MRI-derived Measures Research Articles

The genetics of spatiotemporal variation in cortical thickness in youth

Prior studies have shown strong genetic effects on cortical thickness (CT), structural covariance, and neurodevelopmental trajectories in childhood and adolescence. However, the importance of genetic factors on the induction of spatiotemporal variation during neurodevelopment remains poorly understood. Here, we explore the genetics of maturational coupling by examining 308 MRI-derived regional CT measures in a longitudinal sample of 677 twins and family members. We find dynamic inter-regional genetic covariation in youth, with the emergence of regional subnetworks in late childhood and early adolescence. Three critical neurodevelopmental epochs in genetically-mediated maturational coupling were identified, with dramatic network strengthening near eleven years of age. These changes are associated with statistically-significant (empirical p-value <0.0001) increases in network strength as measured by average clustering coefficient and assortativity. We then identify genes from the Allen Human Brain Atlas with similar co-expression patterns to genetically-mediated structural covariation in children. This set was enriched for genes involved in potassium transport and dendrite formation. Genetically-mediated CT-CT covariance was also strongly correlated with expression patterns for genes located in cells of neuronal origin.

Connecting intermediate phenotypes to disease using multi-omics in heart failure.

Heart failure (HF) is one of the most common, complex, heterogeneous diseases in the world, with over 1-3% of the global population living with the condition. Progression of HF can be tracked via MRI measures of structural and functional changes to the heart, namely left ventricle (LV), including ejection fraction, mass, end-diastolic volume, and LV end-systolic volume. Moreover, while genome-wide association studies (GWAS) have been a useful tool to identify candidate variants involved in HF risk, they lack crucial tissue-specific and mechanistic information which can be gained from incorporating additional data modalities. This study addresses this gap by incorporating transcriptome-wide and proteome-wide association studies (TWAS and PWAS) to gain insights into genetically-regulated changes in gene expression and protein abundance in precursors to HF measured using MRI-derived cardiac measures as well as full-stage all-cause HF. We identified several gene and protein overlaps between LV ejection fraction and end-systolic volume measures. Many of the overlaps identified in MRI-derived measurements through TWAS and PWAS appear to be shared with all-cause HF. We implicate many putative pathways relevant in HF associated with these genes and proteins via gene-set enrichment and protein-protein interaction network approaches. The results of this study (1) highlight the benefit of using multi-omics to better understand genetics and (2) provide novel insights as to how changes in heart structure and function may relate to HF.

Investigating the relationship between radiographic joint space width loss and deep learning-derived magnetic resonance imaging-based cartilage thickness loss in the medial weight-bearing region of the tibiofemoral joint

ObjectiveTo investigate the relationship between measures of radiographic joint space width (JSW) loss and magnetic resonance imaging (MRI)-based cartilage thickness loss in the medial weight-bearing region of the tibiofemoral joint over 12–24 months. To stratify this relationship by clinically meaningful subgroups (sex and pain status). DesignWe analyzed a subset of knees (n ​= ​256) from the Osteoarthritis Initiative (OAI) likely in early stage OA based on joint space narrowing (JSN) measurements. Natural logarithm transformation was used to approximate near normal distributions for JSW loss. Pearson Correlation coefficients described the relationship between ln-transformed JSW loss and several versions of deep learning-derived MRI-based cartilage thickness loss parameters (minimum, maximum, and mean) in subregions of the femoral condyle, tibial plateau, and combined femoral and tibial regions. Linear mixed-effects models evaluated the associations between the ln-transformed radiographic and MRI-derived measures including potential confounders. ResultsWe found weak correlations between ln-transformed JSW loss and MRI-based cartilage thickness ranging from R ​= ​−0.13 (p ​= ​0.20) to R ​= ​0.26 (p ​< ​0.01). Correlations were higher (still poor) among females compared to males and painful compared to non-painful knees. Model results showed weak associations for nearly all MRI-based measures, ranging from no association to β (95% CI) ​= ​0.25 (0.11, 0.39). Associations were higher among females compared to males and minimal differences between painful and non-painful knees. ConclusionsDespite its recommended use in disease-modifying OA drug clinical trials, results suggest that JSW loss is an ineffective proxy measure of cartilage thickness loss over 12–24 months and within a localized region of the tibiofemoral joint.

Clinical utility of diffusion MRI-derived measures of cortical microstructure in a real-world memory clinic setting.

