A User-Friendly Application to Automate CT Renal Stone Measurement

Justin B. Ziemba, Pan Li, Rishab Gurnani, Satomi Kawamoto, Elliot Fishman, George Fung, Wesley W. Ludwig, Dan Stoianovici, Brian R. Matlaga

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Introduction: CT is the gold standard for visualizing renal and ureteral calculi. CT three-dimensional reformatting allows for automatic, accurate, and reliable measurement of stone size, volume, density, and location. In this study, we aimed to develop and test a software platform capable of calculating a battery of clinically important urinary stone parameters at the point-of-care (POC). Methods: The syngo Calcium Scoring (Siemens Corporation) algorithm was modified to identify calcium-based stones using an attenuation threshold (250 HU) within a region of interest. Information automatically obtained after reconstruction included voxel sum and calculated volume, maximum diameter, largest diameter in the x, y, and z planes, cumulative diameter, distribution of attenuation in HU, and position relative to the skin for calculation of the skin-to-stone distance (SSD). This algorithm was packaged into a stand-alone application (MATLAB 9.1). From April 2017 to May 2017, all patients undergoing a noncontrast CT of the abdomen or the abdomen and pelvis at the Johns Hopkins Hospital were eligible for inclusion in this validation cohort. Results: A total of 55 index renal stones were included. The mean volume calculated by voxel sum was 216.53 mm3 (standard deviation [SD] ±616.19, range 1.50-4060.13). The mean volume calculated using the Ackermann's formula and for a sphere was 232.96 mm3 (SD ± 702.65, range 1.24-4074.04) and 1214.63 mm3 (SD ± 4233.41, range 1.77-25,246.40), respectively. The mean largest diameter in any one direction was 6.95 mm (SD ± 7.31, range 1.50-36.40). The maximum density of the stones ranged from 164 to 1725 HU. The mean SSD at the shortest possible point was 14.19 cm (SD ± 6.13, range 6.67-31.28). Conclusions: We developed a stand-alone platform with a simple easy-to-use interface, which will allow any user the ability to calculate a battery of clinically important urinary stone parameters from CT imaging at the POC. This program is now freely available online.

Original languageEnglish (US)
Pages (from-to)685-691
Number of pages7
JournalJournal of Endourology
Issue number8
StatePublished - Aug 2018


  • computer-assisted
  • image processing
  • kidney calculi
  • multidetector CT

ASJC Scopus subject areas

  • Urology


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