Emerging Techniques in Breast MRI

As indicated throughout this chapter, there is a constant effort to move to more sensitive, specific, and quantitative methods for characterizing breast tissue via magnetic resonance imaging (MRI). In the present chapter, we focus on six emerging techniques that seek to quantitatively interrogate the physiological and biochemical properties of the breast. At the physiological scale, we present an overview of ultrafast dynamic contrast-enhanced MRI and magnetic resonance elastography which provide remarkable insights into the vascular and mechanical properties of tissue, respectively. Moving to the biochemical scale, magnetization transfer, chemical exchange saturation transfer, and spectroscopy (both “conventional” and hyperpolarized) methods all provide unique, noninvasive, insights into tumor metabolism. Given the breadth and depth of information that can be obtained in a single MRI session, methods of data synthesis and interpretation must also be developed. Thus, we conclude the chapter with an introduction to two very different, though complementary, methods of data analysis: (1) radiomics and habitat imaging, and (2) mechanism-based mathematical modeling

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke

The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large‐scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain-behavior relationships after stroke

The goal of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well-powered meta- and mega-analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large-scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided

Smaller spared subcortical nuclei are associated with worse post-stroke sensorimotor outcomes in 28 cohorts worldwide

Up to two-thirds of stroke survivors experience persistent sensorimotor impairments. Recovery relies on the integrity of spared brain areas to compensate for damaged tissue. Deep grey matter structures play a critical role in the control and regulation of sensorimotor circuits. The goal of this work is to identify associations between volumes of spared subcortical nuclei and sensorimotor behaviour at different timepoints after stroke. We pooled high-resolution T1-weighted MRI brain scans and behavioural data in 828 individuals with unilateral stroke from 28 cohorts worldwide. Cross-sectional analyses using linear mixed-effects models related post-stroke sensorimotor behaviour to non-lesioned subcortical volumes (Bonferroni-corrected, P < 0.004). We tested subacute (≤90 days) and chronic (≥180 days) stroke subgroups separately, with exploratory analyses in early stroke (≤21 days) and across all time. Sub-analyses in chronic stroke were also performed based on class of sensorimotor deficits (impairment, activity limitations) and side of lesioned hemisphere. Worse sensorimotor behaviour was associated with a smaller ipsilesional thalamic volume in both early (n = 179; d = 0.68) and subacute (n = 274, d = 0.46) stroke. In chronic stroke (n = 404), worse sensorimotor behaviour was associated with smaller ipsilesional putamen (d = 0.52) and nucleus accumbens (d = 0.39) volumes, and a larger ipsilesional lateral ventricle (d = -0.42). Worse chronic sensorimotor impairment specifically (measured by the Fugl-Meyer Assessment; n = 256) was associated with smaller ipsilesional putamen (d = 0.72) and larger lateral ventricle (d = -0.41) volumes, while several measures of activity limitations (n = 116) showed no significant relationships. In the full cohort across all time (n = 828), sensorimotor behaviour was associated with the volumes of the ipsilesional nucleus accumbens (d = 0.23), putamen (d = 0.33), thalamus (d = 0.33) and lateral ventricle (d = -0.23). We demonstrate significant relationships between post-stroke sensorimotor behaviour and reduced volumes of deep grey matter structures that were spared by stroke, which differ by time and class of sensorimotor measure. These findings provide additional insight into how different cortico-thalamo-striatal circuits support post-stroke sensorimotor outcomes

Acute Sleep Deprivation and Circadian Misalignment Associated with Transition onto the First Night of Work Impairs Visual Selective Attention

Background: Overnight operations pose a challenge because our circadian biology promotes sleepiness and dissipates wakefulness at night. Since the circadian effect on cognitive functions magnifies with increasing sleep pressure, cognitive deficits associated with night work are likely to be most acute with extended wakefulness, such as during the transition from a day shift to night shift. Methodology/Principal Findings: To test this hypothesis we measured selective attention (with visual search), vigilance (with Psychomotor Vigilance Task [PVT]) and alertness (with a visual analog scale) in a shift work simulation protocol, which included four day shifts followed by three night shifts. There was a nocturnal decline in cognitive processes, some of which were most pronounced on the first night shift. The nighttime decrease in visual search sensitivity was most pronounced on the first night compared with subsequent nights (p = .04), and this was accompanied by a trend towards selective attention becoming ‘fast and sloppy’. The nighttime increase in attentional lapses on the PVT was significantly greater on the first night compared to subsequent nights (p<.05) indicating an impaired ability to sustain focus. The nighttime decrease in subjective alertness was also greatest on the first night compared with subsequent nights (p<.05). Conclusions/Significance: These nocturnal deficits in attention and alertness offer some insight into why occupational errors, accidents, and injuries are pronounced during night work compared to day work. Examination of the nighttime vulnerabilities underlying the deployment of attention can be informative for the design of optimal work schedules and the implementation of effective countermeasures for performance deficits during night work

