Brain color-coded diffusion imaging: Utility of ACPC reorientation of gradients in healthy subjects and patients

IF 4.9 2区 医学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computer methods and programs in biomedicine Pub Date : 2024-10-02 DOI:10.1016/j.cmpb.2024.108449
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Abstract

Background and Objective

The common structural interpretation of diffusion color-encoded (DCE) maps assumes that the brain is aligned with the gradients of the MRI machine. This is seldom achieved in the field, leading to incorrect red (R), green (G) and blue (B) DCE values for the expected orientation of fiber bundles. We studied the virtual reorientation of gradients according to the anterior commissure – posterior commissure (ACPC) system on the RGB derivatives.

Methods

We measured mean ± standard deviation of average, standard deviation, skewness and kurtosis of RGB derivatives, before (rO) and after (acpcO) gradient reorientation, in one healthy-subject group with head routinely positioned (HS-routine), and in two patient groups, one with essential tremor (ET-Opti), and one with Parkinson's disease (PD-Opti), with head position optimized according to ACPC before acquisition. We studied the pitch, roll and yaw angles of reorientation, and we compared rO and acpcO conditions, and groups (ad hoc statistics).

Results

Pitch (maximum in the HS-routine group) was greater than roll and yaw. After reorientation of gradients, in the HS-routine group, DCE average increased, and Stddev, skewness and kurtosis decreased; R, G and B average increased, and R and B skewness and kurtosis decreased. By contrast, in the ET-Opti group and the PD-Opti group, R, G and B, average and Stddev increased, and skewness and kurtosis decreased. In both rO and acpcO conditions, in the ET-Opti and PD-Opti groups, average and standard deviation were higher, while skewness and kurtosis were lower.

Conclusions

DCE map interpretability depends on brain orientation. Reorientation realigns gradients with the anatomic and physiologic position of the head and brain, as exemplified.
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大脑彩色编码扩散成像:ACPC 梯度重新定向在健康受试者和患者中的实用性。
背景和目的:弥散彩色编码(DCE)图的常见结构解释假定大脑与磁共振成像机的梯度对齐。这在现场很少能实现,导致纤维束预期方向的红色(R)、绿色(G)和蓝色(B)DCE 值不正确。我们根据 RGB 衍生物上的前会阴-后会阴(ACPC)系统研究了梯度的虚拟重新定向:方法:我们在一组头部常规定位(HS-routine)的健康受试者和两组在采集前根据 ACPC 系统优化头部位置的患者中,分别测量了 RGB 衍生物在梯度重新定向前(rO)和后(acpcO)的平均值、标准偏差、偏斜度和峰度(± 标准偏差)。我们研究了调整方向时的俯仰角、滚动角和偏航角,并对 rO 和 acpcO 条件以及各组进行了比较(特别统计):结果:俯仰角(HS 常规组最大)大于滚动角和偏航角。梯度调整后,常规 HS 组的 DCE 平均值增加,stddev、偏斜度和峰度降低;R、G 和 B 平均值增加,R 和 B 偏斜度和峰度降低。相比之下,在 ET-Opti 组和 PD-Opti 组,R、G 和 B 平均值和 Stddev 增加,偏度和峰度减少。在rO和acpcO条件下,ET-Opti组和PD-Opti组的平均值和标准差较高,而偏度和峰度较低:DCE图谱的可解释性取决于大脑定向。如图所示,重新定向可根据头部和大脑的解剖和生理位置重新调整梯度。
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来源期刊
Computer methods and programs in biomedicine
Computer methods and programs in biomedicine 工程技术-工程:生物医学
CiteScore
12.30
自引率
6.60%
发文量
601
审稿时长
135 days
期刊介绍: To encourage the development of formal computing methods, and their application in biomedical research and medical practice, by illustration of fundamental principles in biomedical informatics research; to stimulate basic research into application software design; to report the state of research of biomedical information processing projects; to report new computer methodologies applied in biomedical areas; the eventual distribution of demonstrable software to avoid duplication of effort; to provide a forum for discussion and improvement of existing software; to optimize contact between national organizations and regional user groups by promoting an international exchange of information on formal methods, standards and software in biomedicine. Computer Methods and Programs in Biomedicine covers computing methodology and software systems derived from computing science for implementation in all aspects of biomedical research and medical practice. It is designed to serve: biochemists; biologists; geneticists; immunologists; neuroscientists; pharmacologists; toxicologists; clinicians; epidemiologists; psychiatrists; psychologists; cardiologists; chemists; (radio)physicists; computer scientists; programmers and systems analysts; biomedical, clinical, electrical and other engineers; teachers of medical informatics and users of educational software.
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