Published online May 15, 2022. doi: 10.4251/wjgo.v14.i5.1014
Peer-review started: December 1, 2021
First decision: December 27, 2021
Revised: December 29, 2021
Accepted: April 21, 2022
Article in press: April 21, 2022
Published online: May 15, 2022
Gastrointestinal stromal tumors (GISTs) are clinically heterogeneous with varying degrees of malignant potential. Therefore, preoperative evaluation of the biological behavior of GISTs is important for surgical decision-making. Endoscopic resection is an effective and safe treatment for gastric GISTs smaller than 2 cm. Nevertheless, whether endoscopic surgery can be used in resecting gastric GISTs between 2 and 5 cm remains controversial considering the potential risk of metastasis and recurrence. The difficulty in assessing the malignant potential of 2-5 cm gastric GISTs present challenges to surgeons.
Preoperative prediction of the malignant potential and prognosis of GISTs is crucial for clinical decision-making. Radiomics has also been used to preoperatively predict the malignant potential of GISTs. However, the study on 2-5 cm gastric GISTs has not yet been reported.
As stated above, we proposed a radiomics method for predicting the malignant potential of 2-5 cm gastric GISTs based on preoperative enhanced computerized tomography (CT) images. The method may be helpful for preoperative design of individualized treatment strategy for patients with 2-5 cm gastric GISTs.
This was a retrospective study in which three models were constructed, including radiological model, radiomics model, and nomogram model. A radiological model was constructed based on CT findings and clinical characteristics. XGboost method was used to construct a radiomics model. Nomogram was constructed by combining the radiomics score with CT findings.
The area under the curve (AUC) of the nomogram model was significantly larger than the AUC of the radiological model in both the training group and the test group. The decision curve of analysis showed that the nomogram model produces increased benefit across the entire risk threshold range.
In this study, we developed a radiomics model and a nomogram for malignancy differentiation of 2-5 cm gastric GISTs, which achieved satisfactory discrimination and had the potential to act as a reproducible imaging marker to support the decision-making support in a noninvasive and effective way.
Future research should be considered on model validation and more integral factors such as KIT and PDGFRA mutations.