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基于传统磁共振成像对白质微观结构的统计估计

Statistical estimation of white matter microstructure from conventional MRI.

作者信息

Suttner Leah H, Mejia Amanda, Dewey Blake, Sati Pascal, Reich Daniel S, Shinohara Russell T

机构信息

Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States.

Department of Biostatistics, The Johns Hopkins University, Baltimore, MD 21205, United States.

出版信息

Neuroimage Clin. 2016 Sep 14;12:615-623. doi: 10.1016/j.nicl.2016.09.010. eCollection 2016.

DOI:10.1016/j.nicl.2016.09.010
PMID:27722085
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5048084/
Abstract

Diffusion tensor imaging (DTI) has become the predominant modality for studying white matter integrity in multiple sclerosis (MS) and other neurological disorders. Unfortunately, the use of DTI-based biomarkers in large multi-center studies is hindered by systematic biases that confound the study of disease-related changes. Furthermore, the site-to-site variability in multi-center studies is significantly higher for DTI than that for conventional MRI-based markers. In our study, we apply the Quantitative MR Estimation Employing Normalization (QuEEN) model to estimate the four DTI measures: MD, FA, RD, and AD. QuEEN uses a voxel-wise generalized additive regression model to relate the normalized intensities of one or more conventional MRI modalities to a quantitative modality, such as DTI. We assess the accuracy of the models by comparing the prediction error of estimated DTI images to the scan-rescan error in subjects with two sets of scans. Across the four DTI measures, the performance of the models is not consistent: Both MD and RD estimations appear to be quite accurate, while AD estimation is less accurate than MD and RD; the accuracy of FA estimation is poor. Thus, in some cases when assessing white matter integrity, it may be sufficient to acquire conventional MRI sequences alone.

摘要

扩散张量成像(DTI)已成为研究多发性硬化症(MS)和其他神经系统疾病中白质完整性的主要方法。不幸的是,基于DTI的生物标志物在大型多中心研究中的应用受到系统偏差的阻碍,这些偏差混淆了疾病相关变化的研究。此外,多中心研究中DTI的站点间变异性明显高于基于传统MRI的标志物。在我们的研究中,我们应用定量磁共振估计归一化(QuEEN)模型来估计四种DTI测量值:平均扩散率(MD)、各向异性分数(FA)、径向扩散率(RD)和轴向扩散率(AD)。QuEEN使用体素级广义相加回归模型,将一种或多种传统MRI模态的归一化强度与定量模态(如DTI)相关联。我们通过比较估计的DTI图像的预测误差与两组扫描受试者的重扫误差来评估模型的准确性。在四种DTI测量中,模型的性能并不一致:MD和RD估计似乎相当准确,而AD估计不如MD和RD准确;FA估计的准确性较差。因此,在某些评估白质完整性的情况下,仅获取传统MRI序列可能就足够了。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08c/5048084/bb98fdd1af53/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08c/5048084/a97bfd1bc868/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08c/5048084/166c453c461e/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08c/5048084/01f97c459ceb/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08c/5048084/598f197f91df/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08c/5048084/bb98fdd1af53/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08c/5048084/a97bfd1bc868/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08c/5048084/166c453c461e/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08c/5048084/01f97c459ceb/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08c/5048084/598f197f91df/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08c/5048084/bb98fdd1af53/gr5.jpg

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