Preoperative classification of endometriosis: a narrative review of revised American Society for Reproductive Medicine (r-ASRM), #Enzian, American Association of Gynecologic Laparoscopists (AAGL) 2021, and Numerical Multi-Scoring System of Endometriosis (NMS-E) systems

Introduction

Endometriosis is a chronic inflammatory disease affecting approximately 10% of women of reproductive age worldwide (1). It is a leading cause of chronic pelvic pain, dysmenorrhea, dyspareunia, dyschezia, and infertility (2). Lesions may present as ovarian endometriotic cysts, but they can also involve the peritoneum, fallopian tubes, and deeply infiltrate the uterosacral ligaments and Douglas pouch—referred to as deep endometriosis (DE). These lesions often lead to adhesions and anatomical distortion, potentially requiring multidisciplinary surgical treatment, especially when the bowel or urinary tract is involved (3-6).

When symptoms do not respond to medical therapy, such as hormonal treatment, or when dyspareunia or infertility becomes the primary concern, surgical intervention—typically laparoscopic—is often considered. In such cases, accurate preoperative assessment of the lesion’s location and severity is critical for effective surgical planning. However, commonly used systems such as the revised American Society for Reproductive Medicine (r-ASRM) classification (7,8) and the Endometriosis Fertility Index (EFI), though valuable for predicting infertility, also depend on intraoperative findings, particularly the Least Function (LF) score (9,10). Consequently, neither system can predict the severity of endometriosis or infertility without surgical findings.

To address these limitations, alternative diagnostic and classification frameworks have been proposed. Among them, the #Enzian classification (11-18) and the 2021 American Association of Gynecologic Laparoscopists (AAGL) classification (19-25) have gained attention as systems suitable for preoperative imaging-based evaluation. In addition, our group has developed the Numerical Multi-Scoring System of Endometriosis (NMS-E), a novel, non-invasive approach that combines ultrasound and pelvic examination findings to estimate disease severity and surgical complexity (26-30).

Considering these developments, this review explores the strengths and limitations of the #Enzian and AAGL 2021 classification systems and introduces NMS-E as an emerging approach for comprehensive preoperative assessment. We present this article in accordance with the Narrative Review reporting checklist (available at https://gpm.amegroups.com/article/view/10.21037/gpm-25-3/rc).

Methods

This narrative review focused on three classification systems relevant to the preoperative evaluation of endometriosis: the #Enzian classification (with emphasis on its 2021 revision), the 2021 AAGL classification, and the NMS-E.

A comprehensive literature search was conducted using PubMed (January 2015–January 2025), supplemented by Embase and Scopus. Most relevant articles were also indexed in PubMed. No restrictions were applied regarding study type, and both English and Japanese-language articles were considered (Table 1). A detailed search strategy for PubMed is provided in Table S1.

The following search terms were used:

• “#Enzian classification” OR “Enzian score”;
• “AAGL 2021 classification” OR “2021 AAGL endometriosis classification”.

After deduplication and full-text screening:

• #Enzian classification. A total of 66 articles related to the Enzian classification were identified. Based on their relevance to the 2021 revision and their methodological or clinical applicability, 7 key publications were selected for detailed analysis. These included 3 original research articles (11,15,16), 3 structured narrative reviews (12-14), and 1 radiological application study (17).
• AAGL 2021 classification. A total of 19 articles related to the AAGL 2021 classification were identified. Of these, 7 were selected for detailed analysis: 2 original studies (19), 1 external validation study (23), 1 narrative review (25), and 3 editorial commentaries addressing classification critique and implementation.
• NMS-E. As this system was developed by our institution, database searches were not required. Instead, five publications by our group were included: three peer-reviewed original research articles validating the system (e.g., adhesion scoring, pain scoring, and correlation with surgical outcomes) (28-30), one methodology paper describing the process of assigning the NMS-E score (26), and one observational study assessing interobserver agreement in scoring accuracy (27).

Review of the origins and evolution of the r-ASRM, #Enzian, AAGL 2021, and NMS-E classifications

Endometriosis is a complex gynecological condition that requires accurate classification systems to support diagnosis, treatment planning, and research. Although the r-ASRM classification is unsuitable for preoperative assessment, it has served as the foundation of endometriosis staging for decades (12,31).

To address its limitations, numerous alternative classification and diagnostic approaches have been proposed (31-39), including the Enzian system (8,40-42), the EFI (9,10), Ultrasound-Based Endometriosis Staging System (UBESS) (43), and various ultrasound-based mapping methods (44,45).