To investigate cortical microstructural measures from diffusion MRI as "neurodegeneration" markers that could improve prognostic accuracy in mild cognitive impairment (MCI). The prognostic power of Amyloid/Tau/Neurodegeneration (ATN) biomarkers to predict progression from MCI to AD or non-AD dementia was investigated. Ninety patients underwent clinical evaluation (follow-up interval 32 ± 18 months), lumbar puncture, and MRI. Participants were grouped by clinical stage and cerebrospinal fluid Amyloid and Tau status. T1-structural and diffusion MRI scans were analyzed to calculate diffusion metrics related to cortical columnar structure (AngleR, ParlPD, PerpPD+), cortical mean diffusivity, and fractional anisotropy. Statistical tests were corrected for multiple comparisons. Prognostic power was assessed using receiver operating characteristic (ROC) analysis and related indices. A progressive increase of whole-brain cortical diffusion values was observed along the AD continuum, with all A+ groups showing significantly higher AngleR than A-T-. Investigating clinical progression to dementia, the AT biomarkers together showed good positive predictive value (with 90.91% of MCI A+T+ converting to dementia) but poor negative predictive value (with 40% of MCI A-T- progressing to a mix of AD and non-AD dementias). Adding whole-brain AngleR as an N marker, produced good differentiation between stable and converting MCI A-T- patients (0.8 area under ROC curve) and substantially improved negative predictive value (+21.25%). Results support the clinical utility of cortical microstructure to aid prognosis, especially in A-T- patients. Further work will investigate other complexities of the real-world clinical setting, including A-T+ groups. Diffusion MRI measures of neurodegeneration may complement fluid AT markers to support clinical decision-making.

Differing genetic variants associated with liver fat and their contrasting relationships with cardiovascular diseases and cancer

The mechanisms underlying the association of steatotic liver disease with cardiovascular and cancer outcomes are poorly understood. We aimed to use MRI-derived measures of liver fat and genetics to investigate causal mechanisms that link higher liver fat to various health outcomes. We conducted a genome-wide association study on 37,358 UK Biobank participants to identify genetic variants associated with liver fat measured from MRI scans. We used a Mendelian randomisation approach to investigate the causal effect of liver fat on health outcomes independent of BMI, alcohol consumption and lipids using data from published genome-wide association studies and FinnGen. We identified 13 genetic variants associated with liver fat that had differing effects on the risks of health outcomes. Genetic variants associated with impaired hepatic triglyceride export showed liver fat-increasing alleles to be correlated with a reduced risk of coronary artery disease and myocardial infarction but an elevated risk of type 2 diabetes, while variants associated with enhanced de novo lipogenesis showed liver fat-increasing alleles to be linked to a higher risk of myocardial infarction and coronary artery disease. Genetically higher liver fat content increased the risk of non-alcohol-related cirrhosis, hepatocellular carcinoma, and intrahepatic bile duct and gallbladder cancers, exhibiting a dose-dependent relationship, irrespective of the mechanism. This study provides fresh insight into the heterogeneous effect of liver fat on health outcomes. It challenges the notion that liver fat per se is an independent risk factor for cardiovascular disease, underscoring the dependency of this association on the specific mechanisms that drive fat accumulation in the liver. However, excess liver fat, regardless of the underlying mechanism, appears to be causally linked to cirrhosis and cancers in a dose-dependent manner. This research advances our understanding of the heterogeneity in mechanisms influencing liver fat accumulation, providing new insights into how liver fat accumulation may impact various health outcomes. The findings challenge the notion that liver fat is an independent risk factor for cardiovascular disease and highlight the mechanistic effect of some genetic variants on fat accumulation and the development of cardiovascular diseases. This study is of particular importance for healthcare professionals including physicians and researchers, as well as patients, as it allows for more targeted and personalised treatment by understanding the relationship between liver fat and various health outcomes. The findings emphasise the need for a personalised management approach and a reshaping of risk assessment criteria. It also provides room for prioritising a clinical intervention aimed at reducing liver fat content (likely via intentional weight loss) that could help protect against liver-related fibrosis and cancer.

Correlation of Noninvasive Cardiac MRI Measures of Left Ventricular Myocardial Function and Invasive Pressure-Volume Parameters in a Porcine Ischemia-Reperfusion Model.

