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Robotic Transrectal Computed Tomographic Ultrasound with Artificial Neural Network Analysis: First Validation and Comparison with MRI-Guided Biopsies and Radical Prostatectomy.

Authors :
Harland N
Russo GI
Kaufmann S
Amend B
Rausch S
Erne E
Scharpf M
Nikolaou K
Stenzl A
Bedke J
Kruck S
Source :
Urologia internationalis [Urol Int] 2022; Vol. 106 (1), pp. 90-96. Date of Electronic Publication: 2021 Aug 17.
Publication Year :
2022

Abstract

Introduction: There is still a lack of availability of high-quality multiparametric magnetic resonance imaging (mpMRI) interpreted by experienced uro-radiologists to rule out clinically significant PC (csPC). Consequently, we developed a new imaging method based on computed tomographic ultrasound (US) supported by artificial neural network analysis (ANNA).<br />Methods: Two hundred and two consecutive patients with visible mpMRI lesions were scanned and recorded by robotic CT-US during mpMRI-TRUS biopsy. Only significant index lesions (ISUP ≥2) verified by whole-mount pathology were retrospectively analyzed. Their visibility was reevaluated by 2 blinded investigators by grayscale US and ANNA.<br />Results: In the cohort, csPC was detected in 105 cases (52%) by mpMRI-TRUS biopsy. Whole-mount histology was available in 44 cases (36%). In this subgroup, mean PSA level was 8.6 ng/mL, mean prostate volume was 33 cm3, and mean tumor volume was 0.5 cm3. Median PI-RADS and ISUP of index lesions were 4 and 3, respectively. Index lesions were visible in grayscale US and ANNA in 25 cases (57%) and 30 cases (68%), respectively. Combining CT-US-ANNA, we detected index lesions in 35 patients (80%).<br />Conclusions: The first results of multiparametric CT-US-ANNA imaging showed promising detection rates in patients with csPC. US imaging with ANNA has the potential to complement PC diagnosis.<br /> (© 2021 S. Karger AG, Basel.)

Details

Language :
English
ISSN :
1423-0399
Volume :
106
Issue :
1
Database :
MEDLINE
Journal :
Urologia internationalis
Publication Type :
Academic Journal
Accession number :
34404057
Full Text :
https://doi.org/10.1159/000517674