After years of ongoing development, several systems have now emerged that are specifically designed for use in the preoperative setting.

This is followed by an evaluation of three classification systems—#Enzian, AAGL 2021, and NMS-E—which have emerged as promising tools for preoperative diagnosis and surgical planning.

r-ASRM classification

Origin and purpose

The r-ASRM classification was originally introduced as the American Fertility Society (AFS) classification in 1979 (7) to standardize the staging of endometriosis. It provided a scoring framework based on lesion size, location, and adhesions in the peritoneum, Douglas pouch, ovaries, and fallopian tubes. The initial maximum score was 54 points, categorizing disease into four stages: Stage I (mild, 1–5), Stage II (moderate, 6–15), Stage III (severe, 16–40), and Stage IV (extensive, >40). Revisions in 1985 (8) and 1996 (46,47) refined lesion evaluation and increased the maximum score to 150 points to enable more detailed staging of advanced disease.

Despite its simplicity and widespread use, the r-ASRM classification is limited in preoperative settings. It relies entirely on intraoperative findings, provides only a retrospective measure of disease severity, and lacks predictive power for surgical complexity, pain symptoms, or fertility prognosis. Furthermore, it does not account for DE outside the pelvis. These limitations highlight the need for adjunctive or alternative classification systems that are specifically designed for preoperative use (12,14,16).

#Enzian classification

Development and Features

Introduced in 2005, the Enzian classification was created to improve the description of DE lesions (40). It employs a tumor-node-metastasis (TNM)-inspired system, categorizing DE in three compartments (A: rectovaginal septum/vagina; B: uterosacral ligaments; C: bowel) and additional modifiers for involvement of other structures (such as kidneys, bladder, and extragenital locations). Lesions are graded 1–3 based on size (<1, 1–3, >3 cm).

To address its initial overlap with the r-ASRM classification and better delineate deep infiltrating lesions, the Enzian system was revised in 2012 (48). This revision eliminated redundancy with r-ASRM by clearly limiting the scope of Enzian to retroperitoneal and deep lesions, while introducing supplementary categories (FA: adenomyosis, FB: bladder, FU: ureters, FI: intestines, FO: other locations) for more comprehensive anatomical mapping.

The system further expanded in 2021 to include ovarian endometriomas (O), superficial peritoneal lesions (S), and adenomyosis (A), establishing #Enzian as the most anatomically comprehensive classification to date (11). It thus provides a more complete representation of disease presentation, particularly in cases involving deep or extrapelvic endometriosis, than the r-ASRM classification (14).

Preoperative application

Originally designed for intraoperative description, #Enzian has been adapted for preoperative use through imaging (11). Magnetic resonance imaging (MRI) or dedicated transvaginal ultrasound techniques allow mapping of lesions to Enzian compartments (17). This enables surgeons to anticipate bowel or other organ involvement and plan multidisciplinary surgical teams as needed (16). However, the #Enzian system’s complexity and reliance on high-level imaging interpretation can limit its routine use (14). Pain and adhesion assessments are not part of the classification (12), so clinical symptoms must be correlated separately. Initial validation studies have shown that preoperative MRI-based #Enzian correlates moderately with surgical findings (17,18), but further research is needed to establish its prognostic value.

Limitations

Despite its comprehensive anatomical mapping, #Enzian is less effective in evaluating mild disease and superficial lesions (11). Its grading of adhesions is simplistic, focusing mainly on the assessment of tubal patency and peri-tubal adhesion mobility, without providing a comprehensive mapping of adhesion distribution (14). Additionally, training is required to accurately assign Enzian categories from imaging (17), potentially limiting its adoption in general practice.

AAGL 2021 classification

Concept and design

The AAGL 2021 endometriosis classification was developed to assess surgical complexity by assigning individual scores to four components: superficial peritoneal lesions, ovarian endometriomas, DE, and pelvic adhesions (19). The summed score is used to classify cases into Complexity Levels 1 (least complex) to 4 (most complex). Unlike r-ASRM and Enzian, which mainly describe anatomical extent, the AAGL system is designed to guide surgical decision-making by quantifying anticipated operative difficulty. It incorporates clinical and imaging findings to support preoperative planning.

Clinical utility

By focusing on factors that impact surgery (such as obliteration of the cul-de-sac, multifocal disease, and dense adhesions), the AAGL classification provides a roadmap for surgeons. A higher score suggests the need for advanced surgical skills or a multi-disciplinary team on standby. Early validation studies have shown that AAGL classification scores correlate with actual operative complexity and can predict the need for measures like bowel resection or ureteral dissection (23,24). This predictive ability makes it valuable for pre-surgical counseling and resource planning.

