Department of Radiology, Iwate Medical University, 2-1-1, Idaidori, Yahaba, 028-3695, Japan.
Center for Radiological Science, Iwate Medical University, 2-1-1, Idaidori, Yahaba, 028-3695, Japan.
BMC Med Imaging. 2023 Oct 30;23(1):171. doi: 10.1186/s12880-023-01139-7.
A super-resolution deep learning reconstruction (SR-DLR) algorithm trained using data acquired on the ultrahigh spatial resolution computed tomography (UHRCT) has the potential to provide better image quality of coronary arteries on the whole-heart, single-rotation cardiac coverage on a 320-detector row CT scanner. However, the advantages of SR-DLR at coronary computed tomography angiography (CCTA) have not been fully investigated. The present study aimed to compare the image quality of the coronary arteries and in-stent lumen between SR-DLR and model-based iterative reconstruction (MBIR). We prospectively enrolled 70 patients (median age, 69 years; interquartile range [IQR], 59-75 years; 50 men) who underwent CCTA using a 320-detector row CT scanner between January and August 2022. The image noise in the ascending aorta, left atrium, and septal wall of the ventricle was measured, and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in the proximal coronary arteries were calculated. Of the twenty stents, stent strut thickness and luminal diameter were quantitatively evaluated. The image noise on SR-DLR was significantly lower than that on MBIR (median 22.1 HU; IQR, 19.3-24.9 HU vs. 27.4 HU; IQR, 24.2-31.2 HU, p < 0.01), whereas the SNR (median 16.3; IQR, 11.8-21.8 vs. 13.7; IQR, 9.9-18.4, p = 0.01) and CNR (median 24.4; IQR, 15.5-30.2 vs. 19.2; IQR, 14.1-23.2, p < 0.01) on SR-DLR were significantly higher than that on MBIR. Stent struts were significantly thinner (median, 0.68 mm; IQR, 0.61-0.78 mm vs. 0.81 mm; IQR, 0.72-0.96 mm, p < 0.01) and in-stent lumens were significantly larger (median, 1.84 mm; IQR, 1.65-2.26 mm vs. 1.52 mm; IQR, 1.28-2.25 mm, p < 0.01) on SR-DLR than on MBIR. Although further large-scale studies using invasive coronary angiography as the reference standard, comparative studies with UHRCT, and studies in more challenging population for CCTA are needed, this study's initial experience with SR-DLR would improve the utility of CCTA in daily clinical practice due to the better image quality of the coronary arteries and in-stent lumen at CCTA compared with conventional MBIR.
一种使用超高空间分辨率计算机断层扫描 (UHRCT) 采集的数据进行训练的超分辨率深度学习重建 (SR-DLR) 算法有可能提供更好的冠状动脉整体心脏、320 排 CT 扫描仪单次旋转心脏覆盖的图像质量。然而，SR-DLR 在冠状动脉计算机断层血管造影术 (CCTA) 中的优势尚未得到充分研究。本研究旨在比较 SR-DLR 和基于模型的迭代重建 (MBIR) 对冠状动脉和支架内管腔的图像质量。我们前瞻性地招募了 70 名患者（中位年龄 69 岁；四分位距 [IQR]，59-75 岁；50 名男性），他们在 2022 年 1 月至 8 月期间使用 320 排 CT 扫描仪进行 CCTA。测量升主动脉、左心房和心室间隔壁的图像噪声，并计算近端冠状动脉的信噪比 (SNR) 和对比噪声比 (CNR)。对二十个支架进行定量评估，包括支架支柱厚度和管腔直径。SR-DLR 的图像噪声明显低于 MBIR（中位数 22.1HU；IQR，19.3-24.9HU 比 27.4HU；IQR，24.2-31.2HU，p<0.01），而 SNR（中位数 16.3；IQR，11.8-21.8 比 13.7；IQR，9.9-18.4，p=0.01）和 CNR（中位数 24.4；IQR，15.5-30.2 比 19.2；IQR，14.1-23.2，p<0.01）在 SR-DLR 上明显高于 MBIR。支架支柱明显更薄（中位数，0.68mm；IQR，0.61-0.78mm 比 0.81mm；IQR，0.72-0.96mm，p<0.01），支架内管腔明显更大（中位数，1.84mm；IQR，1.65-2.26mm 比 1.52mm；IQR，1.28-2.25mm，p<0.01）在 SR-DLR 上比在 MBIR 上。尽管需要进一步使用有创冠状动脉造影作为参考标准的大规模研究、与 UHRCT 的比较研究以及在更具挑战性的 CCTA 人群中的研究，但由于与传统的 MBIR 相比，SR-DLR 可改善冠状动脉和支架内管腔的 CCTA 图像质量，因此本研究的初步经验可能会提高 CCTA 在日常临床实践中的应用价值。
