Endometriosis affects roughly 10% of women of reproductive age globally, which is approximately 190 million women worldwide. <a href="https://www.who.int/news-room/fact-sheets/detail/endometriosis">3</a>  This makes it one of the most common conditions that affect the reproductive system, with 1 in 10 women being affected.In this article, we will explain what endometriosis is and outline the following:<ul><li>Symptoms of endometriosis</li><li>Treatment for endometriosis</li><li>How endometriosis affects your ability to get pregnant</li><li>How endometriosis impacts your IVF success</li></ul><h2>What is endometriosis?</h2>Endometriosis is a condition where cells similar to those located in the womb&#39;s lining grow in other places of the body, such as the ovaries or fallopian tubes.<a href="https://www.endometriosis-uk.org/what-endometriosis">1</a> Each month, these cells react to the changing hormone levels in the same way as the ones in the womb&#39;s lining: by breaking down and being removed as a period bleed. However, the endometriosis cells that are not in the womb&#39;s lining cannot be removed from the body as they should be and instead build up in the body. This in turn causes inflammation, pain and the formation of scar tissue. Credit: <a href="https://www.endometriosis-uk.org/what-endometriosis">endometriosis-uk.org</a> In the UK, 1.5 million women and those assigned female at birth are diagnosed with endometriosis. <a href="https://www.endometriosis-uk.org/what-endometriosis">1</a> It can affect women of any age, including teenagers and women going through menopause. <h2>What are the symptoms of endometriosis?</h2>The symptoms of endometriosis may vary between individuals and depend on the severity of the condition. Some women may be affected badly, whereas others are less so. Some common symptoms of endometriosis include:<ul><li>pain in your lower stomach or back (also called pelvic pain) – usually worse during your period</li><li>heavy periods</li><li>very strong period pain (such that stops you from doing your normal activities)</li><li>pain during or after sex</li><li>pain when urinating during your period</li><li>feeling sick, constipated, diarrhoea, or blood in your urine during your period</li><li>difficulty getting pregnant <a href="https://www.nhs.uk/conditions/endometriosis/#:~:text=Endometriosis%20is%20a%20condition%20where,are%20treatments%20that%20can%20help.">2</a></li></ul><h2>What is the treatment for endometriosis?</h2>Currently, there is no treatment for endometriosis. However, the symptoms usually can be well managed. Treatments for symptoms of endometriosis include:<ul><li>painkillers to manage pain, such as ibuprofen and paracetamol</li><li>hormone medicines and contraceptives, including the combined pill, contraceptive patch, hormonal intrauterine device (IUD) and contraceptive implant, as well as hormonal medicines, called gonadotrophin-releasing hormone (GnRH) analogues</li></ul>Hormonal medication and contraception alter your hormones in such a way that you no longer have periods. In this way, the endometriosis-affected tissues don’t have to be removed either and therefore do not cause pain.<ul><li>surgery to cut away the areas of endometriosis tissue</li><li>surgery to remove part or all of the organs affected by endometriosis, such as part of your colon, or your appendix or womb (called a hysterectomy). <a href="https://www.nhs.uk/conditions/endometriosis/#:~:text=Endometriosis%20is%20a%20condition%20where,are%20treatments%20that%20can%20help.">2</a></li></ul><h2>Will endometriosis affect my ability to get pregnant?</h2>Endometriosis does not directly cause infertility, but it is often associated with difficulties in conceiving with up to 30-50% of women with endometriosis experiencing infertility. <a href="https://www.reproductivefacts.org/news-and-publications/patient-fact-sheets-and-booklets/documents/fact-sheets-and-info-booklets/endometriosis-does-it-cause-infertility/">5</a> However, even for women with severe endometriosis, natural conception is still possible. It is estimated that 60-70% of those with endometriosis can get pregnant spontaneously. <a href="https://www.endometriosis-uk.org/endometriosis-fertility-and-pregnancy">4</a>Laparoscopy surgery has been shown to improve pregnancy rates. During the surgery, patches of endometriosis tissues are removed, which allows successful ovulation, fertilisation and/or implantation.  <h2>Will fertility treatment help me get pregnant if I have endometriosis?</h2>Assisted reproductive technologies, such as intrauterine insemination (IUI) or in vitro fertilisation (IVF) can help conception for women with endometriosis. If endometriosis is mild, IUI with a low level of medical stimulation of the ovaries has been found useful. <a href="https://www.eshre.eu/Guideline/Endometriosis">6</a> IVF is recommended to improve chances of getting pregnant especially if infertility is due to blocked fallopian tubes. <a href="https://www.eshre.eu/Guideline/Endometriosis">6</a> IVF is when an egg is fertilised outside of the body. The ovaries are stimulated to produce more eggs than usual by taking fertility medications. Then, the eggs are collected from the ovaries and fertilised with sperm in a laboratory. The resulting embryo is then returned to the womb to grow and develop.<h2>What are the success rates of IVF for women with endometriosis?</h2>For severe endometriosis, the chances of IVF success without prior laparoscopy is around 29%. A combination of both approaches may give a success rate of up to 46.9%. <a href="https://pubmed.ncbi.nlm.nih.gov/25373015/">7</a> The course of treatment will depend on individual medical histories and your doctor will help you navigate your IVF treatment.At Apricity, we deliver personalised, expert care to support you at every step of your fertility journey. Our trusted team of fertility doctors and dedicated fertility advisors are here to answer your medical questions and guide you through your fertility treatment.You can book a free call with our fertility advisor who will guide you through your next steps. <a href="https://calendly.com/apricity-scheduling/first-call-with-a-fertility-advisor?month=2023-02">Book a call</a><h2>Where can I get the support I need?</h2>Endometriosis can affect a person’s life in significant ways, such as:<ul><li>Chronic pain</li><li>Lack of energy</li><li>Depression</li><li>An inability to conceive</li><li>Difficulty in fulfilling work, social commitments, and romantic relationships</li></ul>However, with the right treatment, the symptoms of endometriosis can be made more  manageable.There are many support groups, including:<ul><li><a href="https://www.endometriosis-uk.org/get-support">Endometriosis.uk</a>, which has a helpline and a lot of valuable information </li><li>Regional <a href="https://www.endometriosis-uk.org/support-groups">support groups</a></li><li><a href="https://healthunlocked.com/endometriosis-uk">Endometriosis forum </a></li><li>If you&#39;re in distress and need someone to talk to, you can call the <a href="https://www.samaritans.org/">Samaritans&#39;</a> 24-hour emotional support line in full confidence: 116 123.</li></ul>

