"Tissue post-classification using the measured acoustic signals during 355 nm laser atherectomy procedures".

The current laser atherectomy technologies to treat patients with challenging (to-cross) total chronic occlusions with a step-by-step (SBS) approach (without leading guide wire ), are lacking real-time signal monitoring of the ablated tissues, and carry the risk for vessel perforation. We present first time post-classification of ablated tissues using acoustic signals recorded by a microphone placed nearby during five atherectomy procedures using 355 nm solid-state Auryon™ laser device performed with an SBS approach, some with highly severe calcification. Using our machine learning algorithm, the classification results of these ablation signals recordings from five patients showed 93.7% classification accuracy with arterial vs. non-arterial wall material. While still very preliminary and requiring a larger study and thereafter as commercial device, the results of these first acoustic post-classification in SBS cases are very promising. This study implies, as a general statement, that on-line recording of the acoustic signals using a non-contact microphone, may potentially serve for an on-line classification of the ablated tissue in SBS cases. This technology could be used to confirm correct positioning in the vasculature, and by this, to potentially further reduce the risk of perforation using 355 nm laser atherectomy in such procedures. This article is protected by copyright. All rights reserved.