Imaging Measures Research Articles

Remote Sensing Assessment of Water Resources, Vegetation, and Land Surface Temperature in Eastern Saudi Arabia: Identification, Variability, and Trends

Saudi Arabia has one of the biggest water shortages and the least vegetation in the world, which is presumed to provoke this problem further due to climate change. Therefore, the present study investigates the water, vegetation, and temperature over Al-Asfar Lake region, Al Ahsa, Eastern province of Saudi Arabia using the Normalized Difference Water Index (NDWI), Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST: °C) from Landsat-8 based operational land imager (OLI) measurements for the period 2013 to 2023. This study presented annual and seasonal (dry months: June–September and wet months: December–April) spatiotemporal distribution and variations, calculated their absolute change and trends, and examined their relationship. Results showed positive NDWI values over Al-Asfar Lake, indicating waterbodies; while positive NDVI values on the lake's bank, signifying vegetation. Notably, there were significant temporal variations in water and vegetation observed on annual, seasonal, and monthly scales. The study also found an overall decrease in vegetation areas of 5.36 km2 in 2023 compared to 2013, while waterbodies increased by 8.83 km2. The trend analysis using area-averaged data demonstrated that NDWI increased on annual (0.0075/year) and seasonal (dry: 0.0083/year and wet: 0.0049/year) scales, while NDVI decreased (annual: 0.0066/year, dry: 0.0083/year, and wet: 0.0009/year). Moreover, LST was recorded least amount over waterbodies (28.23 °C) and vegetation (32.45 °C) covered areas compared to the entire lake region (38.43 °C), respectively. Remark, LST displayed decreasing trends over waterbodies (−0.05/year), followed by vegetation (−0.17/year), and the entire lake region (−0.0001/year), signifying that water and vegetation are vital components to controlling land surface temperature in this region. Finally, the LST showed a positive correlation with NDVI and negative correlation with NDWI. There may be a direct and indirect impact of climate change upon NDVI, LST, and NDWI as shown by the decreases in NDVI and LST and an increase in NDWI. This study can be considered as a base document to monitor waterbodies, vegetation cover, and temperature changes using remote sensing measurements of NDWI, NDVI, and LST, which will assist policymakers in developing water resource management, irrigation planning, and environmental monitoring strategies.

Spinal cord lesion MRI and behavioral outcomes in a miniature pig model of spinal cord injury: exploring preclinical potential through an ad hoc comparison with human SCI.

prospective case series of Yucatan miniature pig spinal cord contusion injury model with comparison to human cases of spinal cord injury (SCI). to describe magnetic resonance imaging (MRI) measures of spinal cord lesion severity along with estimates of lateral corticospinal tracts spared neural tissue in both a less severe and more severe contusion SCI model, as well as to describe their corresponding behavioral outcome changes. University laboratory setting. Following a more severe and less severe SCI, each pig underwent spinal cord MRI to measure lesion characteristics, along with locomotor and urodynamics outcomes testing. In the pig with more severe SCI, locomotor and urodynamic outcomes were poor, and both the spinal cord lesion volume and damage estimates to the lateral corticospinal tracts were large. Conversely, in the pig with less severe SCI, locomotor and urodynamic outcomes were favorable, with the spinal cord lesion volume and damage estimates to the lateral corticospinal tracts being less pronounced. For two human cases matched on estimates of damage to the lateral corticospinal tract regions, the clinical presentations were similar to the pig outcomes, with more limited mobility and more limited bladder functional independence in the more severe case. Our initial findings contribute valuable insights to the emergent field of MRI-based evaluation of spinal cord lesions in pig models, offering a promising avenue for understanding and potentially improving outcomes in spinal cord injuries.

Accelerated High-Resolution Deep Learning Reconstruction Turbo Spin Echo MRI of the Knee at 7 T.

