Adrienne N. Dula

The University of Texas at Austin

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Steven Warach

The University of Texas at Austin

Seth A. Smith

Vanderbilt University Medical Center

John C. Gore

Vanderbilt University Medical Center

Lara A. Boyd

University of British Columbia

Kristin A. Wong

The University of Texas at Austin

Sook‐Lei Liew

University of Southern California

Michael R. Borich

Georgia Institute of Technology

Steven A. Kautz

Medical University of South Carolina

Adriana Bastos Conforto

Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo

George F. Wittenberg

VA Pittsburgh Healthcare System

Cooperative Institutions

University of Southern California

112

Ibero American University

Imaging Center

Vanderbilt University

Vanderbilt University Medical Center

The University of Texas at Austin

University of Melbourne

Harvard University

Stanford University

University of Toronto

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Bioluminescence Imaging Reveals Dynamics of Beta Cell Loss in the Non-Obese Diabetic (NOD) Mouse Model

PLoS ONE (2013)

John Virostko Armandla Radhika Greg Poffenberger Adrienne N. Dula Daniel J. Moore

We generated a mouse model (MIP-Luc-VU-NOD) that enables non-invasive bioluminescence imaging (BLI) of beta cell loss during the progression of autoimmune diabetes and determined the relationship between BLI and disease progression. MIP-Luc-VU-NOD mice displayed insulitis and a decline in bioluminescence with age which correlated with beta cell mass, plasma insulin, and pancreatic insulin content. Bioluminescence declined gradually in female MIP-Luc-VU-NOD mice, reaching less than 50% of the initial BLI at 10 weeks of age, whereas hyperglycemia did not ensue until mice were at least 16 weeks old. Mice that did not become diabetic maintained insulin secretion and had less of a decline in bioluminescence than mice that became diabetic. Bioluminescence measurements predicted a decline in beta cell mass prior to the onset of hyperglycemia and tracked beta cell loss. This model should be useful for investigating the fundamental processes underlying autoimmune diabetes and developing new therapies targeting beta cell protection and regeneration.

Bioluminescence imaging

NOD mice

Insulitis

BETA (programming language)

10.1371/journal.pone.0057784

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Citations (22)

Larger perivascular space volume fraction is associated with worse post-stroke sensorimotor outcomes: An ENIGMA analysis

medRxiv (Cold Spring Harbor Laboratory) (2024)

Stuti Chakraborty Jeiran Choupan Octavio Marin-Pardo Mahir H. Khan Giuseppe Barisano

ABSTRACT BACKGROUND Perivascular Spaces (PVS) are a marker of cerebral small vessel disease (CSVD) that are visible on brain imaging. Larger PVS has been associated with poor quality of life and cognitive impairment post-stroke. However, the association between PVS and post-stroke sensorimotor outcomes has not been investigated. METHODS 602 individuals with a history of stroke across 24 research cohorts from the ENIGMA Stroke Recovery Working Group were included. PVS volume fractions were obtained using a validated, automated segmentation pipeline from the basal ganglia (BG) and white matter centrum semiovale (CSO), separately. Robust mixed effects regressions were used to a) examine the cross-sectional association between PVS volume fraction and post-stroke sensorimotor outcomes and b) to examine whether PVS volume fraction was associated with other measures of CSVD and overall brain health (e.g., white matter hyperintensities [WMHs], brain age [measured by predicted age difference, brain-PAD]). RESULTS Larger PVS volume fraction in the CSO, but not BG, was associated with worse post-stroke sensorimotor outcomes (b = -0.06, p = 0.047). Higher burden of deep WMH (b = 0.25, p <0.001), periventricular WMH (b = 0.16, p <0.001) and higher brain-PAD (b = 0.09, p <0.001) were associated with larger PVS volume fraction in the CSO. CONCLUSIONS Our data show that PVS volume fraction in the CSO is cross-sectionally associated with sensorimotor outcomes after stroke, above and beyond standard lesion metrics. PVS may provide insight into how the overall vascular health of the brain impacts inter-individual differences in post-stroke sensorimotor outcomes.

