Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: de Silva, Suresh, Lockhart, Kathleen R., Aslan, Peter, Nash, Peter, Hutton, Anthony, Malouf, David, Lee, Dominic, Cozzi, Paul, MacLean, Fiona, Thompson, James
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
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
_version_ 1784782488895225856
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
work_keys_str_mv AT desilvasuresh differentiationofrenalmasseswithmultiparametricmrithedesilvastgeorgeclassificationscheme
AT lockhartkathleenr differentiationofrenalmasseswithmultiparametricmrithedesilvastgeorgeclassificationscheme
AT aslanpeter differentiationofrenalmasseswithmultiparametricmrithedesilvastgeorgeclassificationscheme
AT nashpeter differentiationofrenalmasseswithmultiparametricmrithedesilvastgeorgeclassificationscheme
AT huttonanthony differentiationofrenalmasseswithmultiparametricmrithedesilvastgeorgeclassificationscheme
AT maloufdavid differentiationofrenalmasseswithmultiparametricmrithedesilvastgeorgeclassificationscheme
AT leedominic differentiationofrenalmasseswithmultiparametricmrithedesilvastgeorgeclassificationscheme
AT cozzipaul differentiationofrenalmasseswithmultiparametricmrithedesilvastgeorgeclassificationscheme
AT macleanfiona differentiationofrenalmasseswithmultiparametricmrithedesilvastgeorgeclassificationscheme
AT thompsonjames differentiationofrenalmasseswithmultiparametricmrithedesilvastgeorgeclassificationscheme