Resonant frequency analysis of dental implants

TL;DR

This study uses numerical modeling to analyze how resonant frequency analysis can indicate the healing process of dental implants, highlighting its limitations and proposing a new healing factor for early detection.

Contribution

The paper introduces a numerical approach to assess the sensitivity of resonant frequency analysis to bone healing around dental implants and proposes a normalized healing factor for early-stage detection.

Findings

Resonant frequency is insensitive to healing unless the weakened layer is large.

A normalized healing factor can identify early healing stages.

Sensitivity of RFA to bone property changes is relatively weak.

Abstract

Dental implant stability influences the decision on the determination of the duration between implant insertion and loading, This work investigates the resonant frequency analysis by means of a numerical model. The investigation is done numerically through the determination of the eigenfrequencies and performing a steady state response analyses using a commercial finite element package. A peri-implant interface, of simultaneously varying stiffness (density) and layer thickness is introduced in the numerical 3D model in order to probe the sensitivity of the eigenfrequencies and steady state response to an evolving weakened layer, in an attempt to identify the bone reconstruction around the implant. For the first two modes, the resonant frequency is somewhat insensitive to the healing process, unless the weakened layer is rather large and compliant, like in the very early stages of the implantation. A "Normalized Healing Factor" is devised in the spirit of the Implant Stability Quotient, which can identify the healing process especially at the early stages after implantation. The sensitivity of the RFA to changes of mechanical properties of periprosthetic bone tissue seems relatively weak. Another indicator considering the amplitude as well as the resonance frequency might be more adapted to bone healing estimations. However, these results need to be verified experimentally as well as clinically.