Mouse serum albumin induces neuronal apoptosis and tauopathies.

The elderly frequently present impaired blood-brain barrier which is closely associated with various neurodegenerative diseases. However, how the albumin, the most abundant protein in the plasma, leaking through the disrupted BBB, contributes to the neuropathology remains poorly understood. We here demonstrated that mouse serum albumin-activated microglia induced astrocytes to A1 phenotype to remarkably increase levels of Elovl1, an astrocytic synthase for very long-chain saturated fatty acids, significantly promoting VLSFAs secretion and causing neuronal lippoapoptosis through endoplasmic reticulum stress response pathway. Moreover, MSA-activated microglia triggered remarkable tau phosphorylation at multiple sites through NLRP3 inflammasome pathway. Intracerebroventricular injection of MSA into the brains of C57BL/6J mice to a similar concentration as in patient brains induced neuronal apoptosis, neuroinflammation, increased tau phosphorylation, and decreased the spatial learning and memory abilities, while Elovl1 knockdown significantly prevented the deleterious effect of MSA. Overall, our study here revealed that MSA induced tau phosphorylation and neuron apoptosis based on MSA-activated microglia and astrocytes, respectively, showing the critical roles of MSA in initiating the occurrence of tauopathies and cognitive decline, and providing potential therapeutic targets for MSA-induced neuropathology in multiple neurodegenerative disorders.

Fully Automated Segmentation of Human Eyeball Using Three-Dimensional U-Net in T2 Magnetic Resonance Imaging.

Purpose: To develop and validate a fully automated deep-learning-based tool for segmentation of the human eyeball using a three-dimensional (3D) U-Net, compare its performance to semiautomatic segmentation ground truth and a two-dimensional (2D) U-Net, and analyze age and sex differences in eyeball volume, as well as gaze-dependent volume consistency in normal subjects. Methods: We retrospectively collected 474 magnetic resonance imaging (MRI) scans, including different gazing scans, from 119 patients. A 10-fold cross-validation was applied to separate the dataset into training, test, and validation sets for both the 3D U-Net and 2D U-Net. Performance accuracy was measured using four quantitative metrics compared to the ground truth, and Bland-Altman plot analysis was conducted. Age and sex differences in eyeball volume and variability in eyeball volume differences across gazing directions were analyzed. Results: The 3D U-Net outperformed the 2D U-Net with mean accuracy scores >0.95, showing acceptable agreement in the Bland-Altman plot analysis despite a tendency for slight overestimation (mean difference = -0.172 cm³). Significant sex differences and age effects on eyeball volume were observed for both methods (P < 0.05). No significant volume differences were found between the segmentation methods or within each method for the different gazing directions. Significant differences in performance accuracy were identified among the five gazing directions, with the upward direction showing a notably lower performance. Conclusions: Our study demonstrated the effectiveness of 3D U-Net human eyeball volume segmentation using T2-weighted MRI. The robustness and reliability of 3D U-Net across diverse populations and gaze directions support enhanced ophthalmic diagnosis and treatment strategies. Translational Relevance: Our findings demonstrate the feasibility of using the proposed 3D U-Net model for the automatic segmentation of the human eyeball, with potential applications in various ophthalmic research fields that require the analysis of 3D geometric eye globe shapes or eye movement detection.

Prediction of Amyloid ß-Positivity with both MRI Parameters and Cognitive Function Using Machine Learning.

Purpose: To investigate the MRI markers for the prediction of amyloid ß (Aß)-positivity in mild cognitive impairment (MCI) and Alzheimer's disease (AD), and to evaluate the differences in MRI markers between Aß-positive (Aß [+]) and -negative groups using the machine learning (ML) method. Materials and Methods: This study included 139 patients with MCI and AD who underwent amyloid PET-CT and brain MRI. Patients were divided into Aß (+) (n = 84) and Aß-negative (n = 55) groups. Visual analysis was performed with the Fazekas scale of white matter hyperintensity (WMH) and cerebral microbleeds (CMB) scores. The WMH volume and regional brain volume were quantitatively measured. The multivariable logistic regression and ML using support vector machine, and logistic regression were used to identify the best MRI predictors of Aß-positivity. Results: The Fazekas scale of WMH (p = 0.02) and CMB scores (p = 0.04) were higher in Aß (+). The volumes of hippocampus, entorhinal cortex, and precuneus were smaller in Aß (+) (p < 0.05). The third ventricle volume was larger in Aß (+) (p = 0.002). The logistic regression of ML showed a good accuracy (81.1%) with mini-mental state examination (MMSE) and regional brain volumes. Conclusion: The application of ML using the MMSE, third ventricle, and hippocampal volume is helpful in predicting Aß-positivity with a good accuracy.

