Histiocytic sarcoma with spinal necrosis in a dog with progressing non-ambulatory tetraparesis
Bibliographic record
Abstract
Background: Histiocytic sarcoma (HS) is an aggressive malignant neoplasm, and widespread metastasis occurs with a fatal outcome. HS involving the central nervous system is relatively uncommon. Spinal cord necrosis, a very rare condition, could be induced by ischemia or infarction. Here, we report a dog progressing non-ambulatory tetraparesis with spinal cord necrosis caused by HS. Case Description: A 9-year-old male Labrador Retriever was presented with a progressing non-ambulatory tetraparesis. CT imaging revealed lysis of the spinous process of T7 and a ring-shaped lesion surrounding the soft tissue of lung fields. T2-weighted MRI showed the spinous processes of T6 to T8 as hyperintense, and the lesion infiltrated into the T7 vertebra and the spinal cord. After euthanasia, the final diagnosis upon necropsy was HS, which was observed in the lung, spinous process, thoracic cord, and the pulmonary hilar lymph node. Moreover, necrotic spots were spread widely through the thoracic spinal cord. Conclusion: This report outlines a case of canine HS in the lung, spinous process, thoracic cord, and pulmonary hilar lymph node. Ischemic deficit and necrosis of the thoracic spinal cord resulted from the compression of perivascular tumor cells, which rapidly led to progressive tetraparesis. Although the diagnosis was difficult, MRI and CT images helped determine the prognosis. To our knowledge, this is the first case report of canine HS with direct spinal cord involvement associated with spinal necrosis.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".