Establishing a radiomics model using contrast-enhanced ultrasound for preoperative prediction of neoplastic gallbladder polyps exceeding 10 mm
Abstract Background A key challenge in the medical field is managing gallbladder polyps (GBP) > 10 mm, especially when their nature is uncertain. GBP with a diameter exceeding 10 mm are associated with an increased risk of gallbladder cancer, making the key to their management the differentiation...
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2025-02-01
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| Series: | European Journal of Medical Research |
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| Online Access: | https://doi.org/10.1186/s40001-025-02292-1 |
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| author | Dong Jiang Yi Qian Yijun Gu Ru Wang Hua Yu Zhenmeng Wang Hui Dong Dongyu Chen Yan Chen Haozheng Jiang Yiran Li |
| author_facet | Dong Jiang Yi Qian Yijun Gu Ru Wang Hua Yu Zhenmeng Wang Hui Dong Dongyu Chen Yan Chen Haozheng Jiang Yiran Li |
| author_sort | Dong Jiang |
| collection | DOAJ |
| description | Abstract Background A key challenge in the medical field is managing gallbladder polyps (GBP) > 10 mm, especially when their nature is uncertain. GBP with a diameter exceeding 10 mm are associated with an increased risk of gallbladder cancer, making the key to their management the differentiation between benign and malignant types. The current practice, due to the inability to predict accurately, leads to excessive surgeries and ineffective follow-ups, increasing patient risks and medical burdens. Purpose This study aims to establish an imaging radiomics model using clinical data and contrast-enhanced ultrasound (CEUS) to predict neoplastic GBP exceeding 10 mm in diameter preoperatively. Materials and methods Data from 119 patients with GBP > 10 mm of unknown origin were analyzed. A total of 1197 features were extracted from the GBP area using conventional ultrasound (US) and CEUS. Significant features were identified using the Mann–Whitney U test and further refined with a least absolute shrinkage and selection operator (LASSO) regression model to construct radiomic features. By integrating clinical characteristics, a radiomics nomogram was developed. The diagnostic efficacy of the preoperative logistic regression (LR) model was validated using receiver operating characteristic (ROC) curves, calibration plots, and the Hosmer–Lemeshow test. CEUS is an examination based on conventional ultrasound, and conventional two-dimensional ultrasound still poses significant challenges in differential diagnosis. CEUS has a high accuracy rate in diagnosing the benign or malignant nature of gallbladder space-occupying lesions, which can significantly reduce the preoperative waiting time for related examinations and provide more reliable diagnostic information for clinical practice. Results Feature selection via Lasso led to a final LR model incorporating high-density lipoprotein, smoking status, basal width, and Rad_Signature. This model, derived from machine learning frameworks including Support Vector Machine (SVM), Logistic Regression (LR), Multilayer Perceptron (MLP), k-Nearest Neighbors (KNN), and eXtreme Gradient Boosting (XGBoost) with fivefold cross-validation, showed AUCs of 0.95 (95% CI: 0.90–0.99) and 0.87 (95% CI: 0.72–1.0) in internal validation. The model exhibited excellent calibration, confirmed by calibration graphs and the Hosmer–Lemeshow test (P = 0.551 and 0.544). Conclusion The LR model accurately predicts neoplastic GBP > 10 mm preoperatively. Radiomics with CEUS is a powerful tool for analysis of GBP > 10 mm. The model not only improves diagnostic accuracy and reduces healthcare costs but also optimizes patient management through personalized treatment plans, enhancing clinical outcomes and ensuring resources are more precisely allocated to patients who need surgery. |
| format | Article |
| id | doaj-art-d6bc882ac02f467cb4ab48bad2429db5 |
| institution | Kabale University |
| issn | 2047-783X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | BMC |
| record_format | Article |
| series | European Journal of Medical Research |
| spelling | doaj-art-d6bc882ac02f467cb4ab48bad2429db52025-02-09T12:26:43ZengBMCEuropean Journal of Medical Research2047-783X2025-02-0130111610.1186/s40001-025-02292-1Establishing a radiomics model using contrast-enhanced ultrasound for preoperative prediction of neoplastic gallbladder polyps exceeding 10 mmDong Jiang0Yi Qian1Yijun Gu2Ru Wang3Hua Yu4Zhenmeng Wang5Hui Dong6Dongyu Chen7Yan Chen8Haozheng Jiang9Yiran Li10Department of Ultrasound, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical UniversityDepartment of Ultrasound, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical UniversityDepartment of Ultrasound, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical UniversityDepartment of Ultrasound, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical UniversityDepartment of Pathology, Shanghai Eastern Hepatobiliary Surgery Hospital, Third Affiliated Hospital