The aim of this study was to compare the image quality of 7 T turbo spin echo (TSE) knee images acquired with varying factors of parallel-imaging acceleration reconstructed with deep learning (DL)-based and conventional algorithms. This was a prospective single-center study. Twenty-three healthy volunteers underwent 7 T knee magnetic resonance imaging. Two-, 3-, and 4-fold accelerated high-resolution fat-signal-suppressing proton density (PD-fs) and T1-weighted coronal 2D TSE acquisitions with an encoded voxel volume of 0.31 × 0.31 × 1.5 mm3 were acquired. Each set of raw data was reconstructed with a DL-based and a conventional Generalized Autocalibrating Partially Parallel Acquisition (GRAPPA) algorithm. Three readers rated image contrast, sharpness, artifacts, noise, and overall quality. Friedman analysis of variance and the Wilcoxon signed rank test were used for comparison of image quality criteria. The mean age of the participants was 32.0 ± 8.1 years (15 male, 8 female). Acquisition times at 4-fold acceleration were 4 minutes 15 seconds (PD-fs, Supplemental Video is available at http://links.lww.com/RLI/A938) and 3 minutes 9 seconds (T1, Supplemental Video available at http://links.lww.com/RLI/A939). At 4-fold acceleration, image contrast, sharpness, noise, and overall quality of images reconstructed with the DL-based algorithm were significantly better rated than the corresponding GRAPPA reconstructions (P < 0.001). Four-fold accelerated DL-reconstructed images scored significantly better than 2- to 3-fold GRAPPA-reconstructed images with regards to image contrast, sharpness, noise, and overall quality (P ≤ 0.031). Image contrast of PD-fs images at 2-fold acceleration (P = 0.087), image noise of T1-weighted images at 2-fold acceleration (P = 0.180), and image artifacts for both sequences at 2- and 3-fold acceleration (P ≥ 0.102) of GRAPPA reconstructions were not rated differently than those of 4-fold accelerated DL-reconstructed images. Furthermore, no significant difference was observed for all image quality measures among 2-fold, 3-fold, and 4-fold accelerated DL reconstructions (P ≥ 0.082). This study explored the technical potential of DL-based image reconstruction in accelerated 2D TSE acquisitions of the knee at 7 T. DL reconstruction significantly improved a variety of image quality measures of high-resolution TSE images acquired with a 4-fold parallel-imaging acceleration compared with a conventional reconstruction algorithm.

Association between synovial tissue damage and pain in late-stage knee osteoarthritis: A cross-sectional study

ObjectiveTo identify the presence and distribution of histopathological features of synovial inflammation and tissue damage, and to test their associations with US imaging measures of synovitis and patient-reported measures of pain in knee osteoarthritis (OA). DesignIn the cross-sectional study of 122 patients undergoing surgery for painful late-stage (Kellgren-Lawrence Grade 3 or 4) knee OA, we compared ultrasound (US) measures of synovitis (n=118) and pain (Knee Injury and Osteoarthritis Outcome Score) to histopathological measures of inflammation vs. synovial tissue damage in synovial tissue biopsies. Associations of histopathological features with US measures of inflammation or pain were assessed using linear or logistic regression, while controlling for covariates. ResultsHistopathological features of inflammation were associated with higher odds of moderate/severe US synovitis (OR=1.34 [95%CI 1.04, 1.74), whereas features of synovial tissue damage were associated with lower odds of moderate/severe US synovitis (OR = 0.77 [95%CI 0.57, 1.03]). Worse histopathological scores for synovial tissue damage were associated with more pain (-1.47 [95%CI -2.88, -0.05]), even while adjusting for synovial inflammation (-1.61 [95%CI -3.12, -0.10]). ConclusionsSynovial tissue damage is associated with pain in late-stage knee OA, independent from inflammation and radiographic damage. These novel findings suggest that preventing synovial tissue damage may be an important goal of disease-modifying OA therapy.

Relationships between plasma biomarkers, tau PET, FDG PET, and volumetric MRI in mild to moderate Alzheimer's disease patients.

