Abstract 18934: Surface Illumination and Autofluorescence Modeling for Assessment of Radiofrequency Ablation Lesions
Introduction: Lesion depth is a key parameter for surgical guidance of radiofrequency (RF) ablation; a common treatment of atrial fibrillation. Real-time optical techniques hold a promise to provide clinicians with immediate feedback on lesion depth. Our previous studies have revealed a strong correlation between surface-illuminated tissue autofluorescence and lesion depth. Here we use modeling and experimental approaches to understand the underlying mechanisms and determine its potential.
Methods: Porcine left atrial wall was excised and illuminated with 365nm light from the endocardium (Fig. 1.A). Emitted light was collected by a CCD camera A filter centered at 360nm ±10nm was used to collect the excitation light profile, then a tunable filter was used to collect the autofluorescence profile. A 3D Monte Carlo model simulated light transport within the tissue. Optical parameters were derived from literature and the experimental setup was modeled, generating a 365nm light distribution (Fig. 1.B). Autofluorescence was then simulated using this distribution as a source map for emitted light within the 400nm to 500nm range (Fig. 1.C).
Results: The observed intensity profile of 365nm light peaked at 0.3mm tissue depth, then exponentially declined to 37% of peak value at 0.8mm. Modelling confirmed experimental results (Fig. 1.D), indicating that autofluorescence emission may be observed several mm below the tissue surface (Fig. 1.C). Human atrial wall thickness is typically <3mm, suggesting that surface illumination methods may be sensitive to autofluorescence changes throughout the atrial wall.
Conclusions: Matched experimental and modeled data have revealed that 365nm surface illumination of porcine myocardium causes autofluorescence emission reaching several millimeters of depth. Results indicate that surface autofluorescence may be able to evaluate lesion depth during RF ablation procedures.
Author Disclosures: N. Dana: Research Grant; Modest; NIH R01EB015007. H. Asfour: Research Grant; Modest; NIH R41HL120511. S. Emelianov: Research Grant; Modest; NIH R01HL124417, NIH R01EB015007. N. Sarvazyan: Research Grant; Modest; LuxCath-GWU Research Agreement, NIH R41HL120511.
- © 2016 by American Heart Association, Inc.