Outcomes Post-Laparoscopic Intervention for Accessory and Cavitated Uterine Masses: A Review and a Molecular Insight
Bibliographic record
Abstract
BACKGROUND: Accessory and cavitated uterine masses (ACUM) are rare Mullerian anomalies, defined as an isolated accessory cavitated mass lined with endometrial epithelium. OBJECTIVES: This article explores ACUM lesions from two aspects and integrates a case report of a successful laparoscopic-assisted intervention for ACUM in a 24-year-old woman with refractory dysmenorrhea with a review of current literature on laparoscopic surgical techniques. Unique to this case was the process of undergoing targeted genetic sequencing via the Find ITTM Panel Version 3.4 on the ACUM, looking for mutations in KRAS, PIK3CA, and FGFR2. A process that was inspired by recent reports that indicate that even normal endometrium can harbor cancer-associated mutations. METHODS: A comprehensive search of Ovid MEDLINE and Embase was performed. Studies were selected if they explored laparoscopic surgery's impact on ACUM patients' outcomes related to fertility, menorrhagia, or dysmenorrhea. Risk of bias assessment was performed using the JBI Critical Appraisal Checklist. OUTCOME: From 160 articles identified, 25 full-text articles were analyzed with a total of 75 unique patients discussed. Dysmenorrhea was present in 100% of cases (n = 75/75), and laparoscopic resection improved patient symptoms in 84% (n = 63/75) of cases. The mass excised in the case was positive for somatic missense mutations in RET (R813W) and HRAS (G12S) genes, identified at low variant allele frequencies. CONCLUSIONS AND OUTLOOK: These results demonstrated that laparoscopic surgical approaches are effective and frequently the first surgical approach chosen for the treatment of ACUM, but that techniques to treat these conditions are not standardized. This case is the first to demonstrate mutations in ACUM, suggesting a potential role for cancer-associated somatic mutations in their genesis. Future developments in this area may include sending more of these samples for genetic analysis, improving our understanding of how these lesions are formed, while also working to standardize how they are removed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".