title: Multiparameter classifications of optical tomographic images.
abstract: This research study explores the combined use of more than one parameter derived from optical tomographic images to increase diagnostic accuracy which is measured in terms of sensitivity and specificity. Parameters considered include, for example, smallest or largest absorption or scattering coefficients or the ratios thereof in an image region of interest. These parameters have been used individually in a previous study to determine if a finger joint is affected or not affected by rheumatoid arthritis. To combine these parameters in the analysis we employ here a vector quantization based classification method called Self-Organizing Mapping (SOM). This method allows producing multivariate ROC-curves from which sensitivity and specificities can be determined. We found that some parameter combinations can lead to higher sensitivities whereas others to higher specificities when compared to singleparameter classifications employed in previous studies. The best diagnostic accuracy, in terms of highest Youden index, was achieved by combining three absorption parameters [maximum(micro a), minimum(micro a), and the ratio of minimum(micro a) and maximum(micro a)], which result in a sensitivity of 0.78, a specificity of 0.76, a Youden index of 0.54, and an area under the curve (AUC) of 0.72. These values are higher than for previously reported single parameter classifications with a best sensitivity and specificity of 0.71, a Youden index of 0.41, and an AUC of 0.66.
authors.affiliation: Columbia University, Department of Biomedical Engineering, New York, New York 10027, USA. ck2204@columbia.edu
authors.forename: Christian D
authors.initials: CD
authors.lastname: Klose
authors.forename: Alexander D
authors.initials: AD
authors.lastname: Klose
authors.forename: Uwe
authors.initials: U
authors.lastname: Netz
authors.forename: Juergen
authors.initials: J
authors.lastname: Beuthan
authors.forename: Andreas H
authors.initials: AH
authors.lastname: Hielscher
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D041622:Tomography, Optical / Q000379:methods*