al. [ Science 293 (2001) 2425–2430]. The data comes from a single-subject experiment, organized in 10 runs where eight classes of stimuli were presented in each run. The comparisons were carried out on voxel subsets of different sizes, selected through seven popular voxel selection methods. We found that, while SVM was robust, accurate and scalable, some classifier ensemble methods demonstrated significantly better performance. The best classifiers were found to be the random subspace ensemble of SVM classifiers, rotation forest and ensembles with random linear and random spherical oracle.
TL;DR: A novel filter based on the NLM filter is proposed to improve the denoising effect and achieves betterDenoising performance over the other filters being compared.
Abstract: The non-local means (NLM) filter removes noise by calculating the weighted average of the pixels in the global area and shows superiority over existing local filter methods that only consider local neighbor pixels. This filter has been successfully extended from 2D images to 3D images and has been applied to denoising 3D magnetic resonance (MR) images. In this article, a novel filter based on the NLM filter is proposed to improve the denoising effect. Considering the characteristics of Rician noise in the MR images, denoising by the NLM filter is first performed on the squared magnitude images. Then, unbiased correcting is carried out to eliminate the biased deviation. When performing the NLM filter, the weight is calculated based on the Gaussian-filtered image to reduce the disturbance of the noise. The performance of this filter is evaluated by carrying out a qualitative and quantitative comparison of this method with three other filters, namely, the original NLM filter, the unbiased NLM (UNLM) filter and the Rician NLM (RNLM) filter. Experimental results demonstrate that the proposed filter achieves better denoising performance over the other filters being compared.
TL;DR: In the two patients with intracranial stenoses, 4D flow velocity measurements showed that one patient had normal velocity profiles in agreement with a previous magnetic resonance angiogram (MRA), while the second showed increased velocities that indicated a less significant narrowing than suspected on a previous MRA, as confirmed by catheter angiography.
Abstract: The aim of this study was to evaluate intracranial arterial stenoses and aneurysms with accelerated time-resolved three-dimensional (3D) phase-contrast MRI or 4D flow. The 4D flow technique was utilized to image four normal volunteers, two patients with intracranial stenoses and two patients with intracranial aneurysms. In order to reduce scan time, parallel imaging was combined with an acquisition strategy that eliminates the corners of k-space. In the two patients with intracranial stenoses, 4D flow velocity measurements showed that one patient had normal velocity profiles in agreement with a previous magnetic resonance angiogram (MRA), while the second showed increased velocities that indicated a less significant narrowing than suspected on a previous MRA, as confirmed by catheter angiography. This result may have prevented an invasive angiogram. In the two patients with 4-mm intracranial aneurysm, one had a stable helical flow pattern with a large jet, while the other had a temporally unstable flow pattern with a more focal jet possibly indicating that the second aneurysm may have a higher likelihood of rupture. Accelerated 4D flow provides time-resolved 3D velocity data in an 8- to 10-min scan. In the stenosis patients, the addition of 4D flow to a traditional MRA adds the velocity data provided from transcranial Doppler ultrasound (TCD) possibly allowing for more accurate grading of stenoses. In the aneurysm patients, visualization of flow patterns may help to provide prognostic information about future risk of rupture.
TL;DR: Patients with HAD have lower levels of Glx concentrations and Glx/Cr ratio in FWM, which was associated with impaired performance in specific cognitive domains, including executive functioning, fine motor, attention and working memory performance.
