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1.
Hum Brain Mapp ; 2020 Jun 29.
Artigo em Inglês | MEDLINE | ID: mdl-32596977

RESUMO

The ENIGMA group on Generalized Anxiety Disorder (ENIGMA-Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega-analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between-country transfer of subject-level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega-analyses.

2.
Mol Psychiatry ; 2020 May 28.
Artigo em Inglês | MEDLINE | ID: mdl-32467648

RESUMO

Emerging evidence suggests that obesity impacts brain physiology at multiple levels. Here we aimed to clarify the relationship between obesity and brain structure using structural MRI (n = 6420) and genetic data (n = 3907) from the ENIGMA Major Depressive Disorder (MDD) working group. Obesity (BMI > 30) was significantly associated with cortical and subcortical abnormalities in both mass-univariate and multivariate pattern recognition analyses independent of MDD diagnosis. The most pronounced effects were found for associations between obesity and lower temporo-frontal cortical thickness (maximum Cohen´s d (left fusiform gyrus) = -0.33). The observed regional distribution and effect size of cortical thickness reductions in obesity revealed considerable similarities with corresponding patterns of lower cortical thickness in previously published studies of neuropsychiatric disorders. A higher polygenic risk score for obesity significantly correlated with lower occipital surface area. In addition, a significant age-by-obesity interaction on cortical thickness emerged driven by lower thickness in older participants. Our findings suggest a neurobiological interaction between obesity and brain structure under physiological and pathological brain conditions.

3.
Cogn Neuropsychiatry ; 24(2): 93-107, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30774035

RESUMO

BACKGROUND AND AIMS: Cognitive impairments are primary hallmarks symptoms of bipolar disorder (BD). Whether these deficits are markers of vulnerability or symptoms of the disease is still unclear. This study used a component-wise gradient (CGB) machine learning algorithm to identify cognitive measures that could accurately differentiate pediatric BD, unaffected offspring of BD parents, and healthy controls. METHODS: 59 healthy controls (HC; 11.19 ± 3.15 yo; 30 girls), 119 children and adolescents with BD (13.31 ± 3.02 yo, 52 girls) and 49 unaffected offspring of BD parents (UO; 9.36 ± 3.18 yo; 22 girls) completed the CANTAB cognitive battery. RESULTS: CGB achieved accuracy of 73.2% and an AUROC of 0.785 in classifying individuals as either BD or non-BD on a dataset held out for validation for testing. The strongest cognitive predictors of BD were measures of processing speed and affective processing. Measures of cognition did not differentiate between UO and HC. CONCLUSIONS: Alterations in processing speed and affective processing are markers of BD in pediatric populations. Longitudinal studies should determine whether UO with a cognitive profile similar to that of HC are at less or equal risk for mood disorders. Future studies should include relevant measures for BD such as verbal memory and genetic risk scores.


Assuntos
Transtorno Bipolar/diagnóstico , Transtorno Bipolar/psicologia , Transtornos Cognitivos/diagnóstico , Transtornos Cognitivos/psicologia , Testes Neuropsicológicos , Adolescente , Criança , Cognição/fisiologia , Feminino , Humanos , Estudos Longitudinais , Masculino , Memória/fisiologia , Pais/psicologia
4.
J Behav Health Serv Res ; 46(3): 415-433, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-29873034

RESUMO

Young adults experiencing first-episode psychosis have historically been difficult to retain in mental health treatment. Communities across the United States are implementing Coordinated Specialty Care to improve outcomes for individuals experiencing first-episode psychosis. This mixed-methods research study examined the relationship between program services and treatment retention, operationalized as the likelihood of remaining in the program for 9 months or more. In the adjusted analysis, male gender and participation in home-based cognitive behavioral therapy were associated with an increased likelihood of remaining in treatment. The key informant interview findings suggest the shared decision-making process and the breadth, flexibility, and focus on functional recovery of the home-based cognitive behavioral therapy intervention may have positively influenced treatment retention. These findings suggest the use of shared decision-making and improved access to home-based cognitive behavioral therapy for first-episode psychosis patients may improve outcomes for this vulnerable population.


