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A User-Friendly Application to Automate CT Renal Stone Measurement.

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Area of Science:

  • Medical Imaging
  • Urology
  • Software Development

Background:

  • Computed Tomography (CT) is the standard for visualizing kidney and ureteral stones.
  • Three-dimensional CT reformatting enables precise measurement of stone size, volume, density, and location.
  • Accurate stone characterization is vital for effective clinical management.

Purpose of the Study:

  • To develop and validate a software platform for calculating key urinary stone parameters.
  • To enable point-of-care (POC) analysis of urinary stone characteristics using CT imaging.
  • To provide clinicians with an accessible tool for quantitative stone assessment.

Main Methods:

  • Modified a commercial algorithm (syngo Calcium Scoring) to identify stones based on attenuation thresholds.
  • Developed a stand-alone application using MATLAB to automatically calculate stone parameters including volume, diameter, density, and skin-to-stone distance (SSD).
  • Validated the platform on a cohort of 55 renal stones from patients undergoing noncontrast CT scans.

Main Results:

  • The software platform successfully calculated various stone parameters, including mean volume (216.53 mm³), largest diameter (6.95 mm), and maximum density (164-1725 HU).
  • Mean skin-to-stone distance (SSD) was calculated as 14.19 cm.
  • The developed platform demonstrated the ability to derive clinically relevant stone metrics from CT data.

Conclusions:

  • A user-friendly, stand-alone software platform was successfully developed for calculating urinary stone parameters from CT imaging.
  • The platform enables point-of-care (POC) quantitative analysis of urinary stones.
  • This freely available online tool empowers users to obtain critical stone metrics for improved patient care.