ArcheD, a residual neural network for prediction of cerebrospinal fluid amyloid-beta from amyloid PET images.

Detection and measurement of amyloid-beta (Aß) in the brain is a key factor for early identification and diagnosis of Alzheimer's disease (AD). We aimed to develop a deep learning model to predict Aß cerebrospinal fluid (CSF) concentration directly from amyloid PET images, independent of tracers, brain reference regions or preselected regions of interest. We used 1870 Aß PET images and CSF measurements to train and validate a convolutional neural network ("ArcheD"). We evaluated the ArcheD performance in relation to episodic memory and the standardized uptake value ratio (SUVR) of cortical Aß. We also compared the brain region's relevance for the model's CSF prediction within clinical-based and biological-based classifications. ArcheD-predicted Aß CSF values correlated with measured Aß CSF values (r = 0.92; q < 0.01), SUVR (rAV45 = -0.64, rFBB = -0.69; q < 0.01) and episodic memory measures (0.33 < r < 0.44; q < 0.01). For both classifications, cerebral white matter significantly contributed to CSF prediction (q < 0.01), specifically in non-symptomatic and early stages of AD. However, in late-stage disease, the brain stem, subcortical areas, cortical lobes, limbic lobe and basal forebrain made more significant contributions (q < 0.01). Considering cortical grey matter separately, the parietal lobe was the strongest predictor of CSF amyloid levels in those with prodromal or early AD, while the temporal lobe played a more crucial role for those with AD. In summary, ArcheD reliably predicted Aß CSF concentration from Aß PET scans, offering potential clinical utility for Aß level determination.

Cortical Amyloid Burden Relates to Basal Forebrain Volume in Subjective Cognitive Decline.

BACKGROUND: Atrophy of cholinergic basal forebrain (BF) nuclei is a frequent finding in magnetic resonance imaging (MRI) volumetry studies that examined patients with prodromal or clinical Alzheimer's disease (AD), but less clear for individuals in earlier stages of the clinical AD continuum. OBJECTIVE: To examine BF volume reductions in subjective cognitive decline (SCD) participants with AD pathologic changes. METHODS: The present study compared MRI-based BF volume measurements in age- and sex-matched samples of N = 24 amyloid-positive and N = 24 amyloid-negative SCD individuals, based on binary visual ratings of Florbetaben positron emission tomography (PET) measurements. Additionally, we assessed associations of BF volume with cortical amyloid burden, based on semiquantitative Centiloid (CL) analyses. RESULTS: Group differences approached significance for BF total volume (p = 0.061) and the Ch4 subregion (p = 0.059) only, showing the expected relative volume reductions for the amyloid-positive subgroup. There were also significant inverse correlations between BF volumes and CL values, which again were most robust for BF total volume and the Ch4 subregion. CONCLUSIONS: The results are consistent with the hypothesis that amyloid-positive SCD individuals, which are considered to represent a transitional stage on the clinical AD continuum, already show incipient alterations of BF integrity. The negative association with a continuous measure of cortical amyloid burden also suggests that this may reflect an incremental process. Yet, further research is needed to evaluate whether BF changes already emerge at "grey zone" levels of amyloid accumulation, before amyloidosis is reliably detected by PET visual readings.

The effect of plasma cortisol on hippocampal atrophy and clinical progression in mild cognitive impairment.

Introduction: Both elevated cortisol and hippocampal volume have been linked to an increased risk for the development of Alzheimer's disease (AD). This longitudinal study assessed the effects of plasma cortisol on hippocampal atrophy and clinical progression rates in patients with mild cognitive impairment (MCI). Methods: Patients with amnestic MCI (n = 304) were selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) based on availability of baseline plasma cortisol and hippocampal volume measures, assessed at baseline and during follow-ups. We investigated associations between plasma cortisol, hippocampal volume, and risk of clinical progression to AD over a study period of up to 100 months (mean follow-up time 36.8 months) using linear mixed models, Cox proportional hazards models, and Kaplan-Meier estimators. Results: Plasma cortisol predicted greater hippocampal atrophy, such that participants with higher cortisol showed faster decline in hippocampal volume over time (interaction: ß = -0.15, p = 0.004). Small hippocampal volume predicted a higher risk of clinical progression to AD (haard ratio [HR] = 2.15; confidence in terval [CI], 1.64-2.80; p < 0.001). A similar effect was not found for cortisol (HR = 1.206; CI, 0.82-1.37; p = 0.670) and there was no statistical evidence for an interaction between hippocampal volume and cortisol on clinical progression (HR = 0.81; CI, 0.57-0.17; p = 0.260). Discussion: Our findings suggest that higher cortisol predicts higher hippocampal atrophy, which in turn is a risk factor for progression to AD. Regulation of the hypothalamic-pituitary-adrenal axis through stress-reducing lifestyle interventions might be a protective factor against hippocampal degeneration at the prodromal stage of AD.