Endometriosis and fertility 

Endometriosis is one of the most common conditions affecting the reproductive system. What are the symptoms, how is endometriosis diagnosed, what treatments are there for endometriosis and can you get pregnant with endometriosis?

Endometriosis and fertility

The field of fertility, and more broadly healthcare, encompasses very sensitive data, such as patient test results, ultrasound images and medical history. It is important for us to ensure that this data is safe, that it is used in a responsible way (for example, taking into account the possible biases of a database) and that the AI tools derived from this data are well documented to guarantee the reproducibility of the results as well as their use in the defined conditions and not out of context. This can help doctors make more informed decisions about fertility treatment options and improve the chances of success for patients.AI-driven technologies like these are currently at the forefront of medical research breakthroughs that will shape the future of healthcare. However, their success depends on access to medical data which is strongly protected due to its highly sensitive nature. New solutions are therefore needed to enable both medical innovation and patients&#39; privacy.<h1>Why does this matter?</h1><ul><li>We are committed to protecting our patient data, keeping it secure and private</li><li>Our data models are well documented so that they can be used responsibly</li><li>We pay attention to biases and discrimination </li><li>We strive for a continuous performance evaluation: we carefully choose which metrics we want to optimise which depends on the problem we want to solve.</li></ul>The certification shows Apricity’s commitment to using our and our partners’ data responsibly and creating trusted AI to improve fertility treatment. It is a way to reassure our partners that we will use their data in a careful manner to prevent any risk to the data. In return, we will be able to provide doctors with more accurate and actionable information to help them make better decisions about patient care. This will improve the success rates of fertility treatments and make them more accessible to a wider range of patients.You can read more about our AI projects <a href="https://www.apricity.life/ai">here</a>.

Apricity awarded certification for responsible and trustworthy data science 

Artificial Intelligence is increasingly present in our daily lives and the regulations around AI can remain unclear. As part of our commitment to the use of responsible AI, Apricity has received the LabelIA label for responsible and trusted data science.

