Atypical Cystic Primary Hepatic GIST: A Case Report of Rare Presentation and Long-Term Survival
Bibliographic record
Abstract
Primary hepatic gastrointestinal stromal tumours (PHGISTs) are rare and frequently misdiagnosed due to their atypical presentation and uncertain origin. The purpose of this article is to present the case of a 79-year-old female patient with a gigantic PHGIST characterized by a predominantly cystic nature-an extremely rare presentation, as most cases of PHGIST are solid. Despite extensive imaging and exploratory laparotomy, the primary origin remained uncertain, leading to questioning about whether it was a true primary hepatic GIST or an atypical metastatic lesion. The initial therapeutic approach involved a surgical procedure aimed to confirm the diagnosis and achieve reductive tumourectomy. Following the surgery, the patient was administered imatinib with a favourable clinical response for four and a half years-an atypical pattern of resistance, as most patients typically develop therapeutic resistance within two to three years. A second surgical intervention was performed to address a cystic lesion localized in the left hepatic lobe, followed by an atypical segment III hepatectomy to achieve macroscopic resection. Subsequently, the patient received sunitinib for two and a half years, which resulted in temporary disease stabilization. However, the sunitinib treatment was associated with hypertension and leukopenia. The patient's overall survival was 8 years, suggesting that individualized therapeutic strategies and close monitoring might be the key in such cases. Furthermore, this case confirms the role of surgical intervention even in advanced disease stages, with multiple major resections contributing significantly to prolonged survival. The interplay between surgical and oncologic therapies remains essential to guiding clinical decisions. Given the unusual cystic presentation, this case highlights the necessity to expand the pathological and molecular profiling of PHGISTs. Furthermore, the atypical timeline of resistance development and treatment-related toxicity emphasizes the importance of further research into the genetic and pharmacological determinants of PHGISTs. These findings advocate for the refinement of diagnostic, therapeutic, and surveillance protocols tailored to rare GIST subtypes.
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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 | 0.000 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".