Predicting long‐term clinical stability in amyloid‐positive subjects by FDG‐PET
Annals of Clinical and Translational Neurology, online-first, doi:10.1002/acn3.782
Publication year: 2019
Imaging biomarkers can be used to screen participants for Alzheimer’s disease clinical trials. To test the predictive values in clinical progression of neuropathology change (amyloid‐PET) or brain metabolism as neurodegeneration biomarker ([18F]FDG‐PET), we evaluated data from N = 268 healthy controls and N = 519 mild cognitive impairment subjects. Despite being a significant risk factor, amyloid positivity was not associated with clinical progression in the majority (≥60%) of subjects. Notably, a negative [18F]FDG‐PET scan at baseline strongly predicted clinical stability with high negative predictive values (>0.80) for both groups. We suggest [18F]FDG‐PET brain metabolism or other neurodegeneration measures should be coupled to amyloid‐PET to exclude clinically stable individuals from clinical trials.
Brain glucose metabolism in Lewy body dementia: implications for diagnostic criteria
Alzheimers Res Ther. 2019 Feb 23;11(1):20. doi: 10.1186/s13195-019-0473-4.
Publication year: 2019
[18F]FDG-PET hypometabolism patterns are indicative of different neurodegenerative conditions, even from the earliest disease phase. This makes [18F]FDG-PET a valuable tool in the diagnostic workup of neurodegenerative diseases. The utility of [18F]FDG-PET in dementia with Lewy bodies (DLB) needs further validation by considering large samples of patients and disease comparisons and applying state-of-the-art statistical methods. Here, we aimed to provide an extensive validation of the [18F]FDG-PET metabolic signatures in supporting DLB diagnosis near the first clinical assessment, which is characterized by high diagnostic uncertainty, at the single-subject level.
In this retrospective study, we included N = 72 patients with heterogeneous clinical classification at entry (mild cognitive impairment, atypical parkinsonisms, possible DLB, probable DLB, and other dementias) and an established diagnosis of DLB at a later follow-up. We generated patterns of [18F]FDG-PET hypometabolism in single cases by using a validated voxel-wise analysis (p < 0.05, FWE-corrected). The hypometabolism patterns were independently classified by expert raters blinded to any clinical information. The final clinical diagnosis at follow-up (2.94 ± 1.39 [0.34-6.04] years) was considered as the diagnostic reference and compared with clinical classification at entry and with [18F]FDG-PET classification alone. In addition, we calculated the diagnostic accuracy of [18F]FDG-PET maps in the differential diagnosis of DLB with Alzheimer’s disease dementia (ADD) (N = 60) and Parkinson’s disease (PD) (N = 36).
The single-subject [18F]FDG-PET hypometabolism pattern, showing temporo-parietal and occipital involvement, was highly consistent across DLB cases. Clinical classification at entry produced several misclassifications with an agreement of only 61.1% with the diagnostic reference. On the contrary, [18F]FDG-PET hypometabolism maps alone accurately predicted diagnosis of DLB at follow-up (88.9%). The high power of the [18F]FDG-PET hypometabolism signature in predicting the final clinical diagnosis allowed a ≈ 50% increase in accuracy compared to the first clinical assessment alone. Finally, [18F]FDG-PET hypometabolism maps yielded extremely high discriminative power, distinguishing DLB from ADD and PD conditions with an accuracy of > 90%.
The present validation of the diagnostic and prognostic accuracy of the disease-specific brain metabolic signature in DLB at the single-subject level argues for the consideration of [18F]FDG-PET in the early phase of the DLB diagnostic flowchart. The assessment of the [18F]FDG-PET hypometabolism pattern at entry may shorten the diagnostic time, resulting in benefits for treatment options and management of patients.
