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Neuroimaging often involves acquiring high-resolution anatomical images along with other low-resolution image modalities, like diffusion and functional magnetic resonance imaging. Performing gray matter statistics with low-resolution image modalities is a challenge due to registration artifacts and partial volume effects. Gray matter surface based spatial statistics (GS-BSS) has been shown to provide higher sensitivity using gray matter surfaces compared to that of skeletonization approach of gray matter based spatial statistics which is adapted from tract based spatial statistics in diffusion studies. In this study, we improve upon GS-BSS incorporating neurite orientation dispersion and density imaging (NODDI) based search (denoted N-GSBSS) by 1) enhancing metrics mapping from native space, 2) incorporating maximum orientation dispersion index (ODI) search along surface normal, and 3) proposing applicability to other modalities, such as functional MRI (fMRI). We evaluated the performance of N-GSBSS against three baseline pipelines: volume-based registration, FreeSurfer's surface registration and ciftify pipeline for fMRI and simulation studies. First, qualitative mean ODI results are shown for N-GSBSS with and without NODDI based search in comparison with ciftify pipeline. Second, we conducted one-sample t-tests on working memory activations in fMRI to show that the proposed method can aid in the analysis of low resolution fMRI data. Finally we performed a sensitivity test in a simulation study by varying percentage change of intensity values within a region of interest in gray matter probability maps. N-GSBSS showed higher sensitivity in the simulation test compared to the other methods capturing difference between the groups starting at 10% change in the intensity values. The computational time of N-GSBSS is 68 times faster than that of traditional surface-based or 86 times faster than that of ciftify pipeline analysis.
Copyright © 2019 Elsevier Inc. All rights reserved.
Diffusion magnetic resonance images typically suffer from spatial distortions due to susceptibility induced off-resonance fields, which may affect the geometric fidelity of the reconstructed volume and cause mismatches with anatomical images. State-of-the art susceptibility correction (for example, FSL's TOPUP algorithm) typically requires data acquired twice with reverse phase encoding directions, referred to as blip-up blip-down acquisitions, in order to estimate an undistorted volume. Unfortunately, not all imaging protocols include a blip-up blip-down acquisition, and cannot take advantage of the state-of-the art susceptibility and motion correction capabilities. In this study, we aim to enable TOPUP-like processing with historical and/or limited diffusion imaging data that include only a structural image and single blip diffusion image. We utilize deep learning to synthesize an undistorted non-diffusion weighted image from the structural image, and use the non-distorted synthetic image as an anatomical target for distortion correction. We evaluate the efficacy of this approach (named Synb0-DisCo) and show that our distortion correction process results in better matching of the geometry of undistorted anatomical images, reduces variation in diffusion modeling, and is practically equivalent to having both blip-up and blip-down non-diffusion weighted images.
Copyright © 2019 Elsevier Inc. All rights reserved.
Chemical exchange saturation transfer (CEST) imaging of fast exchanging amine protons at 3 ppm offset from the water resonant frequency is of practical interest, but quantification of fast exchanging pools by CEST is challenging. To effectively saturate fast exchanging protons, high irradiation powers need to be applied, but these may cause significant direct water saturation as well as non-specific semi-solid magnetization transfer (MT) effects, and thus decrease the specificity of the measured signal. In addition, the CEST signal may depend on the water longitudinal relaxation time (T ), which likely varies between tissues and with pathology, further reducing specificity. Previously, an analysis of the asymmetry of saturation effects (MTR ) has been commonly used to quantify fast exchanging amine CEST signals. However, our results show that MTR is greatly affected by the above factors, as well as asymmetric MT and nuclear Overhauser enhancement (NOE) effects. Here, we instead applied a relatively more specific inverse analysis method, named AREX (apparent exchange-dependent relaxation), that has previously been applied only to slow and intermediate exchanging solutes. Numerical simulations and controlled phantom experiments show that, although MTR depends on T and semi-solid content, AREX acquired in steady state does not, which suggests that AREX is more specific than MTR . By combining with a fitting approach instead of using the asymmetric analysis to obtain reference signals, AREX can also avoid contaminations from asymmetric MT and NOE effects. Animal experiments show that these two quantification methods produce differing contrasts between tumors and contralateral normal tissues in rat brain tumor models, suggesting that conventional MTR applied in vivo may be influenced by variations in T , semi-solid content, or NOE effect. Thus, the use of MTR may lead to misinterpretation, while AREX with corrections for competing effects likely enhances the specificity and accuracy of quantification to fast exchanging pools.
Copyright © 2017 John Wiley & Sons, Ltd.
