Objectives The prognosis of borderline forms of anomalies that can be detected by ultrasound is one of the most challenging issues in prenatal diagnosis. The aim of this study was to determine the prognosis for fetuses presenting with isolated mild ventriculomegaly (MVM). Methods Fetuses in which the width of the lateral ventricular atria was 10–12 mm and which had no other detectable chromosomal or morphological anomalies were followed by monthly ultrasound examinations until delivery. For the cases identified up to December 1997, postnatal information was gathered retrospectively through interviews. Children born from January 1998 onwards were included in a protocol involving planned neuropsychiatric visits at 12 and 18 months of age in which the Griffith scale was used to assess neurodevelopment. Results Between September 1992 and January 2001, 60 fetuses with isolated MVM were identified. Ventricular dilatation diminished in 18 cases (and became normal in nine of these) and stabilized in 42 cases. Information was obtained on 38 children born up to December 1997 and their neurodevelopment was found to be completely normal. The 22 children born from January 1998 onwards showed normal development at 12 and 18 months of age. Conclusions When MVM is observed on prenatal ultrasound examination it can be very difficult to offer parents appropriate counseling. It is important to exclude aneuploidy or morphological abnormalities but even then there will be anxieties about long‐term neurological outcome. Our data, which show normal neurodevelopment between 18 months and 10 years after birth in cases of MVM (10–12 mm), should provide a basis for reassuring counseling. Copyright © 2003 ISUOG. Published by John Wiley & Sons, Ltd.

Based on growing demand for assisted reproduction technology, improved predictive models are required to optimize in vitro fertilization/intracytoplasmatic sperm injection strategies, prioritizing single embryo transfer. There are still several obstacles to overcome for the purpose of improving assisted reproductive success, such as intra-and inter-observer subjectivity in embryonic selection, high occurrence of multiple pregnancies, maternal and neonatal complications. Here, we compare studies that used several variables that impact the success of assisted reproduction, such as blastocyst morphology and morphokinetic aspects of embryo development as well as characteristics of the patients submitted to assisted reproduction, in order to predict embryo quality, implantation or live birth. Thereby, we emphasize the proposal of an artificial intelligence-based platform for a more objective method to predict live birth.

OBJECTIVE: To study the application of image processing for segmentation of blastocysts images and extraction of potential variables for prediction of embryo fitness. DESIGN: Retrospective study. SETTING: Single reproductive medical center. IVI-RMA (Valencia, Spain) between 2017 and 2019. PATIENTS: An initial dataset including 353 images from EmbryoScope and 474 images from Geri incubators was acquired, of which 320 images from EmbryoScope and 309 images from Geri incubators were used in this study. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Successful segmentation of images into trophectoderm (TE), blastocoel, and inner cell mass (ICM) using the proposed processing steps. RESULTS: A total of 33 variables were automatically generated by digital image processing, each representing a different aspect of the embryo and describing a different characteristic of the expanding blastocyst (EX), ICM, or TE. These variables can be categorized into texture, gray level average, gray level standard deviation, modal value, relations, and light level. The automated and directed steps of the proposed processing protocol exclude spurious results, except when image quality (e.g., focus) prevents correct segmentation. CONCLUSIONS: The proposed image processing protocol that can successfully segment human blastocyst images from two distinct sources and extract 33 variables with potential utility in embryo selection for ART.

Despite the use of new techniques on embryo selection and the presence of equipment on the market, such as EmbryoScope® and Geri®, which help in the evaluation of embryo quality, there is still a subjectivity between the embryologist’s classifications, which are subjected to inter- and intra-observer variability, therefore compromising the successful implantation of the embryo. Nonetheless, with the acquisition of images through the time-lapse system, it is possible to perform digital processing of these images, providing a better analysis of the embryo, in addition to enabling the automatic analysis of a large volume of information. An image processing protocol was developed using well-established techniques to segment the image of blastocysts and extract variables of interest. A total of 33 variables were automatically generated by digital image processing, each one representing a different aspect of the embryo and describing a different characteristic of the blastocyst. These variables can be categorized into texture, gray-level average, gray-level standard deviation, modal value, relations, and light level. The automated and directed steps of the proposed processing protocol exclude spurious results, except when image quality (e.g., focus) prevents correct segmentation. The image processing protocol can segment human blastocyst images and automatically extract 33 variables that describe quantitative aspects of the blastocyst’s regions, with potential utility in embryo selection for assisted reproductive technology (ART).

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