Classification of Preschoolers with Low-Functioning Autism Spectrum Disorder Using Multimodal MRI Data.

Multimodal imaging studies targeting preschoolers and low-functioning autism spectrum disorder (ASD) patients are scarce. We applied machine learning classifiers to parameters from T1-weighted MRI and DTI data of 58 children with ASD (age 3-6 years) and 48 typically developing controls (TDC). Classification performance reached an accuracy, sensitivity, and specificity of 88.8%, 93.0%, and 83.8%, respectively. The most prominent features were the cortical thickness of the right inferior occipital gyrus, mean diffusivity of the middle cerebellar peduncle, and nodal efficiency of the left posterior cingulate gyrus. Machine learning-based analysis of MRI data was useful in distinguishing low-functioning ASD preschoolers from TDCs. Combination of T1 and DTI improved classification accuracy about 10%, and large-scale multi-modal MRI studies are warranted for external validation.

Quantitative evaluation of intraorbital optic nerve in optic atrophy using diffusion tensor imaging.

The aim of this study is to quantitatively investigate the microstructural properties of the optic nerve (ON) in vivo using diffusion tensor imaging (DTI) in patients with unilateral optic atrophy (OA) and to determine their association with retinal nerve fiber layer (RNFL) thickness of the optic nerve head (ONH). Six patients with unilateral OA and 11 control subjects underwent DTI. ONs from ONH to the orbital apex were tracked. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were computed in both ONs and their correlation with RNFL thickness measured using optical coherence tomography was also analyzed. FA of atrophic ON was lower than that of non-affected and control ONs (atrophic [A], 0.136 ± 0.059; non-affected [N], 0.384 ± 0.048; control [C], 0.389 ± 0.053). MD and RD of atrophic ONs were higher than those of non-affected and control ONs (MD, A, 0.988 ± 0.247; N, 0.658 ± 0.058; C, 0.687 ± 0.079; RD, A, 0.920 ± 0.247; N, 0.510 ± 0.054; C, 0.532 ± 0.078). All DTI measures of atrophic ON except for AD showed a significant correlation with RNFL thickness of ONH; FA showed the strongest correlation, followed by RD and MD (FA, R2 = 0.936, P < 0.001; RD, R2 = 0.795, P < 0.001; MD, R2 = 0.655, P = 0.001). This study reports quantitative analysis of the ON using DTI and differences in DTI measures between atrophic and normal ONs. The significant correlation between DTI measures and RNFL thickness suggests the applicability of DTI as a clinical tool to evaluate the ON.

In vivo Analysis of Normal Optic Nerve in an Elderly Population Using Diffusion Magnetic Resonance Imaging Tractography.

Purpose: To quantitatively investigate the microstructural properties of the optic nerve (ON) in vivo using diffusion magnetic resonance imaging (dMRI) tractography in an elderly population and to determine the differences between the ON diffusion properties stratified by basic demographics. Methods: We measured fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) of the intraorbital ON in cognitively normal controls selected from the Alzheimer's Disease Neuroimaging Initiative 3 database (n =104; mean age = 73. 8 ± 8.1 years) using dMRI probabilistic tractography and evaluated the correlation between diffusion parameters and demographic factors. Diffusion parameters were measured in 20 equidistant nodes along the tract, and the data from proximal 70% (14 nodes) of the intraorbital ON were averaged. Results: The mean FA of the intraorbital ON was 0.392 ± 0.063, and the mean MD was 1.163 ± 0.165 µm2/s. The mean RD was 0.882 ± 0.152 µm2/s, and the mean AD was 1.693 ± 0.183 µm2/s. The multiple linear regression model showed a negative correlation between FA and age. FA in females was significantly higher than males, whereas RD in female was significantly lower. Conclusions: We measured the diffusion properties of the intraorbital ON using dMRI tractography in an elderly cognitively normal population. The diffusion properties detected by dMRI tractography may substantially reflect the microstructure of the ON.

