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Combined PET-MR Brain Registration to Discriminate between Alzheimer's Disease and Healthy Controls

机译:合并宠物MR脑登记以区分阿尔茨海默病和健康对照

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Previous amyloid positron emission tomography (PET) imaging studies have shown that Alzheimer's disease (AD) patients exhibit higher standardised uptake value ratios (SUVRs) than healthy controls. Automatic methods for SUVR calculation in brain images are typically based on registration of PET brain data to a template, followed by computation of the mean uptake ratio in a set of regions in the template space. Resulting SUVRs will therefore have some dependence on the registration method. It is widely accepted that registration based on anatomical information provides optimal results. However, in clinical practice, good quality anatomical data may not be available and registration is often based on PET data alone. We investigate the effect of using functional and structural image information during the registration of PET volumes to a template, by comparing six registration methods: affine registration, non-linear registration using PET-driven demons, non-linear registration using magnetic resonance (MR) driven demons, and our novel joint PET-MR registration technique with three different combination weightings. Our registration method jointly registers PET-MR brain volume pairs, by combining the incremental updates computed in single-modality local correlation coefficient demons registrations. All six registration methods resulted in significantly higher mean SUVRs for diseased subjects compared to healthy subjects. Furthermore, the combined PET-MR registration method resulted in a small, but significant, increase in the mean Dice overlaps between cortical regions in the MR brain volumes and the MR template, compared with the single-modality registration methods. These results suggest that a non-linear, combined PET-MR registration method can perform at least as well as the single-modality registration methods in terms of the separation between SUVRs and Dice overlaps, and may be well suited to discriminate between populations of AD patients and healthy controls.
机译:以前的淀粉样态正电子发射断层扫描(PET)成像研究表明,阿尔茨海默病(AD)患者表现出较高的标准化摄取价值比(SUVRS)而不是健康对照。脑图像中SUVR计算的自动方法通常基于PET脑数据的登记到模板,然后计算模板空间中的一组区域中的平均摄取比。因此,产生的SUVRS将对注册方法有一些依赖性。众所周知,基于解剖信息的注册提供了最佳结果。然而,在临床实践中,可能无法使用良好的质量解剖数据,并且通常仅基于PET数据。我们调查在PET卷的登记期间使用功能和结构图像信息到模板中的效果,通过比较六个注册方法:仿射登记,使用PET驱动恶魔的非线性注册,使用磁共振的非线性注册(MR)具有三种不同组合重量的驱动的恶魔和我们的新型联合宠物MR登记技术。我们的注册方法通过组合单模局部相关系数恶魔注册中计算的增量更新来联合寄存宠物MR脑体积对。与健康受试者相比,所有六种注册方法导致患病受试者的平均值明显高。此外,与单模登记方法相比,组合的PET-MR登记方法导致MR脑体积和MR模板的皮质区域之间的平均骰子重叠的小而显着。这些结果表明,非线性,组合的PET-MR登记方法至少可以在SUVRS和骰子之间的分离中执行单模登记方法,并且可以非常适合区分广告的群体患者和健康对照。

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