The brain metabolic signature of visual hallucinations in Dementia with Lewy Bodies
CORTEX 2018, epub ahead of print. https://doi.org/10.1016/j.cortex.2018.06.014
Publication year: 2018
Visual hallucinations (VH) are a core clinical feature of dementia with Lewy bodies (DLB), but their specific neural substrate remains elusive. We used 18F-FDG-PET to study the neural dysfunctional signature of VH in a group of 38 DLB patients (mean age±sd 72.9±7.5) with available anamnestic records, cognitive and neurological examination and NeuroPsychiatric Inventory assessing VH. We tested the voxel-wise correlation between 18F-FDG-PET hypometabolism and VH NPI scores at the whole-group level, then adopting inter-regional correlation analysis to explore the resting-state networks (RSNs) metabolic connectivity in DLB patients with and without visual hallucinations, as compared to N=38 age-matched healthy controls (HCs) (mean age±sd 71.5±6.9). At the whole-group level, we found a negative correlation between VH NPI scores and 18F-FDG-PET hypometabolism in the right occipito-temporal cortex (p<0.001 uncorrected, p<0.05 Family-Wise Error cluster-corrected). Then, splitting the group according to VH presence, we found that DLB non-hallucinators presented a pattern of connectivity seeding from this occipito-temporal cluster and extending to the ventral visual stream. At difference, the DLB hallucinators showed a metabolic connectivity pattern limited to the occipital-dorsal parietal regions. As for RSNs, both the DLB subgroups showed a markedly reduced extent of attentional and visual networks compared to HCs, with a variable alteration in the topography. DLB-VH patients showed a more pronounced shrinkage of the primary visual network, which was disconnected from the higher visual hubs, at difference with both HC and DLB non-hallucinators. These findings suggest that an altered brain metabolic connectivity within and beyond visual systems may promote VH in DLB. These results support the most recent neurocognitive models interpreting VH as the result of an inefficient recruitment of the ventral visual stream and of a large-scale multi-network derangement.
Rates of Amyloid Imaging Positivity in Patients With Primary Progressive Aphasia
JAMA Neurology. Published online January 8, 2018. doi:10.1001/jamaneurol.2017.4309
Publication year: 2018
Importance The ability to predict the pathology underlying different neurodegenerative syndromes is of critical importance owing to the advent of molecule-specific therapies.
Objective To determine the rates of positron emission tomography (PET) amyloid positivity in the main clinical variants of primary progressive aphasia (PPA).
Design, Setting, and Participants This prospective clinical-pathologic case series was conducted at a tertiary research clinic specialized in cognitive disorders. Patients were evaluated as part of a prospective, longitudinal research study between January 2002 and December 2015. Inclusion criteria included clinical diagnosis of PPA; availability of complete speech, language, and cognitive testing; magnetic resonance imaging performed within 6 months of the cognitive evaluation; and PET carbon 11–labeled Pittsburgh Compound-B or florbetapir F 18 brain scan results. Of 109 patients referred for evaluation of language symptoms who underwent amyloid brain imaging, 3 were excluded because of incomplete language evaluations, 5 for absence of significant aphasia, and 12 for presenting with significant initial symptoms outside of the language domain, leaving a cohort of 89 patients with PPA.
Main Outcomes and Measures Clinical, cognitive, neuroimaging, and pathology results.
Results Twenty-eight cases were classified as imaging-supported semantic variant PPA (11 women [39.3%]; mean [SD] age, 64  years), 31 nonfluent/agrammatic variant PPA (22 women [71.0%]; mean [SD] age, 68  years), 26 logopenic variant PPA (17 women [65.4%]; mean [SD] age, 63  years), and 4 mixed PPA cases. Twenty-four of 28 patients with semantic variant PPA (86%) and 28 of 31 patients with nonfluent/agrammatic variant PPA (90%) had negative amyloid PET scan results, while 25 of 26 patients with logopenic variant PPA (96%) and 3 of 4 mixed PPA cases (75%) had positive scan results. The amyloid positive semantic variant PPA and nonfluent/agrammatic variant PPA cases with available autopsy data (2 of 4 and 2 of 3, respectively) all had a primary frontotemporal lobar degeneration and secondary Alzheimer disease pathologic diagnoses, whereas autopsy of 2 patients with amyloid PET–positive logopenic variant PPA confirmed Alzheimer disease. One mixed PPA patient with a negative amyloid PET scan had Pick disease at autopsy.
Conclusions and Relevance Primary progressive aphasia variant diagnosis according to the current classification scheme is associated with Alzheimer disease biomarker status, with the logopenic variant being associated with carbon 11–labeled Pittsburgh Compound-B positivity in more than 95% of cases. Furthermore, in the presence of a clinical syndrome highly predictive of frontotemporal lobar degeneration pathology, biomarker positivity for Alzheimer disease may be associated more with mixed pathology rather than primary Alzheimer disease.
Low-dose CT for the spatial normalization of PET images: A validation procedure for amyloid-PET semi-quantification
Neuroimage:Clinical (20) pp.153-160
Publication year: 2018
The reference standard for spatial normalization of brain positron emission tomography(PET) images involves structural Magnetic Resonance Imaging (MRI) data. However, the lack of such structural information is fairly common in clinical settings. This might lead to lack of proper image quantification and to evaluation based only on visual ratings, which does not allow research studies or clinical trials based on quantification.
