Ovarian tissue quality assessment and fertility preservation strategies enabled by multi-omics and artificial intelligence: current applications and clinical perspectives

Ovarian tissue cryopreservation (OTC) is essential for fertility preservation in cancer survivors, prepubertal girls, and individuals at high risk of premature ovarian insufficiency (POI). Yet conventional evaluation methods, such as histology and follicle counting, provide limited insight into tissue viability, microenvironmental integrity, molecular injury, and oncologic safety. Recent advances in multi-omics, including transcriptomics, single-cell sequencing, proteomics, and spatial transcriptomics, enable high-resolution characterization of follicular heterogeneity, stromal status, and potential malignant contamination. Concurrently, artificial intelligence (AI) offers automated follicle detection, quantitative tissue assessment, and multimodal prediction models that can support individualized clinical decisions. This review summarizes emerging applications of multi-omics and AI in ovarian tissue quality assessment and highlights their potential to transform fertility preservation strategies. Integrating molecular profiling with AI-based prediction may establish a more precise and intelligent framework for tissue selection, transplantation planning, and reproductive outcome prediction.