Unenhanced x-ray computed tomography (CT) is the initial imaging modality of choice for patients presenting to the emergency department with acute flank pain. 

For patients with recurrent stone disease, CT is a critical tool for the quantification cicstksplas_noLoadingof size, number and location of stones, as well as for the assessment of metabolic activity – i.e., stone growth or new stone formation in a year. However, current clinical imaging software and workflow have proven to be inadequate to efficiently and accurately characterize kidney stones, especially for the most complex cases with multiple stones and irregular shapes. As a result, accurate quantification of renal stone burden is rarely included in a radiology report.

The CT Clinical Innovation Center has been developing a semi-automated software system (qSAS) that is able to provide a standardized report of urinary stones using reproducible metrics in order to support radiologists, clinicians, and researchers. qSAS generates fully standardized stone reports in less than 5 minutes per case. The only user interaction required is a coarse delineation of the kidneys, following which the software automatically identifies any renal stone, properly excluding any hardware in the kidneys such as stents and nephrostomy tubes.

Developed with the support of the U54 O’Brien urology research center at Mayo Clinic, qSAS is currently used for all kidney stones CT imaging research at our institution. We have now made qSAS freely available to the stone imaging research community. Watch a tutorial of its functionalities, download the research agreement and send it back to us to receive a copy of the software. It’s that simple! We look forward to facilitating your research and together, improve stone imaging research.
*Note that this software is not FDA approved and should not be used for clinical diagnostic purposes.

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User Documents

Software Sharing Agreement (external investigators)
Please download the form to your desktop or other location to complete.  Make sure to click on "Submit" to send to Mayo staff.  Once reviewed and signed, you will receive back a completed copy, if requested.

Software Sharing Acknowledgment (Mayo internal investigators)

qSAS User Manual

1. Ferrero et al.  Quantitative stone analysis software for clinical and research studies.  ROCK Society Annual Meeting; 2018
2. Montoya et al. Semi‐automated analysis of urinary stones using dual‐energy CT in a preoperative setting: Improved workflow and reporting. 102nd Annual Meeting of the Radiology Society of North America; 2016
3. Ferrero et al. qSAS: A quantitative stone analysis software for research CT imaging studies.  National Institutes of Health Renal Imaging Symposium; 2018



qSAS Development Team

Andrea Ferrero, PhD
Cynthia H. McCollough, PhD
Jamison E. Thorne

Xinhui Duan, PhD
Darwin Garcia
Taylor Moen
Juan Montoya Cardona
Terri J. Vrtiska, MD
Jayse Weaver

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