ArcheD, a residual neural network for prediction of cerebrospinal fluid amyloid-beta from amyloid PET images.

Detection and measurement of amyloid-beta (Aß) aggregation in the brain is a key factor for early identification and diagnosis of Alzheimer's disease (AD). We aimed to develop a deep learning model to predict Aß cerebrospinal fluid (CSF) concentration directly from amyloid PET images, independent of tracers, brain reference regions or preselected regions of interest. We used 1870 Aß PET images and CSF measurements to train and validate a convolutional neural network ("ArcheD"). We evaluated the ArcheD performance in relation to episodic memory and the standardized uptake value ratio (SUVR) of cortical Aß. We also compared the brain region's relevance for the model's CSF prediction within clinical-based and biological-based classifications. ArcheD-predicted Aß CSF values correlated strongly with measured Aß CSF values ( r =0.81; p <0.001) and showed correlations with SUVR and episodic memory measures in all participants except in those with AD. For both clinical and biological classifications, cerebral white matter significantly contributed to CSF prediction ( q <0.01), specifically in non-symptomatic and early stages of AD. However, in late-stage disease, brain stem, subcortical areas, cortical lobes, limbic lobe, and basal forebrain made more significant contributions (q<0.01). Considering cortical gray matter separately, the parietal lobe was the strongest predictor of CSF amyloid levels in those with prodromal or early AD, while the temporal lobe played a more crucial role for those with AD. In summary, ArcheD reliably predicted Aß CSF concentration from Aß PET scans, offering potential clinical utility for Aß level determination and early AD detection.

No impact of attenuation and scatter correction on the interpretation of dopamine transporter SPECT in patients with clinically uncertain parkinsonian syndrome.

PURPOSE: The benefit from attenuation and scatter correction (ASC) of dopamine transporter (DAT)-SPECT for the detection of nigrostriatal degeneration in clinical routine is still a matter of debate. The current study evaluated the impact of ASC on visual interpretation and semi-quantitative analysis of DAT-SPECT in a large patient sample. METHODS: One thousand seven hundred forty consecutive DAT-SPECT with 123I-FP-CIT from clinical routine were included retrospectively. SPECT images were reconstructed iteratively without and with ASC. Attenuation correction was based on uniform attenuation maps, scatter correction on simulation. All SPECT images were categorized with respect to the presence versus the absence of Parkinson-typical reduction of striatal 123I-FP-CIT uptake by three independent readers. Image reading was performed twice to assess intra-reader variability. The specific 123I-FP-CIT binding ratio (SBR) was used for automatic categorization, separately with and without ASC. RESULTS: The mean proportion of cases with discrepant categorization by the same reader between the two reading sessions was practically the same without and with ASC, about 2.2%. The proportion of DAT-SPECT with discrepant categorization without versus with ASC by the same reader was 1.66% ± 0.50% (1.09-1.95%), not exceeding the benchmark of 2.2% from intra-reader variability. This also applied to automatic categorization of the DAT-SPECT images based on the putamen SBR (1.78% discrepant cases between without versus with ASC). CONCLUSION: Given the large sample size, the current findings provide strong evidence against a relevant impact of ASC with uniform attenuation and simulation-based scatter correction on the clinical utility of DAT-SPECT to detect nigrostriatal degeneration in patients with clinically uncertain parkinsonian syndrome.

Individualized Summary Assessment of Detailed Neuropsychological Testing for the Etiological Diagnosis of Newly Detected Cognitive Impairment in Hospitalized Geriatric Patients.

