ArticleBMC urology2022
Differentiation of renal masses with multi-parametric MRI: the de Silva St George classification scheme.
Article in BMC urology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- A novel CT-based normalization strategy using lesion-to-spleen density ratios for renal mass characterization.Abdominal radiology (New York) · 2026Article
- Impact of tumor size and sex on diagnostic discrepancies in renal mass imaging.Scientific reports · 2025Article
- Feasibility and Reproducibility of T2 Mapping Compared with Diffusion-Weighted Imaging in Solid Renal Masses.Bioengineering (Basel, Switzerland) · 2024Article
- Artificial intelligence support in MR imaging of incidental renal masses: an early health technology assessment.European radiology · 2024Article
- Imaging modalities for characterising T1 renal tumours: A systematic review and meta-analysis of diagnostic accuracy.BJUI compass · 2024Review
- Scientific Status Quo of Small Renal Lesions: Diagnostic Assessment and Radiomics.Journal of clinical medicine · 2024Review
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo develop a system for multi-parametric MRI to differentiate benign from malignant solid renal masses and assess its accuracy compared to the gold standard of histopathological diagnosis.
methodsThis is a retrospective analysis of patients who underwent 3 Tesla mpMRI for further assessment of small renal tumours with specific scanning and reporting protocol incorporating T2 HASTE signal intensity, contrast enhancement ratios, apparent diffusion coefficient and presence of microscopic/macroscopic fat. All MRIs were reported prior to comparison with histopathologic diagnosis and a reporting scheme was developed. 2 × 2 contingency table analysis (sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV)), Fisher Exact test were used to assess the association between suspicion of malignancy on mpMRI and histopathology, and descriptive statistics were performed.
results67 patients were included over a 5-year period with a total of 75 renal masses. 70 masses were confirmed on histopathology (five had pathognomonic findings for angiomyolipomas; biopsy was therefore considered unethical, so these were included without histopathology). Three patients were excluded due to a non-diagnostic result, non-standardised imaging and one found to be an organising haematoma rather than a mass. Therefore 72 cases were included in analysis (in 64 patients, with seven patients having multiple tumours). Unless otherwise specified, all further statistics refer to individual tumours rather than patients. 52 (72.2%) were deemed 'suspicious or malignant' and 20 (27.8%) were deemed 'benign' on mpMRI. 51 cases (70.8%) had renal cell carcinoma confirmed. The sensitivity, NPV, specificity and PPV for MRI for detecting malignancy were 96.1%, 90%, 85.7% and 94.2% respectively, Fisher's exact test demonstrated p < 0.0001 for the association between suspicion of malignancy on MRI and histopathology.
conclusionThe de Silva St George classification scheme performed well in differentiating benign from malignant solid renal masses, and may be useful in predicting the likelihood of malignancy to determine the need for biopsy/excision. Further validation is required before this reporting system can be recommended for clinical use.
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