Stroke recovery phenotyping through network trajectory approaches and graph neural networks
(2022) Brain Informatics, 9 (1), art. no. 13, .
Krishnagopal, S.a , Lohse, K.b , Braun, R.c
a Gatsby Computational Neuroscience Unit, University College London, London, W1T 4JG, United Kingdom
b Physical Therapy and Neurology, Washington University School of Medicine, 4444 Forest Park Ave., Suite 1101, St. Louis, MO 63108-2212, United States
c Department of Neurology, University of Maryland School of Medicine, 655 W. Baltimore Street, Bressler Research Building, 12th Floor, on behalf of the GPAS Collaboration, Phenotyping Core, Baltimore, MD 21201, United States
Abstract
Stroke is a leading cause of neurological injury characterized by impairments in multiple neurological domains including cognition, language, sensory and motor functions. Clinical recovery in these domains is tracked using a wide range of measures that may be continuous, ordinal, interval or categorical in nature, which can present challenges for multivariate regression approaches. This has hindered stroke researchers’ ability to achieve an integrated picture of the complex time-evolving interactions among symptoms. Here, we use tools from network science and machine learning that are particularly well-suited to extracting underlying patterns in such data, and may assist in prediction of recovery patterns. To demonstrate the utility of this approach, we analyzed data from the NINDS tPA trial using the Trajectory Profile Clustering (TPC) method to identify distinct stroke recovery patterns for 11 different neurological domains at 5 discrete time points. Our analysis identified 3 distinct stroke trajectory profiles that align with clinically relevant stroke syndromes, characterized both by distinct clusters of symptoms, as well as differing degrees of symptom severity. We then validated our approach using graph neural networks to determine how well our model performed predictively for stratifying patients into these trajectory profiles at early vs. later time points post-stroke. We demonstrate that trajectory profile clustering is an effective method for identifying clinically relevant recovery subtypes in multidimensional longitudinal datasets, and for early prediction of symptom progression subtypes in individual patients. This paper is the first work introducing network trajectory approaches for stroke recovery phenotyping, and is aimed at enhancing the translation of such novel computational approaches for practical clinical application. © 2022, The Author(s).
Author Keywords
Disease subtyping; Graph neural networks; Network medicine; Network science; Stroke recovery
Document Type: Article
Publication Stage: Final
Source: Scopus
Imaging peripheral nerve micro-anatomy with MUSE, 2D and 3D approaches
(2022) Scientific Reports, 12 (1), art. no. 10205, .
Kolluru, C.a , Todd, A.b , Upadhye, A.R.a c , Liu, Y.a , Berezin, M.Y.d , Fereidouni, F.e , Levenson, R.M.e , Wang, Y.f , Shoffstall, A.J.a c , Jenkins, M.W.a g , Wilson, D.L.a f
a Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, United States
b University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, United States
c APT Center, Louis Stokes Cleveland VA Medical Center, Cleveland, OH 44106, United States
d Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, United States
e Department of Pathology and Laboratory Medicine, UC Davis Health, Sacramento, CA 95817, United States
f Department of Radiology, Case Western Reserve University, Cleveland, OH 44106, United States
g Department of Pediatrics, Case Western Reserve University, Cleveland, OH 44106, United States
Abstract
Understanding peripheral nerve micro-anatomy can assist in the development of safe and effective neuromodulation devices. However, current approaches for imaging nerve morphology at the fiber level are either cumbersome, require substantial instrumentation, have a limited volume of view, or are limited in resolution/contrast. We present alternative methods based on MUSE (Microscopy with Ultraviolet Surface Excitation) imaging to investigate peripheral nerve morphology, both in 2D and 3D. For 2D imaging, fixed samples are imaged on a conventional MUSE system either label free (via auto-fluorescence) or after staining with fluorescent dyes. This method provides a simple and rapid technique to visualize myelinated nerve fibers at specific locations along the length of the nerve and perform measurements of fiber morphology (e.g., axon diameter and g-ratio). For 3D imaging, a whole-mount staining and MUSE block-face imaging method is developed that can be used to characterize peripheral nerve micro-anatomy and improve the accuracy of computational models in neuromodulation. Images of rat sciatic and human cadaver tibial nerves are presented, illustrating the applicability of the method in different preclinical models. © 2022, The Author(s).
Funding details
National Institute of Biomedical Imaging and BioengineeringNIBIBR01EB028635
1OT2OD025340-01
National Institute of Biomedical Imaging and BioengineeringNIBIB
National Institutes of HealthNIH
National Cancer InstituteNCIR01CA208623
Document Type: Article
Publication Stage: Final
Source: Scopus
Normal aging in mice is associated with a global reduction in cortical spectral power and network-specific declines in functional connectivity
(2022) NeuroImage, 257, art. no. 119287, .
