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Multicenter Study
. 2023 Sep;41(9):2381-2388.
doi: 10.1007/s00345-023-04519-4. Epub 2023 Jul 22.

Artificial intelligence to improve cytology performance in urothelial carcinoma diagnosis: results from validation phase of the French, multicenter, prospective VISIOCYT1 trial

Thierry Lebret  1 , Xavier Paoletti  2   3 , Geraldine Pignot  4 , Mathieu Roumiguié  5 , Marc Colombel  6 , Laurent Savareux  7 , Grégory Verhoest  8 , Laurent Guy  9 , Jérome Rigaud  10 , Stéphane De Vergie  10 , Grégoire Poinas  11 , Stéphane Droupy  12 , François Kleinclauss  13 , Monique Courtade-Saïdi  14 , Eric Piaton  15 , Camelia Radulescu  16 , Nathalie Rioux-Leclercq  17 , Christine Kandel-Aznar  18 , Karine Renaudin  19   20 , Béatrix Cochand-Priollet  21 , Yves Allory  22   23 , Sébastien Nivet  24 , Morgan Rouprêt  25
Affiliations
Multicenter Study

Artificial intelligence to improve cytology performance in urothelial carcinoma diagnosis: results from validation phase of the French, multicenter, prospective VISIOCYT1 trial

Thierry Lebret et al. World J Urol. 2023 Sep.

Abstract

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.

Keywords: Artificial intelligence; Bladder; Cancer; Deep learning; Markers; Urothelial.

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Conflict of interest statement

Thierry Lebret declares receiving consulting fees, honoraria, and/or support for attending meetings from Astellas Pharma, Bayer, Bristol Myer Squibb, IPSEN, MSD, Roche, and VitaDX. Grégoire Poinas declares receiving support from VitaDX to conduct this study. Monique Courtade-Saïdi declares being the president of the French Society for Cytology and having received payment for expert testimony from VitaDX. Nathalie Rioux-Leclercq declares having received grants from INCa (the French National Cancer Institute), for a translational study and from the Nominoë Foundation to develop digital pathology at the CHU Rennes. Karine Renaudin declares having received payments from MSD. Béatrix Cochand-Priollet declares receiving support for attending meetings. Nivet declares having shares and being employed by VitaDX. Morgan Rouprêt declares having received consulting fees from Cepheid, OncoDiag, Astellas Pharma, Janssen, IPSEN, and VitaDX. All other authors have nothing to declare.

Figures

Fig. 1
Fig. 1
Patient flow diagram for the validation phase of the VISIOCYT1 trial
See this image and copyright information in PMC

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