Coming Soon: The Next Evolution of the Mac2021 Tool

Coming Soon: The Next Evolution of the Mac2021 Tool

For many clinicians, Müllerian anomalies are encountered only a handful of times throughout their careers. These rare congenital differences of the reproductive tract can be difficult to diagnose, challenging to classify, and confusing for both providers and patients.

Recognizing the need for a modern, practical approach, the ASRM Practice Committee charged the Müllerian Anomalies Task Force, led by Dr. Samantha Pfeifer, with updating the original American Fertility Society (AFS) Müllerian Anomalies Classification. The result was the ASRM Müllerian Anomalies Classification 2021 (MAC2021), a framework designed to provide greater clarity, consistency, and clinical relevance in the diagnosis and management of these complex conditions.

At the same time, ASRM staff recognized an opportunity to expand the classification's impact beyond a published document. Working closely with the task force, the ASRM Education Department developed an interactive web-based platform that transformed the classification into a practical educational and clinical resource. The goal was to create a tool that could help clinicians, educators, trainees, researchers, and patients better understand and apply the classification in real-world settings. The MAC2021 tool continues to evolve. Coming soon, a redesigned mobile-responsive platform, expanded educational resources, enhanced imaging guidance, and the introduction of MAVI, an AI-powered navigator, are helping make information about Müllerian anomalies more accessible than ever before.

Why an Update Was Needed

One of the biggest challenges surrounding Müllerian anomalies is the lack of a universally accepted way to describe them.

Because these conditions are relatively uncommon, many gynecologists, reproductive endocrinologists, radiologists, and trainees have limited exposure to them. Different specialties have often used different terminology, which can make diagnosis, communication, and research more difficult.

The ASRM MAC2021 classification organizes anomalies into major categories while recognizing that many patients do not fit perfectly into a single box. Clear descriptions and visual illustrations help users understand both common presentations and the many variations that exist within each category.

"We have simple two-dimensional drawings under the theory that when you go to a restaurant and don't speak the language, you can point to a picture and have a good understanding of what that is," said Dr. Pfeifer, describing the tool. "And so that's the basis of the classification. We can use words to describe all the subtleties because these anomalies don't come necessarily in standard presentations or appearances, and there are many subtleties and variations that we wanted to try and capture within the classification."

Creating a Common Language

A major goal of the MAC2021 update was to improve consistency.

Historically, the same anomaly could be referred to by multiple names depending on who was describing it. The updated classification identifies preferred terminology and provides a shared framework for use across specialties. This consistency is important not only for patient care but also for research and education.

The need for a common language is particularly important in imaging. Many Müllerian anomalies are diagnosed using ultrasound or MRI, yet radiologists and gynecologists have not always used the same terminology when interpreting findings. The updated MAC2021 tool helps bridge that gap by providing clear definitions, diagnostic criteria, and imaging examples that support more consistent communication and diagnosis.

From Classification to Interactive Learning Tool

From the beginning, the vision for MAC2021 extended beyond creating a classification system.

Jessica Goldstein, ASRM staff liaison to the Practice Committee, recognized the potential to transform the classification into a digital educational resource that could enhance accessibility, clinical application, and learner engagement. To bring that vision to life, Sarah Ramaiah, PhD, Lead Instructional Designer in the ASRM Education Department, led the design and development of the original MAC2021 web application.

Working closely with the Müllerian Anomalies Task Force, Ramaiah translated the classification into an interactive digital experience that made the content easier to navigate, understand, and apply. The resulting platform allowed users to move beyond a static publication and engage with the classification as a practical educational tool. Together, the task force and ASRM staff created a resource that could support clinicians, educators, trainees, and researchers alike.

Building on the success of the original platform, the 2026 redesign introduced a fully mobile-responsive experience with improved navigation, expanded educational resources, and new tools designed to support learning at the point of care.

Richer Educational Content

While the classification remains the foundation of the tool, the newest version includes substantial new educational content.

