PubTransformer

A site to transform Pubmed publications into these bibliographic reference formats: ADS, BibTeX, EndNote, ISI used by the Web of Knowledge, RIS, MEDLINE, Microsoft's Word 2007 XML.

Magnetic Resonance Imaging - Top 30 Publications

Prediction of N0 Irradiated Rectal Cancer Comparing MRI Before and After Preoperative Chemoradiotherapy.

The prediction of lymph node status using MRI has an impact on the management of rectal cancer, both before and after preoperative chemoradiotherapy.

Clinical and imaging features of spinal cord type of neuro Behçet disease: A case report and systematic review.

To investigate the clinical and MRI characteristics of spinal cord nerve Behçet's disease.

Accurate Estimation of Functional Liver Volume Using Gd-EOB-DTPA MRI Compared to MDCT/(99m)Tc-SPECT Fusion Imaging.

We assessed the utility of dynamic magnetic resonance imaging (MRI) with gadoxetate-ethoxybenzyl-diethylenetriamine penta-aceticpenta-acetic acid (Gd-EOB-DTPA) (EOB-MRI) for estimating functional liver volume compared to (99m)Tc-galactosyl albumin single-photon-emission computed tomography ((99m)Tc-GSA SPECT).

Glymphatic MRI in idiopathic normal pressure hydrocephalus.

The glymphatic system has in previous studies been shown as fundamental to clearance of waste metabolites from the brain interstitial space, and is proposed to be instrumental in normal ageing and brain pathology such as Alzheimer's disease and brain trauma. Assessment of glymphatic function using magnetic resonance imaging with intrathecal contrast agent as a cerebrospinal fluid tracer has so far been limited to rodents. We aimed to image cerebrospinal fluid flow characteristics and glymphatic function in humans, and applied the methodology in a prospective study of 15 idiopathic normal pressure hydrocephalus patients (mean age 71.3 ± 8.1 years, three female and 12 male) and eight reference subjects (mean age 41.1 + 13.0 years, six female and two male) with suspected cerebrospinal fluid leakage (seven) and intracranial cyst (one). The imaging protocol included T1-weighted magnetic resonance imaging with equal sequence parameters before and at multiple time points through 24 h after intrathecal injection of the contrast agent gadobutrol at the lumbar level. All study subjects were kept in the supine position between examinations during the first day. Gadobutrol enhancement was measured at all imaging time points from regions of interest placed at predefined locations in brain parenchyma, the subarachnoid and intraventricular space, and inside the sagittal sinus. Parameters demonstrating gadobutrol enhancement and clearance in different locations were compared between idiopathic normal pressure hydrocephalus and reference subjects. A characteristic flow pattern in idiopathic normal hydrocephalus was ventricular reflux of gadobutrol from the subarachnoid space followed by transependymal gadobutrol migration. At the brain surfaces, gadobutrol propagated antegradely along large leptomeningeal arteries in all study subjects, and preceded glymphatic enhancement in adjacent brain tissue, indicating a pivotal role of intracranial pulsations for glymphatic function. In idiopathic normal pressure hydrocephalus, we found delayed enhancement (P < 0.05) and decreased clearance of gadobutrol (P < 0.05) at the Sylvian fissure. Parenchymal (glymphatic) enhancement peaked overnight in both study groups, possibly indicating a crucial role of sleep, and was larger in normal pressure hydrocephalus patients (P < 0.05 at inferior frontal gyrus). We interpret decreased gadobutrol clearance from the subarachnoid space, along with persisting enhancement in brain parenchyma, as signs of reduced glymphatic clearance in idiopathic normal hydrocephalus, and hypothesize that reduced glymphatic function is instrumental for dementia in this disease. The study shows promise for glymphatic magnetic resonance imaging as a method to assess human brain metabolic function and renders a potential for contrast enhanced brain extravascular space imaging.

Using a reference when defining an abnormal MRI reduces false-positive MRI results-a longitudinal study in two cohorts at risk for rheumatoid arthritis.

The use of hand and foot MRI in the diagnostic process of RA has been advocated. Recent studies showed that MRI is helpful in predicting progression from clinically suspect arthralgia (CSA) to clinical arthritis, and from undifferentiated arthritis (UA) to RA. Symptom-free persons can also show inflammation on MRI. This study aimed to evaluate if MRI findings in symptom-free volunteers are relevant when defining a positive MRI.

Focal T2 and FLAIR hyperintensities within the infarcted area: A suitable marker for patient selection for treatment?