Purpose To assess the correlation between noninvasive cardiac MRI-derived parameters with pressure-volume (PV) loop data and evaluate changes in left ventricular function after myocardial infarction (MI). Materials and Methods Sixteen adult female swine were induced with MI, with six swine used as controls and 10 receiving platelet-derived growth factor-AB (PDGF-AB). Load-independent measures of cardiac function, including slopes of end-systolic pressure-volume relationship (ESPVR) and preload recruitable stroke work (PRSW), were obtained on day 28 after MI. Cardiac MRI was performed on day 2 and day 28 after infarct. Global longitudinal strain (GLS) and global circumferential strain (GCS) were measured. Ventriculo-arterial coupling (VAC) was derived from PV loop and cardiac MRI data. Pearson correlation analysis was performed. Results GCS (r = 0.60, P = .01), left ventricular ejection fraction (LVEF) (r = 0.60, P = .01), and cardiac MRI-derived VAC (r = 0.61, P = .01) had a significant linear relationship with ESPVR. GCS (r = 0.75, P < .001) had the strongest significant linear relationship with PRSW, followed by LVEF (r = 0.67, P = .005) and cardiac MRI-derived VAC (r = 0.60, P = .01). GLS was not significantly correlated with ESPVR or PRSW. There was a linear correlation (r = 0.82, P < .001) between VAC derived from cardiac MRI and from PV loop data. GCS (-3.5% ± 2.3 vs 0.5% ± 1.4, P = .007) and cardiac MRI-derived VAC (-0.6 ± 0.6 vs 0.3 ± 0.3, P = .001) significantly improved in the animals treated with PDGF-AB 28 days after MI compared with controls. Conclusion Cardiac MRI-derived parameters of MI correlated with invasive PV measures, with GCS showing the strongest correlation. Cardiac MRI-derived measures also demonstrated utility in assessing therapeutic benefit using PDGF-AB. Keywords: Cardiac MRI, Myocardial Infarction, Pressure Volume Loop, Strain Imaging, Ventriculo-arterial Coupling Supplemental material is available for this article. © RSNA, 2024.

#1081 Associations of MRI-derived kidney volume, kidney function, body composition, and physical performance in &amp;gt;38 000 UK Biobank participants

Abstract Background and Aims Kidney volume is used as predictive and therapeutic marker for several clinical conditions. However, there is a lack of large-scale studies examining the relationship between kidney volume and various clinicodemographic factors, including kidney function, body composition, and physical performance. Method In this observational study, MRI-derived kidney volume measurements from 38,526 UK Biobank participants were analyzed. Major kidney volume-related measures included body surface area (BSA)-adjusted total kidney volume (TKV) and the difference of bilateral kidneys. Multivariable-adjusted linear regression and cubic spline analyses were used to explore the association between kidney volume-related measures and clinicodemographic factors. Cox regression was used to identify the risks of death, non-kidney cancer, myocardial infarction (MI), and ischemic stroke. Results The median of BSA-adjusted TKV and difference in kidney volume were 141.9 (128.1–156.9) mL/m2 and 1.08 (1.04–1.15) fold, respectively. Higher BSA-adjusted TKV was significantly associated with higher eGFR (beta [95% CIs], 0.43 [0.42–0.44]; P &amp;lt; 0.001), higher composition of muscle volume (beta [95% CIs], 0.50 [0.48–0.51]; P &amp;lt; 0.001), and higher mean handgrip strength (beta [95% CIs], 0.15 [0.13–0.16]; P &amp;lt; 0.001), while associated with lower visceral adipose tissue volume (VAT, beta [95% CIs], −0.09 [−0.11 – −0.07]; P &amp;lt; 0.001) in adjusted models. Higher difference in bilateral kidney volumes was associated with lower eGFR, muscle volume, and physical performance, while associated with higher proteinuria and VAT. Conclusion Higher BSA-adjusted TKV and lower discrepancies in bilateral kidney volumes are associated with higher renal function, muscle volume, and physical performance.

MINocyclinE to Reduce inflammation and blood-brain barrier leakage in small Vessel diseAse (MINERVA): A phase II, randomized, double-blind, placebo-controlled experimental medicine trial.

