Impacts of skull stripping on construction of three-dimensional T1-weighted imaging-based brain structural network in full-term neonates

Abstract Background: Skull stripping remains a challenge for neonatal brain MR image analysis. However, little is known about how accuracy of the skull stripping affects the neonatal brain tissue segmentation and subsequent network construction. This paper therefore aimed to clarify this issue by comparing two automatic (FSL’s Brain Extraction Tool, BET; Infant Brain Extraction and Analysis Toolbox, iBEAT) and a semiautomatic (iBEAT with manual correction) processes in constructing 3D T1-weighted imaging (T1WI)-based brain structural network. Methods: Twenty-two full-term neonates (gestational age, 37-42 weeks; boys/girls, 13/9) without abnormalities on MRI who underwent brain 3D T1WI were retrospectively recruited. Two automatic (BET and iBEAT) and a semiautomatic preprocessing (iBEAT with manual correction) workflows were separately used to perform the skull stripping. Brain tissue segmentation and volume calculation were performed by a John Hopkins atlas-based method. Sixty-four gray matter regions were selected as nodes; volume covariance network and its properties (clustering coefficient, C p ; characteristic path length, L p ; local efficiency, E local ; global efficiency, E global ) were calculated by GRETNA. Analysis of variance (ANOVA) was used to compare the differences in the calculated volumes between three workflows. Results: There were significant differences in volumes of 48 brain region between three workflows ( P <0.05). Three neonatal brain structural networks presented small-world topology. The semiautomatic workflow showed remarkably decreased C p , increased L p , decreased E local , and E global , in contrast to two automatic ones. Conclusions: Imperfect skull stripping indeed affected the accuracy of brain structural network in full-term neonates.

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Impacts of skull stripping on construction of three-dimensional T1-weighted imaging-based brain structural network in full-term neonates

10.21203/rs.2.22268/v3 ◽

2020 ◽

Author(s):

Geliang Wang ◽

Yajie Hu ◽

Xianjun Li ◽

Miaomiao Wang ◽

Congcong Liu ◽

...

Keyword(s):

Brain Tissue ◽

Full Term ◽

Neonatal Brain ◽

Tissue Segmentation ◽

Term Neonates ◽

Brain Extraction ◽

Brain Tissue Segmentation ◽

Skull Stripping ◽

Structural Network ◽

Manual Correction

Abstract Background: Skull stripping remains a challenge for neonatal brain MR image analysis. However, little is known about how accuracy of the skull stripping affects the neonatal brain tissue segmentation and subsequent network construction. This paper therefore aimed to clarify this issue by comparing two automatic (FMRIB Software Library's Brain Extraction Tool, BET; Infant Brain Extraction and Analysis Toolbox, iBEAT) and a semiautomatic (iBEAT with manual correction) processes in constructing 3D T1-Weighted Imaging (T1WI)-based brain structural network. Methods: Twenty-two full-term neonates (gestational age, 37-42 weeks; boys/girls, 13/9) without abnormalities on MRI who underwent brain 3D T1WI were retrospectively recruited. Two automatic (BET and iBEAT) and a semiautomatic preprocessing (iBEAT with manual correction) workflows were separately used to perform the skull stripping. Brain tissue segmentation and volume calculation were performed by a John Hopkins atlas-based method. Sixty-four gray matter regions were selected as nodes; volume covariance network and its properties (clustering coefficient, C p ; characteristic path length, L p ; local efficiency, E local ; global efficiency, E global ) were calculated by GRETNA. Analysis of variance (ANOVA) was used to compare the differences in the calculated volume between three workflows. Results: There were significant differences in volumes of 50 brain regions between three workflows ( P <0.05). Three neonatal brain structural networks presented small-world topology. The semiautomatic workflow showed remarkably decreased C p , increased L p , decreased E local , and decreased E global , in contrast to two automatic ones. Conclusions: Imperfect skull stripping indeed affected the accuracy of brain structural network in full-term neonates.

