SynthesisEuropean radiology2018
ADC as a useful diagnostic tool for differentiating benign and malignant vertebral bone marrow lesions and compression fractures: a systematic review and meta-analysis.
Synthesis in European radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 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
32 citing papers in PubMed, 2 syntheses or guidelines pooled it, 60 citations in OpenAlex.
- Diagnostic performance of apparent diffusion coefficient (ADC) for differentiating endometrial carcinoma from benign lesions: a systematic review and meta-analysis.Abdominal radiology (New York) · 2021Pooled it
- Diagnostic Performance of Diffusion-Weighted Imaging for Differentiating Malignant From Benign Intraductal Papillary Mucinous Neoplasms of the Pancreas: A Systematic Review and Meta-Analysis.Frontiers in oncology · 2021Pooled it
- Diffusion-Weighted Imaging in the Musculoskeletal System: Evolving Role in Modern Imaging Practice.Diagnostics (Basel, Switzerland) · 2026Review
- Qualitative and Quantitative Inter-Observer Agreement of Multiparametric Whole-Body MRI in Staging and Follow-Up of Myeloma Patients.Diagnostics (Basel, Switzerland) · 2025Article
- Whole-Body Magnetic Resonance Neurography-Technique, Current Perspectives, and Future Directions.Magnetic resonance imaging clinics of North America · 2025Review
- Review
- Review of whole-body magnetic resonance imaging in multiple myeloma.Japanese journal of radiology · 2024Review
- Multiparametric quantification of T1 and T2 relaxation time of bone metastasis in comparison with red or fatty bone marrow using magnetic resonance fingerprinting.Skeletal radiology · 2024Article
- Neoplastic and Non-Neoplastic Vertebral Marrow Pathologies: Can the Conventional and Advanced MRI Sequences Provide a Definitive Answer?The Indian journal of radiology & imaging · 2023Article
- A 3D Radiomics-Based Artificial Neural Network Model for Benign Versus Malignant Vertebral Compression Fracture Classification in MRI.Journal of digital imaging · 2023Article
- Application of Machine Learning for Differentiating Bone Malignancy on Imaging: A Systematic Review.Cancers · 2023Review
- Imaging of bone marrow pitfalls with emphasis on MRI.The British journal of radiology · 2023Review
- Advances in Bone Marrow Imaging: Strengths and Limitations from a Clinical Perspective.Seminars in musculoskeletal radiology · 2023Article
- Deep learning-based artificial intelligence model for classification of vertebral compression fractures: A multicenter diagnostic study.Frontiers in endocrinology · 2023Article
- Apparent diffusion coefficient values in Modic changes - interobserver reproducibility and relation to Modic type.BMC musculoskeletal disorders · 2022Article
- Diffusion-Weighted Magnetic Resonance Imaging: Clinical Potential and Applications.Journal of clinical medicine · 2022Article
- Diffusion-weighted MRI radiomics of spine bone tumors: feature stability and machine learning-based classification performance.La Radiologia medica · 2022Article
- Review of diffusion-weighted imaging and dynamic contrast-enhanced MRI for multiple myeloma and its precursors (monoclonal gammopathy of undetermined significance and smouldering myeloma).Skeletal radiology · 2022Review
- Whole-body magnetic resonance imaging (WBMRI) versus whole-body computed tomography (WBCT) for myeloma imaging and staging.Skeletal radiology · 2022Review
- Diagnostic Accuracy of Quantitative Imaging Biomarkers in the Differentiation of Benign and Malignant Vertebral Lesions : Combination of Diffusion-Weighted and Proton Density Fat Fraction Spine MRI.Clinical neuroradiology · 2021Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo assess the sensitivity and specificity of quantitative assessment of the apparent diffusion coefficient (ADC) for differentiating benign and malignant vertebral bone marrow lesions (BMLs) and compression fractures (CFs)
methodsAn electronic literature search of MEDLINE and EMBASE was conducted. Bivariate modelling and hierarchical summary receiver operating characteristic modelling were performed to evaluate the diagnostic performance of ADC for differentiating vertebral BMLs. Subgroup analysis was performed for differentiating benign and malignant vertebral CFs. Meta-regression analyses according to subject, study and diffusion-weighted imaging (DWI) characteristics were performed.
resultsTwelve eligible studies (748 lesions, 661 patients) were included. The ADC exhibited a pooled sensitivity of 0.89 (95% confidence interval [CI] 0.80-0.94) and a pooled specificity of 0.87 (95% CI 0.78-0.93) for differentiating benign and malignant vertebral BMLs. In addition, the pooled sensitivity and specificity for differentiating benign and malignant CFs were 0.92 (95% CI 0.82-0.97) and 0.91 (95% CI 0.87-0.94), respectively. In the meta-regression analysis, the DWI slice thickness was a significant factor affecting heterogeneity (p < 0.01); thinner slice thickness (< 5 mm) showed higher specificity (95%) than thicker slice thickness (81%).
conclusionsQuantitative assessment of ADC is a useful diagnostic tool for differentiating benign and malignant vertebral BMLs and CFs. KEY POINTS: • Quantitative assessment of ADC is useful in differentiating vertebral BMLs. • Quantitative ADC assessment for BMLs had sensitivity of 89%, specificity of 87%. • Quantitative ADC assessment for CFs had sensitivity of 92%, specificity of 91%. • The specificity is highest (95%) with thinner (< 5 mm) DWI slice thickness.
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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.