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Differentiation of renal masses with multi-parametric MRI: the de Silva St George classification scheme
PURPOSE: To 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. METHODS: This is a retrospective analysis of patients who underwent 3 Tesla mpMRI for further assessme...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441035/ https://www.ncbi.nlm.nih.gov/pubmed/36057604 http://dx.doi.org/10.1186/s12894-022-01082-9 |
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author | de Silva, Suresh Lockhart, Kathleen R. Aslan, Peter Nash, Peter Hutton, Anthony Malouf, David Lee, Dominic Cozzi, Paul MacLean, Fiona Thompson, James |
author_facet | de Silva, Suresh Lockhart, Kathleen R. Aslan, Peter Nash, Peter Hutton, Anthony Malouf, David Lee, Dominic Cozzi, Paul MacLean, Fiona Thompson, James |
author_sort | de Silva, Suresh |
collection | PubMed |
description | PURPOSE: To 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. METHODS: This 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. RESULTS: 67 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. CONCLUSION: The 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12894-022-01082-9. |
format | Online Article Text |
id | pubmed-9441035 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-94410352022-09-05 Differentiation of renal masses with multi-parametric MRI: the de Silva St George classification scheme de Silva, Suresh Lockhart, Kathleen R. Aslan, Peter Nash, Peter Hutton, Anthony Malouf, David Lee, Dominic Cozzi, Paul MacLean, Fiona Thompson, James BMC Urol Research PURPOSE: To 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. METHODS: This 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. RESULTS: 67 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. CONCLUSION: The 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12894-022-01082-9. BioMed Central 2022-09-03 /pmc/articles/PMC9441035/ /pubmed/36057604 http://dx.doi.org/10.1186/s12894-022-01082-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research de Silva, Suresh Lockhart, Kathleen R. Aslan, Peter Nash, Peter Hutton, Anthony Malouf, David Lee, Dominic Cozzi, Paul MacLean, Fiona Thompson, James Differentiation of renal masses with multi-parametric MRI: the de Silva St George classification scheme |
title | Differentiation of renal masses with multi-parametric MRI: the de Silva St George classification scheme |
title_full | Differentiation of renal masses with multi-parametric MRI: the de Silva St George classification scheme |
title_fullStr | Differentiation of renal masses with multi-parametric MRI: the de Silva St George classification scheme |
title_full_unstemmed | Differentiation of renal masses with multi-parametric MRI: the de Silva St George classification scheme |
title_short | Differentiation of renal masses with multi-parametric MRI: the de Silva St George classification scheme |
title_sort | differentiation of renal masses with multi-parametric mri: the de silva st george classification scheme |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441035/ https://www.ncbi.nlm.nih.gov/pubmed/36057604 http://dx.doi.org/10.1186/s12894-022-01082-9 |
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