Some authors use FLAIR imaging to select patients for stroke treatment. However, the effect of hyperintensity on FLAIR images on outcome and bleeding has been addressed in only few studies with conflicting results.

Magnetic resonance imaging: A possible alternative to a standing lateral radiograph for evaluating cervical sagittal alignment in patients with cervical disc herniation?

Convincing evidence supporting the use of magnetic resonance imaging (MRI) as an effective tool for evaluating cervical sagittal alignment is lacking. This study aims to analyze the differences and correlations between cervical sagittal parameters on x-ray and MRI in patients with cervical disc herniation and to determine whether MRI could substitute for cervical x-ray for measurement of cervical sagittal parameters.

Case 246: MR Imaging of a Complex Cystic Mass in a Newborn Girl.

History A 6-day-old female neonate presented to the outpatient pediatric surgery clinic for evaluation of a possible prenatal abdominal mass. The neonate was delivered at term via cesarean section due to macrosomia, with a reported birth weight of 11 lb 8.7 oz (5.23 kg). The patient's postnatal course was remarkable for resolving neonatal hyperbilirubinemia. A physical examination was remarkable for a palpable mass in the abdomen. Maternal risk factors included class II obesity, type 2 diabetes, and metabolic syndrome. Prenatal images obtained at an outside institution were not available at this time. Ultrasonography (US) of the abdomen and pelvis was performed 6 days after birth. Follow-up US at 29 days of life revealed no substantial change in the appearance of the findings. This patient remained asymptomatic, and gadolinium-enhanced (Magnevist; Bayer Pharma, Berlin, Germany) magnetic resonance (MR) imaging of the abdomen and pelvis was performed at 84 days of life. The mass was excised surgically at 89 days of life, and the patient had an uncomplicated postoperative course.

Perihematomal diffusion restriction as a common finding in large intracerebral hemorrhages in the hyperacute phase.

There is growing evidence that a perihematomal area of restricted diffusion (PDR) exists in intraparenchymal hemorrhages (IPH) within 1 week of symptom onset (SO). Here, we study characteristics and the clinical impact of the PDR in patients with hyperacute (≤ 6 hours from SO) IPH by means of apparent diffusion coefficient (ADC).

Image identification from brain activity using the population receptive field model.

A goal of computational models is not only to explain experimental data but also to make new predictions. A current focus of computational neuroimaging is to predict features of the presented stimulus from measured brain signals. These computational neuroimaging approaches may be agnostic about the underlying neural processes or may be biologically inspired. Here, we use the biologically inspired population receptive field (pRF) approach to identify presented images from fMRI recordings of the visual cortex, using an explicit model of the underlying neural response selectivity. The advantage of the pRF-model is its simplicity: it is defined by a handful of parameters, which can be estimated from fMRI data that was collected within half an hour. Using 7T MRI, we measured responses elicited by different visual stimuli: (i) conventional pRF mapping stimuli, (ii) semi-random synthetic images and (iii) natural images. The pRF mapping stimuli were used to estimate the pRF-properties of each cortical location in early visual cortex. Next, we used these pRFs to identify which synthetic or natural images was presented to the subject from the fMRI responses. We show that image identification using V1 responses is far above chance, both for the synthetic and natural images. Thus, we can identify visual images, including natural images, using the most fundamental low-parameter pRF model estimated from conventional pRF mapping stimuli. This allows broader application of image identification.

Magnetic Resonance Imaging-Based Prostate-Specific Antigen Density for Prediction of Gleason Score Upgrade in Patients With Low-Risk Prostate Cancer on Initial Biopsy.

The aim of this study was to assess the utility of prostate-specific antigen density (PSAD) calculated using magnetic resonance imaging for predicting Gleason score (GS) upgrade in patients with low-risk prostate cancer on biopsy.

Is It Me or My Hormones? Neuroendocrine Activation Profiles to Visual Food Stimuli Across the Menstrual Cycle.

Homeostatic energy balance is controlled via the hypothalamus, whereas regions controlling reward and cognitive decision-making are critical for hedonic eating. Eating varies across the menstrual cycle peaking at the midluteal phase.

Cystatin C, a potential marker for cerebral microvascular compliance, is associated with white-matter hyperintensities progression.

