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1.
Cereb Cortex ; 34(5)2024 May 02.
Artículo en Inglés | MEDLINE | ID: mdl-38771241

RESUMEN

The functional brain connectome is highly dynamic over time. However, how brain connectome dynamics evolves during the third trimester of pregnancy and is associated with later cognitive growth remains unknown. Here, we use resting-state functional Magnetic Resonance Imaging (MRI) data from 39 newborns aged 32 to 42 postmenstrual weeks to investigate the maturation process of connectome dynamics and its role in predicting neurocognitive outcomes at 2 years of age. Neonatal brain dynamics is assessed using a multilayer network model. Network dynamics decreases globally but increases in both modularity and diversity with development. Regionally, module switching decreases with development primarily in the lateral precentral gyrus, medial temporal lobe, and subcortical areas, with a higher growth rate in primary regions than in association regions. Support vector regression reveals that neonatal connectome dynamics is predictive of individual cognitive and language abilities at 2  years of age. Our findings highlight network-level neural substrates underlying early cognitive development.


Asunto(s)
Encéfalo , Cognición , Conectoma , Imagen por Resonancia Magnética , Humanos , Conectoma/métodos , Femenino , Masculino , Imagen por Resonancia Magnética/métodos , Cognición/fisiología , Recién Nacido , Encéfalo/crecimiento & desarrollo , Encéfalo/diagnóstico por imagen , Encéfalo/fisiología , Preescolar , Desarrollo del Lenguaje , Desarrollo Infantil/fisiología
2.
Hum Brain Mapp ; 45(7): e26695, 2024 May.
Artículo en Inglés | MEDLINE | ID: mdl-38727010

RESUMEN

Human infancy is marked by fastest postnatal brain structural changes. It also coincides with the onset of many neurodevelopmental disorders. Atlas-based automated structure labeling has been widely used for analyzing various neuroimaging data. However, the relatively large and nonlinear neuroanatomical differences between infant and adult brains can lead to significant offsets of the labeled structures in infant brains when adult brain atlas is used. Age-specific 1- and 2-year-old brain atlases covering all major gray and white matter (GM and WM) structures with diffusion tensor imaging (DTI) and structural MRI are critical for precision medicine for infant population yet have not been established. In this study, high-quality DTI and structural MRI data were obtained from 50 healthy children to build up three-dimensional age-specific 1- and 2-year-old brain templates and atlases. Age-specific templates include a single-subject template as well as two population-averaged templates from linear and nonlinear transformation, respectively. Each age-specific atlas consists of 124 comprehensively labeled major GM and WM structures, including 52 cerebral cortical, 10 deep GM, 40 WM, and 22 brainstem and cerebellar structures. When combined with appropriate registration methods, the established atlases can be used for highly accurate automatic labeling of any given infant brain MRI. We demonstrated that one can automatically and effectively delineate deep WM microstructural development from 3 to 38 months by using these age-specific atlases. These established 1- and 2-year-old infant brain DTI atlases can advance our understanding of typical brain development and serve as clinical anatomical references for brain disorders during infancy.


Asunto(s)
Atlas como Asunto , Encéfalo , Imagen de Difusión Tensora , Sustancia Gris , Sustancia Blanca , Humanos , Lactante , Preescolar , Masculino , Sustancia Blanca/diagnóstico por imagen , Sustancia Blanca/anatomía & histología , Sustancia Blanca/crecimiento & desarrollo , Femenino , Sustancia Gris/diagnóstico por imagen , Sustancia Gris/crecimiento & desarrollo , Sustancia Gris/anatomía & histología , Imagen de Difusión Tensora/métodos , Encéfalo/diagnóstico por imagen , Encéfalo/crecimiento & desarrollo , Encéfalo/anatomía & histología , Procesamiento de Imagen Asistido por Computador/métodos
3.
MAGMA ; 37(5): 845-857, 2024 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-38869733

RESUMEN

OBJECTIVE: To establish a multi-dimensional representation solely on structural MRI (sMRI) for early diagnosis of AD. METHODS: A total of 3377 participants' sMRI from four independent databases were retrospectively identified to construct an interpretable deep learning model that integrated multi-dimensional representations of AD solely on sMRI (called s2MRI-ADNet) by a dual-channel learning strategy of gray matter volume (GMV) from Euclidean space and the regional radiomics similarity network (R2SN) from graph space. Specifically, the GMV feature map learning channel (called GMV-Channel) was to take into consideration spatial information of both long-range spatial relations and detailed localization information, while the node feature and connectivity strength learning channel (called NFCS-Channel) was to characterize the graph-structured R2SN network by a separable learning strategy. RESULTS: The s2MRI-ADNet achieved a superior classification accuracy of 92.1% and 91.4% under intra-database and inter-database cross-validation. The GMV-Channel and NFCS-Channel captured complementary group-discriminative brain regions, revealing a complementary interpretation of the multi-dimensional representation of brain structure in Euclidean and graph spaces respectively. Besides, the generalizable and reproducible interpretation of the multi-dimensional representation in capturing complementary group-discriminative brain regions revealed a significant correlation between the four independent databases (p < 0.05). Significant associations (p < 0.05) between attention scores and brain abnormality, between classification scores and clinical measure of cognitive ability, CSF biomarker, metabolism, and genetic risk score also provided solid neurobiological interpretation. CONCLUSION: The s2MRI-ADNet solely on sMRI could leverage the complementary multi-dimensional representations of AD in Euclidean and graph spaces, and achieved superior performance in the early diagnosis of AD, facilitating its potential in both clinical translation and popularization.


Asunto(s)
Enfermedad de Alzheimer , Encéfalo , Aprendizaje Profundo , Sustancia Gris , Imagen por Resonancia Magnética , Humanos , Enfermedad de Alzheimer/diagnóstico por imagen , Imagen por Resonancia Magnética/métodos , Femenino , Masculino , Anciano , Estudios Retrospectivos , Encéfalo/diagnóstico por imagen , Sustancia Gris/diagnóstico por imagen , Bases de Datos Factuales , Diagnóstico Precoz , Persona de Mediana Edad , Procesamiento de Imagen Asistido por Computador/métodos , Anciano de 80 o más Años
4.
J Digit Imaging ; 36(4): 1302-1313, 2023 08.
Artículo en Inglés | MEDLINE | ID: mdl-36897422

RESUMEN

Chest radiography is the modality of choice for the identification of rib fractures in young children and there is value for the development of computer-aided rib fracture detection in this age group. However, the automated identification of rib fractures on chest radiographs can be challenging due to the need for high spatial resolution in deep learning frameworks. A patch-based deep learning algorithm was developed to automatically detect rib fractures on frontal chest radiographs in children under 2 years old. A total of 845 chest radiographs of children 0-2 years old (median: 4 months old) were manually segmented for rib fractures by radiologists and served as the ground-truth labels. Image analysis utilized a patch-based sliding-window technique, to meet the high-resolution requirements for fracture detection. Standard transfer learning techniques used ResNet-50 and ResNet-18 architectures. Area-under-curve for precision-recall (AUC-PR) and receiver-operating-characteristic (AUC-ROC), along with patch and whole-image classification metrics, were reported. On the test patches, the ResNet-50 model showed AUC-PR and AUC-ROC of 0.25 and 0.77, respectively, and the ResNet-18 showed an AUC-PR of 0.32 and AUC-ROC of 0.76. On the whole-radiograph level, the ResNet-50 had an AUC-ROC of 0.74 with 88% sensitivity and 43% specificity in identifying rib fractures, and the ResNet-18 had an AUC-ROC of 0.75 with 75% sensitivity and 60% specificity in identifying rib fractures. This work demonstrates the utility of patch-based analysis for detection of rib fractures in children under 2 years old. Future work with large cohorts of multi-institutional data will improve the generalizability of these findings to patients with suspicion of child abuse.


Asunto(s)
Aprendizaje Profundo , Fracturas de las Costillas , Humanos , Niño , Lactante , Preescolar , Recién Nacido , Fracturas de las Costillas/diagnóstico por imagen , Estudios Retrospectivos , Radiografía , Curva ROC
5.
J Digit Imaging ; 36(4): 1419-1430, 2023 08.
Artículo en Inglés | MEDLINE | ID: mdl-37099224

RESUMEN

Measurement of angles on foot radiographs is an important step in the evaluation of malalignment. The objective is to develop a CNN model to measure angles on radiographs, using radiologists' measurements as the reference standard. This IRB-approved retrospective study included 450 radiographs from 216 patients (< 3 years of age). Angles were automatically measured by means of image segmentation followed by angle calculation, according to Simon's approach for measuring pediatric foot angles. A multiclass U-Net model with a ResNet-34 backbone was used for segmentation. Two pediatric radiologists independently measured anteroposterior and lateral talocalcaneal and talo-1st metatarsal angles using the test dataset and recorded the time used for each study. Intraclass correlation coefficients (ICC) were used to compare angle and paired Wilcoxon signed-rank test to compare time between radiologists and the CNN model. There was high spatial overlap between manual and CNN-based automatic segmentations with dice coefficients ranging between 0.81 (lateral 1st metatarsal) and 0.94 (lateral calcaneus). Agreement was higher for angles on the lateral view when compared to the AP view, between radiologists (ICC: 0.93-0.95, 0.85-0.92, respectively) and between radiologists' mean and CNN calculated (ICC: 0.71-0.73, 0.41-0.52, respectively). Automated angle calculation was significantly faster when compared to radiologists' manual measurements (3 ± 2 vs 114 ± 24 s, respectively; P < 0.001). A CNN model can selectively segment immature ossification centers and automatically calculate angles with a high spatial overlap and moderate to substantial agreement when compared to manual methods, and 39 times faster.


