ArticleClinical and experimental hepatology2021
Computed tomography texture-based radiomics analysis in gallbladder cancer: initial experience.
Article in Clinical and experimental hepatology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05718115 (Deep Learning Radiogenomics For Individualized Therapy in Unresectable Gallbladder Cancer), which is not on this map. Cited by 10 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Deep Learning Radiogenomics For Individualized Therapy in Unresectable Gallbladder Cancer
Who cites it
10 citing papers in PubMed.
- Artificial intelligence in gangrenous cholecystitis: advances in risk factor identification and preoperative prediction-a scoping review.Frontiers in surgery · 2026Review
- An MRI-based model for preoperative prediction of tertiary lymphoid structures in patients with gallbladder cancer.Insights into imaging · 2025Article
- Preoperative clinical radiomics model based on deep learning in prognostic assessment of patients with gallbladder carcinoma.BMC cancer · 2025Article
- Radiomic nomograms in CT diagnosis of gall bladder carcinoma: a narrative review.Discover oncology · 2024Review
- Gallbladder cancer: Progress in the Indian subcontinent.World journal of clinical oncology · 2024Review
- Imaging biomarkers between primary and metastatic tumors revealed by total-body positron emission tomography/computed tomography-based radiomics: a case series.Quantitative imaging in medicine and surgery · 2024Article
- Editorial: Role of imaging in biliary tract cancer: diagnosis, staging, response prediction and image-guided therapeutics.Frontiers in oncology · 2024Article
- Radiomics-based machine learning and deep learning to predict serosal involvement in gallbladder cancer.Abdominal radiology (New York) · 2024Article
- Technological Advancements in Interventional Oncology.Diagnostics (Basel, Switzerland) · 2023Review
- Imaging patterns of wall thickening type of gallbladder cancer.Clinical and experimental hepatology · 2022Review
Corrections and comments
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aim of the study: To investigate computed tomography (CT) texture parameters in suspected gallbladder cancer (GBC) and assess its utility in predicting histopathological grade and overall survival. Material and methods: This retrospective pilot study included consecutive patients with clinically suspected GBC. CT images, clinical, and histological or cytological data were retrieved from the database. CT images were reviewed by two radiologists. A single axial CT section in the portal venous phase was selected for texture analysis. Radiomic feature extraction was done using commercially available research software. Results: Thirty-eight patients (31 females, mean age 53.1 years) were included. Malignancy was confirmed in 29 patients in histopathology or cytology analysis, and the rest had no features of malignancy. Exophytic gallbladder mass with associated gallbladder wall thickening was present in 22 (58%) patients. Lymph nodal, liver, and omental metastases were present in 10, 1, and 3 patients, respectively. The mean overall survival was 9.7 months. There were significant differences in mean and kurtosis at medium texture scales to differentiate moderately differentiated and poorly differentiated adenocarcinoma ( Conclusions: Our preliminary results highlight the potential utility of CT texture-based radiomics analysis in patients with GBC. Medium texture scale parameters including both mean and kurtosis, or kurtosis alone, may help predict the histological grade and survival, respectively.
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