Quantitative Analysis of Eyeball Rotation During Lateral Gaze in Intermittent Exotropia: A Magnetic Resonance Imaging Study.

Purpose: To evaluate the eyeball rotation during lateral gaze in patients with intermittent exotropia (IXT) using three-dimensional magnetic resonance imaging (MRI). Methods: In this prospective observational study, patients with IXT (n = 29) underwent orbital MRI during central, right, and left gazes. Fixation targets were placed at a 40° angle for lateral gaze. After acquisition of MR images, the position of the static tissues other than the eyeball in the MR images were matched three-dimensionally. The optical axis was defined as the perpendicular line to its lens passing through the corneal vertex. The rotation angle was measured as the angle between optical axes in central gaze and lateral gaze using ImageJ. A difference of 3° or more in the rotational angle between both eyes was considered a significant difference. Results: Eight patients (26.7%) had a larger adduction angle than the abduction angle of the fellow eye and six patients (20.0%) showed a smaller adduction angle during lateral gaze on at least one side. There was no significant factor associated with the pattern of rotation. Conclusions: Almost one-half of the patients with IXT had significant difference in the rotation angle between both eyes during lateral gaze. Measurement of the rotation angle during lateral gaze using MRI showed that IXT is not a perfectly comitant disturbance of gaze in some subjects. Translational Relevance: Quantitative analysis for eye movements using MRI can provide useful information for physiologic mechanism and proper surgical planning in patients with IXT.

Structural connectivity networks in Alzheimer's disease and Lewy body disease.

OBJECTIVE: We evaluated disruption of the white matter (WM) network related with Alzheimer's disease (AD) and Lewy body disease (LBD), which includes Parkinson's disease and dementia with Lewy bodies. METHODS: We consecutively recruited 37 controls and 77 patients with AD-related cognitive impairment (ADCI) and/or LBD-related cognitive impairment (LBCI). Diagnoses of ADCI and LBCI were supported by amyloid PET and dopamine transporter PET, respectively. There were 22 patients with ADCI, 19 patients with LBCI, and 36 patients with mixed ADCI/LBCI. We investigated the relationship between ADCI, LBCI, graph theory-based network measures on diffusion tensor images, and cognitive dysfunction using general linear models after controlling for age, sex, education, deep WM hyperintensities (WMH), periventricular WMH, and intracranial volume. RESULTS: LBCI, especially mixed with ADCI, was associated with increased normalized path length and decreased normalized global efficiency. LBCI was related to the decreased nodal degree of left caudate, which was further associated with broad cognitive dysfunction. Decreased left caudate nodal degree was associated with decreased fractional anisotropy (FA) in the brain regions vulnerable to LBD. Compared with the control group, the LBCI group had an increased betweenness centrality in the occipital nodes, which was associated with decreased FA in the WM adjacent to the striatum and visuospatial dysfunction. CONCLUSION: Concomitant ADCI and LBCI are associated with the accentuation of LBCI-related WM network disruption centered in the left caudate nucleus. The increase of occipital betweenness centrality could be a characteristic biologic change associated with visuospatial dysfunction in LBCI.

Construction and photocatalytic performance of fluorinated ZnO-TiO2 heterostructure composites.

