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Artificial intelligence to improve cytology performance in urothelial carcinoma diagnosis: results from validation phase of the French, multicenter, prospective VISIOCYT1 trial
PURPOSE: Cytology and cystoscopy, the current gold standard for diagnosing urothelial carcinomas, have limits: cytology has high interobserver variability with moderate or not optimal sensitivity (particularly for low-grade tumors); while cystoscopy is expensive, invasive, and operator dependent. Th...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10465399/ https://www.ncbi.nlm.nih.gov/pubmed/37480491 http://dx.doi.org/10.1007/s00345-023-04519-4 |
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author | Lebret, Thierry Paoletti, Xavier Pignot, Geraldine Roumiguié, Mathieu Colombel, Marc Savareux, Laurent Verhoest, Grégory Guy, Laurent Rigaud, Jérome De Vergie, Stéphane Poinas, Grégoire Droupy, Stéphane Kleinclauss, François Courtade-Saïdi, Monique Piaton, Eric Radulescu, Camelia Rioux-Leclercq, Nathalie Kandel-Aznar, Christine Renaudin, Karine Cochand-Priollet, Béatrix Allory, Yves Nivet, Sébastien Rouprêt, Morgan |
author_facet | Lebret, Thierry Paoletti, Xavier Pignot, Geraldine Roumiguié, Mathieu Colombel, Marc Savareux, Laurent Verhoest, Grégory Guy, Laurent Rigaud, Jérome De Vergie, Stéphane Poinas, Grégoire Droupy, Stéphane Kleinclauss, François Courtade-Saïdi, Monique Piaton, Eric Radulescu, Camelia Rioux-Leclercq, Nathalie Kandel-Aznar, Christine Renaudin, Karine Cochand-Priollet, Béatrix Allory, Yves Nivet, Sébastien Rouprêt, Morgan |
author_sort | Lebret, Thierry |
collection | PubMed |
description | PURPOSE: Cytology and cystoscopy, the current gold standard for diagnosing urothelial carcinomas, have limits: cytology has high interobserver variability with moderate or not optimal sensitivity (particularly for low-grade tumors); while cystoscopy is expensive, invasive, and operator dependent. The VISIOCYT1 study assessed the benefit of VisioCyt(®) for diagnosing urothelial carcinoma. METHODS: VISIOCYT1 was a French prospective clinical trial conducted in 14 centers. The trial enrolled adults undergoing endoscopy for suspected bladder cancer or to explore the lower urinary tract. Participants were allocated either Group 1: with bladder cancer, i.e., with positive cystoscopy or with negative cystoscopy but positive cytology, or Group 2: without bladder cancer. Before cystoscopy and histopathology, slides were prepared for cytology and the VisioCyt(®) test from urine samples. The diagnostic performance of VisioCyt(®) was assessed using sensitivity (primary objective, 70% lower-bound threshold) and specificity (75% lower-bound threshold). Sensitivity was also assessed by tumor grade and T-staging. VisioCyt(®) and cytology performance were evaluated relative to the histopathological assessments. RESULTS: Between October 2017 and December 2019, 391 participants (170 in Group 1 and 149 in Group 2) were enrolled. VisioCyt(®)’s sensitivity was 80.9% (95% CI 73.9–86.4%) and specificity was 61.8% (95% CI 53.4–69.5%). In high-grade tumors, the sensitivity was 93.7% (95% CI 86.0–97.3%) and in low-grade tumors 66.7% (95% CI 55.2–76.5%). Sensitivity by T-staging, compared to the overall sensitivity, was higher in high-grade tumors and lower in low-grade tumors. CONCLUSION: VisioCyt(®) is a promising diagnostic tool for urothelial cancers with improved sensitivities for high-grade tumors and notably for low-grade tumors. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00345-023-04519-4. |
format | Online Article Text |
