Evaluation Of Spectral Discriminant Functions For Guidance Of Laser Angioplasty

Abstract

ABSTRACT Development of a clinically acceptable laser angioplasty system has been hindered by the inability to adequately guide ablative laser radiation to atherosclerotic plaque. Low power laser-induced fluorescence spectroscopy is capable of discriminating normal and atherosclerotic arterial tissue. The purpose of this investigation was to develop and evaluate several spectral classification algorithms that would enable discrimination of atherosclerotic and normal arterial tissue by a computer controlled fluorescence guided laser angioplasty system. 1. INTRODUCTION Development of a clinically acceptable laser angioplasty system has been hindered by the risk of vessel perforation due to laser ablation of normal arterial wall1 . Although several imaging modalities, including fluoroscopy2'3, angioscopy4'5, and high frequency ultrasound6 have been investigated as potential guidance mechanisms, none of these imaging techniques have enabled selective ablation of atherosclerotic plaque. Laser-induced arterial fluorescence spectroscopy has been suggested as an alternative means of laser angioplasty guidance^-lO. A smart laser angioplasty system containing a low power laser could sample arterial fluorescence between ablative laser pulses and use the spectral information to selectively guide plaque ablation. Such a system would require spectral classification algorithms capable of online arterial tissue discrimination. The focus of this study was to develop and evaluate several spectral classification algorithms for this purpose.