Titanium dioxide, as a promising photocatalytic material, has attracted extensive attention in the field of photocatalytic degradation of organic pollutants in sewage. However, the photocatalytic performance needs to be further improved. In this work, fluorinated ZnO-TiO2 composites (F-ZTO) were prepared by a simple coprecipitation method. The photocatalytic performance of the samples was studied in detail with methyl orange as the target degradation product. The results indicated that under the same conditions, the degradation rates of 6% F-ZTO, F-TiO2 and TiO2 for methyl orange reached 93.75%, 76.56% and 62.89% respectively. This showed that the method used in this work could effectively improve the photocatalytic degradation performance of titanium dioxide. 6% F-ZTO showed an excellent photocatalytic activity, which was attributed to the small grain size, the large specific surface area and the effective inhibition of photoelectron-hole recombination due to fluorination and zinc oxide coupling. In three consecutive cycles, the photocatalytic activity was almost maintained, indicating that 6% F-ZTO had a good recycling performance.

Contrast-enhanced T1-weighted image radiomics of brain metastases may predict EGFR mutation status in primary lung cancer.

Identification of EGFR mutations is critical to the treatment of primary lung cancer and brain metastases (BMs). Here, we explored whether radiomic features of contrast-enhanced T1-weighted images (T1WIs) of BMs predict EGFR mutation status in primary lung cancer cases. In total, 1209 features were extracted from the contrast-enhanced T1WIs of 61 patients with 210 measurable BMs. Feature selection and classification were optimized using several machine learning algorithms. Ten-fold cross-validation was applied to the T1WI BM dataset (189 BMs for training and 21 BMs for the test set). Area under receiver operating characteristic curves (AUC), accuracy, sensitivity, and specificity were calculated. Subgroup analyses were also performed according to metastasis size. For all measurable BMs, random forest (RF) classification with RF selection demonstrated the highest diagnostic performance for identifying EGFR mutation (AUC: 86.81). Support vector machine and AdaBoost were comparable to RF classification. Subgroup analyses revealed that small BMs had the highest AUC (89.09). The diagnostic performance for large BMs was lower than that for small BMs (the highest AUC: 78.22). Contrast-enhanced T1-weighted image radiomics of brain metastases predicted the EGFR mutation status of lung cancer BMs with good diagnostic performance. However, further study is necessary to apply this algorithm more widely and to larger BMs.

Identification of Novel Genes Associated with Cortical Thickness in Alzheimer's Disease: Systems Biology Approach to Neuroimaging Endophenotype.

Alzheimer's disease (AD) is a common neurodegenerative disorder characterized by a heterogeneous distribution of pathological changes in the brain. Cortical thickness is one of the most sensitive imaging biomarkers for AD representing structural atrophy. The purpose of this study is to identify novel genes associated with cortical thickness. We measured the whole-brain mean cortical thickness from magnetic resonance imaging (MRI) scans in 919 subjects from the Alzheimer's Disease Neuroimaging Initiative cohort, including 163 AD patients, 488 mild cognitive impairment patients, and 268 cognitively normal participants. Based on the single-nucleotide polymorphism (SNP)-based genome-wide association study, we performed gene-based association analysis for mean cortical thickness. Furthermore, we performed expression quantitative trait loci, protein-protein interaction network, and pathway analysis to identify biologically functional information. We identified four genes (B4GALNT1, RAB44, LOC101927583, and SLC26A10), two pathways (cyclin-dependent protein kinase holoenzyme complex and nuclear cyclin-dependent protein kinase holoenzyme complex), and one protein-protein interaction (B4GALNT1 and GALNT8 pair). These genes are involved in protein degradation, GTPase activity, neuronal loss, and apoptosis. The identified pathways are involved in the cellular processes and neuronal differentiation, which contribute to neuronal loss that is responsible for AD. Furthermore, the most significant SNP (rs12320537) in B4GALNT1 is associated with expression levels of B4GALNT1 in several brain regions. Thus, the identified genes and pathways provide deeper mechanistic insight into the molecular basis of brain atrophy in AD.

Brain structural changes after multi-strategic metamemory training in older adults with subjective memory complaints: A randomized controlled trial.

