Department of Obstetrics & Gynecology, Division of Reproductive Endocrinology and Infertility, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
Department of Medicine, Division of Engineering in Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
PLoS One. 2019 Mar 13;14(3):e0212562. doi: 10.1371/journal.pone.0212562. eCollection 2019.
The fundamental test for male infertility, semen analysis, is mostly a manually performed subjective and time-consuming process and the use of automated systems has been cost prohibitive. We have previously developed an inexpensive smartphone-based system for at-home male infertility screening through automatic and rapid measurement of sperm concentration and motility. Here, we assessed the feasibility of using a similar smartphone-based system for laboratory use in measuring: a) Hyaluronan Binding Assay (HBA) score, a quantitative score describing the sperm maturity and fertilization potential in a semen sample, b) sperm viability, which assesses sperm membrane integrity, and c) sperm DNA fragmentation that assesses the degree of DNA damage. There was good correlation between the manual analysis and smartphone-based analysis for the HBA score when the device was tested with 31 fresh, unprocessed human semen samples. The smartphone-based approach performed with an accuracy of 87% in sperm classification when the HBA score was set at manufacturer's threshold of 80. Similarly, the sperm viability and DNA fragmentation tests were also shown to be compatible with the smartphone-based system when tested with 102 and 47 human semen samples, respectively.
男性不育的基本检测——精液分析,主要是一项手动进行的主观且耗时的过程,而自动化系统的使用成本过高。我们之前开发了一种基于廉价智能手机的系统,可通过自动快速测量精子浓度和活力,实现家庭男性不育筛查。在此,我们评估了类似的基于智能手机的系统在实验室中测量以下参数的可行性:a) 透明质酸结合试验 (HBA) 评分,这是一种定量评分,可描述精液样本中精子的成熟度和受精潜能;b) 精子活力,评估精子膜的完整性;c) 精子 DNA 碎片化,评估 DNA 损伤程度。当该设备用 31 份新鲜、未经处理的人类精液样本进行测试时,手动分析与基于智能手机的分析在 HBA 评分方面具有良好的相关性。当 HBA 评分设置为制造商设定的 80 阈值时,基于智能手机的方法在精子分类方面的准确率为 87%。同样,当用 102 份和 47 份人类精液样本分别测试精子活力和 DNA 碎片化试验时,也证明该方法与智能手机系统兼容。