Apricity awarded LabellA for responsible data science

Apricity is proud to have presented eight exciting posters at the annual #Fertility2023 conference which took place in Belfast last week. The topics of the posters presented this year focused on creating artificial intelligence (AI) tools that could help embryologists in their critical decision-making. These tools ensure that the patients receive the best possible care based on reliable data and improve their chances of fertility treatment success.The Apricity Research and AI team have been presenting on the following:<ul><li>Survey of the fertility professionals’ views on AI in clinical practice</li><li>A novel follicle classification system based on the shape of the distribution of follicle sizes</li><li>Embryo development in 4D</li><li>Factors to consider when deciding how many embryos to transfer</li><li>Secure data access solution for improved research</li><li>Blastocyst component image recognition using AI</li><li>Inner cell mass shape classification system and aneuploidy</li><li>Inner cell mass detection: AI vs humans</li></ul><h2>Survey of the fertility professionals’ views on AI in clinical practice</h2>This survey, conducted by an Imperial College London Master’s student Sabahat Bajwa, focused on understanding how artificial intelligence (AI) tools are viewed by fertility professionals in clinical practice. 144 respondents including embryologists, doctors and academics from 37 countries participated in the survey.It revealed that overall fertility professionals viewed AI positively but remained cautious about its use in fertility as a decision-making support tool. However, 53% of participants agreed that AI could help reduce the burden felt, especially when making clinical decisions. 14 out of 29 respondents that disagreed that AI reduced clinical burden had never experienced the use of AI tools in the first place.AI could help to provide a full understanding of decision-making, which currently is a complex and non-standardised process in both the embryology lab and doctor’s consultation room. The low implementation of AI in clinical fertility environment to date can be explained by insufficient experience, knowledge and validation of AI tools. Therefore, there is a need for training programmes, smooth integration into clinics’ digital ecosystems and further testing of the AI tools, such as increased live birth validation. 
 
 <img src="https://images.prismic.io/apricity/190df488-8eda-469f-ab4d-97bcf59fd843_Screenshot+2023-01-15+at+4.44.50+PM.png?auto=compress,format" alt="" copyright="" />
 
 <h2>A novel follicle classification system based on the shape of the distribution of follicle sizes</h2>Another Apricity research project led by Imperial College London Master’s student Sabahat Bajwa focuses on ovarian stimulation. Ovarian stimulation is a process during the fertility treatment cycle when a female patient’s ovaries are artificially stimulated to produce more eggs for subsequent fertilisation, instead of only one egg that is ovulated during a regular cycle. There are several options for ovarian stimulation used during fertility treatment which differ by certain medicines prescribed by doctors to take over several days/weeks <a href="https://academic.oup.com/hropen/article/2020/2/hoaa009/5827574">1</a>. However, there is no one treatment protocol that works for each woman undergoing fertility treatment. Some patients may develop only very few eggs (and the stimulation will have to be repeated), while others may overreact with a risk of a serious complication called ovarian hyperstimulation syndrome (OHSS). <a href="https://academic.oup.com/hropen/article/2020/2/hoaa009/5827574">1</a> Apricity has been working on AI tools to help clinicians choose the most suitable ovarian stimulation protocol <a href="https://www.apricity.life/ai">2</a>. This project focused on classifying the growth of follicles in a transparent manner so that the clinician can understand the decision being suggested by the AI. Apricity proposed a novel follicle profile classification system based on the shape of the distribution of follicle sizes seen and compared the follicle distributions with patient factors, including AMH, BMI, age and number of eggs collected. This helped to identify differences in variable averages between each follicle distribution, which can be a simple method of categorising follicle tracking data and could be assessed automatically using artificial intelligence.
 
 <img src="https://images.prismic.io/apricity/2b5e81a7-8a90-47bf-b09c-36844487d50a_Screenshot+2023-01-15+at+4.45.09+PM.png?auto=compress,format" alt="" copyright="" />
 
 <h2>Embryo development in 4D</h2>The way cells in an embryo are arranged geometrically has been shown to have an impact on further embryo development. Previous studies by Apricity researched the 3D visualisation of an embryo. This time, using a deep learning AI system, Chloe He, a PhD student at UCL and Data Scientist at Apricity, investigated how these cell arrangements impacted embryo development over time, otherwise known as 4D. 4D embryo visualisation allows visualising the changes in cell arrangements throughout embryo development. This not only provides special insights into embryo development but can also improve the understanding of embryo quality, which is important when deciding which embryo to choose for transfer. 
 