Assuntos
Tomada de Decisões , Acesso aos Serviços de Saúde , Aceitação pelo Paciente de Cuidados de Saúde/psicologia , Transtornos Psicóticos/psicologia , Adulto , Terapia Cognitivo-Comportamental , Feminino , Humanos , Masculino , Serviços de Saúde Mental , Pessoa de Meia-Idade , Transtornos Psicóticos/terapia , Distribuição por Sexo , Estados Unidos , Adulto Jovem
5.
Psychiatry Res Neuroimaging ; 278: 65-68, 2018 08 30.
Artigo em Inglês | MEDLINE | ID: mdl-29907438

RESUMO

Sodium valproate (VPA) has well-established neuroprotective effects and is recommended as treatment in bipolar disorder patients. The neural effects of VPA in pediatric bipolar disorder (PBD) have yet to be established. This preliminary study explored the effects of VPA on brain structure in PBD. Fourteen PBD patients (10 males; mean = 13.43 ± 3.05 years old) underwent a structural MRI before and after a 6-week VPA treatment period. Bayesian linear mixed modeling explored seven brain region volumes as a function of dichotomous pre/post time. Results showed a decrease in amygdala volume over time. These findings need to be confirmed by large-scale, longitudinal studies.


Assuntos
Transtorno Bipolar/tratamento farmacológico , Encéfalo/efeitos dos fármacos , Ácido Valproico/administração & dosagem , Adolescente , Tonsila do Cerebelo/diagnóstico por imagem , Tonsila do Cerebelo/efeitos dos fármacos , Tonsila do Cerebelo/patologia , Teorema de Bayes , Transtorno Bipolar/diagnóstico por imagem , Transtorno Bipolar/patologia , Encéfalo/diagnóstico por imagem , Encéfalo/crescimento & desenvolvimento , Criança , Feminino , Humanos , Imagem por Ressonância Magnética/métodos , Masculino
6.
J Psychiatr Res ; 101: 57-62, 2018 06.
Artigo em Inglês | MEDLINE | ID: mdl-29550609

RESUMO

The hippocampus has been implicated in various mood disorders, with global volume deficits consistently found in patient populations. The hippocampus, however, consists of anatomically distinct subfields, and examination of specific subfield differences may elucidate the possible molecular mechanisms behind psychiatric pathologies. Indeed, adult studies have reported smaller hippocampal subfield volumes in regions within the cornu ammonis (CA1 and CA4), dentate gyrus (DG), and hippocampal tails in both patients with Major Depressive Disorder (MDD) and Bipolar Disorder (BD) compared to healthy controls. Subfield differences in pediatric patients with mood disorders, on the other hand, have not been extensively investigated. In the current study, magnetic resonance imaging scans were acquired for 141 children and adolescents between the ages of eight and eighteen (57 with BD, 30 with MDD, and 54 healthy controls). An automated segmentation method was then used to assess differences in hippocampal subfield volumes. Children and adolescents with BD were found to have significantly smaller volumes in the right CA1, CA4, and right subiculum, as well as the bilateral granule cell layer (GCL), molecular layer (ML), and hippocampal tails. The volume of the right subiculum in BD patients was also found to be negatively correlated with illness duration. Overall, the findings from this cross-sectional study provide evidence for specific hippocampal subfield volume differences in children and adolescents with BD compared to healthy controls and suggest progressive reductions with increased illness duration.


Assuntos
Transtorno Bipolar/patologia , Transtorno Depressivo Maior/patologia , Hipocampo/patologia , Neuroimagem/métodos , Adolescente , Transtorno Bipolar/diagnóstico por imagem , Criança , Transtorno Depressivo Maior/diagnóstico por imagem , Feminino , Hipocampo/diagnóstico por imagem , Humanos , Imagem por Ressonância Magnética , Masculino
7.
Transl Psychiatry ; 7(12): 1283, 2017 12 11.
Artigo em Inglês | MEDLINE | ID: mdl-29225347

RESUMO

Bipolar disorder (BD) has been previously associated with accelerated aging; yet, the mechanisms underlying this association are largely unknown. The epigenetic clock has been increasingly recognized as a valuable aging marker, although its association with other biological clocks in BD patients and high-risk subjects, such as telomere length and mitochondrial DNA (mtDNA) copy number, has never been investigated. We included 22 patients with BD I, 16 siblings of BD patients, and 20 healthy controls in this analysis. DNA was isolated from peripheral blood and interrogated for genome-wide DNA methylation, mtDNA copy number, and telomere length. DNA methylation age (DNAm age) and accelerated aging were calculated using the Horvath age estimation algorithm in blood and in postmortem brain from BD patients and nonpsychiatric controls using publicly available data. Older BD patients presented significantly accelerated epigenetic aging compared to controls, whereas no difference was detected among the younger subjects. Patients showed higher levels of mtDNA copy number, while no difference was found between controls and siblings. mtDNA significantly correlated with epigenetic age acceleration among older subjects, as well and with global functioning in our sample. Telomere length did not show significant differences between groups, nor did it correlate with epigenetic aging or mtDNA copy number. These results suggest that BD may involve an accelerated epigenetic aging, which might represent a novel target for treating BD and subjects at risk. In particular, our results suggest a complex interplay between biological clocks to determine the accelerated aging and its consequences in BD.


