Primary leiomyosarcoma of the inferior vena cava: case report.

The patient was a 63-year-old woman with a chief complaint of blood-stained sputum. A tumor of the inferior vena cava was found on chest computed tomography (CT) and identified as a primary tumor based on multidetector CT and contrast-enhanced MR angiography. An intrapelvic tumor was also discovered. On autopsy, the two tumors were diagnosed as leiomyosarcoma and ovarian fibroma, respectively.

A filmless radiology teaching conference system for pertinent displaying and image searching.

To solve the problems of image displays in filmless radiology conferences for the purpose of teaching, we made an experimental design of a conference system with dual 50-in. plasma monitors for displaying larger images and a shared folder containing shortcuts to images for quick display during conferences on the desktop of each client computer in a picture archival and communication system. The image quality of the monitors was evaluated using the TG18-QC test pattern. The display time of images was measured in 20 cases when the shared folder was used and when it was not. Monitor screen size and image quality, operability, display time of images, and overall impression given by the system were evaluated subjectively by five radiologists. Although the image quality of the monitor was not as high as that of the high-resolution monitors used for diagnostic radiology, its performance was good enough for teaching. The average display time using the shared folder (2.6 +/- 0.39 s) was significantly shorter than without it (16.9 +/- 5.04 s; p = 2.85 x 10(-6)). Despite the need for certain improvements in monitor size and in the operability of the system, the radiologists considered the system suitable for radiology teaching conferences. We believe that this system is useful for institutions that intend to introduce a filmless system for filmless radiology teaching conferences.

A computer-assisted system for diagnostic workstations: automated bone labeling for CT images.

Although accurate information on thoracolumbar bone structure is essential when computed tomography (CT) images are examined, there is no automated method of labeling all the vertebrae and ribs on a CT scan. We are developing a computer-aided diagnosis system that labels ribs and thoracolumbar vertebrae automatically and have evaluated its accuracy. A candidate bone was extracted from the CT image volume data by pixel thresholding and connectivity analysis. All non-bony anatomical structures were removed using a linear discriminate of distribution of CT values and anatomical characteristics. The vertebrae were separated from the ribs on the basis of their distances from the centers of the vertebral bodies. Finally, the thoracic cage and lumbar vertebrae were extracted, and each vertebra was labeled with its own anatomical number by histogram analysis along the craniocaudal midline. The ribs were labeled in a similar manner, based on location data. Twenty-three cases were used for accuracy comparison between our method and the radiologist's. The automated labeling of the thoracolumbar vertebrae was concordant with the judgments of the radiologist in all cases, and all but the first and second ribs were labeled correctly. These two ribs were frequently misidentified, presumably because of pericostal anatomical clutter or high densities of contrast material in the injected veins. We are confident that this system can contribute usefully as part of a picture archiving and communication system workstation, though further technical improvement is required for identification of the upper ribs.