Department of Human Structure and Repair, Ghent University, C. Heymanslaan 10, radiotherapy park, entrance 98, 9000, Ghent, Belgium.
Department of Radiology and Medical Imaging, Ghent University Hospital, C. Heymanslaan 10, 9000, Ghent, Belgium.
Strahlenther Onkol. 2022 Jun;198(6):582-592. doi: 10.1007/s00066-022-01928-z. Epub 2022 Apr 11.
Thiel embalming followed by freezing in the desired position and acquiring CT + MRI scans is expected to be the ideal approach to obtain accurate, enhanced CT data for delineation guideline development. The effect of Thiel embalming and freezing on MRI image quality is not known. This study evaluates the above-described process to obtain enhanced CT datasets, focusing on the integration of MRI data obtained from frozen, Thiel-embalmed specimens.
Three Thiel-embalmed specimens were frozen in prone crawl position and MRI scanning protocols were evaluated based on contrast detail and structural conformity between 3D renderings from corresponding structures, segmented on corresponding MRI and CT scans. The measurement error of the dataset registration procedure was also assessed.
Scanning protocol T1 VIBE FS enabled swift differentiation of soft tissues based on contrast detail, even allowing a fully detailed segmentation of the brachial plexus. Structural conformity between the reconstructed structures on CT and MRI was excellent, with nerves and blood vessels imported into the CT scan never intersecting with the bones. The mean measurement error for the image registration procedure was consistently in the submillimeter range (range 0.77-0.94 mm).
Based on the excellent MRI image quality and the submillimeter error margin, the procedure of scanning frozen Thiel-embalmed specimens in the treatment position to obtain enhanced CT scans is recommended. The procedure can be used to support the postulation of delineation guidelines, or for training deep learning algorithms, considering automated segmentations.
通过泰尔（Thiel）防腐后再进行所需位置的冷冻，并获取 CT 和 MRI 扫描，有望成为获取用于勾画指南开发的准确增强 CT 数据的理想方法。但是，泰尔防腐和冷冻对 MRI 图像质量的影响尚不清楚。本研究评估了上述获得增强 CT 数据集的过程，重点是整合来自冷冻、泰尔防腐标本的 MRI 数据。
将三个泰尔防腐标本在俯卧爬行位置冷冻，并根据对比度细节和对应结构的 3D 渲染之间的结构一致性来评估 MRI 扫描方案，对应结构在相应的 MRI 和 CT 扫描上进行分割。还评估了数据集配准过程的测量误差。
T1 VIBE FS 扫描方案能够根据对比度细节快速区分软组织，甚至可以对臂丛神经进行完全详细的分割。CT 和 MRI 上重建结构之间的结构一致性非常好，导入到 CT 扫描中的神经和血管从未与骨骼交叉。图像配准过程的平均测量误差始终在亚毫米范围内（范围为 0.77-0.94 毫米）。
基于出色的 MRI 图像质量和亚毫米的误差范围，推荐在治疗位置扫描冷冻泰尔防腐标本以获得增强 CT 扫描的方法。该过程可用于支持勾画指南的提出，或用于训练深度学习算法，考虑到自动分割。
