Faculty Bibliography
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Curation of BIDS (CuBIDS): A workflow and software package for streamlining reproducible curation of large BIDS datasets
The Brain Imaging Data Structure (BIDS) is a specification accompanied by a software ecosystem that was designed to create reproducible and automated workflows for processing neuroimaging data. BIDS Apps flexibly build workflows based on the metadata detected in a dataset. However, even BIDS valid metadata can include incorrect values or omissions that result in inconsistent processing across sessions. Additionally, in large-scale, heterogeneous neuroimaging datasets, hidden variability in metadata is difficult to detect and classify. To address these challenges, we created a Python-based software package titled "Curation of BIDS" (CuBIDS), which provides an intuitive workflow that helps users validate and manage the curation of their neuroimaging datasets. CuBIDS includes a robust implementation of BIDS validation that scales to large samples and incorporates DataLad--a version control software package for data--as an optional dependency to ensure reproducibility and provenance tracking throughout the entire curation process. CuBIDS provides tools to help users perform quality control on their images' metadata and identify unique combinations of imaging parameters. Users can then execute BIDS Apps on a subset of participants that represent the full range of acquisition parameters that are present, accelerating pipeline testing on large datasets.
PMID: 36064140
ISSN: 1095-9572
CID: 5332322
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.
PMCID:9203460
PMID: 35710678
ISSN: 2052-4463
CID: 5277912
A longitudinal resource for studying connectome development and its psychiatric associations during childhood
Most psychiatric disorders are chronic, associated with high levels of disability and distress, and present during pediatric development. Scientific innovation increasingly allows researchers to probe brain-behavior relationships in the developing human. As a result, ambitions to (1) establish normative pediatric brain development trajectories akin to growth curves, (2) characterize reliable metrics for distinguishing illness, and (3) develop clinically useful tools to assist in the diagnosis and management of mental health and learning disorders have gained significant momentum. To this end, the NKI-Rockland Sample initiative was created to probe lifespan development as a large-scale multimodal dataset. The NKI-Rockland Sample Longitudinal Discovery of Brain Development Trajectories substudy (N = 369) is a 24- to 30-month multi-cohort longitudinal pediatric investigation (ages 6.0-17.0 at enrollment) carried out in a community-ascertained sample. Data include psychiatric diagnostic, medical, behavioral, and cognitive phenotyping, as well as multimodal brain imaging (resting fMRI, diffusion MRI, morphometric MRI, arterial spin labeling), genetics, and actigraphy. Herein, we present the rationale, design, and implementation of the Longitudinal Discovery of Brain Development Trajectories protocol.
PMCID:9197863
PMID: 35701428
ISSN: 2052-4463
CID: 5277832
Zika virus congenital microcephaly severity classification and the association of severity with neuropsychomotor development
BACKGROUND:Zika virus infection during pregnancy is linked to birth defects, most notably microcephaly, which is associated with neurodevelopmental delays. OBJECTIVE:The goals of the study were to propose a method for severity classification of congenital microcephaly based on neuroradiologic findings of MRI scans, and to investigate the association of severity with neuropsychomotor developmental scores. We also propose a semi-automated method for MRI-based severity classification of microcephaly. MATERIALS AND METHODS/METHODS:We conducted a cross-sectional investigation of 42 infants born with congenital Zika infection. Bayley Scales of Infant and Toddler Development III (Bayley-III) developmental evaluations and MRI scans were carried out at ages 13-39Â months (mean: 24.8Â months; standard deviation [SD]: 5.8Â months). The severity score was generated based on neuroradiologist evaluations of brain malformations. Next, we established a distribution of Zika virus-microcephaly severity score including mild, moderate and severe and investigated the association of severity with neuropsychomotor developmental scores. Finally, we propose a simplified semi-automated procedure for estimating the severity score based only on volumetric measures. RESULTS:The results showed a correlation of r=0.89 (P<0.001) between the Zika virus-microcephaly severity score and the semi-automated method. The trimester of infection did not correlate with the semi-automated method. Neuropsychomotor development correlated with the severity classification based on the radiologic readings and semi-automated method; the more severe the imaging scores, the lower the neuropsychomotor developmental scores. CONCLUSION/CONCLUSIONS:These severity classification methods can be used to evaluate severity of microcephaly and possible association with developmental consequences. The semi-automated methods thus provide an alternative for predicting severity of microcephaly based on only one MRI sequence.
