Biopathological Significance of Early-Phase Amyloid Imaging in the Spectrum of Alzheimer’s Disease

Analysis of positron emission tomography hypometabolic patterns and neuropsychiatric symptoms in patients with dementia syndromes

AIMS

To estimate the proportions of specific hypometabolic patterns and their association with neuropsychiatric symptoms (NPS) in patients with cognitive impairment (CI).

METHODS

This multicenter study with 1037 consecutive patients was conducted from December 2012 to December 2019. ¹⁸ F-FDG PET and clinical/demographic information, NPS assessments were recorded and analyzed to explore the associations between hypometabolic patterns and clinical features by correlation analysis and multivariable logistic regression models.

RESULTS

Patients with clinical Alzheimer's disease (AD, 81.6%, 605/741) and dementia with Lewy bodies (67.9%, 19/28) mostly had AD-pattern hypometabolism, and 76/137 (55.5%) of patients with frontotemporal lobar degeneration showed frontal and anterior temporal pattern (FT-P) hypometabolism. Besides corticobasal degeneration, patients with behavioral variant frontotemporal dementia (36/58), semantic dementia (7/10), progressive non-fluent aphasia (6/9), frontotemporal lobar degeneration and amyotrophic lateral sclerosis (3/5), and progressive supranuclear palsy (21/37) also mostly showed FT-P hypometabolism. The proportion of FT-P hypometabolism was associated with the presence of hallucinations (R = 0.171, p = 0.04), anxiety (R = 0.182, p = 0.03), and appetite and eating abnormalities (R = 0.200, p = 0.01) in AD.

CONCLUSION

Specific hypometabolic patterns in FDG-PET are associated with NPS and beneficial for the early identification and management of NPS in patients with CI.

Deep-learning prediction of amyloid deposition from early-phase amyloid positron emission tomography imaging

OBJECTIVE

While the use of biomarkers for the detection of early and preclinical Alzheimer's Disease has become essential, the need to wait for over an hour after injection to obtain sufficient image quality can be challenging for patients with suspected dementia and their caregivers. This study aimed to develop an image-based deep-learning technique to generate delayed uptake patterns of amyloid positron emission tomography (PET) images using only early-phase images obtained from 0-20 min after radiotracer injection.

METHODS

We prepared pairs of early and delayed [¹¹C]PiB dynamic images from 253 patients (cognitively normal n = 32, fronto-temporal dementia n = 39, mild cognitive impairment n = 19, Alzheimer's disease n = 163) as a training dataset. The neural network was trained with the early images as the input, and the output was the corresponding delayed image. A U-net convolutional neural network (CNN) and a conditional generative adversarial network (C-GAN) were used for the deep-learning architecture and the data augmentation methods, respectively. Then, an independent test data set consisting of early-phase amyloid PET images (n = 19) was used to generate corresponding delayed images using the trained network. Two nuclear medicine physicians interpreted the actual delayed images and predicted delayed images for amyloid positivity. In addition, the concordance of the actual delayed and predicted delayed images was assessed statistically.

RESULTS

The concordance of amyloid positivity between the actual versus AI-predicted delayed images was 79%(κ = 0.60) and 79% (κ = 0.59) for each physician, respectively. In addition, the physicians' agreement rate was at 89% (κ = 0.79) when the same image was interpreted. And, the actual versus AI-predicted delayed images were not readily distinguishable (correct answer rate, 55% and 47% for each physician, respectively). The statistical comparison of the actual versus the predicted delated images indicated that the peak signal-to-noise ratio (PSNR) was 21.8 dB ± 2.2 dB, and the structural similarity index (SSIM) was 0.45 ± 0.04.

CONCLUSION

This study demonstrates the feasibility of an image-based deep-learning framework to predict delayed patterns of Amyloid PET uptake using only the early phase images. This AI-based image generation method has the potential to reduce scan time for amyloid PET and increase the patient throughput, without sacrificing diagnostic accuracy for amyloid positivity.

The Use, Standardization, and Interpretation of Brain Imaging Data in Clinical Trials of Neurodegenerative Disorders

Imaging biomarkers play a wide-ranging role in clinical trials for neurological disorders. This includes selecting the appropriate trial participants, establishing target engagement and mechanism-related pharmacodynamic effect, monitoring safety, and providing evidence of disease modification. In the early stages of clinical drug development, evidence of target engagement and/or downstream pharmacodynamic effect-especially with a clear relationship to dose-can provide confidence that the therapeutic candidate should be advanced to larger and more expensive trials, and can inform the selection of the dose(s) to be further tested, i.e., to "de-risk" the drug development program. In these later-phase trials, evidence that the therapeutic candidate is altering disease-related biomarkers can provide important evidence that the clinical benefit of the compound (if observed) is grounded in meaningful biological changes. The interpretation of disease-related imaging markers, and comparability across different trials and imaging tools, is greatly improved when standardized outcome measures are defined. This standardization should not impinge on scientific advances in the imaging tools per se but provides a common language in which the results generated by these tools are expressed. PET markers of pathological protein aggregates and structural imaging of brain atrophy are common disease-related elements across many neurological disorders. However, PET tracers for pathologies beyond amyloid β and tau are needed, and the interpretability of structural imaging can be enhanced by some simple considerations to guard against the possible confound of pseudo-atrophy. Learnings from much-studied conditions such as Alzheimer's disease and multiple sclerosis will be beneficial as the field embraces rarer diseases.

[18 F]FDG PET may differentiate cerebral amyloid angiopathy from Alzheimer's disease

BACKGROUND

Cerebral amyloid angiopathy (CAA) is a frequent cause of both intracerebral hemorrhage (ICH) and cognitive impairment in the elderly. Diagnosis relies on the Boston criteria, which use magnetic resonance imaging markers including ≥2 exclusively lobar cerebral microbleeds (lCMBs). Although amyloid positron emission tomography (PET) may provide molecular diagnosis, its specificity relative to Alzheimer's disease (AD) is limited due to the prevalence of positive amyloid PET in cognitively normal elderly. Using early-phase ¹¹ C-Pittsburgh compound B as surrogate for tissue perfusion, a significantly lower occipital/posterior cingulate (O/PC) tracer uptake ratio in probable CAA relative to AD was recently reported, consistent with histopathological lesion distribution. We tested whether this finding could be reproduced using [¹⁸ F]fluorodeoxyglucose (FDG)-PET, a widely available modality that correlates well with early-phase amyloid PET in both healthy subjects and AD.

METHODS

From a large memory clinic database, we retrospectively included 14 patients with probable CAA (Boston criteria) and 21 patients with no lCMB fulfilling AD criteria including cerebrospinal fluid biomarkers. In all, [¹⁸ F]FDG-PET/computed tomography (CT) was available as part of routine care. No subject had a clinical history of ICH. Regional standardized [¹⁸ F]FDG uptake values normalized to the pons (standard uptake value ratio [SUVr]) were obtained, and the O/PC ratio was calculated.

RESULTS

The SUVr O/PC ratio was significantly lower in CAA versus AD (1.02 ± 0.14 vs. 1.19 ± 0.18, respectively; p = 0.024).

CONCLUSIONS

Despite the small sample, our findings are consistent with the previous early-phase amyloid PET study. Thus, [¹⁸ F]FDG-PET may help differentiate CAA from AD, particularly in cases of amyloid PET positivity. Larger prospective studies, including in CAA-related ICH, are however warranted.