Visualization of the microstructure and distribution of follicles in deep human ovaries using speckle-modulated optical coherence microscopy

K Koichiro Ito M Momoko Kanaya S Seido Takae N Nao Suzuki K Kosuke Tsukada

Abstract

Ovarian tissue cryopreservation and transplantation remain important fertility preservation options for children, adolescents, and young adults requiring immediate treatment for their primary disease. Reliable visualization of follicle-containing regions may provide useful information for future ovarian tissue assessment. Despite its potential as a noninvasive follicle visualization method, optical coherence microscopy (OCM) remains limited by spatial resolution, imaging depth, and speckle noise when resolving fine follicular structures in deep ovarian tissue. In this study, we applied speckle modulation to a near-infrared wavelength-swept OCM system to visualize follicular microstructures in deep ovarian tissue. OCM images of 4-day-old mouse ovaries revealed dense superficial distributions of primordial follicles, which were distinguishable from primary follicles surrounded by a single layer of granulosa cells. Secondary follicles were predominantly observed in 14-day-old mouse ovarian tissue, and their internal microstructures were visualized. The proposed OCM approach visualized primordial follicular microstructures to depths of approximately 300 and 500 μm in ovarian tissues from a 15-year-old patient with acute myeloid leukemia and a 14-year-old patient with acute lymphoblastic leukemia, respectively. In the examined specimens, follicle localization varied with imaging location and depth, and similar structural features were also observed in HE-stained sections. Although challenges remain regarding imaging depth, acquisition time, and safety validation, these findings demonstrate the technical feasibility of visualizing follicular microstructures in human ovarian tissue and support future studies on ovarian tissue assessment.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 21, Issue 7
Published July 08, 2026
Pages e0331638
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (5)

K

Koichiro Ito

M

Momoko Kanaya

S

Seido Takae

N

Nao Suzuki

K

Kosuke Tsukada