Semen quality assessed by sperm count and sperm cell characteristics such as morphology and motility, is considered to be the main determinant of men’s reproductive health. Therefore, sperm cell selection is vital in assisted reproductive technology (ART) used for the treatment of infertility. Conventional bright field optical microscopy is widely utilized for the imaging and selection of sperm cells based on the qualitative analysis by experienced clinicians. In this study, we report the development of a highly sensitive quantitative phase microscopy (QPM) using partially spatially coherent light source, which is a label-free, non-invasive and high-resolution technique to quantify various biophysical parameters. The partial spatial coherence nature of light source provides a significant improvement in spatial phase sensitivity and hence reconstruction of the phase of the entire sperm cell is demonstrated, which was otherwise not possible using highly spatially coherent light source. High sensitivity of the system enables quantitative phase imaging of the specimens having very low refractive index contrast with respect to the medium like tail of the sperm cells. Further, it also benefits with accurate quantification of 3D-morphological parameters of sperm cells which might be helpful in the infertility treatment. The quantitative analysis of more than 2500 sperm cells under hydrogen peroxide (H 2 O 2 ) induced oxidative stress condition is demonstrated. It is further correlated with motility of sperm cell to study the effect of oxidative stress on healthy sperm cells. The results exhibit a decrease in the maximum phase values of the sperm head as well as decrease in the sperm cell’s motility with increasing oxidative stress, i.e., H 2 O 2 concentration. Various morphological and texture parameters were extracted from the phase maps and subsequently support vector machine (SVM) based machine learning algorithm is employed for the classification of the control and the stressed sperms cells. The algorithm achieves an area under the receiver operator characteristic (ROC) curve of 89.93% based on the all morphological and texture parameters with a sensitivity of 91.18%. The proposed approach can be implemented for live sperm cells selection in ART procedure for the treatment of infertility.
Sperm cell motility and morphology observed under the bright field microscopy are the only criteria for selecting a particular sperm cell during intracytoplasmic Sperm injection (icSi) procedure of Assisted Reproductive Technology (ART). Several factors such as oxidative stress, cryopreservation, heat, smoking and alcohol consumption, are negatively associated with the quality of sperm cell and fertilization potential due to the changing of subcellular structures and functions which are overlooked. However, bright field imaging contrast is insufficient to distinguish tiniest morphological cell features that might influence the fertilizing ability of sperm cell. We developed a partially spatially coherent digital holographic microscope (PSC-DHM) for quantitative phase imaging (QPI) in order to distinguish normal sperm cells from sperm cells under different stress conditions such as cryopreservation, exposure to hydrogen peroxide and ethanol. Phase maps of total 10,163 sperm cells (2,400 control cells, 2,750 spermatozoa after cryopreservation, 2,515 and 2,498 cells under hydrogen peroxide and ethanol respectively) are reconstructed using the data acquired from the PSC-DHM system. Total of seven feedforward deep neural networks (DNN) are employed for the classification of the phase maps for normal and stress affected sperm cells. When validated against the test dataset, the DNN provided an average sensitivity, specificity and accuracy of 85.5%, 94.7% and 85.6%, respectively. The current QPI + DNN framework is applicable for further improving ICSI procedure and the diagnostic efficiency for the classification of semen quality in regard to their fertilization potential and other biomedical applications in general. Semen quality and male fertility potential have been continuously declining all over the world 1-4. At the same time, biomedical and technical advances have made it possible to treat male infertility using assisted reproductive technology (ART) including intracytoplasmic sperm injection (ICSI). Evaluation of semen quality and ICSI procedure are the important steps for the successful outcome of ART. Generally, semen parameters evaluation
Background: Normal mature sperm have a considerably reduced number of mitochondria, which provide the energy required for progressive sperm motility.Literature suggests that disorders of sperm motility may be linked to abnormal sperm mitochondrial number and function.Objectives: To summarise the evidence from literature regarding the association of mitochondrial DNA copy numbers and semen quality with a particular emphasis on the sperm motility. Search strategy: Standard methodology recommended by Cochrane.Selection criteria: All published primary research reporting on the association between mitochondrial DNA copy numbers and semen quality. Data collection and analysis: Using standard methodology recommended byCochrane we pooled results using a random effects model and the findings were reported as a standardised mean difference. Main results:We included ten studies. The primary outcome was sperm mitochondrial DNA copy numbers. A meta-analysis including five studies showed significantly higher mitochondrial DNA copy numbers in abnormal semen analysis compared with normal semen analysis (standardised mean difference 1.08, 95% CI 0.74-1.43). Seven studies included in the meta-analysis showed a significant negative correlation between mitochondrial DNA copy numbers and semen parameters. The quality of evidence was assessed as good to very good in 60% of studies.Conclusions: Our review demonstrates significantly higher mitochondrial DNA in human sperm cells of men with abnormal semen analysis in comparison to men with normal semen analysis.
Background: Normal mature sperm have a considerably reduced number of mitochondria which provide the energy required for progressive sperm motility. Literature suggests that disorders of sperm motility may be linked to abnormal sperm mitochondrial number and function. Objectives: To summarise the evidence from literature regarding the association of mitochondrial DNA copy numbers and semen quality with a particular emphasis on the spermatozoa motility. Search strategy: Standard methodology recommended by Cochrane. Selection criteria: All published primary research reporting on differences in mitochondrial DNA copy numbers between the sperm of males with a normal and abnormal semen analysis. Data collection and analysis: Using standard methodology recommended by Cochrane we pooled results using a random effects model and the findings were reported as a standardised mean difference. Main results: We included 10 trials. The primary outcome was sperm mitochondrial DNA copy numbers. A meta-analysis including five studies showed significantly higher mitochondrial DNA copy numbers in abnormal semen analysis as compared to normal semen analysis(SMD 1.08, 95% CI 0.74-1.43). Three other studies not included in the meta-analysis showed a significant negative correlation between mitochondrial DNA copy numbers and semen parameters. The quality of evidence was assessed as good to very good in 60% of studies. Conclusions: Our review demonstrates significantly higher mitochondrial DNA in human sperm cells of men with abnormal semen analysis in comparison to men with normal semen analysis. PROSPERO registration: CRD42019118841 Funding None received
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