PMID: 35229185
ISSN: 1432-1998
CID: 5174292
Sex differences in brain regional homogeneity during acute abstinence in cocaine use disorder
There are significant sex differences in the clinical characteristics of cocaine use disorder (CUD). As this is a brain disorder that involves changes in functional connectivity, we investigated the existence of sex differences among people with CUD and controls. We used a data-driven method comparing males (n = 20, CK-M) and females with CUD (n = 20, CK-F) and healthy controls (20 males, HC-M and 20 females, HC-F). The participants undertook a resting-state functional magnetic resonance imaging exam. Regional homogeneity (ReHo) was performed to identify group and sex differences. Persons with CUD of both sexes presented lower ReHo parameters than controls, especially within the parietal lobule. Males with CUD showed higher ReHo than females in three right-side brain areas: postcentral gyrus, putamen and fusiform gyrus. It was found that abstinence symptoms severity was associated with lower ReHo values in the right postcentral gyrus and the right fusiform gyrus. Participants with CUD exhibited altered ReHo parameters compared to controls, similar to what is found in ageing-related disorders. Our data also indicate that cocaine has sex-specific effects on brain functioning when analysing ReHo.
PMID: 35470550
ISSN: 1369-1600
CID: 5216982
Toward next-generation primate neuroscience: A collaboration-based strategic plan for integrative neuroimaging
Open science initiatives are creating opportunities to increase research coordination and impact in nonhuman primate (NHP) imaging. The PRIMatE Data and Resource Exchange community recently developed a collaboration-based strategic plan to advance NHP imaging as an integrative approach for multiscale neuroscience.
PMID: 34731649
ISSN: 1097-4199
CID: 5499342
Cortical thickness and subcortical volume abnormalities in male crack-cocaine users
Crack-cocaine offers a higher risk of abuse than intranasal and intravenous use of cocaine. Yet, current treatments remain disappointing and our understanding of the mechanism of crack-cocaine neurotoxicity is still incomplete. Magnetic resonance images studies on brain changes of crack-cocaine addicts show divergent data. The present study investigated gray matter (GM) abnormalities in crack-cocaine dependents (n = 18) compared to healthy controls (n = 17). MRI data was analysed using FreeSurfer and voxel-based morphometry (VBM). FreeSurfer analysis showed that CD had decreased cortical thickness (CT) in the left inferior temporal cortex (lTC), left orbitofrontal cortex (lOFC) and left rostro frontal cortex (lRFC), enlargement in left inferior lateral ventricle, and smaller GM volume in right hippocampus and right ventral diencephalon. VBM analysis showed that CD had significantly decreased GM volume in left Putamen and left nucleus accumbens. Furthermore, we found a negative correlation between duration of crack-cocaine use and lTC CT. These results provide compelling evidence for GM abnormalities in CD and also suggest that duration of crack-cocaine use may be associated with CT alterations.
PMID: 33621927
ISSN: 1872-7506
CID: 4835682
White matter deficits in cocaine use disorder: convergent evidence from in vivo diffusion tensor imaging and ex vivo proteomic analysis
White matter (WM) abnormalities in patients with cocaine use disorder (CUD) have been studied; however, the reported effects on the human brain are heterogenous and most results have been obtained from male participants. In addition, biological data supporting the imaging findings and revealing possible mechanisms underlying the neurotoxic effects of chronic cocaine use (CU) on WM are largely restricted to animal studies. To evaluate the neurotoxic effects of CU in the WM, we performed an in vivo diffusion tensor imaging assessment of male and female cocaine users (n = 75) and healthy controls (HC) (n = 58). Moreover, we performed an ex vivo large-scale proteomic analysis using liquid chromatography-tandem mass spectrometry in postmortem brains of patients with CUD (n = 8) and HC (n = 12). Compared with the HC, the CUD group showed significant reductions in global fractional anisotropy (FA) (p < 0.001), and an increase in global mean (MD) and radial diffusion (RD) (both p < 0.001). The results revealed that FA, RD, and MD alterations in the CUD group were widespread along the major WM tracts, after analysis using the tract-based special statistics approach. Global FA was negatively associated with years of CU (p = 0.0421) and female sex (p < 0.001), but not with years of alcohol or nicotine use. Concerning the fibers connecting the left to the right prefrontal cortex, Brodmann area 9 (BA9), the CUD group presented lower FA (p = 0.006) and higher RD (p < 0.001) values compared with the HC group. A negative association between the duration of CU in life and FA values in this tract was also observed (p = 0.019). Proteomics analyses in BA9 found 11 proteins differentially expressed between cocaine users and controls. Among these, were proteins related to myelination and neuroinflammation. In summary, we demonstrate convergent evidence from in vivo diffusion tensor imaging and ex vivo proteomics analysis of WM disruption in CUD.
