Mapping of transrectal ultrasonographic prostate biopsies: quality control and learning curve assessment by image processing
Pierre Mozer, Michael Baumann (TIMC), Gregoire Chevreau (TIMC),, Alexandre Moreau-Gaudry (TIMC, CHU-Grenoble CIC), Stephane Bart, Raphaele, Renard-Penna, Eva Comperat, Pierre Conort, Marc-Olivier Bitker, Emmanuel, Chartier-Kastler, Francois Richard, Jocelyne Troccaz (TIMC)

TL;DR
This study evaluates a registration algorithm to improve the accuracy and learning curve of transrectal ultrasonographic prostate biopsies, providing a detailed mapping tool for better biopsy targeting.
Contribution
It introduces a registration-based system that enhances biopsy localization accuracy and tracks operator learning over time in prostate cancer diagnosis.
Findings
Operator reached 71% of planned targets with variability based on location.
Operator's dexterity improved significantly over time.
System provides detailed patient biopsy maps without disrupting routine practice.
Abstract
Objective: Mapping of transrectal ultrasonographic (TRUS) prostate biopsies is of fundamental importance for either diagnostic purposes or the management and treatment of prostate cancer, but the localization of the cores seems inaccurate. Our objective was to evaluate the capacities of an operator to plan transrectal prostate biopsies under 2-dimensional TRUS guidance using a registration algorithm to represent the localization of biopsies in a reference 3-dimensional ultrasonographic volume. Methods: Thirty-two patients underwent a series of 12 prostate biopsies under local anesthesia performed by 1 operator using a TRUS probe combined with specific third-party software to verify that the biopsies were indeed conducted within the planned targets. RESULTS: The operator reached 71% of the planned targets with substantial variability that depended on their localization (100% success…
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Taxonomy
TopicsProstate Cancer Diagnosis and Treatment · Colorectal Cancer Screening and Detection
