Article

Progress in the use of helical CT for imaging urinary calculi.

Department of Anatomy and Cell Biology, Indiana University School of Medicine, Indianapolis, Indiana 46202-5120, USA.
Journal of Endourology (Impact Factor: 2.1). 01/2005; 18(10):937-41. DOI: 10.1089/end.2004.18.937
Source: PubMed

ABSTRACT Helical CT has become the preferred method to diagnose urinary calculi in patients presenting with abdominal or flank pain. Recent in vitro studies have shown that CT also can display the internal structure in stones with remarkable detail. Because some stones respond better to SWL than others, knowing stone structure at diagnosis could be helpful in choosing among treatment options. This paper examines the potential for CT to be used in this way. Older CT technology proved to be problematic, in that all studies using low-resolution CT will suffer from an artifact in which stone size affects apparent CT attenuation values. Thus, the observation that stones with low measured CT attenuation break more easily than stones with high attenuation could be attributable entirely to an artifact of stone size. Most stones are composed of more than one mineral, and heterogeneity of composition may contribute to variability in stone response to SWL. Older technology is not useful in evaluating stone composition, but current and emerging CT machines have sufficient resolution to determine the composition and structure of stones inside the patient, provided proper viewing windows are used. Continuing improvement in image resolution in helical CT promises to provide information about stone composition and structure that will ultimately lead to better care for patients with stone disease.

0 Followers
 · 
80 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Objectives To determine the role of stone density and skin-to-stone distance (SSD) by non-contrast computed tomography of the kidneys, ureters and bladder (CT-KUB) in predicting the success of extracorporeal shock wave lithotripsy (ESWL).Methods We evaluated 89 patients who received ESWL for renal and upper ureteric calculi measuring 5–20 mm, over a 12 month period. Mean stone density in Hounsfield units (HU) and mean SSD in millimetres (mm) was determined on pre-treatment CT-KUB at the CT workstation. ESWL was successful if post-treatment residual stone fragments were ≤3 mm.ResultsESWL success was observed in 68.5% of the patients. Mean stone densities were 505 ± 153 and 803 ± 93 HU in ESWL successful and failure groups, respectively; this was statistically significant (p < 0.001, student's t-test). Mean SSD were 10.6 ± 2.0 and 11.2 ± 2.6 cm in ESWL successful and failure groups, respectively, this was not statistically significant.Conclusions This study shows that stone density can help in predicting the outcome of ESWL. We propose that stone densities <500 HU are highly likely to result in successful ESWL. Conversely, stone densities ≥800 HU are less likely to do so. This should be accounted for when considering ESWL.
    British Journal of Medical and Surgical Urology 09/2009; 2(5):180-184. DOI:10.1016/j.bjmsu.2009.05.001
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This review article aims to summarize the value of computed tomography (CT) in determining treatment, specifically shockwave lithotripsy, for patients with renal calculi. Both CT and shockwave lithotripsy (SWL) were new technologies three decades ago and have since evolved both in parallel and synergistically over time. Although initially CT was only a diagnostic tool, advances in its use and postprocessing techniques have allowed for the determination of several stone and patient characteristics that guide therapy. Over time, CT has evolved into a distinctive application as a prognostic tool for SWL. Caution must be observed, however, in over using CT due to the long-term risks of radiation exposure. Ultimately a balance must be struck between clinical utility and patient protection.
  • Urological Research 01/2006; 33(6):481-2; author reply 483. DOI:10.1007/s00240-005-0501-7 · 1.31 Impact Factor