Asunto(s)
Pie , Huesos Metatarsianos , Humanos , Niño , Preescolar , Estudios Retrospectivos , Estudios de Factibilidad , Pie/diagnóstico por imagen , Huesos Metatarsianos/diagnóstico por imagen , Redes Neurales de la Computación
6.
Dev Neurosci ; 44(4-5): 246-265, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-35279653

RESUMEN

Intrauterine hypoxia is a common cause of brain injury in children resulting in a broad spectrum of long-term neurodevelopmental sequela, including life-long disabilities that can occur even in the absence of severe neuroanatomic damage. Postnatal hypoxia-ischemia rodent models are commonly used to understand the effects of ischemia and transient hypoxia on the developing brain. Postnatal models, however, have some limitations. First, they do not test the impact of placental pathologies on outcomes from hypoxia. Second, they primarily recapitulate severe injury because they provoke substantial cell death, which is not seen in children with mild hypoxic injury. Lastly, they do not model preterm hypoxic injury. Prenatal models of hypoxia in mice may allow us to address some of these limitations to expand our understanding of developmental brain injury. The published rodent models of prenatal hypoxia employ multiple days of hypoxic exposure or complicated surgical procedures, making these models challenging to perform consistently in mice. Furthermore, large animal models suggest that transient prenatal hypoxia without ischemia is sufficient to lead to significant functional impairment to the developing brain. However, these large animal studies are resource-intensive and not readily amenable to mechanistic molecular studies. Therefore, here we characterized the effect of late gestation (embryonic day 17.5) transient prenatal hypoxia (5% inspired oxygen) on long-term anatomical and neurodevelopmental outcomes in mice. Late gestation transient prenatal hypoxia increased hypoxia-inducible factor 1 alpha protein levels (a marker of hypoxic exposure) in the fetal brain. Hypoxia exposure predisposed animals to decreased weight at postnatal day 2, which normalized by day 8. However, hypoxia did not affect gestational age at birth, litter size at birth, or pup survival. No differences in fetal brain cell death or long-term gray or white matter changes resulted from hypoxia. Animals exposed to prenatal hypoxia did have several long-term functional consequences, including sex-dichotomous changes. Hypoxia exposure was associated with a decreased seizure threshold and abnormalities in hindlimb strength and repetitive behaviors in males and females. Males exposed to hypoxia had increased anxiety-related deficits, whereas females had deficits in social interaction. Neither sex developed any motor or visual learning deficits. This study demonstrates that late gestation transient prenatal hypoxia in mice is a simple, clinically relevant paradigm for studying putative environmental and genetic modulators of the long-term effects of hypoxia on the developing brain.


Asunto(s)
Lesiones Encefálicas , Placenta , Animales , Animales Recién Nacidos , Encéfalo/patología , Lesiones Encefálicas/patología , Modelos Animales de Enfermedad , Femenino , Hipoxia , Masculino , Ratones , Embarazo , Convulsiones
7.
Eur Radiol ; 32(10): 6965-6976, 2022 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-35999372

RESUMEN

OBJECTIVES: Hippocampal radiomic features (HRFs) can serve as biomarkers in Alzheimer's disease (AD). However, how different hippocampal segmentation methods affect HRFs in AD is still unknown. The aim of the study was to investigate how different segmentation methods affect HRF accuracy in AD analysis. METHODS: A total of 1650 subjects were identified from the Alzheimer's Disease Neuroimaging Initiative database (ADNI). The mini-mental state examination (MMSE) and Alzheimer's disease assessment scale (ADAS-cog13) were also adopted. After calculating the HRFs of intensity, shape, and textural features from each side of the hippocampus in structural magnetic resonance imaging (sMRI), the consistency of HRFs calculated from 7 different hippocampal segmentation methods was validated, and the performance of machine learning-based classification of AD vs. normal control (NC) adopting the different HRFs was also examined. Additional 571 subjects from the European DTI Study on Dementia database (EDSD) were to validate the consistency of results. RESULTS: Between different segmentations, HRFs showed a high measurement consistency (R > 0.7), a high significant consistency between NC, mild cognitive impairment (MCI), and AD (T-value plot, R > 0.8), and consistent significant correlations between HRFs and MMSE/ADAS-cog13 (p < 0.05). The best NC vs. AD classification was obtained when the hippocampus was sufficiently segmented by primitive majority voting (threshold = 0.2). High consistent results were reproduced from independent EDSD cohort. CONCLUSIONS: HRFs exhibited high consistency across different hippocampal segmentation methods, and the best performance in AD classification was obtained when HRFs were extracted by the naïve majority voting method with a more sufficient segmentation and relatively low hippocampus segmentation accuracy. KEY POINTS: • The hippocampal radiomic features exhibited high measurement/statistical/clinical consistency across different hippocampal segmentation methods. • The best performance in AD classification was obtained when hippocampal radiomics were extracted by the naïve majority voting method with a more sufficient segmentation and relatively low hippocampus segmentation accuracy.