BACKGROUND: Metamemory is the process of monitoring and controlling one's memory. Improving metamemory may reduce the memory problem in old age. We hypothesized that metamemory training (MMT) would improve cognition in older adults with subjective memory complaints and change the brain region related to metacognition. METHOD: We recruited and randomized older adults to the multi-strategic memory training of 10 weekly 90-min sessions, based on the metamemory concept or usual care. Cognitive tests including the Elderly Verbal Learning Test, Simple Rey Figure Test, Digit Span, Spatial Span, Categorical Fluency, and the Boston Naming Test were done in 201 participants, together with magnetic resonance imaging (MRI) in 49 participants before and after training. RESULTS: A total of 112 in the training group and 89 in the control group participated. The training group had a significant increase in long-term delayed free recall, categorical fluency, and the Boston Naming test. In MRI, the mean diffusivity of the bundles of axon tracts passing from the frontal lobe to the posterior end of the lateral sulcus decreased in the training group. CONCLUSION: These results indicate that the MMT program has a positive impact on enhancing older people' cognitive performance. Improved white matter integrity in the anterior and posterior cerebrum and increased cortical thickness of prefrontal regions, which related to metacognition, possibly suggest that the effects of the MMT would be induced via the enhancement of cognitive control.

Trajectories of Physiological Brain Aging and Related Factors in People Aged from 20 to over-80.

BACKGROUND/OBJECTIVE: In this study, we investigated a long-term trajectory of brain aging (from the 20 s to over-80) in cognitively normal (CN) individuals. We further determined whether differences in sex, education years, and apolipoprotein E ε 4 status affect age-related cortical thinning. METHODS: A total of 2,944 CN individuals who underwent high-resolution (3.0-Tesla) magnetic resonance imaging were included in this study. Cortical thickness was measured using a surface-based method. Multiple linear regression analyses were performed to evaluate age-related cortical thinning and related factors. RESULTS: Compared to those in their 20 s/30 s, participants in their 40 s showed thinning primarily in the medial and lateral frontal and inferior parietal regions, and cortical thinning occurred across most of the cortices with increasing age. Notably, the precuneus, inferior temporal and lateral occipital regions were relatively spared until later in life. Male and lower education years were associated with greater cortical thinning with distinct regional specificity. CONCLUSION: Our findings provide an important clue to understanding the mechanism of age-related cognitive decline and new strategies for preventing the acceleration of pathological brain aging.

Longitudinal outcomes of amyloid positive versus negative amnestic mild cognitive impairments: a three-year longitudinal study.

We aimed to compare the longitudinal outcome of amnestic mild cognitive impairment (aMCI) patients with significant Pittsburgh Compound B uptake [PiB(+) aMCI] and those without [PiB(-) aMCI]. Cerebral ß-amyloid was measured in 47 patients with aMCI using PiB-positron emission tomography (PET) (31 PiB(+) aMCI and 16 PiB(-) aMCI). Clinical (N = 47) and neuropsychological follow-up (N = 37), and follow-up with brain magnetic resonance imaging (N = 38) and PiB-PET (N = 30) were performed for three years. PiB(+) aMCI had a higher risk of progression to dementia (hazard ratio = 3.74, 95% CI = 1.21-11.58) and faster rate of cortical thinning in the bilateral precuneus and right medial and lateral temporal cortices compared to PiB(-) aMCI. Among six PiB(-) aMCI patients who had regional PiB uptake ratio >1.5 in the posterior cingulate cortex (PCC), three (50.0%) progressed to dementia, and two of them had global PiB uptake ratio >1.5 at the follow-up PiB-PET. Our findings suggest that amyloid imaging is important for predicting the prognosis of aMCI patients, and that it is necessary to pay more attention to PiB(-) aMCI with increased regional PiB uptake in the PCC.

Neural predictors of cognitive improvement by multi-strategic memory training based on metamemory in older adults with subjective memory complaints.

Previous studies have indicated that memory training may help older people improve cognition. However, evidence regarding who will benefit from such memory trainings has not been fully discovered yet. Understanding the clinical and neural inter-individual differences for predicting cognitive improvement is important for maximizing the training efficacy of memory-training programs. The purpose of this study was to find the individual characteristics and brain morphological characteristics that predict cognitive improvement after a multi-strategic memory training based on metamemory concept. Among a total of 49 older adults, 39 participated in the memory-training program and 10 did not. All of them underwent brain MRIs at the entry of the training and received the neuropsychological tests twice, before and after the training. Stepwise regression analysis showed that lower years of education predicted cognitive improvement in the training group. In MRI, thinner cortices of precuneus, cuneus and posterior cingulate gyrus and higher white matter anisotropy of the splenium of corpus callosum predicted cognitive improvement in the training group. Old age, lower education level and individual differences in cortical thickness and white matter microstructure of the episodic memory network may predict outcomes following multi-strategic training.

