Simultaneous Morphology, Motility, and Fragmentation Analysis of Live Individual Sperm Cells for Male Fertility Evaluation

Abstract

A new technique for sperm analysis is presented, measuring DNA fragmentation, morphology with virtual staining, and motility, all three criteria on the same individual unstained live cell. The method relies on quantitative stain‐free interferometric imaging, providing unique topographic structural and content maps of the cell, becoming available for the first time for clinical use, together with deep‐learning frameworks and least‐squares linear approximation. In the common clinical practice, only motility evaluation can be carried out on live human cells, while full morphological evaluation and DNA fragmentation assays require different staining protocols, and therefore cannot be performed on the same cell, resulting in inconsistencies in fertility evaluation. A clinic‐ready interferometric module is used to acquire dynamic sperm cells without chemical staining, together with deep learning to evaluate all three scores per cell with accuracy of 93.1%, 88%, and 90% for morphology, motility, and DNA fragmentation, respectively. It is shown that the expected number of cells that pass all three criteria based on the current evaluations performed separately does not correspond with the number of cells that pass all criteria, demonstrating the importance of the suggested method. The proposed stain‐free evaluation method is expected to decrease uncertainty in infertility diagnosis, increasing treatment success rates.

Keywords

• cell imaging
• deep learning
• digital holographic microscopy
• fertility
• quantitative phase microscopy
• sperm fragmentation