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Cases of iatrogenic cerebral amyloid angiopathy (CAA) have been increasingly reported recently, particularly those associated with neurosurgery. Preclinical studies have shown taxifolin to be promising for treating CAA. We describe a young 42-year-old man with a history of childhood traumatic brain injury that required a craniotomy for hematoma evacuation. He later presented with recurrent lobar intracerebral hemorrhage (ICH) decades later, which was histologically confirmed to be CAA. Serial 11C-Pittsburgh compound B positron emission tomography (11C-PiB-PET) imaging showed a 24% decrease in global standardized uptake value ratio (SUVR) at 10 months after taxifolin use. During this period, the patient experienced clinical improvement with improved consciousness and reduced recurrent ICH frequency, which may be partly attributable to the potential amyloid-ß (Aß) clearing the effect of taxifolin. However, this effect seemed to have diminished at 15 months, CAA should be considered in young patients presenting with recurrent lobar ICH with a history of childhood neurosurgery, and serial 11C-PiB-PET scans warrant further validation as a strategy for monitoring treatment response in CAA for candidate Aß-clearing therapeutic agents such as taxifolin.

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Introduction: Cerebral small vessel disease (SVD) is an important cause of dementia that lacks effective treatment. We evaluated the efficacy and safety of cilostazol, an antiplatelet agent with potential neurovascular protective effects, in slowing the progression of white matter hyperintensities (WMHs) in stroke- and dementia-free subjects harboring confluent WMH on magnetic resonance imaging (MRI). Methods: In this single-center, randomized, double-blind, placebo-controlled study, we randomized stroke- and dementia-free subjects with confluent WMHs to receive cilostazol or placebo for 2 years in a 1:1 ratio. The primary outcome was change in WMH volume over 2 years. Secondary outcomes were changes in brain volumes, lacunes, cerebral microbleeds, perivascular space, and alterations in white matter microstructural integrity, cognition, motor function, and mood. Results: We recruited 120 subjects from October 27, 2014, to January 21, 2019. A total of 55 subjects in the cilostazol group and 54 subjects in the control group were included for intention-to-treat analysis. At 2-year follow-up, the changes in WMH volume were not statistically different between cilostazol treatment and placebo (0.3±1.0 mL vs -0.1±0.8 mL, p = 0.167). Secondary outcomes, bleeding and vascular events, were also not statistically different between the two groups. Discussion: In this trial with stroke- and dementia-free subjects with confluent WMHs, cilostazol did not impact WMH progression but demonstrated an acceptable safety profile. Future studies should address the treatment effects of cilostazol on subjects at different clinical stages of SVD.

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BACKGROUND: There is no simple model to screen for Alzheimer's disease, partly because the diagnosis of Alzheimer's disease itself is complex-typically involving expensive and sometimes invasive tests not commonly available outside highly specialised clinical settings. We aimed to develop a deep learning algorithm that could use retinal photographs alone, which is the most common method of non-invasive imaging the retina to detect Alzheimer's disease-dementia. METHODS: In this retrospective, multicentre case-control study, we trained, validated, and tested a deep learning algorithm to detect Alzheimer's disease-dementia from retinal photographs using retrospectively collected data from 11 studies that recruited patients with Alzheimer's disease-dementia and people without disease from different countries. Our main aim was to develop a bilateral model to detect Alzheimer's disease-dementia from retinal photographs alone. We designed and internally validated the bilateral deep learning model using retinal photographs from six studies. We used the EfficientNet-b2 network as the backbone of the model to extract features from the images. Integrated features from four retinal photographs (optic nerve head-centred and macula-centred fields from both eyes) for each individual were used to develop supervised deep learning models and equip the network with unsupervised domain adaptation technique, to address dataset discrepancy between the different studies. We tested the trained model using five other studies, three of which used PET as a biomarker of significant amyloid ß burden (testing the deep learning model between amyloid ß positive vs amyloid ß negative). FINDINGS: 12 949 retinal photographs from 648 patients with Alzheimer's disease and 3240 people without the disease were used to train, validate, and test the deep learning model. In the internal validation dataset, the deep learning model had 83·6% (SD 2·5) accuracy, 93·2% (SD 2·2) sensitivity, 82·0% (SD 3·1) specificity, and an area under the receiver operating characteristic curve (AUROC) of 0·93 (0·01) for detecting Alzheimer's disease-dementia. In the testing datasets, the bilateral deep learning model had accuracies ranging from 79·6% (SD 15·5) to 92·1% (11·4) and AUROCs ranging from 0·73 (SD 0·24) to 0·91 (0·10). In the datasets with data on PET, the model was able to differentiate between participants who were amyloid ß positive and those who were amyloid ß negative: accuracies ranged from 80·6 (SD 13·4%) to 89·3 (13·7%) and AUROC ranged from 0·68 (SD 0·24) to 0·86 (0·16). In subgroup analyses, the discriminative performance of the model was improved in patients with eye disease (accuracy 89·6% [SD 12·5%]) versus those without eye disease (71·7% [11·6%]) and patients with diabetes (81·9% [SD 20·3%]) versus those without the disease (72·4% [11·7%]). INTERPRETATION: A retinal photograph-based deep learning algorithm can detect Alzheimer's disease with good accuracy, showing its potential for screening Alzheimer's disease in a community setting. FUNDING: BrightFocus Foundation.

