The Effect of Oblique Image Slices on the Accuracy of Quantitative Susceptibility Mapping and a Robust Tilt Correction Method

Quantitative susceptibility mapping (QSM) using the MRI phase to calculate tissue magnetic susceptibility is finding increasing clinical applications. Oblique image slices are often acquired to facilitate radiological viewing and reduce artifacts. Here, we show that artifacts and errors arise in susceptibility maps if oblique acquisition is not properly taken into account in QSM. We performed a comprehensive analysis of the effects of oblique acquisition on brain susceptibility maps and compared tilt correction schemes for three susceptibility calculation methods, using a numerical phantom and human in-vivo images. We demonstrate a robust tilt correction method for accurate QSM with oblique acquisition

Investigating the accuracy and precision of TE‐dependent versus multi‐echo QSM using Laplacian‐based methods at 3 T

Purpose: Multi‐echo gradient‐recalled echo acquisitions for QSM enable optimizing the SNR for several tissue types through multi‐echo (TE) combination or investigating temporal variations in the susceptibility (potentially reflecting tissue microstructure) by calculating one QSM image at each TE (TE‐dependent QSM). In contrast with multi‐echo QSM, applying Laplacian‐based methods (LBMs) for phase unwrapping and background field removal to single TEs could introduce nonlinear temporal variations (independent of tissue microstructure) into the measured susceptibility. Here, we aimed to compare the effect of LBMs on the QSM susceptibilities in TE‐dependent versus multi‐echo QSM. Methods: TE–dependent recalled echo data simulated in a numerical head phantom and gradient‐recalled echo images acquired at 3 T in 10 healthy volunteers. Several QSM pipelines were tested, including four distinct LBMs: sophisticated harmonic artifact reduction for phase data (SHARP), variable‐radius sophisticated harmonic artifact reduction for phase data (V‐SHARP), Laplacian boundary value background field removal (LBV), and one‐step total generalized variation (TGV). Results from distinct pipelines were compared using visual inspection, summary statistics of susceptibility in deep gray matter/white matter/venous regions of interest, and, in the healthy volunteers, regional susceptibility bias analysis and nonparametric tests. Results: Multi‐echo versus TE‐dependent QSM had higher regional accuracy, especially in high‐susceptibility regions and at shorter TEs. Everywhere except in the veins, a processing pipeline incorporating TGV provided the most temporally stable TE‐dependent QSM results with an accuracy similar to multi‐echo QSM. Conclusions: For TE‐dependent QSM, carefully choosing LBMs can minimize the introduction of LBM‐related nonlinear temporal susceptibility variations

The child attachment interview: A psychometric study of reliability and discriminant validity

While well-established attachment measures have been developed for infancy, early childhood, and adulthood, a "measurement gap" has been identified in middle childhood, where behavioral or representational measures are not yet sufficiently robust. This article documents the development of a new measure-the Child Attachment Interview (CAI)-which seeks to bridge this gap. The CAI is a semistructured interview, in which children are invited to describe their relationships with their primary caregivers. The coding system is informed by the Adult Attachment Interview and the Strange Situation Procedure, and produces 4 attachment categories along with a continuous measure of attachment security based on ratings of attachment-related dimensions. The main psychometric properties are presented, including interrater reliability, test-retest reliability, and concurrent and discriminant validities, both for normally developing children and for those referred for mental health treatment. The CAI correlates as expected with other attachment measures and predicts independently collected ratings of social functioning. The findings suggest that the CAI is a reliable, valid, and promising measure of child-parent attachment in middle childhood. Directions for improvements to the coding system are discussed

The strength of the strongest ties in collaborative problem solving

Complex problem solving in science, engineering, and business has become a highly collaborative endeavor. Teams of scientists or engineers collaborate on projects using their social networks to gather new ideas and feedback. Here we bridge the literature on team performance and information networks by studying teams' problem solving abilities as a function of both their within-team networks and their members' extended networks. We show that, while an assigned team's performance is strongly correlated with its networks of expressive and instrumental ties, only the strongest ties in both networks have an effect on performance. Both networks of strong ties explain more of the variance than other factors, such as measured or self-evaluated technical competencies, or the personalities of the team members. In fact, the inclusion of the network of strong ties renders these factors non-significant in the statistical analysis. Our results have consequences for the organization of teams of scientists, engineers, and other knowledge workers tackling today's most complex problems

SEGUE: a Speedy rEgion-Growing algorithm for Unwrapping Estimated phase

Recent Magnetic Resonance Imaging (MRI) techniques, such as Quantitative magnetic Susceptibility Mapping (QSM), employ the signal phase to reveal disease-related changes in tissue composition including iron or calcium content. The MRI phase is also routinely used in functional and diffusion MRI for distortion correction. However, phase images are wrapped into a range of 2π radians. PRELUDE is the gold standard method for robust, spatial, 3-dimensional, MRI phase unwrapping. Unfortunately, PRELUDE's computation time can reach 15 minutes for a severely wrapped brain image and nearly 10 hours to unwrap a full head-and-neck image on a standard PC. Here we develop a Speedy rEgion-Growing algorithm for Unwrapping Estimated phase (SEGUE) based on similar principles to PRELUDE, implemented with additional methods for acceleration. We compared PRELUDE and SEGUE in numerical phantoms, and using in-vivo images of the brain, head-and-neck, and pelvis acquired in 4-5 healthy volunteers and at 4-6 echo times. To overcome chemical-shift-induced errors within the head-and-neck and pelvic images, we also investigated applying both techniques within fat and water masks separately. SEGUE provided almost identical unwrapped phase maps to the gold standard PRELUDE. SEGUE was (1.5 to 70 times) faster than PRELUDE, especially in severely wrapped images at later echoes as well as in the head-and-neck and pelvic images. Applying these techniques within fat and water masks separately successfully removed chemical-shiftinduced errors. SEGUE's MATLAB implementation is available for download. SEGUE is a general unwrapping algorithm not specific to MRI and could, therefore, be used in images acquired with other modalities

The effect of low resolution and coverage on the accuracy of susceptibility mapping

PURPOSE: Quantitative susceptibility mapping (QSM) has found increasing clinical applications. However, to reduce scan time, clinical acquisitions often use reduced resolution and coverage, particularly in the through-slice dimension. The effect of these factors on QSM has begun to be assessed using only balloon phantoms and downsampled brain images. Here, we investigate the effects (and their sources) of low resolution or coverage on QSM using both simulated and acquired images. METHODS: Brain images were acquired at 1 mm isotropic resolution and full brain coverage, and low resolution (up to 6 mm slice thickness) or coverage (down to 20 mm) in 5 healthy volunteers. Images at reduced resolution or coverage were also simulated in these volunteers and in a new, anthropomorphic, numerical phantom. Mean susceptibilities in 5 brain regions, including white matter, were investigated over varying resolution and coverage. RESULTS: The susceptibility map contrast decreased with increasing slice thickness and spacing, and with decreasing coverage below ~40 mm for 2 different QSM pipelines. Our simulations showed that calculated susceptibility values were erroneous at low resolution or very low coverage, because of insufficient sampling and overattenuation of the susceptibility-induced field perturbations. Susceptibility maps calculated from simulated and acquired images showed similar behavior. CONCLUSIONS: Both low resolution and low coverage lead to loss of contrast and errors in susceptibility maps. The widespread clinical practice of using low resolution and coverage does not provide accurate susceptibility maps. Simulations in images of healthy volunteers and in a new, anthropomorphic numerical phantom were able to accurately model low-resolution and low-coverage acquisitions