Klinik für Urologie, Diakonissenkrankenhaus Flensburg, Lehrkrankenhaus der Christian-Albrechts-Universität Kiel des Universitätsklinikums Schleswig-Holstein, Marienhoelzungsweg 2, 24939, Flensburg, Germany.
To improve prostate cancer diagnostic imaging, a computer-based analysis of the transrectal ultrasound signal (C-TRUS) was developed. Until recently, the C-TRUS existed only as a stand-alone device. Now, C-TRUS was developed into a network-compatible module (C-TRUS-MS). This new technology allows users to transmit C-TRUS images from any internet platform to C-TRUS-MS investigation. After analysis, the cancer-suspicious marked images are then retransmitted via internet. Targeted biopsies can then be taken at the urologists' office remotely.
This prospective study investigates whether the rates of prostate cancer detection with C-TRUS-MS "multicenter online" are comparable with those achieved by the stand-alone unit. In addition to patients with a history of multiple systematic random biopsies, a group of patients who had not undergone systematic random biopsies were analyzed.
A total of 1,545 digital images (2-23 per patient, median 6) from 57 urologists were transmitted to the analysis center. After analysis, the color-coded images were sent back electronically and utilized for a maximum of six targeted biopsies. C-TRUS-MS was able to detect prostate cancer in 91 patients. In addition, we evaluated 75 patients without any previous random biopsies. In this group, C-TRUS-MS was able to detect prostate cancer in 31 out of 75 patients (41%).
The results indicate that C-TRUS-MS "online" achieves similar results as the stand-alone system, independent of the user even with little experience in the method. Furthermore, C-TRUS-MS for the first time is able to detect carcinomas in patients without prior biopsies in a high number by taking only six targeted biopsies.
Written by:
Grabski B, Baeurle L, Loch A, Wefer B, Paul U, Loch T. Are you the author?
Reference: World J Urol. 2011 Jun 21. Epub ahead of print.
doi: 10.1007/s00345-011-0713-0
PubMed Abstract
PMID: 21691722
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