Stroke

Perivascular space

Fraction (chemistry)

10.1101/2024.12.20.24319296

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Table of Contents

Journal of Stroke and Cerebrovascular Diseases (2023)

Naaem Simaan Jeremy Molad Asaf Honig Andrei Filioglo Shlomi Peretz

Table (database)

10.1016/s1052-3057(23)00341-5

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Behavioral and Biologic Characteristics of Cancer-related Cognitive Impairment Biotypes

Research Square (Research Square) (2022)

Michele M. Mulholland Sarah Prinsloo Elizabeth Kvale Adrienne N. Dula Oxana Palesh

Abstract Psychiatric diagnosis is moving away from symptom-based classification and towards multi-dimensional, biologically-based characterization, or biotyping. We previously identified three biotypes of chemotherapy-related cognitive impairment based on functional brain connectivity. In this follow-up study, we evaluated additional factors to help explain biotype expression: neurofunctional stability, brain age, apolipoprotein (APOE) genotype, and psychoneurologic symptoms. We also compared the discriminative ability of a traditional, symptom-based cognitive impairment definition with that of biotypes. We found significant differences in cortical brain age (F = 10.86, p < 0.001), neurofunctional stability (F = 2.85, p = 0.040), APOE e4 genotype (X 2 = 7.89, p = 0.048), and psychoneurological symptoms (Pillai = 0.339, p < 0.001) across the three biotypes. The more resilient (Biotype 2) demonstrated significantly higher neurofunctional stability compared to the other biotypes. Symptom-based classification of cognitive impairment did not differentiate biologic or other behavioral variables, suggesting that traditional categorization of cancer-related cognitive effects may miss important characteristics which could inform targeted treatment strategies. Additionally, biotyping, but not symptom-typing, was able to distinguish survivors with cognitive versus psychological effects. Our results suggest that Biotype 1 survivors might benefit from first addressing symptoms of anxiety and fatigue, Biotype 3 might benefit from a treatment plan which includes sleep hygiene, and Biotype 2 might benefit most from cognitive skills training or rehabilitation. Future research should include additional demographic and clinical information to further investigate biotype expression related to risk and resilience and examine integration of more clinically feasible imaging approaches.

10.21203/rs.3.rs-1918472/v1

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Data-driven biomarkers better associate with stroke motor outcomes than theory-based biomarkers

Brain Communications (2024)

Emily Olafson Christoph Sperber Keith Jamison Mark Bowren Aaron D. Boes

Abstract Chronic motor impairments are a leading cause of disability after stroke. Previous studies have associated motor outcomes with the degree of damage to predefined structures in the motor system, such as the corticospinal tract. However, such theory-based approaches may not take full advantage of the information contained in clinical imaging data. The present study uses data-driven approaches to model chronic motor outcomes after stroke and compares the accuracy of these associations to previously-identified theory-based biomarkers. Using a cross-validation framework, regression models were trained using lesion masks and motor outcomes data from 789 stroke patients from the Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA) Stroke Recovery Working Group. Using the explained variance metric to measure the strength of the association between chronic motor outcomes and imaging biomarkers, we compared theory-based biomarkers, like lesion load to known motor tracts, to three data-driven biomarkers: lesion load of lesion-behaviour maps, lesion load of structural networks associated with lesion-behaviour maps, and measures of regional structural disconnection. In general, data-driven biomarkers had stronger associations with chronic motor outcomes accuracy than theory-based biomarkers. Data-driven models of regional structural disconnection performed the best of all models tested (R2 = 0.210, P < 0.001), performing significantly better than the theory-based biomarkers of lesion load of the corticospinal tract (R2 = 0.132, P < 0.001) and of multiple descending motor tracts (R2 = 0.180, P < 0.001). They also performed slightly, but significantly, better than other data-driven biomarkers including lesion load of lesion-behaviour maps (R2 = 0.200, P < 0.001) and lesion load of structural networks associated with lesion-behaviour maps (R2 = 0.167, P < 0.001). Ensemble models - combining basic demographic variables like age, sex, and time since stroke - improved the strength of associations for theory-based and data-driven biomarkers. Combining both theory-based and data-driven biomarkers with demographic variables improved predictions, and the best ensemble model achieved R2 = 0.241, P < 0.001. Overall, these results demonstrate that out-of-sample associations between chronic motor outcomes and data-driven imaging features, particularly when lesion data is represented in terms of structural disconnection, are stronger than associations between chronic motor outcomes and theory-based biomarkers. However, combining both theory-based and data-driven models provides the most robust associations.

Stroke

10.1093/braincomms/fcae254

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Decrease in Stroke Diagnoses During the COVID-19 Pandemic: Where Did All Our Stroke Patients Go?