 <img src="https://images.prismic.io/apricity/32dbb26c-804d-4dd7-901d-30f50158c784_Screenshot+2023-01-15+at+5.35.57+PM.png?auto=compress,format" alt="" copyright="" />
 
 <h2>Factors to consider when deciding how many embryos to transfer</h2>Single embryo transfer is generally recommended for good prognosis patients (women under 37 on their first IVF cycle) regardless of available embryo quality <a href="https://www.hfea.gov.uk/about-us/publications/research-and-data/multiple-births-in-fertility-treatment-2019/#:~:text=For%20patients%20aged%2035%2D37,regardless%20of%20available%20embryo%20quality.">3</a>. The alternative, a multiple embryo transfer, may lead to serious maternal and foetal complications, therefore HFEA has introduced the 10% multiple birth rate target, which means that individual fertility clinics must adjust their clinical practices to maintain their multiple live birth rate under 10%. A study conducted by Jia Lu and Apricity&#39;s research team investigated which factors should be considered when deciding on whether to use elective single embryo transfer (eSET) or multiple embryo transfer (MET). The factors studied included:<ul><li>Maternal age</li><li>Number of eggs collected</li><li>Day of embryo transfer</li><li>Whether it was a fresh or frozen embryo transfer (FET)</li><li>Whether PGT-A was used</li></ul>The study was conducted based on data from five different datasets in four different countries. Different clinics and countries have different fertility treatment practices and guidelines, which is why it is important to reflect diverse contexts in research and control for them. The findings demonstrated that elective single embryo transfer was overall a more successful strategy in all age groups, as it:<ul><li>Increased success rates in patients under 40</li><li>Led to equivalent success rates in patients over 40</li><li>Reduced the risk of multiple live birth in all patients thus avoiding severe complications for mother and baby</li></ul>
 
 <img src="https://images.prismic.io/apricity/e4d79870-e783-4bd2-9af1-498bf09eb683_Screenshot+2023-01-17+at+1.49.40+PM.png?auto=compress,format" alt="" copyright="" />
 
 <h2>Secure data access solution for improved research</h2>If you ever wondered how Apricity uses its AI tools to innovate, improve patient care and maintain data security, you’re in the right place. AI can be an invaluable tool in our everyday lives, including healthcare and fertility. However, to develop these tools and make them as much useful and reliable as possible, one needs to access a lot of data so the AI can learn from it. However, obtaining data for research is a long and usually complicated process due to data protection and security laws.To ensure that patient data is completely secure, Apricity data scientist Timothy Ferrand and the rest of Apricity AI team developed three machine learning algorithms using a novel data access solution. The novel platform enabled the data scientist team to send computer code to run securely on the collaborators’ centre’s on-premise server, thus, achieving a high level of data security as the data never left the centre at any point during the study.The performance of each model was really encouraging. It demonstrated the promise of using a secure third-party data-sharing solution allowing external researchers to provide and use clinically-relevant insights on sensitive fertility data in a secure and trustworthy manner.
 
 <img src="https://images.prismic.io/apricity/1b34300e-1577-4602-a936-b5505f4a12af_Screenshot+2023-01-17+at+2.04.09+PM.png?auto=compress,format" alt="" copyright="" />
 
 <h2>Blastocyst component image recognition using AI</h2>Another important factor when developing AI tools is whether they will be able to work on a variety of data. The main problem when developing machine learning algorithms is that they very often don’t work when tested on different data than they were trained on. We want it to learn and help humans make important clinical decisions, which requires a broader understanding and perceptibility, usually unavailable for humans as easily. For this reason, a master’s student at UCL, Ivan Popov, led a research project focused on creating a machine learning algorithm that can work well on different data. He developed a reliable tool that’s able to recognize different parts of a blastocyst (a day 5 embryo) including:<ul><li>Zona pellucida</li><li>Trophectoderm</li><li>Inner cell mass</li><li>Blastocoel</li></ul>
 
 <img src="https://images.prismic.io/apricity/c6fc887a-148d-4de1-9f93-1229c7b5dd04_Screenshot+2023-01-17+at+2.19.29+PM.png?auto=compress,format" alt="" copyright="" />
 
 It was comparable to the existing state-of-the-art models and was capable of performing high-quality segmentation for unseen data from different equipment. The tool has the potential to aid embryo evaluation by embryologists which is a critical decision when selecting which embryo to transfer. 
 
