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© 2009 by the American Institute of Ultrasound in Medicine
J Ultrasound Med 28:455-460 • 0278-4297

Technical Advance

Mapping of Transrectal Ultrasonographic Prostate Biopsies

Quality Control and Learning Curve Assessment by Image Processing

Pierre Mozer, MD, PhD, Michael Baumann, PhD, Gregoire Chevreau, PhD, Alexandre Moreau-Gaudry, MD, PhD, Stephane Bart, MD, Raphaele Renard-Penna, MD, Eva Comperat, MD, Pierre Conort, MD, Marc-Olivier Bitker, MD, Emmanuel Chartier-Kastler, MD, PhD, Francois Richard, MD and Jocelyne Troccaz, PhD

Departments of Urology (P.M., M.B., G.C., S.B., P.C., M.-O.B., E.C.-K., F.R.), Radiology (R.R.-P.), and Pathology (E.C.), Assistance Publique–Hôpitaux de Paris, Paris, France; Institut de l’Ingénierie et de l’Information en Santé, Gestes Médico-Chirurgicaux Assistés par Ordinateur, Techniques de l’Imagerie de la Modélisation et de la Cognition, Grenoble, France (P.M., A.M.-G., J.T.); and Department of Methodology, Centre d’Investigation Clinique-Investigation Technologique, Grenoble University Hospital, Grenoble, France (A.M.-G.).

Address correspondence to Pierre Mozer, MD, PhD, Department of Urology, Groupe Hospitalier Pitié-Salpétrière, 91 Boulevard de l’Hôpital, 75013 Paris, France., E-mail: pierre.mozer{at}psl.aphp.fr

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 rate for targets in the middle and right parasagittal parts versus 53% for targets in the left lateral base). Feedback from this system after each series of biopsies enabled the operator to significantly improve his dexterity over the course of time (first 16 patients: median score, 7 of 10 and cumulated median biopsy length in targets of 90 mm; last 16 patients, median score, 9 of 10 and a cumulated median length of 121 mm; P = .046). Conclusions. In addition to being a useful tool to improve the distribution of prostate biopsies, the potential of this system is above all the preparation of a detailed "map" of each patient showing biopsy zones without substantial changes in routine clinical practices.

Key Words: image-based tracking • image processing • learning curve • prostate biopsy • quality control • 3-dimensional ultrasonography

Abbreviations: 3D, 3-dimensional • TRUS, transrectal ultrasonographic • 2D, 2-dimensional

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Copyright © 2009 by the American Institute of Ultrasound in Medicine.