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Impacts of skull stripping on construction of three-dimensional T1-weighted imaging-based brain structural network in full-term neonates

10.21203/rs.2.22268/v2 ◽

2020 ◽

Author(s):

Geliang Wang ◽

Yajie Hu ◽

Xianjun Li ◽

Miaomiao Wang ◽

Congcong Liu ◽

...

Keyword(s):

Brain Tissue ◽

Full Term ◽

Neonatal Brain ◽

Tissue Segmentation ◽

Term Neonates ◽

Brain Extraction ◽

Brain Tissue Segmentation ◽

Skull Stripping ◽

Structural Network ◽

Manual Correction

Abstract Background: Skull stripping remains a challenge for neonatal brain MR image analysis. However, little is known about how accuracy of the skull stripping affects the neonatal brain tissue segmentation and subsequent network construction. This paper therefore aimed to clarify this issue by comparing two automatic (FMRIB Software Library's Brain Extraction Tool, BET; Infant Brain Extraction and Analysis Toolbox, iBEAT) and a semiautomatic (iBEAT with manual correction) processes in constructing 3D T1-Weighted Imaging (T1WI)-based brain structural network. Methods: Twenty-two full-term neonates (gestational age, 37-42 weeks; boys/girls, 13/9) without abnormalities on MRI who underwent brain 3D T1WI were retrospectively recruited. Two automatic (BET and iBEAT) and a semiautomatic preprocessing (iBEAT with manual correction) workflows were separately used to perform the skull stripping. Brain tissue segmentation and volume calculation were performed by a John Hopkins atlas-based method. Sixty-four gray matter regions were selected as nodes; volume covariance network and its properties (clustering coefficient, C p ; characteristic path length, L p ; local efficiency, E local ; global efficiency, E global ) were calculated by GRETNA. Analysis of variance (ANOVA) was used to compare the differences in the calculated volume between three workflows. Results: There were significant differences in volumes of 50 brain regions between three workflows ( P <0.05). Three neonatal brain structural networks presented small-world topology. The semiautomatic workflow showed remarkably decreased C p , increased L p , decreased E local , and decreased E global , in contrast to two automatic ones. Conclusions: Imperfect skull stripping indeed affected the accuracy of brain structural network in full-term neonates.

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Application value of three-dimensional arterial spin labeling perfusion imaging in investigating cerebral blood flow dynamics in normal full-term neonates

BMC Pediatrics ◽

10.1186/s12887-019-1876-x ◽

2019 ◽

Vol 19 (1) ◽

Author(s):

Jia-Ning Wang ◽

Jia Li ◽

Huai-Jun Liu ◽

Xiao-Ping Yin ◽

Huan Zhou ◽

...

Keyword(s):

Blood Flow ◽

Cerebral Blood Flow ◽

White Matter ◽

Basal Ganglia ◽

Three Dimensional ◽

Full Term ◽

Term Neonates ◽

Corona Radiata ◽

Frontal White Matter ◽

Blood Flow Dynamics

Abstract Background This study aims to investigate the application value of three-dimensional arterial spin labeling (3DASL) in investigating cerebral blood flow dynamics in full-term neonates. Methods A total of 60 full-term neonates without known intracranial pathology were recruited for 3DASL examination. These neonates were divided into three groups: 1–3 day group, 4–7 day group, and 8–15 day group. On the cerebral blood flow (CBF) images, regions of interest (ROI) were selected from the frontal white matter, parietal white matter, basal ganglia, corona radiata, thalamus and brainstem, and the CBF values of each ROI were recorded. The CBF values of ROIs at bilaterally symmetric locations, the values of each ROI between males and females, and the values of each ROI among these three different age groups were compared. Results The difference in CBF values of the frontal white matter, parietal white matter, basal ganglia, corona radiata and thalamus at the bilateral symmetric positions were not statistically significant. There was no statistical difference in the CBF values of each brain region between the male and female groups. The CBF values at the basal ganglia region, corona radiata and parietal white matter were higher in the 8–15 day group, when compared to the 1–3 day and 4–7 day groups (P < 0.05). The CBF value at the basal ganglia region was higher in the 4–7 day group, when compared to the 1–3 day group (P < 0.05). The CBF value at the frontal white matter was lower in the 4–7 day group, when compared to the 1–3 day and 8–15 day group (P < 0.05). The CBF value at the brainstem was higher in the 4–7 day group, when compared to the 1–3 day and 8–15 day groups (P < 0.05). Conclusion The 3DASL can quantitatively measure CBF, and be used to evaluate cerebral hemodynamics in neonates. The basal ganglia region and corona radiata CBF increases with the increase in neonatal diurnal age.