Asunto(s)
Enfermedad de Alzheimer , Disfunción Cognitiva , Enfermedad de Alzheimer/diagnóstico , Disfunción Cognitiva/patología , Hipocampo/diagnóstico por imagen , Hipocampo/patología , Humanos , Imagen por Resonancia Magnética/métodos , Neuroimagen/métodos
8.
Proc Natl Acad Sci U S A ; 116(10): 4681-4688, 2019 03 05.
Artículo en Inglés | MEDLINE | ID: mdl-30782802

RESUMEN

During the third trimester, the human brain undergoes rapid cellular and molecular processes that reshape the structural architecture of the cerebral cortex. Knowledge of cortical differentiation obtained predominantly from histological studies is limited in localized and small cortical regions. How cortical microstructure is differentiated across cortical regions in this critical period is unknown. In this study, the cortical microstructural architecture across the entire cortex was delineated with non-Gaussian diffusion kurtosis imaging as well as conventional diffusion tensor imaging of 89 preterm neonates aged 31-42 postmenstrual weeks. The temporal changes of cortical mean kurtosis (MK) or fractional anisotropy (FA) were heterogeneous across the cortical regions. Cortical MK decreases were observed throughout the studied age period, while cortical FA decrease reached its plateau around 37 weeks. More rapid decreases in MK were found in the primary visual region, while faster FA declines were observed in the prefrontal cortex. We found that distinctive cortical microstructural changes were coupled with microstructural maturation of associated white matter tracts. Both cortical MK and FA measurements predicted the postmenstrual age of preterm infants accurately. This study revealed a differential 4D spatiotemporal cytoarchitectural signature inferred by non-Gaussian diffusion barriers inside the cortical plate during the third trimester. The cytoarchitectural processes, including dendritic arborization and neuronal density decreases, were inferred by regional cortical FA and MK measurements. The presented findings suggest that cortical MK and FA measurements could be used as effective imaging markers for cortical microstructural changes in typical and potentially atypical brain development.


Asunto(s)
Encéfalo/diagnóstico por imagen , Encéfalo/crecimiento & desarrollo , Recien Nacido Prematuro/crecimiento & desarrollo , Anisotropía , Encéfalo/anatomía & histología , Encéfalo/fisiología , Imagen de Difusión Tensora , Femenino , Humanos , Lactante , Recién Nacido , Masculino
9.
Cereb Cortex ; 30(4): 2673-2689, 2020 04 14.
Artículo en Inglés | MEDLINE | ID: mdl-31819951

RESUMEN

Comprehensive delineation of white matter (WM) microstructural maturation from birth to childhood is critical for understanding spatiotemporally differential circuit formation. Without a relatively large sample of datasets and coverage of critical developmental periods of both infancy and early childhood, differential maturational charts across WM tracts cannot be delineated. With diffusion tensor imaging (DTI) of 118 typically developing (TD) children aged 0-8 years and 31 children with autistic spectrum disorder (ASD) aged 2-7 years, the microstructure of every major WM tract and tract group was measured with DTI metrics to delineate differential WM maturation. The exponential model of microstructural maturation of all WM was identified. The WM developmental curves were separated into fast, intermediate, and slow phases in 0-8 years with distinctive time period of each phase across the tracts. Shorter periods of the fast and intermediate phases in certain tracts, such as the commissural tracts, indicated faster earlier development. With TD WM maturational curves as the reference, higher residual variance of WM microstructure was found in children with ASD. The presented comprehensive and differential charts of TD WM microstructural maturation of all major tracts and tract groups in 0-8 years provide reference standards for biomarker detection of neuropsychiatric disorders.


Asunto(s)
Trastorno del Espectro Autista/diagnóstico por imagen , Encéfalo/diagnóstico por imagen , Encéfalo/crecimiento & desarrollo , Imagen de Difusión Tensora/tendencias , Sustancia Blanca/diagnóstico por imagen , Sustancia Blanca/crecimiento & desarrollo , Niño , Preescolar , Femenino , Humanos , Lactante , Recién Nacido , Masculino
10.
Cereb Cortex ; 29(10): 4208-4222, 2019 09 13.
Artículo en Inglés | MEDLINE | ID: mdl-30534949

RESUMEN

Individual variability in human brain networks underlies individual differences in cognition and behaviors. However, researchers have not conclusively determined when individual variability patterns of the brain networks emerge and how they develop in the early phase. Here, we employed resting-state functional MRI data and whole-brain functional connectivity analyses in 40 neonates aged around 31-42 postmenstrual weeks to characterize the spatial distribution and development modes of individual variability in the functional network architecture. We observed lower individual variability in primary sensorimotor and visual areas and higher variability in association regions at the third trimester, and these patterns are generally similar to those of adult brains. Different functional systems showed dramatic differences in the development of individual variability, with significant decreases in the sensorimotor network; decreasing trends in the visual, subcortical, and dorsal and ventral attention networks, and limited change in the default mode, frontoparietal and limbic networks. The patterns of individual variability were negatively correlated with the short- to middle-range connection strength/number and this distance constraint was significantly strengthened throughout development. Our findings highlight the development and emergence of individual variability in the functional architecture of the prenatal brain, which may lay network foundations for individual behavioral differences later in life.