Assuntos
Envelhecimento , Transtorno Bipolar/genética , DNA Mitocondrial/genética , Epigênese Genética , Adulto , Cerebelo/metabolismo , Variações do Número de Cópias de DNA , Metilação de DNA , Feminino , Humanos , Masculino , Telômero/metabolismo
8.
Int J Bipolar Disord ; 5(1): 33, 2017 Sep 18.
Artigo em Inglês | MEDLINE | ID: mdl-28921165

RESUMO

In the original version of this article (Wu et al. 2017), published on 1 September 2017, the name of author 'Bo Cao' was wrongly displayed. In this Erratum the incorrect name and correct name are shown. The original publication of this article has been corrected.

9.
Int J Bipolar Disord ; 5(1): 32, 2017 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-28861763

RESUMO

Bipolar disorder (BD) is a common disorder with high reoccurrence rate in general population. It is critical to have objective biomarkers to identify BD patients at an individual level. Neurocognitive signatures including affective Go/No-go task and Cambridge Gambling task showed the potential to distinguish BD patients from health controls as well as identify individual siblings of BD patients. Moreover, these neurocognitive signatures showed the ability to be replicated at two independent cohorts which indicates the possibility for generalization. Future studies will examine the possibility of combining neurocognitive data with other biological data to develop more accurate signatures.

10.
Sci Rep ; 7(1): 511, 2017 03 30.
Artigo em Inglês | MEDLINE | ID: mdl-28360420

RESUMO

Cortical gyrification of the brain represents the folding characteristic of the cerebral cortex. How the brain cortical gyrification changes from childhood to old age in healthy human subjects is still unclear. Additionally, studies have shown regional gyrification alterations in patients with major psychiatric disorders, such as major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ). However, whether the lifespan trajectory of gyrification over the brain is altered in patients diagnosed with major psychiatric disorders is still unknown. In this study, we investigated the trajectories of gyrification in three independent cohorts based on structural brain images of 881 subjects from age 4 to 83. We discovered that the trajectory of gyrification during normal development and aging was not linear and could be modeled with a logarithmic function. We also found that the gyrification trajectories of patients with MDD, BD and SCZ were deviated from the healthy one during adulthood, indicating altered aging in the brain of these patients.


Assuntos
Transtorno Bipolar/patologia , Encéfalo/patologia , Transtorno Depressivo Maior/patologia , Longevidade , Esquizofrenia/patologia , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Criança , Pré-Escolar , Demografia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Adulto Jovem
11.
Neuroimage ; 145(Pt B): 254-264, 2017 01 15.
Artigo em Inglês | MEDLINE | ID: mdl-26883067

RESUMO

Diagnosis, clinical management and research of psychiatric disorders remain subjective - largely guided by historically developed categories which may not effectively capture underlying pathophysiological mechanisms of dysfunction. Here, we report a novel approach of identifying and validating distinct and biologically meaningful clinical phenotypes of bipolar disorders using both unsupervised and supervised machine learning techniques. First, neurocognitive data were analyzed using an unsupervised machine learning approach and two distinct clinical phenotypes identified namely; phenotype I and phenotype II. Second, diffusion weighted imaging scans were pre-processed using the tract-based spatial statistics (TBSS) method and 'skeletonized' white matter fractional anisotropy (FA) and mean diffusivity (MD) maps extracted. The 'skeletonized' white matter FA and MD maps were entered into the Elastic Net machine learning algorithm to distinguish individual subjects' phenotypic labels (e.g. phenotype I vs. phenotype II). This calculation was performed to ascertain whether the identified clinical phenotypes were biologically distinct. Original neurocognitive measurements distinguished individual subjects' phenotypic labels with 94% accuracy (sensitivity=92%, specificity=97%). TBSS derived FA and MD measurements predicted individual subjects' phenotypic labels with 76% and 65% accuracy respectively. In addition, individual subjects belonging to phenotypes I and II were distinguished from healthy controls with 57% and 92% accuracy respectively. Neurocognitive task variables identified as most relevant in distinguishing phenotypic labels included; Affective Go/No-Go (AGN), Cambridge Gambling Task (CGT) coupled with inferior fronto-occipital fasciculus and callosal white matter pathways. These results suggest that there may exist two biologically distinct clinical phenotypes in bipolar disorders which can be identified from healthy controls with high accuracy and at an individual subject level. We suggest a strong clinical utility of the proposed approach in defining and validating biologically meaningful and less heterogeneous clinical sub-phenotypes of major psychiatric disorders.