Cerebral white matter hyperintensities (WMHs) are central MRI markers of the brain aging process, but the mechanisms for its progression remain unclear. In this study, we aimed to determine whether the baseline serum cystatin C level represented one mechanism underlying WMH progression, and whether it was associated with the long-term progression of cerebral WMH volume in MRI. 166 consecutive individuals who were ≥50 years of age and who underwent initial/follow-up MRI evaluations within an interval of 34-45 months were included. Serum cystatin C level, glomerular-filtration rate (GFR), and other laboratory parameters were measured at their initial evaluation and at the end of follow-up. Cerebrovascular risk factors, medications, and blood-pressure parameters were also reviewed. WMH progression rate was measured by subtracting WMH volume at baseline from that at the follow-up using volumetric analysis, divided by the MRI intervals. At baseline, WMH volume was 9.61±13.17 mL, mean GFR was 77.3±22.8 mL/min, and mean cystatin C level was 0.92±0.52 mg/L. After 37.9±3.4 months, the change in WMH volume was 3.64±6.85 mL, the progression rate of WMH volume was 1.18±2.28 mL/year, the mean ΔGFR was 2.4±7.9 mL/min, and the mean Δcystatin C was 0.03±0.34 mg/L. The progression rate of WMH volume was linearly associated with cystatin C level (B coefficient = 0.856; 95% confidence interval [CI] 0.174-1.538; P = 0.014), along with the baseline WMH volume (B = 0.039; 95% CI 0.019-0.059; P<0.001), after adjusting for the conventional vascular risk factors, laboratory parameters, medication profiles, and GFR. Especially, patients with a baseline level of cystatin C ≥1.00 mg/L exhibited a much higher progression rate of WMH as compared with those with a baseline level of cystatin C <1.00 mg/L (1.60±1.91 mL/year vs. 0.82±1.63 mL/year, P = 0.010). We concluded that serum cystatin C level is independently associated with the long-term progression rate of the cerebral WMH volume. Therefore, serum cystatin C level might predict the progression of cerebral WMH.

Lack of association of MRI determined subclinical cardiovascular disease with dizziness and vertigo in a cross-sectional population-based study.

We investigated the association between subclinical cardiovascular diseases assessed by MRI examination and symptoms of dizziness and vertigo in participants of a population-based sample.

Reproducibility of frequency-dependent low frequency fluctuations in reaction time over time and across tasks.

Increased levels of reaction time variability (RTV) are characteristics of sustained attention deficits. The clinical significance of RTV has been widely recognized. However, the reliability of RTV measurements has not been widely studied. The present study aimed to assess the test-retest reliability of RTV conventional measurements, e.g., the standard deviation (SD), the coefficient of variation (CV), and a new measurement called the amplitude of low frequency fluctuation (ALFF) of RT. In addition, we aimed to assess differences and similarities of these measurements between different tasks.

Correlations between clinical characteristics and neuroimaging in Chinese patients with subtypes of frontotemporal lobe degeneration.

The aim of the study was to obtain an overview of the clinical and neuroimaging features of Chinese patients with subtypes of frontotemporal lobe degeneration (FTLD).We evaluated the demographic features, clinical presentation, and lobe atrophy depicted by magnetic resonance imaging (MRI) in 133 patients with FTLD. Two positron emission tomography (PET) scans were performed at baseline: [C]Pittsburgh compound B PET to assess amyloid-β plaque load and [F]fluorodeoxyglucose (FDG) PET to assess glucose metabolism.The behavioral variant of FTD (bvFTD) was the most common subtype (67.7%) of FTLD. The percentages of progressive nonfluent aphasia (PNFA) and semantic dementia (SD) were similar. Cerebral lobe atrophy was seen in 87.7% of the cases. The Activities of Daily Living scale, Mini-Mental State Examination, and Montreal Cognitive Assessment scores were significantly correlated with the degree of overall atrophy. The severity of abnormal behavior was correlated with right anterior and right posterior temporal atrophy scores. The overall atrophy scores and atrophy score in the left temporal region were related to cognitive outcomes and Activities of Daily Living scores. Most of the bvFTD patients presented symmetric/asymmetric hypometabolism in the bilateral temporal cortex, frontal cortex, anterior cingulate cortex, insula, and caudate nucleus. All the PNFA patients presented left dominant hypometabolism in the frontal cortex. All the SD patients presented left dominant hypometabolism in the anterior temporal cortex.FTLD is not rare in cognitive clinics, and the ratios of subtypes in Chinese patients are similar to other ethnic groups. Overall atrophy scores, determined by MRI, were related to the severity of cognitive dysfunction and deficits in Activities of Daily Living. Patterns of hypometabolism, determined by [F]FDG PET, were more specific to subtypes of FTLD and may help provide differential diagnoses of variants of FTLD.

