Correlation of brain tissue volume loss with inflammatory biomarkers IL1ß, P-tau, T-tau, and NLPR3 in the aging cognitively impaired population.

Background: Blood inflammatory biomarkers have emerged as important tools for diagnosing, assessing treatment responses, and predicting neurodegenerative diseases. This study evaluated the associations between blood inflammatory biomarkers and brain tissue volume loss in elderly people. Methods: This study included 111 participants (age 67.86 ± 8.29 years; 32 men and 79 women). A battery of the following blood inflammatory biomarkers was measured, including interleukin 1-beta (IL1ß), NACHT, LRR, and PYD domains-containing protein 3 (NLRP3), monomer Aß42 (mAß), oligomeric Aß42 (oAß), miR155, neurite outgrowth inhibitor A (nogo-A), phosphorylated tau (P-tau), and total tau (T-tau). Three-dimensional T1-weight images (3D T1WI) of all participants were prospectively obtained and segmented into gray matter and white matter to measure the gray matter volume (GMV), white matter volume (WMV), and gray-white matter boundary tissue volume (gwBTV). The association between blood biomarkers and tissue volumes was assessed using voxel-based and region-of-interest analyses. Results: GMV and gwBTV significantly decreased as the levels of IL1ß and T-tau increased, while no significant association was found between the level of P-tau and the three brain tissue volumes. Three brain tissue volumes were negatively correlated with the levels of IL1ß, P-tau, and T-tau in the hippocampus. Specifically, IL1ß and T-tau levels showed a distinct negative association with the three brain tissue volume losses in the hippocampus. In addition, gwBTV was negatively associated with the level of NLRP3. Conclusion: The observed association between brain tissue volume loss and elevated levels of IL1ß and T-tau suggests that these biomarkers in the blood may serve as potential biomarkers of cognitive impairment in elderly people. Thus, IL1ß and T-tau could be used to assess disease severity and monitor treatment response after diagnosis in elderly people who are at risk of cognitive decline.

Increased extra-neurite conductivity of brain in patients with Alzheimer's disease: A pilot study.

The objectives of this study were to investigate how the extra-neurite conductivity (EC) and intra-neurite conductivity (IC) were reflected in Alzheimer's disease (AD) patients compared with old cognitively normal (CN) people and patients with amnestic mild cognitive impairment (MCI) and to evaluate the association between those conductivity values and cognitive decline. To do this, high-frequency conductivity (HFC) at the Larmor frequency was obtained using MRI-based electrical property tomography (MREPT) and was decomposed into EC and IC using information of multi-shell multi-gradient direction diffusion tensor images. This prospective single-center study included 20 patients with mild or moderate AD, 25 patients with amnestic MCI, and 21 old CN participants. After decomposing EC and IC from HFC for all participants, we performed voxel-based and regions-of-interest analyses to compare conductivity between the three participant groups and to evaluate the association with either age or the Mini-Mental State Examination (MMSE) scores. We found increased EC in AD compared to CN and MCI. EC was significantly negatively associated with MMSE scores in the insula, and middle temporal gyrus. EC might be used as an imaging biomarker for helping to monitor cognitive function.

The Usefulness of 18F-FDG PET to Differentiate Subtypes of Dementia: The Systematic Review and Meta-Analysis.

