On a mission to increase early detection of esophageal cancer, University of Colorado (CU) Cancer Center member Sachin Wani, MD, is leading a study to see if a novel diagnostic platform can help endoscopists better identify the disease in patients with a condition called Barrett’s esophagus.
Barrett’s esophagus, a premalignant condition for esophageal adenocarcinoma, occurs when the flat lining of the esophagus becomes damaged by acid reflux. The condition is diagnosed in 7% to 10% of individuals with chronic gastroesophageal reflux disease (GERD) and is estimated to be present in 1% to 2% of the general adult population.
As Barrett’s esophagus is associated with an increased risk of developing esophageal cancer, those with the condition should get regular biopsies to check for precancerous cells (known as dysplasia) or early-stage esophageal cancer. When detected early, esophageal cancer is much more treatable endoscopically than it is at later stages. Early treatment can often be performed endoscopically, where later-stage cancers usually require surgery (esophagectomy) with or without chemotherapy and radiation therapy.
“Esophageal adenocarcinoma is a highly lethal cancer with a five-year survival rate of less than 20%,” Wani says. “What is really disappointing is that despite all the advances that we’ve made, the vast majority of patients with esophageal cancer still present with advanced-stage disease.”
An AI-powered diagnostic platform
With sponsorship from medical technology company CDx Diagnostics Inc., Wani is the principal investigator on a four-year study to test the effectiveness of CDx’s advanced diagnostic platform –— WATS3D, or Wide-Area Transepithelial Sampling with computer-assisted three-dimensional analysis — vs. the current standard of care known as the Seattle biopsy protocol. Where the latter method involves obtaining random four-quadrant biopsies of the esophagus, the CDx’s unique brush instrument contains long, stiff bristles that result in the acquisition of more at-risk mucosa. Specimens will be reviewed at the company’s CLIA-certified laboratory with its patented extended depth of field imaging system and artificial intelligence-based platform that assist the pathologists in diagnostic precision. The trial will be conducted at approximately 14 centers across the U.S., including the University of Colorado Division of Gastroenterology and CU Cancer Center. The primary aim of this study is to compare the diagnostic yield of dysplasia or cancer between these two sampling methods.
“It’s a computer-assisted, three-dimensional analysis of samples that we obtain during endoscopy from the Barrett’s segment,” Wani says of the novel sampling technique. “Instead of using forceps biopsies, it’s a brush device that allows you to extensively sample the Barrett’s segment. Then, using the synthesized 3D images and neural network analyses, these samples get assessed and abnormal cells get flagged for the pathologist to look at. The goal is to find patients early in their progression, so that they can avoid having to go through chemotherapy, radiation, and esophagectomy, which are treatments we reserve for advanced-stage cancers.”
New hope for early detection
It’s important to study Barrett’s esophagus, Wani says, because it is the only identifiable premalignant condition for esophageal adenocarcinoma. Traditional endoscopy with biopsies can miss as much as 30% of patients with Barrett’s esophagus-related dysplasia or early esophageal adenocarcinoma. This study will hopefully set the stage for future studies to predict progression to esophageal cancer among patients with Barrett’s esophagus, he says.
“We are excited to be embarking on such an important study that really will impact thousands of patients that are diagnosed with Barrett’s esophagus and esophageal cancer,” Wani says. “If the study shows that this sampling method detects more patients with dysplasia and early esophageal cancer and improves outcomes this could have significant ramifications for the way we perform endoscopy in the future for this patient population.”