Assuntos
Transtorno Bipolar/diagnóstico , Imagem de Difusão por Ressonância Magnética/métodos , Aprendizado de Máquina , Neuroimagem/métodos , Substância Branca/diagnóstico por imagem , Adulto , Transtorno Bipolar/diagnóstico por imagem , Transtorno Bipolar/fisiopatologia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Fenótipo , Sensibilidade e Especificidade
12.
J Psychiatr Res ; 80: 64-72, 2016 09.
Artigo em Inglês | MEDLINE | ID: mdl-27302871

RESUMO

BACKGROUND: Bipolar disorder (BD) is characterized by affective processing bias and variations in personality traits. It is still unknown whether these features are linked to the same structural brain alterations. The aim of this study was to investigate relationships between specific personality traits, white matter (WM) properties, and affective processing in BD and HC. METHODS: 24 healthy controls (HC) and 38 adults with BDI (HC: 29.47 ± 2.23 years, 15 females; BDI: 32.44 ± 1.84 years, 20 females) completed clinical scales and the Big Five Inventory. They were also administered the Affective Go/No-Go (AGN) and the Rapid Visual Processing (RVP) tasks of the Cambridge Neuropsychological Test Automated Battery. Diffusion Tensor Imaging (DTI) assessed the microstructure of WM tracts. RESULTS: In BDI measures of WM properties were reduced across all major brain white matter tracts. As expected, individuals with BDI reported greater neuroticism, lower agreeableness and conscientiousness, and made a greater number of errors in response to affective stimuli in the AGN task compared to HC. High neuroticism scores were associated with faster AGN latency, and overall reduced AGN accuracy in both HC and BDI. Elevated FA values were associated with reduced neuroticism and increased cognitive processing in HC but not in BDI. CONCLUSIONS: Our findings showed important potential links between personality, affective processing and WM integrity in BD. In the future therapeutic interventions for BD using brain stimulation protocols might benefit from the use of DTI to target pathways underlying abnormal affective processing.


Assuntos
Afeto/fisiologia , Transtorno Bipolar/complicações , Transtorno Bipolar/psicologia , Transtornos Cognitivos/etiologia , Leucoencefalopatias/etiologia , Personalidade , Adulto , Análise de Variância , Anisotropia , Imagem de Tensor de Difusão , Feminino , Humanos , Processamento de Imagem Assistida por Computador , Masculino , Testes Neuropsicológicos , Testes de Personalidade , Escalas de Graduação Psiquiátrica , Estatística como Assunto
13.
J Affect Disord ; 201: 51-6, 2016 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-27179338

RESUMO

BACKGROUND: Cognitive deficits have been consistently reported in individuals with bipolar disorder (BD). The cognitive profile of siblings of individuals with BD is, however, less clearly established possibly due to the heterogeneity of neuropsychological measures used in previous studies. The aim of this exploratory study was to assess the cognitive function of siblings of individuals with BD and compare it with that of their first-degree relatives suffering with BD, and healthy controls (HC) using the Cambridge Neuropsychological Test Automated Battery (CANTAB) - a comprehensive and validated computerized cognitive battery. METHODS: We recruited 23 HC (33.52±10.29 years, 8 males), 27 individuals with BD (34.26±10.19 years, 9 males, 25 BDI, 1BDII and 1 BD-NOS), and 15 of their biologically related siblings (37.47±13.15 years, 4 males). Siblings had no current or lifetime history of mental disorders. Participants performed the CANTAB and completed questionnaires assessing mood and global functioning. Multivariate analyses compared CANTAB measures across the three participant groups. RESULTS: Individuals with BD and their siblings were less accurate in a task of sustained attention (Rapid Visual Processing) when compared to HC. Further, individuals with BD displayed pronounced deficits in affective processing (Affective Go/No-Go) compared to HC. There were no cognitive differences between siblings and individuals with BD. After correcting for current depressive symptoms, these results did not reach statistical significance. CONCLUSIONS: Subthreshold depressive symptoms may be associated with reduced sustained attention in healthy siblings of BD patients. This preliminary result needs to be corroborated by large-scale, longitudinal studies assessing the relationship between cognition and mood in vulnerable individuals.