 <img src="https://images.prismic.io/apricity/1d916b8b-693c-4555-b930-b49a2548ef3e_Screenshot+2023-01-17+at+2.23.47+PM.png?auto=compress,format" alt="" copyright="" />
 
 <h2>Inner cell mass shape classification system and aneuploidy</h2>By classifying the inner cell mass (ICM) of a blastocyst, an MSc student at Imperial College London, Elaina Lausic, led a research project on predicting embryo quality and outcome, including aneuploidy, or chromosomal imbalance in embryos, implantation and live birth. She found that, compared to other shapes, blastocysts with spherical ICM led to aneuploid embryos, which generally result in failure of implantation or miscarriage. However, ICM shape proved to not be a predictor of implantation or live birth.These results are highly essential in the work towards non-invasive tools that can help predict embryo aneuploidy. Aneuploidy is the most common obstetrical complication that can explain single and recurrent pregnancy loss <a href="https://www.dovepress.com/genetic-testing-for-aneuploidy-in-patients-who-have-had-multiple-misca-peer-reviewed-fulltext-article-TACG#:~:text=Genetic%20and%20non%2Dgenetic%20causes,which%20result%20in%20a%20miscarriage).">4</a>. Currently, the only way to test it is by performing pre-implantation genetic testing for aneuploidy (PGT-A), which is a highly invasive procedure for the embryo involving a biopsy. Because embryos are fragile, a non-invasive method of finding out whether it is chromosomally balanced (euploid) is much valued. 
 
 <img src="https://images.prismic.io/apricity/1aafa1f9-d8c0-4fe4-90c7-e6a7c07a5d41_Screenshot+2023-01-17+at+3.57.46+PM+%281%29.png?auto=compress,format" alt="" copyright="" />
 
 <h2>Inner cell mass detection: AI vs humans</h2>The main goal of using AI tools in embryology is to set a high-quality standardisation. A high degree of variability, both between and within, embryologists has been found. Since embryologists select embryos based on the grades of such evaluations, there should be no inconsistency, and AI would be really helpful to eliminate this human error. A project led by Dr Celine Jacques, a data analyst at Apricity, investigated how ICM grading compares between and within AI and embryologists based on different factors:<ul><li>The focus of the ICM image</li><li>ICM position within an embryo</li><li>ICM compaction level</li><li>ICM cell number</li></ul>She found that the variation between AI and humans was impacted by the factors in the same way as the variation between humans. The largest variation was seen when ICM was out of focus.
 
 <img src="https://images.prismic.io/apricity/16d2dfbb-c53d-4043-868d-7efeef9c5cc1_Screenshot+2023-01-17+at+4.31.41+PM.png?auto=compress,format" alt="" copyright="" />
 
 When training embryologists or AI models, all four factors should be considered but especially having ICM in focus. Using AI becomes essential, although it should be checked and corrected by experts if necessary.
 
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AI Tools for Fertility Treatment Decision Making 

The Apricity Research and AI team presented at Fertility 2023 conference focused on creating artificial intelligence (AI) tools that could help embryologists in their critical decision-making.

AI Tools for Fertility Treatment Decision Making

We were thrilled to see Apricity&#39;s CEO, Caroline Noublanche, appear in <a target="_blank" rel="noopener" href="https://tech.london/news/5f046440facfc3001c07cb0c?">Tech London&#39;s feature</a> on the start ups normalising women&#39;s health.Alongside HANX&#39;s Sarah Welsh and Emjoy&#39;s Andrea Oliver Garcia, the article explores what the femtech (a term only coined in 2016) industry looks like today. Read about what&#39;s in store for digital women&#39;s health, alongside Caroline&#39;s career journey and passion for transforming the tech industry. “Due to the increased demand in personal and curated experiences, as well as the need to optimise interactions with healthcare providers, we’ve seen a new rise of technologies focused on providing truly individual one to one care,” Caroline shares in the feature. Thank you to Tech London for chatting to Caroline about our story. We couldn&#39;t be prouder of our mission to revolutionise fertility treatment, making it more personal, convenient and advanced. Read the full article <a target="_blank" rel="noopener" href="https://tech.london/news/5f046440facfc3001c07cb0c?utm_source=linkedin&amp;utm_medium=social&amp;utm_campaign=fiveyearson">here</a>.