Observational Study
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Surg. Sep 27, 2024; 16(9): 2942-2952
Published online Sep 27, 2024. doi: 10.4240/wjgs.v16.i9.2942
Advancing gastrointestinal stromal tumor management: The role of imagomics features in precision risk assessment
Gui-Hai Pan, Fei Zhou, Wu-Biao Chen, Ze-Jun Pan
Gui-Hai Pan, Wu-Biao Chen, Ze-Jun Pan, Department of Radiology, The Affiliated Hospital of Guangdong Medical University, Zhanjiang 524001, Guangdong Province, China
Fei Zhou, Department of Endocrinology, The Affiliated Hospital of Guangdong Medical University, Zhanjiang 524001, Guangdong Province, China
Author contributions: Pan GH and Zhou F conceived and designed the study; Chen WB, Pan ZJ, and Zhou F performed the experiments; Pan GH and Chen WB analyzed the data; Pan ZJ and Zhou F wrote the manuscript. All authors reviewed and approved the final version of the manuscript.
Institutional review board statement: This study was reviewed and approved by the Ethics Committee of the Affiliated Hospital of Guangdong Medical University.
Informed consent statement: All participants or their legal representatives voluntarily signed written informed consent forms.
Conflict-of-interest statement: The author declares no conflict of interest.
Data sharing statement: All data can be provided as needed.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Fei Zhou, Department of Endocrinology, The Affiliated Hospital of Guangdong Medical University, No. 57 Renmin Avenue South, Xiashan District, Zhanjiang 524001, Guangdong Province, China. 022141130@mails.ccu.edu.cn
Received: March 25, 2024
Revised: May 24, 2024
Accepted: July 17, 2024
Published online: September 27, 2024
Processing time: 176 Days and 11.9 Hours
Abstract
BACKGROUND

Gastrointestinal stromal tumors (GISTs) vary widely in prognosis, and traditional pathological assessments often lack precision in risk stratification. Advanced imaging techniques, especially magnetic resonance imaging (MRI), offer potential improvements. This study investigates how MRI imagomics can enhance risk assessment and support personalized treatment for GIST patients.

AIM

To assess the effectiveness of MRI imagomics in improving GIST risk stratification, addressing the limitations of traditional pathological assessments.

METHODS

Analyzed clinical and MRI data from 132 GIST patients, categorizing them by tumor specifics and dividing into risk groups. Employed dimension reduction for optimal imagomics feature selection from diffusion-weighted imaging (DWI), T1-weighted imaging (T1WI), and contrast enhanced T1WI with fat saturation (CE-T1WI) fat suppress (fs) sequences.

RESULTS

Age, lesion diameter, and mitotic figures significantly correlated with GIST risk, with DWI sequence features like sphericity and regional entropy showing high predictive accuracy. The combined T1WI and CE-T1WI fs model had the best predictive efficacy. In the test group, the DWI sequence model demonstrated an area under the curve (AUC) value of 0.960 with a sensitivity of 80.0% and a specificity of 100.0%. On the other hand, the combined performance of the T1WI and CE-T1WI fs models in the test group was the most robust, exhibiting an AUC value of 0.834, a sensitivity of 70.4%, and a specificity of 85.2%.

CONCLUSION

MRI imagomics, particularly DWI and combined T1WI/CE-T1WI fs models, significantly enhance GIST risk stratification, supporting precise preoperative patient assessment and personalized treatment plans. The clinical implications are profound, enabling more accurate surgical strategy formulation and optimized treatment selection, thereby improving patient outcomes. Future research should focus on multicenter studies to validate these findings, integrate advanced imaging technologies like PET/MRI, and incorporate genetic factors to achieve a more comprehensive risk assessment.

Keywords: Gastrointestinal stromal tumor; Magnetic resonance imaging; Imagomics; Risk stratification; Precision medicine; Diffusion-weighted imaging; T1-weighted imaging; Contrast enhanced T1-weighted imaging with fat saturation fat suppress

Core Tip: This study unveils the transformative potential of magnetic resonance imaging (MRI) imagomics in the preoperative risk stratification of gastrointestinal stromal tumors (GISTs), challenging traditional, pathology-based assessments. By analyzing imagomics features from MRI sequences, particularly diffusion-weighted imaging and a combined T1-weighted imaging (T1WI)/contrast enhanced T1WI with fat saturation fat suppress model, we have demonstrated unprecedented accuracy in predicting GIST risk levels. These findings not only enhance the precision of preoperative evaluations but also pave the way for more personalized treatment plans, aligning closely with the goals of precision medicine in oncology.