Noncontact photoacoustic spectroscopy (NCPAS) for photoablation control: data acquisition and analysis using cluster analysis

Abstract

Laser photoablation using UV or JR lasers is known to trigger a photo acoustic event. Different target materials can be discriminated by analyzing the photoacoustic signal. In vitro measurements ofNCPAS have revealed the necessity to integrate a number of variable elements (tissue hydration, fluence, laser beam diameter, distance to microphone, etc.). This study defines the parameters needed for the initiation of a seiflearning system for target material recognition. A UV Excimer laser (X=193 nm; Summit Technology, UV 200L) was used to ablate organic polymers (PMMA, PA, PVC), normal and porcine corneal scar tissue, and human cornea in vivo. NCPAS was performed using a microphone (up to 200 kHz) as a detector. During photoablation, the acoustic signal was analyzed by a multiport A/D IBM PC based digital oscilloscope. The data obtained were imported into a Matlab language program and analyzed.NCPAS allows the discrimination of different materials by a characteristically frequency shift of the photoacoustic signal. Detection and online material recognition using NCPAS is a step on the way to a <smart> laser control, based on an artificial neuronal network.

Mechanisms of Pulsed Laser Ablation of Biological Tissues

“…Researchers first sought to achieve selective ablation by making use of intrinsic differences in the optical properties of the tissues involved. − Later, online monitoring and active feedback techniques were introduced to discriminate between different tissue types and to automatically stop the ablation procedure when the transition between the layers is reached. Such techniques include the analysis of the acoustic transients in air generated during ablation, ,− fluorescence spectroscopy for discrimination between plaque and vessel wall, plasma spectroscopy to distinguish between bone and nerve tissue, and analysis of the cavitation bubble dynamics at the fiber tip for controlled sclera perforation in glaucoma surgery. , 388…”

Low-Cost Laser-Acoustic PVC Identification System Based on a Simple Neural Network

“…Furthermore, the results have revealed for the first time that also material-specific, laser-ablative acoustic signals can be generated with a low-power laser diode. In contrast to previous work [ 7 , 8 , 9 , 10 , 11 , 12 , 16 , 17 , 18 , 19 ], however, this is only possible to a limited extent: the laser radiation must be very strongly focused to achieve the required area-related fluence. The individual pulses are also longer than in previous works to introduce sufficient energy.…”

“…The potential of this technology for on-line process control or material discrimination was then recognized [ 7 ] and further investigated [ 8 , 9 , 10 ] by a research group at an ophthalmology clinic in Germany. They showed in [ 9 ] a successful material discrimination for biological tissue but also for three sorts of plastic (including PVC) by using cluster analysis in the frequency domain. In a more recent work, a discrimination accuracy between two sorts of plastic of 98 % was achieved with the cosine similarity technique [ 10 ].…”