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Amyloid imaging plays an important role in the research and diagnosis of dementing disorders. Substantial variation in quantitative methods to measure brain amyloid burden exists in the field. The aim of this work is to investigate the impact of methodological variations to the quantification of amyloid burden using data from the Dominantly Inherited Alzheimer's Network (DIAN), an autosomal dominant Alzheimer's disease population. Cross-sectional and longitudinal [11C]-Pittsburgh Compound B (PiB) PET imaging data from the DIAN study were analyzed. Four candidate reference regions were investigated for estimation of brain amyloid burden. A regional spread function based technique was also investigated for the correction of partial volume effects. Cerebellar cortex, brain-stem, and white matter regions all had stable tracer retention during the course of disease. Partial volume correction consistently improves sensitivity to group differences and longitudinal changes over time. White matter referencing improved statistical power in the detecting longitudinal changes in relative tracer retention; however, the reason for this improvement is unclear and requires further investigation. Full dynamic acquisition and kinetic modeling improved statistical power although it may add cost and time. Several technical variations to amyloid burden quantification were examined in this study. Partial volume correction emerged as the strategy that most consistently improved statistical power for the detection of both longitudinal changes and across-group differences. For the autosomal dominant Alzheimer's disease population with PiB imaging, utilizing brainstem as a reference region with partial volume correction may be optimal for current interventional trials. Further investigation of technical issues in quantitative amyloid imaging in different study populations using different amyloid imaging tracers is warranted.

[This corrects the article DOI: 10.1371/journal.pone.0152082.].

Hyeon O Kim1, Greg P Snyder1, Tyler M Blazey1, Richard E Race2, Bruce Chesebro2, Pamela J Skinner11Department of Veterinary and Biomedical Sciences, University of Minnesota, USA; 2NIH Laboratory of Persistent Viral Diseases, Rocky Mountain Laboratories, Hamilton, Montana, USAAbstract: Prion diseases are fatal neurodegenerative disorders that affect animals and humans. There is a need to gain understanding of prion disease pathogenesis and to develop diagnostic assays to detect prion diseases prior to the onset of clinical symptoms. The goal of this study was to identify genes that show altered expression early in the disease process in the spleen and brain of prion disease-infected mice. Using Affymetrix microarrays, we identified 67 genes that showed increased expression in the brains of prion disease-infected mice prior to the onset of clinical symptoms. These genes function in many cellular processes including immunity, the endosome/lysosome system, hormone activity, and the cytoskeleton. We confirmed a subset of these gene expression alterations using other methods and determined the time course in which these changes occur. We also identified 14 genes showing altered expression prior to the onset of clinical symptoms in spleens of prion disease infected mice. Interestingly, four genes, Atp1b1, Gh, Anp32a, and Grn, were altered at the very early time of 46 days post-infection. These gene expression alterations provide insights into the molecular mechanisms underlying prion disease pathogenesis and may serve as surrogate markers for the early detection and diagnosis of prion disease.Keywords: prion disease, microarrays, gene expression

Amyloid PET imaging is an indispensable tool widely used in the investigation, diagnosis and monitoring of Alzheimer's disease (AD). Currently, a reference region based approach is used as the mainstream quantification technique for amyloid imaging. This approach assumes the reference region is amyloid free and has the same tracer influx and washout kinetics as the regions of interest. However, this assumption may not always be valid. The goal of this work is to evaluate an amyloid imaging quantification technique that uses arterial region of interest as the reference to avoid potential bias caused by specific binding in the reference region. 21 participants, age 58 and up, underwent Pittsburgh compound B (PiB) PET imaging and MR imaging including a time-of-flight (TOF) MR angiography (MRA) scan and a structural scan. FreeSurfer based regional analysis was performed to quantify PiB PET data. Arterial input function was estimated based on coregistered TOF MRA using a modeling based technique. Regional distribution volume (VT) was calculated using Logan graphical analysis with estimated arterial input function. Kinetic modeling was also performed using the estimated arterial input function as a way to evaluate PiB binding (DVRkinetic) without a reference region. As a comparison, Logan graphical analysis was also performed with cerebellar cortex as reference to obtain DVRREF. Excellent agreement was observed between the two distribution volume ratio measurements (r>0.89, ICC>0.80). The estimated cerebellum VT was in line with literature reported values and the variability of cerebellum VT in the control group was comparable to reported variability using arterial sampling data. This study suggests that image-based arterial input function is a viable approach to quantify amyloid imaging data, without the need of arterial sampling or a reference region. This technique can be a valuable tool for amyloid imaging, particularly in population where reference normalization may not be accurate.

