ArticlePloS one2019
Computed tomography based radiomic signature as predictive of survival and local control after stereotactic body radiation therapy in pancreatic carcinoma.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06108310 (ATTRACT - ArTificial inTelligence-based RAdiogenomics in Colon Tumors), which is not on this map. Cited by 44 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.
ATTRACT - ArTificial inTelligence-based RAdiogenomics in Colon Tumors
Who cites it
44 citing papers in PubMed, 1 synthesis or guideline pooled it, 75 citations in OpenAlex.
- Pancreas image mining: a systematic review of radiomics.European radiology · 2021Pooled it
- CT-based vascular invasion in pancreatic ductal adenocarcinoma compared with intraoperative and histological findings.Insights into imaging · 2026Article
- Clinical Applications of Quantitative Imaging and Artificial Intelligence for Pancreatic Cance.Seminars in radiation oncology · 2025Review
- Advancements in Radiomics-Based AI for Pancreatic Ductal Adenocarcinoma.Bioengineering (Basel, Switzerland) · 2025Review
- An update on pancreatic cancer imaging, staging, and use of the PACT-UK radiology template pre- and post-neoadjuvant treatment.The British journal of radiology · 2025Review
- A nomogram-based radiomics for predicting survival to concurrent chemoradiotherapy in inoperable pancreatic cancer: a dual-center cohort study.Frontiers in immunology · 2025Article
- MDMU-Net: 3D multi-dimensional decoupled multi-scale U-Net for pancreatic cancer segmentation.PeerJ. Computer science · 2025Article
- Stereotactic body radiation therapy for the primary tumor and oligometastases versus the primary tumor alone in patients with metastatic pancreatic cancer.Radiation oncology (London, England) · 2024Article
- Understanding the Conundrum of Pancreatic Cancer in the Omics Sciences Era.International journal of molecular sciences · 2024Review
- Delta Radiomic Features Predict Resection Margin Status and Overall Survival in Neoadjuvant-Treated Pancreatic Cancer Patients.Annals of surgical oncology · 2024Article
- Radiomics in stereotactic body radiotherapy for non-small cell lung cancer: a systematic review and radiomic quality score study.Radiation oncology journal · 2024Article
- Artificial intelligence: clinical applications and future advancement in gastrointestinal cancers.Frontiers in artificial intelligence · 2024Review
- Radiomics analysis with three-dimensional and two-dimensional segmentation to predict survival outcomes in pancreatic cancer.World journal of radiology · 2023Article
- Selection of patients with pancreatic adenocarcinoma who may benefit from radiotherapy.Radiation oncology (London, England) · 2023Review
- Mathematical modeling of radiotherapy: impact of model selection on estimating minimum radiation dose for tumor control.Frontiers in oncology · 2023Article
- Comment on "Prognostic value of preoperative enhanced computed tomography as a quantitative imaging biomarker in pancreatic cancer".World journal of gastroenterology · 2022Article
- MRI-based delta-radiomic features for prediction of local control in liver lesions treated with stereotactic body radiation therapy.Scientific reports · 2022Article
- Multimodal survival prediction in advanced pancreatic cancer using machine learning.ESMO open · 2022Article
- Pancreatic cancer, radiomics and artificial intelligence.The British journal of radiology · 2022Review
- Setting the Research Agenda for Clinical Artificial Intelligence in Pancreatic Adenocarcinoma Imaging.Cancers · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo appraise the ability of a radiomics signature to predict clinical outcome after stereotactic body radiation therapy (SBRT) for pancreas carcinoma.
methodsA cohort of 100 patients was included in this retrospective, single institution analysis. Radiomics texture features were extracted from computed tomography (CT) images obtained for the clinical target volume. The cohort of patients was randomly divided into two separate groups for the training (60 patients) and validation (40 patients). Cox regression models were built to predict overall survival and local control. The significant predictors at univariate analysis were included in a multivariate model. The quality of the models was appraised by means of area under the curve and concordance index.
resultsA clinical-radiomic signature associated with Overall Survival (OS) was found significant in both training and validation sets (p = 0.01 and 0.05 and concordance index 0.73 and 0.75 respectively). Similarly, a signature was found for Local Control (LC) with p = 0.007 and 0.004 and concordance index 0.69 and 0.75. In the low risk group, the median OS and LC in the validation group were 14.4 and 28.6 months while in the high-risk group were 9.0 and 17.5 months respectively.
conclusionA CT based radiomic signature was identified which correlate with OS and LC after SBRT and allowed to identify low and high-risk groups of patients.
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.