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

We present a new technique for simultaneously analyzing morphology, motility and DNA fragmentation of live human sperm cells at the single-cell level for male fertility evaluation. It relies on quantitative stain-free interferometric imaging and multiple deep-learning frameworks. In the common clinical practice, only motility evaluation is carried out on live human cells, while full morphological evaluation and DNA fragmentation assays require different staining protocols, and therefore cannot be performed simultaneously on the same cell. This results in a lack of information regarding the intersection of these scores. We use a clinic-ready interferometric module and deep learning to acquire dynamic sperm cells without chemical staining, and evaluate all three scores per each cell together with virtual staining. We show that the number of cells that pass each criterion separately does not accurately predict how many would pass all criteria, thus the triple evaluation per cell is necessary for accurate fertility grading. This stain-free evaluation is expected to decrease the uncertainty in male fertility evaluation, as well as be applied for sperm selection during in vitro fertilization.