Background and Purpose: Dementia subtypes, including Alzheimer's dementia (AD), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD), pose diagnostic challenges. This review examines the effectiveness of 18F-Fluorodeoxyglucose Positron Emission Tomography (18F-FDG PET) in differentiating these subtypes for precise treatment and management. Methods: A systematic review following Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines was conducted using databases like PubMed and Embase to identify studies on the diagnostic utility of 18F-FDG PET in dementia. The search included studies up to November 16, 2022, focusing on peer-reviewed journals and applying the gold-standard clinical diagnosis for dementia subtypes. Results: From 12,815 articles, 14 were selected for final analysis. For AD versus FTD, the sensitivity was 0.96 (95% confidence interval [CI], 0.88-0.98) and specificity was 0.84 (95% CI, 0.70-0.92). In the case of AD versus DLB, 18F-FDG PET showed a sensitivity of 0.93 (95% CI 0.88-0.98) and specificity of 0.92 (95% CI, 0.70-0.92). Lastly, when differentiating AD from non-AD dementias, the sensitivity was 0.86 (95% CI, 0.80-0.91) and the specificity was 0.88 (95% CI, 0.80-0.91). The studies mostly used case-control designs with visual and quantitative assessments. Conclusions: 18F-FDG PET exhibits high sensitivity and specificity in differentiating dementia subtypes, particularly AD, FTD, and DLB. This method, while not a standalone diagnostic tool, significantly enhances diagnostic accuracy in uncertain cases, complementing clinical assessments and structural imaging.

Predicting the apolipoprotein E ε4 allele carrier status based on gray matter volumes and cognitive function.

BACKGROUND: Apolipoprotein E (ApoE) ε4 carriers have a higher risk of developing Alzheimer's disease (AD) and show brain atrophy and cognitive decline even before diagnosis. OBJECTIVE: To predict ApoE ε4 status using gray matter volume (GMV) obtained from magnetic resonance imaging images and demographic data with machine learning (ML) methods. METHODS: We recruited 74 participants (25 probable AD, 24 amnestic mild cognitive impairment, and 25 cognitively normal older people) with known ApoE genotype (22 ApoE ε4 carriers and 52 noncarriers) and scanned them with three-dimensional (3D) T1-weighted (T1W) and 3D double inversion recovery (DIR) sequences. We extracted GMV from regions of interest related to AD pathology and used them as features along with age and mini-mental state examination (MMSE) scores to train different ML models. We performed both receiver operating characteristic curve analysis and the prediction analysis of the ApoE ε4 carrier with different ML models. RESULTS: The best model of ML analyses was a cubic support vector machine (SVM3) that used age, the MMSE score, and DIR GMVs at the amygdala, hippocampus, and precuneus as features (AUC = .88). This model outperformed models using T1W GMV or demographic data alone. CONCLUSION: Our results suggest that brain atrophy with DIR GMV and cognitive decline with aging can be useful biomarkers for predicting ApoE ε4 status and identifying individuals at risk of AD progression.

Evaluation of Efficacy and Safety Using Low Dose Radiation Therapy with Alzheimer's Disease: A Protocol for Multicenter Phase II Clinical Trial.

BACKGROUND: Alzheimer's disease (AD), the most common cause of dementia, is a neurodegenerative disease resulting from extracellular and intracellular deposits of amyloid-ß (Aß) and neurofibrillary tangles in the brain. Although many clinical studies evaluating pharmacological approaches have been conducted, most have shown disappointing results; thus, innovative strategies other than drugs have been actively attempted. OBJECTIVE: This study aims to explore low-dose radiation therapy (LDRT) for the treatment of patients with AD based on preclinical evidence, case reports, and a small pilot trial in humans. METHODS: This study is a phase II, multicenter, prospective, single-blinded, randomized controlled trial that will evaluate the efficacy and safety of LDRT to the whole brain using a linear accelerator in patients with mild AD. Sixty participants will be randomly assigned to three groups: experimental I (24 cGy/6 fractions), experimental II (300 cGy/6 fractions), or sham RT group (0 cGy/6 fractions). During LDRT and follow-up visits after LDRT, possible adverse events will be assessed by the physician's interview and neurological examinations. Furthermore, the effectiveness of LDRT will be measured using neurocognitive function tests and imaging tools at 6 and 12 months after LDRT. We will also monitor the alterations in cytokines, Aß42/Aß40 ratio, and tau levels in plasma. Our primary endpoint is the change in cognitive function test scores estimated by the Alzheimer's Disease Assessment Scale-Korea compared to baseline after 6 months of LDRT. CONCLUSIONS: This study is registered at ClinicalTrials.gov [NCT05635968] and is currently recruiting patients. This study will provide evidence that LDRT is a new treatment strategy for AD.