The "A/T/N" (amyloid/tau/neurodegeneration) framework provides a biological basis for Alzheimer's disease (AD) diagnosis and can encompass additional changes such as inflammation ("I"). A spectrum of T/N/I imaging and plasma biomarkers was acquired in a phase 2 clinical trial of rasagiline in mild to moderate AD patients. We evaluated these to understand biomarker distributions and relationships within this population. Plasma biomarkers of pTau-181, neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), other inflammation-related proteins, imaging measures including fluorodeoxyglucose (FDG) positron emission tomography (PET), flortaucipir PET, and volumetric magnetic resonance imaging (MRI), and cognitive endpoints were analyzed to assess characteristics and relationships for the overall population (N = 47 at baseline and N = 21 for longitudinal cognitive comparisons) and within age-decade subgroups (57-69, 70-79, 80-90 years). Data demonstrate wide clinical and biomarker heterogeneity in this population influenced by age and sex. Plasma pTau-181 and GFAP correlate with tau PET, most strongly in left inferior temporal cortex (p = 0.0002, p = 0.0006, respectively). In regions beyond temporal cortex, tau PET uptake decreased with age for the same pTau-181 or GFAP concentrations. FDG PET and brain volumes correlate with tau PET in numerous regions (such as inferior temporal: p = 0.0007, p = 0.00001, respectively). NfL, GFAP, and all imaging modalities correlate with baseline MMSE; subsequent MMSE decline is predicted by baseline parahippocampal and lateral temporal tau PET (p = 0.0007) and volume (p = 0.0006). Lateral temporal FDG PET (p = 0.006) and volume (p = 0.0001) are most strongly associated with subsequent ADAS-cog decline. NfL correlates with FDG PET and baseline MMSE but not tau PET. Inflammation biomarkers are intercorrelated but correlated with other biomarkers in only the youngest group. Associations between plasma biomarkers, imaging biomarkers, and cognitive status observed in this study provide insight into relationships among biological processes in mild to moderate AD. Findings show the potential to characterize AD patients regarding likely tau pathology, neurodegeneration, prospective clinical decline, and the importance of covariates such as age. Plasma pTau-181 and GFAP correlated with regional and global tau PET in mild to moderate AD.NfL correlated with FDG PET and cognitive endpoints but not plasma pTau-181 or tau PET.Volume and FDG PET showed strong relationships to tau PET, one another, and cognitive status.Temporal volumes most strongly predicted decline in both MMSE and ADAS-cog.Volume and plasma biomarkers can enrich for elevated tau PET with age a significant covariate.

Using DNA Algorithm to Hide a Compressed Ciphertext in Colored Image

Cryptography is the fundamental key to keeping data that are more trusted for the increasing reliability in the digital community. Steganography is widely used to protect any hidden data in the media so that it may not get hacked. The conventional protection styles do not provide the requirements of cyber security under the new hacker's techniques that are applied for any hacking data and confidential information. Moreover, using the encryption algorithms without providing extra barriers alone could provide an opportunity to be breached therefore, boosting the levels of protection is really urgent to shield information against any intruders. This paper submits a proposed algorithm that can be applied to overcome the risks of hacking and increase the data protection. First, this algorithm uses the DNA to encrypt the data, which is then made complex by a multiplier and compressed by using the GZIP algorithm. The final stage is to hide the compressed data in the media (color image pixels) by using the LSB method. When applying these levels of protection, the amount of data compression becomes at 75%, and the image measures proves that good results are fulfilled, for instance, Lina sample measure is for SSIM = 1, PSNR = 67.6119, MSE = 0.0115, UACI = 7.00284 and NPCR = 0.01152. This algorithm contributes to increase the level of data protection in the communication between any parties to transfer certain confidential information.

The genetic architecture of biological age in nine human organ systems.

Investigating the genetic underpinnings of human aging is essential for unraveling the etiology of and developing actionable therapies for chronic diseases. Here, we characterize the genetic architecture of the biological age gap (BAG; the difference between machine learning-predicted age and chronological age) across nine human organ systems in 377,028 participants of European ancestry from the UK Biobank. The BAGs were computed using cross-validated support vector machines, incorporating imaging, physical traits and physiological measures. We identify 393 genomic loci-BAG pairs (P < 5 × 10-8) linked to the brain, eye, cardiovascular, hepatic, immune, metabolic, musculoskeletal, pulmonary and renal systems. Genetic variants associated with the nine BAGs are predominantly specific to the respective organ system (organ specificity) while exerting pleiotropic links with other organ systems (interorgan cross-talk). We find that genetic correlation between the nine BAGs mirrors their phenotypic correlation. Further, a multiorgan causal network established from two-sample Mendelian randomization and latent causal variance models revealed potential causality between chronic diseases (for example, Alzheimer's disease and diabetes), modifiable lifestyle factors (for example, sleep duration and body weight) and multiple BAGs. Our results illustrate the potential for improving human organ health via a multiorgan network, including lifestyle interventions and drug repurposing strategies.

Brain and cervical spinal cord MRI correlates of sensorimotor impairment in patients with multiple sclerosis.