Abstract: Background and Purpose Human immunodeficiency virus (HIV)-associated dementia (HAD) has been extensively studied using magnetic resonance spectroscopy (MRS) at field strengths of 1.5 T. Higher magnetic field strengths (such as 3 T) allow for more reliable determination of certain compounds, such as glutamate (Glu) and glutamine (Gln). The current study was undertaken to investigate the utility of 3-T MRS for evaluating HIV+ patients with different levels of cognitive impairment with emphasis on the measurement of Glu and Glx (the sum of Glu and Gln). Methods Eighty-six HIV+ subjects were evaluated at 3 T using quantitative short echo time single-voxel MRS of frontal white matter (FWM) and basal ganglia (BG). Subjects were divided into three groups according to the Memorial Sloan Kettering (MSK) HIV dementia stage: 21 had normal cognition (NC) (MSK 0), 31 had mild cognitive impairment (MCI) without dementia (clinical MSK stage=0.5), and 34 had dementia (HAD) (MSK≥1). HIV+ subjects had also undergone standardized cognitive testing covering the domains of executive function, verbal memory, attention, information processing speed and motor and psychomotor speed. Between-group differences in metabolite levels in FWM and BG were evaluated using ANOVA. Pearson correlation coefficients were used to explore the associations between the Glu and Glx metabolites and neurocognitive results. Results FWM Glx was lower in HAD (8.1±2.1 mM) compared to both the MCI (9.17±2.1 mM) and NC groups (10.0±1.6 mM) (P=.006). FWM myo-inositol (mI) was higher in HAD (4.15±0.75 mM) compared to both MCI (3.86±0.85 mM) and NC status (3.4±0.67 mM) (P=.006). FWM Glx/creatine (Cr) was lower and FWM mI/Cr was significantly higher in the HAD compared to the MCI and NC groups (P=.01 and P=.004, respectively). BG N-acetyl aspartate (NAA) was lower in the HAD group (6.79±1.53 mM), compared to the MCI (7.5±1.06 mM) and NC (7.6±1.01 mM) groups (P=.036). Significant negative correlations were observed between Glu, Glx and NAA concentrations with Trail-Making Test B (P=.006, P=.0001 and P=.007, respectively), and significant positive correlation was found with the Digit symbol test (P=.02, P=.002 and P=.008, respectively). FWM Glx and NAA concentrations showed negative correlation with Grooved Pegboard nondominant hand (P=.02 and P=.04, respectively). Conclusion Patients with HAD have lower levels of Glx concentrations and Glx/Cr ratio in FWM, which was associated with impaired performance in specific cognitive domains, including executive functioning, fine motor, attention and working memory performance. Three-Tesla MRS measurements of Glx may be a useful indicator of neuronal loss/dysfunction in patients with HIV infection.
TL;DR: Using combined EEG-fMRI signals, useful new information is obtained on the description of the changes in oscillatory activity in alpha and beta bands during MI and on the investigation of the sites of BOLD activity as possible sources in generating these rhythms.
Abstract: The purpose of the present work was to investigate the correlation between topographical changes in brain oscillatory activity and the blood oxygenation level-dependent (BOLD) signal during a motor imagery (MI) task using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) coregistration. EEG was recorded in 7 healthy subjects inside a 1.5 T MR scanner during the imagination of the kinesthetic experience of movement. A Fast Fourier Transform was applied to EEG signal in the rest and active conditions. We used the event-related-synchronization (ERS)/desynchronization (ERD) approach to characterize where the imagination of movement produces a decrease in alpha and beta power. The mean alpha map showed ERD decrease localized over the contralateral sensory motor area (SM1c) and a light desynchronization in the ipsilateral sensory motor area (SM1i); whereas the mean beta map showed ERD decrease over the supplementary motor area (SMA). fMRI showed significant activation in SMA, SM1c, SM1i. The correlation is negative in the contralateral side and positive in the ipsilateral side. Using combined EEG-fMRI signals we obtained useful new information on the description of the changes in oscillatory activity in alpha and beta bands during MI and on the investigation of the sites of BOLD activity as possible sources in generating these rhythms. By correlating BOLD and ERD/ERS we may identify more accurately which regions contribute to changes of the electrical response.
TL;DR: In this article, contrast enhanced perfusion and blood oxygen level-dependent (BOLD) MRI were used to assess kidney transplants with normal function, acute tubular necrosis (ATN) and acute rejection.
Abstract: Functional magnetic resonance imaging (fMRI) is a powerful tool for examining kidney function, including organ blood flow and oxygen bioavailability. We have used contrast enhanced perfusion and blood oxygen level-dependent (BOLD) MRI to assess kidney transplants with normal function, acute tubular necrosis (ATN) and acute rejection. BOLD and MR-perfusion imaging were performed on 17 subjects with recently transplanted kidneys. There was a significant difference between medullary R2⁎ values in the group with acute rejection (R2⁎=16.2/s) compared to allografts with ATN (R2⁎=19.8/s; P=.047) and normal-functioning allografts (R2⁎=24.3/s;P=.0003). There was a significant difference between medullary perfusion measurements in the group with acute rejection (124.4±41.1 ml/100 g per minute) compared to those in patients with ATN (246.9±123.5 ml/100 g per minute; P=.02) and normal-functioning allografts (220.8±95.8 ml/100 g per minute; P=.02). This study highlights the utility of combining perfusion and BOLD MRI to assess renal function. We have demonstrated a decrease in medullary R2⁎ (decrease deoxyhemoglobin) on BOLD MRI and a decrease in medullary blood flow by MR perfusion imaging in those allografts with acute rejection, which indicates an increase in medullary oxygen bioavailability in allografts with rejection, despite a decrease in blood flow.
