Dynamic Amyloid PET: Relationships to 18F-Flortaucipir Tau PET Measures

The complex pathway between amyloid β and cognition: implications for therapy

For decades, the hypothesis that brain deposition of the amyloid β protein initiates Alzheimer's disease has dominated research and clinical trials. Targeting amyloid β is starting to produce therapeutic benefit, although whether amyloid-lowering drugs will be widely and meaningfully effective is still unclear. Despite extensive in-vivo biomarker evidence in humans showing the importance of an amyloid cascade that drives cognitive decline, the amyloid hypothesis does not fully account for the complexity of late-life cognitive impairment. Multiple brain pathological changes, inflammation, and host factors of resilience might also be involved in contributing to the development of dementia. This variability suggests that the benefits of lowering amyloid β might depend on how strongly an amyloid pathway is manifest in an individual in relation to other coexisting pathophysiological processes. A new approach to research and treatment, which fully considers the multiple factors that drive cognitive decline, is necessary.

International Nuclear Medicine Consensus on the Clinical Use of Amyloid Positron Emission Tomography in Alzheimer's Disease

Alzheimer's disease (AD) is the main cause of dementia, with its diagnosis and management remaining challenging. Amyloid positron emission tomography (PET) has become increasingly important in medical practice for patients with AD. To integrate and update previous guidelines in the field, a task group of experts of several disciplines from multiple countries was assembled, and they revised and approved the content related to the application of amyloid PET in the medical settings of cognitively impaired individuals, focusing on clinical scenarios, patient preparation, administered activities, as well as image acquisition, processing, interpretation and reporting. In addition, expert opinions, practices, and protocols of prominent research institutions performing research on amyloid PET of dementia are integrated. With the increasing availability of amyloid PET imaging, a complete and standard pipeline for the entire examination process is essential for clinical practice. This international consensus and practice guideline will help to promote proper clinical use of amyloid PET imaging in patients with AD.

Multimodality imaging of neurodegenerative disorders with a focus on multiparametric magnetic resonance and molecular imaging

Neurodegenerative diseases afflict a large number of persons worldwide, with the prevalence and incidence of dementia rapidly increasing. Despite their prevalence, clinical diagnosis of dementia syndromes remains imperfect with limited specificity. Conventional structural-based imaging techniques also lack the accuracy necessary for confident diagnosis. Multiparametric magnetic resonance imaging and molecular imaging provide the promise of improving specificity and sensitivity in the diagnosis of neurodegenerative disease as well as therapeutic monitoring of monoclonal antibody therapy. This educational review will briefly focus on the epidemiology, clinical presentation, and pathologic findings of common and uncommon neurodegenerative diseases. Imaging features of each disease spanning from conventional magnetic resonance sequences to advanced multiparametric methods such as resting-state functional magnetic resonance imaging and arterial spin labeling imaging will be described in detail. Additionally, the review will explore the findings of each diagnosis on molecular imaging including single-photon emission computed tomography and positron emission tomography with a variety of clinically used and experimental radiotracers. The literature and clinical cases provided demonstrate the power of advanced magnetic resonance imaging and molecular techniques in the diagnosis of neurodegenerative diseases and areas of future and ongoing research. With the advent of combined positron emission tomography/magnetic resonance imaging scanners, hybrid protocols utilizing both techniques are an attractive option for improving the evaluation of neurodegenerative diseases.

Plasma Core Alzheimer's Disease Biomarkers Predict Amyloid Deposition Burden by Positron Emission Tomography in Chinese Individuals with Cognitive Decline