Limitations

The AAGL system, while practical, still omits direct pain quantification and may underestimate disease impact in patients with severe symptoms but lower anatomic scores. Extra-pelvic endometriosis (e.g., diaphragmatic or abdominal wall lesions) is not explicitly addressed (22). Additionally, like Enzian, accurate preoperative scoring relies on thorough imaging and sometimes diagnostic laparoscopy for adhesions, which can be subjective. Ongoing research is expanding on adhesion assessment via ultrasound (e.g., the “sliding sign” for uterine mobility) to improve non-invasive scoring (49).

NMS-E

Development and rationale

The NMS-E was developed by our group to provide an objective, quantifiable assessment of disease severity using only non-invasive preoperative methods (26-30). It evaluates four major components—cyst size, adhesion extent, pain distribution, and uterine findings—based on outpatient assessment, and adds points for rare-site lesions when present. These elements are integrated into a single “E-score”, which reflects the overall severity from mild to severe. Transvaginal ultrasound is used to assess cysts, adhesions, and uterine findings, while pain distribution is evaluated through pelvic examination.

Scoring components (26,30)

• Cyst score: measures the maximum diameter of ovarian endometriomas on ultrasound, assigning up to 5 points per ovary (10 points total if bilateral). Tubal lesions (e.g., hydrosalpinx) add 3 points per side.
• Adhesion score: adhesions are evaluated via transvaginal ultrasound using the uterine and ovarian “sliding sign” technique (49,50). The pelvic cavity is conceptually divided into 10 regions around the uterus and ovaries, and each region is assessed for restricted mobility indicating adhesions. A point is given for each affected region, up to 10 points total.
• Pain score: during pelvic exam, the pelvis is divided into seven regions around the cervix. The patient rates pain in each region using a 0–10 Numerical Rating Scale (NRS). Points are assigned for moderate to severe pain in each region, up to 10 points total, providing a quantitative pain map.
• Uterine score: presence of adenomyosis, a retroverted uterus (51), or deep infiltrating lesions affecting the uterus, each score 3 points (total up to 9). Uterine fibroids are noted but not scored.
• Others: rare-site endometriosis (e.g., bladder, bowel involvement, diaphragmatic, abdominal wall, or pulmonary lesions) automatically adds 10 points per site, acknowledging their significant impact.

These components yield an aggregate E-score, categorizing disease as mild [0–9], moderate [10–17], or severe [≥18] (26). The base maximum E-score is 39, but additional “+α” points from tubal or rare-site involvement can increase it. For example, a patient with bilateral endometriomas (8 points), widespread adhesions (7 points), multifocal pelvic pain (8 points), and adenomyosis and an endometrial nodule (6 points) would receive an E-score of 29, which falls into the severe range (Figure 1).

Figure 1 NMS-E record sheet (top) and example of scoring method (bottom). Adapted with permission from: Ichikawa M, et al. Biomedicines 2024;12:1267. Licensed under CC BY (26). NMS-E, Numerical Multi-Scoring System of Endometriosis.

Clinical implications and applications

NMS-E’s integrated approach allows a single evaluation to capture anatomical findings, symptom severity, and functional impairments such as adhesions that affect fertility. The resulting E-score reflects overall disease burden and correlates with surgical complexity: higher scores have been associated with longer operative durations (30) and may predict the need for advanced surgical procedures. Notably, lower Adhesion Scores have been observed in patients who achieved spontaneous pregnancy post-surgery, compared to those requiring in vitro fertilization (IVF). This highlights NMS-E’s potential for predicting fertility outcomes (28). Additionally, because NMS-E is non-invasive, it can be repeated over time to monitor disease progression, recurrence, or response to interventions, such as adhesion prevention therapy or pain management.

Strengths and limitations

Key advantages of NMS-E include its comprehensiveness—covering pain and adhesions, which are often omitted in other systems—and its accessibility via standard ultrasound and pelvic examination. The physical “mapping” of symptoms and adhesions provides visual guidance for surgical teams and facilitates multidisciplinary communication. Importantly, by directly evaluating pain and adhesions, NMS-E addresses quality-of-life factors, helping align surgical decisions with patient-reported symptoms.

However, several limitations remain. First, examiner variability in ultrasound technique or pelvic exam thoroughness may affect reliability (28). A learning curve exists in performing and interpreting the pain mapping (29). Like many systems, NMS-E does not explicitly account for superficial peritoneal lesions or assess tubal patency beyond its contribution to the cyst score (30). Finally, external validation remains limited, as most published data come from the developers’ institution (30). Broader studies are needed to replicate findings and demonstrate whether NMS-E improves surgical planning or patient-centered outcomes in diverse clinical settings.

