A skyline-view imaging technique for axial projection of the patella: a clinical study.

Our purpose in this study was to evaluate the clinical usefulness of a new skyline-view imaging technique for axial projection of the patella with use of the anterior border of the patella and tibial tuberosity as position indicators. Our database consisted of pairs of axial images of the patella of the same patients, obtained with use of conventional and new techniques for the radiographic diagnosis of knee-joint diseases. A total of 118 pairs of knee images were obtained from 103 patients ranging in age from 16 to 86 years (mean age 49.7 years). The patellar axial positioning errors were determined in each of the images obtained with the two techniques. The relative error according to the patellar tilt was determined from each of the axial images of the patellas of the same patients obtained with the conventional and new techniques for the radiographic diagnosis of knee-joint diseases. The patellar axial positioning error was 0.40 with the conventional technique, whereas that with the new technique was significantly different at 0.30. This clinical study confirmed that the new skyline-view imaging technique, which uses the anterior border of the patella and the tibial tuberosity as position markers that can be confirmed by palpation, provides more accurate axial images than the conventional imaging technique.

Appropriate incidence angle for fundamental research on new skyline radiography development.

Our purpose in this study was to elucidate the relationship between the angles formed between the anterior patella, tibial tuberosity, and the knee joint cavity and the flexion angle, sex, and age of the subjects. We investigated 368 images of 280 patients ranging in age from 16 to 60 years (179 knees of 150 men, mean age 36.4 years; 189 knees of 130 women, mean age 41.4 years) who underwent lateral radiography of the knee. The tibial tuberosity on the lateral radiograph of the knee was defined as a reference point, and a line tangent to the anterior patella was used as a reference line. The angle between the reference line and the straight line from the reference point to the knee joint cavity (incidence angle) was measured. The average incidence angle was 19° (SD 1.8°). There was almost no correlation between the incidence angle and the flexion angle, and neither the knee flexion angle nor age had any influence on the incidence angle. There was a difference between the sexes in the average incidence angle, but this difference was less than 1°. Further study on the same patients is required for comparison of this technique with the conventional technique that uses the femur for reference.

Combined multi-kernel head computed tomography images optimized for depicting both brain parenchyma and bone.

BACKGROUND: The hybrid convolution kernel technique for computed tomography (CT) is known to enable the depiction of an image set using different window settings. OBJECTIVE: Our purpose was to decrease the number of artifacts in the hybrid convolution kernel technique for head CT and to determine whether our improved combined multi-kernel head CT images enabled diagnosis as a substitute for both brain (low-pass kernel-reconstructed) and bone (high-pass kernel-reconstructed) images. METHODS: Forty-four patients with nondisplaced skull fractures were included. Our improved multi-kernel images were generated so that pixels of >100 Hounsfield unit in both brain and bone images were composed of CT values of bone images and other pixels were composed of CT values of brain images. Three radiologists compared the improved multi-kernel images with bone images. RESULTS: The improved multi-kernel images and brain images were identically displayed on the brain window settings. All three radiologists agreed that the improved multi-kernel images on the bone window settings were sufficient for diagnosing skull fractures in all patients. CONCLUSIONS: This improved multi-kernel technique has a simple algorithm and is practical for clinical use. Thus, simplified head CT examinations and fewer images that need to be stored can be expected.

Combined multi-kernel chest computed tomography images optimized for depicting both lung and soft tissue.

PURPOSE: To evaluate the quality of our improved multi-kernel chest computed tomography (CT) images. METHODS: A random sample of 50 normal patients was retrospectively selected from those who underwent chest CT scans between January 2010 and July 2010. Normal lung structures were divided into six categories, and two radiologists independently compared with lung images. RESULTS: The improved multi-kernel images were displayed identically to soft tissue images on soft tissue window settings and were evaluated as equal to lung images on lung window settings. CONCLUSIONS: This improved multi-kernel technique required fewer stored images and simplified examinations of chest CT.

A simple method for identifying image orientation of chest radiographs by use of the center of gravity of the image.

Bedside chest radiography is a frequent X-ray examination when patients are physically incapacitated. An X-ray cassette with an imaging plate is inserted below the patient's body, and the image orientation of the radiograph is determined by the direction of insertion. Therefore, an incorrect direction of insertion would yield an incorrect image orientation for diagnosis, if no correction was performed on the resulting image data. We aimed to develop a computerized method that identifies the image orientation of chest radiographs by using the center of gravity (COG) of the images in terms of pixel values. To develop the computerized method, we used 247 chest images contained in the Japanese Society of Radiological Technology database as training cases, and 1833 bedside chest radiographs obtained in our institution for validation testing. As a result for the 247 training images, the angles which were obtained from directions between the COG of pixel values and the center of the image were distributed between 162.7° and 224.4° in a clockwise direction. We used the angle of the COG to identify the correct view orientation. The range of angles (139.1°-229.0°) for the COG in the chest image with correct image orientation was determined with a 99 % confidence interval for the angles of the COGs obtained from the training images. As a result of the validation test based on the range of angles determined, 99.7 % of the 1833 test images were identified correctly.