Albertson, A.J.a , Landsness, E.C.a , Tang, M.J.b , Yan, P.a , Miao, H.a , Rosenthal, Z.P.c , Kim, B.d , Culver, J.C.e f g h , Bauer, A.Q.e f , Lee, J.-M.a e f
a Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, United States
b Duke University School of Medicine, DUMC 3878, Durham, NC 27710, United States
c Medical Scientist Training Program, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, United States
d Boston University School of Medicine, 72 East Concord St., Boston, MA 02118, United States
e Department of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, United States
f Department of Biomedical Engineering, Washington University, 1 Brookings Drive, St. Louis, MO 63130, United States
g Department of Physics, Washington University, 1 Brookings Drive, St. Louis, MO 63130, United States
h Department of Electrical and Systems Engineering, Washington University, 1 Brookings Drive, St. Louis, MO 63130, United States
Abstract
Normal aging is associated with a variety of neurologic changes including declines in cognition, memory, and motor activity. These declines correlate with neuronal changes in synaptic structure and function. Degradation of brain network activity and connectivity represents a likely mediator of age-related functional deterioration resulting from these neuronal changes. Human studies have demonstrated both general decreases in spontaneous cortical activity and disruption of cortical networks with aging. Current techniques used to study cerebral network activity are hampered either by limited spatial resolution (e.g. electroencephalography, EEG) or limited temporal resolution (e.g., functional magnetic resonance imaging, fMRI). Here we utilize mesoscale imaging of neuronal activity in Thy1-GCaMP6f mice to characterize neuronal network changes in aging with high spatial resolution across a wide frequency range. We show that while evoked activity is unchanged with aging, spontaneous neuronal activity decreases across a wide frequency range (0.01–4 Hz) involving all regions of the cortex. In contrast to this global reduction in cortical power, we found that aging is associated with functional connectivity (FC) deterioration of select networks including somatomotor, cingulate, and retrosplenial nodes. These changes are corroborated by reductions in homotopic FC and node degree within somatomotor and visual cortices. Finally, we found that whole-cortex delta power and delta band node degree correlate with exploratory activity in young but not aged animals. Together these data suggest that aging is associated with global declines in spontaneous cortical activity and focal deterioration of network connectivity, and that these reductions may be associated with age-related behavioral declines. © 2022
Author Keywords
Aging; Cortex; Functional connectivity; GCaMP
Funding details
National Institutes of HealthNIHF31NS103275, K08-NS109292–01A1, K25-NS083754, P01NS080675, R01NS078223, R01NS084028, R01NS094692, R37NS110699, RO1-NS102870
American Heart AssociationAHA20CDA35310607, 20CDA35310845
McDonnell Center for Systems Neuroscience
Document Type: Article
Publication Stage: Final
Source: Scopus
Data-driven uncertainty quantification in computational human head models
(2022) Computer Methods in Applied Mechanics and Engineering, 398, art. no. 115108, .
Upadhyay, K.a b , Giovanis, D.G.c , Alshareef, A.d , Knutsen, A.K.e , Johnson, C.L.f , Carass, A.d , Bayly, P.V.g , Shields, M.D.c , Ramesh, K.T.a b
a Hopkins Extreme Materials Institute, Johns Hopkins University, Baltimore, MD 21218, United States
b Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, United States
c Department of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD 21218, United States
d Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, United States
e Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD 20814, United States
f Department of Biomedical Engineering, University of Delaware, Newark, DE 19716, United States
g Mechanical Engineering and Materials Science, Washington University in St. Louis, St. Louis, MO 63130, United States
Abstract
Computational models of the human head are promising tools for estimating the impact-induced response of the brain, and thus play an important role in the prediction of traumatic brain injury. The basic constituents of these models (i.e., model geometry, material properties, and boundary conditions) are often associated with significant uncertainty and variability. As a result, uncertainty quantification (UQ), which involves quantification of the effect of this uncertainty and variability on the simulated response, becomes critical to ensure reliability of model predictions. Modern biofidelic head model simulations are associated with very high computational cost and high-dimensional inputs and outputs, which limits the applicability of traditional UQ methods on these systems. In this study, a two-stage, data-driven manifold learning-based framework is proposed for UQ of computational head models. This framework is demonstrated on a 2D subject-specific head model, where the goal is to quantify uncertainty in the simulated strain fields (i.e., output), given variability in the material properties of different brain substructures (i.e., input). In the first stage, a data-driven method based on multi-dimensional Gaussian kernel-density estimation and diffusion maps is used to generate realizations of the input random vector directly from the available data. Computational simulations of a small number of realizations provide input–output pairs for training data-driven surrogate models in the second stage. The surrogate models employ nonlinear dimensionality reduction using Grassmannian diffusion maps, Gaussian process regression to create a low-cost mapping between the input random vector and the reduced solution space, and geometric harmonics models for mapping between the reduced space and the Grassmann manifold. It is demonstrated that the surrogate models provide highly accurate approximations of the computational model while significantly reducing the computational cost. Monte Carlo simulations of the surrogate models are used for uncertainty propagation. UQ of the strain fields highlights significant spatial variation in model uncertainty, and reveals key differences in uncertainty among commonly used strain-based brain injury predictor variables. © 2022 Elsevier B.V.