A Quarter-Century After Primary Direct Arterial Switch Operation: Four-D-Flow MRI Video Imaging of Blood Flow Dynamics Outcomes.

Four-dimensional (4-D) flow magnetic resonance imaging (MRI) examination was performed 25 years after a neonatal direct arterial switch operation for simple transposition of the great arteries. The 4-D flow MRI video shows physiological spiral anatomical configuration and laminar streamlines in the great arteries.

Prevalence and Prognostic Significance of Left Ventricular Noncompaction in Patients Referred for Cardiac Magnetic Resonance Imaging.

Presence of prominent left ventricular trabeculation satisfying criteria for left ventricular noncompaction (LVNC) on routine cardiac magnetic resonance examination is frequently encountered; however, the clinical and prognostic significance of these findings remain elusive. This registry aimed to assess LVNC prevalence by 4 current criteria and to prospectively evaluate an association between diagnosis of LVNC by these criteria and adverse events.

Distinct Patterns of Temporal and Directional Connectivity among Intrinsic Networks in the Human Brain.

To determine the spatiotemporal relationships among intrinsic networks of the human brain, we recruited seven neurosurgical patients (four males and three females) who were implanted with intracranial depth electrodes. We first identified canonical resting-state networks at the individual subject level using an iterative matching procedure on each subject's resting-state fMRI data. We then introduced single electrical pulses to fMRI pre-identified nodes of the default network (DN), frontoparietal network (FPN), and salience network (SN) while recording evoked responses in other recording sites within the same networks. We found bidirectional signal flow across the three networks, albeit with distinct patterns of evoked responses within different time windows. We used a data-driven clustering approach to show that stimulation of the FPN and SN evoked a rapid (<70 ms) response that was predominantly higher within the SN sites, whereas stimulation of the DN led to sustained responses in later time windows (85-200 ms). Stimulations in the medial temporal lobe components of the DN evoked relatively late effects (>130 ms) in other nodes of the DN, as well as FPN and SN. Our results provide temporal information about the patterns of signal flow between intrinsic networks that provide insights into the spatiotemporal dynamics that are likely to constrain the architecture of the brain networks supporting human cognition and behavior.SIGNIFICANCE STATEMENT Despite great progress in the functional neuroimaging of the human brain, we still do not know the precise set of rules that define the patterns of temporal organization between large-scale networks of the brain. In this study, we stimulated and then recorded electrical evoked potentials within and between three large-scale networks of the brain, the default network (DN), frontoparietal network (FPN), and salience network (SN), in seven subjects undergoing invasive neurosurgery. Using a data-driven clustering approach, we observed distinct temporal and directional patterns between the three networks, with FPN and SN activity predominant in early windows and DN stimulation affecting the network in later windows. These results provide important temporal information about the interactions between brain networks supporting human cognition and behavior.

The application of high-field magnetic resonance perfusion imaging in the diagnosis of pancreatic cancer.

Pancreatic cancer is the fourth leading cause of cancer death in the world. It is a disease of insidious progression and high lethality. The present study was to investigate the diagnostic value of high-filed magnetic resonance (MR) perfusion imaging in pancreatic cancer. Thirty-three patients with suspected pancreatic cancer were recruited in our study and underwent routine MR imaging. When compared with para-tumoral and normal tissue, the pancreatic lesions showed significant lower slope, peak enhancement (PE), and signal enhancement ratio (SER) as well as higher time to peak (TTP). Para-tumoral tissue was found to have significantly lower slope and PE, slightly higher TTP than normal tissue. MR perfusion imaging displays hemodynamic alterations in both pancreatic cancer and surrounding pancreatic tissue, and provides indirect assessment of tumor vascularity. In conclusion, high field MR perfusion imaging has important clinical significance in early diagnosis of pancreatic cancer.

Left Atrial Fibrosis and Risk of Cerebrovascular and Cardiovascular Events in Patients With Atrial Fibrillation.

Severity of left atrial (LA) fibrosis is a strong predictor of atrial fibrillation (AF) ablation success and has been associated with a history of stroke, hypertension, and heart failure (HF). However, it is unclear whether more severe LA fibrosis independently increases the risk of major adverse cardiovascular and cerebrovascular events (MACCE) among those with AF.

Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection.

