ArticleAbdominal radiology (New York)2019
CT radiomics associations with genotype and stromal content in pancreatic ductal adenocarcinoma.
Article in Abdominal radiology (New York), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pancreas image mining: a systematic review of radiomics.European radiology · 2021Pooled it
- Radiologic-pathologic discrepancy in the tumor size assessment of pancreatic ductal adenocarcinoma in the era of preoperative therapy.Surgery today · 2026Review
- Development and validation of machine learning models integrating spectral computed tomography-derived three-dimensional quantitative parameters for predicting histopathological grade in pancreatic ductal adenocarcinoma.Journal of gastrointestinal oncology · 2026Article
- Radiogenomic landscape of the hallmarks of cancer.Biomarker research · 2026Review
- Advancements in Radiomics-Based AI for Pancreatic Ductal Adenocarcinoma.Bioengineering (Basel, Switzerland) · 2025Review
- Radiomics analysis of dual-layer detector spectral CT-derived iodine maps for predicting Ki-67 PI in pancreatic ductal adenocarcinoma.BMC medical imaging · 2025Article
- From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non-Invasive Precision Medicine in Cancer Patients.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Radiomics in sporadic microsatellite instable, mismatch repair deficient and Lynch syndrome-associated pancreatic ductal adenocarcinoma: a pilot study.Frontiers in oncology · 2025Article
- Identification of SMAD4-mutated pancreatic ductal adenocarcinoma using preoperative contrast-enhanced MRI and clinical characteristics.BMC medical imaging · 2024Article
- Development and validation of a model based on preoperative dual-layer detector spectral computed tomography 3D VOI-based quantitative parameters to predict high Ki-67 proliferation index in pancreatic ductal adenocarcinoma.Insights into imaging · 2024Article
- Multi-parametric atlas of the pre-metastatic liver for prediction of metastatic outcome in early-stage pancreatic cancer.Nature medicine · 2024Article
- Development of a CT radiomics nomogram for preoperative prediction of Ki-67 index in pancreatic ductal adenocarcinoma: a two-center retrospective study.European radiology · 2024Article
- Development of Clinical Radiomics-Based Models to Predict Survival Outcome in Pancreatic Ductal Adenocarcinoma: A Multicenter Retrospective Study.Diagnostics (Basel, Switzerland) · 2024Article
- Feasibility and effectiveness of automatic deep learning network and radiomics models for differentiating tumor stroma ratio in pancreatic ductal adenocarcinoma.Insights into imaging · 2023Article
- Virtual biopsy in abdominal pathology: where do we stand?BJR open · 2023Review
- CT Radiomics and Whole Genome Sequencing in Patients with Pancreatic Ductal Adenocarcinoma: Predictive Radiogenomics Modeling.Cancers · 2022Article
- Machine learning with imaging features to predict the expression of ITGAV, which is a poor prognostic factor derived from transcriptome analysis in pancreatic cancer.International journal of oncology · 2022Article
- Review
- ImaGene: a web-based software platform for tumor radiogenomic evaluation and reporting.Bioinformatics advances · 2022Article
- Radiogenomics of gastroenterological cancer: The dawn of personalized medicine with artificial intelligence-based image analysis.Annals of gastroenterological surgery · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
Abstract
purposeThe aim of this study was to investigate the relationship between CT imaging phenotypes and genetic and biological characteristics in pancreatic ductal adenocarcinoma (PDAC).
methodsIn this retrospective study, consecutive patients between April 2015 and June 2016 who underwent PDAC resection were included if previously consented to a targeted sequencing protocol. Mutation status of known PDAC driver genes (KRAS, TP53, CDKN2A, and SMAD4) in the primary tumor was determined by targeted DNA sequencing and results were validated by immunohistochemistry (IHC). Radiomic features of the tumor were extracted from the preoperative CT scan and used to predict genotype and stromal content.
resultsThe cohort for analysis consisted of 35 patients. Genomic and IHC analysis revealed alterations in KRAS in 34 (97%) patients, and changes in expression of CDKN2A in 29 (83%), SMAD4 in 16 (46%), and in TP53 in 29 (83%) patients. Models created from radiomic features demonstrated associations with SMAD4 status and the number of genes altered. The number of genes altered was the only significant predictor of overall survival (p = 0.016). By linear regression analysis, a prediction model for stromal content achieved an R
conclusionsIn this study, we demonstrate that in PDAC SMAD4 status and tumor stromal content can be predicted using radiomic analysis of preoperative CT imaging. These data show an association between resectable PDAC imaging features and underlying tumor biology and their potential for future precision medicine.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.