Usefulness of 3-dimensional stereotactic surface projection FDG PET images for the diagnosis of dementia

PET molecular imaging for pathophysiological visualization in Alzheimer's disease

Alzheimer's disease (AD) is the most common dementia worldwide. The exact etiology of AD is unclear as yet, and no effective treatments are currently available, making AD a tremendous burden posed on the whole society. As AD is a multifaceted and heterogeneous disease, and most biomarkers are dynamic in the course of AD, a range of biomarkers should be established to evaluate the severity and prognosis. Positron emission tomography (PET) offers a great opportunity to visualize AD from diverse perspectives by using radiolabeled agents involved in various pathophysiological processes; PET imaging technique helps to explore the pathomechanisms of AD comprehensively and find out the most appropriate biomarker in each AD phase, leading to a better evaluation of the disease. In this review, we discuss the application of PET in the course of AD and summarized radiolabeled compounds with favorable imaging characteristics.

Statistical Parametric Mapping in Amyloid Positron Emission Tomography

Alzheimer's disease (AD), the most common cause of dementia, has limited treatment options. Emerging disease modifying therapies are targeted at clearing amyloid-β (Aβ) aggregates and slowing the rate of amyloid deposition. However, amyloid burden is not routinely evaluated quantitatively for purposes of disease progression and treatment response assessment. Statistical Parametric Mapping (SPM) is a technique comparing single-subject Positron Emission Tomography (PET) to a healthy cohort that may improve quantification of amyloid burden and diagnostic performance. While primarily used in 2-[18F]-fluoro-2-deoxy-D-glucose (FDG)-PET, SPM's utility in amyloid PET for AD diagnosis is less established and uncertainty remains regarding optimal normal database construction. Using commercially available SPM software, we created a database of 34 non-APOE ε4 carriers with normal cognitive testing (MMSE > 25) and negative cerebrospinal fluid (CSF) AD biomarkers. We compared this database to 115 cognitively normal subjects with variable AD risk factors. We hypothesized that SPM based on our database would identify more positive scans in the test cohort than the qualitatively rated [11C]-PiB PET (QR-PiB), that SPM-based interpretation would correlate better with CSF Aβ42 levels than QR-PiB, and that regional z-scores of specific brain regions known to be involved early in AD would be predictive of CSF Aβ42 levels. Fisher's exact test and the kappa coefficient assessed the agreement between SPM, QR-PiB PET, and CSF biomarkers. Logistic regression determined if the regional z-scores predicted CSF Aβ42 levels. An optimal z-score cutoff was calculated using Youden's index. We found SPM identified more positive scans than QR-PiB PET (19.1 vs. 9.6%) and that SPM correlated more closely with CSF Aβ42 levels than QR-PiB PET (kappa 0.13 vs. 0.06) indicating that SPM may have higher sensitivity than standard QR-PiB PET images. Regional analysis demonstrated the z-scores of the precuneus, anterior cingulate and posterior cingulate were predictive of CSF Aβ42 levels [OR (95% CI) 2.4 (1.1, 5.1) p = 0.024; 1.8 (1.1, 2.8) p = 0.020; 1.6 (1.1, 2.5) p = 0.026]. This study demonstrates the utility of using SPM with a "true normal" database and suggests that SPM enhances diagnostic performance in AD in the clinical setting through its quantitative approach, which will be increasingly important with future disease-modifying therapies.

Heuristic scoring method utilizing FDG-PET statistical parametric mapping in the evaluation of suspected Alzheimer disease and frontotemporal lobar degeneration

Distinguishing frontotemporal lobar degeneration (FTLD) and Alzheimer Disease (AD) on FDG-PET based on qualitative review alone can pose a diagnostic challenge. SPM has been shown to improve diagnostic performance in research settings, but translation to clinical practice has been lacking. Our purpose was to create a heuristic scoring method based on statistical parametric mapping z-scores. We aimed to compare the performance of the scoring method to the initial qualitative read and a machine learning (ML)-based method as benchmarks. FDG-PET/CT or PET/MRI of 65 patients with suspected dementia were processed using SPM software, yielding z-scores from either whole brain (W) or cerebellar (C) normalization relative to a healthy cohort. A non-ML, heuristic scoring system was applied using region counts below a preset z-score cutoff. W z-scores, C z-scores, or WC z-scores (z-scores from both W and C normalization) served as features to build random forest models. The neurological diagnosis was used as the gold standard. The sensitivity of the non-ML scoring system and the random forest models to detect AD was higher than the initial qualitative read of the standard FDG-PET [0.89-1.00 vs. 0.22 (95% CI, 0-0.33)]. A categorical random forest model to distinguish AD, FTLD, and normal cases had similar accuracy than the non-ML scoring model (0.63 vs. 0.61). Our non-ML-based scoring system of SPM z-scores approximated the diagnostic performance of a ML-based method and demonstrated higher sensitivity in the detection of AD compared to qualitative reads. This approach may improve the diagnostic performance.