Asunto(s)
Encéfalo/crecimiento & desarrollo , Recien Nacido Prematuro/crecimiento & desarrollo , Mapeo Encefálico , Femenino , Humanos , Lactante , Imagen por Resonancia Magnética , Masculino , Vías Nerviosas/crecimiento & desarrollo
11.
Neuroimage ; 185: 836-850, 2019 01 15.
Artículo en Inglés | MEDLINE | ID: mdl-29655938

RESUMEN

Dynamic macrostructural and microstructural changes take place from the mid-fetal stage to 2 years after birth. Delineating structural changes of the brain during early development provides new insights into the complicated processes of both typical development and the pathological mechanisms underlying various psychiatric and neurological disorders including autism, attention deficit hyperactivity disorder and schizophrenia. Decades of histological studies have identified strong spatial and functional maturation gradients in human brain gray and white matter. The recent improvements in magnetic resonance imaging (MRI) techniques, especially diffusion MRI (dMRI), relaxometry imaging, and magnetization transfer imaging (MTI) have provided unprecedented opportunities to non-invasively quantify and map the early developmental changes at whole brain and regional levels. Here, we review the recent advances in understanding early brain structural development during the second half of gestation and the first two postnatal years using modern MR techniques. Specifically, we review studies that delineate the emergence and microstructural maturation of white matter tracts, as well as dynamic mapping of inhomogeneous cortical microstructural organization unique to fetuses and infants. These imaging studies converge into maturational curves of MRI measurements that are distinctive across different white matter tracts and cortical regions. Furthermore, contemporary models offering biophysical interpretations of the dMRI-derived measurements are illustrated to infer the underlying microstructural changes. Collectively, this review summarizes findings that contribute to charting spatiotemporally heterogeneous gray and white matter structural development, offering MRI-based biomarkers of typical brain development and setting the stage for understanding aberrant brain development in neurodevelopmental disorders.


Asunto(s)
Mapeo Encefálico/métodos , Encéfalo/embriología , Encéfalo/crecimiento & desarrollo , Encéfalo/diagnóstico por imagen , Imagen de Difusión por Resonancia Magnética/métodos , Femenino , Feto , Humanos , Procesamiento de Imagen Asistido por Computador , Lactante , Recién Nacido , Masculino
12.
Neuroimage ; 185: 699-710, 2019 01 15.
Artículo en Inglés | MEDLINE | ID: mdl-29913282

RESUMEN

During the 3rd trimester, large-scale neural circuits are formed in the human brain, resulting in a highly efficient and segregated connectome at birth. Despite recent findings identifying important preterm human brain network properties such as rich-club organization, how the structural network develops differentially across brain regions and among different types of connections in this period is not yet known. Here, using high resolution diffusion MRI of 77 preterm-born and full-term neonates scanned at 31.9-41.7 postmenstrual weeks (PMW), we constructed structural connectivity matrices and performed graph-theory-based analyses. Faster increases of nodal efficiency were mainly located at the brain hubs distributed in primary sensorimotor regions, superior-middle frontal, and precuneus regions during 31.9-41.7PMW. Higher rates of edge strength increases were found in the rich-club and within-module connections, compared to other connections. The edge strength of short-range connections increased faster than that of long-range connections. Nodal efficiencies of the hubs predicted individual postmenstrual ages more accurately than those of non-hubs. Collectively, these findings revealed more rapid efficiency increases of the hub and rich-club connections as well as higher developmental rates of edge strength in short-range and within-module connections. These jointly underlie network segregation and differentiated emergence of brain functions.


Asunto(s)
Encéfalo/embriología , Red Nerviosa/embriología , Mapeo Encefálico/métodos , Imagen de Difusión por Resonancia Magnética , Femenino , Humanos , Recién Nacido , Recien Nacido Prematuro , Masculino
13.
Neuroimage ; 185: 685-698, 2019 01 15.
Artículo en Inglés | MEDLINE | ID: mdl-29959046

RESUMEN

During the 3rd trimester, dramatic structural changes take place in the human brain, underlying the neural circuit formation. The survival rate of premature infants has increased significantly in recent years. The large morphological differences of the preterm brain at 33 or 36 postmenstrual weeks (PMW) from the brain at 40PMW (full term) make it necessary to establish age-specific atlases for preterm brains. In this study, with high quality (1.5 × 1.5 × 1.6 mm3 imaging resolution) diffusion tensor imaging (DTI) data obtained from 84 healthy preterm and term-born neonates, we established age-specific preterm and term-born brain templates and atlases at 33, 36 and 39PMW. Age-specific DTI templates include a single-subject template, a population-averaged template with linear transformation and a population-averaged template with nonlinear transformation. Each of the age-specific DTI atlases includes comprehensive labeling of 126 major gray matter (GM) and white matter (WM) structures, specifically 52 cerebral cortical structures, 40 cerebral WM structures, 22 brainstem and cerebellar structures and 12 subcortical GM structures. From 33 to 39 PMW, dramatic morphological changes of delineated individual neural structures such as ganglionic eminence and uncinate fasciculus were revealed. The evaluation based on measurements of Dice ratio and L1 error suggested reliable and reproducible automated labels from the age-matched atlases compared to labels from manual delineation. Applying these atlases to automatically and effectively delineate microstructural changes of major WM tracts during the 3rd trimester was demonstrated. The established age-specific DTI templates and atlases of 33, 36 and 39 PMW brains may be used for not only understanding normal functional and structural maturational processes but also detecting biomarkers of neural disorders in the preterm brains.


