Enatsu Noritoshi, Miyatsuka Isao, An Le My, Inubushi Miki, Enatsu Kunihiro, Otsuki Junko, Iwasaki Toshiroh, Kokeguchi Shoji, Shiotani Masahide
Hanabusa Women's Clinic Kobe Hyogo Japan.
NextGeM inc. Tokyo Japan.
Reprod Med Biol. 2022 Feb 7;21(1):e12443. doi: 10.1002/rmb2.12443. eCollection 2022 Jan-Dec.
The purpose of the study was to invent and evaluate the novel artificial intelligence (AI) system named Fertility image Testing Through Embryo (FiTTE) for predicting blastocyst viability and visualizing the explanations via gradient-based localization.
The authors retrospectively analyzed 19 342 static blastocyst images with related inspection histories from 9961 infertile patients who underwent in vitro fertilization. Among these data, 17 984 cycles of single-blastocyst transfer were used for training, and data from 1358 cycles were used for testing purposes.
The prediction accuracy for clinical pregnancy achieved by a control model using conventional Gardner scoring system was 59.8%, and area under the curve (AUC) was 0.62. FiTTE improved the prediction accuracy by using blastocyst images to 62.7% and AUC of 0.68. Additionally, the accuracy achieved by an ensemble model using image plus clinical data was 65.2% and AUC was 0.71, representing an improvement in prediction accuracy. The visualization algorithm showed brighter colors with blastocysts that resulted in clinical pregnancy.
The authors invented the novel AI system, FiTTE, which could provide more precise prediction of the probability of clinical pregnancy using blastocyst images secondary to single embryo transfer than the conventional Gardner scoring assessments. FiTTE could also provide explanation of AI prediction using colored blastocyst images.
本研究旨在发明并评估一种名为“通过胚胎进行生育力图像检测”（FiTTE）的新型人工智能（AI）系统，用于预测囊胚活力并通过基于梯度的定位可视化解释。
作者回顾性分析了9961例接受体外受精的不孕患者的19342张静态囊胚图像及相关检查记录。在这些数据中，17984个单囊胚移植周期的数据用于训练，1358个周期的数据用于测试。
使用传统加德纳评分系统的对照模型实现的临床妊娠预测准确率为59.8%，曲线下面积（AUC）为0.62。FiTTE通过使用囊胚图像将预测准确率提高到62.7%，AUC为0.68。此外，使用图像加临床数据的集成模型实现的准确率为65.2%，AUC为0.71，表明预测准确率有所提高。可视化算法显示临床妊娠囊胚颜色更亮。
作者发明了新型AI系统FiTTE，与传统加德纳评分评估相比，它可以使用单胚胎移植后的囊胚图像更精确地预测临床妊娠概率。FiTTE还可以使用彩色囊胚图像对AI预测进行解释。
