The effect of surface roughness on the Er:YAG laser-induced photoacoustic removal of bacteria in zero-gap periodontal/peri-implant pocket model - Dominik Šavli; Marko Volk; Katja Molan; Saša Terlep; Špela Levičnik-Höfferle; Aleš Babnik; Mojca Trost; Boris Gašpirc; Matjaž Lukač; David Stopar; Matija Jezeršek (Ultrasonics Sonochemistry, 2025)
Effective biofilm removal from periodontal and peri-implant pockets remains a challenge due to constrained geometry and limited access. This study investigates a novel phenomenon of distant-field cleaning utilizing Er:YAG laser treatment, where removal of bacteria occurs in areas without previously observed cavitation under high-speed imaging. To understand this effect, we developed a transparent zero-gap model simulating a tooth or implant and surrounding soft tissue. We systematically examined the impact of laser fiber insertion depth, cavitation bubble dynamics, the stiffness and roughness of the material, and laser parameters on the cleaning efficiency.Our findings reveal that the removal of bacteria indeed correlates strongly with cavitation occurrence. Deeper optical fiber insertion into the pocket model only enhanced cleaning efficiency by moving the fluid dynamics and enabling deeper water penetration. Surprisingly, high-speed imaging showed no cavitation in distant regions, raising questions about the mechanisms enabling such cleaning. Further investigation uncovered that surface roughness played a critical role in facilitating this distant-field effect. The smooth, transparent surfaces used in imaging experiments suppressed fluid dynamics, while textured surfaces created by 3D-printed molds and bacterial monolayer allowed deeper water penetration and pressure wave propagation. These surface irregularities enabled localized cavitation events and enhanced bacterial disruption, even in regions beyond the laser fiber’s immediate influence.This study emphasizes the significance of surface roughness in test models, highlighting the need for models to closely mimic the conditions of real clinical scenarios for accurate optimization of Er:YAG laser-induced photoacoustic removal of bacteria.