SynthesisEuropean radiology2022
Diagnostic performance of MRI in detecting locally recurrent soft tissue sarcoma: systematic review and meta-analysis.
Synthesis in European radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 14 citations in OpenAlex.
- MRI of soft tissue tumours: a structured "8S framework" aligned with WHO 2020 classification.Skeletal radiology · 2026Review
- Article
- Intravoxel incoherent motion combined with conventional MRI for the differentiation of benign, intermediate, and malignant fibrous soft-tissue tumors.Frontiers in oncology · 2026Article
- Role of Dynamic Contrast-Enhanced MRI in Detecting Post-Treatment Local Recurrence of Soft-Tissue Sarcomas: A Systematic Review and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2026Review
- Spontaneous Muscle Bleeding During Oral Anticoagulation Therapy: When Should We Suspect an Underlying Tumor?Hematology reports · 2025Review
- Postoperative Imaging of Bone and Soft Tissue Tumors in the Extremity: A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2024Review
- An Exploratory Study: Can Native T1 Mapping Differentiate Sarcoma from Benign Soft Tissue Tumors at 1.5 T and 3 T?Cancers · 2024Article
- Impact of postoperative baseline MRI on diagnostic confidence and performance in detecting local recurrence of soft-tissue sarcoma of the limb.Skeletal radiology · 2023Article
- Diagnosis of Local Recurrence of Malignant Soft Tissue Tumors after Reconstructive Surgery on MRI.Journal of clinical medicine · 2023Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo systematically review the diagnostic criteria and performance of MRI in detecting locally recurrent soft tissue sarcoma.
methodsMedline and Embase were searched for original studies on the diagnostic performance of MRI detecting locally recurrent soft tissue sarcoma. Study quality was assessed using QUADAS-2. Sensitivity and specificity were pooled using a bivariate random-effects model.
resultsTen studies were included. There was a high risk of bias with respect to patient selection in 2 studies and a high risk of bias with respect to flow and timing in 8 studies. The presence of a mass yielded a pooled sensitivity of 80.9% and a pooled specificity of 77.0%. Hyperintensity at T2-weighted imaging yielded a pooled sensitivity of 82.4% and a pooled specificity of 11.0%. Hypo- or isointensity at T1-weighted imaging yielded a pooled sensitivity of 82.0% and a pooled specificity of 14.3%. Contrast enhancement images yielded a pooled sensitivity of 95.9% and a pooled specificity of 12.3%. Low signal mass on the apparent diffusion coefficient (ADC) map yielded a pooled sensitivity of 67.5% and a pooled specificity of 95.3%. Early and rapid arterial phase enhancement at dynamic contrast-enhanced (DCE) MRI yielded a pooled sensitivity of 91.3% and a pooled specificity of 84.7%.
conclusionThe presence of a mass appears a useful criterion to diagnose locally recurrent soft tissue sarcoma. Signal characteristics at standard T2- and T1-weighted imaging and contrast enhancement seem less useful because they lack specificity. Functional MRI techniques, including DWI with ADC mapping and DCE, may help to make a correct diagnosis. KEY POINTS: • The presence of a mass at MRI appears useful to diagnose locally recurrent soft tissue sarcoma, because both sensitivity and specificity are fairly high. • Signal characteristics at standard T2- and T1-weighted sequences and contrast enhancement suffer from poor specificity. • DWI with ADC mapping and DCE may help to make a correct diagnosis, but further research is needed to better understand the value of these functional MRI techniques.
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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.