Microvascular morphology alteration using relaxation rate change with gadolinium-based magnetic resonance imaging contrast agent in patients with Alzheimer's disease.

Background: Conventional magnetic resonance imaging (MRI) techniques cannot demonstrate microvascular alterations in mild Alzheimer's disease (AD). Thus, the diagnosis of microvascular pathology commonly relies on postmortem. The purpose of this study was to evaluate alterations of microvascular structures in patients with AD using a 3T clinical MRI system with a commercially available contrast agent. Methods: Eleven patients with AD and 11 cognitively normal (CN) controls were included in this cross-sectional prospective study. R2 and R2* relaxation rate changes (∆R2 and ∆R2*) before and after a Gadolinium (Gd)-based contrast agent injection were calculated from images obtained with a multi-echo turbo spin-echo sequence and multi-echo gradient-echo sequence to obtain microvascular index maps of blood volume fraction (BVf), mean vessel diameter (mVD), vessel size index (VSI), mean vessel density (Q), and microvessel-weighted imaging (MvWI). Two-sample t-test was used to compare those values between the two groups. Correlation analysis was performed to evaluate the relationship between those values and age. Results: BVfs at the corpus callosum and at the thalamus were significantly increased in the AD group (P=0.024 and P=0.005, respectively). BVf at the gray matter (P=0.020) and white matter area (P=0.012) were also significantly increased in the AD group compared with the CN group. MvWIs at the hippocampus and parahippocampal gyrus were significantly increased in the AD group compared with the CN group (P=0.020 and P=0.006, respectively). Voxel-based analysis showed both mVD and VSI were significantly decreased at the prefrontal lobe in the AD group. Q were not significant difference between CN and AD groups. MvWI were significantly positively correlated with age. Conclusions: Microvascular index was a useful non-invasive method to evaluate microvascular morphology alteration. The microvascular morphology of AD was manifested as increasing BVf and microvessel-weighted.

Gray-white matter boundary Z-score and volume as imaging biomarkers of Alzheimer's disease.

Introduction: Alzheimer's disease (AD) presents typically gray matter atrophy and white matter abnormalities in neuroimaging, suggesting that the gray-white matter boundary could be altered in individuals with AD. The purpose of this study was to explore differences of gray-white matter boundary Z-score (gwBZ) and its tissue volume (gwBTV) between patients with AD, amnestic mild cognitive impairment (MCI), and cognitively normal (CN) elderly participants. Methods: Three-dimensional T1-weight images of a total of 227 participants were prospectively obtained from our institute from 2006 to 2022 to map gwBZ and gwBTV on images. Statistical analyses of gwBZ and gwBTV were performed to compare the three groups (AD, MCI, CN), to assess their correlations with age and Korean version of the Mini-Mental State Examination (K-MMSE), and to evaluate their effects on AD classification in the hippocampus. Results: This study included 62 CN participants (71.8 ± 4.8 years, 20 males, 42 females), 72 MCI participants (72.6 ± 5.1 years, 23 males, 49 females), and 93 AD participants (73.6 ± 7.7 years, 22 males, 71 females). The AD group had lower gwBZ and gwBTV than CN and MCI groups. K-MMSE showed positive correlations with gwBZ and gwBTV whereas age showed negative correlations with gwBZ and gwBTV. The combination of gwBZ or gwBTV with K-MMSE had a high accuracy in classifying AD from CN in the hippocampus with an area under curve (AUC) value of 0.972 for both. Conclusion: gwBZ and gwBTV were reduced in AD. They were correlated with cognitive function and age. Moreover, gwBZ or gwBTV combined with K-MMSE had a high accuracy in differentiating AD from CN in the hippocampus. These findings suggest that evaluating gwBZ and gwBTV in AD brain could be a useful tool for monitoring AD progression and diagnosis.

