Category: Clinical Stones: Ureteroscopy
Introduction & Objective :
One challenge in ureteroscopic stone management is an inability to accurately gauge the size of stone fragments. We have developed and validated a novel software (SW) that can accurately measure stone size during flexible ureteroscopy to a 0.14 mm error. We present our evaluation of this SW to identifying stone fragments that can fit through a ureteral access sheath (UAS).
Methods : We created 50 mock stone fragments of 2-6 mm in length and separated them randomly into 5 groups. Each fragment was measured in the transverse and longitudinal dimensions using our novel SW. We attempted to extract the stone fragments through a 12/14F UAS. We utilized the software’s maximum dimension measurement (SWmax) to assess whether the fragment would fit through the UAS. We assessed the performance characteristics for both SWmax < 4.0 mm (the inner diameter of the UAS) and SWmax < 3.85 mm (known measurement error of the software) as criteria for effective fragment removal. Next, six independent operators familiar with ureteroscopy (residents, fellows, attendings) evaluated the images of the stone fragments with a 0.038 inch diameter guide wire as reference. The operators were asked if they thought the fragment would fit through a 12/14F UAS and performance characteristics were similarly calculated.
Results : The median fragment longitudinal length was 4.40 mm (Range: 3.16 – 6.70 mm) and transverse length was 3.76 mm (Range: 2.72 – 5.91 mm). Among all stone fragments, 20/50 (40%) fit through the UAS while the remaining 30/50 (60%) did not. When using a SWmax threshold of 4.0 mm, the sensitivity of the SW to detect fragments small enough for extraction was 84.2% (95% CI: 59.5-95.8%) with a specificity of 96.2% (95% CI: 78.4-99.8%). There was one false-positive fragment with a SWmax of 3.9 mm that did not fit through the UAS. With a SWmax threshold of 3.85 mm, the specificity increased to 100% (95% CI: 83.4-100.0%) while sensitivity decreased to 73.7% (95% CI: 45.7-87.2%). The six operators has a sensitivity of 78.2% (95% CI: 69.7-84.9%) and specificity of 76.0% (95% CI: 68.1-82.5%).
Conclusions : Our novel SW program can accurately and reproducibly identify stone fragments that can successfully be withdrawn through a UAS. Using a SWmax cut-off of 3.85 mm appears to have better specificity for detecting removable stone fragments compared to trained urologists.
Kevin Koo– Fellow, Johns Hopkins University School of Medicine, Baltimore, Maryland
Gregory Joice– Johns Hopkins Hospital, Baltimore, Maryland
Sunghwan Lim– Baltimore, Maryland
Wesley Ludwig– Baltimore, Maryland
Michael Gorin– Assistant Professor of Urology, Oncology, and Radiology, The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland
Dan Stoianovici– Baltimore, Maryland
Brian Matlaga– Baltimore, Maryland
Johns Hopkins University School of Medicine
Kevin Koo, MD, MPH, MPhil, is a fellow in endourology and minimally-invasive urological surgery at the Brady Urological Institute, Johns Hopkins University School of Medicine. He serves as national chair of the AUA Residents and Fellows Committee and is the AUA H. Logan Holtgrewe Legislative Fellow. He is a graduate of the Yale School of Medicine and completed residency at Dartmouth-Hitchcock Medical Center.
Assistant Professor of Urology, Oncology, and Radiology
The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine