Advantages of Using Both Voxel- and Surface-based Morphometry in Cortical Morphology Analysis: A Review of Various Applications

Goto, Masayoshi; Abe, Osamu; Hagiwara, Akifumi; Fujita, Shohei; Kamagata, Koji; Hori, Masaaki; Aoki, Shigeki; Osada, Takahiro; Konishi, Seiki; Masutani, Yoshitaka; Sakamoto, Hajime; Sakano, Yasuaki; Kyogoku, Shinsuke; Daida, Hiroyuki

doi:10.2463/mrms.rev.2021-0096

Cited by 53 publications

(35 citation statements)

References 106 publications

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“…Esta técnica es muy útil para estimar indicadores de la morfología cortical, como el volumen, el espesor, el área y la girificación [80,87]. A partir de la MBS se pueden realizar análisis por regiones o sobre toda la superficie cerebral [44]. Dentro de su procesamiento se incluye: extracción del cerebro, corrección de señal, segmentación de tejidos, construcción de una superficie a partir de los segmentos, normalización espacial, suavizado y análisis estadístico [44].…”

Section: Morfometría Basada En Superficies (Mbs)unclassified

“…A partir de la MBS se pueden realizar análisis por regiones o sobre toda la superficie cerebral [44]. Dentro de su procesamiento se incluye: extracción del cerebro, corrección de señal, segmentación de tejidos, construcción de una superficie a partir de los segmentos, normalización espacial, suavizado y análisis estadístico [44]. Dentro de las herramientas más utilizadas para este tipo de análisis se encuentra FreeSurfer (https://surfer.nmr.mgh.harvard.edu/), BrainVISA (https://brainvisa.info/web/) y BrainVoyager (https://www.brainvoyager.com/).…”

Section: Morfometría Basada En Superficies (Mbs)unclassified

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Contribuciones al estudio de la sensibilidad de la morfometría basada en vóxel aplicada al estudio de la anatomía cerebral de roedores

Braggio¹

2022

RIDAA Tesis Unicen

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La morfometría basada en vóxel (MBV) es una de las técnicas de morfometría cerebral más utilizadas para la investigación de cambios morfológicos en el cerebro. MBV se ha utilizado en conjunto con la aplicación de modelos experimentales animales para investigar el efecto de diversas patologías y su efecto en los cambios de concentración y volumen de materia gris. A pesar de su amplio uso, no existe en la literatura un estudio exhaustivo de su sensibilidad y precisión al momento de detectar atrofias cerebrales en roedores. En este trabajo se aplicó la simulación de atrofias cerebrales en imágenes de resonancia magnética de ratones para poder evaluar el desempeño de diversas variantes de MBV. Se analizó el efecto que tiene el suavizado, la normalización espacial y el tamaño de muestra en los resultados de MBV. Adicionalmente, se estudió en profundidad la sensibilidad del método para detectar atrofias de diferente tamaño y nivel de pérdida de materia gris. Se demostró que los pasos del procesamiento utilizados en MBV son un factor clave en los resultados del método. Además, se pudieron establecer límites específicos de la precisión y sensibilidad del método sentando bases para la interpretación de sus resultados en casos experimentales reales. Voxel based morphometry (VBM) is one of the most widely used brain morphometry techniques for the investigation of morphological changes in the brain. MBV has been used, with the application of experimental animal models, to investigate the effect of various pathologies and their effect on changes in concentration and volume of gray matter. Despite its wide use, there is no exhaustive study in the literature of its sensitivity and accuracy when detecting brain atrophies in rodents. In this work, the simulation of cerebral atrophies in magnetic resonance images of mice was applied in order to evaluate the performance of various VBM pipelines. The effect of smoothing, spatial normalization and sample size on VBM results was analyzed. Additionally, the sensitivity of the method detecting atrophies of different sizes and levels of tissue loss was studied comprehensively. The processing steps used in VBM were shown to be a key factor in the results of the method. In addition, specific limits of the precision and sensitivity of the method could be established, laying the foundation for the interpretation of results in real experimental cases.

