ArticleInsights into imaging2024
Development and validation of a model for predicting the expression of Ki-67 in pancreatic ductal adenocarcinoma with radiological features and dual-energy computed tomography quantitative parameters.
Article in Insights into imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 12 citations in OpenAlex.
- Routine Laboratory Biomarkers for Survival Prediction After Limb-Salvage Surgery in Osteosarcoma: Development of a LASSO-Cox Prognostic Model and Internal Validation.Journal of clinical medicine · 2026Article
- Preoperative prediction of perineural invasion in pancreatic ductal adenocarcinoma using dual-layer spectral CT.Abdominal radiology (New York) · 2026Article
- Research progress on the application of dual energy CT in gastric diseases.Frontiers in medicine · 2026Review
- Early postoperative recurrence prediction in pancreatic ductal adenocarcinoma: a nomogram based on dual-energy computed tomography andQuantitative imaging in medicine and surgery · 2026Article
- Radiomics analysis of dual-energy CT-derived iodine maps for predicting histopathologic grading of pancreatic ductal adenocarcinoma: a two-center study.Frontiers in medicine · 2026Article
- Non-invasive prediction of Ki-67 and p53 biomarkers in spinal ependymoma via deep learning: using multimodal magnetic resonance imaging and clinical data.Biomarker research · 2025Article
- Nomogram for predicting tumor-stroma ratio in pancreatic ductal adenocarcinoma using dual-energy computed tomography.BMC medical imaging · 2025Article
- Dual-energy computed tomography for predicting histological grading and survival in patients with pancreatic ductal adenocarcinoma.European radiology · 2025Article
- Radiomics analysis of dual-layer detector spectral CT-derived iodine maps for predicting Ki-67 PI in pancreatic ductal adenocarcinoma.BMC medical imaging · 2025Article
- Preoperative multiparameter MRI-based prediction of Ki-67 expression in primary central nervous system lymphoma.Precision radiation oncology · 2025Article
- Differential diagnosis of thrombosis and myxoma in unusual heart positions by dual-energy CT multiple parameter imaging: A case series.Medicine · 2025Article
- Evaluation of Ki-67 expression levels in esophageal squamous cell carcinoma using dual-energy CT quantitative parameters.Frontiers in oncology · 2025Article
- Preoperative prediction of Ki-67 expression in hepatocellular carcinoma by spectral imaging on dual-energy computed tomography (DECT).Quantitative imaging in medicine and surgery · 2024Article
- Correlation of dynamic contrast-enhanced ultrasonography and the Ki-67 labelling index in pancreatic ductal adenocarcinoma.World journal of gastroenterology · 2024Article
- Differentiation of pathological subtypes and Ki-67 and TTF-1 expression by dual-energy CT (DECT) volumetric quantitative analysis in non-small cell lung cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
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13 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveTo construct and validate a model based on the dual-energy computed tomography (DECT) quantitative parameters and radiological features to predict Ki-67 expression levels in pancreatic ductal adenocarcinoma (PDAC). MATERIALS AND
methodsData from 143 PDAC patients were analysed. The variables of clinic, radiology and DECT were evaluated. In the arterial phase and portal venous phase (PVP), the normalized iodine concentration (NIC), normalized effective atomic number and slope of the spectral attenuation curves were measured. The extracellular volume fraction (ECVf) was measured in the equilibrium phase. Univariate analysis was used to screen independent risk factors to predict Ki-67 expression. The Radiology, DECT and DECT-Radiology models were constructed, and their diagnostic effectiveness and clinical applicability were obtained through area under the curve (AUC) and decision curve analysis, respectively. The nomogram was established based on the optimal model, and its goodness-of-fit was assessed by a calibration curve.
resultsComputed tomography reported regional lymph node status, NIC of PVP, and ECVf were independent predictors for Ki-67 expression prediction. The AUCs of the Radiology, DECT, and DECT-Radiology models were 0.705, 0.884, and 0.905, respectively, in the training cohort, and 0.669, 0.835, and 0.865, respectively, in the validation cohort. The DECT-Radiology nomogram was established based on the DECT-Radiology model, which showed the highest net benefit and satisfactory consistency.
conclusionsThe DECT-Radiology model shows favourable predictive efficacy for Ki-67 expression, which may be of value for clinical decision-making in PDAC patients. CRITICAL RELEVANCE STATEMENT: The DECT-Radiology model could contribute to the preoperative and non-invasive assessment of Ki-67 expression of PDAC, which may help clinicians to screen out PDAC patients with high Ki-67 expression. KEY POINTS: • Dual-energy computed tomography (DECT) can predict Ki-67 in pancreatic ductal adenocarcinoma (PDAC). • The DECT-Radiology model facilitates preoperative and non-invasive assessment of PDAC Ki-67 expression. • The nomogram may help screen out PDAC patients with high Ki-67 expression.
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