John Roger Bell1,2, Natasza M Posielski2, Kristina L Penniston2, Meghan G Lubner3, Stephen Y Nakada2,3,4, Perry J Pickhardt3,5. 1. 1 Department of Urology, University of Kentucky College of Medicine , Lexington, Kentucky. 2. 2 Department of Urology, University of Wisconsin School of Medicine and Public Health , Madison, Wisconsin. 3. 3 Department of Radiology, University of Wisconsin School of Medicine and Public Health , Madison, Wisconsin. 4. 4 Department of Medicine, University of Wisconsin School of Medicine and Public Health , Madison, Wisconsin. 5. 5 University of Wisconsin Carbone Cancer Center, Madison Wisconsin.
Abstract
INTRODUCTION AND OBJECTIVE: Stone size guides treatment decisions, yet there is no standard method for measuring stone size. Prior work has shown significant variability in manual stone measurements. We tested a novel stone software program designed to provide an automated and objective comprehensive CT-based stone profile. METHODS: Urinary stones identified on CT imaging were manually measured to obtain linear size and maximal stone density (in Hounsfield unit [HU]). Manual stone volume was calculated using the formula 0.52 × length × width × height. The same stones were assessed with computer software capable of automatically providing stone length, density, and volume. Computer measurements were compared with manual measurements. RESULTS: Eighty-five stones were identified on 42 CT scans from 17 patients. Manual measurements showed an average length of 8 mm (range 1.9-21 mm), average maximal density of 686 HU (126-1492 HU), and average stone volume of 192 mm3 (2.9-2555 mm3). Automated computer measurements did not differ from manual measurements for density (755 HU vs 686 HU, p = 0.18) and volume (183 mm3 vs 192 mm3, p = 0.86. Automated length was slightly longer then manual length (10 mm vs 8 mm, p < 0.003). The mean percent differences between manual and automated metrics were 14.3% for density, 21.0% for volume, and 25.2% for length. CONCLUSION: Automated stone measurements can be accomplished quickly and precisely with dedicated software that can assess stones of varying size as well as stones with complex geometry. This software eliminates interobserver variability and offers a comprehensive stone profile with which to make clinical decisions.
INTRODUCTION AND OBJECTIVE: Stone size guides treatment decisions, yet there is no standard method for measuring stone size. Prior work has shown significant variability in manual stone measurements. We tested a novel stone software program designed to provide an automated and objective comprehensive CT-based stone profile. METHODS: Urinary stones identified on CT imaging were manually measured to obtain linear size and maximal stone density (in Hounsfield unit [HU]). Manual stone volume was calculated using the formula 0.52 × length × width × height. The same stones were assessed with computer software capable of automatically providing stone length, density, and volume. Computer measurements were compared with manual measurements. RESULTS: Eighty-five stones were identified on 42 CT scans from 17 patients. Manual measurements showed an average length of 8 mm (range 1.9-21 mm), average maximal density of 686 HU (126-1492 HU), and average stone volume of 192 mm3 (2.9-2555 mm3). Automated computer measurements did not differ from manual measurements for density (755 HU vs 686 HU, p = 0.18) and volume (183 mm3 vs 192 mm3, p = 0.86. Automated length was slightly longer then manual length (10 mm vs 8 mm, p < 0.003). The mean percent differences between manual and automated metrics were 14.3% for density, 21.0% for volume, and 25.2% for length. CONCLUSION: Automated stone measurements can be accomplished quickly and precisely with dedicated software that can assess stones of varying size as well as stones with complex geometry. This software eliminates interobserver variability and offers a comprehensive stone profile with which to make clinical decisions.
Authors: Mohammed A Elbaset; Abdelwahab Hashem; Ahmed Eraky; Mohammed A Badawy; Ahmed El-Assmy; Khaled Z Sheir; Ahmed A Shokeir Journal: World J Urol Date: 2019-04-03 Impact factor: 4.226