Nonlinear microscopy for egg/embryo viability

非线性显微镜检查卵子/胚胎活力

• 批准号: 1540498
• 负责人: Daniel Needleman
• 金额: $ 5万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-04-15 至 2015-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1540498&HistoricalAwards=false
• 关键词: Nonlinear; microscopy; egg; embryo; viability

In vitro fertilization (IVF) clinics perform the diagnostic, surgical and biological procedures necessary for in vitro fertilization cycles, as well as egg freezing procedures and egg and embryo banking. IVF clinics are highly competitive with one another because their success rates are published, and patients are willing to travel to clinics with higher success rates. Especially at high volume clinics, they are interested in innovations that will increase their profitability by driving patient volume through increased success rates. This team aims to create a commercial device that unearths new sources of information of egg/embryo quality that can be incorporated into an algorithm to predict the chance of IVF success.This team is proposing the creation of an algorithm that can assess the quality of an egg or embryo by looking at metabolic and subcellular features of that egg or embryo and correlating those features to ultimate potential to lead to a live birth. The embryologist can use this algorithm to choose the embryo for implantation that is most likely to lead to birth, which should increase success. Clinicians can also use the algorithm on a patient?s eggs, to give the patient a more accurate assessment of her individual fertility potential. Quantifying metabolism is the core piece that will be used to create the algorithm.

体外受精（IVF）诊所进行体外受精周期所需的诊断，手术和生物程序，以及卵子冷冻程序和卵子和胚胎银行。试管婴儿诊所之间竞争激烈，因为他们的成功率是公开的，患者愿意前往成功率更高的诊所。特别是在高容量诊所，他们对创新感兴趣，这些创新将通过提高成功率来增加患者数量，从而提高他们的盈利能力。 该团队的目标是创建一种商业设备，挖掘卵子/胚胎质量的新信息来源，这些信息可以纳入算法中，以预测IVF成功的机会。该团队正在提议创建一种算法，可以通过观察卵子或胚胎的代谢和亚细胞特征来评估卵子或胚胎的质量，并将这些特征与最终导致活产的潜力相关联。胚胎学家可以使用这种算法来选择最有可能导致出生的胚胎植入，这应该会增加成功率。临床医生也可以在病人身上使用这种算法？的卵子，让病人更准确地评估她的个人生育潜力。量化新陈代谢是创建算法的核心部分。