1. Artificial intelligence to improve cytology performances in bladder carcinoma detection: results of the VisioCyt test
- Author
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Camelia Radulescu, Laurent Guy, Sebastien Nivet, Géraldine Pignot, E. Piaton, Mathieu Roumigue, Thierry Lebret, Marc Colombel, Monique Coutade Saidi, Xavier Rebillard, Laurent Savareux, Imagerie Moléculaire et Stratégies Théranostiques (IMoST), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Clermont Auvergne (UCA), CHU Gabriel Montpied [Clermont-Ferrand], CHU Clermont-Ferrand, Hôpital Foch [Suresnes], Université de Versailles Saint-Quentin-en-Yvelines - UFR Sciences de la santé Simone Veil (UVSQ Santé), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC), Hospices Civils de Lyon (HCL), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon, Clinique Médicale Beausoleil, Institut Universitaire du Cancer de Toulouse - Oncopole (IUCT Oncopole - UMR 1037), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Groupement Hospitalier Lyon-Est (GHE)
- Subjects
medicine.diagnostic_test ,business.industry ,Urology ,[SDV]Life Sciences [q-bio] ,030232 urology & nephrology ,Negative control ,Test sensitivity ,Cystoscopy ,medicine.disease ,3. Good health ,Test (assessment) ,03 medical and health sciences ,0302 clinical medicine ,030220 oncology & carcinogenesis ,Cytology ,Bladder tumours ,Carcinoma ,Medicine ,Histological grades ,Artificial intelligence ,business ,ComputingMilieux_MISCELLANEOUS ,Urine cytology - Abstract
Introduction Voided urine cytology is a non-invasive method for diagnosing and following up on bladder carcinoma. But this exam suffers from low sensitivity and a lack of reproducibility due to pathologist examiner dependency, especially in low-grade tumours. Cystoscopy is chosen as the gold-standard exam, although it is considered aggressive by patients, especially when it is repeated. The aim of this study is to explore artificial intelligence (AI) to improve voided cytology. Material and method A national prospective multicentre trial (14 centres) was conducted on 1,360 patients, divided in two groups. The first group included bladder carcinoma diagnosis with different histological grades and stages, and the second group included control patients based on negative cystoscopy and cytology results. The first step of this VISIOCYT1 trial focused on algorithm development and the second step on validating this algorithm. A total of 598 patients were included in this first step, 449 patients with bladder tumours (219 high-grade and 230 low-grade) and 149 as negative control. The VisioCyt test was compared to voided urine cytology performed by experienced uro-pathologists from each centre. Results Overall sensitivity was highly improved by the VisioCyt test compared to cytology, respectively 84.9% vs. 43%. For high-grade tumours, VisioCyt test sensitivity was 92.6% compared to 61.1% for uro-pathologists. Regarding low-grade tumours, VisioCyt test sensitivity was 77% versus 26.3% for uro-pathologists. Conclusion Compared to routine cytology, the first phase of VISIOCYT1 results shows very clear progress in term of sensitivity. It is particularly visible and interesting for low-grade tumours. If the validation cohort confirms these results, it could lead to the VisioCyt test being considered as a very useful aid for pathologists. Moreover, as this test is in fact software based on artificial intelligence, it should become more and more efficient as more data is collected.
- Published
- 2021
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