"MASSIVE" Brain Dataset: Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation

PURPOSE: In this work, we present the MASSIVE (Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation) brain dataset of a single healthy subject, which is intended to facilitate diffusion MRI (dMRI) modeling and methodology development. METHODS: MRI data of one healthy subject (female, 25 years) were acquired on a clinical 3 Tesla system (Philips Achieva) with an eight-channel head coil. In total, the subject was scanned on 18 different occasions with a total acquisition time of 22.5 h. The dMRI data were acquired with an isotropic resolution of 2.5 mm(3) and distributed over five shells with b-values up to 4000 s/mm(2) and two Cartesian grids with b-values up to 9000 s/mm(2) . RESULTS: The final dataset consists of 8000 dMRI volumes, corresponding B0 field maps and noise maps for subsets of the dMRI scans, and ten three-dimensional FLAIR, T1 -, and T2 -weighted scans. The average signal-to-noise-ratio of the non-diffusion-weighted images was roughly 35. CONCLUSION: This unique set of in vivo MRI data will provide a robust framework to evaluate novel diffusion processing techniques and to reliably compare different approaches for diffusion modeling. The MASSIVE dataset is made publically available (both unprocessed and processed) on www.massive-data.org. Magn Reson Med, 2016

The importance of correcting for signal drift in diffusion MRI

PURPOSE: To investigate previously unreported effects of signal drift as a result of temporal scanner instability on diffusion MRI data analysis and to propose a method to correct this signal drift. METHODS: We investigated the signal magnitude of non-diffusion-weighted EPI volumes in a series of diffusion-weighted imaging experiments to determine whether signal magnitude changes over time. Different scan protocols and scanners from multiple vendors were used to verify this on phantom data, and the effects on diffusion kurtosis tensor estimation in phantom and in vivo data were quantified. Scalar metrics (eigenvalues, fractional anisotropy, mean diffusivity, mean kurtosis) and directional information (first eigenvectors and tractography) were investigated. RESULTS: Signal drift, a global signal decrease with subsequently acquired images in the scan, was observed in phantom data on all three scanners, with varying magnitudes up to 5% in a 15-min scan. The signal drift has a noticeable effect on the estimation of diffusion parameters. All investigated quantitative parameters as well as tractography were affected by this artifactual signal decrease during the scan. CONCLUSION: By interspersing the non-diffusion-weighted images throughout the session, the signal decrease can be estimated and compensated for before data analysis; minimizing the detrimental effects on subsequent MRI analyses. Magn Reson Med, 2016. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine

Approaches for estimating minimal clinically important differences in systemic lupus erythematosus.

A minimal clinically important difference (MCID) is an important concept used to determine whether a medical intervention improves perceived outcomes in patients. Prior to the introduction of the concept in 1989, studies focused primarily on statistical significance. As most recent clinical trials in systemic lupus erythematosus (SLE) have failed to show significant effects, determining a clinically relevant threshold for outcome scores (that is, the MCID) of existing instruments may be critical for conducting and interpreting meaningful clinical trials as well as for facilitating the establishment of treatment recommendations for patients. To that effect, methods to determine the MCID can be divided into two well-defined categories: distribution-based and anchor-based approaches. Distribution-based approaches are based on statistical characteristics of the obtained samples. There are various methods within the distribution-based approach, including the standard error of measurement, the standard deviation, the effect size, the minimal detectable change, the reliable change index, and the standardized response mean. Anchor-based approaches compare the change in a patient-reported outcome to a second, external measure of change (that is, one that is more clearly understood, such as a global assessment), which serves as the anchor. Finally, the Delphi technique can be applied as an adjunct to defining a clinically important difference. Despite an abundance of methods reported in the literature, little work in MCID estimation has been done in the context of SLE. As the MCID can help determine the effect of a given therapy on a patient and add meaning to statistical inferences made in clinical research, we believe there ought to be renewed focus on this area. Here, we provide an update on the use of MCIDs in clinical research, review some of the work done in this area in SLE, and propose an agenda for future research

Holmium Nanoparticles: Preparation and In Vitro Characterization of a New Device for Radioablation of Solid Malignancies

# The Author(s) 2010. This article is published with open access at Springerlink.com Purpose The present study introduces the preparation and in vitro characterization of a nanoparticle device comprising holmium acetylacetonate for radioablation of unresectable solid malignancies. Methods HoAcAc nanoparticles were prepared by dissolving holmium acetylacetonate in chloroform, followed by emulsification in an aqueous solution of a surfactant and evaporation of W. Bult: R. Varkevisser: P. R. Luijten: A. D. van het Schip

Optimal control design of turbo spin-echo sequences with applications to parallel-transmit systems