PET/CT systems are widely available and CT normalization procedures need to be explored. Here we describe and validate a procedure for the spatial normalization of PETimages based on the low-dose Computed Tomography (CT) images contextually acquired for attenuation correction in PET/CT systems. We included N = 34 subjects, spanning from cognitively normal to mild cognitive impairment and dementia, who underwent amyloid-PET/CT (18F-Florbetaben) and structural MRI scans. The proposed pipeline is based on the SPM12 unified segmentation algorithm applied to low-dose CT images. The validation of the normalization pipeline focused on 1) statistical comparisons between regional and global 18F-Florbetaben-PET/CT standardized uptake value ratios (SUVrs) estimated from both CT-based and MRI-based normalized PET images (SUVrCT, SUVrMRI) and 2) estimation of the degrees of overlap between warped gray matter (GM) segmented maps derived from CT- and MRI-based spatial transformations.
We found negligible deviations between regional and global SUVrs in the two CT and MRI-based methods. SUVrCT and SUVrMRI global uptake scores showed negligible differences (mean ± sd 0.01 ± 0.03). Notably, the CT- and MRI-based warped GM maps showed excellent overlap (90% within 1 mm).
The proposed analysis pipeline, based on low-dose CT images, allows accurate spatial normalization and subsequent PET image quantification. A CT-based analytical pipeline could benefit both research and clinical practice, allowing the recruitment of larger samples and favoring clinical routine analysis.
18F-VC701-PET and MRI in the in vivo neuroinflammation assessment of a mouse model of multiple sclerosis
J Neuroinflammation. 2018 Feb 5;15(1):33. doi: 10.1186/s12974-017-1044-x
Publication year: 2018
Positron emission tomography (PET) using translocator protein (TSPO) ligands has been used to detect neuroinflammatory processes in neurological disorders, including multiple sclerosis (MS). The aim of this study was to evaluate neuroinflammation in a mouse MS model (EAE) using TSPO-PET with 18F-VC701, in combination with magnetic resonance imaging (MRI).
MOG35-55/CFA and pertussis toxin protocol was used to induce EAE in C57BL/6 mice. Disease progression was monitored daily, whereas MRI evaluation was performed at 1, 2, and 4 weeks post-induction. Microglia activation was assessed in vivo by 18F-VC701 PET at the time of maximum disease score and validated by radioligand ex vivo distribution and immunohistochemistry at 2 and 4 weeks post-immunization.
In vivo and ex vivo analyses show that 18F-VC701 significantly accumulates within the central nervous system (CNS), particularly in the cortex, striatum, hippocampus, cerebellum, and cervical spinal cord of EAE compared to control mice, at 2 weeks post-immunization. MRI confirmed the presence of focal brain lesions at 2 weeks post-immunization in both T1-weighted and T2 images. Of note, MRI abnormalities attenuated in later post-immunization phase. Neuropathological analysis confirmed the presence of microglial activation in EAE mice, consistent with the in vivo increase of 18F-VC701 uptake.
Increase of 18F-VC701 uptake in EAE mice is strongly associated with the presence of microglia activation in the acute phase of the disease. The combined use of TSPO-PET and MRI provided complementary evidence on the ongoing disease process, thus representing an attractive new tool to investigate neuronal damage and neuroinflammation at preclinical levels.
Local and distant relationships between amyloid, tau and neurodegeneration in Alzheimer's Disease
Neuroimage:Clinical, 2017, online-first
Publication year: 2017
The relationships between β-amyloid (Aβ), tau and neurodegeneration within Alzheimer’s Disease pathogenesis are not fully understood. To explore these associations in vivo, we evaluated 30 Aβ PET-positive patients (mean ± sd age 62.4 ± 8.3) with mild probable AD and 12 Aβ PET-negative healthy controls (HC) (mean ± sd age 77.3 ± 6.9) as comparison. All participants underwent 3 T MRI, 11C-PiB (Aβ) PET and 18F-AV1451 (tau) PET. Multimodal correlation analyses were run at both voxel- and region-of-interest levels. 11C-PiB retention in AD showed the most diffuse uptake pattern throughout association neocortex, whereas 18F-AV1451 and gray matter volume reduction (GMR) showed a progressive predilection for posterior cortices (p<0.05 Family-Wise Error-[FWE]-corrected). Voxel-level analysis identified negative correlations between 18F-AV1451 and gray matter peaking in medial and infero-occipital regions (p<0.01 False Discovery Rate-[FDR]-corrected). 18F-AV1451 and 11C-PiB were positively correlated in right parietal and medial/inferior occipital regions (p<0.001 uncorrected). 11C-PiB did not correlate with GMR at the voxel-level. Regionally, 18F-AV1451 was largely associated with local/adjacent GMR whereas frontal 11C-PiB correlated with GMR in posterior regions. These findings suggest that, in mild AD, tau aggregation drives local neurodegeneration, whereas the relationships between Aβ and neurodegeneration are not region specific and may be mediated by the interaction between Aβ and tau.
