Estimation of urinary stone composition by automated processing of CT images

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• 作者：Gr¨¦goire Chevreau ; Jocelyne Troccaz ; Pierre Conort ; Rapha?lle Renard-Penna ; Alain Mallet ; Michel Daudon and Pierre Mozer
• 关键词：Helical computed tomography ; Urinary tract calculi ; Urolithiasis ; Composition
• 刊名：Urological Research
• 出版年：2009
• 出版时间：October, 2009
• 年：2009
• 卷：37
• 期：5
• 页码：241-245
• 全文大小：309.0 KB

文摘

The objective of this article was developing an automated tool for routine clinical practice to estimate urinary stone composition from CT images based on the density of all constituent voxels. A total of 118 stones for which the composition had been determined by infrared spectroscopy were placed in a helical CT scanner. A standard acquisition, low-dose and high-dose acquisitions were performed. All voxels constituting each stone were automatically selected. A dissimilarity index evaluating variations of density around each voxel was created in order to minimize partial volume effects: stone composition was established on the basis of voxel density of homogeneous zones. Stone composition was determined in 52 % of cases. Sensitivities for each compound were: uric acid: 65 % , struvite: 19 % , cystine: 78 % , carbapatite: 33.5 % , calcium oxalate dihydrate: 57 % , calcium oxalate monohydrate: 66.5 % , brushite: 75 % . Low-dose acquisition did not lower the performances (P < 0.05). This entirely automated approach eliminates manual intervention on the images by the radiologist while providing identical performances including for low-dose protocols.