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首页> 外文期刊>Brain structure & function >Automatic multispectral MRI segmentation of human hippocampal subfields: an evaluation of multicentric test-retest reproducibility
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Automatic multispectral MRI segmentation of human hippocampal subfields: an evaluation of multicentric test-retest reproducibility

机译:人类海马子场的自动多光谱MRI分割:多中心试验重度再现性的评估

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Accurate and reproducible automated segmentation of human hippocampal subfields is of interest to study their roles in cognitive functions and disease processes. Multispectral structural MRI methods have been proposed to improve automated hippocampal subfield segmentation accuracy, but the reproducibility in a multicentric setting is, to date, not well characterized. Here, we assessed test-retest reproducibility of FreeSurfer 6.0 hippocampal subfield segmentations using multispectral MRI analysis pipelines (22 healthy subjects scanned twice, a week apart, at four 3T MRI sites). The harmonized MRI protocol included two 3D-T1, a 3D-FLAIR, and a high-resolution 2D-T2. After within-session T1 averaging, subfield volumes were segmented using three pipelines with different multispectral data: two longitudinal ("long_T1s" and "long_T1s_FLAIR") and one cross-sectional ("long_T1s_FLAIR_crossT2"). Volume reproducibility was quantified in magnitude (reproducibility error-RE) and space (DICE coefficient). RE was lower in all hippocampal subfields, except for hippocampal fissure, using the longitudinal pipelines compared to long_T1s_FLAIR_crossT2 (average RE reduction of 0.4-3.6%). Similarly, the longitudinal pipelines showed a higher spatial reproducibility (1.1-7.8% of DICE improvement) in all hippocampal structures compared to long_T1s_FLAIR_crossT2. Moreover, long_T1s_FLAIR provided a small but significant RE improvement in comparison to long_T1s (p = 0.015), whereas no significant DICE differences were found. In addition, structures with volumes larger than 200 mm(3) had better RE (1-2%) and DICE (0.7-0.95) than smaller structures. In summary, our study suggests that the most reproducible hippocampal subfield FreeSurfer segmentations are derived from a longitudinal pipeline using 3D-T1s and 3D-FLAIR. Adapting a longitudinal pipeline to include high-resolution 2D-T2 may lead to further improvements.
机译:人类海马子场的准确性和可重复的自动分割对于研究其在认知功能和疾病过程中的作用感兴趣。已经提出了多光谱结构MRI方法来提高自动化海马子场分割精度,但多元设置的再现性是迄今为止,并不具备很好的表征。在这里,我们评估了使用多光谱MRI分析管道的FreeSurfer 6.0海马子场分割的测试 - 重保持再现性(22个健康受试者扫描两次,在四个3T MRI位点分开)。协调的MRI协议包括两个3D-T1,3D-Flair和高分辨率2D-T2。在会话内完成T1平均后,使用三个管道分割子字段卷,其中三个管道具有不同的多光谱数据:两个纵向(“long_t1s”和“long_t1s_flair”)和一个横截面(“long_t1s_flair_crosst2”)。体积再现性在幅度(再现性误差 - RE)和空间(骰子系数)中量化。除了HONG_T1S_FLAIR_CROSST2相比,使用纵向管道除了海马裂隙外,除了海马裂隙外,RE是否较低。类似地,与LONG_T1S_FLAIR_CROSST2相比,纵向管道在所有海马结构中显示出较高的空间再现性(骰子改善的1.1-7.8%)。此外,与Long_T1S相比,Long_T1S_FLAIR提供了一个小但显着的重新改进(P = 0.015),而没有发现显着的骰子差异。另外,具有大于200mm(3)的体积的结构具有比较小结构更好的Re(1-2%)和骰子(0.7-0.95)。总之,我们的研究表明,最重现的海马子场漏洞分割源自使用3D-T1S和3D-Flair的纵向管道。调整纵向管道以包括高分辨率2D-T2可能导致进一步改进。

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