Contrast-enhanced CT radiomics for prediction of recurrence-free survival in gallbladder carcinoma after surgical resection

Fei, Xiang; Liang, Xiaoyuan; Yang, Lili; Liu, Xingyu; Yan, Sheng

doi:10.1007/s00330-022-08858-5

Cited by 13 publications

(5 citation statements)

References 34 publications

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“…Although the nomogram demonstrated good predictive performance, there were still some limitations in terms of original image selection, modeling methods and assessment of the predictive e cacy. Xiang et al [23] developed a nomogram prediction model based on radiomics signature, pathological T stage, N stage and tumor differentiation grade for the assessment of postoperative recurrence of GBC, which has limited value for clinical treatment decisions preoperatively despite its good predictive ability. Compared to reported studies on GBC survival prediction based on radiomics, we developed a nnU-Net segmentation model and Deepsurv prediction model based on the portal vein phase CT images, more convincing and innovative, and the C-index of the nnU-Net based clinical radiomics model was higher than clinical and radiomics prediction models in the training and testing sets, and close to manual based clinical radiomics model, with the best prognostic assessment ability.…”

Section: Discussionmentioning

confidence: 99%

Preoperative clinical radiomics model based on deep learning in prognostic assessment of patients with gallbladder carcinoma

Jin,

Li,

Zhang

et al. 2024

Preprint

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Objective We aimed to develop a preoperative clinical radiomics survival prediction model based on the radiomics features via deep learning to provide a reference basis for preoperative assessment and treatment decisions for patients with gallbladder carcinoma (GBC). Methods A total of 168 GBC patients who underwent preoperative upper abdominal enhanced CT from one high-volume medical center between January 2011 to December 2020 were retrospectively analyzed. The region of interest (ROI) was manually outlined by two physicians using 3D Slicer software to establish a nnU-Net model. The DeepSurv survival prediction model was developed by combining radiomics features and preoperative clinical variables. Results A total of 1502 radiomics features were extracted from the ROI results based on the nnU-Net model and manual segmentation, and 13 radiomics features were obtained through the 4-step dimensionality reduction methods, respectively. The C-index and AUC of 1-, 2-, and 3-year survival prediction for the nnU-Net based clinical radiomics DeepSurv model was higher than clinical and nnU-Net based radiomics DeepSurv models in the training and testing sets, and close to manual based clinical radiomics DeepSurv model. Delong-test was performed on the AUC of 1-, 2-, and 3-year survival prediction for the two preoperative clinical radiomics DeepSurv prediction models in the testing set, and the results showed that the two models had the same prediction efficiency (all P > 0.05). Conclusions By using the DeepSurv model via nnU-Net segmentation, postoperative survival outcomes for individual gallbladder carcinoma patients could be assessed and stratified, which can provide references for preoperative diagnosis and treatment decisions.

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Section: Discussionmentioning

confidence: 99%

Preoperative clinical radiomics model based on deep learning in prognostic assessment of patients with gallbladder carcinoma

Jin,

Li,

Zhang

et al. 2024

Preprint

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“…This can help to reduce the need for invasive procedures, such as biopsies or surgery, and improve patient outcomes by enabling earlier detection and more accurate diagnosis. Xiang et al (18) recently reported that their radiomics signature comprising 12 features together with their proposed nomogram (comprising pT3/4 stage, pN2 stage, poor differentiation grade, and high radiomics score) could be a promising estimate of the recurrence-free survival (RFS) of patients with GBC. Liu et al (19) used similar techniques and showed that a clinical-radiomics nomogram could be a promising tool for preoperatively predicting the lymph node status of patients with GBC.…”

Section: Discussionmentioning

confidence: 99%

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 tumor stage, distant metastasis, and treatment plan were independent factors affecting prognosis. Many reports have suggested a correlation between tumor stage, distant metastasis, and prognosis in patients with advanced GC[ 19 , 25 , 26 ]. This study found that CRS combined with HIPEC improves the survival time, indicating that this combination is safe and effective.…”

Section: Discussionmentioning

confidence: 99%

Effects of cytoreductive surgery combined with hyperthermic perfusion chemotherapy on prognosis of patients with advanced gallbladder cancer

Wu,

Hua,

Luo

et al. 2023

World J Gastrointest Surg

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BACKGROUND Gallbladder cancer (GC) is a common malignant tumor and one of the leading causes of cancer-related death worldwide. It is typically highly invasive, difficult to detect in the early stages, and has poor treatment outcomes, resulting in high mortality rates. The available treatment options for GC are relatively limited. One emerging treatment modality is hyperthermic intraperitoneal chemotherapy (HIPEC). HIPEC involves delivering heated chemotherapy directly into the abdominal cavity. It combines the strategies of surgical tumor resection and localized chemotherapy administration under hyperthermic conditions, aiming to enhance the concentration and effectiveness of drugs within the local tumor site while minimizing systemic toxicity. AIM To determine the effects of cytoreductive surgery (CRS) combined with HIPEC on the short-term prognosis of patients with advanced GC. METHODS Data from 80 patients treated at the Punan Branch of Renji Hospital, Shanghai Jiao Tong University School of Medicine between January 2018 and January 2020 were retrospectively analyzed. The control group comprised 44 patients treated with CRS, and the research group comprised 36 patients treated with CRS combined with HIPEC. Then, the survival time and prognostic factors of the two groups were compared, as well as liver and kidney function indices before and six days after surgery. Adverse reactions and complications were recorded in both groups. RESULTS The baseline data of the research and control groups were similar (P > 0.05). Six days after surgery, the alanine aminotransferase, aspartate aminotransferase, total bilirubin, and direct bilirubin levels significantly decreased compared to the preoperative levels in both groups (P < 0.05). However, the values did not differ between the two groups six days postoperatively (P > 0.05). Similarly, the postoperative creatinine and blood urea nitrogen levels were significantly lower than the preoperative levels in both groups (P < 0.05), but they did not differ between the groups six days postoperatively (P > 0.05). Furthermore, the research group had fewer postoperative adverse reactions than the control group (P = 0.027). Finally, a multivariate Cox analysis identified the tumor stage, distant metastasis, and the treatment plan as independent factors affecting prognosis (P < 0.05). The three-year survival rate in the study group was higher than that in the control group (P = 0.002). CONCLUSION CRS combined with HIPEC lowers the incidence of adverse reactions and improves survival in patients with advanced GC.

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Contrast-enhanced CT radiomics for prediction of recurrence-free survival in gallbladder carcinoma after surgical resection

Cited by 13 publications

References 34 publications

Preoperative clinical radiomics model based on deep learning in prognostic assessment of patients with gallbladder carcinoma

Preoperative clinical radiomics model based on deep learning in prognostic assessment of patients with gallbladder carcinoma

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

Effects of cytoreductive surgery combined with hyperthermic perfusion chemotherapy on prognosis of patients with advanced gallbladder cancer

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