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

Disentangling the role of gray matter volume and concentration in autism spectrum disorder: A meta-analytic investigation of 25 years of voxel-based morphometry research

Despite over two decades of neuroimaging research, a unanimous definition of the pattern of structural variation associated with autism spectrum disorder (ASD) has yet to be found. One potential impeding issue could be the sometimes ambiguous use of measurements of variations in gray matter volume (GMV) or gray matter concentration (GMC). In fact, while both can be calculated using voxel-based morphometry analysis, these may reflect different underlying pathological mechanisms. We conducted a coordinate-based meta-analysis, keeping apart GMV and GMC studies of subjects with ASD. Results showed distinct and non-overlapping patterns for the two measures. GMV decreases were evident in the cerebellum, while GMC decreases were mainly found in the temporal and frontal regions. GMV increases were found in the parietal, temporal, and frontal brain regions, while GMC increases were observed in the anterior cingulate cortex and middle frontal gyrus. Age-stratified analyses suggested that such variations are dynamic across the ASD lifespan. The present findings emphasize the importance of considering GMV and GMC as distinct yet synergistic indices in autism research.

Comparative anatomy of the caudate nucleus in canids and felids: Associations with brain size, curvature, cross-sectional properties, and behavioral ecology

The evolutionary history of canids and felids is marked by a deep time separation that has uniquely shaped their behavior and phenotype toward refined predatory abilities. The caudate nucleus is a subcortical brain structure associated with both motor control and cognitive, emotional, and executive functions. We used a combination of three-dimensional imaging, allometric scaling, and structural analyses to compare the size and shape characteristics of the caudate nucleus. The sample consisted of MRI scan data obtained from six canid species (Canis lupus lupus, Canis latrans, Chrysocyon brachyurus, Lycaon pictus, Vulpes vulpes, Vulpes zerda), two canid subspecies (Canis lupus familiaris, Canis lupus dingo), as well as three felids (Panthera tigris, Panthera uncia, Felis silvestris catus). Results revealed marked conservation in the scaling and shape attributes of the caudate nucleus across species, with only slight deviations. We hypothesize that observed differences in caudate nucleus size and structure for the domestic canids are reflective of enhanced cognitive and emotional pathways that possibly emerged during domestication.

Volumetric measurement of intracranial meningiomas: a comparison between linear, planimetric, and machine learning with multiparametric voxel-based morphometry methods

PURPOSE

To compare the accuracy of three volumetric methods in the radiological assessment of meningiomas: linear (ABC/2), planimetric, and multiparametric machine learning-based semiautomated voxel-based morphometry (VBM), and to investigate the relevance of tumor shape in volumetric error.

METHODS

Retrospective imaging database analysis at the authors' institutions. We included patients with a confirmed diagnosis of meningioma and preoperative cranial magnetic resonance imaging eligible for volumetric analyses. After tumor segmentation, images underwent automated computation of shape properties such as sphericity, roundness, flatness, and elongation.

RESULTS

Sixty-nine patients (85 tumors) were included. Tumor volumes were significantly different using linear (13.82 cm³ [range 0.13-163.74 cm³]), planimetric (11.66 cm³ [range 0.17-196.2 cm³]) and VBM methods (10.24 cm³ [range 0.17-190.32 cm³]) (p < 0.001). Median volume and percentage errors between the planimetric and linear methods and the VBM method were 1.08 cm³ and 11.61%, and 0.23 cm³ and 5.5%, respectively. Planimetry and linear methods overestimated the actual volume in 79% and 63% of the patients, respectively. Correlation studies showed excellent reliability and volumetric agreement between manual- and computer-based methods. Larger and flatter tumors had greater accuracy on planimetry, whereas less rounded tumors contributed negatively to the accuracy of the linear method.

CONCLUSION

Semiautomated VBM volumetry for meningiomas is not influenced by tumor shape properties, whereas planimetry and linear methods tend to overestimate tumor volume. Furthermore, it is necessary to consider tumor roundness prior to linear measurement so as to choose the most appropriate method for each patient on an individual basis.

Statistical shape analysis of putamen in early-onset Parkinson's disease

OBJECTIVE

To investigate the shape differences in the putamen of early-onset Parkinson's patients compared with healthy controls and to assess and to assess sub-regional brain abnormalities.

METHODS

This study was conducted using the 3-T MRI scans of 23 early-onset Parkinson's patients and age and gender matched control subjects. Landmark coordinate data obtained and Procrustes analysis was used to compare mean shapes. The relationships between the centroid sizes of the left and right putamen, and the durations of disease examined using growth curve models.