A Practical Guide to Rodent Islet Isolation and Assessment

Pancreatic islets of Langerhans secrete hormones that are vital to the regulation of blood glucose and are, therefore, a key focus of diabetes research. Purifying viable and functional islets from the pancreas for study is an intricate process. This review highlights the key elements involved with mouse and rat islet isolation, including choices of collagenase, the collagenase digestion process, purification of islets using a density gradient, and islet culture conditions. In addition, this paper reviews commonly used techniques for assessing islet viability and function, including visual assessment, fluorescent markers of cell death, glucose-stimulated insulin secretion, and intracellular calcium measurements. A detailed protocol is also included that describes a common method for rodent islet isolation that our laboratory uses to obtain viable and functional mouse islets for in vitro study of islet function, beta-cell physiology, and in vivo rodent islet transplantation. The purpose of this review is to serve as a resource and foundation for successfully procuring and purifying high-quality islets for research purposes

Addressing disparities in maternal health care in Pakistan: gender, class and exclusion

Background: After more than two decades of the Safe Motherhood Initiative and Millennium Development Goals aimed at reducing maternal mortality, women continue to die in childbirth at unacceptably high rates in Pakistan. While an extensive literature describes various programmatic strategies, it neglects the rigorous analysis of the reasons these strategies have been unsuccessful, especially for women living at the economic and social margins of society. A critical gap in current knowledge is a detailed understanding of the root causes of disparities in maternal health care, and in particular, how gender and class influence policy formulation and the design and delivery of maternal health care services. Taking Pakistan as a case study, this research builds upon two distinct yet interlinked conceptual approaches to understanding the phenomenon of inequity in access to maternal health care: social exclusion and health systems as social institutions. Methods/Design: This four year project consists of two interrelated modules that focus on two distinct groups of participants: (1) poor, disadvantaged women and men and (2) policy makers, program managers and health service providers. Module one will employ critical ethnography to understand the key axes of social exclusion as related to gender, class and zaat and how they affect women’s experiences of using maternal health care. Through health care setting observations, interviews and document review, Module two will assess policy design and delivery of maternal health services. Discussion: This research will provide theoretical advances to enhance understanding of the power dynamics of gender and class that may underlie poor women’s marginalization from health care systems in Pakistan. It will also provide empirical evidence to support formulation of maternal health care policies and health care system practices aimed at reducing disparities in maternal health care in Pakistan. Lastly, it will enhance inter-disciplinary research capacity in the emerging field of social exclusion and maternal health and help reduce social inequities and achieve the Millennium Development Goal No. 5

Chronic Stroke Sensorimotor Impairment Is Related to Smaller Hippocampal Volumes: An ENIGMA Analysis

Background. Persistent sensorimotor impairments after stroke can negatively impact quality of life. The hippocampus is vulnerable to poststroke secondary degeneration and is involved in sensorimotor behavior but has not been widely studied within the context of poststroke upper‐limb sensorimotor impairment. We investigated associations between non‐lesioned hippocampal volume and upper limb sensorimotor impairment in people with chronic stroke, hypothesizing that smaller ipsilesional hippocampal volumes would be associated with greater sensorimotor impairment. Methods and Results. Cross‐sectional T1‐weighted magnetic resonance images of the brain were pooled from 357 participants with chronic stroke from 18 research cohorts of the ENIGMA (Enhancing NeuoImaging Genetics through Meta‐Analysis) Stroke Recovery Working Group. Sensorimotor impairment was estimated from the FMA‐UE (Fugl‐Meyer Assessment of Upper Extremity). Robust mixed‐effects linear models were used to test associations between poststroke sensorimotor impairment and hippocampal volumes (ipsilesional and contralesional separately; Bonferroni‐corrected, P<0.025), controlling for age, sex, lesion volume, and lesioned hemisphere. In exploratory analyses, we tested for a sensorimotor impairment and sex interaction and relationships between lesion volume, sensorimotor damage, and hippocampal volume. Greater sensorimotor impairment was significantly associated with ipsilesional (P=0.005; β=0.16) but not contralesional (P=0.96; β=0.003) hippocampal volume, independent of lesion volume and other covariates (P=0.001; β=0.26). Women showed progressively worsening sensorimotor impairment with smaller ipsilesional (P=0.008; β=−0.26) and contralesional (P=0.006; β=−0.27) hippocampal volumes compared with men. Hippocampal volume was associated with lesion size (P<0.001; β=−0.21) and extent of sensorimotor damage (P=0.003; β=−0.15). Conclusions. The present study identifies novel associations between chronic poststroke sensorimotor impairment and ipsilesional hippocampal volume that are not caused by lesion size and may be stronger in women.S.-L.L. is supported by NIH K01 HD091283; NIH R01 NS115845. A.B. and M.S.K. are supported by National Health and Medical Research Council (NHMRC) GNT1020526, GNT1045617 (A.B.), GNT1094974, and Heart Foundation Future Leader Fellowship 100784 (A.B.). P.M.T. is supported by NIH U54 EB020403. L.A.B. is supported by the Canadian Institutes of Health Research (CIHR). C.M.B. is supported by NIH R21 HD067906. W.D.B. is supported by the Heath Research Council of New Zealand. J.M.C. is supported by NIH R00HD091375. A.B.C. is supported by NIH R01NS076348-01, Hospital Israelita Albert Einstein 2250-14, CNPq/305568/2016-7. A.N.D. is supported by funding provided by the Texas Legislature to the Lone Star Stroke Clinical Trial Network. Its contents are solely the responsibility of the authors and do not necessarily represent the of ficial views of the Government of the United States or the State of Texas. N.E.-B. is supported by Australian Research Council NIH DE180100893. W.F. is sup ported by NIH P20 GM109040. F.G. is supported by Wellcome Trust (093957). B.H. is funded by and NHMRC fellowship (1125054). S.A.K is supported by NIH P20 HD109040. F.B. is supported by Italian Ministry of Health, RC 20, 21. N.S. is supported by NIH R21NS120274. N.J.S. is supported by NIH/National Institute of General Medical Sciences (NIGMS) 2P20GM109040-06, U54-GM104941. S.R.S. is supported by European Research Council (ERC) (NGBMI, 759370). G.S. is supported by Italian Ministry of Health RC 18-19-20-21A. M.T. is sup ported by National Institute of Neurological Disorders and Stroke (NINDS) R01 NS110696. G.T.T. is supported by Temple University sub-award of NIH R24 –NHLBI (Dr Mickey Selzer) Center for Experimental Neurorehabilitation Training. N.J.S. is funded by NIH/National Institute of Child Health and Human Development (NICHD) 1R01HD094731-01A1