Associations among education, age, and the dementia with Lewy bodies (DLB) metabolic pattern: A European-DLB consortium project

INTRODUCTION

We assessed the influence of education as a proxy of cognitive reserve and age on the dementia with Lewy bodies (DLB) metabolic pattern.

METHODS

Brain 18F-fluorodeoxyglucose positron emission tomography and clinical/demographic information were available in 169 probable DLB patients included in the European DLB-consortium database. Principal component analysis identified brain regions relevant to local data variance. A linear regression model was applied to generate age- and education-sensitive maps corrected for Mini-Mental State Examination score, sex (and either education or age).

RESULTS

Age negatively covaried with metabolism in bilateral middle and superior frontal cortex, anterior and posterior cingulate, reducing the expression of the DLB-typical cingulate island sign (CIS). Education negatively covaried with metabolism in the left inferior parietal cortex and precuneus (making the CIS more prominent).

DISCUSSION

These findings point out the importance of tailoring interpretation of DLB biomarkers considering the concomitant effect of individual, non-disease-related variables such as age and cognitive reserve.

Direct comparison of brain [18F]FDG images acquired by SiPM-based and PMT-based PET/CT: phantom and clinical studies

Background

Silicon photomultiplier-positron emission tomography (SiPM-PET) has better sensitivity, spatial resolution, and timing resolution than photomultiplier tube (PMT)-PET. The present study aimed to clarify the advantages of SiPM-PET in ¹⁸F-fluoro-2-deoxy-D-glucose ([¹⁸F]FDG) brain imaging in a head-to-head comparison with PMT-PET in phantom and clinical studies.

Methods

Contrast was calculated from images acquired from a Hoffman 3D brain phantom, and image noise and uniformity were calculated from images acquired from a pool phantom using SiPM- and PMT-PET. Sequential PMT-PET and SiPM-PET [¹⁸F]FDG images were acquired over a period of 10 min from 22 controls and 10 patients. All images were separately normalized to a standard [¹⁸F]FDG PET template, then the mean standardized uptake values (SUV_mean) and Z-score were calculated using MIMneuro and CortexID Suite, respectively.

Results

Image contrast, image noise, and uniformity in SiPM-PET changed 19.2, 3.5, and − 40.0% from PMT-PET, respectively. These physical indices of both PET scanners satisfied the criteria for acceptable image quality published by the Japanese Society of Nuclear Medicine of contrast > 55%, CV ≤ 15%, and SD ≤ 0.0249, respectively. Contrast was 70.0% for SiPM-PET without TOF and 59.5% for PMT-PET without TOF. The TOF improved contrast by 3.5% in SiPM-PET. The SUV_mean using SiPM-PET was significantly higher than PMT-PET and did not correlate with a time delay. Z-scores were also significantly higher in images acquired from SiPM-PET (except for the bilateral posterior cingulate) than PMT-PET because the peak signal that was extracted by the calculation of Z-score in CortexID Suite was increased. The hypometabolic area in statistical maps was reduced and localized using SiPM-PET. The trend was independent of whether the images were derived from controls or patients.

Conclusions

The improved spatial resolution and sensitivity of SiPM-PET contributed to better image contrast and uniformity in brain [¹⁸F]FDG images. The SiPM-PET offers better quality and more accurate quantitation of brain PET images. The SUV_mean and Z-scores were higher in SiPM-PET than PMT-PET due to improved PVE. [¹⁸F]FDG images acquired using SiPM-PET will help to improve diagnostic outcomes based on statistical image analysis because SiPM-PET would localize the distribution of glucose metabolism on Z-score maps.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40658-020-00337-4.

