We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
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.
- Authors
He, Changjiu; Liu, Jieke; Hu, Shibei; Qing, Haomiao; Luo, Hongbing; Chen, Xiaoli; Liu, Ying; Zhou, Peng
- Abstract
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.
- Subjects
COMPUTED tomography; SQUAMOUS cell carcinoma; DUAL energy CT (Tomography); ALGORITHMS
- Publication
Head & Neck, 2021, Vol 43, Issue 10, p3125
- ISSN
1043-3074
- Publication type
Article
- DOI
10.1002/hed.26812