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Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumor-infiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment.
Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
We present a novel framework for characterizing paired brain networks using techniques in hyper-networks, sparse learning and persistent homology. The framework is general enough for dealing with any type of paired images such as twins, multimodal and longitudinal images. The exact nonparametric statistical inference procedure is derived on testing monotonic graph theory features that do not rely on time consuming permutation tests. The proposed method computes the exact probability in quadratic time while the permutation tests require exponential time. As illustrations, we apply the method to simulated networks and a twin fMRI study. In case of the latter, we determine the statistical significance of the heritability index of the large-scale reward network where every voxel is a network node.
PURPOSE - Quantitative multi-parametric MRI (mpMRI) methods may allow the assessment of renal injury and function in a sensitive and objective manner. This study aimed to evaluate an array of MRI methods that exploit endogenous contrasts including relaxation rates, pool size ratio (PSR) derived from quantitative magnetization transfer (qMT), chemical exchange saturation transfer (CEST), nuclear Overhauser enhancement (NOE), and apparent diffusion coefficient (ADC) for their sensitivity and specificity in detecting abnormal features associated with kidney disease in a murine model of unilateral ureter obstruction (UUO).
METHODS - MRI scans were performed in anesthetized C57BL/6N mice 1, 3, or 6 days after UUO at 7T. Paraffin tissue sections were stained with Masson trichrome following MRI.
RESULTS - Compared to contralateral kidneys, the cortices of UUO kidneys showed decreases of relaxation rates R and R , PSR, NOE, and ADC. No significant changes in CEST effects were observed for the cortical region of UUO kidneys. The MRI parametric changes in renal cortex are related to tubular cell death, tubular atrophy, tubular dilation, urine retention, and interstitial fibrosis in the cortex of UUO kidneys.
CONCLUSION - Measurements of multiple MRI parameters provide comprehensive information about the molecular and cellular changes produced by UUO. Magn Reson Med 79:2216-2227, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
© 2017 International Society for Magnetic Resonance in Medicine.
PURPOSE - We aimed to identify non-invasive imaging parameters that can serve as biomarkers for the integrity of the spinal cord, which is paramount to neurological function. Diffusion tensor imaging (DTI) indices are sensitive to axonal and myelin damage, and have strong potential to serve as such biomarkers. However, averaging DTI indices over large regions of interest (ROIs), a common approach to analyzing the images of injured spinal cord, leads to loss of subject-specific information. We investigated if DTI-tractography-driven, subject-specific demarcation approach can yield measures that are more specific to impairment.
METHODS - In 18 individuals with chronic spinal cord injury (SCI), subject-specific demarcation of the injury region was performed using DTI tractography, which yielded three regions relative to injury (RRI; regions superior to, at, and below injury epicenter). DTI indices averaged over each RRI were correlated with measures of residual motor and sensory function, obtained using the International Standard of Neurological Classification for Spinal Cord Injury (ISNCSCI).
RESULTS - Total ISNCSCI score (ISNCSCI-tot; sum of ISNCSCI motor and sensory scores) was significantly (p < 0.05) correlated with fractional anisotropy and axial and radial diffusivities. ISNCSCI-tot showed strongest correlation with indices measured from the region inferior to the injury epicenter (IRRI), the degree of which exceeded that of those measured from the entire cervical cord-suggesting contribution from Wallerian degeneration.
CONCLUSION - DTI tractography-driven, subject-specific injury demarcation approach provided measures that were more specific to impairment. Notably, DTI indices obtained from the IRRI region showed the highest specificity to impairment, demonstrating their strong potential as biomarkers for the SCI severity.
INTRODUCTION - There is a need to develop imaging methods sensitive to axonal injury in multiple sclerosis (MS), given the prominent impact of axonal pathology on disability and outcome. Advanced multi-compartmental diffusion models offer novel indices sensitive to white matter microstructure. One such model, neurite orientation dispersion and density imaging (NODDI), is sensitive to neurite morphology, providing indices of apparent volume fractions of axons (v), isotropic water (v) and the dispersion of fibers about a central axis (orientation dispersion index, ODI). NODDI has yet to be studied for its sensitivity to spinal cord pathology. Here, we investigate the feasibility and utility of NODDI in the cervical spinal cord of MS patients.
METHODS - NODDI was applied in the cervical spinal cord in a cohort of 8 controls and 6 MS patients. Statistical analyses were performed to test the sensitivity of NODDI-derived indices to pathology in MS (both lesion and normal appearing white matter NAWM). Diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) analysis were also performed to compare with NODDI.
RESULTS - A decrease in NODDI-derived v was observed at the site of the lesion ( < 0.01), whereas a global increase in ODI was seen throughout white matter ( < 0.001). DKI-derived mean kurtosis (MK) and radial kurtosis (RK) and DTI-derived fractional anisotropy (FA) and radial diffusivity (RD) were all significantly different in MS patients ( < 0.02), however NODDI provided higher contrast between NAWM and lesion in all MS patients.
