Volumetric Measures Research Articles

The association between white matter tract structural connectivity and information processing speed in relapsing-remitting multiple sclerosis

BackgroundInformation processing speed (IPS) deterioration is common in relapsing-remitting multiple sclerosis (RRMS) patients [1] and might severely affect quality of life and occupational activity. However, understanding of its neural substrate is not fully elucidated. We aimed to investigate the associations between MRI-derived metrics of neuroanatomical structures, including the tracts, and IPS.MethodsSymbol Digit Modalities Test (SDMT), Paced Auditory Serial Addition Test (PASAT), and Color Trails Test (CTT) were used to evaluate IPS in 73 RRMS consecutive patients, all undergoing only interferon beta (IFN-β) therapy during the study. At the same time, 1.5T MRI including diffusion tensor imaging (DTI) data was acquired for each recruited subject. We analyzed volumetric and diffusion MRI measures (FreeSurfer 6.0) including normalized brain volume (NBV), cortical thickness (thk), white matter hypointensities (WMH), volume (vol), diffusion parameters: mean (MD), radial (RD), axial (AD) diffusivities, and fractional anisotropy (FA) of 18 major white-matter (WM) tracts. Multiple linear regression model with interaction resulted in distinguishing the neural substrate of IPS deficit in the IPS impaired subgroup of patients.ResultsThe most significant tract abnormalities contributing to IPS deficit were right inferior longitudinal fasciculus (R ILF) FA, forceps major (FMAJ) FA, forceps minor (FMIN) FA, R uncinate fasciculus (UNC) AD, R corticospinal tract (CST) FA, and left superior longitudinal fasciculus FA (L SLFT). Among volumetric MRI metrics, IPS deficit was associated with L and R thalamic vol. and cortical thickness of insular regions.ConclusionIn this study, we showed that disconnection of the selected WM tracts, in addition to cortical and deep gray matter (GM) atrophy, might underlie IPS deficit in RRMS patients but more extensive studies are needed for precise associations.

Gray Matter Microstructure Alterations in People with Multiple Sclerosis Based on Cell Body and Neurite Density Imaging (P10-3.007)

<h3>Objective:</h3> To evaluate a novel compartment-based model for apparent cell body and neurite density imaging (SANDI) in gray matter (GM) in people with multiple sclerosis (MS) compared to healthy controls (HC) and its correlation with brain atrophy. <h3>Background:</h3> MS features focal cortical lesions and microstructural changes in normal-appearing GM, which can impact clinical function and disability. High gradient diffusion MRI has potential to optimize GM tissue microstructure characterization by overcoming challenges due to the complexity of underlying components. <h3>Design/Methods:</h3> 41 people with MS and 37 age- and sex-matched HC were scanned on a 3T Connectom MRI scanner equipped with 300mT/m gradients using a multi-shell acquisition protocol consisting of eight b-values at 19msec diffusion time. Microstructural metrics of SANDI, including a measure of soma density (f_soma) in the cortex and deep GM, were compared between MS and HC and correlated with cortical and thalamic atrophy, correcting for multiple comparisons. <h3>Results:</h3> Cortical cell body signal fraction (f_soma) was decreased in MS compared to HC (0.56 vs. 0.58, <i>p</i>=0.027, not surviving FDR-correction). In deep GM, f_soma and extra-cellular signal fraction were significantly decreased in MS compared to HC (<i>FDR-p</i>=0.045 in both), which was most pronounced in progressive MS. Based on spatial analysis, f_soma of caudate nucleus and thalamus were significantly decreased in MS compared to HC (<i>FDR-p</i>=0.003 and <i>FDR-p</i>=0.027, respectively). Whereas cortical atrophy in MS was poorly correlated with cortical f_soma, thalamic atrophy in MS demonstrated moderate correlation with decreased thalamic f_soma (r=0.311, <i>p</i>=0.054) and decreased cortical f_soma (r=0.474, <i>p</i>=0.008). <h3>Conclusions:</h3> SANDI metrics, in particular f_soma, provide detailed GM characterization beyond cortical and thalamic volumes and are able to characterize MS-related microstructural pathology. Decreased cortical cell density correlates with declining thalamic volume and may precede volumetric measures of cortical atrophy in people with MS. <b>Disclosure:</b> Ms. Krijnen has nothing to disclose. Andrew Russo has nothing to disclose. Dr. Salim Karam has nothing to disclose. The institution of Menno M Schoonheim has received research support from Dutch MS Research Foundation. The institution of Menno M Schoonheim has received research support from Eurostars-EUREKA. The institution of Menno M Schoonheim has received research support from ARSEP. The institution of Menno M Schoonheim has received research support from Amsterdam Neuroscience. The institution of Menno M Schoonheim has received research support from MAGNIMS. The institution of Menno M Schoonheim has received research support from ZonMW. The institution of Menno M Schoonheim has received research support from Atara Biotherapeutics. The institution of Menno M Schoonheim has received research support from Biogen. The institution of Menno M Schoonheim has received research support from Celgene/Bristol Meyers Squibb. The institution of Menno M Schoonheim has received research support from Genzyme. The institution of Menno M Schoonheim has received research support from MedDay. The institution of Menno M Schoonheim has received research support from Merck. Dr. Huang has received personal compensation in the range of $0-$499 for serving as a Consultant for Siemens Healthineers. The institution of Dr. Huang has received research support from Siemens Healthineers. The institution of Dr. Huang has received research support from Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School. Dr. Klawiter has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Galen/Atlantica. Dr. Klawiter has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Genentech. Dr. Klawiter has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Banner Life Sciences. Dr. Klawiter has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Greenwich Biosciences. Dr. Klawiter has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for OM1. Dr. Klawiter has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for TG Therapeutics. The institution of Dr. Klawiter has received research support from Biogen. The institution of Dr. Klawiter has received research support from Abbvie. The institution of Dr. Klawiter has received research support from Genentech.