Cerebral small vessel disease (SVD) is a common cause of stroke/vascular dementia with few effective treatments. Neuroinflammation and increased blood-brain barrier (BBB) permeability may influence pathogenesis. In rodent models, minocycline reduced inflammation/BBB permeability. We determined whether minocycline had a similar effect in patients with SVD. MINERVA was a single-center, phase II, randomized, double-blind, placebo-controlled trial. Forty-four participants with moderate-to-severe SVD took minocycline or placebo for 3 months. Co-primary outcomes were microglial signal (determined using 11C-PK11195 positron emission tomography) and BBB permeability (using dynamic contrast-enhanced MRI). Forty-four participants were recruited between September 2019 and June 2022. Minocycline had no effect on 11C-PK11195 binding (relative risk [RR] 1.01, 95% confidence interval [CI] 0.98-1.04), or BBB permeability (RR 0.97, 95% CI 0.91-1.03). Serum inflammatory markers were not affected. 11C-PK11195 binding and increased BBB permeability are present in SVD; minocycline did not reduce either process. Whether these pathophysiological mechanisms are disease-causing remains unclear. ISRCTN15483452 HIGHLIGHTS: We found focal areas of increased microglial signal and increased blood-brain barrier permeability in patients with small vessel disease. Minocycline treatment was not associated with a change in these processes measured using advanced neuroimaging. Blood-brain barrier permeability was dynamic but MRI-derived measurements correlated well with CSF/serum albumin ratio. Advanced neuroimaging is a feasible outcome measure for mechanistic clinical trials.

Quantitative 1H Magnetic Resonance Imaging on Normal and Pathologic Rat Bones by Solid-State 1H ZTE Sequence with Water and Fat Suppression.

Osteoporosis (OP) and osteomalacia (OM) are metabolic bone diseases characterized by mineral and matrix density changes. Quantitative bone matrix density differentiates OM from OP. MRI is a noninvasive and nonionizing imaging technique that can measure bone matrix density quantitatively in ex vivo and in vivo. To demonstrate water + fat suppressed 1H MRI to compute bone matrix density in ex vivo rat femurs in the preclinical model. Prospective. Fifteen skeletally mature female Sprague-Dawley rats, five per group (normal, ovariectomized (OVX), partially nephrectomized/vitamin D (Vit-D) deficient), 250-275 g, ∼15 weeks old. 7T, zero echo time sequence with water + fat (VAPOR) suppression capability, μCT imaging, and gravimetric measurements. Cortical and trabecular bone segments from normal and disease models were scanned in the same coil along with a dual calibration phantom for quantitative assessment of bone matrix density. ANOVA and linear regression were used for data analysis, with P-values <0.05 statistically significant. The MRI-derived three-density PEG pellet densities have a strong linear relationship with physical density measures (r2 = 0.99). The Vit-D group had the lowest bone matrix density for cortical bone (0.47 ± 0.16 g cm-3), whereas the OVX had the lowest bone matrix density for trabecular bone (0.26 ± 0.04 g cm-3). Gravimetry results confirmed these MRI-based observations for Vit-D cortical (0.51 ± 0.07 g cm-3) and OVX trabecular (0.26 ± 0.03 g cm-3) bone groups. Rat femur images were obtained using a modified pulse sequence and a custom-designed double-tuned (1H/31P) transmit-receive solenoid-coil on a 7T preclinical MRI scanner. Phantom experiments confirmed a strong linear relation between MRI-derived and physical density measures and quantitative bone matrix densities in rat femurs from normal, OVX, and Vit-D deficient/partially nephrectomized animals were computed. 2 TECHNICAL EFFICACY: Stage 2.

Associations of MRI-derived kidney volume, kidney function, body composition and physical performance in ≈38000 UK Biobank participants: a population-based observational study.

Kidney volume is used as a predictive and therapeutic marker for several clinical conditions. However, there is a lack of large-scale studies examining the relationship between kidney volume and various clinicodemographic factors, including kidney function, body composition and physical performance. In this observational study, MRI-derived kidney volume measurements from 38526 UK Biobank participants were analysed. Major kidney volume-related measures included body surface area (BSA)-adjusted total kidney volume (TKV) and the difference in bilateral kidneys. Multivariable-adjusted linear regression and cubic spline analyses were used to explore the association between kidney volume-related measures and clinicodemographic factors. Cox or logistic regression was used to identify the risks of death, non-kidney cancer, myocardial infarction, ischaemic stroke and chronic kidney disease (CKD). The median of BSA-adjusted TKV and the difference in kidney volume were 141.9ml/m2 [interquartile range (IQR) 128.1-156.9] and 1.08-fold (IQR 1.04-1.15), respectively. Higher BSA-adjusted TKV was significantly associated with higher estimated glomerular filtration rate {eGFR; β=0.43 [95% confidence interval (CI) 0.42-0.44]; P<.001}, greater muscle volume [β=0.50 (95% CI 0.48-0.51); P<.001] and greater mean handgrip strength [β=0.15 (95% CI 0.13-0.16); P<.001] but lower visceral adipose tissue volume [VAT; β=-0.09 (95% CI -0.11 to -0.07); P<.001] in adjusted models. A greater difference in bilateral kidney volumes was associated with lower eGFR, muscle volume and physical performance but with higher proteinuria and VAT. Higher BSA-adjusted TKV was significantly associated with a reduced risk of CKD [odds ratio (OR) 0.7 (95% CI 0.63-0.77); P<.001], while a greater difference in kidney volume was significantly associated with an increased risk of CKD [OR 1.13 (95% CI 1.07-1.20); P<.001]. Higher BSA-adjusted TKV and lower differences in bilateral kidney volumes are associated with higher kidney function, muscle volume and physical performance and a reduced risk of CKD.

