A key developmental stage in mammalian folliculogenesis is the formation of a fluid-filled lumen (antrum) prior to ovulation. While it has long been speculated that the follicular fluid is essential for oocyte maturation and ovulation, little is known about the morphogenesis and the mechanisms driving the antrum formation and ovulation, potentially due to challenges in imaging tissue dynamics in large tissues. Misregulation of such processes leads to anovulation, a hallmark of infertility in ageing and diseases such as the polycystic ovary syndrome (PCOS). In this review, we discuss recent advances in deep tissue imaging techniques, machine learning and theoretical approaches that have been applied to study development and diseases. We propose that an integrative approach combining these techniques is essential for understanding the physics of hydraulics in follicle development and ovarian functions.
Keywords: Biophotonics; Folliculogenesis; Machine learning; Ovary; Ovulation; Tissue mechanics.
© The Author(s) 2024.