Cervical spinal cord (cSC) lesions and atrophy contribute to disability in multiple sclerosis (MS), but associations with specific sensorimotor dysfunction require further exploration. To investigate the associations of brain and cSC magnetic resonance imaging (MRI) measures with sensorimotor impairment in MS. One hundred fifty-one MS patients and 69 healthy controls underwent 3T MRI and clinical assessments including Expanded Disability Status Scale (EDSS), 9-hole peg test (9-HPT), finger tapping test (FTT), timed 25-foot walk test (T25FWT), and vibration detection threshold (VDT). Random forest ranked brain (T2-hyperintense lesion volume (T2-LV) and normalized deep gray matter (GM), cortical and white matter (WM) volumes) and cSC (T2-LV and total, GM, and WM cross-sectional areas (CSAs) at C2/C3 level) MRI measures relevance in explaining EDSS milestones (EDSS ⩾3.0, ⩾4.0, and ⩾6.0), VDT, pyramidal and sensory functional systems (P-FS and S-FS ⩾2), and motor tests impairment. Various combinations of brain and cSC MRI measures explained EDSS milestones (area under the curve (AUC) =0.879-0.900), VDT (R2 = 0.194), and impaired P-FS (AUC = 0.820), S-FS (AUC = 0.795), 9-HPT (AUC = 0.793), FTT (AUC = 0.740), and T25FWT (AUC = 0.825). cSC GM CSA was the most informative feature for all outcomes, except 9-HPT. cSC MRI measures, especially GM CSA, explain EDSS and sensorimotor dysfunction better than brain measures in MS.

Sex difference in body image, exercise motivation and social comparison among Instagram users: a cross sectional study.

In the 21 st century, impact of social media, particularly Social Networking Sites (SNSs) has been linked to a wide range of human beliefs and expectations. Growing body of research has indicated that body image concerns along with exercise motivation and social comparison are on the rise among young adults. The present study aimed to examine the sex difference in body image, exercise motivation and social comparison among people who use Instagram in the age group 20-30. A total of 212 participants (men=106, women=106) aged 20-30 years, who are users of Instagram completed Body Self Image Questionnaire Short Form as a measure of Body image, Exercise Motivation Inventory - 2 as a measure of Exercise Motivation and Instagram as a Tool for Social Comparison as a measure of Social Comparison. Results showed that a significant difference in body image exist across gender with body image issues higher among females and significant difference in exercise motivation across gender with exercise motivation higher among males. No sex differences were seen in social comparison. It was concluded that body image concerns are higher among females and the drive for exercise is higher among males who used Instagram. It was found that body image concerns were higher among people who exercised regularly as well as among those who followed fitness related pages on Instagram as compared to those who did not. These results provide an insight into the sex differences between the variables and future directions can be aimed at conducting an in-depth analysis using body image, exercise motivation and social comparison.

Remote and unsupervised digital memory assessments can reliably detect cognitive impairment in Alzheimer's disease.

Remote unsupervised cognitive assessments have the potential to complement and facilitate cognitive assessment in clinical and research settings. Here, we evaluate the usability, validity, and reliability of unsupervised remote memory assessments via mobile devices in individuals without dementia from the Swedish BioFINDER-2 study and explore their prognostic utility regarding future cognitive decline. Usability was rated positively; remote memory assessments showed good construct validity with traditional neuropsychological assessments and were significantly associated with tau-positron emission tomography and downstream magnetic resonance imaging measures. Memory performance at baseline was associated with future cognitive decline and prediction of future cognitive decline was further improved by combining remote digital memory assessments with plasma p-tau217. Finally, retest reliability was moderate for a single assessment and good for an aggregate of two sessions. Our results demonstrate that unsupervised digital memory assessments might be used for diagnosis and prognosis in Alzheimer's disease, potentially in combination with plasma biomarkers. Remote and unsupervised digital memory assessments are feasible in older adults and individuals in early stages of Alzheimer's disease. Digital memory assessments are associated with neuropsychological in-clinic assessments, tau-positron emission tomography and magnetic resonance imaging measures. Combination of digital memory assessments with plasma p-tau217 holds promise for prognosis of future cognitive decline. Future validation in further independent, larger, and more diverse cohorts is needed to inform clinical implementation.