Discussion

Comparative analysis of endometriosis classification systems

Each classification system has distinct advantages and limitations in preoperative endometriosis assessment. To facilitate direct comparison, Table 2 summarizes their key characteristics. Each system reflects a different conceptual focus—anatomical staging (r-ASRM, #Enzian), surgical complexity (AAGL 2021), or symptom integration (NMS-E).

Strengths and limitations of each system

• #Enzian classification: originally developed for postoperative assessment, its evolution has made it suitable for preoperative diagnosis using imaging (11). However, the system’s complexity and limited ability to assess pain and superficial lesions reduce its practicality in certain scenarios (14). Moreover, it does not explicitly evaluate the obliteration status of the pouch of Douglas, which is a clinically important feature in surgical planning for DE (29).
• AAGL 2021 classification: designed for surgical planning, it integrates lesion characteristics with a surgical complexity score. However, like the #Enzian classification, it lacks direct assessment of pain severity and provides only limited evaluation of adhesions (22). Additionally, it does not explicitly address lesions in the uterosacral ligament (USL) region, which are clinically important in DE (16). Its limited utility for extra-pelvic lesions and reliance on specialized training further constrain its broader applicability (22).
• NMS-E: this system excels in its intuitive design, integrating lesion evaluation with pain and adhesion scoring. Its focus on non-invasive methods, such as pelvic exams and ultrasound, allows for widespread applicability. Despite its promising features, the need for further validation studies and tools for extra-pelvic lesions highlights areas for improvement (30).

The path to an ideal system

As illustrated in Table 2, the NMS-E system aligns closely with the ideal characteristics of a preoperative diagnostic framework. It provides a comprehensive evaluation through physical mapping, a concise alphanumeric summary, and a single E-score. Its ability to visually represent adhesion localization and pain-inducing regions offers actionable insights for surgical planning and resource allocation (28,29). Moreover, the system’s capacity to predict fertility outcomes and track postoperative adhesion changes enhances its clinical versatility (28).

However, challenges remain. NMS-E’s limited validation necessitates broader clinical trials to establish its reliability across diverse populations (30). Additionally, while the system effectively evaluates intra-pelvic lesions, its inability to directly assess superficial peritoneal implants and extra-pelvic sites highlights areas for further development. Future iterations might integrate advanced imaging or biomarkers to address these gaps.

Future directions

Building on the strengths of existing systems, future diagnostic frameworks should strive to integrate lesion distribution and symptom severity into a unified scoring model. An ideal system would incorporate imaging, clinical examination, and patient-reported outcomes (such as pain scores) to comprehensively grade disease. Emphasis on cost-effective, widely available tools (ultrasound over MRI, standardized exam protocols) will ensure accessibility and broad adoption. Additionally, leveraging emerging technologies—like machine learning algorithms to interpret imaging or predict outcomes—may further enhance diagnostic precision and individualize patient care. Any new system should undergo rigorous multicenter validation to gain international acceptance. Collaborative efforts by expert societies (similar to WES’s involvement in prior consensus) will be crucial to promote a universally adopted classification (12).

Conclusions

The comparison of r-ASRM, #Enzian, AAGL 2021, and NMS-E systems reflects significant progress toward a comprehensive preoperative diagnostic framework for endometriosis. Each system contributes valuable elements: r-ASRM provides historical context and a foundation for staging; #Enzian offers detailed anatomical mapping of deep lesions; AAGL 2021 introduces a focus on surgical complexity; and NMS-E encompasses symptomatology and adhesion assessment. None, however, fully meets the criteria for an ideal preoperative tool. Among them, NMS-E demonstrates considerable potential, particularly in correlating symptoms with lesion findings and aiding minimally invasive surgical planning. To advance endometriosis care, continued refinement and integration of these systems is needed, alongside validation studies that confirm improvements in diagnostic accuracy, surgical outcomes, and patient quality of life. Ultimately, a widely accepted preoperative classification will enhance our ability to tailor interventions, predict prognoses, and improve the overall management of endometriosis.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the Narrative Review reporting checklist. Available at https://gpm.amegroups.com/article/view/10.21037/gpm-25-3/rc

Peer Review File: Available at https://gpm.amegroups.com/article/view/10.21037/gpm-25-3/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://gpm.amegroups.com/article/view/10.21037/gpm-25-3/coif). The authors have no conflicts of interest to declare.

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