RESULTS

While there was a significant difference between the right putamen shape of control and patient groups, there was not found a significant difference in terms of left putamen. Sub-regional analyses showed that for the right putamen, the most prominent deformations were localized in the middle-posterior putamen and minimal deformations were seen in the anterior putamen.

CONCLUSION

Although they were not as pronounced as those in the right putamen, the deformations in the left putamen mimic the deformations in the right putamen which are found mainly in the middle-posterior putamen and at a lesser extend in the anterior putamen.

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

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%.

Subcortical grey matter changes associated with motor symptoms evaluated by the Unified Parkinson's disease Rating Scale (part III): A longitudinal study in Parkinson's disease

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Decreased grey matter volume over time suggests a subcortical alteration in PD.

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Decreased volume in the thalamus may be related to the decline in motor skills.

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Increased volume in the pallidum may contribute to motor impairment.

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Structural changes in line with the model of basal ganglia-thalamocortical circuits.

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VBM and volumetry might capture complementary aspects of structural changes in PD.

Parkinson disease (PD) is characterized by motor deficits related to structural changes in the basal ganglia-thalamocortical circuits. However, it is still unclear the exact nature of the association between grey matter alterations and motor symptoms.

Therefore, the aim of our investigation was to identify the subcortical modifications associated with motor symptoms of PD over time - adopting voxel-based morphometry (VBM) and automated volumetry methods.

We selected fifty subjects with PD from the Parkinson’s Progression Markers Initiative (PPMI) database, who performed an MRI session at two time points: at baseline (i.e. at maximum 2 years after clinical diagnosis of PD) and after 48 months. Motor symptoms were assessed using the part III of the Unified Parkinson’s Disease Rating Scale at the two time points.

Our VBM and volumetric analyses showed a general atrophy in all subcortical regions when comparing baseline with 48 months. These findings confirmed previous observations indicating a subcortical alteration over time in PD. Furthermore, our findings supported the idea that a reduced volume in the thalamus and an increased volume in pallidum may be related to the decline in motor skills. These structural modifications are in accordance with the functional model of the basal ganglia-thalamocortical circuits controlling movements. Moreover, VBM and volumetry provided partially overlapping results, suggesting that these methods might capture complementary aspects of brain degeneration in PD.

Anterior cingulate cortex gray matter volume mediates an association between 2D:4D ratio and trait aggression in women but not men

Previous research demonstrates that prenatal testosterone exposure increases aggression, possibly through its effects on the structure and function of neural circuits supporting threat detection and emotion regulation. Here we examined associations between regional gray matter volume, trait aggression, and the ratio of the second and fourth digit of the hand (2D:4D ratio) as a putative index of prenatal testosterone exposure in 464 healthy young adult volunteers. Our analyses revealed a significant positive correlation between 2D:4D ratio and gray matter volume of the dorsal anterior cingulate cortex (dACC), a brain region supporting emotion regulation, conflict monitoring, and behavioral inhibition. Subsequent analyses demonstrated that reduced (i.e., masculinized) gray matter volume in the dACC mediated the relationship between 2D:4D ratio and aggression in women, but not men. Expanding on this gender-specific mediation, additional analyses demonstrated that the shared variance between 2D:4D ratio, dACC gray matter volume, and aggression in women reflected the tendency to engage in cognitive reappraisal of emotionally provocative stimuli. Our results provide novel evidence that 2D:4D ratio is associated with masculinization of dACC gray matter volume, and that this neural phenotype mediates, in part, the expression of trait aggression in women.

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

BACKGROUND

Schizophrenia is associated with various brain structural abnormalities, including reduced volume of the hippocampi, prefrontal lobes and thalami. Cannabis use increases the risk of schizophrenia but reports of brain structural abnormalities in the cannabis-using population have not been consistent. We used automated image analysis to compare brain structural changes over time in people at elevated risk of schizophrenia for familial reasons who did and did not use cannabis.

METHOD

Magnetic resonance imaging (MRI) scans were obtained from subjects at high familial risk of schizophrenia at entry to the Edinburgh High Risk Study (EHRS) and approximately 2 years later. Differential grey matter (GM) loss in those exposed (n=23) and not exposed to cannabis (n=32) in the intervening period was compared using tensor-based morphometry (TBM).

RESULTS

Cannabis exposure was associated with significantly greater loss of right anterior hippocampal (pcorrected=0.029, t=3.88) and left superior frontal lobe GM (pcorrected=0.026, t=4.68). The former finding remained significant even after the exclusion of individuals who had used other drugs during the inter-scan interval.

CONCLUSIONS

Using an automated analysis of longitudinal data, we demonstrate an association between cannabis use and GM loss in currently well people at familial risk of developing schizophrenia. This observation may be important in understanding the link between cannabis exposure and the subsequent development of schizophrenia.

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

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.