ArticleInsights into imaging2022
Standardised lesion segmentation for imaging biomarker quantitation: a consensus recommendation from ESR and EORTC.
Article in Insights into imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Image Quality Standardization in Radiomics: A Systematic Review of Artifacts, Variability, and Feature Stability.Sensors (Basel, Switzerland) · 2026Pooled it
- Regional ventricular enlargement as an in vivo biomarker of cumulative biomechanical neurodegeneration in former American football players.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Why Radiomics Rarely Reaches the Clinic: Reproducibility, Validation, and Evidence Gap-A Critical Narrative Review.Diagnostics (Basel, Switzerland) · 2026Review
- Based on a radiomics-clinical nomogram to predict the therapeutic effect of pulmonary cryptococcosis pneumonia.Scientific reports · 2026Article
- Clinically aligned whole-body MRI segmentation of skeletal metastases via Supervised Anatomical Pretraining.Journal of bone oncology · 2026Article
- Artificial intelligence for clinical trial design, conduct, and analysis: a narrative review.ESMO real world data and digital oncology · 2026Review
- Pulmonary contusion volume and radiomics as predictors of early-onset pneumonia in trauma patients, a retrospective single-centre study.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2025Observational
- Advancing deep learning-based segmentation for multiple lung cancer lesions in real-world multicenter CT scans.European radiology experimental · 2025Article
- Defining ground truth for prostate segmentation of transrectal ultrasound images: Inter- and intra-observer variability of manual versus semi-automatic methods.Medical physics · 2025Article
- Robustness of radiomics within photon-counting detector CT: impact of acquisition and reconstruction factors.European radiology · 2025Article
- Color-map recommendation for MR relaxometry maps.Magnetic resonance in medicine · 2025Article
- The QIBA Profile for Diffusion-Weighted MRI: Apparent Diffusion Coefficient as a Quantitative Imaging Biomarker.Radiology · 2024Review
- Imaging biomarkers and radiomics in pediatric oncology: a view from the PRIMAGE (PRedictive In silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers) project.Pediatric radiology · 2024Review
- METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII.Insights into imaging · 2024Article
- Quantitative diffusion-weighted MRI response assessment in rhabdomyosarcoma: an international retrospective study on behalf of the European paediatric Soft tissue sarcoma Study Group Imaging Committee.Pediatric radiology · 2023Article
- Advanced MR Techniques for Preoperative Glioma Characterization: Part 1.Journal of magnetic resonance imaging : JMRI · 2023Review
- Independent Validation of a Deep Learning nnU-Net Tool for Neuroblastoma Detection and Segmentation in MR Images.Cancers · 2023Article
Corrections and comments
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Authors and funding
30 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLesion/tissue segmentation on digital medical images enables biomarker extraction, image-guided therapy delivery, treatment response measurement, and training/validation for developing artificial intelligence algorithms and workflows. To ensure data reproducibility, criteria for standardised segmentation are critical but currently unavailable.
methodsA modified Delphi process initiated by the European Imaging Biomarker Alliance (EIBALL) of the European Society of Radiology (ESR) and the European Organisation for Research and Treatment of Cancer (EORTC) Imaging Group was undertaken. Three multidisciplinary task forces addressed modality and image acquisition, segmentation methodology itself, and standards and logistics. Devised survey questions were fed via a facilitator to expert participants. The 58 respondents to Round 1 were invited to participate in Rounds 2-4. Subsequent rounds were informed by responses of previous rounds. RESULTS/
conclusionsItems with ≥ 75% consensus are considered a recommendation. These include system performance certification, thresholds for image signal-to-noise, contrast-to-noise and tumour-to-background ratios, spatial resolution, and artefact levels. Direct, iterative, and machine or deep learning reconstruction methods, use of a mixture of CE marked and verified research tools were agreed and use of specified reference standards and validation processes considered essential. Operator training and refreshment were considered mandatory for clinical trials and clinical research. Items with a 60-74% agreement require reporting (site-specific accreditation for clinical research, minimal pixel number within lesion segmented, use of post-reconstruction algorithms, operator training refreshment for clinical practice). Items with ≤ 60% agreement are outside current recommendations for segmentation (frequency of system performance tests, use of only CE-marked tools, board certification of operators, frequency of operator refresher training). Recommendations by anatomical area are also specified.
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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.