Neuroharmony: A new tool for harmonizing volumetric MRI data from unseen scanners.
Ontology highlight
ABSTRACT:
SUBMITTER: Garcia-Dias R
PROVIDER: S-EPMC7573655 | biostudies-literature | 2020 Oct
REPOSITORIES: biostudies-literature
Publications
Neuroharmony: A new tool for harmonizing volumetric MRI data from unseen scanners.
Garcia-Dias Rafael R Scarpazza Cristina C Baecker Lea L Vieira Sandra S Pinaya Walter H L WHL Corvin Aiden A Redolfi Alberto A Nelson Barnaby B Crespo-Facorro Benedicto B McDonald Colm C Tordesillas-Gutiérrez Diana D Cannon Dara D Mothersill David D Hernaus Dennis D Morris Derek D Setien-Suero Esther E Donohoe Gary G Frisoni Giovanni G Frisoni Giovanni G Tronchin Giulia G Sato João J Marcelis Machteld M Kempton Matthew M van Haren Neeltje E M NEM Gruber Oliver O McGorry Patrick P Amminger Paul P McGuire Philip P Gong Qiyong Q Kahn René S RS Ayesa-Arriola Rosa R van Amelsvoort Therese T Ortiz-García de la Foz Victor V Calhoun Vince V Cahn Wiepke W Mechelli Andrea A
NeuroImage 20200704
Similar Datasets
Project description:Large diffusion-weighted brain MRI (dMRI) studies in neonates are crucial for developmental neuroscience. Our aim was to investigate the utility of ComBat, an empirical Bayes tool for multisite harmonization, in removing site effects from white matter (WM) dMRI measures in healthy infants born at 37 gestational weeks+ 0 days-42 weeks+ 6 days from the Theirworld Edinburgh Birth Cohort (n = 86) and Developing Human Connectome Project (n = 287). Skeletonized fractional anisotropy (FA), mean, axial and radial diffusivity (MD, AD, RD) maps were harmonized. Differences between voxel-wise metrics, skeleton means and histogram widths (5th-95th percentile) were assessed before and after harmonization, as well as variance associated with gestational age at birth and scan. Before harmonization, large cohort differences were observed. Harmonization removed all voxel-wise differences from MD maps and all metric means and histogram widths, however small voxel-wise differences (<1.5 % of voxels) remained in FA, AD and RD. We detected significant relationships between GA at birth and all metrics. When comparing single site and multisite harmonized datasets of equal sample sizes, harmonized data resulted in smaller standardized regression coefficients. ComBat could enable unprecedented sample sizes in developmental neuroscience, offering new horizons for biomarker discovery and validation, understanding typical and atypical brain development, and assessing neuroprotective therapies.
| S-EPMC11683243 | biostudies-literature
Project description:Recent methodological advances in MRI have enabled substantial growth in neuroimaging studies of non-human primates (NHPs), while open data-sharing through the PRIME-DE initiative has increased the availability of NHP MRI data and the need for robust multi-subject multi-center analyses. Streamlined acquisition and analysis protocols would accelerate and improve these efforts. However, consensus on minimal standards for data acquisition protocols and analysis pipelines for NHP imaging remains to be established, particularly for multi-center studies. Here, we draw parallels between NHP and human neuroimaging and provide minimal guidelines for harmonizing and standardizing data acquisition. We advocate robust translation of widely used open-access toolkits that are well established for analyzing human data. We also encourage the use of validated, automated pre-processing tools for analyzing NHP data sets. These guidelines aim to refine methodological and analytical strategies for small and large-scale NHP neuroimaging data. This will improve reproducibility of results, and accelerate the convergence between NHP and human neuroimaging strategies which will ultimately benefit fundamental and translational brain science.
