Error quantification in multi-parameter mapping facilitates robust estimation and enhanced group level sensitivity

Multi-Parameter Mapping (MPM) is a comprehensive quantitative neuroimaging protocol that enables estimation of four physical parameters (longitudinal and effective transverse relaxation rates R1 and R2*, proton density PD, and magnetization transfer saturation MTsat) that are sensitive to microstructural tissue properties such as iron and myelin content. Their capability to reveal microstructural brain differences, however, is tightly bound to controlling random noise and artefacts (e.g. caused by head motion) in the signal. Here, we introduced a method to estimate the local error of PD, R1, and MTsat maps that captures both noise and artefacts on a routine basis without requiring additional data. To investigate the method's sensitivity to random noise, we calculated the model-based signal-to-noise ratio (mSNR) and showed in measurements and simulations that it correlated linearly with an experimental raw-image-based SNR map. We found that the mSNR varied with MPM protocols, magnetic field strength (3T vs. 7T) and MPM parameters: it halved from PD to R1 and decreased from PD to MT_sat by a factor of 3-4. Exploring the artefact-sensitivity of the error maps, we generated robust MPM parameters using two successive acquisitions of each contrast and the acquisition-specific errors to down-weight erroneous regions. The resulting robust MPM parameters showed reduced variability at the group level as compared to their single-repeat or averaged counterparts. The error and mSNR maps may better inform power-calculations by accounting for local data quality variations across measurements. Code to compute the mSNR maps and robustly combined MPM maps is available in the open-source hMRI toolbox.

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Polarization analysis of high-frequency, three-component seismic data

Bulletin of the Seismological Society of America ◽

10.1785/bssa0810020622 ◽

1991 ◽

Vol 81 (2) ◽

pp. 622-642

Author(s):

K. Bataille ◽

J. M. Chiu

Keyword(s):

High Frequency ◽

Time Windows ◽

Random Noise ◽

Polarization State ◽

Principal Component ◽

Small Time ◽

Body Waves ◽

Local Data ◽

Principal Component Approach ◽

Component Approach

Abstract We present a method to determine the polarization of body waves from three-component, high-frequency data and examples of its application. The method is based on the principal component approach. One advantage of this approach is that the polarization state can be determined for small time windows compared with the predominant period of the wave. This is particularly useful for identifying converted waves within the crust. The stability of the result is analyzed with synthetic cases by adding simultaneous arrivals from waves and random noise. The method works well with both synthetic and local data in the detection of the polarization of the wave by separating arrivals from different directions. From the local data, some seismic phases related to crustal conversions are observed that require strong lateral variations.

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A finite element model for predicting the distribution of drugs delivered intracranially to the brain

AJP Regulatory Integrative and Comparative Physiology ◽

10.1152/ajpregu.1997.273.5.r1810 ◽

1997 ◽

Vol 273 (5) ◽

pp. R1810-R1821 ◽

Cited By ~ 25

Author(s):

S. Kalyanasundaram ◽

V. D. Calhoun ◽

K. W. Leong

Keyword(s):

Drug Delivery ◽

Finite Element ◽

Spin Echo ◽

Interleukin 2 ◽

Chemical Species ◽

Transport Processes ◽

Proton Density ◽

Clear Understanding ◽

Tissue Properties ◽

The Brain

Drug therapy to the central nervous system is complicated by the presence of the blood-brain barrier. The development of new drug delivery techniques to overcome this obstacle will be aided by a clear understanding of the transport processes in the brain. A rigorous theoretical framework of the transport of drugs delivered locally to the parenchyma has been developed using the finite element method. Magnetic resonance imaging has been used to track the transport of paramagnetic contrast markers in the brain. The information obtained by postprocessing spin-echo, T1-weighted, and proton density images has been used to refine the mathematical model that includes realistic brain geometry and salient anatomic features and allows for two-dimensional transport of chemical species, including both diffusive and convective contributions. In addition, the effects of regional differences in tissue properties, ventricular boundary, and edema on the transport have been considered. The model has been used to predict transport of interleukin-2 in the brain and study the major determinants of transport, at both early and late times after drug delivery.

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The Spatial Dimension of COVID-19: The Potential of Earth Observation Data in Support of Slum Communities with Evidence from Brazil

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9090557 ◽

2020 ◽

Vol 9 (9) ◽

pp. 557 ◽

Cited By ~ 1

Author(s):

Patricia Lustosa Brito ◽

Monika Kuffer ◽

Mila Koeva ◽

Julio Cesar Pedrassoli ◽

Jiong Wang ◽

...

