This is an international multicentre study aimed at evaluating the combined value of dopaminergic neuroimaging and clinical features in predicting future phenoconversion of idiopathic REM sleep behaviour (iRBD) subjects to overt synucleinopathy. Nine centres sent 123I-FP-CIT-SPECT data of 344 iRBD patients and 256 controls for centralized analysis. 123I-FP-CIT-SPECT images were semiquantified using DaTQUANTTM, obtaining putamen and caudate specific to non-displaceable binding ratios (SBRs). The following clinical variables were also analysed: (i) Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale, motor section score; (ii) Mini-Mental State Examination score; (iii) constipation; and (iv) hyposmia. Kaplan-Meier survival analysis was performed to estimate conversion risk. Hazard ratios for each variable were calculated with Cox regression. A generalized logistic regression model was applied to identify the best combination of risk factors. Bayesian classifier was used to identify the baseline features predicting phenoconversion to parkinsonism or dementia. After quality check of the data, 263 iRBD patients (67.6 ± 7.3 years, 229 males) and 243 control subjects (67.2 ± 10.1 years, 110 males) were analysed. Fifty-two (20%) patients developed a synucleinopathy after average follow-up of 2 years. The best combination of risk factors was putamen dopaminergic dysfunction of the most affected hemisphere on imaging, defined as the lower value between either putamina (P < 0.000001), constipation, (P < 0.000001) and age over 70 years (P = 0.0002). Combined features obtained from the generalized logistic regression achieved a hazard ratio of 5.71 (95% confidence interval 2.85–11.43). Bayesian classifier suggested that patients with higher Mini-Mental State Examination score and lower caudate SBR asymmetry were more likely to develop parkinsonism, while patients with the opposite pattern were more likely to develop dementia. This study shows that iRBD patients older than 70 with constipation and reduced nigro-putaminal dopaminergic function are at high risk of short-term phenoconversion to an overt synucleinopathy, providing an effective stratification approach for future neuroprotective trials. Moreover, we provide cut-off values for the significant predictors of phenoconversion to be used in single subjects.
Hypometabolism in PiB-positive, cognitively normal subjects in a population-based cohort occurs in AD-signature cortical regions and to a lesser extent in other cortical regions. It is more pronounced with higher amyloid load and supports a dose-dependent association. The effect of APOE ε4 carriage in this group of subjects does not appear to modify their hypometabolic "AD-like" neurodegeneration. Consideration of hypometabolism associated with amyloid load may aid trials of AD drug therapy.
Objective: We describe the operationalization of the National Institute on Aging-Alzheimer's Association (NIA-AA) workgroup diagnostic guidelines pertaining to Alzheimer disease (AD) dementia in a large multicenter group of subjects with AD dementia.Methods: Subjects with AD dementia from the Alzheimer's Disease Neuroimaging Initiative (ADNI) with at least 1 amyloid biomarker (n 5 211) were included in this report. Biomarker data from CSF Ab42, amyloid PET, fluorodeoxyglucose-PET, and MRI were examined. The biomarker results were assessed on a per-patient basis and the subject categorization as defined in the NIA-AA workgroup guidelines was determined.Results: When using a requirement that subjects have a positive amyloid biomarker and single neuronal injury marker having an AD pattern, 87% (48% for both neuronal injury biomarkers) of the subjects could be categorized as "high probability" for AD. Amyloid status of the combined Pittsburgh compound B-PET and CSF results showed an amyloid-negative rate of 10% in the AD group. In the ADNI AD group, 5 of 92 subjects fit the category "dementia unlikely due to AD" when at least one neuronal injury marker was negative.Conclusions: A large proportion of subjects with AD dementia in ADNI may be categorized more definitively as high-probability AD using the proposed biomarker scheme in the NIA-AA criteria. A minority of subjects may be excluded from the diagnosis of AD by using biomarkers in clinically categorized AD subjects. In a well-defined AD dementia population, significant biomarker inconsistency can be seen on a per-patient basis. Recent recommendations from the National Institute on Aging-Alzheimer's Association (NIA-AA) workgroup for clinical diagnostic guidelines (NIA-AA-C) for Alzheimer disease (AD) dementia have integrated biomarkers into the diagnostic algorithm of AD.1 The diagnostic category of probable AD (pAD) dementia is modified by the results of biomarker findings.Many investigators have validated biomarkers using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Biomarkers have been used to characterize diagnostic groups within the ADNI population.2,3 AD subject fluorodeoxyglucose (FDG) categorization accuracy in ADNI was 85% 4 and had a sensitivity and specificity of 83% and 78% using a quantitative image analysis program.5 Similar reports on FDG, 6 MRI, 7 or CSF 8 performance are based on ADNI subject categorization. Investigators have evaluated the interaction of biomarker modalities in defining the ADNI subject groups.2,9-11 Other publications predict which subjects will progress to AD using MRI. [12][13][14][15][16] Others have derived new analysis methods for imaging biomarker data [17][18][19][20][21][22][23][24][25][26][27] or developed theories of biomarker progression patterns. 28 To our knowledge, the NIA-AA-C criteria have not yet been studied in a systematic manner.
Our rationale was to conduct a retrospective study comparing 3 123 I-N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl)nortropane ( 123 I-FP-CIT) SPECT quantitative methods in patients with neurodegenerative syndromes as referenced to neuropathologic findings. Methods: 123 I-FP-CIT-SPECT and neuropathologic findings among patients with neurodegenerative syndromes from the Mayo Alzheimer Disease Research Center and Mayo Clinic Study of Aging were examined. Three 123 I-FP-CIT SPECT quantitative assessment methods -MIMneuro, DaTQUANT, and manual region-of-interest creation on a workstation-were compared with neuropathologic findings describing the presence or absence of Lewy body disease (LBD). Striatum-to-background ratios (SBRs) generated by DaTQUANT were compared with the calculated SBRs of the manual method and MIMneuro. The left and right SBRs for caudate, putamen, and striatum were evaluated with the manual method. For DaTQUANT and MIMneuro, the left, right, total, and average SBRs and z scores for whole striatum, caudate, putamen, anterior putamen, and posterior putamen were calculated. Results: The cohort included 24 patients (20 [83%] male, mean age for all patients at death, 75.4 ± 10.0 y). The antemortem clinical diagnoses were Alzheimer disease dementia (n 5 6), probable dementia with Lewy bodies (n 5 12), mixed Alzheimer disease dementia and probable dementia with Lewy bodies (n 5 1), Parkinson disease with mild cognitive impairment (n 5 2), corticobasal syndrome (n 5 1), idiopathic rapid-eye-movement sleep behavior disorder (n 5 1), and behavioral-variant frontotemporal dementia (n 5 1). Seventeen (71%) had LBD. All 3 123 I-FP-CIT SPECT quantitative methods had an area under the receiveroperating-characteristics curve ranging from more than 0.93 to up to 1.000 (P , 0.001) and showed excellent discrimination between LBD and non-LBD patients in each region assessed (P , 0.001). There was no significant difference between the accuracy of the regions in discriminating the 2 groups, with good discrimination for both caudate and putamen. Conclusion: All 3 123 I-FP-CIT SPECT quantitative methods showed excellent discrimination between LBD and non-LBD patients in each region assessed, using both SBRs and z scores.
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