Feasibility, Repeatability, and Correlation to Lung Function of Phase-Resolved Functional Lung (PREFUL) MRI-derived Pulmonary Artery Pulse Wave Velocity Measurements.

Pulse wave velocity (PWV) in the pulmonary arteries (PA) is a marker of vascular stiffening. Currently, only phase-contrast (PC) MRI-based options exist to measure PA-PWV. To test feasibility, repeatability, and correlation to clinical data of Phase-Resolved Functional Lung (PREFUL) MRI-based calculation of PA-PWV. Retrospective. 79 (26 female) healthy subjects (age range 19-78), 58 (24 female) patients with chronic obstructive pulmonary disease (COPD, age range 40-77), 60 (33 female) patients with suspected pulmonary hypertension (PH, age range 28-85). 2D spoiled gradient echo, 1.5T. PA-PWV was measured from PREFUL-derived cardiac cycles based on the determination of temporal and spatial distance between lung vasculature voxels using a simplified (sPWV) method and a more comprehensive (cPWV) method including more elaborate distance calculation. For 135 individuals, PC MRI-based PWV (PWV-QA) was measured. Intraclass-correlation-coefficient (ICC) and coefficient of variation (CoV) were used to test repeatability. Nonparametric tests were used to compare cohorts. Correlation of sPWV/cPWV, PWV-QA, forced expiratory volume in 1 sec (FEV1) %predicted, residual volume (RV) %predicted, age, and right heart catheterization (RHC) data were tested. Significance level α = 0.05 was used. sPWV and cPWV showed no significant differences between repeated measurements (P-range 0.10-0.92). CoV was generally lower than 15%. COPD and PH patients had significantly higher sPWV and cPWV than healthy subjects. Significant correlation was found between sPWV or cPWV and FEV1%pred. (R = -0.36 and R = -0.44), but not with RHC (P-range -0.11 - 0.91) or age (P-range 0.23-0.89). Correlation to RV%pred. was significant for cPWV (R = 0.42) but not for sPWV (R = 0.34, P = 0.055). For all cohorts, sPWV and cPWV were significantly correlated with PWV-QA (R = -0.41 and R = 0.48). PREFUL-derived PWV is feasible and repeatable. PWV is increased in COPD and PH patients and correlates to airway obstruction and hyperinflation. 3 TECHNICAL EFFICACY: Stage 2.

The causal relationship between human blood metabolites and the risk of visceral obesity: a mendelian randomization analysis

BackgroundWe aimed to explore the causal relationship between blood metabolites and the risk of visceral obesity, as measured by visceral adipose tissue (VAT).MethodsSummary statistics for 486 blood metabolites and total, as well as sex-stratified, MRI-derived VAT measurements, adjusted for body mass index (BMI) and height, were collected from previous genome-wide association studies (GWAS). A two-sample Mendelian Randomization (MR) design was used. Comprehensive evaluation was further conducted, including sensitivity analysis, linkage disequilibrium score (LDSC) regression, Steiger test, and metabolic pathway analysis.ResultsAfter multiple testing correction, arachidonate (20:4n6) has been implicated in VAT accumulation (β = 0.35, 95%CI:0.18–0.52, P < 0.001; FDR = 0.025). Additionally, several blood metabolites were identified as potentially having causal relationship (FDR < 0.10). Among them, lysine (β = 0.67, 95%CI: 0.28–1.06, P < 0.001; FDR = 0.074), proline (β = 0.30, 95%CI:0.13–0.48, P < 0.001; FDR = 0.082), valerate (β = 0.50, 95%CI:0.23–0.78, P < 0.001, FDR = 0.091) are associated with an increased risk of VAT accumulation. On the other hand, glycine (β=-0.21, 95%CI: -0.33–0.09), P < 0.001, FDR = 0.076) have a protective effect against VAT accumulation. Most blood metabolites showed consistent trends between different sexes. Multivariable MR analysis demonstrated the effect of genetically predicted arachidonate (20:4n6) and proline on VAT remained after accounting for BMI and glycated hemoglobin (HbA1c). There is no evidence of heterogeneity, pleiotropy, and reverse causality.ConclusionOur MR findings suggest that these metabolites may serve as biomarkers, as well as for future mechanistic exploration and drug target selection of visceral obesity.