BACKGROUND: Neuropsychological testing (NPT) of geriatric inpatients can be affected by the acute illness and/or the hospitalization. OBJECTIVE: To test individualized interpretation of detailed NPT for the differentiation between primary 'neurodegenerative' etiologies (predominantly Alzheimer's disease) and 'other' etiologies (including cerebrovascular disease) of newly detected cognitive impairment in geriatric inpatients without and with delirium in remission. METHODS: 96 geriatric inpatients (81.9±5.6 years, 64.6% females) with clinically uncertain cognitive impairment were included. 31.3% had delirium in remission that was not considered the primary cause of the cognitive impairment. Categorization of the most likely etiology as 'neurodegenerative' or 'other' was established retrospectively by a study neuropsychologist based on individualized summary assessment of detailed NPT compiled in a standardized vignette. The etiological diagnosis based on FDG-PET served as gold standard (54.2% 'neurodegenerative', 45.8% 'other'). RESULTS: Individualized summary assessment by the study neuropsychologist was correct in 80 patients (83.3%, 8 false positive, 8 false negative). The impact of delirium in remission was not significant (p = 0.237). Individualized summary assessment by an independent neuropsychologist resulted in more false positive cases (n = 22) at the same rate of false negative cases (n = 8). Automatic categorization with a decision tree model based on the most discriminative NPT scores was correct in 68 patients (70.8%, 14 false positive, 14 false negative). CONCLUSION: Individualized summary assessment of detailed NPT in the context of relevant clinical information might be useful for the etiological diagnosis of newly detected cognitive impairment in hospitalized geriatric patients, also in patients with delirium in remission, but requires task-specific expertise.

Stereotactical normalization with multiple templates representative of normal and Parkinson-typical reduction of striatal uptake improves the discriminative power of automatic semi-quantitative analysis in dopamine transporter SPECT.

BACKGROUND: The specific binding ratio (SBR) of 123I-FP-CIT in the putamen is widely used to support the interpretation of dopamine transporter (DAT) SPECT. Automatic methods for computation of the putamen SBR often include stereotactical normalization of the individual DAT-SPECT image to an anatomical standard space. This study compared using a single 123I-FP-CIT template image as target for stereotactical normalization versus multiple templates representative of normal and different levels of Parkinson-typical reduction of striatal 123I-FP-CIT uptake. METHODS: 1702 clinical 123I-FP-CIT SPECT images were stereotactically normalized (affine) to the anatomical space of the Montreal Neurological Institute (MNI) with SPM12 either using a single custom-made 123I-FP-CIT template representative of normal striatal uptake or using eight different templates representative of normal and different levels of Parkinson-typical reduction of striatal FP-CIT uptake with and without attenuation and scatter correction. In the latter case, SPM finds the linear combination of the multiple templates that best matches the patient's image. The putamen SBR was obtained using hottest voxels analysis in large unilateral regions-of-interest predefined in MNI space. The histogram of the putamen SBR in the whole sample was fitted by the sum of two Gaussians. The power to differentiate between reduced and normal SBR was estimated by the effect size of the distance between the two Gaussians computed as the differences between their mean values scaled to their pooled standard deviation. RESULTS: The effect size of the distance between the two Gaussians was 3.83 with the single template versus 3.96 with multiple templates for stereotactical normalization. CONCLUSIONS: Multiple templates representative of normal and different levels of Parkinson-typical reduction for stereotactical normalization of DAT-SPECT might provide improved separation between normal and reduced putamen SBR that could result in slightly improved power for the detection of nigrostriatal degeneration.

Same same but different: dopamine transporter SPECT on scanners with CZT vs. NaI detectors.