An In Vivo 11C-(R)-PK11195 PET and In Vitro Pathology Study of Microglia Activation in Creutzfeldt-Jakob Disease
Mol Neurobiol (2017). doi:10.1007/s12035-017-0522-6
Publication year: 2017
Microgliosis is part of the immunobiology of Creutzfeldt-Jakob disease (CJD). This is the first report using 11C-(R)-PK11195 PET imaging in vivo to measure 18 kDa translocator protein (TSPO) expression, indexing microglia activation, in symptomatic CJD patients, followed by a postmortem neuropathology comparison. One genetic CJD (gCJD) patient, two sporadic CJD (sCJD) patients, one variant CJD (vCJD) patient (mean ± SD age, 47.50 ± 15.95 years), and nine healthy controls (mean ± SD age, 44.00 ± 11.10 years) were included in the study. TSPO binding potentials were estimated using clustering and parametric analyses of reference regions. Statistical comparisons were run at the regional and at the voxel-wise levels. Postmortem evaluation measured scrapie prion protein (PrPSc) immunoreactivity, neuronal loss, spongiosis, astrogliosis, and microgliosis. 11C-(R)-PK11195-PET showed a significant TSPO overexpression at the cortical level in the two sCJD patients, as well as thalamic and cerebellar involvement; very limited parieto-occipital activation in the gCJD case; and significant increases at the subcortical level in the thalamus, basal ganglia, and midbrain and in the cerebellum in the vCJD brain. Along with misfolded prion deposits, neuropathology in all patients revealed neuronal loss, spongiosis and astrogliosis, and a diffuse cerebral and cerebellar microgliosis which was particularly dense in thalamic and basal ganglia structures in the vCJD brain. These findings confirm significant microgliosis in CJD, which was variably modulated in vivo and more diffuse at postmortem evaluation. Thus, TSPO overexpression in microglia activation, topography, and extent can vary in CJD subtypes, as shown in vivo, possibly related to the response to fast apoptotic processes, but reaches a large amount at the final disease course.
A Cross-Validation of FDG- and Amyloid-PET Biomarkers in Mild Cognitive Impairment for the Risk Prediction to Dementia due to Alzheimer's Disease in a Clinical Setting.
J Alzheimers Dis. 2017 Jun 24. doi: 10.3233/JAD-170158. [Epub ahead of print]
Publication year: 2017
Assessments of brain glucose metabolism (18F-FDG-PET) and cerebral amyloid burden (11C-PiB-PET) in mild cognitive impairment (MCI) have shown highly variable performances when adopted to predict progression to dementia due to Alzheimer’s disease (ADD). This study investigates, in a clinical setting, the separate and combined values of 18F-FDG-PET and 11C-PiB-PET in ADD conversion prediction with optimized data analysis procedures. Respectively, we investigate the accuracy of an optimized SPM analysis for 18F-FDG-PET and of standardized uptake value ratio semiquantification for 11C-PiB-PET in predicting ADD conversion in 30 MCI subjects (age 63.57±7.78 years). Fourteen subjects converted to ADD during the follow-up (median 26.5 months, inter-quartile range 30 months). Receiver operating characteristic analyses showed an area under the curve (AUC) of 0.89 and of 0.81 for, respectively, 18F-FDG-PET and 11C-PiB-PET. 18F-FDG-PET, compared to 11C-PiB-PET, showed higher specificity (1.00 versus 0.62, respectively), but lower sensitivity (0.79 versus 1.00). Combining the biomarkers improved classification accuracy (AUC = 0.96). During the follow-up time, all the MCI subjects positive for both PET biomarkers converted to ADD, whereas all the subjects negative for both remained stable. The difference in survival distributions was confirmed by a log-rank test (p = 0.002). These results indicate a very high accuracy in predicting MCI to ADD conversion of both 18F-FDG-PET and 11C-PiB-PET imaging, the former showing optimal performance based on the SPM optimized parametric assessment. Measures of brain glucose metabolism and amyloid load represent extremely powerful diagnostic and prognostic biomarkers with complementary roles in prodromal dementia phase, particularly when tailored to individual cases in clinical settings.