OBJECTIVES: To assess the role of multidetector computed tomography (MDCT) with multiplanar reconstruction (MPR) and virtual gastroscopy (VG) for detection and differentiation of gastric subepithelial masses (SEMs) by comparison with endoscopic ultrasonography (EUS). METHODS: Forty-one patients with a suspected SEM were evaluated using EUS and MDCT. MDCT findings were analyzed based on the consensus of two radiologists who were blinded to the EUS findings. The analysis of the CT features included the location, size, and contours of the tumor, the presence of central dimpling, as well as the growth pattern, enhancement pattern, and enhancement degree. The long diameter (LD) and the short diameter (SD) of each lesion were measured and the LD/SD ratios were calculated. EUS and MDCT results were compared with histopathology for the pathologically proven lesions. For the non-pathologically proven lesions, MDCT results were compared with EUS. RESULTS: Among the 41 patients, 34 SEMs were detected using EUS. For the detection of SEMs with MDCT, a sensitivity of 85.3%, a specificity of 85.7%, a positive predictive value of 96.7%, and a negative predictive value of 54.5% were calculated. The overall accuracy of MDCT for detecting and classifying the SEMs was 85.3 and 78.8%, respectively. CONCLUSIONS: MDCT with MPR and VG is a valuable method for the evaluation of SEMs. Specific MDCT criteria for various SEMs may be helpful in making an accurate diagnosis.
OBJECTIVES: To assess the role of multidetector computed tomography (MDCT) with multiplanar reconstruction (MPR) and virtual gastroscopy (VG) for detection and differentiation of gastric subepithelial masses (SEMs) by comparison with endoscopic ultrasonography (EUS). METHODS: Forty-one patients with a suspected SEM were evaluated using EUS and MDCT. MDCT findings were analyzed based on the consensus of two radiologists who were blinded to the EUS findings. The analysis of the CT features included the location, size, and contours of the tumor, the presence of central dimpling, as well as the growth pattern, enhancement pattern, and enhancement degree. The long diameter (LD) and the short diameter (SD) of each lesion were measured and the LD/SD ratios were calculated. EUS and MDCT results were compared with histopathology for the pathologically proven lesions. For the non-pathologically proven lesions, MDCT results were compared with EUS. RESULTS: Among the 41 patients, 34 SEMs were detected using EUS. For the detection of SEMs with MDCT, a sensitivity of 85.3%, a specificity of 85.7%, a positive predictive value of 96.7%, and a negative predictive value of 54.5% were calculated. The overall accuracy of MDCT for detecting and classifying the SEMs was 85.3 and 78.8%, respectively. CONCLUSIONS: MDCT with MPR and VG is a valuable method for the evaluation of SEMs. Specific MDCT criteria for various SEMs may be helpful in making an accurate diagnosis.