An improved quantitative measurement for thyroid cancer detection based on elastography

Abstract

Objective: To evaluate color thyroid elastograms quantitatively and objectively.

Materials and methods: 125 cases (56 malignant and 69 benign) were collected with the HITACHI Vision 900 system (Hitachi Medical System, Tokyo, Japan) and a liner-array-transducer of 6-13MHz. Standard of reference was cytology (FNA-fine needle aspiration) or histology (core biopsy). The original color thyroid elastograms were transferred from red, green, blue (RGB) color space to hue, saturation, value (HSV) color space. Then, hard area ratio was defined. Finally, a SVM classifier was used to classify thyroid nodules into benign and malignant. The relation between the performance and hard threshold was fully investigated and studied.

Results: The classification accuracy changed with the hard threshold, and reached maximum (95.2%) at some values (from 144 to 152). It was higher than strain ratio (87.2%) and color score (83.2%). It was also higher than the one of our previous study (93.6%).

Conclusion: The hard area ratio is an important feature of elastogram, and appropriately selected hard threshold can improve classification accuracy.