Ovarian Cellular Fibroma: Magnetic Resonance Imaging Findings With Pathological Correlation
Bibliographic record
Abstract
Ovarian cellular fibromas are relatively rare and generally have a favorable prognosis. However, their recurrence can occur in cases involving rupture or adhesion. Preoperative diagnosis is crucial for determining the surgical approach and tumor retrieval methods. To date, the radiological findings of this tumor have not been well documented in the literature. We report the case of a 60-year-old postmenopausal woman with an ovarian cellular fibroma. Ultrasonography, computed tomography, and magnetic resonance imaging (MRI) revealed an 8 cm solid mass in the left adnexal area with minimal amount of ascites. On T2-weighted imaging (T2WI), the solid portion on the right side of the mass was mildly hyperintense, with the presence of several cystic components, while the smaller solid portion on the left side was hypointense. A diffusion-restricted site was also observed in the right solid portion of the mass. On dynamic contrast-enhanced MRI, the entire solid portion of the mass showed a faint and gradual enhancement pattern, suggesting a fibrous tumor. Since it could not be confidently diagnosed as an observable benign tumor, diagnostic laparoscopic surgery was performed to remove the mass, and following pathological examination of the tumor, a diagnosis of ovarian cellular fibroma was established. Microscopically, most areas of the tumor showed high cellularity, consistent with the diffusion-restricted site observed on MRI. However, some areas of normal density existed. In cases wherein a fibrous ovarian tumor exhibits diffusion restriction, cellular fibroma should be considered. This finding could have the potential to contribute to preoperative diagnosis and aid in the selection of treatment options. J Clin Gynecol Obstet. 2024;13(3):90-94 doi: https://doi.org/10.14740/jcgo981
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".