of Naval Medical UniversityDepartment of Anesthesiology, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical UniversityDepartment of Pathology, Shanghai Eastern Hepatobiliary Surgery Hospital, Third Affiliated Hospital of Naval Medical UniversityDepartment of Ultrasound, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical UniversityDepartment of Ultrasound, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical UniversityCollege of art and science department: medical anthropology, psychology, public health, Case Western Reserve UniversityDepartment of Ultrasound, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical UniversityAbstract Background A key challenge in the medical field is managing gallbladder polyps (GBP) > 10 mm, especially when their nature is uncertain. GBP with a diameter exceeding 10 mm are associated with an increased risk of gallbladder cancer, making the key to their management the differentiation between benign and malignant types. The current practice, due to the inability to predict accurately, leads to excessive surgeries and ineffective follow-ups, increasing patient risks and medical burdens. Purpose This study aims to establish an imaging radiomics model using clinical data and contrast-enhanced ultrasound (CEUS) to predict neoplastic GBP exceeding 10 mm in diameter preoperatively. Materials and methods Data from 119 patients with GBP > 10 mm of unknown origin were analyzed. A total of 1197 features were extracted from the GBP area using conventional ultrasound (US) and CEUS. Significant features were identified using the Mann–Whitney U test and further refined with a least absolute shrinkage and selection operator (LASSO) regression model to construct radiomic features. By integrating clinical characteristics, a radiomics nomogram was developed. The diagnostic efficacy of the preoperative logistic regression (LR) model was validated using receiver operating characteristic (ROC) curves, calibration plots, and the Hosmer–Lemeshow test. CEUS is an examination based on conventional ultrasound, and conventional two-dimensional ultrasound still poses significant challenges in differential diagnosis. CEUS has a high accuracy rate in diagnosing the benign or malignant nature of gallbladder space-occupying lesions, which can significantly reduce the preoperative waiting time for related examinations and provide more reliable diagnostic information for clinical practice. Results Feature selection via Lasso led to a final LR model incorporating high-density lipoprotein, smoking status, basal width, and Rad_Signature. This model, derived from machine learning frameworks including Support Vector Machine (SVM), Logistic Regression (LR), Multilayer Perceptron (MLP), k-Nearest Neighbors (KNN), and eXtreme Gradient Boosting (XGBoost) with fivefold cross-validation, showed AUCs of 0.95 (95% CI: 0.90–0.99) and 0.87 (95% CI: 0.72–1.0) in internal validation. The model exhibited excellent calibration, confirmed by calibration graphs and the Hosmer–Lemeshow test (P = 0.551 and 0.544). Conclusion The LR model accurately predicts neoplastic GBP > 10 mm preoperatively. Radiomics with CEUS is a powerful tool for analysis of GBP > 10 mm. The model not only improves diagnostic accuracy and reduces healthcare costs but also optimizes patient management through personalized treatment plans, enhancing clinical outcomes and ensuring resources are more precisely allocated to patients who need surgery.https://doi.org/10.1186/s40001-025-02292-1Gallbladder polypsRadiomicsContrast-enhanced ultrasound |
| spellingShingle | Dong Jiang Yi Qian Yijun Gu Ru Wang Hua Yu Zhenmeng Wang Hui Dong Dongyu Chen Yan Chen Haozheng Jiang Yiran Li Establishing a radiomics model using contrast-enhanced ultrasound for preoperative prediction of neoplastic gallbladder polyps exceeding 10 mm European Journal of Medical Research Gallbladder polyps Radiomics Contrast-enhanced ultrasound |
| title | Establishing a radiomics model using contrast-enhanced ultrasound for preoperative prediction of neoplastic gallbladder polyps exceeding 10 mm |
| title_full | Establishing a radiomics model using contrast-enhanced ultrasound for preoperative prediction of neoplastic gallbladder polyps exceeding 10 mm |
| title_fullStr | Establishing a radiomics model using contrast-enhanced ultrasound for preoperative prediction of neoplastic gallbladder polyps exceeding 10 mm |
| title_full_unstemmed | Establishing a radiomics model using contrast-enhanced ultrasound for preoperative prediction of neoplastic gallbladder polyps exceeding 10 mm |
| title_short | Establishing a radiomics model using contrast-enhanced ultrasound for preoperative prediction of neoplastic gallbladder polyps exceeding 10 mm |
| title_sort | establishing a radiomics model using contrast enhanced ultrasound for preoperative prediction of neoplastic gallbladder polyps exceeding 10 mm |
| topic | Gallbladder polyps Radiomics Contrast-enhanced ultrasound |
| url | https://doi.org/10.1186/s40001-025-02292-1 |
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