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Age, Motion, Medical, and Psychiatric Associations With Incidental Findings in Brain MRI

Tobe, Russell H; Tu, Lucia; Roberts, Maya; Kiar, Gregory; Breland, Melissa M; Tian, Yiwen; Kang, Minji; Ross, Rachel; Ryan, Margaret M; Valenza, Emmanuel; Alexander, Lindsay; MacKay-Brandt, Anna; Colcombe, Stanley J; Franco, Alexandre R; Milham, Michael P
IMPORTANCE/UNASSIGNED:Few investigations have evaluated rates of brain-based magnetic resonance imaging (MRI) incidental findings (IFs) in large lifespan samples, their stability over time, or their associations with health outcomes. OBJECTIVES/UNASSIGNED:To examine rates of brain-based IFs across the lifespan, their persistence, and their associations with phenotypic indicators of behavior, cognition, and health; to compare quantified motion with radiologist-reported motion and evaluate its associations with IF rates; and to explore IF consistency across multiple visits. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This cross-sectional study included participants from the Nathan Kline Institute-Rockland Sample (NKI-RS), a lifespan community-ascertained sample, and the Healthy Brain Network (HBN), a cross-sectional community self-referred pediatric sample focused on mental health and learning disorders. The NKI-RS enrolled participants (ages 6-85 years) between March 2012 and March 2020 and had longitudinal participants followed up for as long as 4 years. The HBN enrolled participants (ages 5-21 years) between August 2015 and October 2021. Clinical neuroradiology MRI reports were coded for radiologist-reported motion as well as presence, type, and clinical urgency (category 1, no abnormal findings; 2, no referral recommended; 3, consider referral; and 4, immediate referral) of IFs. MRI reports were coded from June to October 2021. Data were analyzed from November 2021 to February 2023. MAIN OUTCOMES AND MEASURES/UNASSIGNED:Rates and type of IFs by demographic characteristics, health phenotyping, and motion artifacts; longitudinal stability of IFs; and Euler number in projecting radiologist-reported motion. RESULTS/UNASSIGNED:A total of 1300 NKI-RS participants (781 [60.1%] female; mean [SD] age, 38.9 [21.8] years) and 2772 HBN participants (976 [35.2%] female; mean [SD] age, 10.0 [3.5] years) had health phenotyping and neuroradiology-reviewed MRI scans. IFs were common, with 284 of 2956 children (9.6%) and 608 of 1107 adults (54.9%) having IFs, but rarely of clinical concern (category 1: NKI-RS, 619 [47.6%]; HBN, 2561 [92.4%]; category 2: NKI-RS, 647 [49.8%]; HBN, 178 [6.4%]; category 3: NKI-RS, 79 [6.1%]; HBN, 30 [1.1%]; category 4: NKI-RS: 12 [0.9%]; HBN, 6 [0.2%]). Overall, 46 children (1.6%) and 79 adults (7.1%) required referral for their IFs. IF frequency increased with age. Elevated blood pressure and BMI were associated with increased T2 hyperintensities and age-related cortical atrophy. Radiologist-reported motion aligned with Euler-quantified motion, but neither were associated with IF rates. CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this cross-sectional study, IFs were common, particularly with increasing age, although rarely clinically significant. While T2 hyperintensity and age-related cortical atrophy were associated with BMI and blood pressure, IFs were not associated with other behavioral, cognitive, and health phenotyping. Motion may not limit clinical IF detection.
PMCID:10865144
PMID: 38349653
ISSN: 2574-3805
CID: 5635302

The cortical thickness of tricenarian cocaine users assembles features of an octogenarian brain

