MDCT of giant gastric folds: differential diagnosis.
OBJECTIVE
The purpose of this study was to evaluate the efficacy of MDCT in the differentiation of diseases involving giant gastric folds and to identify the features most useful for predicting the presence of malignant gastric disease.


METHODS
Blinded reviewers retrospectively analyzed 16-MDCT scans of 64 patients who had endoscopic findings of giant gastric folds. Thirty of these patients had histopathologic results showing scirrhous carcinoma; 15, large B-cell lymphoma; 14, acute gastric mucosal lesions; and five, Ménétrier disease. Unenhanced transparent volume-rendered images were assessed to determine the morphologic features of the whole stomach. Contrast-enhanced images were used to analyze wall thickness, stratification, enhancement pattern, and perigastric conditions. We used the Cramer phi-prime correlation coefficient to calculate the overall diagnostic accuracy of MDCT in several gastric disorders. Scatterplot analysis was used for overall diagnostic score, and analysis of the receiver operator characteristic curves of the neighboring two diseases was used to locate the cutoff values for best diagnostic accuracy. We used exact logistic regression to identify which MDCT image features were most predictive of the presence of malignant gastric disease.


RESULTS
The gastric wall was found to be significantly thicker in large B-cell lymphoma than in other disorders (p < 0.001). The overall diagnostic accuracy of MDCT in the four diseases was 100%. Loss of wall stratification was deemed the best MDCT predictor of the presence of malignancy.


CONCLUSIONS
MDCT may be a reliable means of noninvasive diagnosis in the care of patients with endoscopically detected giant gastric folds and may be useful for differentiating benign from malignant disease.
Department of Medical Imaging, Kaohsiung Medical University Hospital, Taiwan, Republic of China.
Chiao-Yun
CY
Chen
Twei-Shiun
TS
Jaw
Deng-Chyang
DC
Wu
Yu-Ting
YT
Kuo
Chien-Hung
CH
Lee
Wan-Ting
WT
Huang
Gin-Chung
GC
Liu
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001706:Biopsy; D003937:Diagnosis, Differential; D005260:Female; D005773:Gastroscopy; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011857:Radiographic Image Interpretation, Computer-Assisted; D012189:Retrospective Studies; D013272:Stomach Diseases / Q000000981:diagnostic imaging* / Q000473:pathology; D013274:Stomach Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology; D014057:Tomography, X-Ray Computed / Q000379:methods*