Measurement invariance of two measures of positive body image among Hispanic/Latina undergraduate women

Although positive body image is associated with mental and physical health benefits, there is a relative dearth of research investigating the psychometric properties of commonly used measures of positive body image among Hispanic/Latina women in the United States. The current study explored the psychometric properties of the Body Appreciation Scale-2 (BAS-2; Tylka & Wood-Barcalow, 2015a) and the Functionality Appreciation Scale (FAS; Alleva et al., 2017) in undergraduate women. Altogether 565 undergraduates (n = 386 Hispanic/Latina; n = 179 non-Hispanic White [NHW]) completed the BAS-2, FAS, and demographic questionnaires. Confirmatory factor analysis (CFA) and measurement invariance testing across ethnicity was conducted on each measure. The CFA confirmed the 1-factor, 10-item model of the BAS-2 among Hispanic/Latina women but indicated a less than adequate model fit for the FAS which improved after correlating the residuals of items 6 and 7. Measurement invariance testing revealed evidence of partial scalar invariance of the BAS-2 and full invariance of the FAS across ethnicity. There were no significant mean differences between groups on the measures. These analyses indicate acceptable psychometric properties of the BAS-2 and FAS among Hispanic/Latina women. Nonetheless, they did suggest potentially meaningful group differences in how these items behaved, which warrant further exploration.

Longitudinal associations of reproductive factors and exogeneous estrogens with neuroimaging biomarkers of Alzheimer's disease and cerebrovascular disease.

Female-specific reproductive factors and exogeneous estrogen use are associated with cognition in later life. However, the underlying mechanisms are not understood. The present study aimed to investigate the effect of reproductive factors on neuroimaging biomarkers of Alzheimer's disease (AD) and cerebrovascular pathologies. We evaluated 389 females (median age of 71.7 years) enrolled in the Mayo Clinic Study of Aging with reproductive history data and longitudinal magnetic resonance imaging (MRI) scans. We used linear mixed effect models to examine the associations between reproductive factors and changes in neuroimaging measures. Ever hormonal contraception (HC) use was longitudinally associated with higher fractional anisotropy across the corpus callosum, lower white matter hyperintensity (WMH) volume, and greater cortical thickness in an AD meta-region of interest (ROI). The initiation of menopausal hormone therapy (MHT)>5 years post menopause was associated with higher WMH volume. HC use and initiation of MHT>5 years post menopause were generally associated with neuroimaging biomarkers of cerebrovascular pathologies. Hormonal contraception use was associated with better brain white matter (WM) integrity. Initiation of menopausal hormone therapy>5 years post menopause was associated with worsening brain WM integrity. Hormonal contraception use was associated with greater cortical thickness. Ages at menarche and menopause and number of pregnancies were not associated with imaging measures. There were few associations between reproductive factors or exogenous estrogens and amyloid or tau PET.

Magnetic Resonance Imaging Measures to Track Atrophy Progression in Progressive Supranuclear Palsy in Clinical Trials.

Several magnetic resonance imaging (MRI) measures have been suggested as progression biomarkers in progressive supranuclear palsy (PSP), and some PSP staging systems have been recently proposed. Comparing structural MRI measures and staging systems in tracking atrophy progression in PSP and estimating the sample size to use them as endpoints in clinical trials. Progressive supranuclear palsy-Richardson's syndrome (PSP-RS) patients with one-year-follow-up longitudinal brain MRI were selected from the placebo arms of international trials (NCT03068468, NCT01110720, NCT01049399) and the DescribePSP cohort. The discovery cohort included patients from the NCT03068468 trial; the validation cohort included patients from other sources. Multisite age-matched healthy controls (HC) were included for comparison. Several MRI measures were compared: automated atlas-based volumetry (44 regions), automated planimetric measures of brainstem regions, and four previously described staging systems, applied to volumetric data. Of 508 participants, 226 PSP patients including discovery (n = 121) and validation (n = 105) cohorts, and 251 HC were included. In PSP patients, the annualized percentage change of brainstem and midbrain volume, and a combined index including midbrain, frontal lobe, and third ventricle volume change, were the progression biomarkers with the highest effect size in both cohorts (discovery: >1.6; validation cohort: >1.3). These measures required the lowest sample sizes (n < 100) to detect 30% atrophy progression, compared with other volumetric/planimetric measures and staging systems. This evidence may inform the selection of imaging endpoints to assess the treatment efficacy in reducing brain atrophy rate in PSP clinical trials, with automated atlas-based volumetry requiring smaller sample size than staging systems and planimetry to observe significant treatment effects. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Multimodal dementia identification using lifestyle and brain lesions, a machine learning approach

