应用噪声优化虚拟单能量图像和非线性融合图像算法改善双能 CT 下喉鳞状细胞癌的图像质量。
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.
机构信息
Department of Radiology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
出版信息
Head Neck. 2021 Oct;43(10):3125-3131. doi: 10.1002/hed.26812. Epub 2021 Jul 16.
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.
背景
双能 CT（DECT）已被用于改善头颈部鳞状细胞癌（SCC）的图像质量。本研究旨在评估线性混合图像（LBI）、非线性混合图像（NBI）和噪声优化虚拟单能量图像（VMI+）算法在喉 SCC 中的图像质量。
方法
回顾性纳入 2019 年 6 月至 2020 年 12 月期间的 34 例喉 SCC 患者。使用 LBI（80kV 和 M_0.6）、NBI 和 VMI+（40 和 55keV）算法对 DECT 图像进行重建。评估并比较了对比噪声比（CNR）、肿瘤勾画和整体图像质量。
结果
VMI+（40keV）的 CNR 最高，肿瘤勾画优于 VMI+（55keV）、LBI 和 NBI，而 NBI 的整体图像质量优于 VMI+和 LBI（所有校正后 p<0.05）。
结论
VMI+（40keV）和 NBI 可改善喉 SCC 的图像质量，在 DECT 检查中可能更优。
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