BACKGROUND: The aims of this study were to establish a normal database (NDB) for semiquantification of dopamine transporter (DAT) single-photon emission computed tomography (SPECT) with [123I]FP-CIT on a cadmium zinc telluride (CZT) camera, test the preexisting NaI-derived NDB for use in CZT scans, and compare the diagnostic findings in subjects imaged with a CZT scanner with either the preexisting NaI-based NDB or our newly defined CZT NDB. METHODS: The sample comprised 73 subjects with clinically uncertain parkinsonian syndrome (PS) who prospectively underwent [123I]FP-CIT SPECT on a CZT camera according to standard guidelines with identical acquisition and reconstruction protocols (DaTQUANT). Two experienced readers visually assessed the images and binarized the subjects into "non-neurodegenerative PS" and "neurodegenerative PS". Twenty-five subjects from the "non-neurodegenerative PS" subgroup were randomly selected to establish a CZT NDB. The remaining 48 subjects were defined as "test group". DaTQUANT was used to determine the specific binding ratio (SBR). For the test group, SBR values were transformed to z-scores for the putamen utilizing both the CZT NDB and the manufacturer-provided NaI-based NDB (GE NDB). A predefined fixed cut-off of -2 was used for dichotomization of z-scores to classify neurodegenerative and non-neurodegenerative PS. Performance of semiquantification using the two NDB to identify subjects with neurodegenerative PS was assessed in comparison with the visual rating. Furthermore, a randomized head-to-head comparison of both detector systems was performed semiquantitatively in a subset of 32 out of all 73 subjects. RESULTS: Compared to the visual rating as reference, semiquantification based on the dedicated CZT NDB led to fewer discordant ratings than the GE NDB in CZT scans (3 vs. 8 out of 48 subjects). This can be attributed to the putaminal z-scores being consistently higher with the GE NDB on a CZT camera (median absolute difference of 1.68), suggesting an optimal cut-off of -0.5 for the GE NDB instead of -2.0. Average binding ratios and z-scores were significantly lower in CZT compared to NaI data. CONCLUSIONS: Use of a dedicated, CZT-derived NDB is recommended in [123I]FP-CIT SPECT with a CZT camera since it improves agreement between semiquantification and visual assessment.

Differential diagnosis of amnestic dementia patients based on an FDG-PET signature of autopsy-confirmed LATE-NC.

INTRODUCTION: Limbic age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) is common in advanced age and can underlie a clinical presentation mimicking Alzheimer's disease (AD). We studied whether an autopsy-derived fluorodeoxyglucose positron emission tomography (FDG-PET) signature of LATE-NC provides clinical utility for differential diagnosis of amnestic dementia patients. METHODS: Ante mortem FDG-PET patterns from autopsy-confirmed LATE-NC (N = 7) and AD (N = 23) patients were used to stratify an independent cohort of clinically diagnosed AD dementia patients (N = 242) based on individual FDG-PET profiles. RESULTS: Autopsy-confirmed LATE-NC and AD groups showed markedly distinct temporo-limbic and temporo-parietal FDG-PET patterns, respectively. Clinically diagnosed AD dementia patients showing a LATE-NC-like FDG-PET pattern (N = 25, 10%) were significantly older, showed less abnormal AD biomarker levels, lower APOE ε4, and higher TMEM106B risk allele load. Clinically, they exhibited a more memory-predominant profile and a generally slower disease course. DISCUSSION: An autopsy-derived temporo-limbic FDG-PET signature identifies older amnestic patients whose clinical, genetic, and molecular biomarker features are consistent with underlying LATE-NC.

Vascular Health Is Associated With Functional Connectivity Decline in Higher-Order Networks of Older Adults.

Background: Poor vascular health may impede brain functioning in older adults, thus possibly increasing the risk of cognitive decline and Alzheimer's disease (AD). The emerging link between vascular risk factors (VRF) and longitudinal decline in resting-state functional connectivity (RSFC) within functional brain networks needs replication and further research in independent cohorts. Method: We examined 95 non-demented older adults using the IMAP+ cohort (Caen, France). VRF were assessed at baseline through systolic and diastolic blood pressure, body-mass-index, and glycated hemoglobin (HbA1c) levels. Brain pathological burden was measured using white matter hyperintensity (WMH) volumes, derived from FLAIR images, and cortical ß-Amyloid (Aß) deposition, derived from florbetapir-PET imaging. RSFC was estimated from functional MRI scans within canonical brain networks at baseline and up to 3 years of follow-up. Linear mixed-effects models evaluated the independent predictive value of VRF on longitudinal changes in network-specific and global RSFC as well as a potential association between these RSFC changes and cognitive decline. Results: We replicate that RSFC increased over time in global RSFC and in the default-mode, salience/ventral-attention and fronto-parietal networks. In contrast, higher diastolic blood pressure levels were independently associated with a decrease of RSFC over time in the default-mode, salience/ventral-attention, and fronto-parietal networks. Moreover, higher HbA1c levels were independently associated with a reduction of the observed RSFC increase over time in the salience/ventral-attention network. Both of these associations were independent of brain pathology related to Aß load and WMH volumes. The VRF-related changes in RSFC over time were not significantly associated with longitudinal changes in cognitive performance. Conclusion: Our longitudinal findings corroborate that VRF promote RSFC alterations over time within higher-order brain networks, irrespective of pathological brain burden. Altered RSFC in large-scale cognitive networks may eventually increase the vulnerability to aging and AD.