Rothmann, Leonardo Melo; Tondo, Lucca Pizzato; Borelli, Wyllians Vendramini; Esper, Nathalia Bianchini; Portolan, Eduardo Tavares; Franco, Alexandre Rosa; Portuguez, Mirna Wetters; Ferreira, Pedro Eugênio; Bittencourt, Augusto Martins Lucas; Soder, Ricardo Bernardi; Viola, Thiago Wendt; da Costa, Jaderson Costa; Grassi-Oliveira, Rodrigo
It has been suggested that substance use disorders could lead to accelerated biological aging, but only a few neuroimaging studies have investigated this hypothesis so far. In this cross-sectional study, structural neuroimaging was performed to measure cortical thickness (CT) in tricenarian adults with cocaine use disorder (CUD, n1 = 30) and their age-paired controls (YC, n1 = 30), and compare it with octogenarian elder controls (EC, n1 = 20). We found that CT in the right fusiform gyrus was similar between CUD and EC, thinner than the expected values of YC. We also found that regarding CT of the right inferior temporal gyrus, right inferior parietal cortex, and left superior parietal cortex, the CUD group exhibited parameters that fell in between EC and YC groups. Finally, CT of the right pars triangularis bordering with orbitofrontal gyrus, right superior temporal gyrus, and right precentral gyrus were reduced in CUD when contrasted with YC, but those areas were unrelated to CT of EC. Despite the 50-year age gap between our age groups, CT of tricenarian cocaine users assembles features of an octogenarian brain, reinforcing the accelerated aging hypothesis in CUD.
SCOPUS:85181216053
ISSN: 0360-4012
CID: 5630362

The cortical thickness of tricenarian cocaine users assembles features of an octogenarian brain

Rothmann, Leonardo Melo; Tondo, Lucca Pizzato; Borelli, Wyllians Vendramini; Esper, Nathalia Bianchini; Portolan, Eduardo Tavares; Franco, Alexandre Rosa; Portuguez, Mirna Wetters; Ferreira, Pedro Eugênio; Bittencourt, Augusto Martins Lucas; Soder, Ricardo Bernardi; Viola, Thiago Wendt; da Costa, Jaderson Costa; Grassi-Oliveira, Rodrigo
It has been suggested that substance use disorders could lead to accelerated biological aging, but only a few neuroimaging studies have investigated this hypothesis so far. In this cross-sectional study, structural neuroimaging was performed to measure cortical thickness (CT) in tricenarian adults with cocaine use disorder (CUD, n1  = 30) and their age-paired controls (YC, n1  = 30), and compare it with octogenarian elder controls (EC, n1  = 20). We found that CT in the right fusiform gyrus was similar between CUD and EC, thinner than the expected values of YC. We also found that regarding CT of the right inferior temporal gyrus, right inferior parietal cortex, and left superior parietal cortex, the CUD group exhibited parameters that fell in between EC and YC groups. Finally, CT of the right pars triangularis bordering with orbitofrontal gyrus, right superior temporal gyrus, and right precentral gyrus were reduced in CUD when contrasted with YC, but those areas were unrelated to CT of EC. Despite the 50-year age gap between our age groups, CT of tricenarian cocaine users assembles features of an octogenarian brain, reinforcing the accelerated aging hypothesis in CUD.
PMID: 38284862
ISSN: 1097-4547
CID: 5627812

An open-access dataset of naturalistic viewing using simultaneous EEG-fMRI

Telesford, Qawi K; Gonzalez-Moreira, Eduardo; Xu, Ting; Tian, Yiwen; Colcombe, Stanley J; Cloud, Jessica; Russ, Brian E; Falchier, Arnaud; Nentwich, Maximilian; Madsen, Jens; Parra, Lucas C; Schroeder, Charles E; Milham, Michael P; Franco, Alexandre R
In this work, we present a dataset that combines functional magnetic imaging (fMRI) and electroencephalography (EEG) to use as a resource for understanding human brain function in these two imaging modalities. The dataset can also be used for optimizing preprocessing methods for simultaneously collected imaging data. The dataset includes simultaneously collected recordings from 22 individuals (ages: 23-51) across various visual and naturalistic stimuli. In addition, physiological, eye tracking, electrocardiography, and cognitive and behavioral data were collected along with this neuroimaging data. Visual tasks include a flickering checkerboard collected outside and inside the MRI scanner (EEG-only) and simultaneous EEG-fMRI recordings. Simultaneous recordings include rest, the visual paradigm Inscapes, and several short video movies representing naturalistic stimuli. Raw and preprocessed data are openly available to download. We present this dataset as part of an effort to provide open-access data to increase the opportunity for discoveries and understanding of the human brain and evaluate the correlation between electrical brain activity and blood oxygen level-dependent (BOLD) signals.
PMCID:10447527
PMID: 37612297
ISSN: 2052-4463
CID: 5596052