Dementia diagnosis often relies on expensive and invasive neuroimaging techniques that limit access to early screening. This study proposes an innovative approach for facilitating early dementia screening by estimating diffusion tensor imaging (DTI) measures using accessible lifestyle and brain imaging factors. Conventional DTI analysis, though effective, is often hindered by high costs and limited accessibility. To address this challenge, fuzzy subtractive clustering identified 14 influential variables from the Lifestyle for Brain Health and Brain Atrophy and Lesion Index frameworks, encompassing demographics, medical conditions, lifestyle factors, and structural brain markers. A multilayer perceptron (MLP) neural network was developed using these selected variables to predict fractional anisotropy (FA), a DTI metric reflecting white matter integrity and cognitive function. The MLP model achieved promising results, with a mean squared error of 0.000 878 on the test set for FA prediction, demonstrating its potential for accurate DTI estimation without costly neuroimaging techniques. The FA values in the dataset ranged from 0 to 1, with higher values indicating greater white matter integrity. Thus, a mean squared error of 0.000 878 suggests that the model’s predictions were highly accurate compared to the observed FA values. This multifactorial approach aligns with the current understanding of dementia’s complex etiology influenced by various biological, environmental, and lifestyle factors. By integrating readily available data into a predictive model, this method enables widespread, cost-effective screening for early dementia risk assessment. The proposed accessible screening tool could facilitate timely interventions, preventive strategies, and efficient resource allocation in public health programs, ultimately improving patient outcomes and caregiver burden.

Loss of white matter integrity mediates the association between cortical cerebral microinfarcts and cognitive dysfunction: A longitudinal study

Cortical cerebral microinfarcts (CMIs) are associated with loss of white matter (WM) integrity and cognitive impairment in cross-sectional studies, while further investigation using longitudinal datasets is required. This study aims to establish the association between cortical CMIs and WM integrity assessed by diffusion-tensor imaging (DTI) measures and to investigate whether DTI measures mediate the relationship between cortical CMIs and cognitive decline. Cortical CMIs were graded on 3T MRI. DTI measures were derived from histogram analysis of mean diffusivity (MD) and fractional anisotropy (FA). Cognitive function was assessed using a neuropsychological test battery. Linear mixed-effect models were employed to examine associations of cortical CMIs with longitudinal changes in DTI measures and cognitive function. Final analysis included 231 patients (71.14 ± 7.60 years). Presence of cortical CMIs at baseline was associated with longitudinal changes in MD median and peak height and FA median and peak height, as well as global cognition (β = −0.50, 95%CI: −0.91, −0.09) and executive function (β = −0.77, 95%CI: −1.25, −0.28). MD median mediated the cross-sectional association between cortical CMIs and global cognition. Further studies are required to investigate whether cortical CMIs and loss of WM integrity are causally related or if they are parallel mechanisms that contribute to cognitive decline.

Fuzzy Contrast Enhancement Techniques Using Rule-Based System and Intensification Operator

Contrast enhancement is a crucial step in digital image processing to ensure the production of high-quality images. This paper presents two distinct fuzzy techniques designed to address the nuanced concept of contrast. that utilize rule-based system and intensification operator, respectively, to handle the inherent vagueness associated with the concept of contrast. The fuzzy rule-based system calculates the intensity value of the output image based on the contrast measure (standard deviation) of the input image, thereby enabling effective contrast enhancement for low contrast images. Meanwhile, the fuzzy intensification operator aims to accentuate the differences in intensity levels within the image, thereby enhancing the contrast between various features and details. The experimental results show better image contrast is obtained using both methods. However, fuzzy rule-based approach shows more images with better quality compared to the intensification operator approach. The performance of these techniques is evaluated both visually and quantitatively.

P.023 Review of imaging changes, cognitive decline, and dementia risk in cancer survivors after chemotherapy

Background: Cancer survival rates in Canada have been improving, leading to a steady increase in the number of survivors entering the typical ages of dementia onset. Yet, some cancer treatments (e.g. chemotherapy) are neurotoxic and adversely affect normal brain functioning. We conducted a review to examine changes observed in brain imaging and cognitive measures in survivorship, and long-term risk of dementia among cancer survivors. Methods: 91 Primary studies were selected from PubMed. Inclusion criteria were studies investigating the changes in brain imaging, cognition, and future dementia risk among adult survivors who received chemotherapy. Study quality was assessed based on 1) prospective, controlled design, 2) sample size, and 3) validated imaging and cognitive metrics. Results: Imaging studies identified MRI-based structural grey and white matter changes and functional network changes among survivors. Cognitive studies reported heterogeneous impairments in attention, memory, and executive function. In studies that examined dementia risk among cancer survivors, 67% reported lower risk of dementia, while 33% reported no association or a higher risk. Conclusions: While short-term cognitive impairment with associated changes on brain imaging is widely reported, findings concerning future or long-term cognitive impairment are mixed. Studies are warranted to identify potential connections between short-term and long-term cognitive function after cancer treatment.