Radiation doses from low-dose CT scans in SPECT/CT and PET/CT examinations: A survey in Germany.

AIM: Recently, dose reference levels (DRLs) have been defined in Germany for auxiliary low-dose CT scans in hybrid SPECT/CT and PET/CT examinations, based on data from 2016/17. Here, another survey from 2020 was evaluated and compared with the new DRLs as well as with similar surveys from foreign countries. METHODS: The survey, which had already been conducted in the Nordic countries, queried for various examinations including the following values: patient weight and height, volume CT dose index (CTDIvol), dose length product (DLP). For each examination, statistical parameters such as the third quartile (Q3) were determined from all submitted CTDIvol and DLP values. Additionally, for examinations comprising datasets from at least 10 systems, the third quartile (Q3-Med) of the respective median values of each system was calculated. Q3 and Q3-Med were compared with the newly published DRLs from Germany and values from similar studies from other countries. RESULTS: Data from 15 SPECT/CT and 13 PET/CT systems from 15 nuclear medicine departments were collected. For the following examinations datasets from more than 10 systems were submitted: SPECT lung VQ, SPECT bone, SPECT&PET cardiac, PET brain, PET oncology. Especially for examinations of the thorax and heart, the new DRLs are very strict compared to this study. The CTDIvol values for examinations of the head were lower in this study than the DRLs prescribe now. CONCLUSIONS: For certain examination types, there is a need for dose optimization at some clinics and devices in order to take into account the new DRLs in Germany in the future.

Brain FDG PET for Short- to Medium-Term Prediction of Further Cognitive Decline and Need for Assisted Living in Acutely Hospitalized Geriatric Patients With Newly Detected Clinically Uncertain Cognitive Impairment.

PURPOSE: The aim of this study was to evaluate brain FDG PET for short- to medium-term prediction of cognitive decline, need for assisted living, and survival in acutely hospitalized geriatric patients with newly detected clinically uncertain cognitive impairment (CUCI). MATERIALS AND METHODS: The study included 96 patients (62 females, 81.4 ± 5.4 years) hospitalized due to (sub)acute admission indications with newly detected CUCI (German Clinical Trials Register DRKS00005041). FDG PET was categorized as "neurodegenerative" (DEG+) or "nonneurodegenerative" (DEG-) based on visual inspection by 2 independent readers. In addition, each individual PET was tested voxel-wise against healthy controls (P < 0.001 uncorrected). The resulting total hypometabolic volume (THV) served as reader-independent measure of the spatial extent of neuronal dysfunction/degeneration. FDG PET findings at baseline were tested for association with the change in living situation and change in vital status 12 to 24 months after PET. The association with the annual change of the CDR-SB (Clinical Dementia Rating Sum of Boxes) after PET was tested in a subsample of 72 patients. RESULTS: The mean time between PET and follow-up did not differ between DEG+ and DEG- patients (1.37 ± 0.27 vs 1.41 ± 0.27 years, P = 0.539). Annual change of CDR-SB was higher in DEG+ compared with DEG- patients (2.78 ± 2.44 vs 0.99 ± 1.81, P = 0.001), and it was positively correlated with THV (age-corrected Spearman ρ = 0.392, P = 0.001). DEG+ patients moved from at home to assisted living significantly earlier than DEG- patients (P = 0.050). Survival was not associated with DEG status or with THV. CONCLUSIONS: In acutely hospitalized geriatric patients with newly detected CUCI, the brain FDG PET can contribute to the prediction of further cognitive/functional decline and the need for assisted living within 1 to 2 years.

