Brain Imaging in Alzheimer Disease

Johnson, Keith A.; Fox, Nick C.; Sperling, Reisa A.; Klunk, William E.

doi:10.1101/cshperspect.a006213

Cited by 558 publications

(399 citation statements)

References 230 publications

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“…Unfortunately, while theoretically is not a high risk for the patients, it involves exposure to radiation and radioactivity, and, therefore, it is a method that should better be avoided. Furthermore, it is an expensive method and is not highly available, although this fact is changing in recent years [87]. These reasons lead us to believe that PET imaging is not the best-suited method for massive monitoring of the population.…”

Section: Pet Scansmentioning

confidence: 99%

“…These way, brain areas involved on each task or at the rest state can be detected [116]. Thus, a blood oxygen level-dependent (BOLD) image contrast that provides an indirect measure of neuronal activity is achieved [59,87]. As in the precedent case, an MRI scanner is needed for this type of imaging.…”

Section: Functional Mri (Fmri)mentioning

confidence: 99%

“…Atrophy of the hippocampus can be differenced clearly in AD patients compared to healthy people, but, unfortunately, it may not be so obvious at the early stages, hindering the use of MRI for early detection. Furthermore, brain atrophy is not specific to AD but characteristic of different diseases [87], or the brain can even suffer volume changes due to reasons other than neuronal loss. Nevertheless, some researchers affirm the possibility of predicting and distinguishing between the different stages of AD using automatic MRI analysis and the results reported herein suggest that MRI can contribute positively to an automatic AD diagnosis system, even in its early stages.…”

Section: Structural Mrimentioning

confidence: 99%

“…Structural brain MRI imaging has been widely considered for early detection and diagnosis of AD [28]. This technique can help diagnosing AD in two ways: on one hand, it allows to measure MTL's atrophy, which is closely related to cognition and memory, with very high definition [103,104] and on the other hand, it enables changes on tissue characteristics due to vascular damage to be detected [87]. MTL's atrophy is earliest evidenced in the hippocampus and the entorhinal cortex [28,[105][106][107], followed closely by the parahippocampus and the amygdala [87].…”

Section: Structural Mrimentioning

confidence: 99%

“…Shortly, it consists of applying strong magnetic fields to the area that is wanted to image while the different tissues are distinguished thanks to their particular relaxation responses, i.e. the radiofrequency signal emitted by the protons of each tissue, [87] when the magnetization stops. This is done with an MRI scanner.…”

Section: Structural Mrimentioning

confidence: 99%

See 4 more Smart Citations

On the early diagnosis of Alzheimer's Disease from multimodal signals: A survey

Alberdi

Aztiria

Basarab

2016

Artificial Intelligence in Medicine

164

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Section: Pet Scansmentioning

confidence: 99%

Section: Functional Mri (Fmri)mentioning

confidence: 99%

Section: Structural Mrimentioning

confidence: 99%

Section: Structural Mrimentioning

confidence: 99%

Section: Structural Mrimentioning

confidence: 99%

See 3 more Smart Citations

On the early diagnosis of Alzheimer's Disease from multimodal signals: A survey

Alberdi

Aztiria

Basarab

2016

Artificial Intelligence in Medicine

164

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Hierarchical Organization of Tau and Amyloid Deposits in the Cerebral Cortex

et al. 2017

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IMPORTANCE Abnormal accumulation of tau and amyloid-β (Aβ) proteins in the human brain are 2 pathologic hallmarks of Alzheimer disease (AD). Because pathologic processes begin decades before the onset of the clinical manifestations, the study of the cortical distribution of early-stage pathologic alterations is critical in understanding the underpinnings of the disease. OBJECTIVES To identify the in vivo brain spatial distributions of tau and Aβ deposits in a sample of cognitively normal participants in the Harvard Aging Brain Study, determine spatial patterns of pathologic alterations, and provide means for improved individual in vivo staging. DESIGN, SETTING, AND PARTICIPANTS Eighty-eight individuals from the general community underwent flortaucipir 18 T807 (18 F-T807) and carbon 11-labeled Pittsburgh Compound B (11 C-PiB) positron emission tomographic (PET) imaging. A voxel-level hierarchical clustering approach was used to obtain the main clustering partitions corresponding to the cortical distribution maps of 18 F-T807 and 11 C-PiB. Hierarchical relationships between areas of distinctive pathologic deposits were then studied. Using cerebellar gray reference, 18 F-T807 data were expressed as standardized uptake value ratio, and 11 C-PiB were given as distribution volume ratio. MAIN OUTCOMES AND MEASURES Main in vivo and hierarchically organized tau and Aβ deposits in the elderly brain. RESULTS Of the 88 study participants, 39 (44%) were men, with a mean (SD) age of 76.2 (6.2) years. The tau and Aβ maps both displayed optimal cortical partitions at 4 clusters. The tau deposits were grouped in the temporal lobe, distributed in heteromodal areas, medial and visual regions, and primary somatomotor cortex; the Aβ deposits were clustered in the heteromodal areas and rather patchy in distributed regions involving the primary cortices, medial structures, and temporal areas. Moreover, tau deposits in the temporal lobe and distributed heteromodal areas were tightly nested. CONCLUSIONS AND RELEVANCE Tau and Aβ deposits in the elderly brain generally display well-defined hierarchical cortical relationships as well as overlaps between the principal clusters of both pathologic alterations in the heteromodal association regions. These findings represent systematic, large-scale mechanisms of early AD pathology.

