P-142 ICSI Semi Automation powered by AI: Gateway for Oocyte Quality Assessment real time based on biomechanics during ICSI

Abstract

Abstract Study question Embryo selection based on oolemma elasticity and cytoplasm viscosity using semi automated CL-ICSI technology assisted by Artificial Intelligence Summary answer CL-ICSI syringe/technology is capable of converting embryologist visual and feel of each ICSI procedure into a measurable form for objectivity of assessment in real time. What is known already In last four decades, understanding and/or assessing oocyte quality (based on biomechanics) become one of the needs in order to define the embryo formation and selection. initial days of ICSI, embryologist identifies the oocyte pool as fragile, normal or hyper elastic groups based on visual and indentation methods. Further, a variety of advanced techniques were implemented such as ultra fast imaging, atomic force sensing, micro tactile sensors, microfluidics and zone modulus measuring methods. These techniques were implemented on oocyte donation programs, and limited to research, due to the complexity and technical difficulties in implementing. Study design, size, duration From our observations, we would like to introduce our innovative technology (CL-ICSI) that is semi automation of ICSI procedure which is capable of measuring oolemma elasticity and cytoplasmic viscosity. we show the performance using limited number of discarded oocytes as a proof of concept of our technology. We believe that, exploitation of such technology become an asset/gateway for better understanding of oocyte quality and perhaps contribute in embryo selection based on oocyte biomechanics/quality. Participants/materials, setting, methods Current technology (CL-ICSI) is based on ICSI syringes that are calculated/designed to improve objectivity during the ICSI procedure among inter and intra users. CL-ICSI technology comprises of a semi automated syringe equipped with micro controllers that utilises force sensing and pressure mapping techniques to convert oocyte biomechanics data into measurable read outs on display unit. These measurable readouts are finally fed to AI algorithms that calculate the oocyte quality score as an output. Main results and the role of chance CL-ICSI semi automation technology is designed to minimise embryologist subjectivity during the ICSI procedure. Existing syringes works on manual rotatory mechanism which does not provide the start and stop point of the pressure applied on oocyte for puncturing, which genratlly controlled by embryologists skill and experience. Current technology comes with a click button that is designed to be loaded with potential energy which is proportional to the pressure/force required to puncture oolemma subsequently for sperm deposition. In case of classical syringes, post puncturing opposite rotation is implemented to withdraw the negative pressure or cytoplasmic content flow into the needle. Due to the lack of precise positioning the system become subjective. For this reason, we introduced mechanical potential energy build up, where oolemma puncture occurs with a button click and compensation of negative pressure occurs with releasing the button. This mechanism provides objectivity as well requires less than half of the time for oocyte intervention during ICSI over conventional rotatory syringes. More over, this technology works on pneumatics and is adaptable to all existing micro manipulators. Utilisation of such technologies may help improve the objectivity during ICSI and help understand oocyte quality in addition to the visual morphology assessment using AI. Limitations, reasons for caution CL-ICSI technology may be considered as next generation ICSI systems. Application of this technology in clinical setting in collecting the data from multicenters and different ethnicities might provide information that is a step closer to understand the oocyte quality and its role in embryo formation using artificial intelligence. Wider implications of the findings Embryo selection is one of the key event for single embryo transfer for healthy pregnancies. Morphology and morphokinetics data on oocytes and embryos provide valuable information but are limited, if there are no embryos formed. Current technology (CL-ICSI) may provide new avenues for better understanding on embryo prediction and selection. Trial registration number `not applicable`