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Assessment of serum levels of vitamin B12 in full term neonates with indirect hyperbilirubinemia

Annals of Neonatology Journal ◽

10.21608/anj.2019.45667 ◽

2019 ◽

Vol 0 (0) ◽

pp. 0-0

Author(s):

Gamal Mohamed ◽

Reem Abdel-Salam ◽

Rabie Mortada

Keyword(s):

Vitamin B12 ◽

Serum Levels ◽

Full Term ◽

Term Neonates

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Cord Blood Alkaline Phosphatase as a predictor of Neonatal Jaundice in full term neonates

Zagazig University Medical Journal ◽

10.21608/zumj.2020.43247.1948 ◽

2020 ◽

Vol 0 (0) ◽

pp. 0-0

Author(s):

Samah Esmail ◽

Ali Abdo ◽

Sherief Elgebaly ◽

Marwa Mostafa

Keyword(s):

Alkaline Phosphatase ◽

Cord Blood ◽

Neonatal Jaundice ◽

Full Term ◽

Term Neonates

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Midwifery/Nursing management of hypoglycaemia in healthy full term neonates

JBI Library of Systematic Reviews ◽

10.11124/jbisrir-2003-651 ◽

2003 ◽

Vol 1 (Supplement) ◽

pp. 1-8

Keyword(s):

Full Term ◽

Nursing Management ◽

Term Neonates

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Sufentanil Disposition and Pharmacokinetic Model-Based Dosage Regimen for Sufentanil in Ventilated Full-Term Neonates

Pharmacology ◽

10.1159/000515787 ◽

2021 ◽

pp. 1-6

Author(s):

Pavla Pokorná ◽

Martin Šíma ◽

Birgit Koch ◽

Dick Tibboel ◽

Ondřej Slanař

Keyword(s):

Linear Regression ◽

Dosage Regimen ◽

Regression Models ◽

Drug Disposition ◽

Prospective Trial ◽

Full Term ◽

Pharmacokinetic Parameters ◽

Therapeutic Drug ◽

Linear Regression Models ◽

Term Neonates

Introduction: Sufentanil is a potent synthetic opioid used for analgesia in neonates; however, data concerning drug disposition of sufentanil and dosage regimen are sparse in this population. Therefore, the aim of the study was to explore sufentanil disposition and to propose optimal loading and maintenance doses of sufentanil in ventilated full-term neonates. Methods: Individual sufentanil pharmacokinetic parameters were calculated based on therapeutic drug monitoring data using a 2-compartmental model. Linear regression models were used to explore the covariates. Results: The median (IQR) central volume of distribution (Vdc) and clearance (CL) for sufentanil were 4.7 (4.1–5.4) L/kg and 0.651 (0.433–0.751) L/h/kg, respectively. Linear regression models showed relationship between Vdc (L) and GA (r2 = 0.3436; p = 0.0452) as well as BW (r2 = 0.4019; p = 0.0268). Median optimal sufentanil LD and MD were 2.13 (95% CI: 1.78–2.48) μg/kg and 0.29 (95% CI: 0.22–0.37) μg/kg/h, respectively. Median daily COMFORT-B (IQR) scores ranged from 6 to 23 while no significant relationship between pharmacokinetic parameters and COMFORT-B scores was found. Discussion/Conclusion: Body weight and gestational age were found as weak covariates for sufentanil distribution, and the dosage regimen was developed for a prospective trial.

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