SynthesisLa Radiologia medica2024
Delta radiomics: an updated systematic review.
Synthesis in La Radiologia medica, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
51 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Imaging-based 3D-printed anatomical models for preoperative planning in hepatopancreatobiliary surgery: a single-center pilot study, cost analysis, and systematic review.La Radiologia medica · 2026Pooled it
- Insights into pet-based radiogenomics in oncology: an updated systematic review.European journal of nuclear medicine and molecular imaging · 2025Pooled it
- Application of delta radiomics based on cone-beam computed tomography in predicting radiotherapy efficacy for nasopharyngeal carcinoma.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026Article
- Application advances of habitat imaging based on CT or PET/CT: a systematic review.La Radiologia medica · 2026Review
- Early Prediction of Volumetric Progression in Sellar-Parasellar Meningiomas Using Delta Radiomics on 6-Month MRI Following Gamma Knife Radiosurgery.Diagnostics (Basel, Switzerland) · 2026Article
- Applications of artificial intelligence in nuclear medicine.Zeitschrift fur medizinische Physik · 2026Review
- Development and validation of a multivariable CT-based Delta-radiomics model for predicting efficacy to bevacizumab therapy in patients with colorectal liver metastases.Translational cancer research · 2026Article
- Interpretable dynamic quantitative vascular morphometry features using SHAP for anti-angiogenic therapy response prediction.Science advances · 2026Article
- Why Radiomics Rarely Reaches the Clinic: Reproducibility, Validation, and Evidence Gap-A Critical Narrative Review.Diagnostics (Basel, Switzerland) · 2026Review
- Delta radiomics for predicting early radiation-induced lung injury after thoracic radiotherapy: a retrospective paired-CT study.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026Article
- MRI-Based DeltaHabitat Radiomic Model Predicts Pathological Complete Response in Oral Cavity Cancer Treated With Neoadjuvant Chemoimmunotherapy.Cancer medicine · 2026Article
- CT-Based Radiomics in the Characterization of Solid Renal Tumors: A Systematic Review.Cancers · 2026Review
- Leveraging the non-contrast CT component of PET/CT: an AI-driven delta-radiomics approach to monitor treatment response in metastatic breast cancer.BMC medical imaging · 2026Article
- Therapy-induced tumor regression heterogeneity for early prediction of response and prognosis in HER2-positive breast cancer.BMC medical imaging · 2026Article
- Habitat analysis and other AI technologies for Ki-67 prediction in hepatocellular carcinoma: a multi-center study.BMC cancer · 2026Article
- Radiogenomic landscape of the hallmarks of cancer.Biomarker research · 2026Review
- Multimodal radiomics for early prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer: integration of amide proton transfer weighted imaging in radiomics.BMC medical imaging · 2026Article
- Radiomics of portal-phase ring enhancement: a novel imaging biomarker for bevacizumab response associated with overall survival rates. It might help with surgical decision-making in colorectal liver metastases?Updates in surgery · 2026Article
- Multimodal radiomics for precision management of colorectal cancer.Discover oncology · 2026Review
- Rectal Cancer Radiotherapy Response Prediction: Retrospective Study of Development of a Deep Learning-Based Radiomics Model.JMIR medical informatics · 2026Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRadiomics can provide quantitative features from medical imaging that can be correlated with various biological features and diverse clinical endpoints. Delta radiomics, on the other hand, consists in the analysis of feature variation at different acquisition time points, usually before and after therapy. The aim of this study was to provide a systematic review of the different delta radiomics approaches.
methodsEligible articles were searched in Embase, Pubmed, and ScienceDirect using a search string that included free text and/or Medical Subject Headings (MeSH) with 3 key search terms: 'radiomics,' 'texture,' and 'delta.' Studies were analyzed using QUADAS-2 and the RQS tool.
resultsForty-eight studies were finally included. The studies were divided into preclinical/methodological (5 studies, 10.4%); rectal cancer (6 studies, 12.5%); lung cancer (12 studies, 25%); sarcoma (5 studies, 10.4%); prostate cancer (3 studies, 6.3%), head and neck cancer (6 studies, 12.5%); gastrointestinal malignancies excluding rectum (7 studies, 14.6%) and other disease sites (4 studies, 8.3%). The median RQS of all studies was 25% (mean 21% ± 12%), with 13 studies (30.2%) achieving a quality score < 10% and 22 studies (51.2%) < 25%.
conclusionsDelta radiomics shows potential benefit for several clinical endpoints in oncology, such asdifferential diagnosis, prognosis and prediction of treatment response, evaluation of side effects. Nevertheless, the studies included in this systematic review suffer from the bias of overall low methodological rigor, so that the conclusions are currently heterogeneous, not robust and hardly replicable. Further research with prospective and multicenter studies is needed for the clinical validation of delta radiomics approaches.
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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.