JMIR Aging (2020)

Adrienne N. Dula Gretchel Gealogo Brown Aarushi Aggarwal Kal Clark

Despite the evidence suggesting a high rate of cerebrovascular complications in patients with SARS-CoV-2, reports have indicated decreasing rates of new ischemic stroke diagnoses during the COVID-19 pandemic. The observed decrease in emergency department (ED) visits is unsurprising during this major crisis, as patients are likely to prioritize avoiding exposure to SARS-CoV-2 over addressing what they may perceive as mild symptoms of headache, lethargy, difficulty speaking, and numbness. In the central and south Texas regions where we practice, we suspect that patient admission, treatment, and discharge volumes for acute stroke treatment have decreased significantly since COVID-19-related shelter-at-home orders were issued. Symptoms of stroke are frequently noticed by a family member, friend, or community member before they are recognized by the patients themselves, and these symptoms may be going unnoticed due to limited face-to-face encounters. This possibility emphasizes the importance of patient education regarding stroke warning signs and symptoms during the current period of isolation and social-distancing. The south Texas population, already saddled with above-average rates of cardiovascular and cerebrovascular disease, has a higher stroke mortality rate compared to Texas and U.S. averages; however, the number of patients presenting to EDs with acute ischemic stroke diagnoses is lower than average. In our viewpoint, we aim to present the relative literature to date and outline our ongoing analyses of the highly affected and diverse stroke populations in San Antonio and Austin, Texas, to answer a simple question: where did all our stroke patients go?

Pandemic

Stroke

2019-20 coronavirus outbreak

10.2196/21608

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Citations (33)

Examination of the Spinal Cord in Multiple Sclerosis Patients Using Chemical Exchange Saturation Transfer MRI at 7 Tesla (P06.125)

Neurology (2013)

Adrienne N. Dula Seth A. Smith Siddharama Pawate John C. Gore

OBJECTIVE: Cervical spinal cord application of molecular-based CEST MRI will non-invasively and quantitatively address the current disparity between MRI findings and measures of clinical disability caused by MS. This will be demonstrated through the sensitivity of CEST MRI metrics to the known diffuse histopathology found in NAWM of MS, establishing a non-invasive, quantitative, and predictive understanding of the mechanisms of clinical dysfunction that are poorly represented by macroscopically visual lesions in multiple sclerosis. BACKGROUND: Current radiological markers remain insufficient at capturing pathological correlates of multiple sclerosis (MS). Current imaging methods that quantitatively measure tissue properties do not reliably reflect the dynamic and heterogeneous tissue microenvironment present in the pathological white matter. Furthermore, imaging studies typically concentrate on focal lesions. The normal appearing white matter (NAWM) in cervical spinal cord is a largely unexplored area of MS research, particularly at 7 T. DESIGN/METHODS: All MRI data are acquired on the Philips Achieva 7 T scanner using a surface quadrature coil and 16-channel spine array (Nova Medical) for RF transmission and reception at the level of C2-C4. Statistical analyses are performed in SPSS. Inclusion/Exclusion Criteria: Healthy controls and patients with clinically diagnosed relapsing-remitting MS, based on the McDonald diagnostic criteria above the age of 18 are eligible. RESULTS: CEST imaging of the cervical spinal cord at 7T has reveals differences in the amide proton transfer (APT) metric between healthy white matter and gray matter. Additionally, differences in the APT metric are found in MS lesions of the spinal cord. Further studies focus on normal appearing white matter in the spinal cord with preliminary results indicating the potential to distinguish healthy white matter and normal appearing white matter of MS patients. CONCLUSIONS: CEST MRI at 7T provides increased resolution, signal to noise, and spectral dispersion, facilitating the examination of the biochemical pathyphysiology of MS. Supported by: NIH KL2 RR24977-05. Disclosure: Dr. Dula has nothing to disclose. Dr. Smith has nothing to disclose. Dr. Gore has nothing to disclose.

Saturation (graph theory)

10.1212/wnl.80.7_supplement.p06.125

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Optimization of 7-T Chemical Exchange Saturation Transfer Parameters for Validation of Glycosaminoglycan and Amide Proton Transfer of Fibroglandular Breast Tissue

Radiology (2014)

Adrienne N. Dula Blake E. Dewey Lori R. Arlinghaus Jason M. Williams Dennis W. J. Klomp