Head motion can be estimated at any point of fMRI image processing. Processing steps involving temporal interpolation (e.g., slice time correction or outlier replacement) often precede motion estimation in the literature. From first principles it can be anticipated that temporal interpolation will alter head motion in a scan. Here we demonstrate this effect and its consequences in five large fMRI datasets. Estimated head motion was reduced by 10-50% or more following temporal interpolation, and reductions were often visible to the naked eye. Such reductions make the data seem to be of improved quality. Such reductions also degrade the sensitivity of analyses aimed at detecting motion-related artifact and can cause a dataset with artifact to falsely appear artifact-free. These reduced motion estimates will be particularly problematic for studies needing estimates of motion in time, such as studies of dynamics. Based on these findings, it is sensible to obtain motion estimates prior to any image processing (regardless of subsequent processing steps and the actual timing of motion correction procedures, which need not be changed). We also find that outlier replacement procedures change signals almost entirely during times of motion and therefore have notable similarities to motion-targeting censoring strategies (which withhold or replace signals entirely during times of motion).

Preparation of biogenic gas vesicle nanostructures for use as contrast agents for ultrasound and MRI.

Gas vesicles (GVs) are a unique class of gas-filled protein nanostructures that are detectable at subnanomolar concentrations and whose physical properties allow them to serve as highly sensitive imaging agents for ultrasound and MRI. Here we provide a protocol for isolating GVs from native and heterologous host organisms, functionalizing these nanostructures with moieties for targeting and fluorescence, characterizing their biophysical properties and imaging them using ultrasound and MRI. GVs can be isolated from natural cyanobacterial and haloarchaeal host organisms or from Escherichia coli expressing a heterologous GV gene cluster and purified using buoyancy-assisted techniques. They can then be modified by replacing surface-bound proteins with engineered, heterologously expressed variants or through chemical conjugation, resulting in altered mechanical, surface and targeting properties. Pressurized absorbance spectroscopy is used to characterize their mechanical properties, whereas dynamic light scattering (DLS)and transmission electron microscopy (TEM) are used to determine nanoparticle size and morphology, respectively. GVs can then be imaged with ultrasound in vitro and in vivo using pulse sequences optimized for their detection versus background. They can also be imaged with hyperpolarized xenon MRI using chemical exchange saturation transfer between GV-bound and dissolved xenon-a technique currently implemented in vitro. Taking 3-8 d to prepare, these genetically encodable nanostructures enable multimodal, noninvasive biological imaging with high sensitivity and potential for molecular targeting.

Challenging Occam's Razor: An Unusual Combination of Sarcoidosis and Amyloidosis. The Value of Cardiac Magnetic Resonance Imaging in Infiltrative Cardiomyopathies.

We describe the case of a 66-year old woman with the extremely rare combination of sarcoidosis and amyloidosis (light chain) and the important role of cardiovascular magnetic resonance imaging to differentiate between these 2 infiltrative diseases. Myocardial characterization with T1 mapping can improve disease detection, especially in overlap cases, and possibly obviate the need for cardiac biopsy.

High resolution imaging of the mitral valve in the natural state with 7 Tesla MRI.

Imaging techniques of the mitral valve have improved tremendously during the last decade, but challenges persist. The delicate changes in annulus shape and papillary muscle position throughout the cardiac cycle have significant impact on the stress distribution in the leaflets and chords, thus preservation of anatomically accurate positioning is critical. The aim of this study was to develop an in vitro method and apparatus for obtaining high-resolution 3D MRI images of porcine mitral valves in both the diastolic and systolic configurations with physiologically appropriate annular shape, papillary muscle positions and orientations, specific to the heart from which the valve was harvested. Positioning and mounting was achieved through novel, customized mounting hardware consisting of papillary muscle and annulus holders with geometries determined via pre-mortem ultrasonic intra-valve measurements. A semi-automatic process was developed and employed to tailor Computer Aided Design models of the holders used to mount the valve. All valve mounting hardware was 3D printed using a stereolithographic printer, and the material of all fasteners used were brass for MRI compatibility. The mounted valves were placed within a clear acrylic case, capable of holding a zero-pressure and pressurized liquid bath of a MRI-compatible fluid. Obtaining images from the valve submerged in liquid fluid mimics the natural environment surrounding the valve, avoiding artefacts due to tissue surface tension mismatch and gravitational impact on tissue shape when not neutrally buoyant. Fluid pressure was supplied by reservoirs held at differing elevations and monitored and controlled to within ±1mmHg to ensure that the valves remained steady. The valves were scanned in a 7 Tesla MRI system providing a voxel resolution of at least 80μm. The systematic approach produced 3D datasets of high quality which, when combined with physiologically accurate positioning by the apparatus, can serve as an important input for validated computational models.