Author Keywords
Gaussian process regression; Grassmannian diffusion maps; Head injury model; Surrogate model; Traumatic Brain Injury (TBI); Uncertainty quantification
Funding details
National Institutes of HealthNIHU01 NS112120
National Institute of Neurological Disorders and StrokeNINDS
Document Type: Article
Publication Stage: Final
Source: Scopus
Classifying the Severity of Cubital Tunnel Syndrome: A Preoperative Grading System Incorporating Electrodiagnostic Parameters
(2022) Plastic and Reconstructive Surgery, 150 (1), pp. 115e-126e.
Power, H.A., Peters, B.R., Patterson, J.M.M., Padovano, W.M., Mackinnon, S.E.
From the Division of Plastic Surgery, Department of Surgery, University of Alberta; Division of Plastic and Reconstructive Surgery, Department of Surgery, Washington University School of Medicine; Division of Plastic and Reconstructive Surgery, Department of Surgery, Oregon Health & Science University; and Department of Orthopedic Surgery, University of North Carolina School of Medicine
Abstract
BACKGROUND: Current classifications for cubital tunnel syndrome have not been shown to reliably predict postoperative outcomes. In this article, the authors introduce a new classification that incorporates clinical and electrodiagnostic parameters, including compound muscle action potential amplitude, to classify the preoperative severity of cubital tunnel syndrome. The authors compare this to established classifications and evaluate its association with patient-rated improvement. METHODS: The authors reviewed 44 patients who were treated surgically for cubital tunnel syndrome. Patients were retrospectively classified using their proposed classification and the Akahori, McGowan-Goldberg, Dellon, and Gu classifications. Correlation of grades was assessed by Spearman coefficients and agreement was assessed by weighted kappa coefficients. Patient-reported impairment was assessed using the Disabilities of the Arm, Shoulder, and Hand questionnaire before and after surgery. RESULTS: The classifications tended to grade patients in a similar way, with Spearman coefficients of 0.60 to 0.85 ( p < 0.0001) and weighted kappa coefficients of 0.46 to 0.71 ( p < 0.0001). Preoperative Disabilities of the Arm, Shoulder, and Hand scores increased with severity grade for most classifications. In multivariable analysis, the authors’ classification predicted postoperative Disabilities of the Arm, Shoulder, and Hand score improvement, whereas established classifications did not. CONCLUSIONS: Established classifications are imperfect indicators of preoperative severity. The authors introduce a preoperative classification for cubital tunnel syndrome that incorporates electrodiagnostic findings in addition to classic signs and symptoms. CLINICAL QUESTION/LEVEL OF EVIDENCE: Diagnostic, III. Copyright © 2022 by the American Society of Plastic Surgeons.
Document Type: Article
Publication Stage: Final
Source: Scopus
Loss of Stathmin-2, a hallmark of TDP-43-associated ALS, causes motor neuropathy
(2022) Cell Reports, 39 (13), p. 111001.
Krus, K.L.a , Strickland, A.b , Yamada, Y.b , Devault, L.c , Schmidt, R.E.d , Bloom, A.J.e , Milbrandt, J.f , DiAntonio, A.g
a Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO 63110, USA; Medical Scientist Training Program, Washington University in St. Louis, St. Louis, MO 63110, USA
b Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA
c Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO 63110, USA
d Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63110, USA
e Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA; Needleman Center for Neurometabolism and Axonal Therapeutics, St. Louis, MO 63110, USA
f Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO 63110, USA; Needleman Center for Neurometabolism and Axonal Therapeutics, St. Louis, MO 63110, USA
g Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO 63110, USA; Needleman Center for Neurometabolism and Axonal Therapeutics, St. Louis, MO 63110, USA
Abstract
TDP-43 mediates proper Stathmin-2 (STMN2) mRNA splicing, and STMN2 protein is reduced in the spinal cord of most patients with amyotrophic lateral sclerosis (ALS). To test the hypothesis that STMN2 loss contributes to ALS pathogenesis, we generated constitutive and conditional STMN2 knockout mice. Constitutive STMN2 loss results in early-onset sensory and motor neuropathy featuring impaired motor behavior and dramatic distal neuromuscular junction (NMJ) denervation of fast-fatigable motor units, which are selectively vulnerable in ALS, without axon or motoneuron degeneration. Selective excision of STMN2 in motoneurons leads to similar NMJ pathology. STMN2 knockout heterozygous mice, which better model the partial loss of STMN2 protein found in patients with ALS, display a slowly progressive, motor-selective neuropathy with functional deficits and NMJ denervation. Thus, our findings strongly support the hypothesis that STMN2 reduction owing to TDP-43 pathology contributes to ALS pathogenesis. Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.
