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Improvement of image quality of laryngeal squamous cell carcinoma using noise‐optimized virtual monoenergetic image and nonlinear blending image algorithms in dual‐energy computed tomography
Author(s) -
He Changjiu,
Liu Jieke,
Hu Shibei,
Qing Haomiao,
Luo Hongbing,
Chen Xiaoli,
Liu Ying,
Zhou Peng
Publication year - 2021
Publication title -
head and neck
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.012
H-Index - 127
eISSN - 1097-0347
pISSN - 1043-3074
DOI - 10.1002/hed.26812
Subject(s) - image quality , digital enhanced cordless telecommunications , contrast to noise ratio , physics , image noise , algorithm , nuclear medicine , image (mathematics) , medicine , computer science , artificial intelligence , telecommunications , wireless
Background Dual‐energy computed tomography (DECT) has been used to improve image quality of head and neck squamous cell carcinoma (SCC). This study aimed to assess image quality of laryngeal SCC using linear blending image (LBI), nonlinear blending image (NBI), and noise‐optimized virtual monoenergetic image (VMI+) algorithms. Methods Thirty‐four patients with laryngeal SCC were retrospectively enrolled between June 2019 and December 2020. DECT images were reconstructed using LBI (80 kV and M_0.6), NBI, and VMI+ (40 and 55 keV) algorithms. Contrast‐to‐noise ratio (CNR), tumor delineation, and overall image quality were assessed and compared. Results VMI+ (40 keV) had the highest CNR and provided better tumor delineation than VMI+ (55 keV), LBI, and NBI, while NBI provided better overall image quality than VMI+ and LBI (all corrected p < 0.05). Conclusions VMI+ (40 keV) and NBI improve image quality of laryngeal SCC and may be preferable in DECT examination.