Robust Method for Screening Sleep Apnea With Single-Lead ECG Using Deep Residual Network: Evaluation With Open Database and Patch-Type Wearable Device Data.

This paper proposes a robust method to screen patients with sleep apnea syndrome (SAS) using a single-lead electrocardiogram (ECG). This method consists of minute-by-minute abnormal breathing detection and apnea-hypopnea index (AHI) estimation. Heartbeat interval and ECG-derived respiration (EDR) are calculated using the single-lead ECG and used to train the models, including ResNet18, ResNet34, and ResNet50. The proposed method, using data from 1232 subjects, was developed with two open datasets and experimental data and evaluated using two additional open datasets and data acquired from an abdomen-attached wearable device (in total, data from 189 subjects). ResNet18 showed the best results, having an average Cohen's kappa coefficient of 0.57, in the abnormal breathing detection. Moreover, SAS patient classification, with 15 as the AHI threshold, yielded an average Cohen's kappa coefficient of 0.71. The results of patient classification were biased toward data from the wearable patch-type device, which may be influenced by different ECG waveforms. The proposed method is tuned with a sample of the data from the device, and the performance result of Cohen's kappa increased from 0.54 to 0.91 for SAS patient classification. Our method, proposed in this paper, achieved equivalent performance results with data recorded using an abdomen-attached wearable device and two open datasets used in previous studies, although the method had not used those data during model training. The proposed method could reduce the development costs of commercial software, as it was developed using open datasets, has robust performance throughout all datasets.

Application of High-Frequency Conductivity Map Using MRI to Evaluate It in the Brain of Alzheimer's Disease Patients.

Background: The previous studies reported increased concentrations of metallic ions, imbalanced Na+ and K+ ions, and the increased mobility of protons by microstructural disruptions in Alzheimer's disease (AD). Purpose: (1) to apply a high-frequency conductivity (HFC) mapping technique using a clinical 3T MRI system, (2) compare HFC values in the brains of participants with AD, amnestic mild cognitive impairment (MCI), and cognitively normal (CN) elderly people, (3) evaluate the relationship between HFC values and cognitive decline, and (4) explore usefulness of HFC values as an imaging biomarker to evaluate the differentiation of AD from CN. Materials and Methods: This prospective study included 74 participants (23 AD patients, 27 amnestic MCI patients, and 24 CN elderly people) to explore the clinical application of HFC mapping in the brain from March 2019 to August 2021. We performed statistical analyses to compare HFC maps between the three participant groups, evaluate the association of HFC maps with Mini-Mental State Examination (MMSE) scores, and to evaluate the differentiation between the participant groups for HFC values for some brain areas. Results: We obtained a good HFC map non-invasively. The HFC value was higher in the AD group than in the CN and MCI groups. MMSE scores were negatively associated with HFC values. Age was positively associated with HFC values. The HFC value in the insula has a high area under the receiver operating characteristic (ROC) curve (AUC) value to differentiate AD patients from the CN participants (Sensitivity [SE] = 82, Specificity [SP] =97, AUC = 0.902, p < 0.0001), better than gray matter volume (GMV) in hippocampus (SE = 79, SP = 83, AUC = 0.880, p < 0.0001). The classification for differentiating AD from CN was highest by adding the hippocampal GMV to the insular HFC value (SE = 87, SP = 87, AUC = 0.928, p < 0.0001). Conclusion: High-frequency conductivity values were significantly increased in the AD group compared to the CN group and increased with age and disease severity. HFC values of the insula along with the GMV of the hippocampus can be used as an imaging biomarker to improve the differentiation of AD from CN.

Ultrasensitive probeless capacitive biosensor for amyloid beta (Aß1-42) detection in human plasma using interdigitated electrodes.