PMCID:8081729
PMID: 33911068
ISSN: 2158-3188
CID: 4858852
Journal of the American Academy of Child and Adolescent Psychiatry. 2021:60(2):222-235.DOI: 10.1016/j.jaac.2020.10.013
Systematic Review: Medication Effects on Brain Intrinsic Functional Connectivity in Patients With Attention-Deficit/Hyperactivity Disorder
OBJECTIVE:Resting-state fMRI (R-fMRI) studies of the neural correlates of medication treatment in attention-deficit/hyperactivity disorder (ADHD) have not been systematically reviewed. Systematically identify, assess and summarize within-patient R-fMRI studies of pharmacological-induced changes in patients with ADHD. We critically appraised strengths and limitations, and provide recommendations for future research. METHOD/METHODS:Systematic review of published original reports in English meeting criteria in pediatric and adult patients with ADHD up to July 1, 2020. A thorough search preceded selection of studies matching prespecified criteria. Strengths and limitations of selected studies, regarding design and reporting, were identified based on current best practices. RESULTS:We identified and reviewed 9 studies (5 pediatric and 4 adult studies). Sample sizes were small-medium (16-38 patients), and included few female participants. Medications were methylphenidate, amphetamines, and atomoxetine. Wide heterogeneity was observed in designs, analyses and results, which could not be combined quantitatively. Qualitatively, the multiplicity of brain regions and networks identified, some of which correlated with clinical improvements, do not support a coherent mechanistic hypothesis of medication effects. Overall, reports did not meet current standards to ensure reproducibility. CONCLUSION/CONCLUSIONS:In this emerging field, the few studies using R-fMRI to analyze the neural correlates of medications in patients with ADHD suggest a potential modulatory effect of stimulants and atomoxetine on several intrinsic brain activity metrics. However, methodological heterogeneity and reporting issues need to be addressed in future research to validate findings which may contribute to clinical care. Such a goal is not yet at hand.
PMID: 33137412
ISSN: 1527-5418
CID: 4655932
Resting-State fMRI to Identify the Brain Correlates of Treatment Response to Medications in Children and Adolescents With Attention-Deficit/Hyperactivity Disorder: Lessons From the CUNMET Study
Neuroimaging research seeks to identify biomarkers to improve the diagnosis, prognosis, and treatment of attention-deficit/hyperactivity disorder (ADHD), although clinical translation of findings remains distant. Resting-state functional magnetic resonance imaging (R-fMRI) is increasingly being used to characterize functional connectivity in the brain. Despite mixed results to date and multiple methodological challenges, dominant hypotheses implicate hyperconnectivity across brain networks in patients with ADHD, which could be the target of pharmacological treatments. We describe the experience and results of the ClÃnica Universidad de Navarra (Spain) Metilfenidato (CUNMET) pilot study. CUNMET tested the feasibility of identifying R-fMRI markers of clinical response in children with ADHD undergoing naturalistical pharmacological treatments. We analyzed cross-sectional data from 56 patients with ADHD (18 treated with methylphenidate, 18 treated with lisdexamfetamine, and 20 treatment-naive patients). Standard preprocessing and statistical analyses with attention to control for head motion and correction for multiple comparisons were performed. The only results that survived correction were noted in contrasts of children who responded clinically to lisdexamfetamine after long-term treatment vs. treatment-naive patients. In these children, we observed stronger negative correlations (anticorrelations) across nodes in six brain networks, which is consistent with higher across-network functional segregation in patients treated with lisdexamfetamine, i.e., less inter-network interference than in treatment-naive patients. We also note the lessons learned, which could help those pursuing clinically relevant multidisciplinary research in ADHD en route to eventual personalized medicine. To advance reproducible open science, our report is accompanied with links providing access to our data and analytic scripts.
PMCID:8635006
PMID: 34867544
ISSN: 1664-0640
CID: 5110082