Asunto(s)
Atlas como Asunto , Encéfalo/embriología , Sustancia Gris/embriología , Sustancia Blanca/embriología , Conjuntos de Datos como Asunto , Imagen de Difusión Tensora , Femenino , Edad Gestacional , Humanos , Procesamiento de Imagen Asistido por Computador , Recién Nacido , Recien Nacido Prematuro , Masculino , Vías Nerviosas/embriología
14.
NMR Biomed ; 32(7): e4103, 2019 07.
Artículo en Inglés | MEDLINE | ID: mdl-31038246

RESUMEN

There is increasing interest in applying physiological MRI in neonates, based on the premise that physiological parameters may provide an early biomarker of neonatal brain health and injury. Two commonly used techniques are oxygen extraction fraction (OEF) measurement using T2 -relaxation-under-spin-tagging (TRUST) MRI and cerebral blood flow measurement using phase-contrast (PC) quantitative flow MRI, which collectively provide an assessment of the brain's oxygen consumption. However, prior research has only demonstrated proof of principle of these methods in neonates, without characterization or benchmarking of the techniques. This is because available time is limited in neonatal subjects, especially when scans are performed as add-ons to clinical scans (typically less than 5 min). The work presented aims to examine the TRUST and PC MRI sequences systematically in normal neonates, through research-dedicated scan sessions. A series of characterization and optimization studies were conducted in a total of 26 radiographically normal neonates on 3 T systems. Our results show that TRUST MRI at the superior sagittal sinus (SSS) provides an OEF measurement equivalent to that at the internal jugular vein (r = 0.80, n = 10), yet with shorter scan time. Lower resolution provided better precision in the TRUST measurement (p = 0.001, n = 9). Therefore, the preferred OEF measurement is to apply TRUST MRI at the SSS using a spatial resolution of 2.5 mm. For PC MRI, our results showed that non-gated PC MRI yielded blood flow measurements comparable to those from the more time-consuming gated approach in neonates (r = 0.89, n = 7). It was also found that blood flow could be overestimated by 18% when imaging resolution is larger than 0.3 mm (n = 7). Therefore, non-gated PC MRI with a spatial resolution of 0.3 mm is recommended for neonatal applications. In conclusion, this study verifies consistency of neonatal brain oxygenation and flow measurements across acquisition schemes and points to optimal strategies in parameter selection when using these sequences.


Asunto(s)
Encéfalo/irrigación sanguínea , Circulación Cerebrovascular/fisiología , Imagen por Resonancia Magnética , Oxígeno/metabolismo , Femenino , Humanos , Recién Nacido , Masculino , Marcadores de Spin
15.
Neuroradiology ; 61(1): 63-70, 2019 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-30298188

RESUMEN

PURPOSE: Previous studies have investigated the brain structural abnormalities in children with type I Gaucher disease (GD). The purpose of our study is to investigate the topological efficiency of the brain functional network in children with type 1 GD. METHODS: Twenty-two children diagnosed with type 1 GD and 22 sex- and age-matched healthy controls (HCs) underwent resting-state functional MRI (rs-fMRI) examination. For longitudinal study, the GD patients underwent rs-fMRI examination again after 4.6 years. Graph theoretical analysis was used to assess the brain network topological properties at the global and regional levels. RESULTS: Compared with the HCs, the children with type 1 GD showed a decreased efficiency in functional segregation with a decreased γ (normalized clustering coefficient). In addition, the balance between functional segregation and integration was disrupted with decreased small-worldness (σ). At the regional level, the children with type 1 GD showed significantly decreased nodal degree and efficiency in the right precentral gyrus (PreCG.R) and left postcentral gyrus (PoCG.L). The significantly altered γ, σ, and nodal degree in the PreCG.R and PoCG.L were negatively correlated with the disease duration. No significant alterations in the global and regional topological properties were identified in these patients over time. CONCLUSION: Compared with that of the HCs, the efficiency of the brain functional network in the children with type 1 GD was disrupted, and regional involvement was located in motor- and sensory-related regions. The efficiency of the brain functional network in these patients remained stable over time.