Progressive aggregation and protein misfolding are the initial fundamental indicators of neurodegenerative disorders such as Alzheimer's disease (AD). In this study, a highly sensitive and novel method to detect amyloid beta (Aß) biomarkers, which are a hallmark of AD, using an immunoassay platform-based interdigitated capacitive biosensor, has been explored. For several decades, aptamers have classified as a novel class of molecular recognition probes comprising single-stranded complementary DNA sequences that bind to their identified targets with high specificity and affinity by an in vitro technique called SELEX (systematic evolution of exponential and enrichment). Aptamers, often referred to as "chemical antibodies", possess several highly obvious features for clinical use. The proposed sensing bio-device was fabricated and glazed with oligomeric Aß (oAß) aptamer and anti-oAß antibody, functionalized onto a Pt/Ti-featured SiO2 substrate. Subsequently, analytical studies were conducted to confirm that the specificity, sensitivity, and selective detection of the oAß-based bioengineered surfaces facilitate a label-free approach. The bionic capacitive sensor achieved real-time detection within 5 s (faster response than ELISA) under the femto-molar range concentrations of oAß peptide in plasma using anti-oAß antibody and oAß aptamer with ultra-high affinity. Furthermore, the prepared capacitive biochip was selective against plasma-borne antigens and standby for 100 days at 4 °C. The developed biosensor is suitable for point-of-care (POC) diagnostic applications owing to its portability and scalability. Furthermore, the superior efficacy of oAß in identifying AD has huge potential for biomedical applications.

Analysis of treatment pattern of anti-dementia medications in newly diagnosed Alzheimer's dementia using OMOP CDM.

Anti-dementia medications are widely prescribed to patients with Alzheimer's dementia (AD) in South Korea. This study investigated the pattern of medical management in newly diagnosed patients with AD using a standardized data format-the Observational Medical Outcome Partnership Common Data Model from five hospitals. We examined the anti-dementia treatment patterns from datasets that comprise > 5 million patients during 2009-2019. The medication utility information was analyzed with respect to treatment trends and persistence across 11 years. Among the 8653 patients with newly diagnosed AD, donepezil was the most commonly prescribed anti-dementia medication (4218; 48.75%), followed by memantine (1565; 18.09%), rivastigmine (1777; 8.98%), and galantamine (494; 5.71%). The rising prescription trend during observation period was found only with donepezil. The treatment pathways for the three cholinesterase inhibitors combined with N-methyl-D-aspartate receptor antagonist were different according to the drugs (19.6%; donepezil; 28.1%; rivastigmine, and 17.2%; galantamine). A 12-month persistence analysis showed values of approximately 50% for donepezil and memantine and approximately 40% for rivastigmine and galantamine. There were differences in the prescribing pattern and persistence among anti-dementia medications from database using the Observational Medical Outcome Partnership Common Data Model on the Federated E-health Big Data for Evidence Renovation Network platform in Korea.

Myelin-Weighted Imaging Presents Reduced Apparent Myelin Water in Patients with Alzheimer's Disease.

The purpose of this study was to investigate myelin loss in both AD and mild cognitive impairment (MCI) patients with a new myelin water mapping technique within reasonable scan time and evaluate the clinical relevance of the apparent myelin water fraction (MWF) values by assessing the relationship between decreases in myelin water and the degree of memory decline or aging. Twenty-nine individuals were assigned to the cognitively normal (CN) elderly group, 32 participants were assigned to the MCI group, and 31 patients were assigned to the AD group. A 3D visualization of the short transverse relaxation time component (ViSTa)-gradient and spin-echo (GraSE) sequence was developed to map apparent MWF. Then, the MWF values were compared between the three participant groups and was evaluated the relationship with the degree of memory loss. The AD group showed a reduced apparent MWF compared to the CN and MCI groups. The largest AUC (area under the curve) value was in the corpus callosum and used to classify the CN and AD groups using the apparent MWF. The ViSTa-GraSE sequence can be a useful tool to map the MWF in a reasonable scan time. Combining the MWF in the corpus callosum with the detection of atrophy in the hippocampus can be valuable for group classification.