Purpose To (a) implement simulation-optimized chemical exchange saturation transfer (CEST) measurements sensitive to amide proton transfer (APT) and glycosaminoglycan (GAG) hydroxyl proton transfer effects in the human breast at 7 T and (b) determine the reliability of these techniques for evaluation of fibroglandular tissue in the healthy breast as a benchmark for future studies of pathologic findings. Materials and Methods All human studies were institutional review board approved, were HIPAA compliant, and included informed consent. The CEST parameters of saturation duration (25 msec) and amplitude (1 μT) were chosen on the basis of simulation-driven optimization for APT contrast enhancement with the CEST effect quantified by using residuals of a Lorentzian fit. Optimized parameters were implemented at 7 T in 10 healthy women in two separate examinations to evaluate the reliability of CEST magnetic resonance (MR) imaging measurements in the breast. CEST z-spectra were acquired over saturation offset frequencies ranging between ±40 ppm by using a quadrature unilateral breast coil. The imaging–repeat imaging reliability was assessed in terms of the intraclass correlation coefficient, which indicates the ratio of between-subject variation to total variation. Results Simulations were performed of the Bloch equations with chemical exchange–guided selection of optimal values for pulse duration and amplitude, 25 msec and 1 μT, respectively. Reliability was evaluated by using intraclass correlation coefficients (95% confidence intervals), with acceptable results: 0.963 (95% confidence interval: 0.852, 0.991) and 0.903 (95% confidence interval: 0.609, 0.976) for APT and GAG, respectively. Conclusion Simulations were used to derive optimal CEST preparation parameters to elicit maximal CEST contrast enhancement in healthy fibroglandular breast tissue due to APT at 7 T. By using these parameters, reproducible values were obtained for both the amide and hydroxyl protons from CEST MR imaging at 7 T and are feasible in the human breast. © RSNA, 2014

Coefficient of variation

10.1148/radiol.14140762

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P4‐067: Novel high‐field mri applied to the early detection of Alzheimer's disease‐related pathology

Alzheimer s & Dementia (2011)

Tracy Porchak Tricia A. Thornton‐Wells Brandon A. Ally Erin Hussey Seth A. Smith

Beta-amyloid plaques and tau-containing neurofibrillary tangles are recognized biomarkers of Alzheimer's disease (AD) onset and progression, yet hemodynamic and/or metabolic modulations that may precede such changes are currently debated. Importantly, detecting and evaluating early-stage pathogenesis is critical to characterizing disease etiology and guiding treatments intended to prevent irreversible tissue damage. Magnetic resonance imaging (MRI) poses potential for investigating pathological biomarkers owing to its variety of noninvasive contrast mechanisms. Therefore, we have initiated a collaborative effort between imaging physicists, neuropsychologists, and geneticists with the aim of identifying hemodynamic, neurochemical, and metabolic biomarkers in preclinical AD using novel MRI approaches at intermediate (3T) and high (7T) magnetic field. This study has been divided into three stages with distinct benchmarks for success: (i) to optimize high-field protocols for at-risk (APOE-e4 carrier or family history) AD populations, (ii) to measure neurochemical and hemodynamic parameters in preclinical at-risk populations (APOE-e4 carrier or family history), and (iii) to evaluate imaging biomarkers in patients with clinical AD. In addition to structural scans, novel approaches with AD-relevant contrasts have been implemented: (1) arterial spin labeling (cerebral blood flow), (2) vascular-space-occupancy (cerebral blood volume), (3) T1-? (beta-amyloid), (4) chemical-exchange-saturation-transfer (neurochemicals), (5) spontaneous blood-oxygenation-level-dependent (functional-connectivity), (6) susceptibility weighting (microbleeds) and (7) T2-relaxation-under-spin-tagging (oxygen extraction fraction). The imaging choices were motivated by (i) uniqueness, i.e. approaches that have not been robustly tested in AD and (ii) approaches that generate specific contrasts for parameters hypothesized to be implicated in early-stage AD. This study represents an active trial with a target enrollment of 10 patients per month. We have implemented the above approaches, performed quality control measurements in healthy populations and are actively enrolling at-risk volunteers with mild cognitive impairment. Fig. 1 shows representative images from the AD protocol; pilot data from at-risk subjects, in the context of healthy volunteers, will be discussed. A novel high-field MRI protocol has been implemented for early detection of hemodynamic, neurochemical and metabolic changes that may precede structural or clinical changes in AD. This ongoing work is a multi-departmental effort and is expected to provide mechanistic clues regarding early-stage functional changes in AD. Representative images from novel imaging approaches employed in AD protocol. (a) 7T high-spatial resolution (1.6 mm) functional connectivity mapping, (b) 3.OT noninvasive cerebral blood flow imaging with arterial spin labeling. 7T high-spatial resolution (0.75 mm) structural imaging, and (d) 7T high spatial resolution (0.5 mm)susceptility weighted imaging.

Neurochemical

10.1016/j.jalz.2011.05.2087

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Response by Dula et al to Letter Regarding Article, “Neuroimaging in Ischemic Stroke Is Different Between Men and Women in the DEFUSE 3 Cohort”

Stroke (2020)

Adrienne N. Dula Michael Mlynash Gregory W. Albers Steven Warach

Stroke

10.1161/strokeaha.120.029168

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