Comparing machine learning-derived MRI-based and blood-based neurodegeneration biomarkers in predicting syndromal conversion in early AD.

We compared the machine learning-derived, MRI-based Alzheimer's disease (AD) resemblance atrophy index (AD-RAI) with plasma neurofilament light chain (NfL) level in predicting conversion of early AD among cognitively unimpaired (CU) and mild cognitive impairment (MCI) subjects. We recruited participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) who had the following data: clinical features (age, gender, education, Montreal Cognitive Assessment [MoCA]), structural MRI, plasma biomarkers (p-tau181 , NfL), cerebrospinal fluid biomarkers (CSF) (Aβ42, p-tau181 ), and apolipoprotein E (APOE) ε4 genotype. We defined AD using CSF Aβ42 (A+) and p-tau181 (T+). We defined conversion (C+) if a subject progressed to the next syndromal stage within 4 years. Of 589 participants, 96 (16.3%) were A+T+C+. AD-RAI performed better than plasma NfL when added on top of clinical features, plasma p-tau181 , and APOE ε4 genotype (area under the curve [AUC]=0.832 vs. AUC=0.650 among CU, AUC=0.853 vs. AUC=0.805 among MCI) in predicting A+T+C+. AD-RAI outperformed plasma NfL in predicting syndromal conversion of early AD. AD-RAI outperformed plasma NfL in predicting syndromal conversion among early AD. AD-RAI showed better metrics than volumetric hippocampal measures in predicting syndromal conversion. Combining clinical features, plasma p-tau181 and apolipoprotein E (APOE) with AD-RAI is the best model for predicting syndromal conversion.

Deep learning prediction of motor performance in stroke individuals using neuroimaging data

The degree of motor impairment and profile of recovery after stroke are difficult to predict for each individual. Measures obtained from clinical assessments, as well as neurophysiological and neuroimaging techniques have been used as potential biomarkers of motor recovery, with limited accuracy up to date. To address this, the present study aimed to develop a deep learning model based on structural brain images obtained from stroke participants and healthy volunteers. The following inputs were used in a multi-channel 3D convolutional neural network (CNN) model: fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity maps obtained from Diffusion Tensor Imaging (DTI) images, white and gray matter intensity values obtained from Magnetic Resonance Imaging, as well as demographic data (e.g., age, gender). Upper limb motor function was classified into “Poor” and “Good” categories. To assess the performance of the DL model, we compared it to more standard machine learning (ML) classifiers including k-nearest neighbor, support vector machines (SVM), Decision Trees, Random Forests, Ada Boosting, and Naïve Bayes, whereby the inputs of these classifiers were the features taken from the fully connected layer of the CNN model. The highest accuracy and area under the curve values were 0.92 and 0.92 for the 3D-CNN and 0.91 and 0.91 for the SVM, respectively. The multi-channel 3D-CNN with residual blocks and SVM supported by DL was more accurate than traditional ML methods to classify upper limb motor impairment in the stroke population. These results suggest that combining volumetric DTI maps and measures of white and gray matter integrity can improve the prediction of the degree of motor impairment after stroke. Identifying the potential of recovery early on after a stroke could promote the allocation of resources to optimize the functional independence of these individuals and their quality of life.

Evaluation of transorbital sonography measures of optic nerve diameter in the context of global and regional brain volume in multiple sclerosis

Transorbital sonography (TOS) could be a swift and convenient method to detect the atrophy of the optic nerve, possibly providing a marker that might reflect other quantitative structural markers of multiple sclerosis (MS). Here we evaluate the utility of TOS as a complementary tool for assessing optic nerve atrophy, and investigate how TOS-derived measures correspond to volumetric brain markers in MS. We recruited 25 healthy controls (HC) and 45 patients with relapsing–remitting MS and performed B-mode ultrasonographic examination of the optic nerve. Patients additionally underwent MRI scans to obtain T1-weighted, FLAIR and STIR images. Optic nerve diameters (OND) were compared between HC, MS patients with and without history of optic neuritis (non-ON) using a mixed-effects ANOVA model. The relationship between within-subject-average OND and global and regional brain volumetric measures was investigated using FSL SIENAX, voxel-based morphometry and FSL FIRST. OND was significantly different between HC-MS (HC = 3.2 ± 0.4 mm, MS = 3 ± 0.4 mm; p < 0.019) and we found significant correlation between average OND and normalised whole brain (β = 0.42, p < 0.005), grey matter (β = 0.33, p < 0.035), white matter (β = 0.38, p < 0.012) and ventricular cerebrospinal fluid volume (β = − 0.36, p < 0.021) in the MS group. History of ON had no impact on the association between OND and volumetric data. In conclusion, OND is a promising surrogate marker in MS, that can be simply and reliably measured using TOS, and its derived measures correspond to brain volumetric measures. It should be further explored in larger and longitudinal studies.