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OBJECTIVES: Elderly persons harbouring severe white matter hyperintensity (WMH), a radiological manifestation of cerebral small vessel disease (SVD), have an increased risk of dementia, stroke and poor functional outcomes. A simple screening tool will enhance their recruitment into preventive trials for SVD. We explored the clinical utility of the pulsatility index (PI) of the middle cerebral artery (MCA), obtained from transcranial Doppler ultrasound (TCD), in identifying severe WMH among community elderly persons with vascular risk factors. METHODS: Three hundred and thirty-one dementia- and stroke-free community elderly subjects with hypertension and/or diabetes mellitus underwent TCD to obtain the MCA PI. The WMH volume on 3.0 Tesla MRI was quantified and normalized to each subject's brain volume. The normalized WMH volumes were classified as low (<14.5 ml, 1 standard deviation [SD] above the mean, 84th percentile) or high (≥14.5 ml). The severity of WMH was also rated visually with the Fazekas score. Logistic regression and receiver-operator characteristics (ROC) analysis were performed to evaluate the association between the MCA PI and the severity of WMH. RESULTS: The MCA PI was not an independent predictor of severe WMH. An MCA PI ≥1.095 detected high normalized WMH volumes with an area under the curve (AUC) of 0.553 (95% CI 0.473-0.633), sensitivity of 0.556, and specificity of 0.523. ROC analysis of the MCA PI in predicting high Fazekas scores yielded similar findings. CONCLUSION: In stroke- and dementia-free elderly persons with vascular risk factors, the MCA PI was unable to identify severe WMH. (Word count: 260).

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BACKGROUND: The Montreal Cognitive Assessment (MoCA) is psychometrically superior over the Mini-mental State Examination (MMSE) for cognitive screening in stroke or transient ischemic attack (TIA). It is free for clinical and research use. The objective of this study is to convert scores from the MMSE to MoCA and MoCA-5-minute protocol (MoCA-5 min) and to examine the ability of the converted scores in detecting cognitive impairment after stroke or TIA. METHODS: A total of 904 patients were randomly divided into training (n = 623) and validation (n = 281) samples matched for demography and cognition. MMSE scores were converted to MoCA and MoCA-5 min using (1) equipercentile method with log-linear smoothing and (2) Poisson regression adjusting for age and education. Receiver operating characteristics curve analysis was used to examine the ability of the converted scores in differentiating patients with cognitive impairment. RESULTS: The mean education was 5.8 (SD = 4.6; ranged 0-20) years. The entire spectrum of MMSE scores was converted to MoCA and MoCA-5 min using equipercentile method. Relationship between MMSE and MoCA scores was confounded by age and education, and a conversion equation with adjustment for age and education was derived. In the validation sample, the converted scores differentiated cognitively impaired patients with area under receiver operating characteristics curve 0.826 to 0.859. CONCLUSION: We provided 2 methods to convert scores from the MMSE to MoCA and MoCA-5 min based on a large sample of patients with stroke or TIA having a wide range of education and cognitive levels. The converted scores differentiated patients with cognitive impairment after stroke or TIA with high accuracy.

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OBJECTIVE: Understanding how symptomatic intracranial atherosclerotic disease (ICAD) evolves with current medical therapy may inform secondary stroke prevention. METHODS: In a prospective academic-initiated study, we recruited 50 patients (mean age = 63.4 ± 9.0 years) with acute strokes attributed to high-grade (≥70%) intracranial atherosclerotic stenosis for 3-dimensional rotational angiograms before and after intensive medical therapy for 12 months. Treatment targets included low-density lipoprotein ≤ 70mg/dl, glycosylated hemoglobin (HbA1c) ≤ 6.5%, and systolic blood pressure ≤ 140 mmHg. We analyzed infarct topography and monitored microembolic signal in recurrent strokes. The reference group was a published cohort of 143 ICAD patients. RESULTS: Overall, the stenoses regressed from 79% at baseline (interquartile range [IQR] = 71-87%) to 63% (IQR = 54-74%) in 1 year (p < 0.001). Specifically, the qualifying lesions (n = 49) regressed (stenosis reduced >10%) in 24 patients (49%), remained quiescent (stenosis same or ±10%) in 21 patients (43%), and progressed (stenosis increased >10%) in 4 patients (8%). There was no difference in intensity of risk factor control between groups of diverging clinical or angiographic outcomes. Higher HbA1c at baseline predicted plaque regression at 1 year (odds ratio = 4.4, 95% confidence interval = 1.4-14.5, p = 0.006). Among the 6 patients with recurrent strokes pertaining to the qualifying stenosis, 5 patients had solitary or rosarylike acute infarcts along the internal or anterior border zones, and 2 patients showed microembolic signals in transcranial Doppler ultrasound. INTERPRETATION: A majority of symptomatic high-grade intracranial plaques had regressed or remained quiescent by 12 months under intensive medical therapy. Artery-to-artery thromboembolism with impaired washout at border zones was a common mechanism in stroke recurrence.

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We evaluated the safety and efficacy of rituximab in seven Chinese patients with neuromyelitis optica (NMO) or neuromyelitis optica syndrome disorders (NMOSD) in a tertiary medical center in Hong Kong. After rituximab induction, five patients became relapse-free and two had 50% reduction of relapses over a median follow-up of 24 months. No further deterioration of functional status, measured by the Expanded Disability Status Scale, was observed in all patients. Infusions were well tolerated except in two patients who developed transient hypotension. Rituximab reduced clinical relapse and prevented neurological deterioration in a small cohort of Chinese patients with NMO or NMOSD.

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