MRI-Based Assessment of Brain Tumor Hypoxia: Correlation with Histology.

Cerebral hypoxia significantly impacts the progression of brain tumors and their resistance to radiotherapy. This study employed streamlined quantitative blood-oxygen-level-dependent (sqBOLD) MRI to assess the oxygen extraction fraction (OEF)-a measure of how much oxygen is being extracted from vessels, with higher OEF values indicating hypoxia. Simultaneously, we utilized vessel size imaging (VSI) to evaluate microvascular dimensions and blood volume. A cohort of ten patients, divided between those with glioma and those with brain metastases, underwent a 3 Tesla MRI scan. We generated OEF, cerebral blood volume (CBV), and vessel size maps, which guided 3-4 targeted biopsies per patient. Subsequent histological analyses of these biopsies used hypoxia-inducible factor 1-alpha (HIF-1α) for hypoxia and CD31 for microvasculature assessment, followed by a correlation analysis between MRI and histological data. The results showed that while the sqBOLD model was generally applicable to brain tumors, it demonstrated discrepancies in some metastatic tumors, highlighting the need for model adjustments in these cases. The OEF, CBV, and vessel size maps provided insights into the tumor's hypoxic condition, showing intertumoral and intratumoral heterogeneity. A significant relationship between MRI-derived measurements and histological data was only evident in the vessel size measurements (r = 0.68, p < 0.001).

Advanced fibrosis leads to overestimation of steatosis with quantitative ultrasound in individuals without hepatic steatosis.

The effect of hepatic fibrosis stage on quantitative ultrasound based on the attenuation coefficient (AC) for liver lipid quantification is controversial. The objective of this study was to determine how the degree of fibrosis assessed by magnetic resonance (MR) elastography affects AC based on the ultrasound-guided attenuation parameter according to the grade of hepatic steatosis, using magnetic resonance imaging (MRI)-derived proton density fat fraction (MRIderived PDFF) as the reference standard. Between February 2020 and April 2021, 982 patients with chronic liver disease who underwent AC and MRI-derived PDFF measurement as well as MR elastography were enrolled. Multiple regression was used to investigate whether AC was affected by the degree of liver stiffness. AC increased as liver stiffness progressed in 344 patients without hepatic steatosis (P=0.009). In multivariable analysis, AC was positively correlated with skin-capsule distance (P<0.001), MR elastography value (P=0.037), and MRI-derived PDFF (P<0.001) in patients without hepatic steatosis. In 52 of 982 patients (5%), the correlation between AC and MRIderived PDFF fell outside the 95% confidence interval for the regression line slope. Patients with MRI-derived PDFF lower than their AC (n=36) had higher fibrosis-4 scores, albumin-bilirubin scores, and MR elastography values than patients with MRI-derived PDFF greater than their AC (n=16; P=0.018, P=0.001, and P=0.011, respectively). AC is affected by liver fibrosis (MR elastography value ≥6.7 kPa) only in patients without hepatic steatosis (MRI-derived PDFF <5.2%). These values should be interpreted with caution in patients with advanced liver fibrosis.

Normative Measurements of L1 to S1 Neuroforaminal Dimensions Derived From Plain Film Radiography, Computed Tomography, and Magnetic Resonance Imaging.

