ArticleClinical cancer research : an official journal of the American Association for Cancer Research2018
A Visually Apparent and Quantifiable CT Imaging Feature Identifies Biophysical Subtypes of Pancreatic Ductal Adenocarcinoma.
Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers, 1 of them a synthesis that pooled it.
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Who cites it
79 citing papers in PubMed, 1 synthesis or guideline pooled it, 108 citations in OpenAlex.
- Integrated imaging and molecular analysis to decipher tumor microenvironment in the era of immunotherapy.Seminars in cancer biology · 2022Pooled it
- Bounding box-based 3D AI model for user-guided volumetric segmentation of pancreatic ductal adenocarcinoma on standard-of-care CTs.Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.] · 2023Trial
- Article
- Updates on Imaging Assessment of Pancreatic Cancer for Determining Anatomic and Biologic Resectability.Korean journal of radiology · 2026Review
- Contrast enhanced CT and MRI interchangeably reflect tumor characteristics in murine pancreatic cancer.Scientific reports · 2026Article
- Can Machine Learning Predict Metastatic Sites in Pancreatic Ductal Adenocarcinoma? A Radiomic Analysis.Journal of imaging informatics in medicine · 2026Article
- Preoperative Soluble AXL in Plasma Predicts Futility of Resecting Pancreatic Ductal Adenocarcinoma.Current oncology (Toronto, Ont.) · 2026Article
- Evaluation of histological tumor necrosis in pancreatic ductal adenocarcinoma via the quantitative parameters from enhanced computed tomography and its relationship with tumor prognosis.Quantitative imaging in medicine and surgery · 2025Article
- A risk score system including CT features for predicting early recurrence of resectable pancreatic ductal adenocarcinoma after radical resection: a dual-center retrospective study.European radiology · 2025Article
- Comparative Prognostic Roles of β-Catenin Expression and Tumor-Stroma Ratio in Pancreatic Cancer: Neoadjuvant Chemotherapy vs. Upfront Surgery.Current oncology (Toronto, Ont.) · 2025Article
- Clinical Applications of Quantitative Imaging and Artificial Intelligence for Pancreatic Cance.Seminars in radiation oncology · 2025Review
- MRI-based risk stratification for predicting overall survival in pancreatic ductal adenocarcinoma.Insights into imaging · 2025Article
- AI-Driven insights in pancreatic cancer imaging: from pre-diagnostic detection to prognostication.Abdominal radiology (New York) · 2025Review
- Mechanistic insight for T-cell exclusion by cancer-associated fibroblasts in human lung cancer.eLife · 2025Article
- The Landmark Series: The Future of Pancreatic Cancer Clinical Trials.Annals of surgical oncology · 2025Review
- Unveiling Matrix Metalloproteinase 13's Dynamic Role in Breast Cancer: A Link to Physical Changes and Prognostic Modulation.International journal of molecular sciences · 2025Review
- Stroma and lymphocytes identified by deep learning are independent predictors for survival in pancreatic cancer.Scientific reports · 2025Article
- Dual-energy CT extracellular volume fraction predicts tumor collagen ratio and possibly survival for inoperable pancreatic cancer patients.European radiology · 2025Article
- HIF-1α expression is associated with the pathological response to neoadjuvant chemotherapy in pancreatic ductal adenocarcinoma patients and can be predicted using CECT features.Quantitative imaging in medicine and surgery · 2025Article
- Noninvasive Computed Tomography-Based Quantification of Tumor Fibrosis Predicts Pancreatic Cancer Response to Gemcitabine/Nab-Paclitaxel.Research (Washington, D.C.) · 2025Article
19 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
38 authors at 1 institution in 1 country.
Funding
Abstract
purposePancreatic ductal adenocarcinoma (PDAC) is a heterogeneous disease with variable presentations and natural histories of disease. We hypothesized that different morphologic characteristics of PDAC tumors on diagnostic computed tomography (CT) scans would reflect their underlying biology. EXPERIMENTAL
designWe developed a quantitative method to categorize the PDAC morphology on pretherapy CT scans from multiple datasets of patients with resectable and metastatic disease and correlated these patterns with clinical/pathologic measurements. We modeled macroscopic lesion growth computationally to test the effects of stroma on morphologic patterns, hypothesizing that the balance of proliferation and local migration rates of the cancer cells would determine tumor morphology.
resultsIn localized and metastatic PDAC, quantifying the change in enhancement on CT scans at the interface between tumor and parenchyma (delta) demonstrated that patients with conspicuous (high-delta) tumors had significantly less stroma, higher likelihood of multiple common pathway mutations, more mesenchymal features, higher likelihood of early distant metastasis, and shorter survival times compared with those with inconspicuous (low-delta) tumors. Pathologic measurements of stromal and mesenchymal features of the tumors supported the mathematical model's underlying theory for PDAC growth.
conclusionsAt baseline diagnosis, a visually striking and quantifiable CT imaging feature reflects the molecular and pathological heterogeneity of PDAC, and may be used to stratify patients into distinct subtypes. Moreover, growth patterns of PDAC may be described using physical principles, enabling new insights into diagnosis and treatment of this deadly disease.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.