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06.03.2022 | Topic Paper

External validation of the computerized analysis of TRUS of the prostate with the ANNA/C-TRUS system: a potential role of artificial intelligence for improving prostate cancer detection

verfasst von: Vito Lorusso, Boukary Kabre, Geraldine Pignot, Nicolas Branger, Andrea Pacchetti, Jeanne Thomassin-Piana, Serge Brunelle, Nicola Nicolai, Gennaro Musi, Naji Salem, Emanuele Montanari, Ottavio de Cobelli, Gwenaelle Gravis, Jochen Walz

Erschienen in: World Journal of Urology | Ausgabe 3/2023

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Abstract

Purpose

Prostate cancer (PCa) imaging has been revolutionized by the introduction of multi-parametric Magnetic Resonance Imaging (mpMRI). Transrectal ultrasound (TRUS) has always been considered a low-performance modality. To overcome this, a computerized artificial neural network analysis (ANNA/C–TRUS) of the TRUS based on an artificial intelligence (AI) analysis has been proposed. Our aim was to evaluate the diagnostic performance of the ANNA/C-TRUS system and its ability to improve conventional TRUS in PCa diagnosis.

Methods

We retrospectively analyzed data from 64 patients with PCa and scheduled for radical prostatectomy who underwent TRUS followed by ANNA/C-TRUS analysis before the procedure. The results of ANNA/C-TRUS analysis with whole mount sections from final pathology.

Results

On a per-sectors analysis, sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV) and accuracy were 62%, 81%, 80%, 64% and 78% respectively. The values for the detection of clinically significant prostate cancer were 69%, 77%, 88%, 50% and 75%. The diagnostic values for high grade tumours were 70%, 74%, 91%, 41% and 74%, respectively. Cancer volume (≤ 0.5 or greater) did not influence the diagnostic performance of the ANNA/C-TRUS system.

Conclusions

ANNA/C-TRUS represents a promising diagnostic tool and application of AI for PCa diagnosis. It improves the ability of conventional TRUS to diagnose prostate cancer, preserving its simplicity and availability. Since it is an AI system, it does not hold the inter-observer variability nor a learning curve. Multicenter biopsy-based studies with the inclusion of an adequate number of patients are needed to confirm these results.

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Titel: External validation of the computerized analysis of TRUS of the prostate with the ANNA/C-TRUS system: a potential role of artificial intelligence for improving prostate cancer detection
verfasst von: Vito Lorusso
Boukary Kabre
Geraldine Pignot
Nicolas Branger
Andrea Pacchetti
Jeanne Thomassin-Piana
Serge Brunelle
Nicola Nicolai
Gennaro Musi
Naji Salem
Emanuele Montanari
Ottavio de Cobelli
Gwenaelle Gravis
Jochen Walz
Publikationsdatum: 06.03.2022
Verlag: Springer Berlin Heidelberg
Erschienen in: World Journal of Urology / Ausgabe 3/2023
Print ISSN: 0724-4983
Elektronische ISSN: 1433-8726
DOI: https://doi.org/10.1007/s00345-022-03965-w

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External validation of the computerized analysis of TRUS of the prostate with the ANNA/C-TRUS system: a potential role of artificial intelligence for improving prostate cancer detection