TL;DR: This study demonstrates anisotropy of water diffusion in normal breast tissue and establishes a normative range of breast FA values, which may be important for clinical interpretation and standardization of techniques.
Abstract: Purpose The objective of this study was to evaluate diffusion anisotropy of the breast parenchyma and assess the range and repeatability of diffusion tensor imaging (DTI) parameters in normal breast tissue. Materials and Methods The study was approved by our institutional review board and included 12 healthy females (median age, 36 years). Diffusion tensor imaging was performed at 1.5 T using a diffusion-weighted echo planar imaging sequence. Diffusion tensor imaging parameters including tensor eigenvalues ( λ 1 , λ 2 , λ 3 ), fractional anisotropy (FA) and apparent diffusion coefficient (ADC) were measured for anterior, central and posterior breast regions. Results Mean normal breast DTI measures were λ 1 =2.51×10 −3 mm 2 /s, λ 2 =1.89×10 −3 mm 2 /s, λ 3 =1.39×10 −3 mm 2 /s, ADC=1.95±0.24×10 −3 mm 2 /s and FA=0.29±0.05 for b =600 s/mm 2 . Significant regional differences were observed for both FA and ADC ( P b =0, 600 s/mm 2 vs. b =0, 1000 s/mm 2 , showed significant differences in ADC ( P Conclusion This study demonstrates anisotropy of water diffusion in normal breast tissue and establishes a normative range of breast FA values. Attention to the influence of breast region and b value on breast DTI measurements may be important for clinical interpretation and standardization of techniques.
TL;DR: Initial results suggest that this acquisition scheme has the potential to overcome strong field inhomogeneities acting over extended acquisition durations, exceeding 100 ms for a single-shot image, and to be superior to traditional schemes in non-homogeneous magnetic field environments.
Abstract: An approach has been recently introduced for acquiring two-dimensional (2D) nuclear magnetic resonance images in a single scan, based on the spatial encoding of the spin interactions. This article explores the potential of integrating this spatial encoding together with conventional temporal encoding principles, to produce 2D single-shot images with moderate field of views. The resulting “hybrid” imaging scheme is shown to be superior to traditional schemes in non-homogeneous magnetic field environments. An enhancement of previously discussed pulse sequences is also proposed, whereby distortions affecting the image along the spatially encoded axis are eliminated. This new variant is also characterized by a refocusing of T 2 * effects, leading to a restoration of high-definition images for regions which would otherwise be highly dephased and thus not visible. These single-scan 2D images are characterized by improved signal-to-noise ratios and a genuine T 2 contrast, albeit not free from inhomogeneity distortions. Simple postprocessing algorithms relying on inhomogeneity phase maps of the imaged object can successfully remove most of these residual distortions. Initial results suggest that this acquisition scheme has the potential to overcome strong field inhomogeneities acting over extended acquisition durations, exceeding 100 ms for a single-shot image.
TL;DR: The combination of DTI and DCE MRI has significantly better accuracy in prostate cancer diagnosis than either technique alone.
