Introduction: EUS is an accurate means of evaluating and diagnosing submucosal lesions of the GI tract. The aim of this study was to prospectively determine interobserver agreement for the EUS classification of submucosal masses among endosonographers with different levels of training and experience from multiple centers. Methods: Twenty patients with submucosal mass lesions diagnosed by upper endoscopy underwent EUS. Surgical findings were available for 16 patients. In 4 patients with obvious cystic/vascular structures (i.e., varices) no surgical specimen was necessary. A blinded observer developed a study videotape of critical endoscopic and EUS real-time imaging for each lesion. The videotape was distributed to 10 endosonographers, each with at least 1 year of experience, who independently reviewed the videotape and recorded their diagnosis based on EUS features. These endosonographers used previously agreed-upon standardized EUS diagnostic criteria for each category of lesion. A kappa (κ) statistic, used to evaluate agreement, was calculated for each lesion category for the 10 endosonographers as a group and individually. An overall kappa statistic was also calculated. Significance was analyzed with a two-tailed t test. Results: Agreement was excellent for cystic lesions (κ = 0.80) and extrinsic compressions (κ = 0.94), good for lipoma (κ = 0.65), fair for leiomyoma and vascular lesions (κ = 0.53 and 0.54, respectively), and poor for other submucosal lesions (κ = 0.34). Overall agreement among observers was good (κ = 0.63). Furthermore, a significant association was noted between total years of EUS experience and the number of correct answers (p = 0.01). Conclusions: Interobserver agreement is good for characterizing submucosal masses by EUS. However, it appears to be better for some lesions than others. The overall length of experience with EUS appears to play an important role in the accuracy of this modality in the evaluation of submucosal lesions.
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging