Gastrointestinal stromal tumor (GIST) presenting as a multilocular cystic intra-abdominal mass in a dog
Bibliographic record
Abstract
BACKGROUND: Gastrointestinal stromal tumor (GIST) is a malignant mesenchymal neoplasm described in humans, dogs, and cats. A hallmark of diagnosis for GISTs is positive immunohistochemical labelling with c-Kit (CD117). The differentiation of GIST from other mesenchymal neoplasms of the gastrointestinal tract is pivotal to allow for initiation of appropriate treatment. In humans, cystic GIST has been described, though this has not been reported in dogs. In humans, the cystic form of GIST has been associated with a favorable prognosis. In the present paper, we report a case of multilocular cystic GIST in a dog, which has not previously been described in this species. CASE PRESENTATION: A ten-year-old, male-entire Maltese terrier mix breed dog presented with a large cystic mural mass of the duoedenum and orad jejunum. Histopathology and positive immunohistochemical staining with CD117 confirmed a diagnosis of GIST. No evidence of metastasis was detected on routine staging with abdominal sonography and thoracic radiography at the time of diagnosis. Surgical resection was performed and toceranib therapy was initiated post-operatively. Metastasis was documented 251 days after surgery on computed tomography. Due to clinical deterioration, the patient was humanely euthanised 370 days after surgical excision. CONCLUSIONS: There are few differential diagnoses for large multilocular cystic intra-abdominal masses in dogs. This case presents a previously undescribed presentation of gastrointestinal stromal tumor in the dog as a predominantly multilocular cystic mass. It remains unclear if the cystic form of GIST may represent a favorable prognosis in dogs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".