White matter microstructural abnormalities and gray matter volume alterations in obsessive-compulsive disorder: A coordinate-based meta-analysis

Tao, Qiuying; Dang, Jinghan; Niu, Xiaoyu; Gao, Xinyu; Zhang, Mengzhe; Yang, Zhengui; Xu, Yinhuan; Yu, Miaomiao; Han, Shaoqiang; Cheng, Jingliang; Zhang, Yong

doi:10.1016/j.jad.2022.09.035

Cited by 10 publications

(5 citation statements)

References 66 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although previous studies have reported VGM [ 34 – 36 ] and cortical thickness [ 37 – 39 ] changes in patients with OCD compared with healthy controls, the VGM and cortical thickness features were not retained during the feature selection stage in our study. Some sulcal depth features were selected, however, the classification models of sulcal depth underperformed on testing set.…”

Section: Discussionmentioning

confidence: 99%

“…To be specific, amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo) and degree of centrality (DC) were extracted from resting-state functional MRI (rs-fMRI) as the functional neuroimaging markers; volume of gray matter (VGM), cortical thickness and sulcal depth were extracted from T1-weighted images as the structural neuroimaging markers. These MRI indices were used because previous studies have successfully revealed altered ALFF [ 21 – 23 ], fALFF [ 24 – 27 ], ReHo [ 28 – 31 ], DC [ 32 , 33 ], VGM [ 34 – 36 ] and cortical thickness [ 37 – 39 ] in various brain regions, including the traditional CSTC circuit and newly reported regions, such as the occipital, parietal, and temporal lobes and the cerebellum, in patients with OCD. Sulcal depth may provide valuable information for classification since previous studies indicate the association of altered sulcus morphology and psychotic disease [ 40 – 42 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Functional and structural MRI based obsessive-compulsive disorder diagnosis using machine learning methods

Huang,

Yang,

Luo

et al. 2023

BMC Psychiatry

View full text Add to dashboard Cite

Background The success of neuroimaging in revealing neural correlates of obsessive-compulsive disorder (OCD) has raised hopes of using magnetic resonance imaging (MRI) indices to discriminate patients with OCD and the healthy. The aim of this study was to explore MRI based OCD diagnosis using machine learning methods. Methods Fifty patients with OCD and fifty healthy subjects were allocated into training and testing set by eight to two. Functional MRI (fMRI) indices, including amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), degree of centrality (DC), and structural MRI (sMRI) indices, including volume of gray matter, cortical thickness and sulcal depth, were extracted in each brain region as features. The features were reduced using least absolute shrinkage and selection operator regression on training set. Diagnosis models based on single MRI index / combined MRI indices were established on training set using support vector machine (SVM), logistic regression and random forest, and validated on testing set. Results SVM model based on combined fMRI indices, including ALFF, fALFF, ReHo and DC, achieved the optimal performance, with a cross-validation accuracy of 94%; on testing set, the area under the receiver operating characteristic curve was 0.90 and the validation accuracy was 85%. The selected features were located both within and outside the cortico-striato-thalamo-cortical (CSTC) circuit of OCD. Models based on single MRI index / combined fMRI and sMRI indices underperformed on the classification, with a largest validation accuracy of 75% from SVM model of ALFF on testing set. Conclusion SVM model of combined fMRI indices has the greatest potential to discriminate patients with OCD and the healthy, suggesting a complementary effect of fMRI indices on the classification; the features were located within and outside the CSTC circuit, indicating an importance of including various brain regions in the model.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Functional and structural MRI based obsessive-compulsive disorder diagnosis using machine learning methods

Huang,

Yang,

Luo

et al. 2023

BMC Psychiatry

View full text Add to dashboard Cite

show abstract

“…(Besiroglu et al, 2022) A CBMA reported that the gray matter volume (GMV) of OCD patients was signi cantly decreased in right inferior frontal gyrus triangular part, right superior temporal gyrus and right hippocampus. (Tao et al, 2023) The divergent conclusions above may be attributed to differences in sample size and analytical methods.…”

Section: Meta-regression Analysesmentioning

confidence: 99%

Cortical thickness alternation in obsessive-compulsive disorder patients compared with healthy controls

