Magnetic Susceptibility Source Separation Solely from Gradient Echo Data: Histological Validation.

Quantitative susceptibility mapping (QSM) facilitates mapping of the bulk magnetic susceptibility of tissue from the phase of complex gradient echo (GRE) MRI data. QSM phase processing combined with an R2* model of magnitude of multiecho gradient echo data (R2*QSM) allows separation of dia- and para-magnetic components (e.g., myelin and iron) that contribute constructively to R2* value but destructively to the QSM value of a voxel. This R2*QSM technique is validated against quantitative histology­optical density of myelin basic protein and Perls' iron histological stains of rim and core of 10 ex vivo multiple sclerosis lesions, as well as neighboring normal appearing white matter. We found that R2*QSM source maps are in good qualitative agreement with histology, e.g., showing increased iron concentration at the edge of the rim+ lesions and myelin loss in the lesions' core. Furthermore, our results indicate statistically significant correlation between paramagnetic and diamagnetic tissue components estimated with R2*QSM and optical densities of Perls' and MPB stains. These findings provide direct support for the use of R2*QSM magnetic source separation based solely on GRE complex data to characterize MS lesion composition.

Implicit-Bias Remedies: Treating Discriminatory Bias as a Public-Health Problem.

Accumulated findings from studies in which implicit-bias measures correlate with discriminatory judgment and behavior have led many social scientists to conclude that implicit biases play a causal role in racial and other discrimination. In turn, that belief has promoted and sustained two lines of work to develop remedies: (a) individual treatment interventions expected to weaken or eradicate implicit biases and (b) group-administered training programs to overcome biases generally, including implicit biases. Our review of research on these two types of sought remedies finds that they lack established methods that durably diminish implicit biases and have not reproducibly reduced discriminatory consequences of implicit (or other) biases. That disappointing conclusion prompted our turn to strategies based on methods that have been successful in the domain of public health. Preventive measures are designed to disable the path from implicit biases to discriminatory outcomes. Disparity-finding methods aim to discover disparities that sometimes have obvious fixes, or that at least suggest where responsibility should reside for developing a fix. Disparity-finding methods have the advantage of being useful in remediation not only for implicit biases but also systemic biases. For both of these categories of bias, causes of discriminatory outcomes are understood as residing in large part outside the conscious awareness of individual actors. We conclude with recommendations to guide organizations that wish to deal with biases for which they have not yet found solutions.