Performance evaluation of automated white matter hyperintensity segmentation algorithms in a multicenter cohort on cognitive impairment and dementia.

Background: White matter hyperintensities (WMH), a biomarker of small vessel disease, are often found in Alzheimer's disease (AD) and their advanced detection and quantification can be beneficial for research and clinical applications. To investigate WMH in large-scale multicenter studies on cognitive impairment and AD, appropriate automated WMH segmentation algorithms are required. This study aimed to compare the performance of segmentation tools and provide information on their application in multicenter research. Methods: We used a pseudo-randomly selected dataset (n = 50) from the DZNE-multicenter observational Longitudinal Cognitive Impairment and Dementia Study (DELCODE) that included 3D fluid-attenuated inversion recovery (FLAIR) images from participants across the cognitive continuum. Performances of top-rated algorithms for automated WMH segmentation [Brain Intensity Abnormality Classification Algorithm (BIANCA), lesion segmentation toolbox (LST), lesion growth algorithm (LGA), LST lesion prediction algorithm (LPA), pgs, and sysu_media] were compared to manual reference segmentation (RS). Results: Across tools, segmentation performance was moderate for global WMH volume and number of detected lesions. After retraining on a DELCODE subset, the deep learning algorithm sysu_media showed the highest performances with an average Dice's coefficient of 0.702 (±0.109 SD) for volume and a mean F1-score of 0.642 (±0.109 SD) for the number of lesions. The intra-class correlation was excellent for all algorithms (>0.9) but BIANCA (0.835). Performance improved with high WMH burden and varied across brain regions. Conclusion: To conclude, the deep learning algorithm, when retrained, performed well in the multicenter context. Nevertheless, the performance was close to traditional methods. We provide methodological recommendations for future studies using automated WMH segmentation to quantify and assess WMH along the continuum of cognitive impairment and AD dementia.

Severity of Subjective Cognitive Complaints and Worries in Older Adults Are Associated With Cerebral Amyloid-ß Load.

Subjective cognitive decline (SCD) is considered an early risk stage for dementia due to Alzheimer's disease (AD) and the development of pathological brain changes, such as the aggregation of amyloid-beta (amyloid-ß) plaques. This study evaluates the association between specific features of SCD and cerebral amyloid-ß load measured by positron emission tomography (PET) with 18F-florbetaben in 40 cognitively normal older individuals. Global amyloid-ß, as well as regional amyloid-ß load for the frontal, temporal, parietal, and cingulate cortex, was quantified. Specific features of SCD, such as subjective cognitive complaints and worry, were assessed using the 39-item Everyday Cognition Scales and the 16-item Penn State Worry Questionnaire. Spearman's rank partial correlation analyses, adjusted for age and apolipoprotein E ε4 status, were conducted to test the associations between specific features of SCD and cerebral amyloid-ß load. The severity of subjective cognitive complaints in everyday memory and organization was positively correlated with amyloid-ß load in the frontal cortex. In addition, the severity of subjective cognitive complaints in everyday planning was positively correlated with amyloid-ß load in the parietal cortex. Higher levels of worry were associated with higher amyloid-ß load in the frontal cortex. After correction of the PET data for partial volume effects, these associations were reduced to trend level. In conclusion, the severity of subjective cognitive complaints and the level of trait worry were positively associated with cortical amyloid-ß burden, particularly in the frontal and parietal cortex. Further studies are required to elucidate the direction of these associations in order to develop strategies to prevent amyloid deposition and cognitive decline.

Data-driven FDG-PET subtypes of Alzheimer's disease-related neurodegeneration.

