ArticleInsights into imaging2022
DWI-based radiomic signature: potential role for individualized adjuvant chemotherapy in intrahepatic cholangiocarcinoma after partial hepatectomy.
Article in Insights into imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Artificial intelligence in the diagnosis and prognosis of intrahepatic cholangiocarcinoma: Applications and challenges.World journal of gastrointestinal oncology · 2025Review
- Diagnosis of Cholangiocarcinoma: The New Biological and Technological Horizons.Diagnostics (Basel, Switzerland) · 2025Review
- ChatGPT as an effective tool for quality evaluation of radiomics research.European radiology · 2025Article
- Artificial intelligence and multi-omics driven models would be the future of intrahepatic cholangiocarcinoma prediction research.Hepatobiliary surgery and nutrition · 2024Article
- Cholangiocarcinoma imaging: from diagnosis to response assessment.Abdominal radiology (New York) · 2024Review
- Letter to the editor Re "Nomogram based on clinical and preoperative CT features for predicting the early recurrence of combined hepatocellular-cholangiocarcinoma: a multicenter study".La Radiologia medica · 2024Article
- Personalized intrahepatic cholangiocarcinoma prognosis prediction using radiomics: Application and development trend.Frontiers in oncology · 2023Review
- CT-Based Radiomics Can Predict the Efficacy of Anlotinib in Advanced Non-Small-Cell Lung Cancer.Journal of oncology · 2022Article
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Authors and funding
11 authors at 3 institutions in 2 countries.
Funding
Abstract
objectivesTo develop a diffusion-weighted imaging (DWI) based radiomic signature for predicting early recurrence (ER) (i.e., recurrence within 1 year after surgery), and to explore the potential value for individualized adjuvant chemotherapy.
methodsA total of 124 patients with intrahepatic cholangiocarcinoma (ICC) were randomly divided into the training (n = 87) and the validation set (n = 37). Radiomic signature was built using radiomic features extracted from DWI with random forest. An integrated radiomic nomogram was constructed with multivariate logistic regression analysis to demonstrate the incremental value of the radiomic signature beyond clinicopathological-radiographic factors. A clinicopathological-radiographic (CPR) model was constructed as a reference.
resultsThe radiomic signature showed a comparable discrimination performance for predicting ER to CPR model in the validation set (AUC, 0.753 vs. 0.621, p = 0.274). Integrating the radiomic signature with clinicopathological-radiographic factors further improved prediction performance compared with CPR model, with an AUC of 0.821 (95%CI 0.684-0.959) in the validation set (p = 0.01). The radiomic signature succeeded to stratify patients into distinct survival outcomes according to their risk index of ER, and remained an independent prognostic factor in multivariable analysis (disease-free survival (DFS), p < 0.0001; overall survival (OS), p = 0.029). Furthermore, adjuvant chemotherapy improved prognosis in high-risk patients defined by the radiomic signature (DFS, p = 0.029; OS, p = 0.088) and defined by the nomogram (DFS, p = 0.031; OS, p = 0.023), whereas poor chemotherapy efficacy was detected in low-risk patients.
conclusionsThe preoperative DWI-based radiomic signature could improve prognostic prediction and help to identify ICC patients who may benefit from postoperative adjuvant chemotherapy.
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