Department of Diagnostic and Interventional Radiology, Eberhard-Karls University, Hoppe-Seyler-Str. 3, 72076 Tuebingen, Germany.
Department of Diagnostic and Interventional Radiology, Eberhard-Karls University, Hoppe-Seyler-Str. 3, 72076 Tuebingen, Germany.
Eur J Radiol. 2024 Sep;178:111523. doi: 10.1016/j.ejrad.2024.111523. Epub 2024 May 22.
Neck computed tomography (NCT) is essential for diagnosing suspected neck tumors and abscesses, but radiation exposure can be an issue. In conventional reconstruction techniques, limiting radiation dose comes at the cost of diminished diagnostic accuracy. Therefore, this study aimed to evaluate the effects of an AI-based denoising post-processing software solution in low-dose neck computer tomography.
From 01 September 2023 to 01 December 2023, we retrospectively included patients with clinically suspected neck tumors from the same single-source scanner. The scans were reconstructed using Advanced Modeled Iterative Reconstruction (Original) at 100% and simulated 50% and 25% radiation doses. Each dataset was post-processed using a novel denoising software solution (Denoising). Three radiologists with varying experience levels subjectively rated image quality, diagnostic confidence, sharpness, and contrast for all pairwise combinations of radiation dose and reconstruction mode in a randomized, blinded forced-choice setup. Objective image quality was assessed using ROI measurements of mean CT numbers, noise, and a contrast-to-noise ratio (CNR). An adequately corrected mixed-effects analysis was used to compare objective and subjective image quality.
At each radiation dose level, pairwise comparisons showed significantly lower image noise and higher CNR for Denoising than for Original (p < 0.001). In subjective analysis, image quality, diagnostic confidence, sharpness, and contrast were significantly higher for Denoising than for Original at 100 and 50 % (p < 0.001). However, there were no significant differences in the subjective ratings between Original 100 % and Denoising 25 % (p = 0.906).
The investigated denoising algorithm enables diagnostic-quality neck CT images with radiation doses reduced to 25% of conventional levels, significantly minimizing patient exposure.
颈部计算机断层扫描（NCT）对于诊断疑似颈部肿瘤和脓肿至关重要，但辐射暴露可能是一个问题。在传统的重建技术中，限制辐射剂量会降低诊断准确性。因此，本研究旨在评估一种基于人工智能的降噪后处理软件解决方案在低剂量颈部计算机断层扫描中的效果。
从 2023 年 9 月 1 日至 2023 年 12 月 1 日，我们回顾性地纳入了来自同一单源扫描仪的临床疑似颈部肿瘤患者。扫描使用高级模型迭代重建（原始）以 100%和模拟 50%和 25%的辐射剂量进行重建。每个数据集都使用一种新的降噪软件解决方案（降噪）进行后处理。三位经验水平不同的放射科医生在随机、盲法、强制选择的设置中对所有辐射剂量和重建模式的配对组合进行了图像质量、诊断信心、清晰度和对比度的主观评估。使用 ROI 测量平均 CT 数、噪声和对比噪声比（CNR）来评估客观图像质量。使用充分校正的混合效应分析来比较客观和主观的图像质量。
在每个辐射剂量水平，配对比较显示，与原始相比，降噪的图像噪声明显降低，对比度噪声比（CNR）明显升高（p<0.001）。在主观分析中，与原始相比，降噪在 100%和 50%（p<0.001）时的图像质量、诊断信心、清晰度和对比度均显著更高。然而，原始 100%和降噪 25%之间的主观评分没有显著差异（p=0.906）。
该研究的去噪算法可以在将辐射剂量降低到常规水平的 25%的情况下获得具有诊断质量的颈部 CT 图像，显著减少患者的辐射暴露。
