The Mexican magnetic resonance imaging dataset of patients with cocaine use disorder: SUDMEX CONN

Ángeles-Valdez, Diego; Rasgado-Toledo, Jalil; Issa-Garcia, Victor; Balducci, Thania; Villicaña, Viviana; Valencia, Alely; González-Olvera, Jorge; Reyes-Zamorano, Ernesto; Garza‐Villarreal, Eduardo A.

doi:10.1038/s41597-022-01251-3

Cited by 18 publications

(22 citation statements)

References 66 publications

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“…CA and HC were selected from the Mexican database on cocaine use disorder 29 . This open database contains demographic, clinical and imaging data from 145 subjects who were recruited as part of a project on the study of addictions.…”

Section: Methodsmentioning

confidence: 99%

“…CA and HC were selected from the Mexican database on cocaine use disorder. 29 This open database contains demographic, clinical and imaging data from 145 subjects who were recruited as part of a project on the study of addictions. CA was assessed using the MINI Mini‐PLUS interview in Spanish version 5.0.0 that uses the diagnostic and statistical manual of mental disorders (DSM‐IV) criteria.…”

Section: Methodsmentioning

confidence: 99%

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The complexity of cortical folding is reduced in chronic cocaine users

et al. 2023

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Cocaine use is a worldwide health problem with psychiatric, somatic and socioeconomic complications, being the second most widely used illicit drug in the world. Despite several structural neuroimaging studies, the alterations in cortical morphology associated with cocaine use and addiction are still poorly understood. In this study, we compared the complexity of cortical folding (CCF), a measure that aims to summarize the convoluted structure of the cortex between patients with cocaine addiction (n = 52) and controls (n = 36), and correlated it with characteristics of addiction and impulsivity. We found that patients with cocaine addiction had greater impulsivity and showed reduced CCF in a cluster that encompassed the left insula and the supramarginal gyrus (SMG) and in one in the left medial orbitofrontal cortex.Finally, the CCF in the left medial orbitofrontal cortex was correlated with the age of onset of cocaine addiction and with attentional impulsivity. Overall, our findings suggest that chronic cocaine use is associated with changes in the cortical surface in the fronto-parieto-limbic regions that underlie emotional regulation and these changes are associated with earlier cocaine use. Future longitudinal studies are warranted to unravel the association of these changes with the diathesis for the disorder and with the chronic use of this substance.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

The complexity of cortical folding is reduced in chronic cocaine users

et al. 2023

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“…The sample consisted of 63 (8 females) cocaine use disorder patients (CUD) and 42 (9 females) healthy controls (HC), recruited as part of the SUDMEX CONN database (14), paired by age, sex, handedness, and education. We included participants with T1-weighted, diffusion-weighted imaging (DWI), and resting-state fMRI (rsfMRI) sequences for this study.…”

Section: Methodsmentioning

confidence: 99%

“…All participants provided verbal and written informed consent. Recruitment criteria and full sample details are described in Angeles-Valdez (14).…”

Section: Methodsmentioning

confidence: 99%

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Structural and functional pathology in cocaine use disorder with polysubstance use: a multimodal fusion approach

Rasgado-Toledo

Duvvada²,

Shah

et al. 2023

Preprint

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Cocaine use disorder (CUD) is described as a compulsive urge to seek and consume cocaine despite the inimical consequences. MRI studies from different modalities have shown that CUD patients exhibit structural and/or functional connectivity pathology among several brain regions. Nevertheless, both connectivities are commonly studied and analyzed separately, which may potentially obscure its relationship between them, and with the clinical pathology. Here, we compare and contrast structural and functional brain networks in CUD patients and healthy controls (HC) using multimodal fusion. The sample consisted of 63 (8 females) CUD patients and 42 (9 females) healthy controls (HC), recruited as part of the SUDMEX CONN database. For this, we computed a battery of graph-based measures from multi-shell diffusion-weighted imaging and resting state fc-fMRI to quantify local and global connectivity. Then we used multimodal canonical component analysis plus joint independent component analysis (mCCA+jICA) to compare between techniques, and evaluate group differences and its association with clinical alteration. Unimodal results showed a striatal decrease in the participation coefficient, but applied supervised data fusion revealed other regions with cocaine-related alterations in joint functional communication. When performing multimodal fusion analysis, we observed a higher centrality of the interrelationship and a lower participation coefficient in patients with CUD. In contrast to the unimodal approach, the multimodal fusion method was able to reveal latent information about brain regions involved in impairment due to cocaine abuse. The present results could help in understanding the pathology of CUD in order to develop better pre-treatment/post-treatment intervention designs.

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A Survey of Publicly Available MRI Datasets for Potential Use in Artificial Intelligence Research

Dishner,

McRae‐Posani,

Bhowmik

et al. 2023

Magnetic Resonance Imaging

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Artificial intelligence (AI) has the potential to bring transformative improvements to the field of radiology; yet, there are barriers to widespread clinical adoption. One of the most important barriers has been access to large, well‐annotated, widely representative medical image datasets, which can be used to accurately train AI programs. Creating such datasets requires time and expertise and runs into constraints around data security and interoperability, patient privacy, and appropriate data use. Recognizing these challenges, several institutions have started curating and providing publicly available, high‐quality datasets that can be accessed by researchers to advance AI models. The purpose of this work was to review the publicly available MRI datasets that can be used for AI research in radiology. Despite being an emerging field, a simple internet search for open MRI datasets presents an overwhelming number of results. Therefore, we decided to create a survey of the major publicly accessible MRI datasets in different subfields of radiology (brain, body, and musculoskeletal), and list the most important features of value to the AI researcher. To complete this review, we searched for publicly available MRI datasets and assessed them based on several parameters (number of subjects, demographics, area of interest, technical features, and annotations). We reviewed 110 datasets across sub‐fields with 1,686,245 subjects in 12 different areas of interest ranging from spine to cardiac. This review is meant to serve as a reference for researchers to help spur advancements in the field of AI for radiology.Level of EvidenceLevel 4Technical EfficacyStage 6

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The Mexican magnetic resonance imaging dataset of patients with cocaine use disorder: SUDMEX CONN

Cited by 18 publications

References 66 publications

The complexity of cortical folding is reduced in chronic cocaine users

The complexity of cortical folding is reduced in chronic cocaine users

Structural and functional pathology in cocaine use disorder with polysubstance use: a multimodal fusion approach

A Survey of Publicly Available MRI Datasets for Potential Use in Artificial Intelligence Research

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