Correlations between Gray Matter and White Matter Degeneration in Pure Alzheimer's Disease, Pure Subcortical Vascular Dementia, and Mixed Dementia.

Alzheimer's disease dementia (ADD) and subcortical vascular dementia (SVaD) both show cortical thinning and white matter (WM) microstructural changes. We evaluated different patterns of correlation between gray matter (GM) and WM microstructural changes in pure ADD, pure SVaD, and mixed dementia. We enrolled 40 Pittsburgh compound B (PiB) positive ADD patients without WM hyperintensities (pure ADD), 32 PiB negative SVaD patients (pure SVaD), 23 PiB positive SVaD patients (mixed dementia), and 56 normal controls. WM microstructural integrity was quantified using fractional anisotropy (FA), axial diffusivity (DA), and radial diffusivity (DR) values. We used sparse canonical correlation analysis to show correlated regions of cortical thinning and WM microstructural changes. In pure ADD patients, lower FA in the frontoparietal area correlated with cortical thinning in the left inferior parietal lobule and bilateral paracentral lobules. In pure SVaD patients, lower FA and higher DR across extensive WM regions correlated with cortical thinning in bilateral fronto-temporo-parietal regions. In mixed dementia patients, DR and DA changes across extensive WM regions correlated with cortical thinning in the bilateral fronto-temporo-parietal regions. Our findings showed that the relationships between GM and WM degeneration are distinct in pure ADD, pure SVaD, and mixed dementia, suggesting that different pathomechanisms underlie their correlations.

Protective effects of APOE e2 against disease progression in subcortical vascular mild cognitive impairment patients: A three-year longitudinal study.

Although the association between apolipoprotein E (APOE) genotype and disease progression is well characterized in patients with Alzheimer's disease, such a relationship is unknown in patients with subcortical vascular cognitive impairment. We evaluated whether APOE genotype is associated with disease progression in subcortical vascular mild cognitive impairment (svMCI) patients. We prospectively recruited 72 svMCI patients (19 APOE4 carriers, 42 APOE3 homozygotes, and 11 APOE2 carriers). Patients were annually followed-up with brain MRI and neuropsychological tests for three years and underwent a second Pittsburgh compound B (PiB)-PET at a mean interval of 32.3 months. Amyloid-ß burden was quantified by PiB standardized uptake value ratio (SUVR), and the amount of small vessel disease was quantified by number of lacune and small vessel disease score on MRI. We also measured cortical thickness. During the three years of follow-up, compared to the APOE3 homozygotes, there was less increase in PiB SUVR among APOE2 carriers (p = 0.023), while the APOE genotype did not show significant effects on small vessel disease progression. APOE2 carriers also showed less cortical thinning (p = 0.023) and a slower rate of cognitive decline (p = 0.009) compared to those with APOE3 homozygotes. Our findings suggest that, in svMCI patients, APOE2 has protective effects against amyloid-ß accumulation, cortical thinning, and cognitive decline.

Coronary artery calcium is associated with cortical thinning in cognitively normal individuals.

To evaluate the association between coronary artery calcium (CAC) and cortical thickness in a large sample of cognitively normal individuals, with special emphasis in determining if the association thickness has regional brain specificity and if it is mediated by white matter hyperintensities (WMH). A total of 512 participants were included in this study. CAC scores were assessed by multi-detector computed tomography. Cortical thickness was measured using a surface-based method. Linear mixed models were used to assess the association between CAC scores and cortical thickness. In fully adjusted models, increased CAC scores were associated with cortical thinning across several brain regions, which generally overlapped with the distribution of default mode network. The association between CAC scores and cortical thickness was significantly stronger in participants with moderate or severe WMH compared to those with none or mild WMH, even though CAC scores were not associated with WMH. In cognitively normal adults, CAC was associated with cortical thinning in areas related to cognitive function. This association was evident after adjusting for multiple coronary artery disease risk factors and for WMH, suggesting that CAC may be more closely related to Alzheimer's Disease-type disease rather than to cerebral small vessel disease.

