Test Tube Baby

Test-tube baby is a fertility treatment in medicine known as “in vitro fertilization” (IVF). This method involves the fertilization of a female reproductive cell (egg) with a male reproductive cell (sperm) outside the body, in a laboratory environment, followed by the transfer of the resulting embryo into the uterus. Developed for couples unable to conceive naturally, this method has become one of the most common commonly used and effective techniques in the treatment of infertility today.

History of Test-tube Baby and the First Birth Worldwide

The test-tube baby (IVF) process first came to prominence in the 1930s through research conducted in USA on animals. Gregory Pincus emerged as one of the pioneers in this field with his claim of fertilizing rabbit eggs in a laboratory setting. In the 1940s, Rock and Menkin worked with human eggs obtained through surgical intervention and observed signs of fertilization; however, these efforts did not result in a birth. Throughout the 1950s and 1960s, various science researchers conducted human IVF on studies, but success was not achieved due to technical limitations and insufficient scientific knowledge.

The pivotal Truth dönüm moment occurred in 1968 when British embryologist Robert Edwards and gynecologist Patrick Steptoe joined forces. This collaboration focused on the fundamental steps of egg maturation in the laboratory, sperm preparation, fertilization, and embryo transfer, overcoming numerous technical challenges over the years.

The contribution of the team’s nurse-technician Jean Purdy was also significant. After a decade of scientific and clinical research, on 25 July 1978, a healthy baby girl named Louise Brown was born in Oldham, England, marking the world’s first successful test-tube baby birth. This breakthrough is recognized as a landmark in reproductive medicine.

History of Test-tube Baby and the First Birth in Türkiye

Test-tube baby applications in Türkiye began to develop in the late 1980s, and the first successful birth occurred on 18 April 1989 in İzmir. This birth took place at the Test-tube Baby Center within the Department of Gynecology and Obstetrics at Ege University, under the leadership of Professor Dr. S. Aricioglu, and resulted in the birth of twins named Universe and Ece Erol. This event is considered a turning point in the history of assisted reproductive technologies in Türkiye.

Ege University Test-tube Baby Center

The Ege University Test-tube Baby Center is one of the first such centers established within a university in Türkiye. Founded in 1988, the center played a leading role in the widespread adoption of test-tube baby procedures across the country following its first birth in 1989. The center provides not only only treatment services but also conducts research and educational activities.

The Ege University Test-tube Baby Center continues to provide active services with its advanced laboratory infrastructure and multidisciplinary team of specialists.

Image depicting a girl and a boy twin born in the maternity ward of İzmir Ege University Hospital. (Generated by artificial intelligence.)

Conditions for Test-tube Baby Treatment

The test-tube baby method is recommended for individuals and couples who are unable to conceive naturally under certain conditions. These include blocked fallopian tubes, reduced ovarian reserve due to advanced age, low sperm count or poor sperm quality, endometriosis, and unexplained infertility, among other causes place.

Additionally, IVF is often chosen for couples who have not achieved success with prior methods such as intrauterine insemination.

Test-tube Baby Treatment Process and Stages

The IVF treatment generally consists of four main stages:

1. Ovarian Stimulation: The woman’s ovaries are stimulated with hormonal injections to produce multiple eggs.
2. Egg Retrieval (OPU): Mature eggs are collected under anesthesia.
3. Fertilization and Embryo Development: The retrieved eggs are fertilized with sperm in the laboratory. This can be done using conventional IVF or intracytoplasmic sperm injection (ICSI).
4. Embryo Transfer: One or more fertilized and developed embryos are transferred into the uterus. A pregnancy test is performed approximately 10–12 days after the transfer.

Representative image of the IVF treatment process. (Generated by artificial intelligence.)

Laboratory Procedures and Technological Advancements

One of the most important critical factors influencing the success of IVF is laboratory conditions. Advanced techniques such as fertilization in vitro, embryo culture, embryo quality assessment, embryo cryopreservation (cryopreservation), preimplantation genetic testing (PGT), and time-lapse embryo monitoring systems are employed. These practices enhance the selection of healthy embryos and increase the chances of pregnancy.

Challenges in Test-tube Baby Treatment

Some potential difficulties and side effects associated with IVF include ovarian hyperstimulation syndrome (OHSS), failure to retrieve eggs or embryos, failure of the embryo to implant in the uterus, and pregnancy loss through miscarriage. Additionally, emotional and psychological stress can affect couples undergoing treatment. For this reason, psychological support is also recommended throughout the treatment process.

Test-tube Baby in Advanced Age and Special Cases

A woman’s age is a direct factor affecting the success of IVF treatment. Advanced age (typically 35 years and older) is associated with a decline in both the number and quality of eggs. In such cases, higher-dose hormone stimulation protocols may be applied, and alternative methods such as egg donation may be recommended. In addition, specific clinical conditions such as polycystic ovary syndrome (PCOS) and endometriosis also influence the treatment plan.

Image of a baby in the mother’s arms. (Generated by artificial intelligence.)

Success Rates and Influencing Factors

The success rate of IVF treatment varies depending on multiple factors including age, egg quality, sperm parameters, embryo quality, and uterine conditions. Success rates are higher among younger women and decline with advancing age. Overall, success rates typically range between 30% and 50%.

Ethical Debates and Social Perception

IVF treatments have also generated social and ethical debates. This method has provoked diverse interpretations from religious, cultural, and social perspectives and has periodically entered public discourse due to issues such as embryo freezing, embryo selection, and surrogacy. At the same time, increased societal awareness of infertility has led to greater acceptance and higher levels of public approval for IVF treatments.

Artificial Intelligence and Machine Learning in Embryo Selection

Artificial intelligence (AI) and machine learning (ML) technologies are being developed to enable more objective, fast and accurate embryo selection in IVF treatments. Traditionally, embryo quality is assessed by embryologists based on morphological criteria under a microscope. However, this method is subjective and can vary between different experts. Therefore, AI-based models offer alternative approaches that provide more consistent and scientifically grounded embryo selection.

In 2024, a work published in Frontiers in Artificial Intelligence by Borna, Sepehri, and Maleki introduced a novel artificial intelligence algorithm named DeepEmbryo designed for embryo selection. DeepEmbryo is designed to predict pregnancy outcomes by analyzing embryo images captured at three distinct time points (19, 44, and 68 hour post-fertilization) routinely obtained in IVF laboratories. This algorithm operates compatibly with existing laboratory infrastructure without requiring time-lapse systems, offering broad applicability.

Image illustrating AI-based embryo selection. (Generated by artificial intelligence.)

DeepEmbryo first segments embryo images using a U-Net architecture. In this stage, background images outside the embryo are removed, and only the embryo region is used for analysis. Subsequently, each of the three images from different developmental stages is processed through convolutional neural networks (CNNs) to extract feature vectors. These vectors are combined to produce a single output predicting pregnancy likelihood. The model leverages transfer learning (transfer learning) by building upon previously trained deep networks, enabling high-accuracy predictions even with limited data.

The DeepEmbryo algorithm can predict pregnancy outcomes from embryo images with a 75% accuracy accuracy rate. This success rate is significantly higher than the 48.41% accuracy achieved by experienced embryologists using majority consensus in the same study. Furthermore, all variants of the algorithm delivered more consistent and successful results compared to human experts.

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