| S-EPMC8594288 | biostudies-literature
Project description:ObjectiveMetachromatic leukodystrophy (MLD) is an inherited lysosomal disorder due to a deficiency in arylsulfatase A with progressive demyelination and neurological decline. This retrospective MRI study investigated the extent of cortical involvement at time of diagnosis, and clinical correlates to both conventional and regional volumetric measures of brain involvement.Methods3D-T1-weighted MRI scans were used to determine cortical thickness and surface-based cerebral cortical gray matter (GM) and cerebral white matter (WM) volume (GMV and WMV), WM lesions, thalamus, and cerebellum. MRI-MLD severity scores were obtained from FLAIR images. Associations between clinical and imaging data were examined using correlation coefficients.ResultsTwenty patients with MLD (mean age 13.7 years, range 2-35) and 20 controls (mean age 13.9 years, range 2-40) were included. Compared with control subjects, late-infantile, and juvenile patients (n = 14) had significantly diminished cerebral cortical GMV and thalamus volume (P < 0.05), but did not differ in WMV and cortical thickness. Adult patients (n = 6) showed significantly reduced GMV, WMV and cortical thickness (all P < 0.05). Regional analysis showed statistically significant cortical thinning in the cingulate gyrus and most pronounced thinning with age in the frontal lobe of MLD patients. Intelligence quotient (IQ) correlated with MRI-MLD scores (r = -0.87, P < 0.001).InterpretationSignificant cerebral cortical GMV loss is already present in early stages of MLD. IQ correlates with WM severity scores and lesion volume, but not with volumetric measures. In adult presentations, there is more pronounced global atrophy with GMV and WMV loss and accelerated cortical thinning, most prominently in the cingulate gyrus and frontal lobes.
| S-EPMC4574810 | biostudies-literature
Project description:Cerebrovascular reactivity (CVR) is defined as the ratio of the cerebral blood flow (CBF) response to an increase in a vasoactive stimulus. We used changes in blood oxygenation level-dependent (BOLD) MRI as surrogates for changes of CBF, and standardized quantitative changes in arterial partial pressure of carbon dioxide as the stimulus. Despite uniform stimulus and test conditions, differences in voxel-wise BOLD changes between testing sites may remain, attributable to physiologic and machine variability. We generated a reference atlas of normal CVR metrics (voxel-wise mean and SD) for each of two sites. We hypothesized that there would be no significant differences in CVR between the two atlases enabling each atlas to be used at any site. A total of 69 healthy subjects were tested to create site-specific atlases, with 20 of those individuals tested at both sites. 38 subjects were scanned at Site 1 (17F, 37.5 ± 16.8 y) and 51 subjects were tested at Site 2 (22F, 40.9 ± 17.4 y). MRI platforms were: Site 1, 3T Magnetom Skyra Siemens scanner with 20-channel head and neck coil; and Site 2, 3T HDx Signa GE scanner with 8-channel head coil. To construct the atlases, test results of individual subjects were co-registered into a standard space and voxel-wise mean and SD CVR metrics were calculated. Map comparisons of z scores found no significant differences between white matter or gray matter in the 20 subjects scanned at both sites when analyzed with either atlas. We conclude that individual CVR testing, and atlas generation are compatible across sites provided that standardized respiratory stimuli and BOLD MRI scan parameters are used. This enables the use of a single atlas to score the normality of CVR metrics across multiple sites.
| S-EPMC8134667 | biostudies-literature
Project description:Volumetric layouts of data are becoming increasingly common in a number of fields. Visualizing these data often requires downloading a large suite of dedicated tools with a significant learning curve. This process can be overwhelming for students or new researchers looking to quickly visualize and showcase a volumetric dataset. QuickVol was developed as a system to allow for rapid viewing of volumetric data without requiring extra setup. Built on WebGL, our system can run on any modern web browser, including mobile browsers, and can work completely offline. Additionally, an experimental immersive hand-tracking feature is included, which allows for hands-free manipulation of the imported volume, along with a showcase mode for viewing with a virtual reality headset.