Abstract 4173: Lipidome of mammographic breast density in premenopausal women

Abstract Introduction: High mammographic breast density (MBD) is a strong risk factor for breast cancer, but the biological mechanisms underlying high MBD are not well understood. We, therefore, comprehensively investigated for the first time the associations of lipid species with volumetric measures of MBD to elucidate potential biological mechanisms of high MBD in premenopausal women. Methods: We performed lipidomic profiling on 705 premenopausal women recruited during their annual screening mammogram at Washington University School of Medicine, St. Louis, MO. Lipidomic profiling for 982 lipid species was completed at Metabolon (Durham, NC®). Lipid species with greater than 300 missing values (N=125) were excluded from the analysis. Using nearest neighbor methods, we imputed the lipid species missing less than 300 values. We used Volpara 1.5 (Volpara Health®) to quantify volumetric measures of MBD - volumetric percent density (VPD), dense volume (DV), and non-dense volume (NDV). We investigated the associations of the lipid species with MBD measures using multivariable linear regression models adjusting for age, age at menarche, body shape at age 10, race/ethnicity, body fat %, family history of breast cancer, oral contraceptive use, parity/age at first birth, and alcohol use. MBD measures were log10-transformed, and lipid species were standardized. Linear coefficients were back-transformed to the original scale and considered significant if the Bonferroni corrected p&amp;lt;0.05. Results: In multivariable linear regression models, 34 lipid species were inversely associated with VPD. The lipid species belong to the triacylglycerol (TAG, N=26), diacylglycerol (DAG, N=6), phosphatidylcholine (PC, N=1), and cholesterol ester (N=1) pathways. DAG(16:0/18:2) and TAG54:6-FA20:4 displayed the largest inverse associations with one standard deviation increase in DAG(16:0/18:2), and TAG54:6-FA20:4 corresponding to 9.9% (p=0.002), and 9.6% (p=0.007) decrease in VPD, respectively. Eleven lipid species were significantly associated with NDV, with 10 species (all TAG) having a positive association and 1 inverse association PC(18:1/18:1). The strongest positive association was observed with TAG54:6-FA20:4. One standard deviation increase in TAG54:6-FA20:4 was associated with a 9.8% increase in NDV (p=0.01). Several of the lipid species (N=8, 23.5%) that were associated with VPD were also associated with NDV, but in opposite directions. No lipid species were significantly associated with DV. Conclusions: Our study identified many lipid species, especially in TAG and DAG pathways, that were associated with VPD and NDV and offer new insights into the biological mechanisms underlying high MBD in premenopausal women. Future studies are needed to validate our results and the translational potential. Citation Format: Kayla R. Getz, Myung S. Jeon, Chongliang Luo, Jingqin Luo, Adetunji T. Toriola. Lipidome of mammographic breast density in premenopausal women. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4173.

The FEDRA Longitudinal Study: Repeated Volumetric Breast Density Measures and Breast Cancer Risk

Mammographic breast density (MBD) is a strong independent risk factor for breast cancer (BC). We investigated the association between volumetric MBD measures, their changes over time, and BC risk in a cohort of women participating in the FEDRA (Florence-EPIC Digital mammographic density and breast cancer Risk Assessment) study. The study was carried out among 6148 women with repeated MBD measures from full-field digital mammograms and repeated information on lifestyle habits, reproductive history, and anthropometry. The association between MBD measures (modeled as time-dependent covariates), their relative annual changes, and BC risk were evaluated by adjusted Cox models. During an average of 7.8 years of follow-up, 262 BC cases were identified. BC risk was directly associated with standard deviation increments of volumetric percent density (VPD, HR 1.37, 95%CI 1.22-1.54) and dense volume (DV, HR 1.29, 95%CI 1.18-1.41). An inverse association emerged with non-dense volume (NDV, HR 0.82, 95%CI 0.69-0.98). No significant associations emerged between annual changes in VPD, DV, NDV, and BC risk. Higher values of MBD measures, modeled as time-dependent covariates, were positively associated with increased BC risk, while an inverse association was evident for increasing NDV. No effect of annual changes in MBD emerged.

Behavioral variant frontotemporal dementia in patients with primary psychiatric disorder: A magnetic resonance imaging study.

