A Comparison of Voxel-Based Morphometry and Volumetry Methods in the Context of the Neural Basis of Aggression

Emerton, Britt C.; Jerram, Matthew; Deckersbach, Thilo; Dougherty, Darin D.; Fulwiler, Carl E.; Gansler, David A.

doi:10.1007/s11682-009-9075-2

Cited by 10 publications

(6 citation statements)

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“…However in recent years, iterative normalization and optimized segmentation procedures and algorithms have been developed to improve the final tissue classification (Ashburner and Friston, 2005). Emerton et al (2009) showed convergence in the VBM method in comparison with tracing-based volumetry methods; however they advocated the two methods to be considered complementary rather than interchangeable methods, due to different statistical approaches. Furthermore the same authors suggested that convergence depends on various factors such as inter-subject anatomical variability of the region of interest and/or the VBM preprocessing protocol employed.…”

Section: Discussionmentioning

confidence: 99%

Reduced cortical gray matter volume in male adolescents with substance and conduct problems

Dalwani

Sakai

Mikulich‐Gilbertson

et al. 2011

Drug and Alcohol Dependence

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Boys with serious conduct and substance problems (“Antisocial Substance Dependence” (ASD)) repeatedly make impulsive and risky decisions in spite of possible negative consequences. Because prefrontal cortex (PFC) is involved in planning behavior in accord with prior rewards and punishments, structural abnormalities in PFC could contribute to a person's propensity to make risky decisions. Methods We acquired high-resolution structural images of 25 male ASD patients (ages 14–18 years) and 19 controls of similar ages using a 3T MR system. We conducted whole-brain voxel-based morphometric analysis (p<0.05, corrected for multiple comparisons at whole-brain cluster-level) using Statistical Parametric Mapping version-5 and tested group differences in regional gray matter (GM) volume with analyses of covariance, adjusting for total GM volume, age, and IQ; we further adjusted between-group analyses for ADHD and depression. As secondary analyses, we tested for negative associations between GM volume and impulsivity within groups and separately, GM volume and symptom severity within patients using whole-brain regression analyses. Results ASD boys had significantly lower GM volume than controls in left dorsolateral PFC (DLPFC), right lingual gyrus and bilateral cerebellum, and significantly higher GM volume in right precuneus. Left DLPFC GM volume showed negative association with impulsivity within controls and negative association with substance dependence severity within patients. Conclusions ASD boys show reduced GM volumes in several regions including DLPFC, a region highly relevant to impulsivity, disinhibition, and decision-making, and cerebellum, a region important for behavioral regulation, while they showed increased GM in precuneus, a region associated with self-referential and self-centered thinking.

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Section: Discussionmentioning

confidence: 99%

Reduced cortical gray matter volume in male adolescents with substance and conduct problems

Dalwani

Sakai

Mikulich‐Gilbertson

et al. 2011

Drug and Alcohol Dependence

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show abstract

“…The apparent inconsistency between these two methodologies can probably explained by the differing sensitivities of the two image analysis techniques. Volumetric approaches have greater sensitivity for the detection of diffuse change whereas automated voxel-based approaches are more likely to detect localized effects (Giuliani et al 2005; Emerton et al 2009). When this is considered, it is not entirely surprising that findings from the two approaches do not exactly tally.…”

Section: Discussionmentioning

confidence: 99%

Tensor-based morphometry of cannabis use on brain structure in individuals at elevated genetic risk of schizophrenia

et al. 2012

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“…Many studies [ 9 , 10 ] give detailed insights on comparisons between voxel based and volumetric studies.…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for Differential Prognosis of Brain Degenerative Diseases Using Radiomics-Based Textural Analysis and Ensemble Learning Classifiers

Jain

Jain³

2021

Computational and Mathematical Methods in Medicine

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We propose a novel approach to develop a computer-aided decision support system for radiologists to help them classify brain degeneration process as physiological or pathological, aiding in early prognosis of brain degenerative diseases. Our approach applies computational and mathematical formulations to extract quantitative information from biomedical images. Our study explores the longitudinal OASIS-3 dataset, which consists of 4096 brain MRI scans collected over a period of 15 years. We perform feature extraction using Pyradiomics python package that quantizes brain MRI images using different texture analysis methods. Studies indicate that Radiomics has rarely been used for analysis of brain cognition; hence, our study is also a novel effort to determine the efficiency of Radiomics features extracted from structural MRI scans for classification of brain degenerative diseases and to create awareness about Radiomics. For classification tasks, we explore various ensemble learning classification algorithms such as random forests, bagging-based ensemble classifiers, and gradient-boosted ensemble classifiers such as XGBoost and AdaBoost. Such ensemble learning classifiers have not been used for biomedical image classification. We also propose a novel texture analysis matrix, Decreasing Gray-Level Matrix or DGLM. The features extracted from this filter helped to further improve the accuracy of our decision support system. The proposed system based on XGBoost ensemble learning classifiers achieves an accuracy of 97.38%, with sensitivity 99.82% and specificity 97.01%.

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A Comparison of Voxel-Based Morphometry and Volumetry Methods in the Context of the Neural Basis of Aggression

Cited by 10 publications

References 50 publications

Reduced cortical gray matter volume in male adolescents with substance and conduct problems

Reduced cortical gray matter volume in male adolescents with substance and conduct problems

Tensor-based morphometry of cannabis use on brain structure in individuals at elevated genetic risk of schizophrenia

A Novel Method for Differential Prognosis of Brain Degenerative Diseases Using Radiomics-Based Textural Analysis and Ensemble Learning Classifiers

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