ArticleRadiation oncology (London, England)2021
Delta radiomics analysis of Magnetic Resonance guided radiotherapy imaging data can enable treatment response prediction in pancreatic cancer.
Article in Radiation oncology (London, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses 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
27 citing papers in PubMed, 2 syntheses or guidelines pooled it, 42 citations in OpenAlex.
- Delta radiomics: an updated systematic review.La Radiologia medica · 2024Pooled it
- Artificial intelligence applied to image-guided radiation therapy (IGRT): a systematic review by the Young Group of the Italian Association of Radiotherapy and Clinical Oncology (yAIRO).La Radiologia medica · 2024Pooled it
- Longitudinal radiomics of liver metastases during magnetic resonance-guided radiotherapy.Physics and imaging in radiation oncology · 2026Article
- MRI- and report-based multimodal model with SHAP-based explanation for preoperative prediction of deep stromal invasion in early-stage cervical cancer.Insights into imaging · 2026Article
- Noninvasive evaluation and clinical value prediction of tumor-infiltrating neutrophil-to-T-cell ratio in pancreatic ductal adenocarcinoma.NPJ digital medicine · 2026Article
- Clinical Applications of Quantitative Imaging and Artificial Intelligence for Pancreatic Cance.Seminars in radiation oncology · 2025Review
- Critical review of patient outcome study in head and neck cancer radiotherapy.Meta-radiology · 2025Article
- Article
- MR-linac: role of artificial intelligence and automation.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2025Review
- Delta-Radiomics Using Machine Learning Classifiers With Auxiliary Data Sets to Predict Disease Progression During Magnetic Resonance-Guided Radiotherapy in Adrenal Metastases.JCO clinical cancer informatics · 2025Article
- Recent technical advancements and clinical applications of MR-guided radiotherapy in lung cancer treatment.Frontiers in oncology · 2025Review
- Radiomics in radiology: What the radiologist needs to know about technical aspects and clinical impact.La Radiologia medica · 2024Review
- Magnetic Resonance-Guided Cancer Therapy Radiomics and Machine Learning Models for Response Prediction.Tomography (Ann Arbor, Mich.) · 2024Review
- Delta radiomics to track radiation response in lung tumors receiving stereotactic magnetic resonance-guided radiotherapy.Physics and imaging in radiation oncology · 2024Article
- Novel Functional Radiomics for Prediction of Cardiac Positron Emission Tomography Avidity in Lung Cancer Radiotherapy.JCO clinical cancer informatics · 2024Article
- Repeatability, reproducibility, and the effects of radiotherapy on radiomic features of lowfield MR-LINAC images of the prostate.Frontiers in oncology · 2024Article
- The Promise and Future of Radiomics for Personalized Radiotherapy Dosing and Adaptation.Seminars in radiation oncology · 2023Review
- Review
- Beyond diagnosis: is there a role for radiomics in prostate cancer management?European radiology experimental · 2023Review
- The progress of PET/MRI in clinical management of patients with pancreatic malignant lesions.Frontiers in oncology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundMagnetic Resonance Image guided Stereotactic body radiotherapy (MRgRT) is an emerging technology that is increasingly used in treatment of visceral cancers, such as pancreatic adenocarcinoma (PDAC). Given the variable response rates and short progression times of PDAC, there is an unmet clinical need for a method to assess early RT response that may allow better prescription personalization. We hypothesize that quantitative image feature analysis (radiomics) of the longitudinal MR scans acquired before and during MRgRT may be used to extract information related to early treatment response.
methodsHistogram and texture radiomic features (n = 73) were extracted from the Gross Tumor Volume (GTV) in 0.35T MRgRT scans of 26 locally advanced and borderline resectable PDAC patients treated with 50 Gy RT in 5 fractions. Feature ratios between first (F1) and last (F5) fraction scan were correlated with progression free survival (PFS). Feature stability was assessed through region of interest (ROI) perturbation.
resultsLinear normalization of image intensity to median kidney value showed improved reproducibility of feature quantification. Histogram skewness change during treatment showed significant association with PFS (p = 0.005, HR = 2.75), offering a potential predictive biomarker of RT response. Stability analyses revealed a wide distribution of feature sensitivities to ROI delineation and was able to identify features that were robust to variability in contouring.
conclusionsThis study presents a proof-of-concept for the use of quantitative image analysis in MRgRT for treatment response prediction and providing an analysis pipeline that can be utilized in future MRgRT radiomic studies.
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.