Assuntos
Transtorno Bipolar/complicações , Transtorno Bipolar/psicologia , Transtornos Cognitivos/complicações , Transtornos Cognitivos/psicologia , Irmãos/psicologia , Adulto , Feminino , Humanos , Estudos Longitudinais , Masculino , Análise Multivariada , Testes Neuropsicológicos , Inquéritos e Questionários , Análise e Desempenho de Tarefas
14.
Biol Psychiatry Cogn Neurosci Neuroimaging ; 1(2): 186-194, 2016 Mar 01.
Artigo em Inglês | MEDLINE | ID: mdl-27047994

RESUMO

BACKGROUND: Neuroanatomical abnormalities in Bipolar disorder (BD) have previously been reported. However, the utility of these abnormalities in distinguishing individual BD patients from Healthy controls and stratify patients based on overall illness burden has not been investigated in a large cohort. METHODS: In this study, we examined whether structural neuroimaging scans coupled with a machine learning algorithm are able to distinguish individual BD patients from Healthy controls in a large cohort of 256 subjects. Additionally, we investigated the relationship between machine learning predicted probability scores and subjects' clinical characteristics such as illness duration and clinical stages. Neuroimaging scans were acquired from 128 BD patients and 128 Healthy controls. Gray and white matter density maps were obtained and used to 'train' a relevance vector machine (RVM) learning algorithm which was used to distinguish individual patients from Healthy controls. RESULTS: The RVM algorithm distinguished patients from Healthy controls with 70.3 % accuracy (74.2 % specificity, 66.4 % sensitivity, chi-square p<0.005) using white matter density data and 64.9 % accuracy (71.1 % specificity, 58.6 % sensitivity, chi-square p<0.005) with gray matter density. Multiple brain regions - largely covering the fronto - limbic system were identified as 'most relevant' in distinguishing both groups. Patients identified by the algorithm with high certainty (a high probability score) - belonged to a subgroup with more than ten total lifetime manic episodes including hospitalizations (late stage). CONCLUSIONS: These results indicate the presence of widespread structural brain abnormalities in BD which are associated with higher illness burden - which points to neuroprogression.

15.
J Affect Disord ; 192: 219-25, 2016 Mar 01.
Artigo em Inglês | MEDLINE | ID: mdl-26748737

RESUMO

BACKGROUND: Previous studies have reported that patients with bipolar disorder (BD) present with cognitive impairments during mood episodes as well as euthymic phase. However, it is still unknown whether reported neurocognitive abnormalities can objectively identify individual BD patients from healthy controls (HC). METHODS: A total of 21 euthymic BD patients and 21 demographically matched HC were included in the current study. Participants performed the computerized Cambridge Neurocognitive Test Automated Battery (CANTAB) to assess cognitive performance. The least absolute shrinkage selection operator (LASSO) machine learning algorithm was implemented to identify neurocognitive signatures to distinguish individual BD patients from HC. RESULTS: The LASSO machine learning algorithm identified individual BD patients from HC with an accuracy of 71%, area under receiver operating characteristic curve of 0.7143 and significant at p=0.0053. The LASSO algorithm assigned individual subjects with a probability score (0-healthy, 1-patient). Patients with rapid cycling (RC) were assigned increased probability scores as compared to patients without RC. A multivariate pattern of neurocognitive abnormalities comprising of affective Go/No-go and the Cambridge gambling task was relevant in distinguishing individual patients from HC. LIMITATIONS: Our study sample was small as we only considered euthymic BD patients and demographically matched HC. CONCLUSION: Neurocognitive abnormalities can distinguish individual euthymic BD patients from HC with relatively high accuracy. In addition, patients with RC had more cognitive impairments compared to patients without RC. The predictive neurocognitive signature identified in the current study can potentially be used to provide individualized clinical inferences on BD patients.


