Background: We aimed at improving image quality (IQ) of sparse-view computed tomography (CT) images using a U-Net for lung metastasis detection and determining the best tradeoff between number of views, IQ, and diagnostic confidence. Methods: CT images from 41 subjects aged 62.8 $\pm$ 10.6 years (mean $\pm$ standard deviation), 23 men, 34 with lung metastasis, 7 healthy, were retrospectively selected (2016-2018) and forward projected onto 2,048-view sinograms. Six corresponding sparse-view CT data subsets at varying levels of undersampling were reconstructed from sinograms using filtered backprojection with 16, 32, 64, 128, 256, and 512 views. A dual-frame U-Net was trained and evaluated for each subsampling level on 8,658 images from 22 diseased subjects. A representative image per scan was selected from 19 subjects (12 diseased, 7 healthy) for a single-blinded multireader study. These slices, for all levels of subsampling, with and without U-Net postprocessing, were presented to three readers. IQ and diagnostic confidence were ranked using predefined scales. Subjective nodule segmentation was evaluated using sensitivity and Dice similarity coefficient (DSC); clustered Wilcoxon signed-rank test was used. Results: The 64-projection sparse-view images resulted in 0.89 sensitivity and 0.81 DSC, while their counterparts, postprocessed with the U-Net, had improved metrics (0.94 sensitivity and 0.85 DSC) (p = 0.400). Fewer views led to insufficient IQ for diagnosis. For increased views, no substantial discrepancies were noted between sparse-view and postprocessed images. Conclusions: Projection views can be reduced from 2,048 to 64 while maintaining IQ and the confidence of the radiologists on a satisfactory level.

翻译：背景：本研究旨在通过U-Net改善稀疏视图计算机断层扫描（CT）图像质量，用于肺转移检测，并确定视图数量、图像质量与诊断置信度之间的最优权衡。方法：回顾性选取2016-2018年间41名受试者（年龄62.8±10.6岁（均值±标准差），其中23名男性、34名肺转移患者及7名健康受试者）的CT图像，将其正向投影至2048视图正弦图。基于滤波反投影法，从正弦图中重建出六组不同欠采样程度的对应稀疏视图CT数据子集（含16、32、64、128、256和512视图）。针对每个欠采样级别，使用来自22名患病受试者的8658张图像训练并评估双帧U-Net。从19名受试者（12名患病、7名健康）中每例扫描选取一张代表性图像，开展单盲多读者研究。这些图像（涵盖所有欠采样级别，经/未经U-Net后处理）由三位读者评估，采用预设量表对图像质量和诊断置信度进行排序。主观结节分割评估使用敏感度和Dice相似系数（DSC），并采用聚类Wilcoxon符号秩检验。结果：64投影稀疏视图图像获得0.89敏感度和0.81 DSC，而经U-Net后处理的对应图像指标提升至0.94敏感度和0.85 DSC（p=0.400）。更少视图导致图像质量不足以诊断。随视图增加，稀疏视图图像与后处理图像之间未出现显著差异。结论：在保持图像质量及放射科医师诊断置信度处于满意水平的前提下，投影视图可从2048减少至64。