Automated workflow for volumetric assessment of signal intensity ratio on T1-weighted MR images after multiple gadolinium administrations

多次注射钆后T1加权MR图像信号强度比值体积评估的自动化工作流程

阅读:1

Abstract

Purpose: Repeated injections of linear gadolinium-based contrast agent (GBCA) have shown correlations with increased signal intensities (SI) on unenhanced T1-weighted (T1w) images. Assessment is usually performed manually on a single slice and the SI as an average of a freehand region-of-interest is reported. We aim to develop a fully automated software that segments and computes SI ratio of dentate nucleus (DN) to pons (DN/P) and globus pallidus (GP) to thalamus (GP/T) for the assessment of gadolinium presence in the brain after a serial GBCA administrations. Approach: All patients ( N = 113 ) underwent at least eight GBCA enhanced scans. The modal SI in the DN, GP, pons, and thalamus were measured volumetrically on unenhanced T1w images and corrected based on the reference protocol (measurement 1) and compared to the SI-uncorrected-modal-volume (measurement 2), SI-corrected-mean-volume (measurement 3), as well as SI-corrected-modal-single slice (measurement 4) approaches. Results: Automatic processing worked on all 2119 studies (1150 at 1.5 T and 969 at 3 T). DN/P were 1.085 ± 0.048 (1.5 T) and 0.979 ± 0.061 (3 T). GP/T were 1.084 ± 0.039 (1.5 T) and 1.069 ± 0.042 (3 T). Modal DN/P ratios from volumetric assessment at 1.5 T failed to show a statistical difference with or without SI corrections ( p = 0.71 ). All other t -tests demonstrated significant differences (measurement 2, 3, 4 compared to 1, p < 0.001 ). Conclusion: The fully automatic method is an effective powerful tool to streamline the analysis of SI ratios in the deep brain tissues. Divergent SI ratios using different approaches reinforces the need to standardize the measurement for the research in this field.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。