PURPOSE: The design of turbo spin-echo sequences is modeled as a dynamic optimization problem which includes the case of inhomogeneous transmit radiofrequency fields. This problem is efficiently solved by optimal control techniques making it possible to design patient-specific sequences online. THEORY AND METHODS: The extended phase graph formalism is employed to model the signal evolution. The design problem is cast as an optimal control problem and an efficient numerical procedure for its solution is given. The numerical and experimental tests address standard multiecho sequences and pTx configurations. RESULTS: Standard, analytically derived flip angle trains are recovered by the numerical optimal control approach. New sequences are designed where constraints on radiofrequency total and peak power are included. In the case of parallel transmit application, the method is able to calculate the optimal echo train for two-dimensional and three-dimensional turbo spin echo sequences in the order of 10 s with a single central processing unit (CPU) implementation. The image contrast is maintained through the whole field of view despite inhomogeneities of the radiofrequency fields. CONCLUSION: The optimal control design sheds new light on the sequence design process and makes it possible to design sequences in an online, patient-specific fashion. Magn Reson Med, 2016. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine

Diffusion Tensor MRI of the Heart – In Vivo Imaging of Myocardial Fiber Architecture

Despite many difficulties, the field of cardiac diffusion imaging is slowly but steadily making progress. In recent years it was demonstrated that reproducible measurement of diffusion parameters and fiber architecture in healthy and diseased hearts is possible. In this review we will discuss the basics of diffusion imaging as well as various reconstruction and analysis models. Furthermore, we cover the main challenges and proposed solutions that come with in vivo cardiac diffusion imaging. In vivo and ex vivo diffusion imaging of the heart has shown that the technique has great potential to better understand cardiac function, characterize cardiac pathology, and understand myofiber remodeling in response to injury or disease

Blood oxygenation level-dependent (BOLD) total and extravascular signal changes and ΔR2* in human visual cortex at 1.5, 3.0 and 7.0 T.

The characterisation of the extravascular (EV) contribution to the blood oxygenation level-dependent (BOLD) effect is important for understanding the spatial specificity of BOLD contrast and for modelling approaches that aim to extract quantitative metabolic parameters from the BOLD signal. Using bipolar crusher gradients, total (b = 0 s/mm(2) ) and predominantly EV (b = 100 s/mm(2) ) gradient echo BOLD ΔR(2)* and signal changes (ΔS/S) in response to visual stimulation (flashing checkerboard; f = 8 Hz) were investigated sequentially (within < 3 h) at 1.5, 3.0 and 7.0 T in the same subgroup of healthy volunteers (n = 7) and at identical spatial resolutions (3.5 × 3.5 × 3.5 mm(3)). Total ΔR(2)* (z-score analysis) values were -0.61 ± 0.10 s(-1) (1.5 T), -0.74 ± 0.05 s(-1) (3.0 T) and -1.37 ± 0.12 s(-1) (7.0 T), whereas EV ΔR(2)* values were -0.28 ± 0.07 s(-1) (1.5 T), -0.52 ± 0.07 s(-1) (3.0 T) and -1.25 ± 0.11 s(-1) (7.0 T). Although EV ΔR(2)* increased linearly with field, as expected, it was found that EV ΔS/S increased less than linearly with field in a manner that varied with TE choice. Furthermore, unlike ΔR(2)*, total and EV ΔS/S did not converge at 7.0 T. These trends were similar whether a z-score analysis or occipital lobe-based region-of-interest approach was used for voxel selection. These findings suggest that calibrated BOLD approaches may benefit from an EV ΔR(2)* measurement as opposed to a ΔS/S measurement at a single TE

Blood oxygenation level-dependent (BOLD) total and extravascular signal changes and ΔR2* in human visual cortex at 1.5, 3.0 and 7.0 T.

The characterisation of the extravascular (EV) contribution to the blood oxygenation level-dependent (BOLD) effect is important for understanding the spatial specificity of BOLD contrast and for modelling approaches that aim to extract quantitative metabolic parameters from the BOLD signal. Using bipolar crusher gradients, total (b = 0 s/mm(2) ) and predominantly EV (b = 100 s/mm(2) ) gradient echo BOLD ΔR(2)* and signal changes (ΔS/S) in response to visual stimulation (flashing checkerboard; f = 8 Hz) were investigated sequentially (within < 3 h) at 1.5, 3.0 and 7.0 T in the same subgroup of healthy volunteers (n = 7) and at identical spatial resolutions (3.5 × 3.5 × 3.5 mm(3)). Total ΔR(2)* (z-score analysis) values were -0.61 ± 0.10 s(-1) (1.5 T), -0.74 ± 0.05 s(-1) (3.0 T) and -1.37 ± 0.12 s(-1) (7.0 T), whereas EV ΔR(2)* values were -0.28 ± 0.07 s(-1) (1.5 T), -0.52 ± 0.07 s(-1) (3.0 T) and -1.25 ± 0.11 s(-1) (7.0 T). Although EV ΔR(2)* increased linearly with field, as expected, it was found that EV ΔS/S increased less than linearly with field in a manner that varied with TE choice. Furthermore, unlike ΔR(2)*, total and EV ΔS/S did not converge at 7.0 T. These trends were similar whether a z-score analysis or occipital lobe-based region-of-interest approach was used for voxel selection. These findings suggest that calibrated BOLD approaches may benefit from an EV ΔR(2)* measurement as opposed to a ΔS/S measurement at a single TE