Abstract: The purpose of this work was to compare diagnostic accuracy of Diffusion Tensor Imaging (DTI), Dynamic Contrast Enhanced MRI (DCE MRI), and their combination in diagnosing prostate cancer. Twenty five patients with clinical suspicion of prostate cancer underwent MRI, prior to transrectal ultrasound (TRUS)-guided biopsies. MRI data were correlated to biopsy results. Logistic regression models were constructed for the DTI parameters, DCE MRI parameters, and their combination. The areas under the Receiver Operator Characteristic curves (AUC) were compared between the models. The nonparametric Wilcoxon signed rank test was used for statistical analysis. The sensitivity and specificity values were respectively 81% (74% – 87%) and 85% (79% – 90%) for DTI and 63% (55% – 70%) and 90% (85% – 94%) for DCE. The combination “DTI or DCE MRI” had 100% (97% – 100%) sensitivity and 77% (69% – 83%) specificity, while “DTI and DCE MRI” had 44% (37% – 52%) sensitivity and 98% (94% – 100%) specificity. The AUC for DTI + DCE parameters was significantly higher than that for either DTI (0.96 vs. 0.92, p = 0.0143) or DCE MRI parameters (0.96 vs. 0.87, p = 0.00187) alone. In conclusion, the combination of DTI and DCE MRI has significantly better accuracy in prostate cancer diagnosis than either technique alone.
TL;DR: The neurovascular relationship during periods of spontaneous activity is explored by using temporal kernel canonical correlation analysis (tkCCA), a multivariate method that can take into account any features in the signals that univariate analysis cannot and represent the first multivariate analysis of intracranial electrophysiology and high-resolution fMRI.
Abstract: Functional magnetic resonance imaging (fMRI) based on the so-called blood oxygen level-dependent (BOLD) contrast is a powerful tool for studying brain function not only locally but also on the large scale. Most studies assume a simple relationship between neural and BOLD activity, in spite of the fact that it is important to elucidate how the "when" and "what" components of neural activity are correlated to the "where" of fMRI data. Here we conducted simultaneous recordings of neural and BOLD signal fluctuations in primary visual (V1) cortex of anesthetized monkeys. We explored the neurovascular relationship during periods of spontaneous activity by using temporal kernel canonical correlation analysis (tkCCA). tkCCA is a multivariate method that can take into account any features in the signals that univariate analysis cannot. The method detects filters in voxel space (for fMRI data) and in frequency-time space (for neural data) that maximize the neurovascular correlation without any assumption of a hemodynamic response function (HRF). Our results showed a positive neurovascular coupling with a lag of 4-5 s and a larger contribution from local field potentials (LFPs) in the γ range than from low-frequency LFPs or spiking activity. The method also detected a higher correlation around the recording site in the concurrent spatial map, even though the pattern covered most of the occipital part of V1. These results are consistent with those of previous studies and represent the first multivariate analysis of intracranial electrophysiology and high-resolution fMRI.
TL;DR: The results indicated that Cr was well tolerated and oral Cr significantly improved the muscle PCr/Pi ratio and preserved the muscle strength in short term, however, this study provides no evidence that creatine will prove beneficial after long-term treatment, or have any positive effect on patient lifespan.
Abstract: Randomized, placebo-controlled single blinded study was carried out to evaluate the effect of oral creatine supplementation on cellular energetics, manual muscle test (MMT) score and functional status in steroid-naive, ambulatory boys suffering with Duchenne muscular dystrophy (DMD; n=33). Eighteen patients received creatine monohydrate (Cr; 5 g/day for 8 weeks), while 15 received placebo (500 mg of vitamin C). Phosphorus metabolite ratios were determined from the right calf muscle of patients using phosphorus magnetic resonance spectroscopy ((31)P MRS) both prior to (baseline) and after supplementation of Cr or placebo. In addition, metabolite ratios were determined in normal calf muscle of age and sex matched controls (n=8). Significant differences in several metabolite ratios were observed between controls and DMD patients indicating a lower energy state in these patients. Analysis using analysis of covariance adjusted for age and stature showed that the mean phosphocreatine (PCr)/inorganic phosphate (Pi) ratio in patients treated with Cr (4.7; 95% CI; 3.9-5.6) was significantly higher (P=.03) compared to the placebo group (3.3; 95% CI; 2.5-4.2). The mean percentage increase in PCr/Pi ratio was also more in patients 7 years), after supplementation. These results imply that the significant difference observed in PCr/Pi ratio between the Cr and the placebo groups after supplementation may be attributed to a decrease of PCr in the placebo group and an increase in PCr in the Cr group. Changes in MMT score between the two groups was significant (P=.04); however, no change in functional scale (P=.19) was observed. Parents reported subjective improvement on Cr supplementation versus worsening in placebo (P=.02). Our results indicated that Cr was well tolerated and oral Cr significantly improved the muscle PCr/Pi ratio and preserved the muscle strength in short term. However, this study provides no evidence that creatine will prove beneficial after long-term treatment, or have any positive effect on patient lifespan.