Author Keywords
axon degeneration; CP: Neuroscience; motor neuron; neurodegeneration; neuropathy; NMNAT2; SARM1; SCG-10; stathmin
Document Type: Article
Publication Stage: Final
Source: Scopus
Association of State Medicaid Expansion Status with Rates of Suicide among US Adults
(2022) JAMA Network Open, 5 (6), p. E2217228.
Patel, H.a , Barnes, J.b , Osazuwa-Peters, N.c d e , Bierut, L.J.a
a Department of Psychiatry, Washington University, School of Medicine in St Louis, 660 S Euclid Ave, St Louis, MO 63110, United States
b Department of Radiation Oncology, Washington University, School of Medicine in St Louis, St Louis, MO, United States
c Diversity, Equity, and Inclusion, JAMA Otolaryngology-Head and Neck Surgery, United States
d Department of Population Health Sciences, Duke University, School of Medicine, Durham, NC, United States
e Department of Head and Neck Surgery & Communication Sciences, Duke University, School of Medicine, Durham, NC, United States
Abstract
Importance: In the US, suicide is the 10th leading cause of death and a serious mental health emergency. National programs that address suicide list access to mental health care as key in prevention, and more large-scale policies are needed to improve access to mental health care and address this crisis. The Patient Protection and Affordable Care Act (ACA) Medicaid Expansion Program was implemented in several states with the goal of increasing access to the health care system. Objective: To compare changes in suicide rates in states that expanded Medicaid under the ACA vs states that did not. Design, Setting, and Participants: In this cross-sectional study, state-level mortality rates were obtained from the National Center for Health Statistics for US individuals aged 20 to 64 years from January 1, 2000, to December 31, 2018. Data analysis was performed from April 18, 2021, to April 15, 2022. Exposures: Changes in suicide mortality rates among nonelderly adults before and after Medicaid expansion in expansion and nonexpansion states were compared using adjusted difference-in-differences analyses via hierarchical bayesian linear regression. Main Outcomes and Measures: Suicide rates using death by suicide as the primary measure. Results: Of the total population at risk for suicide, 50.4% were female, 13.3% were Black, 79.5% were White, and 7.2% were of other races. The analytic data set contained suicide mortality data for 2907 state-age-year units covering the general US population. A total of 553912 deaths by suicide occurred during the study period, with most occurring in White (496219 [89.6%]) and male (429580 [77.6%]) individuals. There were smaller increases in the suicide rate after 2014 in Medicaid expansion (2.56 per 100000 increase) compared with nonexpansion states (3.10 per 100000 increase). In adjusted difference-in-differences analysis, a significant decrease of -0.40 (95% credible interval, -0.66 to -0.14) suicides per 100000 individuals was found, translating to 1818 suicides that were averted in 2015 to 2018. Conclusions and Relevance: In this cross-sectional study, although suicide rates increased in both groups, blunting of these rates occurred among nonelderly adults in the Medicaid expansion states compared with nonexpansion states. Because this difference may be linked to increased access to mental health care, policy makers should consider suicide prevention as a benefit of expanding access to health care. © 2022 EDP Sciences. All rights reserved.
Funding details
National Institute of Mental HealthNIMHK01 DE030916
National Institute on Drug AbuseNIDAR25 MH112473
National Institute of Dental and Craniofacial ResearchNIDCR
Document Type: Article
Publication Stage: Final
Source: Scopus
Primary Prevention of Stroke in Children with Sickle Cell Anemia in Nigeria: Protocol for a Mixed Methods Implementation Study in a Community Hospital
(2022) JMIR Research Protocols, 11 (6), art. no. e37927, .
