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MRI segmentation of the rhesus monkey brain for volumetric analysis of aging and age-related disease.

机译:恒河猴脑的MRI分割,用于分析衰老和与年龄相关的疾病。

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摘要

The goals of this study were to develop automated methods to segment and analyze MRI scans of the rhesus monkey brain and then to apply these methods to identify brain changes in normal aging and experimentally induced hypertension. To accomplish these goals, a reference atlas consisting of 15 specific neuroanatomical structures was manually segmented from dual-echo spin-echo (DE SE) images of one behaviorally normal, young, rhesus monkey (age 7). The resulting atlas provides an anatomical reference for the automated Template Driven Segmentation (TDS) algorithm (Warfield, 1995). TDS elastically matches (or warps) the atlas to images which have been statistically segmented for gray matter, white matter and cerebrospinal fluid (CSF), thus anatomically parcellating these regions into the structures contained in the atlas. The validity of TDS was determined by comparing manual segmentations of five normal, young (age 5–12) monkey brains by five expert raters. Intra-class coefficient analysis and mean volume comparison revealed good agreement, sensitivity and specificity for 11 of the 15 structures. The relative reliability of TDS compared to one manual rater was assessed by repeating segmentations of two monkey scans. The volumes segmented for all 15 structures by the manual rater varied between the two assessments, but there was no variation in TDS volumes. This automated method was then used to segment DE SE brain images of eight young (5–12 years), six middle-aged (16–19 years) and eight old (24–30 years) monkeys. Results demonstrated a statistically significant, age-related decrease in the volumes of forebrain parenchyma, gray matter and white matter, but an increase in the volume of the third ventricle. The cognitive status of these monkeys was assessed by a battery of learning and memory tests, but volume changes were not associated with any behavioral results. TDS was also applied to scans from 10 young monkeys with experimentally induced hypertension (12 months duration). Despite hypertension-induced cognitive impairments, TDS did not detect any statistically significant volume changes in brain structures analyzed. The effectiveness of the method developed here will facilitate efficient analysis of MRI data in the search for the relationship between brain volumes and changes in brain function.
机译:这项研究的目的是开发自动化的方法来分割和分析恒河猴脑的MRI扫描,然后将这些方法应用于识别正常衰老和实验性高血压中的脑部变化。为了实现这些目标,我们从一只行为正常的年轻恒河猴(7岁)的双回波自旋回波(DE SE)图像中手动分割了由15个特定神经解剖结构组成的参考图集。生成的图集为自动模板驱动分割(TDS)算法提供了解剖学参考(Warfield,1995)。 TDS将地图集与已针对灰色物质,白质和脑脊髓液(CSF)进行了统计分割的图像进行弹性匹配(或扭曲),从而从解剖学上将这些区域分解为地图集中包含的结构。通过比较五个专家评估者对五个正常,年轻(5至12岁)猴脑的手动分割来确定TDS的有效性。类内系数分析和平均体积比较显示15种结构中的11种具有良好的一致性,敏感性和特异性。通过重复两次猴子扫描的分割,评估了TDS与一个手动评估器相比的相对可靠性。手动评估器对所有15个结构划分的体积在​​两次评估之间有所不同,但TDS体积没有变化。然后使用这种自动化方法对八只年轻(5-12岁),六只中年(16-19岁)和八岁(24-30岁)的猴子的DE SE脑图像进行分割。结果表明,前脑实质,灰质和白质的体积与年龄相关,具有统计学意义,但第三脑室的体积却有所增加。通过一系列的学习和记忆测试评估了这些猴子的认知状态,但体积变化与任何行为结果均无关。 TDS还用于对10只实验性高血压(持续12个月)的小猴子进行扫描。尽管有高血压引起的认知障碍,TDS并未在所分析的大脑结构中发现任何统计学上显着的体积变化。此处开发的方法的有效性将有助于对MRI数据进行有效分析,以寻找脑容量与脑功能变化之间的关系。

著录项

  • 作者

    Wisco, Jonathan Jayme.;

  • 作者单位

    Boston University.;

  • 授予单位 Boston University.;
  • 学科 Biology Neuroscience.; Biology Anatomy.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 164 p.
  • 总页数 164
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 神经科学;生物形态学;
  • 关键词

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