Mossa-Basha Mahmud, Zhu Chengcheng, Pandhi Tanya, Mendoza Steve, Azadbakht Javid, Safwat Ahmed, Homen Dean, Zamora Carlos, Gnanasekaran Dinesh Kumar, Peng Ruiyue, Cen Steven, Duddalwar Vinay, Alger Jeffry R, Wang Danny J J
From the Department of Radiology (M.M.-B., C.Z., A.S), University of Washington, Seattle, Washington
From the Department of Radiology (M.M.-B., C.Z., A.S), University of Washington, Seattle, Washington.
AJNR Am J Neuroradiol. 2024 Oct 3;45(10):1468-1474. doi: 10.3174/ajnr.A8367.
Considering recent iodinated contrast shortages and a focus on reducing waste, developing protocols with lower contrast dosing while maintaining image quality through artificial intelligence is needed. This study compared reduced iodinated contrast media and standard dose CTP acquisitions, and the impact of deep learning denoising on CTP image quality in preclinical and clinical studies. The effect of reduced X-ray mAs dose was also investigated in preclinical studies.
Twelve swine underwent 9 CTP examinations each, performed at combinations of 3 different x-ray (37, 67, and 127 mAs) and iodinated contrast media doses (10, 15, and 20 mL). Clinical CTP acquisitions performed before and during the iodinated contrast media shortage and protocol change (from 40 to 30 mL) were retrospectively included. Eleven patients with reduced iodinated contrast media dosages and 11 propensity-score-matched controls with the standard iodinated contrast media dosages were included. A residual encoder-decoder convolutional neural network (RED-CNN) was trained for CTP denoising using space-weighted image average filtered CTP images as the target. The standard, RED-CNN-denoised, and space-weighted image average noise-filtered images for animal and human studies were compared for quantitative SNR and qualitative image evaluation.
The SNR of animal CTP images decreased with reductions in iodinated contrast media and milliampere-second doses. Contrast dose reduction had a greater effect on SNR than milliampere-second reduction. Noise-filtering by space-weighted image average and RED-CNN denoising progressively improved the SNR of CTP maps, with RED-CNN resulting in the highest SNR. The SNR of clinical CTP images was generally lower with a reduced iodinated contrast media dose, which was improved by the space-weighted image average and RED-CNN denoising ( < .05). Qualitative readings consistently rated RED-CNN denoised CTP as the best quality, followed by space-weighted image average and then standard CTP images.
Deep learning-denoising can improve image quality for low iodinated contrast media CTP protocols, and could approximate standard iodinated contrast media dose CTP, in addition to potentially improving image quality for low milliampere-second acquisitions.
鉴于近期碘化造影剂短缺以及对减少浪费的关注，需要制定在通过人工智能保持图像质量的同时降低造影剂剂量的方案。本研究在临床前和临床研究中比较了减少碘化造影剂用量与标准剂量CTP采集，以及深度学习去噪对CTP图像质量的影响。在临床前研究中还研究了降低X射线mAs剂量的效果。
12头猪每头接受9次CTP检查，检查在3种不同X射线剂量（37、67和127 mAs）与碘化造影剂剂量（10、15和20 mL）的组合下进行。回顾性纳入了在碘化造影剂短缺和方案改变（从40 mL降至30 mL）之前及期间进行的临床CTP采集。纳入了11例碘化造影剂用量减少的患者以及11例倾向评分匹配的使用标准碘化造影剂用量的对照。使用空间加权图像平均滤波后的CTP图像作为目标，训练了一个残差编码器 - 解码器卷积神经网络（RED - CNN）用于CTP去噪。对动物和人体研究的标准图像、经RED - CNN去噪的图像以及空间加权图像平均噪声滤波后的图像进行定量SNR和定性图像评估比较。
动物CTP图像的SNR随着碘化造影剂和毫安秒剂量的减少而降低。造影剂剂量减少对SNR的影响大于毫安秒减少的影响。通过空间加权图像平均和RED - CNN去噪进行噪声滤波可逐步提高CTP图的SNR，其中RED - CNN导致的SNR最高。临床CTP图像在碘化造影剂剂量减少时SNR通常较低，通过空间加权图像平均和RED - CNN去噪可得到改善（P <.05）。定性读数一致将经RED - CNN去噪的CTP评为质量最佳，其次是空间加权图像平均，然后是标准CTP图像。
深度学习去噪可改善低碘化造影剂CTP方案的图像质量，除了可能改善低毫安秒采集的图像质量外，还可接近标准碘化造影剂剂量CTP的图像质量。
