Getzmann Jonas M, Deininger-Czermak Eva, Melissanidis Savvas, Ensle Falko, Kaushik Sandeep S, Wiesinger Florian, Cozzini Cristina, Sconfienza Luca M, Guggenberger Roman
Institute of Diagnostic and Interventional Radiology, University Hospital Zurich (USZ), Zurich, Switzerland.
University of Zurich (UZH), Zurich, Switzerland.
Insights Imaging. 2024 Aug 9;15(1):202. doi: 10.1186/s13244-024-01751-3.
To generate pseudo-CT (pCT) images of the pelvis from zero echo time (ZTE) MR sequences and compare them to conventional CT.
Ninety-one patients were prospectively scanned with CT and MRI including ZTE sequences of the pelvis. Eleven ZTE image volumes were excluded due to implants and severe B1 field inhomogeneity. Out of the 80 data sets, 60 were used to train and update a deep learning (DL) model for pCT image synthesis from ZTE sequences while the remaining 20 cases were selected as an evaluation cohort. CT and pCT images were assessed qualitatively and quantitatively by two readers.
Mean pCT ratings of qualitative parameters were good to perfect (2-3 on a 4-point scale). Overall intermodality agreement between CT and pCT was good (ICC = 0.88 (95% CI: 0.85-0.90); p < 0.001) with excellent interreader agreements for pCT (ICC = 0.91 (95% CI: 0.88-0.93); p < 0.001). Most geometrical measurements did not show any significant difference between CT and pCT measurements (p > 0.05) with the exception of transverse pelvic diameter measurements and lateral center-edge angle measurements (p = 0.001 and p = 0.002, respectively). Image quality and tissue differentiation in CT and pCT were similar without significant differences between CT and pCT CNRs (all p > 0.05).
Using a DL-based algorithm, it is possible to synthesize pCT images of the pelvis from ZTE sequences. The pCT images showed high bone depiction quality and accurate geometrical measurements compared to conventional CT. CRITICAL RELEVANCE STATEMENT: pCT images generated from MR sequences allow for high accuracy in evaluating bone without the need for radiation exposure. Radiological applications are broad and include assessment of inflammatory and degenerative bone disease or preoperative planning studies.
pCT, based on DL-reconstructed ZTE MR images, may be comparable with true CT images. Overall, the intermodality agreement between CT and pCT was good with excellent interreader agreements for pCT. Geometrical measurements and tissue differentiation were similar in CT and pCT images.
从零回波时间（ZTE）磁共振序列生成骨盆的伪CT（pCT）图像，并将其与传统CT进行比较。
前瞻性地对91例患者进行CT和MRI扫描，包括骨盆的ZTE序列。由于植入物和严重的B1场不均匀性，排除了11个ZTE图像体积。在80个数据集中，60个用于训练和更新用于从ZTE序列合成pCT图像的深度学习（DL）模型，其余20例被选为评估队列。由两名阅片者对CT和pCT图像进行定性和定量评估。
定性参数的平均pCT评分良好至完美（4分制中为2 - 3分）。CT和pCT之间的总体模态间一致性良好（ICC = 0.88（95%CI：0.85 - 0.90）；p < 0.001），pCT的阅片者间一致性极佳（ICC = 0.91（95%CI：0.88 - 0.93）；p < 0.001）。除骨盆横径测量和外侧中心边缘角测量外（分别为p = 0.001和p = 0.002），大多数几何测量在CT和pCT测量之间未显示出任何显著差异（p > 0.05）。CT和pCT的图像质量和组织区分相似，CT和pCT的对比噪声比之间无显著差异（所有p > 0.05）。
使用基于深度学习的算法，可以从ZTE序列合成骨盆的pCT图像。与传统CT相比，pCT图像显示出较高的骨骼描绘质量和准确的几何测量结果。关键相关性声明：从磁共振序列生成的pCT图像在无需辐射暴露的情况下对骨骼评估具有高精度。放射学应用广泛，包括炎性和退行性骨病的评估或术前规划研究。
基于深度学习重建ZTE磁共振图像的pCT可能与真实CT图像相当。总体而言，CT和pCT之间的模态间一致性良好，pCT的阅片者间一致性极佳。CT和pCT图像中的几何测量和组织区分相似。