| S-EPMC11635019 | biostudies-literature
Project description:The use of multicentric data is becoming essential for developing generalizable radiomic signatures. In particular, Magnetic Resonance Imaging (MRI) data used in brain oncology are often heterogeneous in terms of scanners and acquisitions, which significantly impact quantitative radiomic features. Various methods have been proposed to decrease dependency, including methods acting directly on MR images, i.e., based on the application of several preprocessing steps before feature extraction or the ComBat method, which harmonizes radiomic features themselves. The ComBat method used for radiomics may be misleading and presents some limitations, such as the need to know the labels associated with the "batch effect". In addition, a statistically representative sample is required and the applicability of a signature whose batch label is not present in the train set is not possible. This work aimed to compare a priori and a posteriori radiomic harmonization methods and propose a code adaptation to be machine learning compatible. Furthermore, we have developed AutoComBat, which aims to automatically determine the batch labels, using either MRI metadata or quality metrics as inputs of the proposed constrained clustering. A heterogeneous dataset consisting of high and low-grade gliomas coming from eight different centers was considered. The different methods were compared based on their ability to decrease relative standard deviation of radiomic features extracted from white matter and on their performance on a classification task using different machine learning models. ComBat and AutoComBat using image-derived quality metrics as inputs for batch assignment and preprocessing methods presented promising results on white matter harmonization, but with no clear consensus for all MR images. Preprocessing showed the best results on the T1w-gd images for the grading task. For T2w-flair, AutoComBat, using either metadata plus quality metrics or metadata alone as inputs, performs better than the conventional ComBat, highlighting its potential for data harmonization. Our results are MRI weighting, feature class and task dependent and require further investigations on other datasets.
| S-EPMC9325761 | biostudies-literature
Project description:Neurodevelopment continues through adolescence, with notable maturation of white matter tracts comprising regional fiber systems progressing at different rates. To identify factors that could contribute to regional differences in white matter microstructure development, large samples of youth spanning adolescence to young adulthood are essential to parse these factors. Recruitment of adequate samples generally relies on multi-site consortia but comes with the challenge of merging data acquired on different platforms. In the current study, diffusion tensor imaging (DTI) data were acquired on GE and Siemens systems through the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA), a multi-site study designed to track the trajectories of regional brain development during a time of high risk for initiating alcohol consumption. This cross-sectional analysis reports baseline Tract-Based Spatial Statistic (TBSS) of regional fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (L1), and radial diffusivity (LT) from the five consortium sites on 671 adolescents who met no/low alcohol or drug consumption criteria and 132 adolescents with a history of exceeding consumption criteria. Harmonization of DTI metrics across manufacturers entailed the use of human-phantom data, acquired multiple times on each of three non-NCANDA participants at each site's MR system, to determine a manufacturer-specific correction factor. Application of the correction factor derived from human phantom data measured on MR systems from different manufacturers reduced the standard deviation of the DTI metrics for FA by almost a half, enabling harmonization of data that would have otherwise carried systematic error. Permutation testing supported the hypothesis of higher FA and lower diffusivity measures in older adolescents and indicated that, overall, the FA, MD, and L1 of the boys were higher than those of the girls, suggesting continued microstructural development notable in the boys. The contribution of demographic and clinical differences to DTI metrics was assessed with General Additive Models (GAM) testing for age, sex, and ethnicity differences in regional skeleton mean values. The results supported the primary study hypothesis that FA skeleton mean values in the no/low-drinking group were highest at different ages. When differences in intracranial volume were covaried, FA skeleton mean reached a maximum at younger ages in girls than boys and varied in magnitude with ethnicity. Our results, however, did not support the hypothesis that youth who exceeded exposure criteria would have lower FA or higher diffusivity measures than the no/low-drinking group; detecting the effects of excessive alcohol consumption during adolescence on DTI metrics may require longitudinal study.
| S-EPMC4808415 | biostudies-literature
Project description:PurposeThe analysis of diffusion data obtained under large gradient nonlinearities necessitates corrections during data reconstruction and analysis. While two such preprocessing pipelines have been proposed, no comparative studies assessing their performance exist. Furthermore, both pipelines neglect the impact of subject motion during acquisition, which, in the presence of gradient nonlinearities, induces spatio-temporal B-matrix variations. Here, spatio-temporal B-matrix tracking (STB) is proposed and its performance compared to established pipelines.MethodsDiffusion tensor MRI (DT-MRI) was performed using a 300 mT/m gradient system. Data were acquired with volunteers positioned in regions with pronounced gradient nonlinearities, and used to compare the performance of six different processing pipelines, including STB.ResultsUp to 30% errors were observed in DT-MRI parameter estimates when neglecting gradient nonlinearities. Moreover, the order in which B0 inhomogeneity, eddy current and gradient nonlinearity corrections were performed was found to impact the consistency of parameter estimates significantly. Although, no pipeline emerged as a clear winner, the STB approach seemed to yield the most consistent parameter estimates under large gradient nonlinearities.ConclusionsUnder large gradient nonlinearities, the choice of preprocessing pipeline significantly impacts the estimated diffusion parameters. Motion-induced spatio-temporal B-matrix variations can lead to systematic bias in the parameter estimates, that can be ameliorated using the proposed STB framework.
