加速药物伙伴关系®精神分裂症项目的MR神经成像协议。

IF 3 Q2 PSYCHIATRY
Michael P Harms, Kang-Ik K Cho, Alan Anticevic, Nicolas R Bolo, Sylvain Bouix, Dylan Campbell, Tyrone D Cannon, Guillermo Cecchi, Mathias Goncalves, Anastasia Haidar, Dylan E Hughes, Igor Izyurov, Omar John, Tina Kapur, Nicholas Kim, Elana Kotler, Marek Kubicki, Joshua M Kuperman, Kristen Laulette, Ulrich Lindberg, Christopher Markiewicz, Lipeng Ning, Russell A Poldrack, Yogesh Rathi, Paul A Romo, Zailyn Tamayo, Cassandra Wannan, Alana Wickham, Walid Yassin, Juan Helen Zhou, Jean Addington, Luis Alameda, Celso Arango, Nicholas J K Breitborde, Matthew R Broome, Kristin S Cadenhead, Monica E Calkins, Eric Yu Hai Chen, Jimmy Choi, Philippe Conus, Cheryl M Corcoran, Barbara A Cornblatt, Covadonga M Diaz-Caneja, Lauren M Ellman, Paolo Fusar-Poli, Pablo A Gaspar, Carla Gerber, Louise Birkedal Glenthøj, Leslie E Horton, Christy Lai Ming Hui, Joseph Kambeitz, Lana Kambeitz-Ilankovic, Matcheri S Keshavan, Sung-Wan Kim, Nikolaos Koutsouleris, Jun Soo Kwon, Kerstin Langbein, Daniel Mamah, Daniel H Mathalon, Vijay A Mittal, Merete Nordentoft, Godfrey D Pearlson, Jesus Perez, Diana O Perkins, Albert R Powers, Jack Rogers, Fred W Sabb, Jason Schiffman, Jai L Shah, Steven M Silverstein, Stefan Smesny, William S Stone, Gregory P Strauss, Judy L Thompson, Rachel Upthegrove, Swapna K Verma, Jijun Wang, Daniel H Wolf, Rene S Kahn, John M Kane, Patrick D McGorry, Barnaby Nelson, Scott W Woods, Martha E Shenton, Stephen J Wood, Carrie E Bearden, Ofer Pasternak
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引用次数: 0

摘要

MRI神经成像已成为临床高危(CHR)精神病发展个体研究的常见组成部分,目的是了解CHR状态下潜在的大脑区域和系统,并确定预后或预测性生物标志物,以提高我们预测临床结果的能力。迄今为止,大多数涉及MRI在CHR中的研究可能没有足够的动力来产生可靠和可推广的神经成像结果。在这里,我们描述了在复杂的多站点,多供应商环境中实施的前瞻性,先进和现代的神经成像方案,作为大规模加速药物合作伙伴®精神分裂症计划(AMP®SCZ)的一部分,包括各种选择的基本原理。该方案包括T1和t2加权结构扫描,静息状态fMRI和扩散加权成像,在两个时间点收集,大约相隔2个月。我们还提出了几个指标的初步方差成分分析,如信噪比(SNR/CNR)和空间平滑度,以提供参与者、地点和平台(即扫描仪模型)方差的相对百分比的定量数据。由于不同扫描仪的扩散成像硬件能力的差异,与位置相关的差异通常很小(通常为55%)。此外,由于供应商在获取和重建过程中存在固有的难以控制的差异,空间平滑度通常具有较大的平台相关方差。这些结果说明了在AMP SCZ神经成像数据分析中需要考虑的一些因素,这将是迄今为止最大的CHR队列。在https://vimeo.com/1059777228?share=copy#t=0观看哈姆斯博士对这篇文章的讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The MR neuroimaging protocol for the Accelerating Medicines Partnership® Schizophrenia Program.

Neuroimaging with MRI has been a frequent component of studies of individuals at clinical high risk (CHR) for developing psychosis, with goals of understanding potential brain regions and systems impacted in the CHR state and identifying prognostic or predictive biomarkers that can enhance our ability to forecast clinical outcomes. To date, most studies involving MRI in CHR are likely not sufficiently powered to generate robust and generalizable neuroimaging results. Here, we describe the prospective, advanced, and modern neuroimaging protocol that was implemented in a complex multi-site, multi-vendor environment, as part of the large-scale Accelerating Medicines Partnership® Schizophrenia Program (AMP® SCZ), including the rationale for various choices. This protocol includes T1- and T2-weighted structural scans, resting-state fMRI, and diffusion-weighted imaging collected at two time points, approximately 2 months apart. We also present preliminary variance component analyses of several measures, such as signal- and contrast-to-noise ratio (SNR/CNR) and spatial smoothness, to provide quantitative data on the relative percentages of participant, site, and platform (i.e., scanner model) variance. Site-related variance is generally small (typically <10%). For the SNR/CNR measures from the structural and fMRI scans, participant variance is the largest component (as desired; 40-76%). However, for SNR/CNR in the diffusion scans, there is substantial platform-related variance (>55%) due to differences in the diffusion imaging hardware capabilities of the different scanners. Also, spatial smoothness generally has a large platform-related variance due to inherent, difficult to control, differences between vendors in their acquisitions and reconstructions. These results illustrate some of the factors that will need to be considered in analyses of the AMP SCZ neuroimaging data, which will be the largest CHR cohort to date.Watch Dr. Harms discuss this article at https://vimeo.com/1059777228?share=copy#t=0 .

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