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Section: Morfometría Basada En Superficies (Mbs)unclassified

Contribuciones al estudio de la sensibilidad de la morfometría basada en vóxel aplicada al estudio de la anatomía cerebral de roedores

Braggio¹

2022

RIDAA Tesis Unicen

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“…The established links between frailty, cognitive decline, and functional impairments prompt the necessity to investigate brain structure in frailty [ 2 ]. Voxel based morphometry (VBM) can provide measures of white and gray matter density [ 3 , 4 , 5 , 6 ]. Ageing of the brain is not accompanied by significant neuronal loss [ 7 ]; whereas, WM volume rapidly declines after 60–70 years of age across multiple regions [ 8 , 9 ].…”

Section: Introductionmentioning

confidence: 99%

Resistance Training Increases White Matter Density in Frail Elderly Women

Bucci

Iozzo

Merisaari

et al. 2023

JCM

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We aimed to investigate the effects of maternal obesity on brain structure and metabolism in frail women, and their reversibility in response to exercise. We recruited 37 frail elderly women (20 offspring of lean/normal-weight mothers (OLM) and 17 offspring of obese/overweight mothers (OOM)) and nine non-frail controls to undergo magnetic resonance and diffusion tensor imaging (DTI), positron emission tomography with Fluorine-18-fluorodeoxyglucose (PET), and cognitive function tests (CERAD). Frail women were studied before and after a 4-month resistance training, and controls were studied once. White matter (WM) density (voxel-based morphometry) was higher in OLM than in OOM subjects. Exercise increased WM density in both OLM and OOM in the cerebellum in superior parietal regions in OLM and in cuneal and precuneal regions in OOM. OLM gained more WM density than OOM in response to intervention. No significant results were found from the Freesurfer analysis, nor from PET or DTI images. Exercise has an impact on brain morphology and cognition in elderly frail women.

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“…In this study, to address the difficulty of detecting cerebral oxygen metabolism changes in preeclampsia in a timely, non-invasive, and safe manner, we used QQ-based OEF mapping to evaluate brain metabolic oxygen consumption. Voxel-based morphometry (VBM) can detect brain injury at the voxel level [ 15 16 ] and detect brain abnormalities more sensitively. Therefore, we hypothesized that QQ-based OEF imaging combined with the VBM method could sensitively reveal abnormal cerebral oxygen metabolism and central nervous system damage in preeclampsia.…”

Section: Introductionmentioning

confidence: 99%

Assessing Cerebral Oxygen Metabolism Changes in Patients With Preeclampsia Using Voxel-Based Morphometry of Oxygen Extraction Fraction Maps in Magnetic Resonance Imaging

et al. 2023

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Objective The objective of this study was to analyze the different brain oxygen metabolism statuses in preeclampsia using magnetic resonance imaging and investigate the factors that affect cerebral oxygen metabolism in preeclampsia. Materials and Methods Forty-nine women with preeclampsia (mean age 32.4 years; range, 18–44 years), 22 pregnant healthy controls (PHCs) (mean age 30.7 years; range, 23–40 years), and 40 non-pregnant healthy controls (NPHCs) (mean age 32.5 years; range, 20–42 years) were included in this study. Brain oxygen extraction fraction (OEF) values were computed using quantitative susceptibility mapping (QSM) plus quantitative blood oxygen level-dependent magnitude-based OEF mapping (QSM + quantitative blood oxygen level-dependent imaging or QQ) obtained with a 1.5-T scanner. Voxel-based morphometry (VBM) was used to investigate the differences in OEF values in the brain regions among the groups. Results Among the three groups, the average OEF values were significantly different in multiple brain areas, including the parahippocampus, multiple gyri of the frontal lobe, calcarine, cuneus, and precuneus (all P -values were less than 0.05, after correcting for multiple comparisons). The average OEF values of the preeclampsia group were higher than those of the PHC and NPHC groups. The bilateral superior frontal gyrus/bilateral medial superior frontal gyrus had the largest size of the aforementioned brain regions, and the OEF values in this area were 24.2 ± 4.6, 21.3 ± 2.4, and 20.6 ± 2.8 in the preeclampsia, PHC, and NPHC groups, respectively. In addition, the OEF values showed no significant differences between NPHC and PHC. Correlation analysis revealed that the OEF values of some brain regions (mainly involving the frontal, occipital, and temporal gyrus) were positively correlated with age, gestational week, body mass index, and mean blood pressure in the preeclampsia group ( r = 0.361–0.812). Conclusion Using whole-brain VBM analysis, we found that patients with preeclampsia had higher OEF values than controls.

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Advantages of Using Both Voxel- and Surface-based Morphometry in Cortical Morphology Analysis: A Review of Various Applications

Cited by 53 publications

References 106 publications

Contribuciones al estudio de la sensibilidad de la morfometría basada en vóxel aplicada al estudio de la anatomía cerebral de roedores

Contribuciones al estudio de la sensibilidad de la morfometría basada en vóxel aplicada al estudio de la anatomía cerebral de roedores

Resistance Training Increases White Matter Density in Frail Elderly Women

Assessing Cerebral Oxygen Metabolism Changes in Patients With Preeclampsia Using Voxel-Based Morphometry of Oxygen Extraction Fraction Maps in Magnetic Resonance Imaging

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