Early brain development is crucial for lifelong neurodevelopmental health. However, current clinical practice offers limited knowledge of normal embryonic brain anatomy on ultrasound, despite the brain undergoing rapid changes within the time-span of days. To provide detailed insights into normal brain development and identify deviations, we created the 4D Human Embryonic Brain Atlas using a deep learning-based approach for groupwise registration and spatiotemporal atlas generation. Our method introduced a time-dependent initial atlas and penalized deviations from it, ensuring age-specific anatomy was maintained throughout rapid development. The atlas was generated and validated using 831 3D ultrasound images from 402 subjects in the Rotterdam Periconceptional Cohort, acquired between gestational weeks 8 and 12. We evaluated the effectiveness of our approach with an ablation study, which demonstrated that incorporating a time-dependent initial atlas and penalization produced anatomically accurate results. In contrast, omitting these adaptations led to anatomically incorrect atlas. Visual comparisons with an existing ex-vivo embryo atlas further confirmed the anatomical accuracy of our atlas. In conclusion, the proposed method successfully captures the rapid anotomical development of the embryonic brain. The resulting 4D Human Embryonic Brain Atlas provides a unique insights into this crucial early life period and holds the potential for improving the detection, prevention, and treatment of prenatal neurodevelopmental disorders.

翻译：早期大脑发育对终身神经发育健康至关重要。然而，尽管大脑在数天时间内经历快速变化，当前临床实践对超声下正常胚胎脑解剖结构的认知仍有限。为深入理解正常大脑发育并识别异常，我们采用基于深度学习的群体配准与时空图谱生成方法，构建了四维人类胚胎脑图谱。本方法引入了时间依赖性初始图谱并惩罚对其的偏离，从而确保在快速发育过程中维持年龄特异性解剖结构。该图谱使用来自鹿特丹围孕期队列402名受试者的831幅三维超声图像生成并验证，数据采集于孕周8至12周。我们通过消融实验评估了方法的有效性，结果表明结合时间依赖性初始图谱与惩罚机制可产生解剖学准确的结果；反之，忽略这些适应性调整则会导致解剖学错误的图谱。与现有离体胚胎图谱的视觉对比进一步证实了本图谱的解剖学准确性。综上所述，所提方法成功捕捉了胚胎大脑的快速解剖学发育。由此产生的四维人类胚胎脑图谱为这一关键生命早期阶段提供了独特见解，并有望提升产前神经发育障碍的检测、预防与治疗水平。