Blood-based biomarkers have been considered as a promising method for the diagnosis of Alzheimer's disease (AD). The reliability and accuracy of plasma core AD biomarkers, including phosphorylated tau (P-tau181), total tau (T-tau), Aβ42, and Aβ40, have also been confirmed in diagnosing AD and predicting cerebral β-amyloid (Aβ) deposition in Western populations, while fewer research studies have ever been conducted in China's Han population. In this study, we investigated the capability of plasma core AD biomarkers in predicting cerebral Aβ deposition burden among the China Aging and Neurodegenerative Disorder Initiative (CANDI) cohort consisting of cognitively normal (CN), mild cognitive impairment (MCI), AD dementia, and non-Alzheimer's dementia disease (Non-ADD). Body fluid (plasma and CSF) AD core biomarkers were measured via single-molecule array (Simoa) immunoassay. The global standard uptake value ratio (SUVR) was then calculated by ¹⁸F-florbetapir PET, which was divided into positive (+) and negative (-). The most significant correlation between plasma and CSF was plasma P-tau181 (r = 0.526, P < 0.0001). Plasma P-tau181 and P-tau181/T-tau ratio were positively correlated with global SUVR (r = 0.257, P < 0.0001; r = 0.263, P < 0.0001, respectively), while Aβ42 and Aβ42/Aβ40 ratio were negatively correlated with global SUVR (r = -0.346, P < 0.0001; r = -0.407, P < 0.0001, respectively). Interestingly, voxel-wise analysis showed that plasma P-tau181 and P-tau181/T-tau ratio were negatively related to ¹⁸F-florbetapir PET in the hippocampus and parahippocampal cortex. The optimal predictive capability in distinguishing all Aβ+ participants from Aβ- participants and MCI+ from MCI- subgroups was the plasma P-tau181/T-tau ratio (AUC = 0.825 and 0.834, respectively). Our study suggested that plasma P-tau181 and P-tau181/T-tau ratio possessed better diagnostic and predictive values than plasma Aβ42 and Aβ42/Aβ40 in this cohort, a finding that may be useful in clinical practices and trials in China.

Measurement of neurodegeneration using a multivariate early frame amyloid PET classifier

Introduction

Amyloid measurement provides important confirmation of pathology for Alzheimer's disease (AD) clinical trials. However, many amyloid positive (Am+) early-stage subjects do not worsen clinically during a clinical trial, and a neurodegenerative measure predictive of decline could provide critical information. Studies have shown correspondence between perfusion measured by early amyloid frames post-tracer injection and fluorodeoxyglucose (FDG) positron emission tomography (PET), but with limitations in sensitivity. Multivariate machine learning approaches may offer a more sensitive means for detection of disease related changes as we have demonstrated with FDG.

Methods

Using summed dynamic florbetapir image frames acquired during the first 6 minutes post-injection for 107 Alzheimer's Disease Neuroimaging Initiative subjects, we applied optimized machine learning to develop and test image classifiers aimed at measuring AD progression. Early frame amyloid (EFA) classification was compared to that of an independently developed FDG PET AD progression classifier by scoring the FDG scans of the same subjects at the same time point. Score distributions and correlation with clinical endpoints were compared to those obtained from FDG. Region of interest measures were compared between EFA and FDG to further understand discrimination performance.

Results

The EFA classifier produced a primary pattern similar to that of the FDG classifier whose expression correlated highly with the FDG pattern (R-squared 0.71), discriminated cognitively normal (NL) amyloid negative (Am-) subjects from all Am+ groups, and that correlated in Am+ subjects with Mini-Mental State Examination, Clinical Dementia Rating Sum of Boxes, and Alzheimer's Disease Assessment Scale-13-item Cognitive subscale (R = 0.59, 0.63, 0.73) and with subsequent 24-month changes in these measures (R = 0.67, 0.73, 0.50).

Discussion

Our results support the ability to use EFA with a multivariate machine learning-derived classifier to obtain a sensitive measure of AD-related loss in neuronal function that correlates with FDG PET in preclinical and early prodromal stages as well as in late mild cognitive impairment and dementia.

Highlights

The summed initial post-injection minutes of florbetapir positron emission tomography  correlate with fluorodeoxyglucose.A machine learning classifier enabled sensitive detection of early prodromal Alzheimer's disease.Early frame amyloid (EFA) classifier scores correlate with subsequent change in Mini-Mental State Examination, Clinical Dementia Rating Sum of Boxes, and Alzheimer's Disease Assessment Scale-13-item Cognitive subscale.EFA classifier effect sizes and clinical prediction outperformed region of interest standardized uptake value ratio.EFA classification may aid in stratifying patients to assess treatment effect.

Clinical Applications of PET/MR Imaging

PET/MR imaging is in routine clinical use and is at least as effective as PET/CT for oncologic and neurologic studies with advantages with certain PET radiopharmaceuticals and applications. In addition, whole body PET/MR imaging substantially reduces radiation dosages compared with PET/CT which is particularly relevant to pediatric and young adult population. For cancer imaging, assessment of hepatic, pelvic, and soft-tissue malignancies may benefit from PET/MR imaging. For neurologic imaging, volumetric brain MR imaging can detect regional volume loss relevant to cognitive impairment and epilepsy. In addition, the single-bed position acquisition enables dynamic brain PET imaging without extending the total study length which has the potential to enhance the diagnostic information from PET.