The clinical diagnosis of behavioral variant frontotemporal dementia (bvFTD) in patients with a history of primary psychiatric disorder (PPD) is challenging. PPD shows the typical cognitive impairments observed in patients with bvFTD. Therefore, the correct identification of bvFTD onset in patients with a lifetime history of PPD is pivotal for an optimal management. Twenty-nine patients with PPD were included in this study. After clinical and neuropsychological evaluations, 16 patients with PPD were clinically classified as bvFTD (PPD-bvFTD+), while in 13 cases clinical symptoms were associated with the typical course of the psychiatric disorder itself (PPD-bvFTD-). Voxel- and surface-based investigations were used to characterize gray matter changes. Volumetric and cortical thickness measures were used to predict the clinical diagnosis at a single-subject level using a support vector machine (SVM) classification framework. Finally, we compared classification performances of magnetic resonance imaging (MRI) data with automatic visual rating scale of frontal and temporal atrophy. PPD-bvFTD+ showed a gray matter decrease in thalamus, hippocampus, temporal pole, lingual, occipital, and superior frontal gyri compared to PPD-bvFTD- (p<.05, family-wise error-corrected). SVM classifier showed a discrimination accuracy of 86.2% in differentiating PPD patients with bvFTD from those without bvFTD. Our study highlights the utility of machine learning applied to structural MRI data to support the clinician in the diagnosis of bvFTD in patients with a history of PPD. Gray matter atrophy in temporal, frontal, and occipital brain regions may represent a useful hallmark for a correct identification of dementia in PPD at a single-subject level.

Association of volumetric MRI measures and disability in MS patients of the same age: Descriptions from a birth year cohort.

Although MRI-based markers of neuroinflammation have proven crucial for the diagnosis of multiple sclerosis (MS), predicting clinical progression with inflammation remains difficult. Neurodegenerative markers such as brain volume loss show stronger clinical (predictive) correlations, but also harbor age-related variation that must be disentangled from disease duration. In this study we investigated how clinical disability is related to volumetric MRI measures in a cohort of MS patients and healthy controls (HC) of the same age: Project Y. This study included 234 MS patients born in 1966 and 112 HC born between 1965 and 1967 in the Netherlands. Disability was quantified using the expanded disability status scale (EDSS), nine hole peg test (9HPT), and timed 25 foot walking test (T25FWT). Volumes were quantified on 3T MRI as normalized whole brain (NBV) and regional gray matter (GM) volumes using the same scanner and MRI protocol: cortical (normalized cortical gray matter volume; NCGMV), deep (NDGMV), thalamic (NThalV), and cerebellar (NCbV) GM volumes. In addition, mean upper cervical cord area (MUCCA), white matter lesion volume (LV), and spinal cord lesions were assessed. These measures were compared between patients and HC, and related to disability measures using linear regression. Mean age of people with MS (PwMS) was 52.8 years (SD 0.9) and median disease duration 15.8 years (IQR 8.7-24.8). All global and regional brain measures were lower in MS patients compared to HC. Univariate regression models showed that NDGMV (β=-0.20) and MUCCA (β=-0.38) were most strongly related to the EDSS in all PwMS. After subtype stratification, MUCCA was most strongly related to the EDSS (β=-0.60) and 9HPT (β=-0.55) in secondary progressive PwMS. Multivariate regression models demonstrated that in all PwMS, the EDSS was best explained by lower MUCCA, longer disease durations and a progressive disease course (adjusted-R (Sastre-Garrigaetal., 2017)=0.26, p < 0.001). MUCCA was a consistent correlate in separate models of the EDSS for all PwMS, relapsing and progressive onset PwMS. The 9HPT (adjusted-R (Sastre-Garrigaetal., 2017)=0.20, p < 0.001) was best explained by lower MUCCA, higher LV and pack years, while lower limb disability (adjusted-R (Sastre-Garrigaetal., 2017)=0.11, p < 0.001) was best explained by lower MUCCA, progressive onset MS and female sex. Our results indicate that in a cohort unbiased by age differences, spinal cord and deep gray matter volumes best related to physical disability. Our results support the use of these measures in clinical practice and trials.

Abstract P211: Associations of the Mediterranean and MIND Diets With Brain Volume in the Boston Puerto Rican Health Study

Objectives: Although few studies are available, some evidence suggests that greater adherence to the MeD (Mediterranean Diet) and MIND (Mediterranean-Dietary Approaches to Reduce Hypertension Intervention for Neurocognitive Delay) dietary patterns may benefit cognitive function among Hispanic/Latino adults. Greater regional and total brain volumetric measures are associated with an increased risk of dementia, but whether the MeD and MIND dietary patterns relate to brain volume among Hispanic/Latino adults remains unclear. The objective of the current study was to quantify the associations of these dietary patterns with brain volume among Hispanic/Latino adults. Methods: Data are from the Boston Puerto Rican Health Study, which recruited 1500 older Puerto Rican adults residing in the Boston Metro Area. Approximately 13 years from baseline, a subsample of participants (n=240) were invited to a follow-up visit where brain scans were conducted using a 3T MRI scanner. Diet was estimated using the mean intake from a validated food frequency questionnaire administered at baseline, ~2, and ~6 years. The MeD score has 6 adequacy and 3 moderation components, whereas MIND has 10 and 5 components, respectively. Component scores were summed to get a total dietary score, where a higher value indicates greater adherence to the pattern. Total scores range from 0-9 for MeD and 0-15 for MIND. Outcomes included hippocampal, amygdalar, and total gray matter volumes. The residual method was used to adjust brain volumes for differences in intracranial volume and values were z score transformed prior to analyses. Multiple linear regression models were adjusted for age, sex, total energy, the time between the baseline and 13-year visits, education, physical activity, BMI, and smoking status. After exclusions for missing data, the sample size was n=225. Results: The mean age of the participants was 55±7 years and was primarily female [79%, (178 of 225)]. On average, the time between the baseline and MRI visits was 12.8±1.1 years. Higher MeD score was significantly associated with greater hippocampal [β (95% CI), 0.19 (0.053, 0.32), amygdalar [0.16 (0.03, 0.29)], and total grey matter volumes [0.14 (0.01, 0.26)] ( P &lt;0.05 for all). Similarly, positive associations were observed between the MIND score and hippocampal [0.18 (0.05, 0.31), amygdalar [0.14 (0.01, 0.27)], and total grey matter volumes [0.14 (0.01, 0.27)] ( P &lt;0.05 for all). Conclusion: Our findings suggest that the observed beneficial associations of the MeD and MIND dietary patterns with cognitive function among Hispanic/Latino adults, may in part be through impacts on regional and total brain volume. These results provide evidence that can inform tailored dietary recommendations and interventions targeting brain health among older Puerto Rican adults. Funding Sources: This study was supported by NIH grants R01AG055948, P50 HL105185, and P01 AG023394.