CONCLUSION - NODDI provides unique contrast that is not available with DKI or DTI, enabling improved characterization of the spinal cord in MS.
PURPOSE - In principle, MR methods that exploit magnetization transfer (MT) may be used to quantify changes in the molecular composition of tissues after injury. The ability to track such changes in injured spinal cord may allow more precise assessment of the state of neural tissues.
METHODS - Z-Spectra were obtained from the cervical spinal cord before and after a unilateral dorsal column lesion in monkeys at 9.4T. The amplitudes of chemical exchange saturation transfer (CEST) and nuclear Overhauser enhancement (NOE) effects from multiple proton pools, along with nonspecific semisolid MT effects from immobile macromolecules, were quantified using a five-peak Lorenzian fitting of each Z-spectrum.
RESULTS - Abnormal tissues/cysts that formed around lesion sites exhibited relatively low correlations between their Z-spectra and that of normal gray matter (GM). Compared with normal GM, cysts showed strong CEST but weak semisolid MT and NOE effects after injury. The abnormal tissues around lesion sites were heterogeneous and showed different regional Z-spectra. Different regional correlations between proton pools were observed. Longitudinally, injured spinal cord tissue exhibited remarkable recovery in all subjects.
CONCLUSION - Characterization of multiple proton pools from Z-spectra permitted noninvasive, regional, quantitative assessments of changes in tissue composition of injured spinal cord over time. Magn Reson Med 79:1070-1082, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
© 2017 International Society for Magnetic Resonance in Medicine.
OBJECTIVE - Currently, approximately 60-70% of patients with unilateral temporal lobe epilepsy (TLE) remain seizure-free 3 years after surgery. The goal of this work was to develop a presurgical connectivity-based biomarker to identify those patients who will have an unfavorable seizure outcome 1-year postsurgery.
METHODS - Resting-state functional and diffusion-weighted 3T magnetic resonance imaging (MRI) was acquired from 22 unilateral (15 right, 7 left) patients with TLE and 35 healthy controls. A seizure propagation network was identified including ipsilateral (to seizure focus) and contralateral hippocampus, thalamus, and insula, with bilateral midcingulate and precuneus. Between each pair of regions, functional connectivity based on correlations of low frequency functional MRI signals, and structural connectivity based on streamline density of diffusion MRI data were computed and transformed to metrics related to healthy controls of the same age.
RESULTS - A consistent connectivity pattern representing the network expected in patients with seizure-free outcome was identified using eight patients who were seizure-free at 1-year postsurgery. The hypothesis that increased similarity to the model would be associated with better seizure outcome was tested in 14 other patients (Engel class IA, seizure-free: n = 5; Engel class IB-II, favorable: n = 4; Engel class III-IV, unfavorable: n = 5) using two similarity metrics: Pearson correlation and Euclidean distance. The seizure-free connectivity model successfully separated all the patients with unfavorable outcome from the seizure-free and favorable outcome patients (p = 0.0005, two-tailed Fisher's exact test) through the combination of the two similarity metrics with 100% accuracy. No other clinical and demographic predictors were successful in this regard.
SIGNIFICANCE - This work introduces a methodologic framework to assess individual patients, and demonstrates the ability to use network connectivity as a potential clinical tool for epilepsy surgery outcome prediction after more comprehensive validation.
Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.
Dopamine function is broadly implicated in multiple neuropsychiatric conditions believed to have a genetic basis. Although a few positron emission tomography (PET) studies have investigated the impact of single-nucleotide polymorphisms (SNPs) in the dopamine D2 receptor gene (DRD2) on D2/3 receptor availability (binding potential, BP), these studies have often been limited by small sample size. Furthermore, the most commonly studied SNP in D2/3 BP (Taq1A) is not located in the DRD2 gene itself, suggesting that its linkage with other DRD2 SNPs may explain previous PET findings. Here, in the largest PET genetic study to date (n=84), we tested for effects of the C957T and -141C Ins/Del SNPs (located within DRD2) as well as Taq1A on BP of the high-affinity D2 receptor tracer F-Fallypride. In a whole-brain voxelwise analysis, we found a positive linear effect of C957T T allele status on striatal BP bilaterally. The multilocus genetic scores containing C957T and one or both of the other SNPs produced qualitatively similar striatal results to C957T alone. The number of C957T T alleles predicted BP in anatomically defined putamen and ventral striatum (but not caudate) regions of interest, suggesting some regional specificity of effects in the striatum. By contrast, no significant effects arose in cortical regions. Taken together, our data support the critical role of C957T in striatal D2/3 receptor availability. This work has implications for a number of psychiatric conditions in which dopamine signaling and variation in C957T status have been implicated, including schizophrenia and substance use disorders.
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.