In vivo quantification of β-amyloid deposition using positron emission tomography is emerging as an important procedure for the early diagnosis of the Alzheimer's disease and is likely to play an important role in upcoming clinical trials of disease modifying agents. However, many groups use manually defined regions, which are non-standard across imaging centers. Analyses often are limited to a handful of regions because of the labor-intensive nature of manual region drawing. In this study, we developed an automatic image quantification protocol based on FreeSurfer, an automated whole brain segmentation tool, for quantitative analysis of amyloid images. Standard manual tracing and FreeSurfer-based analyses were performed in 77 participants including 67 cognitively normal individuals and 10 individuals with early Alzheimer's disease. The manual and FreeSurfer approaches yielded nearly identical estimates of amyloid burden (intraclass correlation = 0.98) as assessed by the mean cortical binding potential. An MRI test-retest study demonstrated excellent reliability of FreeSurfer based regional amyloid burden measurements. The FreeSurfer-based analysis also revealed that the majority of cerebral cortical regions accumulate amyloid in parallel, with slope of accumulation being the primary difference between regions.

The cerebral white matter is vulnerable to injury in very preterm infants (born prior to 30 weeks gestation), resulting in a spectrum of lesions. These range from severe forms, including cystic periventricular leukomalacia and periventricular hemorrhagic infarction, to minor focal punctate lesions. Moderate to severe white matter injury in preterm infants has been shown to predict later neurodevelopmental disability, although outcomes can vary widely in infants with qualitatively comparable lesions. Resting state functional connectivity magnetic resonance imaging has been increasingly utilized in neurodevelopmental investigations and may provide complementary information regarding the impact of white matter injury on the developing brain. We performed resting state functional connectivity magnetic resonance imaging at term equivalent postmenstrual age in fourteen preterm infants with moderate to severe white matter injury secondary to periventricular hemorrhagic infarction. In these subjects, resting state networks were identifiable throughout the brain. Patterns of aberrant functional connectivity were observed and depended upon injury severity. Comparisons were performed against data obtained from prematurely-born infants with mild white matter injury and healthy, term-born infants and demonstrated group differences. These results reveal structural-functional correlates of preterm white matter injury and carry implications for future investigations of neurodevelopmental disability.

Abstract Introduction Structural magnetic resonance imaging is a marker of gray matter health and decline that is sensitive to impaired cognition and Alzheimer's disease pathology. Prior work has shown that both amyloid β (Aβ) and tau biomarkers are related to cortical thinning, but it is unclear what unique influences they have on the brain. Methods Aβ pathology was measured with [18F] AV‐45 (florbetapir) positron emission tomography (PET) and tau was assessed with [18F] AV‐1451 (flortaucipir) PET in a population of 178 older adults, of which 123 had longitudinal magnetic resonance imaging assessments (average of 5.7 years) that preceded the PET acquisitions. Results In cross‐sectional analyses, greater tau PET pathology was associated with thinner cortices. When examined independently in longitudinal models, both Aβ and tau were associated with greater antecedent loss of gray matter. However, when examined in a combined model, levels of tau, but not Aβ, were still highly related to change in cortical thickness. Discussion Measures of tau PET are strongly related to gray matter atrophy and likely mediate relationships between Aβ and gray matter.