Assuntos
Transtorno Bipolar/diagnóstico , Transtornos Cognitivos/diagnóstico , Transtorno Ciclotímico/psicologia , Testes Neuropsicológicos/estatística & dados numéricos , Adulto , Algoritmos , Transtorno Bipolar/psicologia , Estudos de Casos e Controles , Transtornos Cognitivos/psicologia , Feminino , Humanos , Aprendizado de Máquina , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes
16.
J Affect Disord ; 193: 109-16, 2016 Mar 15.
Artigo em Inglês | MEDLINE | ID: mdl-26773901

RESUMO

OBJECTIVE: A growing body of evidence has put forward clinical risk factors associated with patients with mood disorders that attempt suicide. However, what is not known is how to integrate clinical variables into a clinically useful tool in order to estimate the probability of an individual patient attempting suicide. METHOD: A total of 144 patients with mood disorders were included. Clinical variables associated with suicide attempts among patients with mood disorders and demographic variables were used to 'train' a machine learning algorithm. The resulting algorithm was utilized in identifying novel or 'unseen' individual subjects as either suicide attempters or non-attempters. Three machine learning algorithms were implemented and evaluated. RESULTS: All algorithms distinguished individual suicide attempters from non-attempters with prediction accuracy ranging between 65% and 72% (p<0.05). In particular, the relevance vector machine (RVM) algorithm correctly predicted 103 out of 144 subjects translating into 72% accuracy (72.1% sensitivity and 71.3% specificity) and an area under the curve of 0.77 (p<0.0001). The most relevant predictor variables in distinguishing attempters from non-attempters included previous hospitalizations for depression, a history of psychosis, cocaine dependence and post-traumatic stress disorder (PTSD) comorbidity. CONCLUSION: Risk for suicide attempt among patients with mood disorders can be estimated at an individual subject level by incorporating both demographic and clinical variables. Future studies should examine the performance of this model in other populations and its subsequent utility in facilitating selection of interventions to prevent suicide.


Assuntos
Algoritmos , Aprendizado de Máquina , Modelos Estatísticos , Transtornos do Humor/psicologia , Tentativa de Suicídio/estatística & dados numéricos , Adolescente , Adulto , Idoso , Comorbidade , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Transtornos do Humor/epidemiologia , Projetos Piloto , Reprodutibilidade dos Testes , Medição de Risco/métodos , Fatores de Risco , Suicídio/prevenção & controle , Adulto Jovem
17.
Psychiatry Res ; 234(2): 265-271, 2015 Nov 30.
Artigo em Inglês | MEDLINE | ID: mdl-26459075

RESUMO

Previous studies have reported abnormalities of white-matter diffusivity in pediatric bipolar disorder. However, it has not been established whether these abnormalities are able to distinguish individual subjects with pediatric bipolar disorder from healthy controls with a high specificity and sensitivity. Diffusion-weighted imaging scans were acquired from 16 youths diagnosed with DSM-IV bipolar disorder and 16 demographically matched healthy controls. Regional white matter tissue microstructural measurements such as fractional anisotropy, axial diffusivity and radial diffusivity were computed using an atlas-based approach. These measurements were used to 'train' a support vector machine (SVM) algorithm to predict new or 'unseen' subjects' diagnostic labels. The SVM algorithm predicted individual subjects with specificity=87.5%, sensitivity=68.75%, accuracy=78.12%, positive predictive value=84.62%, negative predictive value=73.68%, area under receiver operating characteristic curve (AUROC)=0.7812 and chi-square p-value=0.0012. A pattern of reduced regional white matter fractional anisotropy was observed in pediatric bipolar disorder patients. These results suggest that atlas-based diffusion weighted imaging measurements can distinguish individual pediatric bipolar disorder patients from healthy controls. Notably, from a clinical perspective these findings will contribute to the pathophysiological understanding of pediatric bipolar disorder.


Assuntos
Transtorno Bipolar/diagnóstico , Transtorno Bipolar/metabolismo , Encéfalo/metabolismo , Imagem de Difusão por Ressonância Magnética/métodos , Máquina de Vetores de Suporte , Adolescente , Anisotropia , Transtorno Bipolar/classificação , Encéfalo/patologia , Criança , Manual Diagnóstico e Estatístico de Transtornos Mentais , Feminino , Humanos , Masculino , Substância Branca/metabolismo , Substância Branca/patologia
18.
J Psychiatr Res ; 62: 84-91, 2015 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-25687738

