Incidental lymphangioleiomyomatosis in pelvic lymph nodes associated with Malignant neoplasm of the ovary – two case reports
Bibliographic record
Abstract
To the Editor, Lymphangioleiomyomatosis (LAM), a rare, destructive and progressive neoplastic disease, generally arises in the lung and occurs predominantly in women of childbearing age or premenopausal age [1].Primary extrapulmonary LAM is extremely rare, with only a handful of cases being reported, leading to limited information being available regarding the pathologic characteristics.Here we report two cases of LAM of the pelvic lymph node, accidentally discovered after surgical staging of ovarian malignancy.This report shows that occult LAM can be detected in surgical staging of pelvic tumors.The diagnosis should be based on clinicopathological features and immunohistochemical examination, to avoid a missed diagnosis or misdiagnosis.Written informed consent was obtained from the patient described in this letter, and the investigation was conducted in accordance with the Declaration of Helsinki (1975).The ethics committees of the Affiliated Hospital of Southwest Medical University approved this study.The first case was of a 55-year-old postmenopausal woman admitted to the hospital with abnormal uterine bleeding for more than 2 months.Doppler ultrasound suggested mixed cystic-solid echogenicity in the posterior uterus with a size of 10 × 9.5 × 7.5 cm, leading to a differential diagnosis of malignant tumor with pelvic lymph node metastasis.The second case was of a 54-year-old woman, who presented with a mass in her right ovary.The patient underwent an oophorectomy ten years ago, for clear cell carcinoma of the left ovary.After reviewing the abdominal computed tomography, a space-occupying lesion was seen in the right ovary, but no further treatment was given at the time and the tumor gradually enlarged.Total hysterectomy, bilateral adnexectomy and lymph node
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".