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ORIGINAL ARTICLE
Year : 2016  |  Volume : 29  |  Issue : 2  |  Page : 297-302

Role of multidetector computed tomography without contrast enhancement in predicting the outcome of extracorporeal shock wave lithotripsy for urinary calculi


1 Visitor in Radiology Department, Faculty of Medicine, Menoufia University, Menoufia, Egypt
2 Radiology Department, Faculty of Medicine, Menoufia University, Menoufia, Egypt

Correspondence Address:
Alaa Mohamed Mohamed El Mahdy
El-Baramoon, beside DR. Amira Pharmacy, Mansoura, Dakahlia
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/1110-2098.192414

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Objective: The aim of this study was to evaluate the role of nonenhancing computed tomography as a predictive factor for successful extracorporeal shock wave lithotripsy (ESWL) for urinary calculi to avoid the cost of ineffective ESWL. Background: Urolithiasis is a universal problem. Many methods of treatment of urolithiasis are described, among which is ESWLs. The outcome of ESWL is affected by several factors. Multidetector computed tomography (MDCT) can aid the localization of calculi and may provide accurate anatomical detail, providing valuable data such as stone size and stone density as predictors for ESWL success. Materials and methods: This study included 54 patients who presented with symptomatic renal colic and hematuria at the ESWL unit. ESWL was used as the primary treatment option for all patients. All patients were investigated by MDCT before and after ESWL treatment. Successful ESWL was defined when a patient had achieved complete clearance of the stone fragments or had small residual gravels of size less than 4 mm. ESWL failure was defined as no breakage of the stone after three sessions. Results: A high rate of ESWL success after a second session of ESWL was achieved in 26 cases (48.1%), followed by a first session in 15 cases (27.8%), with an overall success rate of 90.7% in 49 cases. Also, smaller size and density of urinary stones will increase the success rate of ESWL. Conclusion: MDCT can be used to provide valuable data on urinary stones to aid treatment decisions and predict the outcome of ESWL.


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