Enhancing collaborative neuroimaging research: introducing COINSTAC Vaults for federated analysis and reproducibility

Martin, Dylan; Basodi, Sunitha; Panta, Sandeep; Rootes-Murdy, Kelly; Prae, Paul; Sarwate, Anand D; Kelly, Ross; Romero, Javier; Baker, Bradley T; Gazula, Harshvardhan; Bockholt, Jeremy; Turner, Jessica A; Esper, Nathalia B; Franco, Alexandre R; Plis, Sergey; Calhoun, Vince D
Collaborative neuroimaging research is often hindered by technological, policy, administrative, and methodological barriers, despite the abundance of available data. COINSTAC (The Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation) is a platform that successfully tackles these challenges through federated analysis, allowing researchers to analyze datasets without publicly sharing their data. This paper presents a significant enhancement to the COINSTAC platform: COINSTAC Vaults (CVs). CVs are designed to further reduce barriers by hosting standardized, persistent, and highly-available datasets, while seamlessly integrating with COINSTAC's federated analysis capabilities. CVs offer a user-friendly interface for self-service analysis, streamlining collaboration, and eliminating the need for manual coordination with data owners. Importantly, CVs can also be used in conjunction with open data as well, by simply creating a CV hosting the open data one would like to include in the analysis, thus filling an important gap in the data sharing ecosystem. We demonstrate the impact of CVs through several functional and structural neuroimaging studies utilizing federated analysis showcasing their potential to improve the reproducibility of research and increase sample sizes in neuroimaging studies.
PMID: 37404336
ISSN: 1662-5196
CID: 5539162

Cingulate cortical thickness in cocaine use disorder: mediation effect between early life stress and cocaine consumption

Bittencourt, Augusto Martins Lucas; Silveira, Bárbara Luiza Belmonte da; Tondo, Lucca Pizzato; Rothmann, Leonardo Melo; Franco, Alexandre Rosa; Ferreira, Pedro Eugenio Mazzucchi Santana; Viola, Thiago Wendt; Grassi-Oliveira, Rodrigo
OBJECTIVE:The cingulate gyrus is implicated in the neurobiology of addiction, such as chronic cocaine consumption. Early life stress (ELS) is an important moderator of cocaine use disorder (CUD). Therefore, we investigated the effect of CUD on cingulate cortical thickness and tested whether a history of ELS could influence the effects of CUD. METHODS:Participants aged 18-50 years (78 with CUD due to crack cocaine consumption and 53 healthy controls) underwent magnetic resonance imaging and the cingulate thickness (rostral anterior, caudal anterior, posterior, and isthmus regions) was analysed. The clinical assessment comprised the Childhood Trauma Questionnaire (CTQ) and the Addiction Severity Index. Group comparisons adjusting by sex, age, and education were performed. Mediation models were generated where lifetime cocaine use, CTQ score, and cortical thickness corresponded to the independent variable, intermediary variable, and outcome, respectively. RESULTS:Group comparisons revealed significant differences in six out of eight cingulate cortices, showing lower thickness in the CUD group. Furthermore, years of regular cocaine use was the variable most associated with cingulate thickness. Negative correlations were found between CTQ scores and the isthmus cingulate (right hemisphere), as well as with the rostral anterior cingulate (left hemisphere). In the mediation analysis, we observed a significant negative direct effect of lifetime cocaine use on the isthmus cingulate and an indirect effect of cocaine use mediated by CTQ score. CONCLUSION/CONCLUSIONS:Our findings suggest that a history of ELS could aggravate the negative effects of chronic cocaine use on the cingulate gyrus, particularly in the right isthmus cingulate cortex.
PMID: 36416534
ISSN: 1601-5215
CID: 5394202

