WATS for Barrett's surveillance

Wide-area transepithelial sampling for dysplasia detection in Barrett's esophagus: a systematic review and meta-analysis

BACKGROUND AND AIMS

Seattle protocol forceps biopsy sampling (FB) is currently recommended for surveillance in Barrett's esophagus (BE) but limited by sampling error and lack of compliance. Wide-area transepithelial sampling with 3-dimensional analysis (WATS3D; CDx Diagnostics, Suffern, NY, USA) is reported to increase BE dysplasia detection. We assessed the incremental yield and clinical significance of WATS3D for dysplasia detection over FB in a systematic review and meta-analysis.

METHODS

We queried major scientific databases for studies using WATS3D and FB from 2000 to 2020. The primary outcome was the incremental yield of WATS3D-detected dysplasia (defined as a composite of indefinite for dysplasia, low- and high-grade dysplasia [HGD] and esophageal adenocarcinoma [EAC]) over FB. Secondary outcomes were incremental yields of HGD/EAC and rate of reconfirmation of WATS3D dysplasia on subsequent FB.

RESULTS

Meta-analysis of 7 eligible studies demonstrated that FB diagnosed dysplasia in 15.9% of cases, whereas the incremental yield with WATS3D was 7.2% (95% confidence interval, 3.9%-11.5%; I²= 92.1%). Meta-analysis of 6 studies demonstrated that FB diagnosed HGD/EAC in 2.3% of patients, whereas the incremental yield with WATS3D was 2.1% (95% confidence interval, .4%-5.3%; I²= 92.7%). Notably, WATS3D was negative in 62.5% of cases where FB identified dysplasia. Two studies reported reconfirmation of WATS3D dysplasia with FB histology in only 20 patients.

CONCLUSIONS

WATS3D increases dysplasia detection; however, the clinical significance of this increased dysplasia detection remains uncertain. Data from endoscopic follow-up to ascertain FB histology in patients with dysplasia based solely on WATS3D are needed to determine the optimal clinical application and significance of WATS3D-only dysplasia.

Artificial Intelligence and Its Role in Identifying Esophageal Neoplasia

Randomized trials have demonstrated that ablation of dysplastic Barrett's esophagus can reduce the risk of progression to cancer. Endoscopic resection for early stage esophageal adenocarcinoma and squamous cell carcinoma can significantly reduce postoperative morbidity compared to esophagectomy. Unfortunately, current endoscopic surveillance technologies (e.g., high-definition white light, electronic, and dye-based chromoendoscopy) lack sensitivity at identifying subtle areas of dysplasia and cancer. Random biopsies sample only approximately 5% of the esophageal mucosa at risk, and there is poor agreement among pathologists in identifying low-grade dysplasia. Machine-based deep learning medical image and video assessment technologies have progressed significantly in recent years, enabled in large part by advances in computer processing capabilities. In deep learning, sequential layers allow models to transform input data (e.g., pixels for imaging data) into a composite representation that allows for classification and feature identification. Several publications have attempted to use this technology to help identify dysplasia and early esophageal cancer. The aims of this reviews are as follows: (a) discussing limitations in our current strategies to identify esophageal dysplasia and cancer, (b) explaining the concepts behind deep learning and convolutional neural networks using language appropriate for clinicians without an engineering background, (c) systematically reviewing the literature for studies that have used deep learning to identify esophageal neoplasia, and (d) based on the systemic review, outlining strategies on further work necessary before these technologies are ready for "prime-time," i.e., use in routine clinical care.

Imaging for Barrett's esophagus: state of the art

PURPOSE OF REVIEW

Barrett's esophagus is the premalignant condition for esophageal cancer and the diagnosis of esophageal adenocarcinoma on index endoscopy is increasing. Many advanced endoscopic techniques are available and aim to identify Barrett's esophagus-associated neoplasia earlier, thereby preventing progression into malignancy.

RECENT FINDINGS

It is well established adherence to Seattle protocol increases dysplasia detection but leaves large portions of mucosa unsampled. Recent attention has been given to wide-area transepithelial sampling as an additional means of biopsy and shows increased dysplasia detection rates. Many endoscopic techniques aim to increase the success of diagnosis of Barrett's esophagus-associated neoplasia, including probe confocal endomicroscopy, volumetric laser endomicroscopy, and virtual chromoendoscopy. Interestingly, volumetric laser endomicroscopy may also be useful in delineating margins during endoscopic mucosal resection, leading to both diagnostic and therapeutic applications.

SUMMARY

Advanced endoscopic techniques are available to increase detection of Barrett's esophagus-associated neoplasia; however, these remain localized to academic centers of excellence. With recent advancements in both sampling techniques and the potential application of imaging to therapeutics, these techniques are becoming more accessible to community endoscopists.