Klose Christian D, Klose Alexander D, Netz Uwe, Beuthan Juergen, Hielscher Andreas H
Columbia University, Department of Biomedical Engineering, New York, New York 10027, USA.
J Biomed Opt. 2008 Sep-Oct;13(5):050503. doi: 10.1117/1.2981806.
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.
本研究探讨了利用光学断层图像中的多个参数来提高诊断准确性，诊断准确性通过灵敏度和特异度来衡量。所考虑的参数包括，例如，感兴趣图像区域中的最小或最大吸收系数或散射系数及其比率。在之前的一项研究中，这些参数已被单独用于确定手指关节是否受类风湿性关节炎影响。为了在分析中组合这些参数，我们在此采用一种基于矢量量化的分类方法，称为自组织映射（SOM）。该方法允许生成多元ROC曲线，从中可以确定灵敏度和特异度。我们发现，与之前研究中使用的单参数分类相比，一些参数组合可导致更高的灵敏度，而其他参数组合则可导致更高的特异度。就最高约登指数而言，通过组合三个吸收参数[最大（微观a）、最小（微观a）以及最小（微观a）与最大（微观a）的比率]可实现最佳诊断准确性，其灵敏度为0.78，特异度为0.76，约登指数为0.54，曲线下面积（AUC）为0.72。这些值高于之前报道的单参数分类，其最佳灵敏度和特异度为0.71，约登指数为0.41，AUC为0.66。