Thinking of food: The mental representation of healthy foods as unprepared

We find that people implicitly and explicitly represent healthy foods they categorize as healthy in their purest, least prepared forms but represent foods they categorize as unhealthy in their most prepared forms (e.g., a veggie patty is represented as frozen while a beef burger is represented in a bun with melted cheese and ready to eat). We find this effect across several studies using both image and word sorting measures in explicit tasks and implicit association tasks. The effect results from the perception of health and taste as two conflicting goals. Preparation (e.g., cooking, adding toppings) makes food more delicious, which creates categorization ambiguity. Hence, healthy food is thought of as unprepared. Indeed, individual differences in perceived health-taste goal conflict moderate the effect. Critically, the representation of healthy foods matters for food decisions. In an experiment that manipulated the descriptive language on a restaurant menu, emphasizing the preparation of foods increased participants’ preference for healthy foods (with no improvement for unhealthy foods).

Longitudinal myelin content measures of slowly expanding lesions using 7T MRI in multiple sclerosis.

Slowly expanding lesions (SELs) are thought to represent a subset of chronic active lesions and have been associated with clinical disability, severity, and disease progression. The purpose of this study was to characterize SELs using advanced magnetic resonance imaging (MRI) measures related to myelin and neurite density on 7Tesla (T) MRI. The study design was retrospective, longitudinal, observational cohort with multiple sclerosis (n=15). Magnetom 7T scanner was used to acquire magnetization-prepared 2 rapid acquisition gradient echo and advanced MRI including visualization of short transverse relaxation time component (ViSTa) for myelin, quantitative magnetization transfer (qMT) for myelin, and neurite orientation dispersion density imaging (NODDI). SELs were defined as lesions showing ≥12% of growth over 12months on serial MRI. Comparisons of quantitative measures in SELs and non-SELs were performed at baseline and over time. Statistical analyses included two-sample t-test, analysis of variance, and mixed-effects linear model for MRI metrics between lesion types. A total of 1075 lesions were evaluated. Two hundred twenty-four lesions (21%) were SELs, and 216 (96%) of the SELs were black holes. At baseline, compared to non-SELs, SELs showed significantly lower ViSTa (1.38vs. 1.53, p<.001) and qMT (2.47vs. 2.97, p<.001) but not in NODDI measures (p>.27). Longitudinally, only ViSTa showed a greater loss when comparing SEL and non-SEL (p=.03). SELs have a lower myelin content relative to non-SELs without a difference in neurite measures. SELs showed a longitudinal decrease in apparent myelin water fraction reflecting greater tissue injury.

Investigating nutrient biomarkers of healthy brain aging: a multimodal brain imaging study

The emerging field of Nutritional Cognitive Neuroscience aims to uncover specific foods and nutrients that promote healthy brain aging. Central to this effort is the discovery of nutrient profiles that can be targeted in nutritional interventions designed to promote brain health with respect to multimodal neuroimaging measures of brain structure, function, and metabolism. The present study therefore conducted one of the largest and most comprehensive nutrient biomarker studies examining multimodal neuroimaging measures of brain health within a sample of 100 older adults. To assess brain health, a comprehensive battery of well-established cognitive and brain imaging measures was administered, along with 13 blood-based biomarkers of diet and nutrition. The findings of this study revealed distinct patterns of aging, categorized into two phenotypes of brain health based on hierarchical clustering. One phenotype demonstrated an accelerated rate of aging, while the other exhibited slower-than-expected aging. A t-test analysis of dietary biomarkers that distinguished these phenotypes revealed a nutrient profile with higher concentrations of specific fatty acids, antioxidants, and vitamins. Study participants with this nutrient profile demonstrated better cognitive scores and delayed brain aging, as determined by a t-test of the means. Notably, participant characteristics such as demographics, fitness levels, and anthropometrics did not account for the observed differences in brain aging. Therefore, the nutrient pattern identified by the present study motivates the design of neuroscience-guided dietary interventions to promote healthy brain aging.