Bello-Manga, H.a , Haliru, L.b , Ahmed, K.A.b , Tabari, A.M.c , Farouk, B.U.c , Bahago, G.Y.d , Kazaure, A.S.e , Muhammad, A.S.f , Gwarzo, S.A.f , Baumann, A.A.g , DeBaun, M.R.h , King, A.A.i
a Department of Hematology and Blood Transfusion, Barau Dikko Teaching Hospital, Kaduna State University, Kaduna, Nigeria
b Department of Pediatrics, Barau Dikko Teaching Hospital, Kaduna State University, Kaduna, Nigeria
c Department of Radiology, Barau Dikko Teaching Hospital, Kaduna State University, Kaduna, Nigeria
d Department of Nursing Services, Haematology Unit, Barau Dikko Teaching Hospital, Kaduna, Nigeria
e Department of Pharmaceutical Services, Barau Dikko Teaching Hopsital, Kaduna, Nigeria
f Research Office, Barau Dikko Teaching Hospital, Kaduna, Nigeria
g Department of Surgery, Washington University in St. Louis, St. Louis, MO, United States
h Department of Pediatrics, Division of Pediatric Neurology, Vanderbilt University School of Medicine, Nashville, TN, United States
i Program in Occupational Therapy, Department of Medicine, Pediatrics, Surgery, and Education, Washington University School of Medicine, St. Louis, MO, United States
Abstract
Background: In Nigeria, approximately 150,000 children with sickle cell anemia (SCA) are born annually, accounting for more than half of all SCA births worldwide. Without intervention, about 11% of children with SCA will develop a stroke before their 20th birthday. Evidence-based practices for primary stroke prevention include screening for abnormal transcranial Doppler (TCD) measurements coupled with regular blood transfusion therapy for at least one year, followed by hydroxyurea (HU) therapy indefinitely. In high-resource countries, this strategy contributes to a 92% decrease in stroke incidence rates. In 2016, as part of a capacity building objective of the Stroke Prevention Trial in Nigeria (1R01NS094041: SPRING), TCD screening was adopted as standard care at Barau Dikko Teaching Hospital in Kaduna. However, with just 70 radiologists and only 3 certified in TCD screening in the state, just 5.49% (1101/20,040) of eligible children with SCA were screened. Thus, there is a need to explore alternate implementation strategies to ensure children with SCA receive standard care TCD screening to decrease stroke incidence. Objective: This protocol describes a study to create a stroke prevention program in a community hospital in Kaduna through task shifting TCD screening to nurses and training medical officers to initiate and monitor HU utilization for stroke prevention. Methods: This study will be conducted at 2 sites (teaching hospital and community hospital) over a period of 3 years (November 2020 to November 2023), in 3 phases using both quasi-experimental and effectiveness-implementation study designs. In the needs assessment phase, focus groups and structured interviews will be conducted with health care providers and hospital administrators to identify barriers and facilitators to evidence-based stroke prevention practices. Results from the needs assessment will inform intervention strategies and a process plan to fit the needs of the community hospital. In the capacity building phase, nurses and medical officers at the community hospital will be trained on TCD screening and HU initiation and monitoring. In the implementation phase, children with SCA aged 2-16 years will be recruited into a nonrandomized single-arm prospective trial to determine the feasibility of initiating a task-shifted stroke prevention program by recording recruitment, retention, and adherence rates. The Reach and Effectiveness components of the RE-AIM (Reach, Effectiveness, Adoption, Implementation and Maintenance) framework will be used to evaluate implementation outcomes between the community and teaching hospitals. Results: The needs assessment phase of the study was completed in February 2021. Manuscript on findings is currently in preparation. Capacity building is ongoing with TCD training and sickle cell disease and stroke education sessions for nurses and doctors in the community hospital. Recruitment for the implementation trial is expected to commence in July 2022. Conclusions: This study proposes a structured, theory-driven approach to create a stroke prevention program in a community hospital in Kaduna, Nigeria, to decrease stroke incidence among children with SCA. Results will provide preliminary data for a definitive randomized clinical trial in implementation science. ©Halima Bello-Manga, Lawal Haliru, Kudrat Abdulkareem Ahmed, Abdulkadir Musa Tabari, Bilkisu Usman Farouk, Gloria Yimi Bahago, Aisha Shuaibu Kazaure, Abdulrasheed Sani Muhammad, Samira Abubakar Gwarzo, Ana A Baumann, Michael R DeBaun, Allison A King.
Author Keywords
sickle cell anemia; stroke prevention; transcranial Doppler ultrasonography
Funding details
National Institutes of HealthNIH1R01NS094041
Fogarty International CenterFIC
National Institute of Neurological Disorders and StrokeNINDS1 P50 MH122351-01A1, 1K24 HL14830, 1U24HL154426-01, 3D43TW011541-01S1, 3R01HD091218, 5U01HL133994-05, 5U24HL136790, K43TW011583, P50 CA-244431, UL1TR002345
Washington University School of Medicine in St. LouisWUSM
Document Type: Article
Publication Stage: Final
Source: Scopus
New Multi-Center Clinical Trial to Address Cochlear Implantation of Children with Asymmetric Hearing Loss or Single-Sided Deafness
(2022) Hearing Journal, 75 (6), pp. 12-14.
