Ou Yangming, Zöllei Lilla, Retzepi Kallirroi, Castro Victor, Bates Sara V, Pieper Steve, Andriole Katherine P, Murphy Shawn N, Gollub Randy L, Grant Patricia Ellen
Psychiatric Neuroimaging, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts.
Laboratory for Computational Neuroimaging, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts.
Hum Brain Mapp. 2017 Jun;38(6):3052-3068. doi: 10.1002/hbm.23573. Epub 2017 Mar 31.
Diffusion imaging is critical for detecting acute brain injury. However, normal apparent diffusion coefficient (ADC) maps change rapidly in early childhood, making abnormality detection difficult. In this article, we explored clinical PACS and electronic healthcare records (EHR) to create age-specific ADC atlases for clinical radiology reference. Using the EHR and three rounds of multiexpert reviews, we found ADC maps from 201 children 0-6 years of age scanned between 2006 and 2013 who had brain MRIs with no reported abnormalities and normal clinical evaluations 2+ years later. These images were grouped in 10 age bins, densely sampling the first 1 year of life (5 bins, including neonates and 4 quarters) and representing the 1-6 year age range (an age bin per year). Unbiased group-wise registration was used to construct ADC atlases for 10 age bins. We used the atlases to quantify (a) cross-sectional normative ADC variations; (b) spatiotemporal heterogeneous ADC changes; and (c) spatiotemporal heterogeneous volumetric changes. The quantified age-specific whole-brain and region-wise ADC values were compared to those from age-matched individual subjects in our study and in multiple existing independent studies. The significance of this study is that we have shown that clinically acquired images can be used to construct normative age-specific atlases. These first of their kind age-specific normative ADC atlases quantitatively characterize changes of myelination-related water diffusion in the first 6 years of life. The quantified voxel-wise spatiotemporal ADC variations provide standard references to assist radiologists toward more objective interpretation of abnormalities in clinical images. Our atlases are available at https://www.nitrc.org/projects/mgh_adcatlases. Hum Brain Mapp 38:3052-3068, 2017. © 2017 Wiley Periodicals, Inc.
扩散成像对于检测急性脑损伤至关重要。然而,正常的表观扩散系数(ADC)图在儿童早期变化迅速,这使得异常检测变得困难。在本文中,我们探索了临床PACS和电子健康记录(EHR),以创建针对特定年龄的ADC图谱,供临床放射学参考。通过EHR和三轮多专家评审,我们找到了2006年至2013年间扫描的201名0至6岁儿童的ADC图,这些儿童脑部MRI检查未报告异常,且两年多后临床评估正常。这些图像被分为10个年龄组,对生命的第一年进行了密集采样(5个组,包括新生儿和4个季度),并涵盖了1至6岁的年龄范围(每年一个年龄组)。使用无偏组间配准为10个年龄组构建ADC图谱。我们使用这些图谱来量化:(a)横断面正常ADC变化;(b)时空异质性ADC变化;以及(c)时空异质性体积变化。将量化的特定年龄全脑和区域ADC值与我们研究中以及多个现有独立研究中年龄匹配的个体受试者的值进行比较。本研究的意义在于,我们已经表明临床获取的图像可用于构建针对特定年龄的正常图谱。这些首例特定年龄的正常ADC图谱定量表征了生命最初6年中与髓鞘形成相关的水扩散变化。量化的体素级时空ADC变化提供了标准参考,以帮助放射科医生更客观地解释临床图像中的异常。我们的图谱可在https://www.nitrc.org/projects/mgh_adcatlases获取。《人类脑图谱》38:3052 - 3068,2017。© 2017威利期刊公司。