Curation of BIDS (CuBIDS): A workflow and software package for streamlining reproducible curation of large BIDS datasets

Covitz, Sydney; Tapera, Tinashe M; Adebimpe, Azeez; Alexander-Bloch, Aaron F; Bertolero, Maxwell A; Feczko, Eric; Franco, Alexandre R; Gur, Raquel E; Gur, Ruben C; Hendrickson, Timothy; Houghton, Audrey; Mehta, Kahini; Murtha, Kristin; Perrone, Anders J; Robert-Fitzgerald, Tim; Schabdach, Jenna M; Shinohara, Russell T; Vogel, Jacob W; Zhao, Chenying; Fair, Damien A; Milham, Michael P; Cieslak, Matthew; Satterthwaite, Theodore D
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

Liew, Sook-Lei; Lo, Bethany P; Donnelly, Miranda R; Zavaliangos-Petropulu, Artemis; Jeong, Jessica N; Barisano, Giuseppe; Hutton, Alexandre; Simon, Julia P; Juliano, Julia M; Suri, Anisha; Wang, Zhizhuo; Abdullah, Aisha; Kim, Jun; Ard, Tyler; Banaj, Nerisa; Borich, Michael R; Boyd, Lara A; Brodtmann, Amy; Buetefisch, Cathrin M; Cao, Lei; Cassidy, Jessica M; Ciullo, Valentina; Conforto, Adriana B; Cramer, Steven C; Dacosta-Aguayo, Rosalia; de la Rosa, Ezequiel; Domin, Martin; Dula, Adrienne N; Feng, Wuwei; Franco, Alexandre R; Geranmayeh, Fatemeh; Gramfort, Alexandre; Gregory, Chris M; Hanlon, Colleen A; Hordacre, Brenton G; Kautz, Steven A; Khlif, Mohamed Salah; Kim, Hosung; Kirschke, Jan S; Liu, Jingchun; Lotze, Martin; MacIntosh, Bradley J; Mataró, Maria; Mohamed, Feroze B; Nordvik, Jan E; Park, Gilsoon; Pienta, Amy; Piras, Fabrizio; Redman, Shane M; Revill, Kate P; Reyes, Mauricio; Robertson, Andrew D; Seo, Na Jin; Soekadar, Surjo R; Spalletta, Gianfranco; Sweet, Alison; Telenczuk, Maria; Thielman, Gregory; Westlye, Lars T; Winstein, Carolee J; Wittenberg, George F; Wong, Kristin A; Yu, Chunshui
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

Tobe, Russell H; MacKay-Brandt, Anna; Lim, Ryan; Kramer, Melissa; Breland, Melissa M; Tu, Lucia; Tian, Yiwen; Trautman, Kristin Dietz; Hu, Caixia; Sangoi, Raj; Alexander, Lindsay; Gabbay, Vilma; Castellanos, F Xavier; Leventhal, Bennett L; Craddock, R Cameron; Colcombe, Stanley J; Franco, Alexandre R; Milham, Michael P
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

Esper, Nathalia Bianchini; Franco, Alexandre Rosa; Soder, Ricardo Bernardi; Bomfim, Rodrigo Cerqueira; Nunes, Magda Lahorgue; Radaelli, Graciane; Esper, Katherine Bianchini; Kotoski, Aline; Pripp, Willian; Neto, Felipe Kalil; Azambuja, Luciana Schermann; Mathias, Nathália Alves; da Costa, Danielle Irigoyen; Portuguez, Mirna Wetters; da Costa, Jaderson Costa; Buchweitz, Augusto
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 13-39 months (mean: 24.8 months; standard deviation [SD]: 5.8 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