Epithelial Thickness Proposed as Biomarker to Guide Treatment of Barrett's Esophagus
Key findings
- In a study of 57 patients with Barrett's esophagus, applying a surface flattening and contrast enhancement algorithm to volumetric laser endomicroscopy images resulted in rapid, reliable measurements of epithelial thickness
- Interobserver agreement for measurements made with contrast-enhanced images was significantly higher than for those made with the original images, demonstrating the ability of the algorithm to clarify epithelial boundaries
- Barrett's epithelial thickness varied widely between patients and within patients, suggesting that treatment may need to be personalized to each patient and even to each segment of metaplasia
When Barrett's esophagus demonstrates transformation to early intraepithelial neoplasia, the standard treatment is radiofrequency ablation (RFA). However, the response can be incomplete in up to about half of patients, and strictures develop in up to 12%.
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Guillermo J. Tearney, MD, PhD, chief of the Massachusetts General Hospital Wellman Center for Photomedicine, and colleagues have a theory about the reasons for these poor outcomes: variations in Barrett's epithelial thickness (BET). They believe thicker BETs could result in reduced RFA efficacy and thinner BETs could result in strictures.
Dr. Tearney's group has developed an algorithm that enables a rapid, reliable measurement of BET. In Digestive Diseases and Sciences, the authors explain that their eventual aim is to correlate BET with the response to RFA so interventionists can decide whether RFA will be suitable for an individual patient.
The Use of Volumetric Laser Endomicroscopy
Volumetric laser endomicroscopy (VLE) can be used to obtain high-resolution, detailed cross-sectional images of the mucosal layers of the esophageal wall. Unfortunately, its effectiveness for measuring BET is often reduced by signal attenuation and a lack of obvious layering in Barrett's esophagus.
To improve visualization, the researchers developed an algorithm to be applied to the VLE images that flattens the mucosal surface and enhances the contrast of different esophageal wall layers.
A Nested Cohort Study
The researchers studied 57 patients with Barrett's esophagus from the U.S. VLE registry, which represents 18 study centers. These patients had a VLE scan of adequate quality prior to RFA and a Prague M length of at least 1 cm. All scans were performed between May 2015 and October 2016 using second-generation VLE probes.
The researchers measured BET at eight places on both standard and contrast-enhanced images. Three to 10 months later, they repeated the measurements.
Thickness per Patient
BET appeared to vary along the Barrett's segment of each patient. In the contrast-enhanced images, the average BET per patient ranged from 224–257 μm to 670–705 μm.
The researchers speculate that the wide range of BET between patients might help explain the variable response to RFA.
Intra- and Interobserver Agreement
The consistency of the measurements performed was considered very good:
- Intraobserver agreement: The intra-class coefficient was 0.818 (95% CI, 0.798–0.839) for the VLE expert and 0.890 (95% CI, 0.878–0.900) for the research fellow
- Interobserver agreement, contrast-enhanced images: The intra-class coefficient was 0.880 (95% CI, 0.867–0.891)
- Interobserver agreement, original images: The intra-class coefficient was 0.778 (95% CI, 0.754–0.799)
The higher interobserver agreement for contrast-enhanced images demonstrates the capability of the algorithm to clarify Barrett's esophagus epithelial boundaries in VLE images.
Toward the Future
Dr. Tearney and his colleagues have research underway to correlate BET with treatment response. If they can find associations, BET could be used to determine in real-time whether fixed-dose RFA is appropriate or whether a deeper therapy, such as cryoablation or endoscopic mucosal resection, should be used. The researchers are also working to automate the measurement of mean BET per patient.
The variability in BETs among and within patients suggests that treatment may need to be personalized to each patient or even to each segment. Once an automated system is available, it could be integrated into the RFA catheter to give precisely the right dose in each location, with the goals of achieving optimal ablation depth, improved treatment response and fewer strictures.
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