id | pubmed-10465399 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-104653992023-08-31 Artificial intelligence to improve cytology performance in urothelial carcinoma diagnosis: results from validation phase of the French, multicenter, prospective VISIOCYT1 trial Lebret, Thierry Paoletti, Xavier Pignot, Geraldine Roumiguié, Mathieu Colombel, Marc Savareux, Laurent Verhoest, Grégory Guy, Laurent Rigaud, Jérome De Vergie, Stéphane Poinas, Grégoire Droupy, Stéphane Kleinclauss, François Courtade-Saïdi, Monique Piaton, Eric Radulescu, Camelia Rioux-Leclercq, Nathalie Kandel-Aznar, Christine Renaudin, Karine Cochand-Priollet, Béatrix Allory, Yves Nivet, Sébastien Rouprêt, Morgan World J Urol Original Article PURPOSE: Cytology and cystoscopy, the current gold standard for diagnosing urothelial carcinomas, have limits: cytology has high interobserver variability with moderate or not optimal sensitivity (particularly for low-grade tumors); while cystoscopy is expensive, invasive, and operator dependent. The VISIOCYT1 study assessed the benefit of VisioCyt(®) for diagnosing urothelial carcinoma. METHODS: VISIOCYT1 was a French prospective clinical trial conducted in 14 centers. The trial enrolled adults undergoing endoscopy for suspected bladder cancer or to explore the lower urinary tract. Participants were allocated either Group 1: with bladder cancer, i.e., with positive cystoscopy or with negative cystoscopy but positive cytology, or Group 2: without bladder cancer. Before cystoscopy and histopathology, slides were prepared for cytology and the VisioCyt(®) test from urine samples. The diagnostic performance of VisioCyt(®) was assessed using sensitivity (primary objective, 70% lower-bound threshold) and specificity (75% lower-bound threshold). Sensitivity was also assessed by tumor grade and T-staging. VisioCyt(®) and cytology performance were evaluated relative to the histopathological assessments. RESULTS: Between October 2017 and December 2019, 391 participants (170 in Group 1 and 149 in Group 2) were enrolled. VisioCyt(®)’s sensitivity was 80.9% (95% CI 73.9–86.4%) and specificity was 61.8% (95% CI 53.4–69.5%). In high-grade tumors, the sensitivity was 93.7% (95% CI 86.0–97.3%) and in low-grade tumors 66.7% (95% CI 55.2–76.5%). Sensitivity by T-staging, compared to the overall sensitivity, was higher in high-grade tumors and lower in low-grade tumors. CONCLUSION: VisioCyt(®) is a promising diagnostic tool for urothelial cancers with improved sensitivities for high-grade tumors and notably for low-grade tumors. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00345-023-04519-4. Springer Berlin Heidelberg 2023-07-22 2023 /pmc/articles/PMC10465399/ /pubmed/37480491 http://dx.doi.org/10.1007/s00345-023-04519-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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/) . |
spellingShingle | Original Article Lebret, Thierry Paoletti, Xavier Pignot, Geraldine Roumiguié, Mathieu Colombel, Marc Savareux, Laurent Verhoest, Grégory Guy, Laurent Rigaud, Jérome De Vergie, Stéphane Poinas, Grégoire Droupy, Stéphane Kleinclauss, François Courtade-Saïdi, Monique Piaton, Eric Radulescu, Camelia Rioux-Leclercq, Nathalie Kandel-Aznar, Christine Renaudin, Karine Cochand-Priollet, Béatrix Allory, Yves Nivet, Sébastien Rouprêt, Morgan Artificial intelligence to improve cytology performance in urothelial carcinoma diagnosis: results from validation phase of the French, multicenter, prospective VISIOCYT1 trial |
title | Artificial intelligence to improve cytology performance in urothelial carcinoma diagnosis: results from validation phase of the French, multicenter, prospective VISIOCYT1 trial |
title_full | Artificial intelligence to improve cytology performance in urothelial carcinoma diagnosis: results from validation phase of the French, multicenter, prospective VISIOCYT1 trial |
title_fullStr | Artificial intelligence to improve cytology performance in urothelial carcinoma diagnosis: results from validation phase of the French, multicenter, prospective VISIOCYT1 trial |
title_full_unstemmed | Artificial intelligence to improve cytology performance in urothelial carcinoma diagnosis: results from validation phase of the French, multicenter, prospective VISIOCYT1 trial |
title_short | Artificial intelligence to improve cytology performance in urothelial carcinoma diagnosis: results from validation phase of the French, multicenter, prospective VISIOCYT1 trial |
title_sort | artificial intelligence to improve cytology performance in urothelial carcinoma diagnosis: results from validation phase of the french, multicenter, prospective visiocyt1 trial |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10465399/ https://www.ncbi.nlm.nih.gov/pubmed/37480491 http://dx.doi.org/10.1007/s00345-023-04519-4 |
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