Cortical development in fetuses with congenital heart defects using an automated brain‐age prediction algorithm

Everwijn, S.M.; Namburete, Ana I. L.; Geloven, Nan van; Jansen, Frederik W.; Papageorghiou, Aris T.; Noble, J. Alison; Teunissen, A. K. K.; Rozendaal, L.; Blom, Nico A.; Lith, J. M. M. van; Haak, Monique C.

doi:10.1111/aogs.13687

Cited by 7 publications

(3 citation statements)

References 30 publications

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“…Cases were found to have significantly less mature brains than controls: −3.2 days, 95%CI (1.6; 4.8) p = < . 001 30 (Figure 1). When comparing the slopes, no significant difference was found in maturation velocity between cases and controls (maturation difference = 0.2 days/week, 95%CI [−0.2; 0.5] P = .…”

Section: Resultsmentioning

confidence: 99%

The association between flow and oxygenation and cortical development in fetuses with congenital heart defects using a brain‐age prediction algorithm

et al. 2020

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Objectives Presumably, changes in fetal circulation contribute to the delay in maturation of the cortex in fetuses with congenital heart defect (CHD). The aim of the current study is to analyze fetal brain development based on hemodynamic differences, using novel brain‐age prediction software. Methods We have performed detailed neurosonography, including acquiring 3D volumes, prospectively in cases with isolated CHD from 20 weeks onwards. An algorithm that assesses the degree of fetal brain‐age automatically was used to compare CHD cases to controls. We stratified CHD cases according to flow and oxygenation profiles by lesion physiology and performed subgroup analyses. Results A total of 616 ultrasound volumes of 162 CHD cases and 75 controls were analyzed. Significant differences in maturation of the cortex were observed in cases with normal blood flow toward the brain (−3.8 days, 95%CI [−5.5; −2.0], P = <.001) and low (−4.0 days, 95% CI [−6.7; −1.2] P = <.05; hypoplastic left heart syndrome[HLHS]) and mixed (−4.4 days, 95%CI [−6.4; −2.5] p = <.001) oxygen saturation in the ascending aorta (TGA) and in cardiac mixing (eg, Fallot) cases. Conclusion The current study shows significant delay in brain‐age in TGA and Fallot cases as compared to control cases. However, the small differences found in this study questions the clinical relevance.

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Section: Resultsmentioning

confidence: 99%

The association between flow and oxygenation and cortical development in fetuses with congenital heart defects using a brain‐age prediction algorithm

et al. 2020

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“…The in- and exclusion criteria and CHD-types for the HAND-study have been previously described. (5) , (6) The study protocol was approved by the local ethics committee (P13.07). In the CHD-group, cases with extracardiac structural malformations or genetic syndromes were not included.…”

Section: Methodsmentioning

confidence: 99%

Feasibility of neurosonography in CHD-fetuses and controls in a clinical tertiary setting

Everwijn,

van Bohemen,

Jansen

et al. 2024

European Journal of Obstetrics & Gynecology and Reproductiv

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“…However, the study did not explain the reasons for these differences or whether they were only due to decreased oxygenated blood flow to the fetal brain. The authors have previously published another study on this matter and concluded that, compared to healthy control cases, fetuses with isolated congenital heart abnormalities had a slight delay in their cortical development [134].…”

Section: Head and Neck Anomaliesmentioning

confidence: 99%

Enhancing Fetal Anomaly Detection in Ultrasonography Images: A Review of Machine Learning-Based Approaches

Yousefpour Shahrivar,

Karami,

Karami

2023

Biomimetics

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Fetal development is a critical phase in prenatal care, demanding the timely identification of anomalies in ultrasound images to safeguard the well-being of both the unborn child and the mother. Medical imaging has played a pivotal role in detecting fetal abnormalities and malformations. However, despite significant advances in ultrasound technology, the accurate identification of irregularities in prenatal images continues to pose considerable challenges, often necessitating substantial time and expertise from medical professionals. In this review, we go through recent developments in machine learning (ML) methods applied to fetal ultrasound images. Specifically, we focus on a range of ML algorithms employed in the context of fetal ultrasound, encompassing tasks such as image classification, object recognition, and segmentation. We highlight how these innovative approaches can enhance ultrasound-based fetal anomaly detection and provide insights for future research and clinical implementations. Furthermore, we emphasize the need for further research in this domain where future investigations can contribute to more effective ultrasound-based fetal anomaly detection.

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Cortical development in fetuses with congenital heart defects using an automated brain‐age prediction algorithm

Cited by 7 publications

References 30 publications

The association between flow and oxygenation and cortical development in fetuses with congenital heart defects using a brain‐age prediction algorithm

The association between flow and oxygenation and cortical development in fetuses with congenital heart defects using a brain‐age prediction algorithm

Feasibility of neurosonography in CHD-fetuses and controls in a clinical tertiary setting

Enhancing Fetal Anomaly Detection in Ultrasonography Images: A Review of Machine Learning-Based Approaches

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