Retrospective cohort. To report normative measurements of L1 to S1 lumbar neuroforamina on plain film radiography (PFR), computed tomography (CT), and magnetic resonance imaging (MRI), accounting for patients' sex and ethnicity. The quantitative criteria fothe diagnosis of neuroforaminal stenosis remains unknown. Acquiring a thorough understanding of normative foraminal dimensions is a key step in formulating objective parameters for neuroforaminal stenosis. We measured 988 images from 494 patients between 18 and 35 years old without spinal pathology who received PFR, CT, or MRI within 1 year of each other. Neuroforaminal measurements were defined as the height, area, and sagittal and axial widths. Statistical analyses were performed to assess relationships among PFR, CT, and MRI-derived neuroforaminal measurements, as well as the influence of patients' sex and ethnicity. 330 PFR, 377 CT, and 281 MRI were measured. Of these, 213 PFR and CT, 117 PFR and MRI, and 164 MRI and CT intrapatient images were compared. Statistically significant differences were observed among PFR, CT, and MRI measurements across all levels L1 to S1. PFR measurements were larger compared with those derived from CT and MRI. Weak-to-moderate correlations were observed between PFR and CT, PFR and MRI, and CT and MRI, with the magnitude of correlation decreasing caudally from L1 to S1. Variations in neuroforaminal anatomy were observed based on sex and ethnicity. This study reports 25,951 measurements of normal L1 to S1 neuroforaminal anatomy assessed by PFR, CT, and MRI. The values reported in this study may be used as normative reference measurements of the lumbar neuroforamina. PFR measurements of the neuroforamina are larger compared with those derived from CT and MRI across all levels from L1 to S1. There is a poor correlation between PFR, CT, and MRI when measuring the lumbar neuroforamina. Differences in neuroforaminal anatomy are evident based on patients' sex and ethnicity.

Subject classification and cross-time prediction based on functional connectivity and white matter microstructure features in a rat model of Alzheimer’s using machine learning

BackgroundThe pathological process of Alzheimer’s disease (AD) typically takes decades from onset to clinical symptoms. Early brain changes in AD include MRI-measurable features such as altered functional connectivity (FC) and white matter degeneration. The ability of these features to discriminate between subjects without a diagnosis, or their prognostic value, is however not established.MethodsThe main trigger mechanism of AD is still debated, although impaired brain glucose metabolism is taking an increasingly central role. Here, we used a rat model of sporadic AD, based on impaired brain glucose metabolism induced by an intracerebroventricular injection of streptozotocin (STZ). We characterized alterations in FC and white matter microstructure longitudinally using functional and diffusion MRI. Those MRI-derived measures were used to classify STZ from control rats using machine learning, and the importance of each individual measure was quantified using explainable artificial intelligence methods.ResultsOverall, combining all the FC and white matter metrics in an ensemble way was the best strategy to discriminate STZ rats, with a consistent accuracy over 0.85. However, the best accuracy early on was achieved using white matter microstructure features, and later on using FC. This suggests that consistent damage in white matter in the STZ group might precede FC. For cross-timepoint prediction, microstructure features also had the highest performance while, in contrast, that of FC was reduced by its dynamic pattern which shifted from early hyperconnectivity to late hypoconnectivity.ConclusionsOur study highlights the MRI-derived measures that best discriminate STZ vs control rats early in the course of the disease, with potential translation to humans.

Abstract 17045: Investigating the Causal Relationship Between Glycemic Trait and Great Vessels Structures Using Mendelian Randomization

Introduction: Diabetes has been inversely associated with aortic aneurysm. However, it remains unclear whether this relationship is causal. In this study, we investigated the relationship between diabetes and glycemic traits, and MRI-derived measures of the great vessels (aortic and pulmonary artery) morphologies using Mendelian randomization (MR). Methods: We employed an inverse-variance weighted method to conduct a two-sample MR analysis using summary statistics from genome-wide association studies of glycemic traits (fasting insulin [FI], fasting glucose [FG], glycated hemoglobin [HbA1c], 2-hour glucose after oral challenge [2hGlu], and type 2 diabetes [T2D]) and MRI-derived measures of aortic morphology including ascending and descending aortic diameters (AAoD and DAoD), aortic distensibility (AoDist), aortic strain (AoStr), and pulmonary artery diameter (PAD). Sensitivity analysis was performed using the MR-Egger method, and pleiotropy was assessed using the MR-PRESSO method. Results: We observed evidence for associations between glycemic traits and aortic measures. Regarding aortic diameter, genetically predicted increases levels of 2hGlu, FG, and HbA1c were associated with decreased AAoD (2hGlu β = -0.11, p &lt; 0.05; FG β = -0.15, p = 0.0002; HbA1c β = -0.18, p = 0.01) and DAoD (2hGlu β = -0.09, p &lt; 0.001; FG β = -0.17, p = 0.0002; HbA1c β = -0.09, p = 0.02). No significant associations were observed between FI or T2D and both measures. We found that a genetically predicted increase in FI was associated with decreased AoStr (β = -0.23, p = 0.002) and AoDist (β = -0.18, p = 0.02), while a genetically predicted increase in HbA1c was associated with an increased AoStr (β = 0.18, p = 0.0008) and AoDist (β = 0.12, p = 0.03). Lastly, increased levels of FG and HbA1c were associated with an increase in PAD (FG β = 0.11, p = 0.02; HbA1C FG β = 0.25, p = 0.001). Conclusions: The genetic evidence supports the effects of glycemic traits on the aortic vasculature, providing additional causal evidence to support the epidemiological evidence linking high glucose exposure to aortic aneurysm. Further research is needed to better understand the mechanisms underlying these relationships.