TL;DR: Phantom experiment and mice experiments demonstrated the feasibility of a nonambiguous identification of superparamagnetic contrast agents.
Abstract: Superparamagnetic iron oxide (SPIO) particles generate signal void regions on gradient echo images due to their strong magnetization. In practice, the signal void region might be indistinguishable from that generated by air. However, the response of SPIO to an externally applied magnetic field is nonlinear. Magnetization of SPIO saturates at around 1 T while magnetization of water and air increase linearly with field strength. Phantom experiment and mice experiments demonstrated the feasibility of a nonambiguous identification of superparamagnetic contrast agents.
TL;DR: The idea that the use of a patient specific measured AIF, not necessarily averaged over a large volume, offers a significant benefit with respect to an external AIF or a measured cohort average AIF is supported.
Abstract: It is widely recognised that the measurement of the arterial input function (AIF) is a key issue and a major source of errors in the pharmacokinetic modelling of dynamic, contrast-enhanced magnetic resonance imaging (DCE-MRI) data, and the modality of the AIF determination is still a matter of debate In this study we addressed the problem of the intrinsic variability of the AIF within the imaged volume of a DCE-MRI scan by systematically investigating the change in the concentration of contrast agent over time and the fit parameters of the derived vascular input function (VIF) obtained from the superior sagittal sinus (SSS) of a patient population that was scanned longitudinally during treatment for high grade glioma From a total of 82 scanning sessions, we compared the results obtained with three different DCE-MRI protocols and between two different fitting functions We applied a correction algorithm to the measured concentration-time curves to minimize the effect of the low temporal resolution on the VIF, and investigated the effect of this algorithm on the reproducibility Finally, where possible, we compared the signal obtained in the SSS to the signal obtained in the middle cerebral artery We found a good intrapatient reproducibility of both the measured gadolinium concentrations and VIF parameters, and that the variation of the parameters due to slice location within a patient was significantly lower than the intra patient variation Intrapatient, interscan differences were significantly less marked than inter-patient differences showing a good intraclass correlation coefficient We did encounter a MRI protocol dependence of the VIF fitting parameters The correction algorithm significantly improved the reproducibility of the fitting parameters These results support the idea that the use of a patient specific measured AIF, not necessarily averaged over a large volume, offers a significant benefit with respect to an external AIF or a measured cohort average AIF
TL;DR: In this paper, the diagnostic efficacy of WB-DWI and FDG-PET/CT was compared for assessment of non-small cell lung cancer (NSCLC) patients. But, WBDWI is not a feasible clinical technique for the assessment of NSCLC, lymph nodes and metastastic spread with high sensitivity and accuracy, but it was limited in the evaluation of neck lymph node metastases and small metastastic lung nodules.
Abstract: Objective To compare the diagnostic efficacy of whole-body diffusion-weighted imaging (WB-DWI) and [18F] fluoro-2-D-glucose PET/CT(FDG-PET/CT)for assessment of non–small cell lung cancer (NSCLC) patients. Materials and Methods A group of 56 patients (21 female, 35 male; 35–76 years) with NSCLC proved by pathologic examination or follow-up imaging findings was set as reference standards, and all patients underwent both WB-DWI at 1.5T (MAGNETOM Avanto) and PET/CT (Biograph 16). For WB-DWI, a free breathing diffusion-weighted single-shot spin-echo epi-sequence in five-stations (head-neck, thorax, abdomen, pelvis-thigh) was used. Each station-series contained 30 contiguous axial slices. Imaging parameters: FOV 360×360 mm, matrix size 128×80. B -values: 0 and 1000 s/mm 2 applied along x, y and z, 5 averages, acquisition time: 2.23 min/series, total: 11.55 min. The efficacy of WB-DWI and PET/CT were determined in a blinded reading by two radiologists and two nuclear medicine physicians using pathology and size change during follow up exams as the reference standard. Results Primary tumors ( n =56 patients) were correctly detected in 56 (100%) patients by both PET/CT and WB-DWI. Ninety-six lymph nodes metastases were determined with pathologic and follow-up examinations. Sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV) being for lymph node metastases: 91%, 90%, 90%, 96%, 80% with WB-DWI and 98%, 97%, 97%, 99%, 93% with PET-CT, other metastases: 90%, 95%, 92%, 97%, 83% with WB-DWI and 98%, 100%, 98%, 100%, 95% with PET-CT). Differences in the accuracy of lymph node metastasis detection between PET/CT and WB-DWI ( P =.031) were significant. The differences were not statistically significant for detection of other metastases. Conclusions WB-DWI is a feasible clinical technique for the assessment of NSCLC, lymph nodes and metastastic spread with high sensitivity and accuracy, but it was limited in the evaluation of neck lymph node metastases and small metastastic lung nodules.