MRI Volumetric Analysis of the Hypothalamus and Limbic System across the Pediatric Age Span

Literature is scarce regarding volumetric measures of limbic system components across the pediatric age range. The purpose of this study is to remedy this scarcity by reporting continuous volumetric measurements of limbic system components, and to provide consistent stratification data including age-related trajectories and sex-related differences in the pediatric age range in order to improve the recognition of structural variations that might reflect pathology. In this retrospective study, MRI sequences of children with normal clinical MRI examinations of the brain acquired between January 2010 and December 2019 were included. Isotropic 3D T1-weighted were processed using FreeSurfer version 7.3. Total brain volume and volumes of the limbic system including the hippocampus, parahippocampal gyrus, amygdala, hypothalamus, cingulate gyrus, entorhinal cortex, anteroventral thalamic nucleus, and whole thalamus were assessed. Parcellated output was displayed with the respective label map overlay and images were visually inspected for accuracy of regional segmentation results. Continuous data are provided as mean and standard deviation with quadratic trendlines and as mean and 95% confidence intervals. Categorical data are presented as integers and percentages (%). A total of 724 children (401 female, 55.4%), with a mean age at time of MRI of 10.9 ± 4.2 years (range: 1.9-18.2 years), were included in the study. For females, the total brain volume increased from 955 ± 70 mL at the age of 2-3 years to 1140 ± 110 mL at the age of 17-18 years. Similarly, the total brain volume increased for males from 1004 ± 83 mL to 1263 ± 96 mL. The maximum volume was noted at 11-12 years for females (1188 ± 90 mL) and at 14-15 years for males (1310 ± 159 mL). Limbic system structures reached their peak volume more commonly between the 13-14 years to 17-18 years age groups. The male cingulate gyrus, entorhinal cortex, and anteroventral thalamic nucleus reached peak volume before or at 9-10 years. This study provides unique age- and sex-specific volumes of the components of the limbic system throughout the pediatric age range to serve as normal values in comparative studies. Quantification of volumetric abnormalities of the limbic system on brain MRI may offer insights into phenotypical variations of diseases and may help elucidate new pathological phenotypes.

Normalized Echocardiographic Values From Guideline-Directed Dedicated Views for Cardiac Dimensions and Left Ventricular Function

BackgroundContinuous technologic development and updated recommendations for image acquisitions creates a need to update the current normal reference ranges for echocardiography. The best method of indexing cardiac volumes is unknown. ObjectivesThe authors used 2- and 3-dimensional echocardiographic data from a large cohort of healthy individuals to provide updated normal reference data for dimensions and volumes of the cardiac chambers as well as central Doppler measurements. MethodsIn the fourth wave of the HUNT (Trøndelag Health) study in Norway 2,462 individuals underwent comprehensive echocardiography. Of these, 1,412 (55.8% women) were classified as normal and formed the basis for updated normal reference ranges. Volumetric measures were indexed to body surface area and height in powers of 1 to 3. ResultsNormal reference data for echocardiographic dimensions, volumes, and Doppler measurements were presented according to sex and age. Left ventricular ejection fraction had lower normal limits of 50.8% for women and 49.6% for men. According to sex-specific age groups, the upper normal limits for left atrial end-systolic volume indexed to body surface area ranged from 44 mL/m2 to 53 mL/m2, and the corresponding upper normal limit for right ventricular basal dimension ranged from 43 mm to 53 mm. Indexing to height raised to the power of 3 accounted for more of the variation between sexes than indexing to body surface area. ConclusionsThe authors present updated normal reference values for a wide range of echocardiographic measures of both left- and right-side ventricular and atrial size and function from a large healthy population with a wide age-span. The higher upper normal limits for left atrial volume and right ventricular dimension highlight the importance of updating reference ranges accordingly following refinement of echocardiographic methods.