A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms.

Accurate lesion segmentation is critical in stroke rehabilitation research for the quantification of lesion burden and accurate image processing. Current automated lesion segmentation methods for T1-weighted (T1w) MRIs, commonly used in stroke research, lack accuracy and reliability. Manual segmentation remains the gold standard, but it is time-consuming, subjective, and requires neuroanatomical expertise. We previously released an open-source dataset of stroke T1w MRIs and manually-segmented lesion masks (ATLAS v1.2, N = 304) to encourage the development of better algorithms. However, many methods developed with ATLAS v1.2 report low accuracy, are not publicly accessible or are improperly validated, limiting their utility to the field. Here we present ATLAS v2.0 (N = 1271), a larger dataset of T1w MRIs and manually segmented lesion masks that includes training (n = 655), test (hidden masks, n = 300), and generalizability (hidden MRIs and masks, n = 316) datasets. Algorithm development using this larger sample should lead to more robust solutions; the hidden datasets allow for unbiased performance evaluation via segmentation challenges. We anticipate that ATLAS v2.0 will lead to improved algorithms, facilitating large-scale stroke research

Colorectal cancer screening, perceived discrimination, and low-income and trust in doctors: a survey of minority patients

<p>Abstract</p> <p>Background</p> <p>Completion of colorectal cancer (CRC) screening testing is lower among low-income and minority groups than the population as a whole. Given the multiple cancer screening health disparities known to exist within the U.S., this study investigated the relationship between perceived discrimination, trust in most doctors, and completion of Fecal Occult Blood Testing (FOBT) among a low-income, minority primary care population in an urban setting.</p> <p>Methods</p> <p>We recruited a convenience sample of adults over age 40 (n = 282) from a federally qualified community health center (70% African American). Participants completed a survey which included measures of trust in most doctors, perceived discrimination, demographics and report of cancer screening.</p> <p>Results</p> <p>Participants reported high levels of trust in most doctors, regardless of sex, race, education or income. High trust was associated with low perceived discrimination (p < 0.01). The trend was for older participants to express more trust (p = 0.09) and less perceived discrimination (p < 0.01). Neither trust nor discrimination was associated with race or education. Trust was higher among participants over 50 who were up-to-date on FOBT screening vs. those who were not (31 vs. 29 (median), p < 0.05 by T-test). Among those over 50, up-to-date FOBT screening was nearly associated with high trust (p < 0.06; 95% CI 0.99, 1.28) and low perceived discrimination (p < 0.01; 95% CI 0.76, 0.96). Nevertheless, in multivariate-modeling, age and income explained FOBT completion better than race, trust and discrimination.</p> <p>Conclusion</p> <p>Perceived discrimination was related to income, but not race, suggesting that discrimination is not unique to minorities, but common to those in poverty. Since trust in most doctors trended toward being related to age, FOBT screening could be negatively influenced by low trust and perceived discrimination in health care settings. A failure to address these issues in middle-aged, low income individuals could exacerbate future disparities in CRC screening.</p