Quantitative Assessment of Thyroid Nodules Using Dual-Energy Computed Tomography: Iodine Concentration Measurement and Multiparametric Texture Analysis for Differentiating between Malignant and Benign Lesions

Hayato Tomita; Hirofumi Kuno; Kotaro Sekiya; Katharina Otani; Osamu Sakai; Baojun Li; Takashi Hiyama; Keiichi Nomura; Hidefumi Mimura; Tatsushi Kobayashi

doi:10.1155/2020/5484671

Quantitative Assessment of Thyroid Nodules Using Dual-Energy Computed Tomography: Iodine Concentration Measurement and Multiparametric Texture Analysis for Differentiating between Malignant and Benign Lesions

Int J Endocrinol. 2020 Mar 18:2020:5484671. doi: 10.1155/2020/5484671. eCollection 2020.

Authors

Affiliations

¹ Department of Diagnostic Radiology, National Cancer Center Hospital East, Chiba 277-8577, Japan.
² Department of Radiology, St. Marianna University School of Medicine, Kawasaki 216-8511, Japan.
³ AT Innovation Department, Siemens Healthcare K. K., Tokyo 141-8644, Japan.
⁴ Department of Radiology, Boston Medical Center, Boston University School of Medicine, Boston 02118, USA.

Abstract

Results: The 34 nodules comprised 14 benign nodules and 20 malignant nodules. Iodine content and Hounsfield unit curve slopes did not differ significantly between benign and malignant thyroid nodules (P = 0.480-0.670). However, significant differences in the texture features of monochromatic images were observed between benign and malignant nodules: histogram mean and median, co-occurrence matrix contrast, gray-level gradient matrix (GLGM) skewness, and mean gradients and variance of gradients for GLGM at 80 keV (P = 0.014-0.044). The highest AUC was 0.77, for the histogram mean and median of images acquired at 80 keV.

Conclusions: Texture features extracted from monochromatic images using DECT, specifically acquired at high keV, may be a promising diagnostic approach for thyroid nodules. A further large study for incidental thyroid nodules using DECT texture analysis is required to validate our results.