(PR37) Clinical Augmented Reality and Artificial Intelligence (CLARAi) to measure and localize cortical changes of brain in an odontogenic pain model of Endodontic origin

Humanity has continually struggled with the anxiety and pain associated with invasive dental procedures such as endodontic treatment. For many years, clinicians have been seeking objective pain assessment solutions via neuroimaging techniques focusing on the brain to detect pain. Unfortunately, most of those techniques are not applicable in the clinical environment or lack accuracy. This study examined subjects with symptomatic apical periodontitis in an endodontically involved tooth with the goal of determining the accuracy of quantifying and mapping ongoing dental pain and its mild evoked stimulation (percussion). To correlate the clinical status i.e. pain and anxiety with the functional connectivity of brain, to further discriminate anxiety from pain, and immediate relief of pain by local anesthesia administration based on patients’ somatosensory and pre-frontal cortex hemodynamic activation and connectivity.

Methods: Clinical dental pain was triggered in patients (n=24) by tooth stimulation with eight consecutive percussions. We used a portable optical neuroimaging technology and functional near-infrared spectroscopy to gauge the cortical activity during evoked acute dental pain. The data is decoded using a neural network (NN)–based AI algorithm to classify hemodynamic response data into pain and no-pain brain states in real time. Results were presented according to CLARAi (Clinical augmented reality and artificial intelligence), which reliably supports visualization, as well as precisely measuring and localizing ongoing/evoked pain, anxiety and relief of clinical dental pain and associated anxiety, directly from the patient’s brain.