RESUMO

BACKGROUND: Diagnosis of pediatric neuropsychiatric disorders such as unipolar depression is largely based on clinical judgment - without objective biomarkers to guide diagnostic process and subsequent therapeutic interventions. Neuroimaging studies have previously reported average group-level neuroanatomical differences between patients with pediatric unipolar depression and healthy controls. In the present study, we investigated the utility of multiple neuromorphometric indices in distinguishing pediatric unipolar depression patients from healthy controls at an individual subject level. METHODS: We acquired structural T1-weighted scans from 25 pediatric unipolar depression patients and 26 demographically matched healthy controls. Multiple neuromorphometric indices such as cortical thickness, volume, and cortical folding patterns were obtained. A support vector machine pattern classification model was 'trained' to distinguish individual subjects with pediatric unipolar depression from healthy controls based on multiple neuromorphometric indices and model predictive validity (sensitivity and specificity) calculated. RESULTS: The model correctly identified 40 out of 51 subjects translating to 78.4% accuracy, 76.0% sensitivity and 80.8% specificity, chi-square p-value = 0.000049. Volumetric and cortical folding abnormalities in the right thalamus and right temporal pole respectively were most central in distinguishing individual patients with pediatric unipolar depression from healthy controls. CONCLUSIONS: These findings provide evidence that a support vector machine pattern classification model using multiple neuromorphometric indices may qualify as diagnostic marker for pediatric unipolar depression. In addition, our results identified the most relevant neuromorphometric features in distinguishing PUD patients from healthy controls.


Assuntos
Mapeamento Encefálico , Encéfalo/patologia , Transtorno Depressivo/diagnóstico , Processamento de Imagem Assistida por Computador , Adolescente , Análise de Variância , Criança , Feminino , Humanos , Imagem por Ressonância Magnética , Masculino , Máquina de Vetores de Suporte
19.
Artigo em Inglês | MEDLINE | ID: mdl-25191631

RESUMO

Modern ultrasound systems can output video images containing more spatial and temporal information than still images. Super-resolution techniques can exploit additional information but face two challenges: image registration and complex motion. In addition, information from multiple available frequencies is unexploited. Herein, we utilised these information sources to create better ultrasound images and videos, extending existing technologies for image capture. Spatial and frequency-based super-resolution processing using multiple motion estimation and frequency combination was applied to ultrasound videos of deforming models. Processed images are larger, have greater clarity and detail, and less variability in intensity between frames. Significantly, strain measurements are more accurate and precise than those from raw videos, and have a higher contrast ratio between 'tumour' and 'surrounding tissue' in a phantom model. We attribute improvements to reduced noise and increased resolution in processed images. Our methods can significantly improve quantitative and qualitative assessments of ultrasound images when compared assessments of standard images.

20.
J Biomech Eng ; 134(2): 024504, 2012 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-22482679

RESUMO

Strain is an essential metric in tissue mechanics. Strains and strain distributions during functional loads can help identify damaged and pathologic regions as well as quantify functional compromise. Noninvasive strain measurement in vivo is difficult to perform. The goal of this in vitro study is to determine the efficacy of digital image correlation (DIC) methods to measure strain in B-mode ultrasound images. The Achilles tendons of eight male Wistar rats were removed and mechanically cycled between 0 and 1% strain. Three cine video images were captured for each specimen: (1) optical video for manual tracking of optical markers; (2) optical video for DIC tracking of optical surface markers; and (3) ultrasound video for DIC tracking of image texture within the tissue. All three imaging modalities were similarly able to measure tendon strain during cyclic testing. Manual/ImageJ-based strain values linearly correlated with DIC (optical marker)-based strain values for all eight tendons with a slope of 0.970. DIC (optical marker)-based strain values linearly correlated with DIC (ultrasound texture)-based strain values for all eight tendons with a slope of 1.003. Strain measurement using DIC was as accurate as manual image tracking methods, and DIC tracking was equally accurate when tracking ultrasound texture as when tracking optical markers. This study supports the use of DIC to calculate strains directly from the texture present in standard B-mode ultrasound images and supports the use of DIC for in vivo strain measurement using ultrasound images without additional markers, either artificially placed (for optical tracking) or anatomically in view (i.e., bony landmarks and/or muscle-tendon junctions).


Assuntos
Processamento de Imagem Assistida por Computador/métodos , Estresse Mecânico , Tendões/diagnóstico por imagem , Animais , Fenômenos Biomecânicos , Masculino , Fenômenos Ópticos , Ratos , Ratos Wistar , Ultrassonografia
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