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The purpose of this study was to develop methods for the differentiation of urinary stones and vascular calcifications using computer-aided diagnosis (CAD) of non-contrast computed tomography (CT) images. From May 2003 to February 2004, 56 patients that underwent a pre-contrast CT examination and subsequently diagnosed as ureter stones were included in the study. Fifty-nine ureter stones and 53 vascular calcifications on pre-contrast CT images of the patients were evaluated. The shapes of the lesions including disperseness, convex hull depth, and lobulation count were analyzed for patients with ureter stones and vascular calcifications. In addition, the internal textures including edge density, skewness, difference histogram variation (DHV), and the gray-level co-occurrence matrix moment were also evaluated for the patients. For evaluation of the diagnostic accuracy of the shape and texture features, an artificial neural network (ANN) and receiver operating characteristics curve (ROC) analyses were performed. Of the several shape factors, disperseness showed a statistical difference between ureter stones and vascular calcifications (p < 0.05). For the internal texture features, skewness and DHV showed statistical differences between ureter stones and vascular calcifications (p < 0.05). The performance of the ANN was evaluated by examining the area under the ROC curves (AUC, A (z)). The A (z) value was 0.85 for the shape parameters and 0.88 for the texture parameters. In this study, several parameters regarding shape and internal texture were statistically different between ureter stones and vascular calcifications. The use of CAD would make it possible to differentiate ureter stones from vascular calcifications by a comparison of these parameters.

The aim of this study was to develop wireless Picture Archiving and Communication System (PACS) device and to analyze its effect on image transfer from portable imaging modalities to the main PACS server. Using a laptop computer equipped with wireless local area network (LAN), the authors developed a wireless PACS device with DICOM modality worklist and DICOM storage server modules. This laptop computer could be easily fixed to portable imaging modalities such as ultrasound machines. From May to August 2007, 112 portable examinations were evaluated. Of these, 62 were done with wireless LAN-based PACS device, and 50 were done without wireless PACS device. To evaluate the impact of the wireless LAN-based PACS device on productivity and workflow, we analyzed the mean time delay and standard deviations (SD) both in cases where wireless LAN-based PACS device was used and in cases where it was not used. Statistical analysis was performed using a t test. The mean time interval from image acquisition to storage in the main PACS when the wireless LAN-based PACS device was used was 342.4 s (5 min and 42.4 s, SD = 509.2 s). When the wireless PACS was not used, the mean time interval was 2,305.5 s (38 min and 25.5 s, SD = 1,371.8 s). The mean time interval was statistically different between the two groups (t test, p < 0.001). The wireless LAN-based PACS device could help in reducing the storage intervals of images obtained by portable machines and in promoting effective and rapid treatment of patients who have undergone portable imaging examinations.