Keyword(s):

Data Gathering ◽

Spatial Dimension ◽

Vital Role ◽

Earth Observation ◽

Physical Parameters ◽

Observation Data ◽

Local Data ◽

Middle Income ◽

Earth Observation Data ◽

Poor Communities

The COVID-19 health emergency is impacting all of our lives, but the living conditions and urban morphologies found in poor communities make inhabitants more vulnerable to the COVID-19 outbreak as compared to the formal city, where inhabitants have the resources to follow WHO guidelines. In general, municipal spatial datasets are not well equipped to support spatial responses to health emergencies, particularly in poor communities. In such critical situations, Earth observation (EO) data can play a vital role in timely decision making and can save many people’s lives. This work provides an overview of the potential of EO-based global and local datasets, as well as local data gathering procedures (e.g., drones), in support of COVID-19 responses by referring to two slum areas in Salvador, Brazil as a case study. We discuss the role of datasets as well as data gaps that hinder COVID-19 responses. In Salvador and other low- and middle-income countries’ (LMICs) cities, local data are available; however, they are not up to date. For example, depending on the source, the population of the study areas in 2020 varies by more than 20%. Thus, EO data integration can help in updating local datasets and in the acquisition of physical parameters of poor urban communities, which are often not systematically collected in local surveys.

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Nuclear magnetic resonance (NMR) micro-imaging of stems of Linum usitatissimum

The Journal of Agricultural Science ◽

10.1017/s0021859600014064 ◽

1992 ◽

Vol 119 (2) ◽

pp. 157-164 ◽

Cited By ~ 5

Author(s):

G. J. McDougall ◽

B. A. Goodman ◽

J. A. Chudek

Keyword(s):

Nuclear Magnetic Resonance ◽

Magnetic Resonance ◽

Linum Usitatissimum ◽

Structural Information ◽

Paramagnetic Species ◽

Proton Density ◽

Relaxation Rates ◽

Histological Techniques ◽

Advantages And Disadvantages ◽

Nuclear Magnetic

SUMMARYNuclear magnetic resonance (NMR) micro-imaging techniques have been employed to study noninvasively the spatial distribution of mobile protons (1H) around the cotyledonary node of flax (Linum usitatissimum) plants of two differing growth morphologies. The gross anatomy of the tissues of the stem can be discerned as a result of differences in their mobile 1H contents. The technique produced excellent images of the complex changes in stem structure that occur at the point of origin of side shoots. Detailed structure within the xylem could be visualized and the presence of fibre bundles deduced as dark areas amongst tissues of higher 1H signal intensity.As a result of the non-invasive and non-destructive nature of NMR-imaging, the images obtained have been compared to micrographs obtained by conventional histological techniques on the same plant tissue. In general, the two approaches produce comparable results, but the NMR images are influenced by the relaxation properties of the protons as well as their concentration. Paramagnetic species, such as Mn2+ ions, produce enhanced relaxation rates of protons in their vicinity and an apparent increase in proton density at short recycle times. Thus an NMR image can yield both chemical and structural information. Some of the advantages and disadvantages of this technique over conventional histological methods are discussed.

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Estimation of the macromolecular proton fraction and bound pool T2 in multiple sclerosis

Multiple Sclerosis Journal ◽

10.1191/1352458504ms1105oa ◽

2004 ◽

Vol 10 (6) ◽

pp. 607-613 ◽

Cited By ~ 37

Author(s):

Davies GR ◽

Tozer DJ ◽

Cercignani M ◽

Ramani A ◽

Dalton CM ◽

...

Keyword(s):

Multiple Sclerosis ◽

Spin Echo ◽

Magnetization Transfer ◽

Time Estimation ◽

Fast Spin Echo ◽

Proton Density ◽

Normal Appearing White Matter ◽

Spin Echo Sequence ◽

Fast Spin Echo Sequence ◽

Weighted Sequences

This study used a model for magnetization transfer (MT) to estimate two underlying parameters: the macromolecular proton fraction (f) and the bound pool T2 (T2b) in patients with multiple sclerosis (MS). Sixty patients with clinically definite MS and 27 healthy controls were imaged using: (1) a dual echo fast spin echo sequence, (2) a MT sequence (with ten MT power and offset frequency combinations) and (3) proton density and T1 weighted sequences (for T1 relaxation time estimation). Fourteen normal-appearing white matter (NAWM) regions of interest (ROI) and six normal-appearing gray matter (NAGM) ROIs were outlined in all subjects. Lesions were also contoured in subjects affected by MS. The model was fitted to the data leading to estimates of T2b and f. Results showed that T2b was increased in lesions whereas f was reduced. In NAWM, f was decreased while T2b was only increased in secondary progressive MS. NAWM f correlated modestly with disability. Further studies are needed to investigate the pathological basis of the abnormalities observed.

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The Prognostic Value of White-Matter Selective Double Inversion Recovery MRI Sequence in Multiple Sclerosis: An Exploratory Study

Diagnostics ◽

10.3390/diagnostics11040686 ◽

2021 ◽

Vol 11 (4) ◽

pp. 686

Author(s):

Francesco Crescenzo ◽

Damiano Marastoni ◽

Anna Isabella Pisani ◽

Agnese Tamanti ◽

Caterina Dapor ◽

...

