Abstract
ObjectiveTo explore a new method for color image analysis of ultrasomics and investigate the efficiency in differentiating focal liver lesions (FLLs) by Red, Green, and Blue (RGB) three-channel SWE-based ultrasomics model.MethodsOne hundred thirty FLLs were randomly divided into training set (n = 65) and validation set (n = 65). The RGB three-channel and direct conversion methods were applied to the same color SWE images. Ultrasomics features were extracted from the preprocessing images establishing two feature data sets. The least absolute shrinkage and selection operator (LASSO) logistic regression model was applied for feature selection and model construction. Two models, named RGB model (based on RGB three-channel conversion) and direct model (based on direct conversion), were used to differentiate FLLs. The diagnosis performance of the two models was evaluated by area under the curve (AUC), calibration curves, decision curves, and net reclassification index (NRI).ResultsIn the validation cohort, the AUC of the direct model and RGB model in characterization on FLLs were 0.813 and 0.926, respectively (p = 0.038). Calibration curves and decision curves indicated that the RGB model had better calibration efficiency and provided greater clinical benefits. NRI revealed that the RGB model correctly reclassified 7% of malignant cases and 25% of benign cases compared to the direct model (p = 0.01).ConclusionThe RGB model generated by RGB three-channel method yielded better diagnostic efficiency than the direct model established by direct conversion method. The RGB three-channel method may be promising on ultrasomics analysis of color images in clinical application.
Highlights
Shear-wave elastography (SWE), as an elasticity-based US technique, is widely used in lesion characterization and liver stiffness assessment [1,2,3,4]
Forty focal liver lesions (FLLs) were benign with focal nodular hyperplasia (n = 8), hemangioma (n = 27), and inflammatory pseudotumor (n = 5)
The results showed that Random Forest (RF) (AUC = 0.813 and 0.926 for direct model and RGB model, respectively) outperformed the other classifiers
Summary
Shear-wave elastography (SWE), as an elasticity-based US technique, is widely used in lesion characterization and liver stiffness assessment [1,2,3,4]. According to human’s sensitivity to the R, G, and B colors, Lightness, which is based on the formula of gray intensity = 0.2126R + 0.7152G + 0.0722B, more closely corresponds to human perception and preferable in color image conversion, which is achieved via a nonlinear transformation of the RGB color space. It is not a lossless method for color to grayscale image conversion, which suffers from a domain shifting problem due to the overlaps of Red, Green, and Blue (RGB) channel values [9, 10]. The drawback of the latter method was that information about the object’s location, shape and texture are discarded
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