Asunto(s)
Mapeo Encefálico/métodos , Enfermedad de Gaucher/diagnóstico por imagen , Imagen por Resonancia Magnética/métodos , Red Nerviosa/diagnóstico por imagen , Estudios de Casos y Controles , Niño , Femenino , Enfermedad de Gaucher/patología , Humanos , Interpretación de Imagen Asistida por Computador , Estudios Longitudinales , Masculino , Red Nerviosa/patología
16.
Cereb Cortex ; 27(3): 1949-1963, 2017 03 01.
Artículo en Inglés | MEDLINE | ID: mdl-26941380

RESUMEN

Human brain functional networks are topologically organized with nontrivial connectivity characteristics such as small-worldness and densely linked hubs to support highly segregated and integrated information processing. However, how they emerge and change at very early developmental phases remains poorly understood. Here, we used resting-state functional MRI and voxel-based graph theory analysis to systematically investigate the topological organization of whole-brain networks in 40 infants aged around 31 to 42 postmenstrual weeks. The functional connectivity strength and heterogeneity increased significantly in primary motor, somatosensory, visual, and auditory regions, but much less in high-order default-mode and executive-control regions. The hub and rich-club structures in primary regions were already present at around 31 postmenstrual weeks and exhibited remarkable expansions with age, accompanied by increased local clustering and shortest path length, indicating a transition from a relatively random to a more organized configuration. Moreover, multivariate pattern analysis using support vector regression revealed that individual brain maturity of preterm babies could be predicted by the network connectivity patterns. Collectively, we highlighted a gradually enhanced functional network segregation manner in the third trimester, which is primarily driven by the rapid increases of functional connectivity of the primary regions, providing crucial insights into the topological development patterns prior to birth.


Asunto(s)
Encéfalo/diagnóstico por imagen , Encéfalo/crecimiento & desarrollo , Recien Nacido Prematuro/crecimiento & desarrollo , Encéfalo/fisiología , Conectoma , Femenino , Humanos , Procesamiento de Imagen Asistido por Computador , Lactante , Recien Nacido Prematuro/fisiología , Imagen por Resonancia Magnética/métodos , Masculino , Vías Nerviosas/diagnóstico por imagen , Vías Nerviosas/crecimiento & desarrollo , Vías Nerviosas/fisiología , Descanso
17.
Neuroimage ; 147: 233-242, 2017 02 15.
Artículo en Inglés | MEDLINE | ID: mdl-27988320

RESUMEN

The human brain develops rapidly during 32-45 postmenstrual weeks (PMW), a critical stage characterized by dramatic increases of metabolic demand. The increasing metabolic demand can be inferred through measurements of regional cerebral blood flow (CBF), which might be coupled to regional metabolism in preterm brains. Arterial spin labeled (ASL) perfusion MRI is one of the few viable approaches for imaging regional CBF of preterm brains, but must be optimized for the extremely slow blood velocity unique in preterm brains. In this study, we explored the spatiotemporal CBF distribution in newborns scanned at the age of 32-45PMW using a pseudo-continuous ASL (pCASL) protocol adapted to slow blood flow in neonates. A total of 89 neonates were recruited. PCASL MRI was acquired from 34 normal newborns and phase contrast (PC) images from 19 newborns. Diffusion tensor images (DTI) were acquired from all 89 neonates for measuring cortical fractional anisotropy (FA), which characterizes cortical microstructure. Reproducible CBF measurements were obtained with the adjusted pCASL sequence. Global CBF measurement based on PC MRI was found to double its value in the 3rd trimester. Regional CBF increases were heterogeneous across the brain with a significantly higher rate of CBF increase in the frontal lobe and a lower rate of CBF increase in the occipital lobe. A significant correlation was found between frontal cortical CBF and cortical FA measurements (p<0.01). Increasing CBF values observed in the frontal lobe corresponded to lower FA values, suggesting that dendritic arborization and synaptic formation might be associated with an elevated local CBF. These results offer a preliminary account of heterogeneous regional CBF increases in a vital early developmental period and may shed the light on underlying metabolic support for cortical microstructural changes during the developmental period of 32-45PMW. Preterm effects and limitations of pCASL techniques in newborns need to be carefully considered for interpretation these results.


Asunto(s)
Encéfalo , Circulación Cerebrovascular/fisiología , Angiografía por Resonancia Magnética/métodos , Encéfalo/anatomía & histología , Encéfalo/diagnóstico por imagen , Encéfalo/fisiología , Imagen de Difusión Tensora , Femenino , Edad Gestacional , Humanos , Recién Nacido , Recien Nacido Prematuro , Masculino , Marcadores de Spin
18.
Hum Brain Mapp ; 38(11): 5375-5390, 2017 11.
Artículo en Inglés | MEDLINE | ID: mdl-28815879