Standardizing MRI orientation improves reliability of entorhinal and transentorhinal cortical volume measurement

The current study compared the reliability of manual collateral sulcus depth and entorhinal and transentorhinal cortical volume measurements between native oriented MRI scans versus MRI scans realigned to the hippocampal long axis. Data included 10 participants with two serial 3.0T MRI scans from the Alzheimer's Disease Neuroimaging Initiative. Both collateral sulcus depth and entorhinal and transentorhinal cortical volume measurement reliability improved from the native to the hippocampal oriented scans. Standardizing scan orientation is important to optimize reliability of MRI-derived manual measurements of the entorhinal and transentorhinal cortices. In quantitative MRI studies, aligning scans to a common, normalized orientation is recommended.

The impact of head orientation with respect to B0 on diffusion tensor MRI measures.

Diffusion tensor MRI (DT-MRI) remains the most commonly used approach to characterise white matter (WM) anisotropy. However, DT estimates may be affected by tissue orientation w.r.t. due to local gradients and intrinsic orientation dependence induced by the microstructure. This work aimed to investigate whether and how diffusion tensor MRI-derived measures depend on the orientation of the head with respect to the static magnetic field, . By simulating WM as two compartments, we demonstrated that compartmental anisotropy can induce the dependence of diffusion tensor measures on the angle between WM fibres and the magnetic field. In in vivo experiments, reduced radial diffusivity and increased axial diffusivity were observed in white matter fibres perpendicular to compared to those parallel to . Fractional anisotropy varied by up to as a function of the angle between WM fibres and the orientation of the main magnetic field. To conclude, fibre orientation w.r.t. is responsible for up to variance in diffusion tensor measures across the whole brain white matter from all subjects and head orientations. Fibre orientation w.r.t. may introduce additional variance in clinical research studies using diffusion tensor imaging, particularly when it is difficult to control for (e.g., fetal or neonatal imaging, or when the trajectories of fibres change due to, e.g., space occupying lesions).

Treatment Effect on Brain Atrophy Correlates with Treatment Effect on Cognition in Multiple Sclerosis.

The purpose of this study was to evaluate the extent to which treatment effect on magnetic resonance imaging (MRI)-derived measures of brain atrophy and focal lesions can mediate, at the trial level, the treatment effect on cognitive outcomes in multiple sclerosis (MS). We collected all published randomized clinical trials in MS lasting at least 2 years and including as end points: active MRI lesions (defined as new/enlarging T2 lesions), brain atrophy (defined as a change in brain volume between month 12 and month 24), and change in cognitive performance (assessed by the Paced Auditory Serial Addition Test [PASAT]). Relative reductions were used to quantify the treatment effect on MRI markers (lesions and atrophy), whereas the standardized mean difference (Hedges g) between baseline and follow-up cognitive assessment was used to quantify the treatment effects on cognition. A linear regression, weighted for trial size, was used to assess the relationship between the treatment effects on MRI markers and cognition. Fourteen trials including more than 8,813 patients with MS were included in the meta-regression. Treatment effect on cognition was strongly associated with the treatment effect on brain atrophy (R2 = 0.79, p < 0.001), but was not correlated with the treatment effect on active MRI lesions (R2 = 0.16, p = 0.14). Results reported here suggest that brain atrophy, a well-established MRI marker in MS clinical trials, can be used as a main outcome for clinical trials with drugs targeting cognitive impairment and neurodegeneration. ANN NEUROL 2023.