TL;DR: It is suggested that it is possible to acquire highly undersampled breast DCE-MRI data with improved spatial and/or temporal resolution with minimal loss of image quality.
Abstract: A number of methods using temporal and spatial constraints have been proposed for reconstruction of undersampled dynamic magnetic resonance imaging (MRI) data. The complex data can be constrained or regularized in a number of different ways, for example, the time derivative of the magnitude and phase image voxels can be constrained separately or jointly. Intuitively, the performance of different regularizations will depend on both the data and the chosen temporal constraints. Here, a complex temporal total variation (TV) constraint was compared to the use of separate real and imaginary constraints, and to a magnitude constraint alone. Projection onto Convex Sets (POCS) with a gradient descent method was used to implement the diverse temporal constraints in reconstructions of DCE MRI data. For breast DCE data, serial POCS with separate real and imaginary TV constraints was found to give relatively poor results while serial/parallel POCS with a complex temporal TV constraint and serial POCS with a magnitude-only temporal TV constraint performed well with an acceleration factor as large as R=6. In the tumor area, the best method was found to be parallel POCS with complex temporal TV constraint. This method resulted in estimates for the pharmacokinetic parameters that were linearly correlated to those estimated from the fully-sampled data, with Ktrans,R=6=0.97 Ktrans,R=1+0.00 with correlation coefficient r=0.98, kep,R=6=0.95 kep,R=1+0.00 (r=0.85). These results suggest that it is possible to acquire highly undersampled breast DCE-MRI data with improved spatial and/or temporal resolution with minimal loss of image quality.
TL;DR: In this article, a new method for tissue classification of brain magnetic resonance images (MRI) of the brain is proposed, which is based on local image models where each model models the image content in a subset of the image domain.
Abstract: A new method for tissue classification of brain magnetic resonance images (MRI) of the brain is proposed. The method is based on local image models where each models the image content in a subset of the image domain. With this local modeling approach, the assumption that tissue types have the same characteristics over the brain needs not to be evoked. This is important because tissue type characteristics, such as T1 and T2 relaxation times and proton density, vary across the individual brain and the proposed method offers improved protection against intensity non-uniformity artifacts that can hamper automatic tissue classification methods in brain MRI. A framework in which local models for tissue intensities and Markov Random Field priors are combined into a global probabilistic image model is introduced. This global model will be an inhomogeneous Markov Random Field and it can be solved by standard algorithms such as iterative conditional modes. The division of the whole image domain into local brain regions possibly having different intensity statistics is realized via sub-volume probabilistic atlases. Finally, the parameters for the local intensity models are obtained without supervision by maximizing the weighted likelihood of a certain finite mixture model. For the maximization task, a novel genetic algorithm almost free of initialization dependency is applied. The algorithm is tested on both simulated and real brain MR images. The experiments confirm that the new method offers a useful improvement of the tissue classification accuracy when the basic tissue characteristics vary across the brain and the noise level of the images is reasonable. The method also offers better protection against intensity non-uniformity artifact than the corresponding method based on a global (whole image) modeling scheme.
TL;DR: The current usage of the multivariate autoregressive model for fMRI is described, the issues that arise when it is applied to hemodynamic time series are discussed, and several extensions are considered.
