Artificial intelligence to improve cytology performance in urothelial carcinoma diagnosis: results from validation phase of the French, multicenter, prospective VISIOCYT1 trial.
Artificial intelligence
Bladder
Cancer
Deep learning
Markers
Urothelial
Journal
World journal of urology
ISSN: 1433-8726
Titre abrégé: World J Urol
Pays: Germany
ID NLM: 8307716
Informations de publication
Date de publication:
Sep 2023
Sep 2023
Historique:
received:
22
03
2023
accepted:
01
07
2023
medline:
31
8
2023
pubmed:
22
7
2023
entrez:
22
7
2023
Statut:
ppublish
Résumé
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 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 Between October 2017 and December 2019, 391 participants (170 in Group 1 and 149 in Group 2) were enrolled. VisioCyt VisioCyt
Identifiants
pubmed: 37480491
doi: 10.1007/s00345-023-04519-4
pii: 10.1007/s00345-023-04519-4
pmc: PMC10465399
doi:
Types de publication
Multicenter Study
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2381-2388Informations de copyright
© 2023. The Author(s).
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