Enophthalmos as the Initial Systemic Finding of Undiagnosed Metastatic Breast Carcinoma
Bibliographic record
Abstract
PURPOSE: To report on the importance of detecting and investigating non-traumatic enophthalmos, which occurred as the first presenting sign of an undiagnosed metastatic breast carcinoma in two patients with no prior history of neoplasia. DESIGN: Case series. OBSERVATIONS: The first case consists of a 74-year-old woman with no significant past medical history, who presented with a non-traumatic enophthalmos and ptosis of her left eye, and horizontal diplopia on right-gaze. Imaging revealed an intraconal lesion of her left orbit, with orbital fat atrophy. Transcutaneous anterior orbitotomy was performed for tumor biopsy, and the histopathology study concluded on a diagnosis of orbital metastasis consistent with infiltrative breast carcinoma. Thorough breast imaging and multiple breast biopsies were not able to localize the primary tumor. The second case consists of a 76-year-old woman, with no prior relevant medical history, who presented for progressive enophthalmos and ptosis of her right eye. Imaging revealed an osteolytic lesion of her right frontal bone, and multiple infiltrative lesions implicating both orbits. A biopsy was performed through a transcutaneous anterior orbitotomy and histopathology study lead to a diagnosis of metastatic lobular breast carcinoma. The primary breast tumor was localized using positron emission tomography, and further biopsy confirmed the diagnosis. CONCLUSION: Although uncommon, non-traumatic enophthalmos has a broad differential diagnosis. In some rare instances, it may be the initial presentation of orbital metastases in patients with no prior history of cancer, and in the absence of other systemic symptoms. Clinicians must be thorough when assessing and investigating this clinical entity. A comprehensive eye exam, systemic evaluation, orbit imaging, biopsy and immunohistochemistry analysis are essential to promptly diagnose orbital metastases and plan the appropriate treatment.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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 | 0.001 |
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".