Tissue discrimination by uncorrected autofluorescence spectra

TY - JOUR

T1 - Tissue discrimination by uncorrected autofluorescence spectra

T2 - a proof-of-principle study for tissue-specific laser surgery

AU - Stelzle, Florian

AU - Knipfer, Christian

AU - Adler, Werner

AU - Rohde, Maximilian

AU - Oetter, Nicolai

AU - Nkenke, Emeka

AU - Schmidt, Michael

AU - Tangermann-Gerk, Katja

PY - 2013/10/11

Y1 - 2013/10/11

N2 - Laser surgery provides a number of advantages over conventional surgery. However, it implies large risks for sensitive tissue structures due to its characteristic non-tissue-specific ablation. The present study investigates the discrimination of nine different ex vivo tissue types by using uncorrected (raw) autofluorescence spectra for the development of a remote feedback control system for tissue-selective laser surgery. Autofluorescence spectra (excitation wavelength 377 ± 50 nm) were measured from nine different ex vivo tissue types, obtained from 15 domestic pig cadavers. For data analysis, a wavelength range between 450 nm and 650 nm was investigated. Principal Component Analysis (PCA) and Quadratic Discriminant Analysis (QDA) were used to discriminate the tissue types. ROC analysis showed that PCA, followed by QDA, could differentiate all investigated tissue types with AUC results between 1.00 and 0.97. Sensitivity reached values between 93% and 100% and specificity values between 94% and 100%. This ex vivo study shows a high differentiation potential for physiological tissue types when performing autofluorescence spectroscopy followed by PCA and QDA. The uncorrected autofluorescence spectra are suitable for reliable tissue discrimination and have a high potential to meet the challenges necessary for an optical feedback system for tissue-specific laser surgery.

AB - Laser surgery provides a number of advantages over conventional surgery. However, it implies large risks for sensitive tissue structures due to its characteristic non-tissue-specific ablation. The present study investigates the discrimination of nine different ex vivo tissue types by using uncorrected (raw) autofluorescence spectra for the development of a remote feedback control system for tissue-selective laser surgery. Autofluorescence spectra (excitation wavelength 377 ± 50 nm) were measured from nine different ex vivo tissue types, obtained from 15 domestic pig cadavers. For data analysis, a wavelength range between 450 nm and 650 nm was investigated. Principal Component Analysis (PCA) and Quadratic Discriminant Analysis (QDA) were used to discriminate the tissue types. ROC analysis showed that PCA, followed by QDA, could differentiate all investigated tissue types with AUC results between 1.00 and 0.97. Sensitivity reached values between 93% and 100% and specificity values between 94% and 100%. This ex vivo study shows a high differentiation potential for physiological tissue types when performing autofluorescence spectroscopy followed by PCA and QDA. The uncorrected autofluorescence spectra are suitable for reliable tissue discrimination and have a high potential to meet the challenges necessary for an optical feedback system for tissue-specific laser surgery.

KW - Algorithms

KW - Animals

KW - Laser Therapy

KW - Pattern Recognition, Automated

KW - Pilot Projects

KW - Spectrometry, Fluorescence

KW - Surgery, Computer-Assisted

KW - Swine

KW - Tissue Array Analysis

KW - Journal Article

KW - Research Support, Non-U.S. Gov't

U2 - 10.3390/s131013717

DO - 10.3390/s131013717

M3 - SCORING: Journal article

C2 - 24152930

VL - 13

SP - 13717

EP - 13731

JO - SENSORS-BASEL

JF - SENSORS-BASEL

SN - 1424-8220

IS - 10

ER -