Dataset Information

Preoperative prediction of gastrointestinal stromal tumors with high Ki-67 proliferation index based on CT features.

ABSTRACT:

Background

To determine whether preoperative computed tomography (CT) features can be used for the prediction of gastrointestinal stromal tumors (GISTs) with a high Ki-67 proliferation index (Ki-67 PI).

Methods

A total of 198 patients with surgically and pathologically proven GISTs were retrospectively included. All GISTs were divided into a low Ki-67 PI group (<10%) and a high Ki-67 PI group (≥10%). All imaging features were blindly interpreted by two radiologists. Receiver operating characteristic (ROC) curve analyses were conducted to evaluate the predictive performance of the imaging features.

Results

Imaging features were found to be significantly different between the low and the high Ki-67 PI groups (P<0.05). Wall thickness of necrosis showed the highest predictive ability, with an area under the curve (AUC) of 0.838 [95% confidence interval (CI): 0.627-0.957], followed by necrosis, necrosis degree, hyperenhancement of the overlying mucosa (HYOM), and long diameter (LD) (AUC >0.7, P<0.05). HYOM was the strongest predictive feature for the high Ki-67 PI GISTs group, with an odds ratio (OR) value of 30.037 (95% CI: 5.707-158.106).

Conclusions

Imaging features, including the presence of necrosis, high necrosis degree, thick wall of necrosis, and HYOM were significant predictive indicators for the high Ki-67 PI GISTs group.

SUBMITTER: Yang CW

PROVIDER: S-EPMC8576677 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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Publications

Preoperative prediction of gastrointestinal stromal tumors with high Ki-67 proliferation index based on CT features.

Yang Cai-Wei CW Liu Xi-Jiao XJ Zhao Lian L Che Feng F Yin Yuan Y Chen Hui-Jiao HJ Zhang Bo B Wu Min M Song Bin B

Annals of translational medicine 20211001 20

<h4>Background</h4>To determine whether preoperative computed tomography (CT) features can be used for the prediction of gastrointestinal stromal tumors (GISTs) with a high Ki-67 proliferation index (Ki-67 PI).<h4>Methods</h4>A total of 198 patients with surgically and pathologically proven GISTs were retrospectively included. All GISTs were divided into a low Ki-67 PI group (<10%) and a high Ki-67 PI group (≥10%). All imaging features were blindly interpreted by two radiologists. Receiver opera ...[more]

PMID: 34790762

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Project description:ObjectivesTo evaluate and analyze radiomics models based on non-contrast-enhanced computed tomography (CT) and different phases of contrast-enhanced CT in predicting Ki-67 proliferation index (PI) among patients with pathologically confirmed gastrointestinal stromal tumors (GISTs).MethodsA total of 383 patients with pathologically proven GIST were divided into a training set (n = 218, vendor 1) and 2 validation sets (n = 96, vendor 2; n = 69, vendors 3-5). Radiomics features extracted from the most recent non-contrast-enhanced and three contrast-enhanced CT scan prior to pathological examination. Random forest models were trained for each phase to predict tumors with high Ki-67 proliferation index (Ki-67>10%) and were evaluated using the area under the receiver operating characteristic curve (AUC) and other metrics on the validation sets.ResultsOut of 107 radiomics features extracted from each phase of CT images, four were selected for analysis. The model trained using the non-contrast-enhanced phase achieved an AUC of 0.792 in the training set and 0.822 and 0.711 in the two validation sets, similar to models trained on different contrast-enhanced phases (p > 0.05). Several relevant features, including NGTDM Busyness and tumor size, remained predictive in non-contrast-enhanced and different contrast-enhanced images.ConclusionThe results of this study indicate that a radiomics model based on non-contrast-enhanced CT matches that of models based on different phases of contrast-enhanced CT in predicting the Ki-67 PI of GIST. GIST may exhibit similar radiological patterns irrespective of the use of contrast agent, and such radiomics features may help quantify these patterns to predict Ki-67 PI of GISTs.Clinical relevance statementGIST may exhibit similar radiomics patterns irrespective of contrast agent; thus, radiomics models based on non-contrast-enhanced CT could be an alternative for risk stratification in GIST patients with contraindication to contrast agent.Key points• Performance of radiomics models in predicting Ki-67 proliferation based on different CT phases is evaluated. • Non-contrast-enhanced CT-based radiomics models performed similarly to contrast-enhanced CT in risk stratification in GIST patients. • NGTDM Busyness remains stable to contrast agents in GISTs in radiomics models.

Dataset Information

Preoperative prediction of gastrointestinal stromal tumors with high Ki-67 proliferation index based on CT features.

Background

Methods

Results

Conclusions

Publications

Preoperative prediction of gastrointestinal stromal tumors with high Ki-67 proliferation index based on CT features.

Similar Datasets

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