Firszt, J.B.a , Cadieux, J.b , Eisenberg, L.S.c , Germiller, J.A.d , Wolfe, J.e , Koeritzer, M.f
a Department of Otolaryngology, Washington University School of Medicine, St. Louis, United States
b St. Louis Children’s Hospital, Washington University, St. Louis, United States
c University of Southern California, United States
d Division of Otolaryngology, Children’s Hospital of Philadelphia, United States
e Hearts for Hearing Foundation in Oklahoma City, United States
f MN, United States
Funding details
National Institutes of HealthNIH
National Institute on Deafness and Other Communication DisordersNIDCD
Document Type: Article
Publication Stage: Final
Source: Scopus
Real-time motion monitoring improves functional MRI data quality in infants
(2022) Developmental Cognitive Neuroscience, 55, art. no. 101116, .
Badke D’Andrea, C.a b c , Kenley, J.K.d , Montez, D.F.d , Mirro, A.E.e , Miller, R.L.d , Earl, E.A.f , Koller, J.M.b , Sung, S.g h , Yacoub, E.i , Elison, J.T.g h , Fair, D.A.g h j , Dosenbach, N.U.F.c d e k l , Rogers, C.E.d , Smyser, C.D.c d e , Greene, D.J.a
a Department of Cognitive Science, University of California San Diego, La Jolla, CA 92093, United States
b Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
c Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
d Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
e Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, United States
f Data Science and Sharing Team, National Institute of Mental Health, NIH, DHHS, Bethesda, MD 20899, United States
g Institute of Child Development, College of Education and Human Development, University of Minnesota, Minneapolis, MN 55455, United States
h Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN 55455, United States
i Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN 55455, United States
j Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55455, United States
k Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, United States
l Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States
Abstract
Imaging the infant brain with MRI has improved our understanding of early neurodevelopment. However, head motion during MRI acquisition is detrimental to both functional and structural MRI scan quality. Though infants are typically scanned while asleep, they commonly exhibit motion during scanning causing data loss. Our group has shown that providing MRI technicians with real-time motion estimates via Framewise Integrated Real-Time MRI Monitoring (FIRMM) software helps obtain high-quality, low motion fMRI data. By estimating head motion in real time and displaying motion metrics to the MR technician during an fMRI scan, FIRMM can improve scanning efficiency. Here, we compared average framewise displacement (FD), a proxy for head motion, and the amount of usable fMRI data (FD ≤ 0.2 mm) in infants scanned with (n = 407) and without FIRMM (n = 295). Using a mixed-effects model, we found that the addition of FIRMM to current state-of-the-art infant scanning protocols significantly increased the amount of usable fMRI data acquired per infant, demonstrating its value for research and clinical infant neuroimaging. © 2022 The Authors
Author Keywords
Functional MRI; Head motion; Infant brain; Neurodevelopment; Neuroimaging
Funding details
National Institutes of HealthNIHK02 NS089852, P50 HD103525, R01 HD057098, R01 HD061619, R01 MH113570, R01 MH113883, R44MH121276, R44MH122066, R44MH123567
Dana FoundationDF
University of WashingtonUW
Document Type: Article
Publication Stage: Final
Source: Scopus
Does hearing loss affect the risk of involvement in a motor vehicle crash?
(2022) Journal of Transport and Health, art. no. 101387, .
Dow, J.a , Boucher, L.l , Carr, D.b , Charlton, J.c , Hill, L.d , Koppel, S.c , Lilly, R.e , Marottoli, R.f , O’Neill, D.g , Rapoport, M.h , Roy, C.a , Sévigny, B.i , Swirsky, N.j , Gagné, E.a , Giroux, C.a , Rader, T.k
a Société de l’assurance automobile du Québec, Canada
b Washington University in St. Louis, United States
c Monash University Accident Research Centre, Monash University, Australia
d University of California San Diego, United States
e Health Sciences Complex, St-John’s NL, Canada
f Yale University and VA Connecticut, United States
g Royal College of Physicians of Ireland, Dublin, Ireland
h Sunnybrook Hospital, Toronto, Canada
i Règie de l’assurance médicale du Québec, Canada
j University of Manitoba Faculty of Health Sciences, Winnipeg, Canada
k Canadian Medical Association Journal, Ottawa, Canada
l Centre hospitalier de l’université de Montréal, Canada
Abstract
Aim: This study systematically reviewed the literature on motor vehicle crash (MVC) risk for drivers with hearing loss in medicine, psychology, and transport databases, that quantify its effect on MVC to enable licensing agencies to make evidence-based decisions on fitness-to-drive hearing standards. Results: 1717 articles were identified of which 563 were duplicates. Twelve studies were retained for full-text review of which four published between 1968 and 2016 were judged to have met all the selection criteria. Three studies demonstrated no significant increase in MVC risk, while one reported a decrease in risk. Conclusions: Although the small number of studies that met all the inclusion criteria is a limitation, the expert panel concluded that the quality of the studies permitted the conclusion that the evidence does not support a relationship between hearing impairment and the risk of an MVC. Driver fitness standards recognise this fact implicitly in that none of the national fitness-to-drive standards selected for comparison applied licence restrictions to non-commercial drivers. © 2022
Author Keywords
Crash risk; Fitness to drive; Hearing impairment; Road safety
Funding details
Accident Research Centre, Monash UniversityMUARC
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Empowerment in people with Parkinson’s disease: A scoping review and qualitative interview study
(2022) Patient Education and Counseling, .
