Role of Multidetector CT Imaging in the Risk Stratification of Gastrointestinal Stromal Tumors (GISTs)–A Retrospective Analysis
Bibliographic record
Abstract
Abstract Background Gastrointestinal stromal tumors (GISTs) are the most common gastrointestinal mesenchymal neoplasms which can arise from any part of the gastrointestinal tract (GIT) or an extraintestinal location. Size and the organ of origin are the major imaging inputs expected from the radiologist. However, it is worthwhile to find out which imaging characteristics on MDCT correlate with risk stratification. This knowledge would help the clinician in treatment planning and prognostication. The aim of this retrospective study is to evaluate the various MDCT imaging characteristics of GISTs and find out which parameters have significant association with risk and subsequent development of metastasis on follow-up whenever it was possible. Materials and Methods This is a retrospective study conducted on 45 histopathologically proven cases of GIST from two institutions by searching from the digital archives. The following imaging parameters were analyzed: maximum size in any plane, organ of origin, shape (round, ovoid or irregular), margin (well-defined or ill-defined), surface (smooth or lobulated), percentage of necrosis, growth pattern, enhancement characteristics–both intensity (mild, moderate or significant) and pattern (homogenous vs. heterogenous), calcification, infiltration into adjacent organs, and presence of metastasis at presentation or on follow-up. Results CT morphological parameters of significance in risk stratification as per our study include tumor necrosis, predominant cystic change, irregular and lobulated shape/surface characteristics, and adjacent organ infiltration. The parameters which were associated with development of metastasis were size > 5 cm, necrosis > 30%, and the presence of adjacent organ infiltration. Conclusion The radiologist has an important role in ascertaining the size of tumor as well as the organ of origin accurately to guide the clinician in risk calculation and subsequent prognostication. In addition, certain CT characteristics mentioned above, namely, tumor size, significant necrosis/cystic changes, irregular/lobulated contour, and invasion of adjacent organs, help in risk stratification and in predicting metastasis/poor prognosis.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".