BACKGROUND: Previous research has described distinct subtypes of Alzheimer's disease (AD) based on the differences in regional patterns of brain atrophy on MRI. We conducted a data-driven exploration of distinct AD neurodegeneration subtypes using FDG-PET as a sensitive molecular imaging marker of neurodegenerative processes. METHODS: Hierarchical clustering of voxel-wise FDG-PET data from 177 amyloid-positive patients with AD dementia enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI) was used to identify distinct hypometabolic subtypes of AD, which were then further characterized with respect to clinical and biomarker characteristics. We then classified FDG-PET scans of 217 amyloid-positive patients with mild cognitive impairment ("prodromal AD") according to the identified subtypes and studied their domain-specific cognitive trajectories and progression to dementia over a follow-up interval of up to 72 months. RESULTS: Three main hypometabolic subtypes were identified: (i) "typical" (48.6%), showing a classic posterior temporo-parietal hypometabolic pattern; (ii) "limbic-predominant" (44.6%), characterized by old age and a memory-predominant cognitive profile; and (iii) a relatively rare "cortical-predominant" subtype (6.8%) characterized by younger age and more severe executive dysfunction. Subtypes classified in the prodromal AD sample demonstrated similar subtype characteristics as in the AD dementia sample and further showed differential courses of cognitive decline. CONCLUSIONS: These findings complement recent research efforts on MRI-based identification of distinct AD atrophy subtypes and may provide a potentially more sensitive molecular imaging tool for early detection and characterization of AD-related neurodegeneration variants at prodromal disease stages.

Topographic patterns of white matter hyperintensities are associated with multimodal neuroimaging biomarkers of Alzheimer's disease.

BACKGROUND: White matter hyperintensities (WMH) are frequently found in Alzheimer's disease (AD). Commonly considered as a marker of cerebrovascular disease, regional WMH may be related to pathological hallmarks of AD, including beta-amyloid (Aß) plaques and neurodegeneration. The aim of this study was to examine the regional distribution of WMH associated with Aß burden, glucose hypometabolism, and gray matter volume reduction. METHODS: In a total of 155 participants (IMAP+ cohort) across the cognitive continuum from normal cognition to AD dementia, FLAIR MRI, AV45-PET, FDG-PET, and T1 MRI were acquired. WMH were automatically segmented from FLAIR images. Mean levels of neocortical Aß deposition (AV45-PET), temporo-parietal glucose metabolism (FDG-PET), and medial-temporal gray matter volume (GMV) were extracted from processed images using established AD meta-signature templates. Associations between AD brain biomarkers and WMH, as assessed in region-of-interest and voxel-wise, were examined, adjusting for age, sex, education, and systolic blood pressure. RESULTS: There were no significant associations between global Aß burden and region-specific WMH. Voxel-wise WMH in the splenium of the corpus callosum correlated with greater Aß deposition at a more liberal threshold. Region- and voxel-based WMH in the posterior corpus callosum, along with parietal, occipital, and frontal areas, were associated with lower temporo-parietal glucose metabolism. Similarly, lower medial-temporal GMV correlated with WMH in the posterior corpus callosum in addition to parietal, occipital, and fontal areas. CONCLUSIONS: This study demonstrates that local white matter damage is correlated with multimodal brain biomarkers of AD. Our results highlight modality-specific topographic patterns of WMH, which converged in the posterior white matter. Overall, these cross-sectional findings corroborate associations of regional WMH with AD-typical Aß deposition and neurodegeneration.

Abnormal Regional and Global Connectivity Measures in Subjective Cognitive Decline Depending on Cerebral Amyloid Status.

BACKGROUND: Amyloid-ß accumulation was found to alter precuneus-based functional connectivity (FC) in mild cognitive impairment (MCI) and Alzheimer's disease (AD) dementia, but its impact is less clear in subjective cognitive decline (SCD), which in combination with AD pathologic change is theorized to correspond to stage 2 of the Alzheimer's continuum in the 2018 NIA-AA research framework. OBJECTIVE: This study addresses how amyloid pathology relates to resting-state fMRI FC in SCD, especially focusing on the precuneus. METHODS: From the DELCODE cohort, two groups of 24 age- and gender-matched amyloid-positive (SCDAß+) and amyloidnegative SCD (SCDß-) patients were selected according to visual [18F]-Florbetaben (FBB) PET readings, and studied with resting-state fMRI. Local (regional homogeneity [ReHo], fractional amplitude of low-frequency fluctuations [fALFF]) and global (degree centrality [DC], precuneus seed-based FC) measures were compared between groups. Follow-up correlation analyses probed relationships of group differences with global and precuneal amyloid load, as measured by FBB standard uptake value ratios (SUVR=⫖FBB). RESULTS: ReHo was significantly higher (voxel-wise p < 0.01, cluster-level p < 0.05) in the bilateral precuneus for SCDAß+patients, whereas fALFF was not altered between groups. Relatively higher precuneus-based FC with occipital areas (but no altered DC) was observed in SCDAß+ patients. In this latter cluster, precuneus-occipital FC correlated positively with global (SCDAß+) and precuneus SUVRFBB (both groups). CONCLUSION: While partial confounding influences due to a higher APOE ε4 carrier ratio among SCDAß+ patients cannot be excluded, exploratory results indicate functional alterations in the precuneus hub region that were related to amyloid-ß load, highlighting incipient pathology in stage 2 of the AD continuum.