Dong,

Zheng,

Shen

et al. 2024

Preprint

View full text Add to dashboard Cite

Cortical morphological abnormalities are one of the neuropathological changes of obsessive-compulsive disorder (OCD). The surface-based morphometry (SBM) analyses have reported altered cortical thickness (CTh) among patients with OCD in numerous neuroimaging studies; however, the results have been inconsistent. We are attempting to utilize meta-analysis of whole-brain data to investigate changes in cortical thickness among individuals with OCD. This endeavor may enhance spatial accuracy in identification, thus effectively improving our recognition of OCD and facilitating the development of more precise and efficient treatment strategies. The seed-based d mapping (SDM) approach was employed to conduct a vertex-wise coordinate-based meta-analysis (CBMA) of whole-brain studies that explored CTh alteration among patients with OCD, compared with healthy controls (HCs). A systematic literature search identified 9 studies (containing 9 datasets) of CTh, including 518 patients with OCD and 449 healthy controls (HCs). Overall, patients with OCD showed decreased CTh in the left anterior cingulate / paracingulate gyri, right insula, as well as increased CTh in the left lingual gyrus, left inferior frontal gyrus, orbital part, left superior frontal gyrus, dorsolateral of the regions. Besides, the Meta-regression analyses revealed a negative correlation between age and cortical thickness of the right insula in patients with OCD. Due to the limited number of studies and sample sizes included in the final analysis, as well as partial data missing from some samples, we were unable to conduct a comprehensive subgroup analysis. Besides, the outcomes of meta-regression analyses should be interpreted cautiously due to their reliance on a limited number of studies. The meta-analysis revealed cortical thickness alterations in specific regions of the brain among individuals diagnosed with OCD. These findings contribute to a deeper understanding of the underlying mechanisms of OCD brain dysfunction and provide insights for early intervention strategies for the disorder.

show abstract

“…Previous studies using classic brain morphometries have identified widespread structural alterations across the brain in patients with OCD, including frontal, temporal, parietal, limbic, cerebellar, and striatal regions. [14][15][16][17] However, these alterations, alongside changes in interregional connectivity, [18][19][20] within or beyond the cortico-striatal-thalamo-cortical (CSTC) circuit, [21][22][23] have not been holistically elucidated, thus impeding the interpretation of in vivo dendritic morphology imaging within the context of conventional brain metrics. Thus, this investigation not only aimed to examine variations in gray matter dendritic morphology in OCD but also to explore their interplay with classic brain morphometries.…”

Section: Introductionmentioning

confidence: 99%

Pathological Networking of Gray Matter Dendritic Density With Classic Brain Morphometries in OCD

Zhang,

Zhou,

Chen

et al. 2023

JAMA Netw Open

View full text Add to dashboard Cite

ImportanceThe pathogenesis of obsessive-compulsive disorder (OCD) may involve altered dendritic morphology, but in vivo imaging of neurite morphology in OCD remains limited. Such changes must be interpreted functionally within the context of the multimodal neuroimaging approach to OCD.ObjectiveTo examine whether dendritic morphology is altered in patients with OCD compared with healthy controls (HCs) and whether such alterations are associated with other brain structural metrics in pathological networks.Design, Setting, and ParticipantsThis case-control study used cross-sectional data, including multimodal brain images and clinical symptom assessments, from 108 patients with OCD and 108 HCs from 2014 to 2017. Patients with OCD were recruited from Shanghai Mental Health Center, Shanghai, China, and HCs were recruited via advertisements. The OCD group comprised unmedicated adults with a Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) (DSM-IV) diagnosis of OCD, while the HCs were adults without any DSM-IV diagnosis, matched for age, sex, and education level. Data were analyzed from September 2019 to April 2023.ExposureDSM-IV diagnosis of OCD.Main Outcomes and MeasuresMultimodal brain imaging was used to compare neurite microstructure and classic morphometries between patients with OCD and HCs. The whole brain was searched to identify regions exhibiting altered morphology in patients with OCD and explore the interplay between the brain metrics representing these alterations. Brain-symptom correlations were analyzed, and the performance of different brain metric configurations were evaluated in distinguishing patients with OCD from HCs.ResultsAmong 108 HCs (median [IQR] age, 26 [23-31] years; 50 [46%] female) and 108 patients with OCD (median [IQR] age, 26 [24-31] years; 46 [43%] female), patients with OCD exhibited deficient neurite density in the right lateral occipitoparietal regions (peak t = 3.821; P ≤ .04). Classic morphometries also revealed widely-distributed alterations in the brain (peak t = 4.852; maximum P = .04), including the prefrontal, medial parietal, cingulate, and fusiform cortices. These brain metrics were interconnected into a pathological brain network associated with OCD symptoms (global strength: HCs, 0.253; patients with OCD, 0.941; P = .046; structural difference, 0.572; P &lt; .001). Additionally, the neurite density index exhibited high discriminatory power in distinguishing patients with OCD from HCs (accuracy, ≤76.85%), and the entire pathological brain network also exhibited excellent discriminative classification properties (accuracy, ≤82.87%).Conclusions and RelevanceThe findings of this case-control study underscore the utility of in vivo imaging of gray matter dendritic density in future OCD research and the development of neuroimaging-based biomarkers. They also endorse the concept of connectopathy, providing a potential framework for interpreting the associations among various OCD symptom–related morphological anomalies.

show abstract

White matter microstructural abnormalities and gray matter volume alterations in obsessive-compulsive disorder: A coordinate-based meta-analysis

Cited by 10 publications

References 66 publications

Functional and structural MRI based obsessive-compulsive disorder diagnosis using machine learning methods

Functional and structural MRI based obsessive-compulsive disorder diagnosis using machine learning methods

Cortical thickness alternation in obsessive-compulsive disorder patients compared with healthy controls

Pathological Networking of Gray Matter Dendritic Density With Classic Brain Morphometries in OCD

Contact Info

Product

Resources

About