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Prediction of the mitotic index and preoperative risk stratification of gastrointestinal stromal tumors with CT radiomic features

  • Abdominal Radiology
  • Published:
La radiologia medica Aims and scope Submit manuscript

Abstract

Objective

The objective is to develop a mitotic prediction model and preoperative risk stratification nomogram for gastrointestinal stromal tumor (GIST) based on computed tomography (CT) radiomic features.

Methods

A total of 267 GIST patients from 2009.07 to 2015.09 were retrospectively collected and randomly divided into (6:4) training cohort and validation cohort. The 2D-tumor region of interest was delineated from the portal-phase images on contrast-enhanced (CE)-CT, and radiomic features were extracted. Lasso regression method was used to select valuable features to establish a radiomic model for predicting mitotic index in GIST. Finally, the nomogram of preoperative risk stratification was constructed by combining the radiomic features and clinical risk factors.

Results

Four radiomic features closely related to the level of mitosis were obtained, and a mitotic radiomic model was constructed. The area under the curve (AUC) of the radiomics signature model used to predict mitotic levels in training and validation cohorts (training cohort AUC = 0.752; 95% confidence interval [95%CI] 0.674–0.829; validation cohort AUC = 0.764; 95% CI 0.667–0.862). Finally, the preoperative risk stratification nomogram combining radiomic features was equivalent to the clinically recognized gold standard AUC (0.965 vs. 0.983) (p = 0.117). The Cox regression analysis found that the nomogram score was one of the independent risk factors for the long-term prognosis of the patients.

Conclusion

Preoperative CT radiomic features can effectively predict the level of mitosis in GIST, and combined with preoperative tumor size, accurate preoperative risk stratification can be performed to guide clinical decision-making and individualized treatment.

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Data availability

Data are available for bona fide researchers who request it from the authors.

Abbreviations

GIST(s):

Gastrointestinal stromal tumor(s)

CT:

Computed tomography

ROI:

Region of interest

CE-CT:

Contrast-enhanced computed tomography

LASSO:

Least absolute shrinkage and selection operator

AUC:

Area under the curve

CI:

Confidence interval

NIH:

National Institutes of Health

NCCN:

National Comprehensive Cancer Network

BMI:

Body mass index

ICC:

Intraclass correlation coefficient

GLCM:

Gray-level co-occurrence matrix

GLRLM:

Gray-level run-length matrix

GLSZM:

Gray-level size zone matrix

GLDM:

Gray-level dependence matrix

NGTDM:

Neighboring gray tone difference matrix

ROC:

Receiver operating characteristic

RFS:

Recurrence-free survival

OS:

Overall survival

HR:

Hazard ratio

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Acknowledgements

We thank all patients, their families and all investigators involved in the present study. I would also like to thank my tutor, Professor Jian-Wei Xie.

Funding

This research was funded by Fujian Province medical “Innovation Double High” construction fund ([2021] No. 76).

Author information

Author notes

  1. Jian-Xian Lin, Fu-Hai Wang and Zu-Kai Wang have contributed equally to this work.

Authors and Affiliations

  1. Department of Gastric Surgery, Fujian Medical University Union Hospital, No. 29 Xinquan Road, Fuzhou, 350001, Fujian Province, China

    Jian-Xian Lin, Fu-Hai Wang, Zu-Kai Wang, Jia-Bin Wang, Chao-Hui Zheng, Ping Li, Chang-Ming Huang & Jian-Wei Xie

  2. Fujian Provincial Minimally Invasive Medical Center, Fuzhou, China

    Jian-Xian Lin, Fu-Hai Wang, Zu-Kai Wang, Jia-Bin Wang, Chao-Hui Zheng, Ping Li, Chang-Ming Huang & Jian-Wei Xie

  3. Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Jian-Xian Lin, Fu-Hai Wang, Zu-Kai Wang, Jia-Bin Wang, Chao-Hui Zheng, Ping Li, Chang-Ming Huang & Jian-Wei Xie

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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by J-XL, F-HW and Z-KW. The first draft of the manuscript was written by J-XL, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Chang-Ming Huang or Jian-Wei Xie.

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The authors declare no conflict of interest.

Data statement

The authors declare that they had full access to all of the data in this study and the authors take complete responsibility for the integrity of the data and the accuracy of the data analysis.

Institutional review board statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the institutional review board.

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This study is a retrospective study, and patients' informed consent was waived with the approval of the institutional review board.

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Lin, JX., Wang, FH., Wang, ZK. et al. Prediction of the mitotic index and preoperative risk stratification of gastrointestinal stromal tumors with CT radiomic features. Radiol med 128, 644–654 (2023). https://doi.org/10.1007/s11547-023-01637-2

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