| S-EPMC8103165 | biostudies-literature
Project description:BackgroundNeuroimaging data from large epidemiologic cohort studies often come from multiple scanners. The variations of MRI measurements due to differences in magnetic field strength, image acquisition protocols, and scanner vendors can influence the interpretation of aggregated data. The purpose of the present study was to compare methods that meta-analyze findings from a small number of different MRI scanners.MethodsWe proposed a bootstrap resampling method using individual participant data and compared it with two common random effects meta-analysis methods, DerSimonian-Laird and Hartung-Knapp, and a conventional pooling method that combines MRI data from different scanners. We first performed simulations to compare the power and coverage probabilities of the four methods in the absence and presence of scanner effects on measurements. We then examined the association of age with white matter hyperintensity (WMH) volumes from 787 participants.ResultsIn simulations, the bootstrap approach performed better than the other three methods in terms of coverage probability and power when scanner differences were present. However, the bootstrap approach was consistent with pooling, the optimal approach, when scanner differences were absent. In the association of age with WMH volume, we observed that age was significantly associated with WMH volumes using the bootstrap approach, pooling, and the DerSimonian-Laird method, but not using the Hartung-Knapp method (p < 0.0001 for the bootstrap approach, DerSimonian-Laird, and pooling but p = 0.1439 for the Hartung-Knapp approach).ConclusionThe bootstrap approach using individual participant data is suitable for integrating outcomes from multiple MRI scanners regardless of absence or presence of scanner effects on measurements.
| S-EPMC8324567 | biostudies-literature
Project description:The monitoring and management of radio frequency (RF) exposure is critical for ensuring magnetic resonance imaging (MRI) safety. Commercial MRI scanners can overestimate specific absorption rates (SAR) and improperly restrict clinical MRI scans or the application of new MRI sequences, while underestimation of SAR can lead to tissue heating and thermal injury. Accurate scanner-independent RF dosimetry is essential for measuring actual exposure when SAR is critical for ensuring regulatory compliance and MRI safety, for establishing RF exposure while evaluating interventional leads and devices, and for routine MRI quality assessment by medical physicists. However, at present there are no scanner-independent SAR dosimeters.An SAR dosimeter with an RF transducer comprises two orthogonal, rectangular copper loops and a spherical MRI phantom. The transducer is placed in the magnet bore and calibrated to approximate the resistive loading of the scanner's whole-body birdcage RF coil for human subjects in Philips, GE and Siemens 3 tesla (3T) MRI scanners. The transducer loop reactances are adjusted to minimize interference with the transmit RF field (B1) at the MRI frequency. Power from the RF transducer is sampled with a high dynamic range power monitor and recorded on a computer. The deposited power is calibrated and tested on eight different MRI scanners. Whole-body absorbed power vs weight and body mass index (BMI) is measured directly on 26 subjects.A single linear calibration curve sufficed for RF dosimetry at 127.8 MHz on three different Philips and three GE 3T MRI scanners. An RF dosimeter operating at 123.2 MHz on two Siemens 3T scanners required a separate transducer and a slightly different calibration curve. Measurement accuracy was ∼3%. With the torso landmarked at the xiphoid, human adult whole-body absorbed power varied approximately linearly with patient weight and BMI. This indicates that whole-body torso SAR is on average independent of the imaging subject, albeit with fluctuations.Our 3T RF dosimeter and transducers accurately measure RF exposure in body-equivalent loads and provide scanner-independent assessments of whole-body RF power deposition for establishing safety compliance useful for MRI sequence and device testing.
| S-EPMC3843752 | biostudies-other