Kang, E.a , Friz, D.b , Lipsey, K.c , Foster, E.R.d
a Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO, United States
b Gynecology/Gynecologic Oncology, Barnes Jewish Hospital, St. Louis, MO, United States
c Bernard Becker Medical Library, Washington University School of Medicine, St. Louis, MO, United States
d Program in Occupational Therapy, Department of Neurology, & Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
Abstract
Objective: To synthesize empowerment definitions in Parkinson’s disease (PD) literature and understand people with PD’s perspective on empowerment in the context of an existing empowerment conceptual model. Methods: This mixed-methods study included a scoping review of PD empowerment literature and interviews with adults with PD. Five databases were searched for articles that defined empowerment concepts. We analyzed 1:1 semi-structured interviews on empowerment with people with PD. All data were analyzed using hybrid thematic analysis. Results: Eight of 242 records were included in this review. Empowerment is defined as an intrapersonal (e.g., personal control over oneself or healthcare) or interpersonal construct (e.g., person-centered care). Thirty-seven participants completed the interview. Participants perceived empowerment as a multifaceted concept that interacts with determinants and moderators from different ecological levels. Conclusion: Empowerment is a noteworthy multilevel and relational construct that can interplay with important health-related factors. The developed working conceptual model of empowerment can inform future studies to explore empowerment concepts in more depth and develop PD empowerment-based interventions. Practice implications: The empowerment definitions, indicators, determinants, and moderators identified in this study can help researchers, clinicians, and policymakers critically conceptualize empowerment and develop interventions to support people with PD. © 2022 Elsevier B.V.
Author Keywords
Empowerment; Mixed methods; Parkinson’s disease; Patient engagement; Patient-centered care; Qualitative research; Review; Therapeutic alliance
Funding details
National Institute of Neurological Disorders and StrokeNINDSR25NS100133
Washington University in St. LouisWUSTL
Document Type: Review
Publication Stage: Article in Press
Source: Scopus
Moderation Effects in Personality Disorder Research
(2022) Personality Disorders: Theory, Research, and Treatment, .
Vize, C.E.a , Baranger, D.A.A.b , Finsaas, M.C.c , Goldstein, B.L.d , Olino, T.M.e , Lynam, D.R.f
a Department of Psychiatry, University of Pittsburgh, United States
b Department of Psychiatry, Washington University in St. Louis, United States
c Department of Psychiatry, Columbia University, United States
d Department of Psychiatry, University of Connecticut, United States
e Department of Psychology and Neuroscience, Temple University, United States
f Department of Psychological Sciences, Purdue University, United States
Abstract
Tests of statistical interactions (or tests of moderation effects) in personality disorder research are a common way for researchers to examine nuanced hypotheses relevant to personality pathology. However, the nature of statistical interactions makes them difficult to reliably detect in many research scenarios. The present study used a flexible, simulation-based approach to estimate statistical power to detect trait-by-trait interactions common to psychopathy research using the Triarchic model of Psychopathy and the Psychopathic Personality Inventory. Our results show that even above-average sample sizes in these literatures (e.g., N = 428) provide inadequate power to reliably detect trait-by-trait interactions, and the sample sizes needed to detect interaction effect sizes in realistic scenarios are extremely large, ranging from 1,300 to 5,200. The implications for trait-by-trait interactions in psychopathy are discussed, as well as how the present findings might generalize to other areas of personality disorder research. We provide recommendations for how to design research studies that can provide informative tests of interactions in personality disorder research, but also highlight that a more realistic option is to abandon the traditional approach when testing for interaction effects and adopt alternative approaches that may be more productive. © 2022. American Psychological Association
Author Keywords
Moderation; Power analysis; Psychopathy; Statistical interaction; Statistical power
Funding details
National Institute of Mental HealthNIMHR01-MH107495, T32-MH013043, T32-MH018269, T32-MH018951
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Quantifying Patient Investment in Novel Neurological Drug Development
(2022) Neurotherapeutics, .