Abstract: Connectivity refers to the relationships that exist between different regions of the brain. In the context of functional magnetic resonance imaging (fMRI), it implies a quantifiable relationship between hemodynamic signals from different regions. One aspect of this relationship is the existence of small timing differences in the signals in different regions. Delays of 100 ms or less may be measured with fMRI, and these may reflect important aspects of the manner in which brain circuits respond as well as the overall functional organization of the brain. The multivariate autoregressive time series model has features to recommend it for measuring these delays and is straightforward to apply to hemodynamic data. In this review, we describe the current usage of the multivariate autoregressive model for fMRI, discuss the issues that arise when it is applied to hemodynamic time series and consider several extensions. Connectivity measures like Granger causality that are based on the autoregressive model do not always reflect true neuronal connectivity; however, we conclude that careful experimental design could make this methodology quite useful in extending the information obtainable using fMRI.
TL;DR: Both in vivo large rodent MR imaging and localized spectroscopy at the extremely high field of 21.1 T are feasible and demonstrate improved resolution and sensitivity valuable for structural and functional brain analysis.
Abstract: The first in vivo sodium and proton MR images and localized spectra of rodents were attained using the wide bore (105 mm) high resolution 21.1 T magnet, built and operated at the National High Magnetic Field Laboratory (Tallahassee, FL). Head images of normal mice (C57BL/6J) and Fisher rats (~ 250 g) were acquired with custom designed RF probes at frequencies of 237/900 MHz for sodium and proton, respectively. Sodium MRI resolutions of ~0.125 μL for mouse and rat heads were achieved by using a 3D back-projection pulse sequence. A gain in SNR of ~ 3 for sodium and of ~ 2 times for proton were found relative to corresponding MR images acquired at 9.4 T. 3D FLASH proton mouse images (50×50×50 μm3) were acquired in 90 min and corresponding rat images (100×100×100 μm3) within a total time of 120 min. Both in vivo large rodent MR imaging and localized spectroscopy at the extremely high field of 21.1 T are feasible and demonstrate improved resolution and sensitivity valuable for structural and functional brain analysis.
TL;DR: This work develops a fully automatic three-step 3D segmentation approach based upon a modified region growing approach and a further threshold technique that is modularized and can be applied for normal and fat accumulated liver tissue properties.
Abstract: Automatic 3D liver segmentation in magnetic resonance (MR) data sets has proven to be a very challenging task in the domain of medical image analysis There exist numerous approaches for automatic 3D liver segmentation on computer tomography data sets that have influenced the segmentation of MR images In contrast to previous approaches to liver segmentation in MR data sets, we use all available MR channel information of different weightings and formulate liver tissue and position probabilities in a probabilistic framework We apply multiclass linear discriminant analysis as a fast and efficient dimensionality reduction technique and generate probability maps then used for segmentation We develop a fully automatic three-step 3D segmentation approach based upon a modified region growing approach and a further threshold technique Finally, we incorporate characteristic prior knowledge to improve the segmentation results This novel 3D segmentation approach is modularized and can be applied for normal and fat accumulated liver tissue properties
TL;DR: T2 was found to increase fivefold for tendons and twofold for entheses due to the magic angle effect, and a resonance frequency shift up to 1.2 ppm was observed for both tendon and enthesesDue to the bulk susceptibility effect when their orientation was changed from 0 degree to 90 degrees relative to B(0).
Abstract: Tendons and entheses are magnetic resonance (MR) “invisible” when imaged with conventional clinical pulse sequences. When the highly ordered, collagen-rich fibers in tendons and entheses are placed at the magic angle, dipolar interactions are decreased and their T2s are often considerably increased. The bulk magnetic susceptibility of tendons and entheses also varies with orientation to B0, leading to a direction-dependent resonance frequency shift. Ultrashort echo time (UTE) sequences with a minimum TE of 8 μs provide high signal from both tendons and entheses. The combination of a UTE sequence with an interleaved undersampled variable TE acquisition scheme provides a new approach for fast spectroscopic imaging of short T2 tissues. This UTE spectroscopic imaging (UTESI) technique provides quantitative information including T2⁎, chemical shift and resonance frequency shift due to bulk susceptibility effect. In this article, the orientational effects on tendons and entheses were investigated using a UTESI sequence on a clinical 3-T scanner. T2⁎ was found to increase fivefold for tendons and twofold for entheses due to the magic angle effect. A resonance frequency shift up to 1.2 ppm was observed for both tendons and entheses due to the bulk susceptibility effect when their orientation was changed from 0° to 90° relative to B0.