Counting on random number generation: Uncovering mild executive dysfunction in congenital heart disease

Congenital heart disease (CHD) is associated with various neurocognitive deficits, particularly targeting executive functions (EFs), of which random number generation (RNG) is one indicator. RNG has, however, never been investigated in CHD. We administered the Mental Dice Task (MDT) to 67 young adults with CHD and 55 healthy controls. This 1-minute-task requires the generation of numbers 1 to 6 in a random sequence. RNG performance was correlated with a global EF score. Participants underwent MRI to examine structural-volumetric correlates of RNG. Compared to controls, CHD patients showed increased backward counting, reflecting deficient inhibition of automatized behavior. They also lacked a small-number bias (higher frequency of small relative to large numbers). RNG performance was associated with global EF scores in both groups. In CHD patients, MRI revealed an inverse association of counting bias with most of the volumetric measurements and the amount of small numbers was positively associated with corpus callosum volume, suggesting callosal involvement in the “pseudoneglect in number space”.In conclusion, we found an impaired RNG performance in CHD patients, which is associated with brain volumetric measures. RNG, reportedly resistant to learning effects, may be an ideal task for the longitudinal assessment of EFs in patients with CHD.

The effect of musicality on language recovery after awake glioma surgery.

Awake craniotomy is increasingly used to resect intrinsic brain tumors while preserving language. The level of musical training might affect the speed and extend of postoperative language recovery, as increased white matter connectivity in the corpus callosum is described in musicians compared to non-musicians. In this cohort study, we included adult patients undergoing treatment for glioma with an awake resection procedure at two neurosurgical centers and assessed language preoperatively (T1) and postoperatively at three months (T2) and one year (T3) with the Diagnostic Instrument for Mild Aphasia (DIMA), transferred to z-scores. Moreover, patients' musicality was divided into three groups based on the Musical Expertise Criterion (MEC) and automated volumetric measures of the corpus callosum were conducted. We enrolled forty-six patients, between June 2015 and September 2021, and divided in: group A (non-musicians, n = 19, 41.3%), group B (amateur musicians, n = 17, 36.9%) and group C (trained musicians, n = 10, 21.7%). No significant differences on postoperative language course between the three musicality groups were observed in the main analyses. However, a trend towards less deterioration of language (mean/SD z-scores) was observed within the first three months on the phonological domain (A: -0.425/0.951 vs. B: -0.00100/1.14 vs. C: 0.0289/0.566, p-value = 0.19) with a significant effect between non-musicians vs. instrumentalists (A: -0.425/0.951 vs. B + C: 0.201/0.699, p = 0.04). Moreover, a non-significant trend towards a larger volume (mean/SD cm3) of the corpus callosum was observed between the three musicality groups (A: 6.67/1.35 vs. B: 7.09/1.07 vs. C: 8.30/2.30, p = 0.13), with the largest difference of size in the anterior corpus callosum in non-musicians compared to trained musicians (A: 3.28/0.621 vs. C: 4.90/1.41, p = 0.02). With first study on this topic, we support that musicality contributes to language recovery after awake glioma surgery, possibly attributed to a higher white matter connectivity at the anterior part of the corpus callosum. Our conclusion should be handled with caution and interpreted as hypothesis generating only, as most of our results were not significant. Future studies with larger sample sizes are needed to confirm our hypothesis.

Aerobic exercise is associated with region-specific changes in volumetric, tensor-based, and fixel-based measures of white matter integrity in healthy older adults

White matter integrity and cognition have been found to decline with advancing adult age. Aerobic exercise may be effective in counteracting these declines. Generally, white matter integrity has been quantified using a volumetric measure (WMV) and with tensor-based parameters, such as fractional anisotropy (FA) and mean diffusivity (MD), the validity of which appears to be compromised in the presence of crossing fibers. Fixel-based analysis techniques claim to overcome this problem by yielding estimates of fiber density (FD), cross-section (FC), and their product (FDC) in multiple directions per voxel. In a sample of 61 healthy older adults (63–76 years old), we quantified changes in white matter integrity following an aerobic exercise intervention with the commonly used volumetric and tensor-based metrics (WMV, FA, MD) and with fixel-based metrics (FD, FC, FDC). We investigated the associations of changes in these white matter parameters with changes in cardiovascular fitness and Digit Symbol Substitution task (DSST) performance, a marker of perceptual speed. In line with previous findings, we observed maintained WMV in the corpus callosum of exercisers, and positive change-change correlations between WMV and fitness, and between WMV and perceptual speed. For FA and MD, group differences in change opposite to those hypothesized were found in the corpus callosum, posterior corona radiata, and superior longitudinal fasciculus at an uncorrected significance threshold. Likewise, regions in superficial WM in the prefrontal cortex showed group differences in FD and FDC change, uncorrected, with more positive change in controls and more negative change in exercisers. Finally, changes in FD and FDC were found to be inversely correlated to changes in fitness and DSST performance. The present results corroborate previous findings of WMV changes, but cast doubt on current physiological interpretations of both tensor-based and fixel-based indicators of white matter properties in the context of exercise intervention studies.