Clinical Use of Integrated Positron Emission Tomography-Magnetic Resonance Imaging for Dementia Patients

Combining magnetic resonance imaging (MRI) with 2-deoxy-2-F-fluoro-D-glucose positron emission tomography (FDG-PET) data improve the imaging accuracy for detection of Alzheimer disease and related dementias. Integrated FDG-PET-MRI is a recent technical innovation that allows both imaging modalities to be obtained simultaneously from individual patients with cognitive impairment. This report describes the practical benefits and challenges of using integrated FDG-PET-MRI to support the clinical diagnosis of various dementias. Over the past 7 years, we have performed integrated FDG-PET-MRI on >1500 patients with possible cognitive impairment or dementia. The FDG-PET and MRI protocols are the same as current conventions, but are obtained simultaneously over 25 minutes. An additional Dixon MRI sequence with superimposed bone atlas is used to calculate PET attenuation correction. A single radiologist interprets all imaging data and generates 1 report. The most common positive finding is concordant temporoparietal volume loss and FDG hypometabolism that suggests increased risk for underlying Alzheimer disease. Lobar-specific atrophy and FDG hypometabolism patterns that may be subtle, asymmetric, and focal also are more easily recognized using combined FDG-PET and MRI, thereby improving detection of other neurodegeneration conditions such as primary progressive aphasias and frontotemporal degeneration. Integrated PET-MRI has many practical benefits to individual patients, referrers, and interpreting radiologists. The integrated PET-MRI system requires several modifications to standard imaging center workflows, and requires training individual radiologists to interpret both modalities in conjunction. Reading MRI and FDG-PET together increases imaging diagnostic yield for individual patients; however, both modalities have limitations in specificity.

Metabolic patterns across core features in dementia with lewy bodies

OBJECTIVE

To identify brain regions whose metabolic impairment contributes to dementia with Lewy bodies (DLB) clinical core features expression and to assess the influence of severity of global cognitive impairment on the DLB hypometabolic pattern.

METHODS

Brain fluorodeoxyglucose positron emission tomography and information on core features were available in 171 patients belonging to the imaging repository of the European DLB Consortium. Principal component analysis was applied to identify brain regions relevant to the local data variance. A linear regression model was applied to generate core-feature-specific patterns controlling for the main confounding variables (Mini-Mental State Examination [MMSE], age, education, gender, and center). Regression analysis to the locally normalized intensities was performed to generate an MMSE-sensitive map.

RESULTS

Parkinsonism negatively covaried with bilateral parietal, precuneus, and anterior cingulate metabolism; visual hallucinations (VH) with bilateral dorsolateral-frontal cortex, posterior cingulate, and parietal metabolism; and rapid eye movement sleep behavior disorder (RBD) with bilateral parieto-occipital cortex, precuneus, and ventrolateral-frontal metabolism. VH and RBD shared a positive covariance with metabolism in the medial temporal lobe, cerebellum, brainstem, basal ganglia, thalami, and orbitofrontal and sensorimotor cortex. Cognitive fluctuations negatively covaried with occipital metabolism and positively with parietal lobe metabolism. MMSE positively covaried with metabolism in the left superior frontal gyrus, bilateral-parietal cortex, and left precuneus, and negatively with metabolism in the insula, medial frontal gyrus, hippocampus in the left hemisphere, and right cerebellum.

INTERPRETATION

Regions of more preserved metabolism are relatively consistent across the variegate DLB spectrum. By contrast, core features were associated with more prominent hypometabolism in specific regions, thus suggesting a close clinical-imaging correlation, reflecting the interplay between topography of neurodegeneration and clinical presentation in DLB patients. Ann Neurol 2019;85:715-725.

PET Imaging for Early Detection of Alzheimer's Disease: From Pathologic to Physiologic Biomarkers

This article describes the application of various PET imaging agents in the investigation and diagnosis of Alzheimer's disease (AD), including radiotracers for pathologic biomarkers of AD such as β-amyloid deposits and tau protein aggregates, and the neuroinflammation biomarker 18 kDa translocator protein, as well as physiologic biomarkers, such as cholinergic receptors, glucose metabolism, and the synaptic density biomarker synaptic vesicle glycoprotein 2A. Potential of these biomarkers for early AD diagnosis is also assessed.