Low-contrast detectability in volume rendering: a phantom study on multidetector-row spiral CT data.
To cope with the increasing amount of CT data, there is growing interest in direct volume-rendering techniques (VRT) as a diagnostic tool. The aim of this phantom study was to analyze the low-contrast detectability (LCD) of VRT compared with multi-planar reformations (MPR). Soft tissue lesions were simulated by spheres of different diameters (3-8 mm). The average lesion density was 15 HU compared with a background density of 35 HU. Two different CT protocols with 40 and 150 mAs were performed on a multi-detector row CT. The scanning parameters were as following: 140 kV; 2x0.5-mm slice collimation; pitch 2 (table movement per rotation/single slice collimation), and reconstruction with 0.5-mm slice thickness at 0.5-mm interval. A B30 kernel was used for reconstruction. The VRT was performed by mapping Hounsfield values to gray levels equal to a CT window (center: 60 HU; window: 370 HU ). A linear ramp was applied for the opacity transfer function varying the maximum opacity between 0.1 and 1.0. A statistical method based on the Rose model was used to calculate the detection threshold depending on lesion size and image noise. Additionally, clinical data of 2 patients with three liver lesions of different sizes and density were evaluated. In VRT, LCD was most dependent on object size. Regarding lesions larger than 5 mm, VRT is significantly superior to MPR (p<0.05) for all opacity settings. In lesions sized 3-5 mm a maximum opacity level approximately 40-50% showed a near equivalent detectability in VRT and MPR. For higher opacity levels VRT was superior to MPR. Only for 3-mm lesions MPR performed slightly better in low-contrast detectability (p<0.05). Compared with MPR, VRT shows similar performance in LCD. Due to noise suppression effects, it is suited for visualization of data with high noise content.
Shin
Hoen-Oh
HO
Department of Diagnostic Radiology, Medical School Hannover, Carl-Neuberg-Strasse 1, 30625 Hannover, Germany. shin.hoen-oh@mh-hannover.de
Falck
Christian V
CV
Galanski
Michael
M
D000368:Aged; D002276:Carcinoid Tumor / Q000000981:diagnostic imaging / Q000556:secondary; D006528:Carcinoma, Hepatocellular / Q000000981:diagnostic imaging; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional; D007414:Intestinal Neoplasms / Q000000981:diagnostic imaging; D007421:Intestine, Small / Q000000981:diagnostic imaging; D008099:Liver / Q000000981:diagnostic imaging; D008103:Liver Cirrhosis / Q000000981:diagnostic imaging; D008113:Liver Neoplasms / Q000000981:diagnostic imaging / Q000556:secondary; D008297:Male; D019047:Phantoms, Imaging; D011856:Radiographic Image Enhancement; D012680:Sensitivity and Specificity; D036542:Tomography, Spiral Computed