Three-dimensional visualisation of human ovarian follicles using a whole-mount immunolabelling and optical tissue

A S Harrison1, B D Bjarkadottir1, N Kuscu1

  • 1Nuffield Department of Women's & Reproductive Health, University of Oxford, Women's Centre, John Radcliffe Hospital, Oxford, United Kingdom.

Reproduction & Fertility
|October 31, 2025
PubMed

To more accurately classify human ovarian follicles by developing a novel methodology with three-dimensional visualisation using whole-mount immunolabelling and optical tissue clearing techniques. A whole-mount immunolabelling protocol combined with optical tissue clearing was applied to human ovarian tissue for three-dimensional follicle analysis. Key markers, including DAPI for nuclear staining, DDX4 for oocyte-specific labelling, and LAMININ for basal membranes, were used to visualise follicular structures. The tissues underwent a clearing process to enable confocal z-stack imaging to obtain detailed three-dimensional data. Ovarian cortical tissue from three paediatric patients (aged 9-12 years) who had not undergone chemotherapy treatment was collected. The tissue was dissected into small fragments and stained to identify viable follicles. Follicle and oocyte size, as well as granulosa cell size and type, were assessed across multiple dimensions (XY, XZ, YZ planes). Follicles were classified as primordial or transitional based on granulosa cell characteristics. Three-dimensional analysis across XY, XZ, and YZ planes revealed that 58% of follicles, initially classified as primordial using conventional two-dimensional methods, were misidentified as transitional due to the presence of cuboidal granulosa cells that were only detectable in multi-plane analysis. Moreover, three-dimensional analyses revealed significant differences in the number and size of cuboidal granulosa cells detected on transitional follicles. This study presents a novel whole-mount immunolabelling and optical tissue clearing methodology for accurate three-dimensional visualisation and classification of human ovarian follicles. This technique improves the accuracy of follicle staging and provides a valuable tool for future research into ovarian function, reproductive health, and conditions impacting follicle development.

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