Respiratory Event Detection During Sleep Using Electrocardiogram and Respiratory Related Signals: Using Polysomnogram and Patch-Type Wearable Device Data.

This paper presents an automatic algorithm for the detection of respiratory events in patients using electrocardiogram (ECG) and respiratory signals. The proposed method was developed using data of polysomnogram (PSG) and those recorded from a patch-type device. In total, data of 1,285 subjects were used for algorithm development and evaluation. The proposed method involved respiratory event detection and apnea-hypopnea index (AHI) estimation. Handcrafted features from the ECG and respiratory signals were applied to machine learning algorithms including linear discriminant analysis, quadratic discriminant analysis, random forest, multi-layer perceptron, and the support vector machine (SVM). High performance was demonstrated when using SVM, where the overall accuracy achieved was 83% and the Cohen's kappa was 0.53 for the minute-by-minute respiratory event detection. The correlation coefficient between the reference AHI obtained using the PSG and estimated AHI as per the proposed method was 0.87. Furthermore, patient classification based on an AHI cutoff of 15 showed an accuracy of 87% and a Cohen's kappa of 0.72. The proposed method increases performance result, as it records the ECG and respiratory signals simultaneously. Overall, it can be used to lower the development cost of commercial software owing to the use of open datasets.

Association Between Plasma Amyloid-ß and Neuropsychological Performance in Patients With Cognitive Decline.

Objective: To investigate the association between plasma amyloid-ß (Aß) levels and neuropsychological performance in patients with cognitive decline using a highly sensitive nano-biosensing platform. Methods: We prospectively recruited 44 patients with cognitive decline who underwent plasma Aß analysis, amyloid positron emission tomography (PET) scanning, and detailed neuropsychological tests. Patients were classified into a normal control (NC, n = 25) or Alzheimer's disease (AD, n = 19) group based on amyloid PET positivity. Multiple linear regression was performed to determine whether plasma Aß (Aß40, Aß42, and Aß42/40) levels were associated with neuropsychological test results. Results: The plasma levels of Aß42/40 were significantly different between the NC and AD groups and were the best predictor of amyloid PET positivity by receiver operating characteristic curve analysis [area under the curve of 0.952 (95% confidence interval, 0.892-1.000)]. Although there were significant differences in the neuropsychological performance of cognitive domains (language, visuospatial, verbal/visual memory, and frontal/executive functions) between the NC and AD groups, higher levels of plasma Aß42/40 were negatively correlated only with verbal and visual memory performance. Conclusion: Our results demonstrated that plasma Aß analysis using a nano-biosensing platform could be a useful tool for diagnosing AD and assessing memory performance in patients with cognitive decline.

Development and evaluation of a T1 standard brain template for Alzheimer disease.