Accurate quantification of chemical exchange saturation transfer (CEST) effects, including dipole-dipole mediated relayed nuclear Overhauser enhancement (rNOE) saturation transfer, is important for applications and studies of molecular concentration and transfer rate (and thereby pH or temperature). Although several quantification methods, such as Lorentzian difference (LD) analysis, multiple-pool Lorentzian fits, and the three-point method, have been extensively used in several preclinical and clinical applications, the accuracy of these methods has not been evaluated. Here we simulated multiple-pool Z spectra containing the pools that contribute to the main CEST and rNOE saturation transfer signals in the brain, numerically fit them using the different methods, and then compared their derived CEST metrics with the known solute concentrations and exchange rates. Our results show that the LD analysis overestimates contributions from amide proton transfer (APT) and intermediate exchanging amine protons; the three-point method significantly underestimates both APT and rNOE saturation transfer at -3.5 ppm (NOE(-3.5)). The multiple-pool Lorentzian fit is more accurate than the other two methods, but only at lower irradiation powers (≤1 μT at 9.4 T) within the range of our simulations. At higher irradiation powers, this method is also inaccurate because of the presence of a fast exchanging CEST signal that has a non-Lorentzian lineshape. Quantitative parameters derived from in vivo images of rodent brain tumor obtained using an irradiation power of 1 μT were also compared. Our results demonstrate that all three quantification methods show similar contrasts between tumor and contralateral normal tissue for both APT and the NOE(-3.5). However, the quantified values of the three methods are significantly different. Our work provides insight into the fitting accuracy obtainable in a complex tissue model and provides guidelines for evaluating other newly developed quantification methods.
Copyright © 2017 John Wiley & Sons, Ltd.
The importance of epistasis-or statistical interactions between genetic variants-to the development of complex disease in humans has been controversial. Genome-wide association studies of statistical interactions influencing human traits have recently become computationally feasible and have identified many putative interactions. However, statistical models used to detect interactions can be confounded, which makes it difficult to be certain that observed statistical interactions are evidence for true molecular epistasis. In this study, we investigate whether there is evidence for epistatic interactions between genetic variants within the cis-regulatory region that influence gene expression after accounting for technical, statistical, and biological confounding factors. We identified 1,119 (FDR = 5%) interactions that appear to regulate gene expression in human lymphoblastoid cell lines, a tightly controlled, largely genetically determined phenotype. Many of these interactions replicated in an independent dataset (90 of 803 tested, Bonferroni threshold). We then performed an exhaustive analysis of both known and novel confounders, including ceiling/floor effects, missing genotype combinations, haplotype effects, single variants tagged through linkage disequilibrium, and population stratification. Every interaction could be explained by at least one of these confounders, and replication in independent datasets did not protect against some confounders. Assuming that the confounding factors provide a more parsimonious explanation for each interaction, we find it unlikely that cis-regulatory interactions contribute strongly to human gene expression, which calls into question the relevance of cis-regulatory interactions for other human phenotypes. We additionally propose several best practices for epistasis testing to protect future studies from confounding.
Copyright © 2016 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
PURPOSE - To investigate the influence of transcytolemmal water exchange on estimates of tissue microstructural parameters derived from diffusion MRI using conventional PGSE and IMPULSED methods.
METHODS - Computer simulations were performed to incorporate a broad range of intracellular water life times τ (50-∞ ms), cell diameters d (5-15 μm), and intrinsic diffusion coefficient D (0.6-2 μm /ms) for different values of signal-to-noise ratio (SNR) (10 to 50). For experiments, murine erythroleukemia (MEL) cancer cells were cultured and treated with saponin to selectively change cell membrane permeability. All fitted microstructural parameters from simulations and experiments in vitro were compared with ground-truth values.
RESULTS - Simulations showed that, for both PGSE and IMPULSED methods, cell diameter d can be reliably fit with sufficient SNR (≥ 50), whereas intracellular volume fraction f is intrinsically underestimated due to transcytolemmal water exchange. D can be reliably fit only with sufficient SNR and using the IMPULSED method with short diffusion times. These results were confirmed with those obtained in the cell culture experiments in vitro.
CONCLUSION - For the sequences and models considered in this study, transcytolemmal water exchange has minor effects on the fittings of d and D with physiologically relevant membrane permeabilities if the SNR is sufficient (> 50), but f is intrinsically underestimated. Magn Reson Med 77:2239-2249, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
© 2016 International Society for Magnetic Resonance in Medicine.
BACKGROUND AND PURPOSE - Clinical measurements of cerebral perfusion have been increasingly performed with multiecho dynamic susceptibility contrast-MR imaging techniques due to their ability to remove confounding T1 effects of contrast agent extravasation from perfusion quantification. However, to this point, the extra information provided by multiecho techniques has not been used to improve the process of estimating the arterial input function, which is critical to accurate perfusion quantification. The purpose of this study is to investigate methods by which multiecho DSC-MRI data can be used to automatically avoid voxels whose signal decreases to the level of noise when calculating the arterial input function.
MATERIALS AND METHODS - Here we compare postprocessing strategies for clinical multiecho DSC-MR imaging data to test whether arterial input function measures could be improved by automatically identifying and removing voxels exhibiting signal attenuation (truncation) artifacts.
RESULTS - In a clinical pediatric population, we found that the Pearson correlation coefficient between ΔR2* time-series calculated from each TE individually was a valuable criterion for automated estimation of the arterial input function, resulting in higher peak arterial input function values while maintaining smooth and reliable arterial input function shapes.