MacPherson, A.a , Gumnit, E.a , Ouimet, C.a , Hutchinson, N.a , Kieburtz, K.b , Pearson, T.S.c , Kimmelman, J.a
a Department of Equity, Ethics and Policy, McGill University School of Population and Global Health, 2001 McGill College Avenue, Montreal, QC, H3A 1G1, Canada
b Department of Neurology, University of Rochester, Rochester, NY, United States
c Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
Abstract
While the drug development literature provides numerous estimates of the financial costs to bring a new drug to market, the investment of patient-participants in the research process has not been described. Trial participants and their caregivers, like companies, invest time and undertake risk when they participate in prelicense trials. We determined the average number of patient-participants needed to develop a novel neurological drug. We created a cohort of 108 unapproved drugs first tested for efficacy between 2006 and 2011 and used ClinicalTrials.gov to capture enrollment in all subsequent prelicense trials of these drugs over a 9-year period. Our primary outcome was the average number of patients enrolled in prelicense neurological drug trials per drug that ultimately attained FDA approval, including patients who participated in both successful and unsuccessful development efforts. Five drugs (4.6%) were FDA approved, and 66,751 patient-participants were enrolled across successful and unsuccessful drug development efforts, resulting in an average of 13,350 patients for each drug attaining approval (95% CI 7155 to 54,954). Our estimates reveal the substantial amount patients and their caregivers contribute to private drug development. © 2022, The American Society for Experimental NeuroTherapeutics, Inc.
Author Keywords
Clinical trials; CNS disorders; Drug development; Research ethics
Funding details
Canadian Institutes of Health ResearchIRSC
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
A tissue-fraction estimation-based segmentation method for quantitative dopamine transporter SPECT
(2022) Medical Physics, .
Liu, Z.a , Moon, H.S.a , Li, Z.a , Laforest, R.b , Perlmutter, J.S.b c , Norris, S.A.b c , Jha, A.K.a b
a Department of Biomedical Engineering, Washington University, St. Louis, MO, United States
b Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
c Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
Abstract
Background: Quantitative measures of dopamine transporter (DaT) uptake in caudate, putamen, and globus pallidus (GP) derived from dopamine transporter–single-photon emission computed tomography (DaT-SPECT) images have potential as biomarkers for measuring the severity of Parkinson’s disease. Reliable quantification of this uptake requires accurate segmentation of the considered regions. However, segmentation of these regions from DaT-SPECT images is challenging, a major reason being partial-volume effects (PVEs) in SPECT. The PVEs arise from two sources, namely the limited system resolution and reconstruction of images over finite-sized voxel grids. The limited system resolution results in blurred boundaries of the different regions. The finite voxel size leads to TFEs, that is, voxels contain a mixture of regions. Thus, there is an important need for methods that can account for the PVEs, including the TFEs, and accurately segment the caudate, putamen, and GP, from DaT-SPECT images. Purpose: Design and objectively evaluate a fully automated tissue-fraction estimation-based segmentation method that segments the caudate, putamen, and GP from DaT-SPECT images. Methods: The proposed method estimates the posterior mean of the fractional volumes occupied by the caudate, putamen, and GP within each voxel of a three-dimensional DaT-SPECT image. The estimate is obtained by minimizing a cost function based on the binary cross-entropy loss between the true and estimated fractional volumes over a population of SPECT images, where the distribution of true fractional volumes is obtained from existing populations of clinical magnetic resonance images. The method is implemented using a supervised deep-learning-based approach. Results: Evaluations using clinically guided highly realistic simulation studies show that the proposed method accurately segmented the caudate, putamen, and GP with high mean Dice similarity coefficients of ∼ 0.80 and significantly outperformed ((Formula presented.)) all other considered segmentation methods. Further, an objective evaluation of the proposed method on the task of quantifying regional uptake shows that the method yielded reliable quantification with low ensemble normalized root mean square error (NRMSE) < 20% for all the considered regions. In particular, the method yielded an even lower ensemble NRMSE of ∼ 10% for the caudate and putamen. Conclusions: The proposed tissue-fraction estimation-based segmentation method for DaT-SPECT images demonstrated the ability to accurately segment the caudate, putamen, and GP, and reliably quantify the uptake within these regions. The results motivate further evaluation of the method with physical-phantom and patient studies. © 2022 American Association of Physicists in Medicine.
Author Keywords
objective task-based evaluation; parkinson’s disease; partial-volume effects; quantification; segmentation; single-photon emission computed tomography; tissue-fraction effects
Funding details
National Institute of Biomedical Imaging and BioengineeringNIBIBR01‐EB031051, R01‐NS124789, R21‐EB024647, R56‐EB028287
Dystonia Medical Research FoundationDMRF
American Parkinson Disease AssociationAPDA
Foundation for Barnes-Jewish HospitalFBJH
Document Type: Article
Publication Stage: Article in Press
Source: Scopus