BACKGROUND: Patients with Alzheimer disease (AD) and mild cognitive impairment (MCI) have high variability in brain tissue loss, making it difficult to use a disease-specific standard brain template. The objective of this study was to develop an AD-specific three-dimensional (3D) T1 brain tissue template and to evaluate the characteristics of the populations used to form the template. METHODS: We obtained 3D T1-weighted images from 294 individuals, including 101 AD, 96 amnestic MCI, and 97 cognitively normal (CN) elderly individuals, and segmented them into different brain tissues to generate AD-specific brain tissue templates. Demographic data and clinical outcome scores were compared between the three groups. Voxel-based analyses and regions-of-interest-based analyses were performed to compare gray matter volume (GMV) and white matter volume (WMV) between the three participant groups and to evaluate the relationship of GMV and WMV loss with age, years of education, and Mini-Mental State Examination (MMSE) scores. RESULTS: We created high-resolution AD-specific tissue probability maps (TPMs). In the AD and MCI groups, losses of both GMV and WMV were found with respect to the CN group in the hippocampus (F >44.60, P<0.001). GMV was lower with increasing age in all individuals in the left (r=-0.621, P<0.001) and right (r=-0.632, P<0.001) hippocampi. In the left hippocampus, GMV was positively correlated with years of education in the CN groups (r=0.345, P<0.001) but not in the MCI (r=0.223, P=0.0293) or AD (r=-0.021, P=0.835) groups. WMV of the corpus callosum was not significantly correlated with years of education in any of the three subject groups (r=0.035 and P=0.549 for left, r=0.013 and P=0.821 for right). In all individuals, GMV of the hippocampus was significantly correlated with MMSE scores (left, r=0.710 and P<0.001; right, r=0.680 and P<0.001), while WMV of the corpus callosum showed a weak correlation (left, r=0.142 and P=0.015; right, r=0.123 and P=0.035). CONCLUSIONS: A 3D, T1 brain tissue template was created using imaging data from CN, MCI, and AD participants considering the participants' age, sex, and years of education. Our disease-specific template can help evaluate brains to promote early diagnosis of MCI individuals and aid treatment of MCI and AD individuals.

Relationship between Brain Tissue Changes and Blood Biomarkers of Cyclophilin A, Heme Oxygenase-1, and Inositol-Requiring Enzyme 1 in Patients with Alzheimer's Disease.

Cyclophilin A (CypA), heme oxygenase-1 (HO-1), and inositol-requiring enzyme 1 (IRE1) are believed to be associated with Alzheimer's disease (AD). In this study, we investigated the association between gray matter volume (GMV) changes and blood levels of CypA, HO-1, and IRE1 in cognitively normal (CN) subjects and those with amnestic mild cognitive impairment (aMCI) and AD. Forty-five elderly CN, 34 aMCI, and 39 AD subjects were enrolled in this study. The results of voxel-based multiple regression analysis showed that blood levels of CypA, HO-1, and IRE1 were correlated with GMV on brain magnetic resonance imaging (MRI) in the entire population (p = 0.0005). The three serum protein levels were correlated with GMV of signature AD regions in the population as a whole. CypA values increased with increasing GMV in the occipital gyrus (r = 0.387, p < 0.0001) and posterior cingulate (r = 0.196, p = 0.034). HO-1 values increased with increasing GMV at the uncus (r = 0.307, p = 0.0008), lateral globus pallidus and putamen (r = 0.287, p = 0.002), and hippocampus (r = 0.197, p = 0.034). IRE1 values decreased with increasing GMV at the uncus (r = -0.239, p = 0.010) and lateral globus pallidus and putamen (r = -0.335, p = 0.0002). Associations between the three serum protein levels and regional GMV indicate that the blood levels of these biomarkers may reflect the pathological mechanism of AD in the brain.

Delirium caused by topical administration of cyclopentolate for cataract surgery in mild cognitive impairment due to Alzheimer's disease: A case report.

RATIONALES: Cholinergic modification by anticholinergic medication can produce adverse effects in central nervous system (CNS) and cyclopentolate is an antimuscarinic agent widely used for ophthalmologic management. We demonstrate a rare case of hyperactive delirium caused by topical administration of cyclopentolate in a patient with amnestic mild cognitive impairment (MCI) due to Alzheimer's disease (AD). PATIENT CONCERNS: A 74-year-old man showed acute confusion after preparation for cataract operation in day surgery clinic. The patient became confused and agitated after instillation of topical cyclopentolate drop into the eye and the symptoms persisted over several hours. DIAGNOSIS: Previously the patient had been diagnosed with amnestic MCI with the finding of bilateral medial temporal atrophy on brain magnetic resonance imaging. 18F-flutemetamol positron emission tomography scan demonstrated multifocal amyloid deposition in the brain. INTERVENTIONS: The patient was closely observed with the supportive management. OUTCOMES: The patient began to recover 5 h after the onset of symptoms and the cognitive function was reverted to previous state within 24 h. LESSONS: It is well known that several drugs with anticholinergic effects used in perioperative periods make the patients susceptible to delirium, but even the topical administration of cyclopentolate for cataract surgery also produce adverse CNS effects in a vulnerable patient who is diagnosed with MCI due to AD in this case.