CONCLUSIONS - This work is the first to demonstrate that multiecho information may be useful in clinically important automatic arterial input function estimation because it can be used to improve automatic selection of voxels from which the arterial input function should be measured.
© 2016 by American Journal of Neuroradiology.
Gastric contractions are governed by a bioelectrical event known as slow waves. High-resolution electrical mapping has recently been applied to study complex gastric slow wave spatiotemporal propagations in detail. As these methods are translated to clinical and experimental applications, it is evident that efficient and automated methods are a necessity for analysis. Despite automated methods to detect slow wave events, manual review and correction remains necessary due to the presence of experimental noise in the recordings. Manual deletion of invalid slow wave events is time consuming and inefficient. We have therefore developed an algorithm to eliminate invalid markers of slow waves, via the use of frequency and morphological analysis. The techniques were validated with experimental data using serosal gastric slow wave recordings from animals and humans with a sensitivity of 90% and specificity of 85%. It is anticipated these methods will facilitate analyzing high-resolution slow wave mapping data and accelerate clinical translation of electrical mapping to clinical and diagnostic gastroentrology.
Amide proton transfer (APT) imaging may potentially detect mobile proteins/peptides non-invasively in vivo, but its specificity may be reduced by contamination from other confounding effects such as asymmetry of non-specific magnetization transfer (MT) effects and spin-lattice relaxation with rate R1 (=1/T1). Previously reported spillover, MT and R1 correction methods were based on a two-pool model, in which the existence of multiple water compartments with heterogeneous relaxation properties in real tissues was ignored. Such simple models may not adequately represent real tissues, and thus such corrections may be unreliable. The current study investigated the effectiveness and accuracy of correcting for R1 in APT imaging via simulations and in vivo experiments using tumor-bearing rats subjected to serial injections of Gd-DTPA that produced different tissue R1 values in regions of blood-brain-barrier breakdown. The results suggest that conventional measurements of APT contrast (such as APT* and MTRasym ) may be significantly contaminated by R1 variations, while the R1 -corrected metric AREX* was found to be relatively unaffected by R1 changes over a broad range (0.4-1 Hz). Our results confirm the importance of correcting for spin-lattice relaxation effects in quantitative APT imaging, and demonstrate the reliability of using the observed tissue R1 for corrections to obtain more specific and accurate measurements of APT contrast in vivo. The results also indicate that, due to relatively fast transcytolemmal water exchange, the influence of intra- and extracellular water compartments on CEST measurements with seconds long saturation time may be ignored in tumors.
Copyright © 2015 John Wiley & Sons, Ltd.
BACKGROUND AND PURPOSE - Blood oxygenation level-dependent MR imaging is increasingly used clinically to noninvasively assess cerebrovascular reactivity and/or language and motor function. However, many patients have metallic implants, which will induce susceptibility artifacts, rendering the functional information uninformative. Here, we calculate and interpret blood oxygenation level-dependent MR imaging artifact impact arising from surgically implanted hardware.
MATERIALS AND METHODS - A retrospective analysis of all blood oxygenation level-dependent MRIs (n = 343; B0 = 3T; TE = 35 ms; gradient echo EPI) acquired clinically (year range = 2006-2014) at our hospital was performed. Blood oxygenation level-dependent MRIs were most commonly prescribed for patients with cerebrovascular disease (n = 80) or patients undergoing language or motor localization (n = 263). Artifact volume (cubic centimeters) and its impact on clinical interpretation were determined by a board-certified neuroradiologist.
RESULTS - Mean artifact volume associated with intracranial hardware was 4.3 ± 3.2 cm(3) (range = 1.1-9.4 cm(3)). The mean artifact volume from extracranial hardware in patients with cerebrovascular disease was 28.4 ± 14.0 cm(3) (range = 6.1-61.7 cm(3)), and in patients with noncerebrovascular disease undergoing visual or motor functional mapping, it was 39.9 (3)± 27.0 cm(3) (range = 6.9-77.1 cm(3)). The mean artifact volume for ventriculoperitoneal shunts was 95.7 ± 39.3 cm(3) (range = 64.0-139.6 cm(3)). Artifacts had no-to-mild effects on clinical interpretability in all patients with intracranial implants. Extracranial hardware artifacts had no-to-moderate impact on clinical interpretability, with the exception of 1 patient with 12 KLS-Martin maxDrive screws with severe artifacts precluding clinical interpretation. All examined ventriculoperitoneal shunts resulted in moderate-to-severe artifacts, limiting clinical interpretation.
CONCLUSIONS - Blood oxygenation level-dependent MR imaging yields interpretable functional maps in most patients beyond a small (30-40 cm(3)) artifact surrounding the hardware. Exceptions were ventriculoperitoneal shunts, particularly those with programmable valves and siphon gauges, and large numbers of KLS-Martin maxDrive screws.
© 2015 by American Journal of Neuroradiology.