Users will find expanded radiologic imaging, practical guidance on obtaining high-quality MRI studies, diagnostic algorithms, literature references, and side-by-side comparisons of similar anomalies. The goal is to help clinicians move beyond simply naming an anomaly and toward understanding how to evaluate it correctly.

The updated tool also includes surgical videos sourced from peer-reviewed publications. These videos provide insight into treatment approaches and the complexity of certain procedures while reinforcing when referral to an experienced specialist may be appropriate.

For pediatric and adolescent gynecologists, the platform now includes additional guidance on evaluating younger patients, including imaging considerations for those who may not tolerate standard techniques.

Task force members emphasized that the educational content is designed to improve awareness and understanding while helping clinicians recognize when specialized care is needed. The tool supports diagnosis and education, but it also reinforces the importance of referral and multidisciplinary care for complex cases.

Meet MAVI

One of the most anticipated additions to the redesigned platform is MAVI, the Müllerian Anomalies Virtual Intelligence navigator.

MAVI allows users to ask questions and quickly locate information within the tool rather than searching through multiple sections to find an answer. Designed to provide just-in-time guidance and educational support, MAVI helps users navigate the classification more efficiently and access relevant information when they need it most.

Combined with the platform's mobile-friendly design, MAVI makes the resource easier to use whether clinicians are in the office, reviewing imaging studies, teaching trainees, or discussing a case with colleagues.

Improving Education for Patients and Providers

The task force members repeatedly highlighted the educational value of the MAC2021 tool.

For providers, it offers a structured approach to diagnosis and a better understanding of conditions they may encounter only rarely. For trainees, it serves as a learning resource that can supplement limited clinical exposure. For patients and families, the illustrations, imaging examples, and educational content can help explain anatomy and diagnoses in a way that is easier to understand.

Many patients with Müllerian anomalies spend years searching for answers before receiving an accurate diagnosis. By increasing awareness and improving access to educational resources, the MAC2021 tool has the potential to shorten that journey and help patients reach appropriate care more quickly.

"My patients feel relieved that there are so many different types of Müllerian anomalies," said Dr. Aimee Morrison, a specialist in pediatric and adolescent gynecology and member of the MAC 2021 Task Force. "It very much normalizes for patients that they are not alone in having a Müllerian anomaly."

Bringing Anatomy Into Three Dimensions

Another exciting area of development is the creation of patient-derived 3D models.

Developed from actual MRI and ultrasound imaging, these models transform complex anatomical structures into visual and tactile learning tools. Users can examine both the internal and external anatomy of specific anomalies, creating a level of understanding that is difficult to achieve through two-dimensional images alone.

Unlike generic models, these are based on real patient anatomy, reflecting the variation and complexity that clinicians encounter in practice. The models have already been used in educational settings, where trainees have found them valuable for understanding anatomy and correlating imaging findings with physical structures.

Looking ahead, the models may support patient education, surgical planning, simulation-based training, and future innovations in procedural education. Patients who have contributed imaging data have often expressed enthusiasm about helping improve awareness and diagnosis for others facing similar conditions.

A Resource Built Through Collaboration

Through thoughtful discussion, debate, and shared expertise, the MAC 2021 Task Force created something far more comprehensive than a classification system alone. "This was really a true multidisciplinary collaboration," said Dr. Petrozza. "I think compared to the first one, we had a lot more input from our radiology colleagues, from our MIGS colleagues, from our pediatric and adolescent colleagues, and of course, we had it from trainees and our reproductive endocrinologists."

Today, MAC2021 serves as a practical educational and clinical resource that helps providers make more accurate diagnoses, communicate more effectively across specialties, and better support patients navigating Müllerian anomalies. As the platform continues to evolve, it reflects ASRM's ongoing commitment to advancing education, improving clinical care, and fostering collaboration across the reproductive medicine community.

Look for changes in the Mac2021 in July.

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