Spectroscopic measurement of cartilage thickness in arthroscopy: ex vivo validation in human knee condyles.
OBJECTIVE
To evaluate the accuracy of articular cartilage thickness measurement when implementing a new technology based on spectroscopic measurement into an arthroscopic camera.


METHODS
Cartilage thickness was studied by ex vivo arthroscopy at a number of sites (N = 113) in human knee joint osteoarthritic femoral condyles and tibial plateaus, removed from 7 patients undergoing total knee replacement. The arthroscopic image spectral data at each site were used to estimate cartilage thickness. Arthroscopically derived thickness values were compared with reference cartilage thickness as measured by 3 different methods: needle penetration, spiral computed tomography scanning, and geometric measurement after sample slicing.


RESULTS
The lowest mean error (0.28 to 0.30 mm) in the regression between arthroscopic and reference cartilage thickness was seen for reference cartilage thickness less than 1.5 mm. Corresponding values for cartilage thickness less than 2.0 and 2.5 mm were 0.32 to 0.40 mm and 0.37 to 0.47 mm, respectively. Cartilage thickness images--created by pixel-by-pixel regression model calculations applied to the arthroscopic images--were derived to demonstrate the clinical use of a camera implementation.


CONCLUSIONS
On the basis of this investigation on osteoarthritic material, when one is implementing the spectroscopic method for estimating cartilage thickness into an arthroscopic camera, errors in the range of 0.28 to 0.30 mm are expected. This implementation does not, however, influence the fact that the spectral method performs less well in the cartilage thickness region from 1.5 to 2.5 mm and cannot assess cartilage thicker than 2.5 mm.


CONCLUSIONS
Imaging cartilage thickness directly in the arthroscopic camera video stream could serve as an interesting image tool for in vivo cartilage quality assessment, in connection with cartilage diagnosis, repair, and follow-up.
Department of Biomedical Engineering, Linköping University, Linköping, Sweden. anders.johansson@biooptico.com
Anders
A
Johansson
Jan-Herman
JH
Kuiper
Tommy
T
Sundqvist
Fredrik
F
Persson
Craig
C
Speier
David
D
D'Alfonso
James B
JB
Richardson
Åke
Å
Öberg
D000368:Aged; D001182:Arthroscopy / Q000379:methods*; D001837:Body Weights and Measures; D002356:Cartilage / Q000473:pathology* / Q000601:surgery*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007719:Knee Joint; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D020370:Osteoarthritis, Knee / Q000473:pathology* / Q000601:surgery*; D036542:Tomography, Spiral Computed