OBJECTIVE: To assess the reproducibility of estimates of prostate volume determined by planimetry from transrectal ultrasonography (TRUS) images. MATERIALS AND METHODS: Two sequential sessions of images obtained by TRUS were obtained from 30 patients, with the ultrasound probe removed and inserted between the sessions. The stored images were outlined, both manually and by computer, and measurements of prostate volume obtained planimetrically. In addition, the ability of the urologist to accurately draw the contour was assessed by outlining predefined contours. RESULTS: The mean (SD) variability of manual outlining between sessions was 3.5 (3.4)%, within one session was 1.7 (1.3)% and of computer outlining between sessions was 4.3 (3.8%). Comparing the results of manual and computer outlining showed a mean (SD) variability of 7.5 (5.6)%, with larger values obtained from computer outlining. The mean (SD) variation in manually outlining predefined contours was 1.4 (1.4)%. CONCLUSIONS: The variability of computer outlining was slightly higher than expected theoretically. The within-session variability was higher than the variation caused by errors in outlining predefined contours, indicating that the interpretation of TRUS images differed with time. Automated determination of prostate volume can save time during clinical investigation and the variability is within the clinically acceptable range of 5%.
OBJECTIVE: To assess the reproducibility of estimates of prostate volume determined by planimetry from transrectal ultrasonography (TRUS) images. MATERIALS AND METHODS: Two sequential sessions of images obtained by TRUS were obtained from 30 patients, with the ultrasound probe removed and inserted between the sessions. The stored images were outlined, both manually and by computer, and measurements of prostate volume obtained planimetrically. In addition, the ability of the urologist to accurately draw the contour was assessed by outlining predefined contours. RESULTS: The mean (SD) variability of manual outlining between sessions was 3.5 (3.4)%, within one session was 1.7 (1.3)% and of computer outlining between sessions was 4.3 (3.8%). Comparing the results of manual and computer outlining showed a mean (SD) variability of 7.5 (5.6)%, with larger values obtained from computer outlining. The mean (SD) variation in manually outlining predefined contours was 1.4 (1.4)%. CONCLUSIONS: The variability of computer outlining was slightly higher than expected theoretically. The within-session variability was higher than the variation caused by errors in outlining predefined contours, indicating that the interpretation of TRUS images differed with time. Automated determination of prostate volume can save time during clinical investigation and the variability is within the clinically acceptable range of 5%.
Authors: R Berges; K Dreikorn; K Höfner; U Jonas; K U Laval; S Madersbacher; M C Michel; R Muschter; M Oelke; L Pientka; C Tschuschke; U Tunn; K Schalkhäuser; B Göckel-Beining; A Heidenreich; H Rübben; K Schalkhäuser; W Thon; J Thüroff; W Weidner Journal: Urologe A Date: 2003-03-12 Impact factor: 0.639
Authors: R Berges; K Dreikorn; K Höfner; S Madersbacher; M C Michel; R Muschter; M Oelke; O Reich; W Rulf; C Tschuschke; U Tunn Journal: Urologe A Date: 2009-11 Impact factor: 0.639
Authors: Nicholas R Paterson; Luke T Lavallée; Laura N Nguyen; Kelsey Witiuk; James Ross; Ranjeeta Mallick; Wael Shabana; Blair MacDonald; Nicola Scheida; Dean Fergusson; Franco Momoli; Sonya Cnossen; Christopher Morash; Ilias Cagiannos; Rodney H Breau Journal: Can Urol Assoc J Date: 2016-08 Impact factor: 1.862
Authors: Brian Garvey; Barış Türkbey; Hong Truong; Marcelino Bernardo; Senthil Periaswamy; Peter L Choyke Journal: Diagn Interv Radiol Date: 2014 May-Jun Impact factor: 2.630