ReviewInvestigative radiology2020
Variability and Standardization of Quantitative Imaging: Monoparametric to Multiparametric Quantification, Radiomics, and Artificial Intelligence.
Review in Investigative radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers, 5 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
90 citing papers in PubMed, 5 syntheses or guidelines pooled it, 168 citations in OpenAlex.
- Magnetic Resonance Imaging-Based Artificial Intelligence in Predicting Prostate Cancer Biochemical Recurrence: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Comparative diagnostic performance of [68 Ga]Ga-FAPI PET/CT and [18 F]FDGPET/CT in biliary tract cancers: a systematic review and meta-analysis.European journal of nuclear medicine and molecular imaging · 2025Pooled it
- Left atrial volume quantification by transthoracic echocardiography versus cardiovascular magnetic resonance: a systematic review and meta-analysis.The international journal of cardiovascular imaging · 2025Pooled it
- Artificial intelligence in estimating fractional flow reserve: a systematic literature review of techniques.BMC cardiovascular disorders · 2023Pooled it
- Radiomic Analysis of MRI for Assessing Response to Neoadjuvant Chemoradiotherapy in Rectal Adenocarcinoma: A Systematic Review and Metaanalysis.Molecular imagingPooled it
- Development and validation of a deep learning signature for predicting lymph node metastasis in lung adenocarcinoma: comparison with radiomics signature and clinical-semantic model.European radiology · 2023Trial
- Recent advances in MR neuroimaging: toward quantitative and AI-driven brain and spinal cord imaging.Japanese journal of radiology · 2026Review
- Subclinical inflammation and early pathogenesis of rheumatic diseases: mechanistic insights relevant to primary care.Irish journal of medical science · 2026Review
- Artificial Intelligence for Detection and Characterisation of Bone Metastases on MRI: A Scoping Review.Cancers · 2026Review
- 3D Freehand Ultrasound Imaging of Optic Nerve Sheath.Investigative radiology · 2026Article
- Article
- Quantitative Permeability MRI for Preoperative Differentiation of Warthin Tumors and Malignant Salivary Gland Lesions.Diagnostics (Basel, Switzerland) · 2026Article
- Real-World Imaging Data: Opportunities and Challenges.JMIR medical informatics · 2026Article
- TRAECR: A Tool for Preprocessing Positron Emission Tomography Imaging for Statistical Modeling.ArXiv · 2026Article
- Design and Preliminary Phantom Study of a 3D-Printed Wrist Immobilization Device for Lateral Radiography.Diagnostics (Basel, Switzerland) · 2026Article
- CT-Based Three-Dimensional Volumetric Analysis of Posterior and Lateral Malleolar Fragments in SER-Type Trimalleolar Ankle Fractures: Correlation and Reproducibility Study.Tomography (Ann Arbor, Mich.) · 2026Article
- Data-Driven Characterization of Knee Structures Using Non-Negative Matrix Factorization of 3D Multi-Echo UTE MRI.NMR in biomedicine · 2026Article
- Review
- Contrast-Enhanced MR Fingerprinting With Delta-Relaxometry: Investigating a New Avenue for Tumor Characterization.Journal of magnetic resonance imaging : JMRI · 2026Observational
- Artificial Intelligence and CT Neuroimaging in Dementia and Psychotic Disorders: A Viewpoint.Journal of imaging informatics in medicine · 2026Review
30 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Radiological images have been assessed qualitatively in most clinical settings by the expert eyes of radiologists and other clinicians. On the other hand, quantification of radiological images has the potential to detect early disease that may be difficult to detect with human eyes, complement or replace biopsy, and provide clear differentiation of disease stage. Further, objective assessment by quantification is a prerequisite of personalized/precision medicine. This review article aims to summarize and discuss how the variability of quantitative values derived from radiological images are induced by a number of factors and how these variabilities are mitigated and standardization of the quantitative values are achieved. We discuss the variabilities of specific biomarkers derived from magnetic resonance imaging and computed tomography, and focus on diffusion-weighted imaging, relaxometry, lung density evaluation, and computer-aided computed tomography volumetry. We also review the sources of variability and current efforts of standardization of the rapidly evolving techniques, which include radiomics and artificial intelligence.
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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.