RESUMEN

Multiple sclerosis (MS) involves damage to white matter microstructures. This damage has been related to grey matter function as measured by standard, physiologically-nonspecific neuroimaging indices (i.e., blood-oxygen-level dependent signal [BOLD]). Here, we used calibrated functional magnetic resonance imaging and diffusion tensor imaging to examine the extent to which specific, evoked grey matter physiological processes were associated with white matter diffusion in MS. Evoked changes in BOLD, cerebral blood flow (CBF), and oxygen metabolism (CMRO2 ) were measured in visual cortex. Individual differences in the diffusion tensor measure, radial diffusivity, within occipital tracts were strongly associated with MS patients' BOLD and CMRO2 . However, these relationships were in opposite directions, complicating the interpretation of the relationship between BOLD and white matter microstructural damage in MS. CMRO2 was strongly associated with individual differences in patients' fatigue and neurological disability, suggesting that alterations to evoked oxygen metabolic processes may be taken as a marker for primary symptoms of MS. This work demonstrates the first application of calibrated and diffusion imaging together and details the first application of calibrated functional MRI in a neurological population. Results lend support for neuroenergetic hypotheses of MS pathophysiology and provide an initial demonstration of the utility of evoked oxygen metabolism signals for neurology research. Hum Brain Mapp 38:5375-5390, 2017. © 2017 Wiley Periodicals, Inc.


Asunto(s)
Sustancia Gris/metabolismo , Esclerosis Múltiple/diagnóstico por imagen , Esclerosis Múltiple/metabolismo , Corteza Visual/diagnóstico por imagen , Corteza Visual/metabolismo , Sustancia Blanca/diagnóstico por imagen , Adulto , Mapeo Encefálico/métodos , Calibración , Circulación Cerebrovascular/fisiología , Estudios de Cohortes , Imagen de Difusión Tensora/métodos , Femenino , Sustancia Gris/diagnóstico por imagen , Sustancia Gris/patología , Humanos , Imagen por Resonancia Magnética/métodos , Masculino , Persona de Mediana Edad , Esclerosis Múltiple/patología , Oxígeno/metabolismo , Índice de Severidad de la Enfermedad , Corteza Visual/patología , Sustancia Blanca/metabolismo , Sustancia Blanca/patología
19.
Hum Brain Mapp ; 37(2): 819-32, 2016 Feb.
Artículo en Inglés | MEDLINE | ID: mdl-26663516

RESUMEN

Atypical age-dependent changes of white matter (WM) microstructure play a central role in abnormal brain maturation of the children with autism spectrum disorder (ASD), but their early manifestations have not been systematically characterized. The entire brain core WM voxels were surveyed to detect differences in WM microstructural development between 31 children with ASD of 2-7 years and 19 age-matched children with typical development (TD), using measurements of fractional anisotropy (FA) and radial diffusivity (RD) from diffusion tensor imaging (DTI). The anatomical locations, distribution, and extent of the core WM voxels with atypical age-dependent changes in a specific tract or tract group were delineated and evaluated by integrating the skeletonized WM with a digital atlas. Exclusively, unidirectional FA increases and RD decreases in widespread WM tracts were revealed in children with ASD before 4 years, with bi-directional changes found for children with ASD of 2-7 years. Compared to progressive development that raised FA and lowered RD during 2-7 years in the TD group, flattened curves of WM maturation were found in multiple major WM tracts of all five tract groups, particularly associational and limbic tracts, in the ASD group with trend lines of ASD and TD crossed around 4 years. We found atypical age-dependent changes of FA and RD widely and heterogeneously distributed in WM tracts of children with ASD. The early higher WM microstructural integrity before 4 years reflects abnormal neural patterning, connectivity, and pruning that may contribute to aberrant behavioral and cognitive development in ASD. Hum Brain Mapp 37:819-832, 2016. © 2015 Wiley Periodicals, Inc.


Asunto(s)
Trastorno del Espectro Autista/patología , Encéfalo/crecimiento & desarrollo , Encéfalo/patología , Sustancia Blanca/crecimiento & desarrollo , Sustancia Blanca/patología , Niño , Preescolar , Análisis por Conglomerados , Imagen de Difusión Tensora , Humanos , Procesamiento de Imagen Asistido por Computador , Modelos Lineales , Masculino , Vías Nerviosas/crecimiento & desarrollo , Vías Nerviosas/patología , Índice de Severidad de la Enfermedad
20.
bioRxiv ; 2024 Apr 11.
Artículo en Inglés | MEDLINE | ID: mdl-38645183

RESUMEN

Infant cerebral blood flow (CBF) delivers nutrients and oxygen to fulfill brain energy consumption requirements for the fastest period of postnatal brain development across lifespan. However, organizing principle of whole-brain CBF dynamics during infancy remains obscure. Leveraging a unique cohort of 100+ infants with high-resolution arterial spin labeled MRI, we found the emergence of the cortical hierarchy revealed by highest-resolution infant CBF maps available to date. Infant CBF across cortical regions increased in a biphasic pattern with initial rapid and sequentially slower rate, with break-point ages increasing along the limbic-sensorimotor-association cortical gradient. Increases in CBF in sensorimotor cortices were associated with enhanced language and motor skills, and frontoparietal association cortices for cognitive skills. The study discovered emergence of the hierarchical limbic-sensorimotor-association cortical gradient in infancy, and offers standardized reference of infant brain CBF and insight into the physiological basis of cortical specialization and real-world infant developmental functioning.

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