A convolutional neural network for fully automated blood SUV determination to facilitate SUR computation in oncological FDG-PET.

PURPOSE: The standardized uptake value (SUV) is widely used for quantitative evaluation in oncological FDG-PET but has well-known shortcomings as a measure of the tumor's glucose consumption. The standard uptake ratio (SUR) of tumor SUV and arterial blood SUV (BSUV) possesses an increased prognostic value but requires image-based BSUV determination, typically in the aortic lumen. However, accurate manual ROI delineation requires care and imposes an additional workload, which makes the SUR approach less attractive for clinical routine. The goal of the present work was the development of a fully automated method for BSUV determination in whole-body PET/CT. METHODS: Automatic delineation of the aortic lumen was performed with a convolutional neural network (CNN), using the U-Net architecture. A total of 946 FDG PET/CT scans from several sites were used for network training (N = 366) and testing (N = 580). For all scans, the aortic lumen was manually delineated, avoiding areas affected by motion-induced attenuation artifacts or potential spillover from adjacent FDG-avid regions. Performance of the network was assessed using the fractional deviations of automatically and manually derived BSUVs in the test data. RESULTS: The trained U-Net yields BSUVs in close agreement with those obtained from manual delineation. Comparison of manually and automatically derived BSUVs shows excellent concordance: the mean relative BSUV difference was (mean ± SD) = (- 0.5 ± 2.2)% with a 95% confidence interval of [- 5.1,3.8]% and a total range of [- 10.0, 12.0]%. For four test cases, the derived ROIs were unusable (< 1 ml). CONCLUSION: CNNs are capable of performing robust automatic image-based BSUV determination. Integrating automatic BSUV derivation into PET data processing workflows will significantly facilitate SUR computation without increasing the workload in the clinical setting.

Impact of age and sex correction on the diagnostic performance of dopamine transporter SPECT.

PURPOSE: The specific binding ratio (SBR) of 123I-FP-CIT (FP-CIT) in the putamen decreases with age by about 5% per decade and most likely is about 10% higher in females. However, the clinical utility of age and sex correction of the SBR is still a matter of debate. This study tested the impact of age and sex correction on the diagnostic performance of the putamen SBR in three independent patient samples. METHODS: Research sample: 207 healthy controls (HC) and 438 Parkinson's disease (PD) patients. Clinical sample A: 183 patients with neurodegenerative parkinsonian syndrome (PS) and 183 patients with non-neurodegenerative PS from one site. Clinical sample B: 84 patients with neurodegenerative PS and 38 patients with non-neurodegenerative PS from another site. Correction for age and sex of the putamen SBR was based on linear regression in the HC or non-neurodegenerative PS, separately in each sample. The area under the ROC curve (AUC) was used as performance measure. RESULTS: The putamen SBR was higher in females compared to males (PPMI: 14%, p < 0.0005; clinical sample A: 7%, p < 0.0005; clinical sample B: 6%, p = 0.361). Age-related decline of the putamen SBR ranged between 3.3 and 10.4% (p ≤ 0.019). In subjects ≥ 50 years, age and sex explained < 10% of SBR between-subjects variance. Correction of the putamen SBR for age and sex resulted in slightly decreased AUC in the PPMI sample (0.9955 versus 0.9969, p = 0.025) and in clinical sample A (0.9448 versus 0.9519, p = 0.057). There was a small, non-significant AUC increase in clinical sample B (0.9828 versus 0.9743, p = 0.232). CONCLUSION: These findings do not support age and sex correction of the putaminal FP-CIT SBR in the diagnostic workup of parkinsonian syndromes. This most likely is explained by the fact that the proportion of between-subjects variance caused by age and sex is considerably below the symptom threshold of about 50% reduction in neurodegenerative PS.