Classifying anatomical subtypes of subjective memory impairment.

We aimed to categorize subjective memory impairment (SMI) individuals based on their patterns of cortical thickness and to propose simple models that can classify each subtype. We recruited 613 SMI individuals and 613 age- and gender-matched normal controls. Using hierarchical agglomerative cluster analysis, SMI individuals were divided into 3 subtypes: temporal atrophy (12.9%), minimal atrophy (52.4%), and diffuse atrophy (34.6%). Individuals in the temporal atrophy (Alzheimer's disease-like atrophy) subtype were older, had more vascular risk factors, and scored the lowest on neuropsychological tests. Combination of these factors classified the temporal atrophy subtype with 73.2% accuracy. On the other hand, individuals with the minimal atrophy (non-neurodegenerative) subtype were younger, were more likely to be female, and had depression. Combination of these factors discriminated the minimal atrophy subtype with 76.0% accuracy. We suggest that SMI can be largely categorized into 3 anatomical subtypes that have distinct clinical features. Our models may help physicians decide next steps when encountering SMI patients and may also be used in clinical trials.

Relative impact of amyloid-ß, lacunes, and downstream imaging markers on cognitive trajectories.

SEE COHEN DOI101093/AWW183 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Amyloid-ß and cerebral small vessel disease are the two major causes of cognitive impairment in the elderly. However, the underlying mechanisms responsible for precisely how amyloid-ß and cerebral small vessel disease affect cognitive impairment remain unclear. We investigated the effects of amyloid-ß and lacunes on downstream imaging markers including structural network and cortical thickness, further analysing their relative impact on cognitive trajectories. We prospectively recruited a pool of 117 mild cognitive impairment patients (45 amnestic type and 72 subcortical vascular type), from which 83 patients received annual follow-up with neuropsychological tests and brain magnetic resonance imaging for 3 years, and 87 patients received a second Pittsburgh compound B positron emission tomography analysis. Structural networks based on diffusion tensor imaging and cortical thickness were analysed. We used linear mixed effect regression models to evaluate the effects of imaging markers on cognitive decline. Time-varying Pittsburgh compound B uptake was associated with temporoparietal thinning, which correlated with memory decline (verbal memory test, unstandardized ß = -0.79, P < 0.001; visual memory test, unstandardized ß = -2.84, P = 0.009). Time-varying lacune number was associated with the degree of frontoparietal network disruption or thinning, which further affected frontal-executive function decline (Digit span backward test, unstandardized ß = -0.05, P = 0.002; Stroop colour test, unstandardized ß = -0.94, P = 0.008). Of the multiple imaging markers analysed, Pittsburgh compound B uptake and the number of lacunes had the greatest association with memory decline and frontal-executive function decline, respectively: Time-varying Pittsburgh compound B uptake (standardized ß = -0.25, P = 0.010) showed the strongest effect on visual memory test, followed by time-varying temporoparietal thickness (standardized ß = 0.21, P = 0.010) and time-varying nodal efficiency (standardized ß = 0.17, P = 0.024). Time-varying lacune number (standardized ß = -0.25, P = 0.014) showed the strongest effect on time-varying digit span backward test followed by time-varying nodal efficiency (standardized ß = 0.17, P = 0.021). Finally, time-varying lacune number (ß = -0.22, P = 0.034) showed the strongest effect on time-varying Stroop colour test followed by time-varying frontal thickness (standardized ß = 0.19, P = 0.026). Our multimodal imaging analyses suggest that cognitive trajectories related to amyloid-ß and lacunes have distinct paths, and that amyloid-ß or lacunes have greatest impact on cognitive decline. Our results provide rationale for the targeting of amyloid-ß and lacunes in therapeutic strategies aimed at ameliorating cognitive decline.