Abstract P022: Quantitative measures of breast density and breast cancer risk prediction among black women in a screening population

Abstract Background: Although mammographic density (MD) is a strong predictor of invasive breast cancer, it has been shown to increase the discriminatory ability of existing risk prediction models only slightly. Breast density is assessed visually by radiologists according to the Breast Imaging Reporting and Data System (BI-RADS) criteria, which has been shown to lack reproducibility. Additionally, the racial diversity of women included in the previous studies was limited. Quantitative measures of breast density have been developed that automatically measure density directly from images. Our prior work found that Black women had lower BI-RADS breast density, despite having a greater quantity of dense breast tissue on average compared with white women when quantitative measures were used. The study purpose was to determine if adding quantitative breast density measures improved breast cancer risk prediction for both white and Black women compared to the Breast Cancer Risk Assessment Tool (BCRAT). Methods: A total of 16,942 women (N=6881 white, N=10061 Black) screened with full-field digital mammography (FFDM) or with a combination of FFDM and digital breast tomosynthesis (DBT) at the Hospital of the University of Pennsylvania (HUP) between September 1, 2010 to December 31, 2014 were included. Area breast density measurements including dense area and area percent density were obtained using a fully automated, validated LIBRA software. All patients were followed from the date of first screening mammogram visit until breast cancer diagnosis or end of follow up on December 31, 2019. We used the BCRA R package (v2.1) for the BCRAT (https://dceg.cancer.gov/tools/risk-assessment/bcra) to estimate the expected 5 year absolute risk for breast cancer. We evaluated the area under the curve (AUC) and calibration (observed to expected ratio, O/E) of the following models: BCRAT alone, BCRAT + BI-RADS density, BCRAT + quantitative density measures, and BCRAT + BI-RADS density + quantitative density measures. Results: There were 123 breast cancers among white and 123 breast cancers among Black women. Adding dense area and area percent density to the BCRAT alone or BCRAT plus BI-RADS density did not improve predictive accuracy for white or Black women. AUC remained close to 0.59 for white women and 0.61 for Black women in all models, with no statistically significant differences in AUCs (DeLong Test p value = 0.09). Underprediction was worse in white women than in Black women. Under-prediction of the BCRAT was reduced when adding percent density from [O/E 1.24 vs. O/E 1.17] in white women. Calibration stayed relatively the same (O/E=1.10) for Black women even when adding both quantitative MD measures. Conclusion: Our results suggest that adding quantitative area mammographic density measurements to the BCRAT does not improves breast cancer risk prediction among Black or white women. Given the increasing use of digital breast tomosynthesis (DBT), future studies should examine whether volumetric breast density measures have superior predictive value among Black women. Citation Format: Mattia A. Mahmoud, Anne Marie McCarthy, Despina Kontos, Emily Conant, Jinbo Chen, Sarah Ehsan, Lauren Pantalone, Walter Mankowski. Quantitative measures of breast density and breast cancer risk prediction among black women in a screening population. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P022.

Morphometric Sex Identification Based on Paranasal Sinus Dimensions in the Indian Population: A CBCT Based Study

Introduction: The creation of technologies using anatomical components like the maxillary sinus and frontal sinus that might preserve their stability yet after extreme events, are helpful for forensic investigations because sex determination is a crucial component of determining the profile of an individual. Aim: To determine the sex using Cone Beam Computed Tomography (CBCT) scans, in a South Indian community by measuring the frontal and maxillary sinuses. Material and Methods: The present cross-sectional study was conducted in the Department of Oral Medicine and Radiology, Sri Balaji Vidyapeeth University, IGIDS, Pondicherry, India, from 1st March 2021 to 31st March 2022. Analysis included 45 CBCT scans from 22 males and 23 females were subjected to volumetric measures in the maxillary sinus and frontal sinus. Applying NNT software, the volume measurement was carried out. The data was used to feed into a sex identification mathematical model. For evaluation, the student’s t-test has been used. Results: In the total study subjects, the mean age of males was 36.909 years and of females was 36.304 years. Only the volume of the frontal sinus varied significantly among males and females (p-value&lt;0.001). The discriminant function analysis equation showed that 50% of males and 91.3% of females correctly identified their gender. According to the crossvalidated categorisation, 71.1% of the people were accurately categorised altogether. Conclusion: Segregation identification, which was validated with evaluations in the frontal and maxillary sinuses with CBCT scans, is another technique for identifying individuals who identify as Indian. The present study shows that paranasal sinus morphologic evaluation is a useful method for identifying a person’s gender.

Use of statistical shape modeling to enhance the fluoroscopic evaluation of the bladder

