A Longitudinal Computed Tomography Imaging in the Diagnosis of Gallbladder Cancer
Background/Aim. To assess whether the diagnostic power of longitudinal multiplanar reformat (MPR) images is superior to that of conventional horizontal images for gallbladder cancer (GBC). Methods. Between 2006 and 2010, a total of 54 consecutive patients with preoperatively diagnosed gallbladder ne...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-01-01
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| Series: | Gastroenterology Research and Practice |
| Online Access: | http://dx.doi.org/10.1155/2015/254156 |
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| Summary: | Background/Aim. To assess whether the diagnostic power of longitudinal multiplanar reformat (MPR) images is superior to that of conventional horizontal images for gallbladder cancer (GBC). Methods. Between 2006 and 2010, a total of 54 consecutive patients with preoperatively diagnosed gallbladder neoplasms located in gallbladder bed were analyzed. These patients underwent cholecystectomy with resection of the adjacent liver parenchyma. The patients were divided into the GBC group (n=30) and the benign group (n=24). MPR images obtained by preoperative multidetector row CT (MDCT) were assessed. Results. Mucosal line was more significantly disrupted in GBC group than that in benign group (93% [28/30 patients] versus 13% [3/24], p<0.001). Maximum (9.3 [4.2–24.8] versus 7.0 mm [2.4–22.6], p=0.29) and minimum (1.2 [1.0–2.4] versus 1.3 mm [1.0–2.6], p=0.23) wall thicknesses on a single MPR plane did not differ significantly; however, the wall thickness ratio (max/min) differed significantly (6.8 [1.92–14.0] versus 5.83 [2.3–8.69], p=0.04). Partial liver enhancement adjacent to tumor on longitudinal images was more common in GBC (40.0% [12/30 patients] versus 12.5% [3/24], p=0.03). Mucosal line disruption was the most reliable independent predictor of diagnosis (odds ratio, 8.5; 95% CI, 5.99–28.1, p<0.001). Conclusion. Longitudinal MPR images are more useful than horizontal images for the diagnosis of GBC. |
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| ISSN: | 1687-6121 1687-630X |