Keyword(s):

Multiple Sclerosis ◽

White Matter ◽

Magnetization Transfer ◽

Inversion Recovery ◽

Double Inversion Recovery ◽

Magnetization Transfer Ratio ◽

Tissue Properties ◽

Relapsing Remitting ◽

3.0 T

Using a white-matter selective double inversion recovery sequence (WM-DIR) that suppresses both grey matter (GM) and cerebrospinal fluid (CSF) signals, some white matter (WM) lesions appear surrounded by a dark rim. These dark rim lesions (DRLs) seem to be specific for multiple sclerosis (MS). They could be of great usefulness in clinical practice, proving to increase the MRI diagnostic criteria specificity. The aims of this study are the identification of DRLs on 1.5 T MRI, the exploration of the relationship between DRLs and disease course, the characterization of DRLs with respect to perilesional normal-appearing WM using magnetization transfer imaging, and the investigation of possible differences in the underlying tissue properties by assessing WM-DIR images obtained at 3.0 T MRI. DRLs are frequent in primary progressive MS (PPMS) patients. Amongst relapsing-remitting MS (RRMS) patients, DRLs are associated with a high risk of the disease worsening and secondary progressive MS (SPMS) conversion after 15 years. The mean magnetization transfer ratio (MTR) of DRLs is significantly different from the lesion without the dark rim, suggesting that DRLs correspond to more destructive lesions.

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A Phantom System Designed to Assess the Effects of Membrane Lipids on Water Proton Relaxation

10.1101/387845 ◽

2018 ◽

Cited By ~ 1

Author(s):

Oshrat Shtangel ◽

Aviv A. Mezer

Keyword(s):

Membrane Lipids ◽

Magnetization Transfer ◽

Membrane Lipid ◽

Water Proton ◽

Proton Relaxation ◽

Proton Density ◽

Brain Lipids ◽

Water Fraction ◽

Lipid Environment

AbstractPurposeQuantitative magnetic resonance imaging (qMRI) provides a method for the non-invasive study of brain structure and associated changes, expressed in physical units. qMRI parameters have been shown to reflect brain tissue composition such as myelin. Nevertheless, it remains a major challenge to identify and quantify the contributions of specific molecular components to the MRI signal. Here, we describe a phantom system that can be used to evaluate the contribution of human brain lipids to qMRI parameters.MethodsA thin layer evaporation-hydration technique was used to formulate liposomes that mimic the physiological bi-layered membrane lipid environment. We then applied quantitative clinical MRI techniques with adjusted bias corrections in order to test the ability of the phantom system to estimate multiple qMRI parameters such as proton density (PD), T1, T2, T2* and magnetization transfer (MT).ResultsThe results indicated that phantoms composed of various lipids could provide a stable and reliable estimation of qMRI parameters. In addition, the calculated water fraction (WF) maps for the phantoms were found to accurately represent the true WF volumes.ConclusionWe have successfully created a biologically relevant liposome phantom system whose lipid composition can be fully controlled. This system can be used to measure the contributions of lipids to qMRI parameters under conditions that are relevant to in-vivo human scans.

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Combining Navigator and Optical Prospective Motion Correction for High-Quality 500 μm Resolution Quantitative Multi-Parameter Mapping at 7T

10.1101/2021.10.26.21265506 ◽

2021 ◽

Author(s):

Lenka Vaculčiaková ◽

Kornelius Podranski ◽

Luke J. Edwards ◽

Dilek Ocal ◽

Thomas Veale ◽

...

Keyword(s):

Relaxation Rate ◽

Motion Correction ◽

The Elderly ◽

Proton Density ◽

Young Cohort ◽

Transverse Relaxation Rate ◽

Spatial Homogeneity ◽

Parameter Mapping ◽

Dementia Patients ◽

Elderly Cohort

AbstractPURPOSEHigh-resolution quantitative multi-parameter mapping shows promise for non-invasively characterizing human brain microstructure but is limited by physiological artifacts. We implemented corrections for rigid head movement and respiration-related B0-fluctuations and evaluated them in healthy volunteers and dementia patients.METHODSCamera-based optical prospective motion correction (PMC) and free-induction decay (FID) navigator correction were implemented in a gradient and RF-spoiled multi-echo 3D gradient echo sequence for mapping proton density (PD), longitudinal relaxation rate (R1) and effective transverse relaxation rate (R2*). We studied their effectiveness separately and in concert in young volunteers and then evaluated the navigator correction (NAVcor) with PMC in a group of elderly volunteers and dementia patients. We used spatial homogeneity within white matter (WM) and gray matter (GM) and scan-rescan measures as quality metrics.RESULTSNAVcor and PMC reduced artifacts and improved the homogeneity and reproducibility of parameter maps. In elderly participants, NAVcor improved scan-rescan reproducibility of parameter maps (coefficient of variation decreased by 14.7% and 11.9% within WM and GM respectively). Spurious inhomogeneities within WM were reduced more in the elderly than in the young cohort (by 9% vs 2%). PMC increased regional GM/WM contrast and was especially important in the elderly cohort, which moved twice as much as the young cohort. We did not find a significant interaction between the two corrections.CONCLUSIONNavigator correction and PMC significantly improved the quality of PD, R1 and R2* maps, particularly in less compliant elderly volunteers and dementia patients.

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