Low risk of prevalent submucosal invasive cancer among patients undergoing esophagectomy for treatment of Barrett's esophagus with high grade dysplasia

A Multiscale Model Evaluates Screening for Neoplasia in Barrett's Esophagus

Barrett’s esophagus (BE) patients are routinely screened for high grade dysplasia (HGD) and esophageal adenocarcinoma (EAC) through endoscopic screening, during which multiple esophageal tissue samples are removed for histological analysis. We propose a computational method called the multistage clonal expansion for EAC (MSCE-EAC) screening model that is used for screening BE patients in silico to evaluate the effects of biopsy sampling, diagnostic sensitivity, and treatment on disease burden. Our framework seamlessly integrates relevant cell-level processes during EAC development with a spatial screening process to provide a clinically relevant model for detecting dysplastic and malignant clones within the crypt-structured BE tissue. With this computational approach, we retain spatio-temporal information about small, unobserved tissue lesions in BE that may remain undetected during biopsy-based screening but could be detected with high-resolution imaging. This allows evaluation of the efficacy and sensitivity of current screening protocols to detect neoplasia (dysplasia and early preclinical EAC) in the esophageal lining. We demonstrate the clinical utility of this model by predicting three important clinical outcomes: (1) the probability that small cancers are missed during biopsy-based screening, (2) the potential gains in neoplasia detection probabilities if screening occurred via high-resolution tomographic imaging, and (3) the efficacy of ablative treatments that result in the curative depletion of metaplastic and neoplastic cell populations in BE in terms of the long-term impact on reducing EAC incidence.

Endoscopic screening for detecting cancer and cancer precursors in Barrett’s esophagus (BE) is currently informed by repeated systematic biopsying of the metaplastic BE tissue. Here we present a comprehensive multiscale model of the natural history of esophageal adenocarcinoma (EAC), which describes the entire multistage process beginning with the conversion event of normal squamous esophageal tissue to BE metaplasia, the spatio-temporal formation of independent dysplastic and malignant clones at the cell level, and finally the appearance of symptomatic EAC in BE. This model lends itself to a systematic exploration of the efficacy and sensitivity of current biopsy-based screening methods to detect neoplasia in BE patients, as well as alternative screening techniques based on high-resolution imaging of the BE tissue. Moreover, the model can also be used to predict the impact of ablative treatments on the risk of occurrence or recurrence of dysplasia or cancer. Due to the lack of studies that attempt to explicitly model the physical and biological dimensions of the screening process itself, our computational model provides a unique, publicly-available tool to improve understanding of factors that limit the efficacy of current screening protocols for BE patients.