Primary Intracranial Thalamic Leiomyosarcoma: Clinical Report of a Case and Review of the Literature
Bibliographic record
Abstract
Purpose:The incidence of the primary intracranial leiomyosarcoma is extremely rare, and few cases have been previously reported worldwide to date. This report was to clarify the potential role of radiotherapy in the management of primary intracranial leiomyosarcoma. Methods and Materials:This report presented a 49-year old man with a 3-month history of a progressively headache and walking unsteadily. The diagnosis was confirmed with thalamic leiomyosarcomaof high-grade malignancyaccording to the pathologic examination after neurosurgical biopsy. The patient didnt undergo surgical resection because of a high risk death. After biopsy, radiotherapy using 3D-CRT technique to the mass site with 55.8Gy/31f/43d was given accordingly. Results: The mass didnt reduce much at the end of radiotherapy. The patient refused systemic chemotherapy, he was alive without signs of local relapse and brain side-effectswith 6 month follow-up. After living eleven months and three weeks after radiotherapy, he died of local progression. Conclusions: Through literature review, the current therapeutic approaches including surgery, radiotherapy as well as chemotherapy appear to have limited effect, but could be beneficious of patients in tumor local control and improvement of the life quality.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".