IntroductionVideo urodynamic studies (VUDS) use fluoroscopic imaging to visualize the bladder and multichannel urodynamics to assess its function. Qualitative assessment of bladder shape is used to identify abnormal features (e.g., diverticula) that correspond with pathophysiology; however, this assessment is limited in its ability to predict bladder function. Therefore, we developed a novel quantitative approach to assess bladder shape obtained from fluoroscopic VUDS images utilizing statistical shape modeling. This method was compared to existing binary and continuous shape quantification methods and used to identify relationships between bladder shape and measures of bladder physiology categorized as related to sensation, incontinence, or emptying.MethodsThis was a retrospective, cross-sectional study of 49 participants. Bladder walls were segmented from fluoroscopic images at rest with the bladder filled to approximately 300 mL. Bladder shape was evaluated in three ways: 1) binary categorization as typical or atypical based on clinical assessment, 2) quantification of height-to-width ratios, and 3) quantification by statistical shape modeling. Independent t-tests and correlations were used to assess associations between the three shape evaluation methods and to define relationships between shape and physiologic measures: 3 volumetric measures describing sensation, 2 dichotomous variables addressing incontinence, and 1 volumetric measure representing emptying.ResultsThe statistical shape model generated 5 modes of variation. Mode 1 corresponded with height-to-width ratio (r=0.920, p&amp;lt;0.001), modes 2 and 3 with diagonal height-to-width ratio (r=0.66 and -0.585, p&amp;lt;0.001 and &amp;lt;0.001), and mode 3 with binary shape categorization (p&amp;lt;0.001). In terms of function, those with atypical bladder shape had impaired emptying (p=0.010), modes 4 and 5 were significantly associated with measures of bladder sensation, mode 3 with urodynamic stress urinary incontinence, and mode 3 with emptying in those able to void (r=0.368, p=0.021). The relationship between mode 3 and emptying across all patients is best fitted by a quadratic function (p&amp;lt;0.001).DiscussionOur results demonstrate that binary shape categorization and bladder shape quantified by statistical shape modeling correspond with measures of bladder physiology. This foundational study establishes statistical shape modeling as a robust bladder shape quantification method that can be used to relate bladder shape with physiology.

Intrinsic Atrial Myopathy Precedes Left Ventricular Dysfunction and Predicts Atrial Fibrillation in Lamin A/C Cardiomyopathy.

In Lamin A/C (LMNA) cardiomyopathy, atrial fibrillation (AF) commonly occurs before dilated cardiomyopathy, and the ability to predict its incidence is limited. We hypothesized that left atrial (LA) echocardiographic phenotyping can identify atrial myopathy and harbingers of AF. Echocardiograms from patients with pathogenic or likely pathogenic variants in LMNA (n=77) with and without reduced left ventricular ejection fraction (LVEF, <50%) were compared to healthy individuals (n=70) and patients with Titin truncating variant cardiomyopathy (TTNtv) (n=35) with similar LVEF, sex, and age distributions. Echocardiographic analysis, blinded to genotype, included strain and volumetric measures of left ventricular and atrial function. The primary outcome was incident AF. At baseline, 43% of the patients with pathogenic or likely pathogenic LMNA variants had a history of AF, including 26% of those with LVEF ≥50%. Compared with healthy subjects, the patients with pathogenic or likely pathogenic LMNA variants and LVEF ≥50% had reduced LA contractile strain (LMNA, 11.8±6.1% versus control, 15.0±4.2%; P=0.003). Compared to LVEF-matched (TTNtv) patients, the patients with pathogenic or likely pathogenic LMNA variants and LVEF <50% displayed no difference in LA size, but a worse LA contractile dysfunction (6.4±4.7% versus 12.6±9.6%; P=0.02). Over a median follow-up of 2.8 (1.2-5.7) years, LA contractile strain was the only significant predictor of AF in multivariable Cox regression (hazard ratio, 4.0 [95% CI, 1.04-15.2]). LMNA cardiomyopathy is associated with early intrinsic atrial myopathy reflected by high AF prevalence and reduced LA contractile strain, even in the absence of LV dysfunction and LA dilation. Whether LA strain can be used as a monitoring strategy to detect and mitigate AF complications requires validation.

Tooth loss and regional grey matter volume

ObjectivesTo investigate whether tooth loss was associated with regional grey matter volume (GMV) in a group of community dwelling older men and women from Ireland. MethodsA group of 380 dementia-free men and women underwent a dental examination and had a Magnetic Resonance Imaging (MRI) scan as part of The Irish Longitudinal Study of Aging (TILDA). Cortical parcellation was conducted using Freesurfer utilities to produce volumetric measures of gyral based regions of interest. Analysis included multiple linear regression to investigate the association between tooth loss and regional GMVs with adjustment for various confounders. ResultsThe mean age of participants was 68.1 years (SD 7.3) and 51.6% of the group were female. 50 (13.2%) of the participants were edentulous, 148 (38.9%) had 1-19 teeth, and 182 (47.9%) had ≥20 teeth. Multiple liner regression analysis with adjustment for a range of potential confounders showed associations between the number of teeth and GMVs in the paracentral lobule and the cuneus cortex. In the paracentral lobule, comparing participants with 1-19 teeth versus edentates there was an increase in GMV of β=323.0mm3 (95% Confidence Interval [CI] 84.5, 561.6) and when comparing participants with ≥20 teeth to edentates there was an increase of β=382.3mm3 (95% CI 126.9, 637.7). In the cuneus cortex, comparing participants with ≥20 teeth to edentates there was an increase in GMV of β=380.5mm3 (95% CI 69.4, 691.5). ConclusionsIn this group of older men and women from Ireland, the number of teeth was associated with GMVs in the paracentral lobule and the cuneus cortex independent of various known confounders. Clinical significanceAlthough not proof of causation, the finding that tooth loss was associated with regional reduced GMV in the brain may represent a potential explanatory link to the observed association between tooth loss and cognitive decline.