Brain MR image segmentation based on an improved active contour model.

It is often a difficult task to accurately segment brain magnetic resonance (MR) images with intensity in-homogeneity and noise. This paper introduces a novel level set method for simultaneous brain MR image segmentation and intensity inhomogeneity correction. To reduce the effect of noise, novel anisotropic spatial information, which can preserve more details of edges and corners, is proposed by incorporating the inner relationships among the neighbor pixels. Then the proposed energy function uses the multivariate Student's t-distribution to fit the distribution of the intensities of each tissue. Furthermore, the proposed model utilizes Hidden Markov random fields to model the spatial correlation between neigh-boring pixels/voxels. The means of the multivariate Student's t-distribution can be adaptively estimated by multiplying a bias field to reduce the effect of intensity inhomogeneity. In the end, we reconstructed the energy function to be convex and calculated it by using the Split Bregman method, which allows our framework for random initialization, thereby allowing fully automated applications. Our method can obtain the final result in less than 1 second for 2D image with size 256 × 256 and less than 300 seconds for 3D image with size 256 × 256 × 171. The proposed method was compared to other state-of-the-art segmentation methods using both synthetic and clinical brain MR images and increased the accuracies of the results more than 3%.

A urinary biomarker-based risk score correlates with multiparametric MRI for prostate cancer detection.

Prostate cancer (PCa) diagnostics would greatly benefit from more accurate, non-invasive techniques for the detection of clinically significant disease, leading to a reduction of over-diagnosis and over-treatment. The aim of this study was to determine the association between a novel urinary biomarker-based risk score (SelectMDx), multiparametric MRI (mpMRI) outcomes, and biopsy results for PCa detection.

Novel Index of Maladaptive Myocardial Remodeling in Hypertension.

Hypertensive left ventricular hypertrophy (HTN-LVH) is a leading cause of heart failure. Conventional patterns of cardiac geometry do not adequately risk-stratify patients with HTN-LVH. Using cardiovascular magnetic resonance, we developed a novel Remodeling Index (RI) that was designed to detect an exaggerated hypertrophic response to hypertension and tested its potential to risk-stratify hypertensive patients.

Diffusion-weighted imaging in gynaecological malignancy.

Diffusion weighted imaging (DWI) has become an essential part of the gynaecological magnetic resonance imaging (MRI) protocol. DWI is used as an adjunct to conventional MRI sequences and has been shown to improve reporting accuracy in the imaging of gynaecological malignancy. In this review, we discuss the role of DWI in the diagnosis, staging, and assessment of treatment response of endometrial, cervical, and ovarian cancer. We also review the role of DWI in the assessment of the sonographically indeterminate ovarian lesion. Further, we highlight potential pitfalls that can beset the accurate interpretation of DWI in patients with gynaecological malignancy.

Noise correlations in the human brain and their impact on pattern classification.

Multivariate decoding methods, such as multivoxel pattern analysis (MVPA), are highly effective at extracting information from brain imaging data. Yet, the precise nature of the information that MVPA draws upon remains controversial. Most current theories emphasize the enhanced sensitivity imparted by aggregating across voxels that have mixed and weak selectivity. However, beyond the selectivity of individual voxels, neural variability is correlated across voxels, and such noise correlations may contribute importantly to accurate decoding. Indeed, a recent computational theory proposed that noise correlations enhance multivariate decoding from heterogeneous neural populations. Here we extend this theory from the scale of neurons to functional magnetic resonance imaging (fMRI) and show that noise correlations between heterogeneous populations of voxels (i.e., voxels selective for different stimulus variables) contribute to the success of MVPA. Specifically, decoding performance is enhanced when voxels with high vs. low noise correlations (measured during rest or in the background of the task) are selected during classifier training. Conversely, voxels that are strongly selective for one class in a GLM or that receive high classification weights in MVPA tend to exhibit high noise correlations with voxels selective for the other class being discriminated against. Furthermore, we use simulations to show that this is a general property of fMRI data and that selectivity and noise correlations can have distinguishable influences on decoding. Taken together, our findings demonstrate that if there is signal in the data, the resulting above-chance classification accuracy is modulated by the magnitude of noise correlations.