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Association Between False Memories and Delusions in Alzheimer Disease

et al. 2023

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ImportanceUnderstanding the mechanisms of delusion formation in Alzheimer disease (AD) could inform the development of therapeutic interventions. It has been suggested that delusions arise as a consequence of false memories.ObjectiveTo investigate whether delusions in AD are associated with false recognition, and whether higher rates of false recognition and the presence of delusions are associated with lower regional brain volumes in the same brain regions.Design, Setting, and ParticipantsSince the Alzheimer’s Disease Neuroimaging Initiative (ADNI) launched in 2004, it has amassed an archive of longitudinal behavioral and biomarker data. This cross-sectional study used data downloaded in 2020 from ADNI participants with an AD diagnosis at baseline or follow-up. Data analysis was performed between June 24, 2020, and September 21, 2021.ExposureEnrollment in the ADNI.Main Outcomes and MeasuresThe main outcomes included false recognition, measured with the 13-item Alzheimer’s Disease Assessment Scale–Cognitive Subscale (ADAS-Cog 13) and the Rey Auditory Verbal Learning Test (RAVLT) and volume of brain regions corrected for total intracranial volume. Behavioral data were compared for individuals with delusions in AD and those without using independent-samples t tests or Mann-Whitney nonparametric tests. Significant findings were further explored using binary logistic regression modeling. For neuroimaging data region of interest analyses using t tests, Poisson regression modeling or binary logistic regression modeling and further exploratory, whole-brain voxel-based morphometry analyses were carried out to explore the association between regional brain volume and false recognition or presence of delusions.ResultsOf the 2248 individuals in the ADNI database, 728 met the inclusion criteria and were included in this study. There were 317 (43.5%) women and 411 (56.5%) men. Their mean (SD) age was 74.8 (7.4) years. The 42 participants with delusions at baseline had higher rates of false recognition on the ADAS-Cog 13 (median score, 3; IQR, 1 to 6) compared with the 549 control participants (median score, 2; IQR, 0 to 4; U = 9398.5; P = .04). False recognition was not associated with the presence of delusions when confounding variables were included in binary logistic regression models. An ADAS-Cog 13 false recognition score was inversely associated with left hippocampal volume (odds ratio [OR], 0.91 [95% CI, 0.88-0.94], P &lt; .001), right hippocampal volume (0.94 [0.92-0.97], P &lt; .001), left entorhinal cortex volume (0.94 [0.91-0.97], P &lt; .001), left parahippocampal gyrus volume (0.93 [0.91-0.96], P &lt; .001), and left fusiform gyrus volume (0.97 [0.96-0.99], P &lt; .001). There was no overlap between locations associated with false recognition and those associated with delusions.Conclusions and RelevanceIn this cross-sectional study, false memories were not associated with the presence of delusions after accounting for confounding variables, and no indication for overlap of neural networks for false memories and delusions was observed on volumetric neuroimaging. These findings suggest that delusions in AD do not arise as a direct consequence of misremembering, lending weight to ongoing attempts to delineate specific therapeutic targets for treatment of psychosis.

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Brain Imaging in Alzheimer Disease

Cited by 558 publications

References 230 publications

On the early diagnosis of Alzheimer's Disease from multimodal signals: A survey

On the early diagnosis of Alzheimer's Disease from multimodal signals: A survey

Hierarchical Organization of Tau and Amyloid Deposits in the Cerebral Cortex

Association Between False Memories and Delusions in Alzheimer Disease

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