Clinical Approach of Low-Dose Whole-Brain Ionizing Radiation Treatment in Alzheimer's Disease Dementia Patients.

Our research team recently published two relevant papers. In one study, we have seen the acute effect of low-dose ionizing irradiation (LDIR) did not reduce the amyloid-ß (Aß) protein concentration in brain tissue, yet significantly improved synaptic degeneration and neuronal loss in the hippocampus and cerebral cortex. Surprisingly, in another study, we could see late effect that the LDIR-treated mice showed significantly improved learning and memory skills compared with those in the sham group. In addition, Aß concentrations were significantly decreased in brain tissue. Furthermore, the pro-inflammatory cytokine tumor necrosis factor-α was decreased and the anti-inflammatory cytokine transforming growth factor-ß was increased in the brain tissue of 5xFAD mice treated with LDIR. Definitive clinical results for the safety and efficacy of LDIR have not yet been published and, despite the promising outcomes reported during preclinical studies, LDIR can only be applied to patients with Alzheimer's disease dementia when clinical results are made available. In addition, in the case of LDIR, additional large-scale clinical studies are necessary to determine the severity of Alzheimer's disease dementia, indications for LDIR, the total dose to be irradiated, fraction size, and intervals of LDIR treatment. The purpose of this review is to summarize the mechanism of LDIR based on existing preclinical results in a way that is useful for conducting subsequent clinical research.

Added Value of Chemical Exchange-Dependent Saturation Transfer MRI for the Diagnosis of Dementia.

OBJECTIVE: Chemical exchange-dependent saturation transfer (CEST) MRI is sensitive for detecting solid-like proteins and may detect changes in the levels of mobile proteins and peptides in tissues. The objective of this study was to evaluate the characteristics of chemical exchange proton pools using the CEST MRI technique in patients with dementia. MATERIALS AND METHODS: Our institutional review board approved this cross-sectional prospective study and informed consent was obtained from all participants. This study included 41 subjects (19 with dementia and 22 without dementia). Complete CEST data of the brain were obtained using a three-dimensional gradient and spin-echo sequence to map CEST indices, such as amide, amine, hydroxyl, and magnetization transfer ratio asymmetry (MTRasym) values, using six-pool Lorentzian fitting. Statistical analyses of CEST indices were performed to evaluate group comparisons, their correlations with gray matter volume (GMV) and Mini-Mental State Examination (MMSE) scores, and receiver operating characteristic (ROC) curves. RESULTS: Amine signals (0.029 for non-dementia, 0.046 for dementia, p = 0.011 at hippocampus) and MTRasym values at 3 ppm (0.748 for non-dementia, 1.138 for dementia, p = 0.022 at hippocampus), and 3.5 ppm (0.463 for non-dementia, 0.875 for dementia, p = 0.029 at hippocampus) were significantly higher in the dementia group than in the non-dementia group. Most CEST indices were not significantly correlated with GMV; however, except amide, most indices were significantly correlated with the MMSE scores. The classification power of most CEST indices was lower than that of GMV but adding one of the CEST indices in GMV improved the classification between the subject groups. The largest improvement was seen in the MTRasym values at 2 ppm in the anterior cingulate (area under the ROC curve = 0.981), with a sensitivity of 100 and a specificity of 90.91. CONCLUSION: CEST MRI potentially allows noninvasive image alterations in the Alzheimer's disease brain without injecting isotopes for monitoring different disease states and may provide a new imaging biomarker in the future.