Development and Validation of a Preoperative Nomogram for Predicting Benign and Malignant Gallbladder Polypoid Lesions

Han, Shuai; Liu, Yu; Li, Xiaohang; Jiang, Xiao; Li, Baifeng; Zhang, Chengshuo; Zhang, Jialin

doi:10.3389/fonc.2022.800449

Cited by 3 publications

(4 citation statements)

References 27 publications

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“…CT is also often used to examine gallbladder disease because contrast enhancement allows the lesion to be distinguished from the surrounding tissue and aids in the diagnosis of gallbladder disease. The base appearance was found to be an independent predictor of benign and malignant GPs in this analysis, which is consistent with prior studies [ 11 , 12 ]. The size of GPs is one of the most important indications of the nature of the tumor and the need for surgery in clinical practice.…”

Section: Discussionsupporting

confidence: 93%

“…To improve the accuracy of the prediction of benign and malignant GPs, several studies have developed multiparametric prediction models that include clinical features, imaging, and radiomics features [ 11 – 13 ]. Han et al [ 12 ] established a nomogram for predicting benign and malignant polypoid lesions and showed that a model combining clinical features and CT-radiomics (AUC = 0.950) could provide a preoperative prediction of benign and malignant identification. However, feature determination and mapping of regions of interest for feature extraction are highly operator-dependent and unstable performance.…”

Section: Introductionmentioning

confidence: 99%

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The value of CT findings combined with inflammatory indicators for preoperative differentiation of benign and malignant gallbladder polypoid lesions

Zhang

Feng

et al. 2023

World J Surg Onc

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Background The study aimed to explore the value of CT findings and inflammatory indicators in differentiating benign and malignant gallbladder polypoid lesions before surgery. Methods The study comprised a total of 113 pathologically confirmed gallbladder polypoid lesions with a maximum diameter ≥ 1 cm (68 benign and 45 malignant), all of which were enhanced CT-scanned within 1 month before surgery. The CT findings and inflammatory indicators of the patients were analyzed by univariate and multivariate logistic regression analysis to identify independent predictors of gallbladder polypoid lesions, and then a nomogram distinguishing benign and malignant gallbladder polypoid lesions was developed by combining these characteristics. The receiver operating characteristic (ROC) curve and decision curve were plotted to assess the performance of the nomogram. Results Base status of the lesion (p < 0.001), plain CT value (p < 0.001), neutrophil–lymphocyte ratio (NLR) (p = 0.041), and monocyte-lymphocyte ratio (MLR) (p = 0.022) were independent predictors of malignant polypoid lesions of the gallbladder. The nomogram model established by incorporating the above factors had good performance in differentiating and predicting benign and malignant gallbladder polypoid lesions (AUC = 0.964), with sensitivity and specificity of 82.4% and 97.8%, respectively. The DCA demonstrated the important clinical utility of our nomogram. Conclusion CT findings combined with inflammatory indicators can effectively differentiate benign and malignant gallbladder polypoid lesions before surgery, which is valuable for clinical decision-making.

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Section: Discussionsupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

The value of CT findings combined with inflammatory indicators for preoperative differentiation of benign and malignant gallbladder polypoid lesions

Zhang

Feng

et al. 2023

World J Surg Onc

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“…With regard to radiomics models reported in the literature for differentiating between benign and malignant lesions, Han et al (20) showed that their combined model could represent a novel approach to effectively evaluate benign and malignant GPs; however, the AUC of their radiomics model was inferior to that of their clinical model, suggesting that their identified radiomics features were as strong as ours. Comparatively, the model outperformed the clinical model in both the training and test cohorts, thereby confirming the reliability of our proposed model.…”

Section: Discussionmentioning

confidence: 66%

Discrimination between benign and malignant gallbladder lesions on enhanced CT imaging using radiomics

Zhuang,

Feng,

Kong

et al. 2024

Acta Radiol

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Background Gallbladder cancer is a rare but aggressive malignancy that is often diagnosed at an advanced stage and is associated with poor outcomes. Purpose To develop a radiomics model to discriminate between benign and malignant gallbladder lesions using enhanced computed tomography (CT) imaging. Material and Methods All patients had a preoperative contrast-enhanced CT scan, which was independently analyzed by two radiologists. Regions of interest were manually delineated on portal venous phase images, and radiomics features were extracted. Feature selection was performed using mRMR and LASSO methods. The patients were randomly divided into training and test groups at a ratio of 7:3. Clinical and radiomics parameters were identified in the training group, three models were constructed, and the models’ prediction accuracy and ability were evaluated using AUC and calibration curves. Results In the training group, the AUCs of the clinical model and radiomics model were 0.914 and 0.968, and that of the nomogram model was 0.980, respectively. There were statistically significant differences in diagnostic accuracy between nomograms and radiomics features ( P <0.05). There was no significant difference in diagnostic accuracy between the nomograms and clinical features ( P >0.05) or between the clinical features and radiomics features ( P >0.05). In the testing group, the AUC of the clinical model and radiomics model were 0.904 and 0.941, and that of the nomogram model was 0.948, respectively. There was no significant difference in diagnostic accuracy between the three groups ( P >0.05). Conclusion It was suggested that radiomics analysis using enhanced CT imaging can effectively discriminate between benign and malignant gallbladder lesions.

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“…The models built by Yuan et al achieved good results in identifying the nature of GBPs [ 19 , 20 ]. Han integrated Radscore, which is calculated by taking 6 radiomics factors into the radiomics model, into the nomogram [ 21 ]. Even though the combined model performed slightly worse than the only clinical model in the testing cohort, it was a promising attempt.…”

Section: Predictive Modelsmentioning

confidence: 99%

Advances in the management of gallbladder polyps: establishment of predictive models and the rise of gallbladder-preserving polypectomy procedures

Liu,

Lu,

Shen

et al. 2024

BMC Gastroenterol

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Gallbladder polyps are a common biliary tract disease whose treatment options have yet to be fully established. The indication of “polyps ≥ 10 mm in diameter” for cholecystectomy increases the possibility of gallbladder excision due to benign polyps. Compared to enumeration of risk factors in clinical guidelines, predictive models based on statistical methods and artificial intelligence provide a more intuitive representation of the malignancy degree of gallbladder polyps. Minimally invasive gallbladder-preserving polypectomy procedures, as a combination of checking and therapeutic approaches that allow for eradication of lesions and preservation of a functional gallbladder at the same time, have been shown to maximize the benefits to patients with benign polyps. Despite the reported good outcomes of predictive models and gallbladder-preserving polypectomy procedures, the studies were associated with various limitations, including small sample sizes, insufficient data types, and unknown long-term efficacy, thereby enhancing the need for multicenter and large-scale clinical studies. In conclusion, the emergence of predictive models and minimally invasive gallbladder-preserving polypectomy procedures has signaled an ever increasing attention to the role of the gallbladder and clinical management of gallbladder polyps.

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Development and Validation of a Preoperative Nomogram for Predicting Benign and Malignant Gallbladder Polypoid Lesions

Cited by 3 publications

References 27 publications

The value of CT findings combined with inflammatory indicators for preoperative differentiation of benign and malignant gallbladder polypoid lesions

The value of CT findings combined with inflammatory indicators for preoperative differentiation of benign and malignant gallbladder polypoid lesions

Discrimination between benign and malignant gallbladder lesions on enhanced CT imaging using radiomics

Advances in the management of gallbladder polyps: establishment of predictive models and the rise of gallbladder-preserving polypectomy procedures

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