Two more radiographic signs for gastric band slippage have been identified.
Two previously unreported radiographic signs of gastric band slippage are evident on upright frontal scout radiographs, according to an article published in the American Journal of Roentgenology.
Researchers from the Alpert Medical School of Brown University in Providence, RI, and Mercy St. Vincent Medical Center in Toledo, Ohio conducted a retrospective study to compare the diagnostic performance of four radiographic signs of gastric band slippage: two previously reported findings (abnormal vertical or horizontal orientation relative to the midsagittal plane through thoracic spine, the abnormal phi angle, and visualization of the band’s central lumen, the “O” sign) and two newer findings (inferior displacement of the superolateral gastric band margin from the diaphragm by more than 2.4 cm, and the presence of an air-fluid level above the gastric band on an upright frontal radiograph obtained before barium ingestion).
Twenty-one patients (19 women) with surgically proven slipped gastric band and 63 randomly selected asymptomatic patients (53 women) with gastric band who had undergone barium swallow studies were selected for the study.
The results for positive slippage were:
“Our data suggest that our two new signs-inferior displacement of the superolateral band margin by more than 2.4 cm from the diaphragm and the presence of an air-fluid level above the band on a frontal radiograph-are more sensitive and specific for gastric band slippage than the previously described signs,” the authors wrote. “We propose that familiarity with these imaging signs of gastric band slippage will aid radiologists in diagnosing affected bariatric patients who have this important complication.”
Lunit Unveils Enhanced AI-Powered CXR Software Update
May 28th 2025The Lunit Insight CXR4 update reportedly offers new features such as current-prior comparison of chest X-rays (CXRs), acute bone fracture detection and a 99.5 percent negative predictive value (NPV) for identifying normal CXRs.
Study Suggests AI Software May Offer Standalone Value for X-Ray Detection of Pediatric Fractures
April 9th 2025Artificial intelligence (AI) software demonstrated a 92 percent sensitivity for detecting fractures in a study involving over 1,600 X-rays from a tertiary pediatric emergency department.