We aimed to compare the ability of diffusion tensor imaging and multi‐compartment spherical mean technique to detect focal tissue damage and in distinguishing between different connectivity patterns ...associated with varying clinical outcomes in multiple sclerosis (MS). Seventy‐six people diagnosed with MS were scanned using a SIEMENS Prisma Fit 3T magnetic resonance imaging (MRI), employing both conventional (T1w and fluid‐attenuated inversion recovery) and advanced diffusion MRI sequences from which fractional anisotropy (FA) and microscopic FA (μFA) maps were generated. Using automated fiber quantification (AFQ), we assessed diffusion profiles across multiple white matter (WM) pathways to measure the sensitivity of anisotropy diffusion metrics in detecting localized tissue damage. In parallel, we analyzed structural brain connectivity in a specific patient cohort to fully grasp its relationships with cognitive and physical clinical outcomes. This evaluation comprehensively considered different patient categories, including cognitively preserved (CP), mild cognitive deficits (MCD), and cognitively impaired (CI) for cognitive assessment, as well as groups distinguished by physical impact: those with mild disability (Expanded Disability Status Scale EDSS <=3) and those with moderate–severe disability (EDSS >3). In our initial objective, we employed Ridge regression to forecast the presence of focal MS lesions, comparing the performance of μFA and FA. μFA exhibited a stronger association with tissue damage and a higher predictive precision for focal MS lesions across the tracts, achieving an R‐squared value of .57, significantly outperforming the R‐squared value of .24 for FA (p‐value <.001). In structural connectivity, μFA exhibited more pronounced differences than FA in response to alteration in both cognitive and physical clinical scores in terms of effect size and number of connections. Regarding cognitive groups, FA differences between CP and MCD groups were limited to 0.5% of connections, mainly around the thalamus, while μFA revealed changes in 2.5% of connections. In the CP and CI group comparison, which have noticeable cognitive differences, the disparity was 5.6% for FA values and 32.5% for μFA. Similarly, μFA outperformed FA in detecting WM changes between the MCD and CI groups, with 5% versus 0.3% of connections, respectively. When analyzing structural connectivity between physical disability groups, μFA still demonstrated superior performance over FA, disclosing a 2.1% difference in connectivity between regions closely associated with physical disability in MS. In contrast, FA spotted a few regions, comprising only 0.6% of total connections. In summary, μFA emerged as a more effective tool than FA in predicting MS lesions and identifying structural changes across patients with different degrees of cognitive and global disability, offering deeper insights into the complexities of MS‐related impairments.
This research reveals that microscopic fractional anisotropy outperforms standard fractional anisotropy in identifying tissue damage and discerning connectivity patterns in multiple sclerosis, thus improving lesion prediction and insight into the disease's cognitive and physical effects.
Introduction
Diffusion tensor imaging (DTI) can assess the structural integrity of the corticospinal tract (CST) in vivo. We aimed to investigate whether CST DTI metrics after intracerebral ...haemorrhage (ICH) are associated with 6-month functional outcome and can improve the predictive performance of the existing ICH score.
Methods
We retrospectively included 42 patients with DTI performed within 5 days after deep supratentorial spontaneous ICH. Ipsilesional-to-contralesional ratios were calculated for fractional anisotropy (rFA) and mean diffusivity (rMD) in the pontine segment (PS) of the CST. We determined the most predictive variables for poor 6-month functional outcome modified Rankin Scale (mRS) > 2 using the least absolute shrinkage and selection operator (LASSO) method. We calculated discrimination using optimism-adjusted estimation of the area under the curve (AUC).
Results
Patients with 6-month mRS > 2 had lower rFA (0.945 ± 0.139 vs 1.045 ± 0.130; OR 0.004 95% CI 0.00–0.77;
p
= 0.04) and higher rMD (1.233 ± 0.418 vs 0.963 ± 0.211; OR 22.5 95% CI 1.46–519.68;
p
= 0.02). Discrimination (AUC) values were: 0.76 (95% CI 0.61–0.91) for the ICH score, 0.71 (95% CI 0.54–0.89) for rFA, and 0.72 (95% CI 0.61–0.91) for rMD. Combined models with DTI and non-DTI variables offer an improvement in discrimination: for the best model, the AUC was 0.82 (95% CI 0.68–0.95;
p
= 0.15).
Conclusion
In our exploratory study, PS-CST rFA and rMD had comparable predictive ability to the ICH score for 6-month functional outcome. Adding DTI metrics to clinical-radiological scores might improve discrimination, but this needs to be investigated in larger studies.
Introduction
Small vessel disease (SVD) causes most spontaneous intracerebral haemorrhage (ICH) and is associated with widespread microstructural brain tissue disruption, which can be quantified via ...diffusion tensor imaging (DTI) metrics: mean diffusivity (MD) and fractional anisotropy (FA). Little is known about the impact of whole-brain microstructural alterations after SVD-related ICH. We aimed to investigate: (1) association between whole-brain DTI metrics and functional outcome after ICH; and (2) predictive ability of these metrics compared to the pre-existing ICH score.
Methods
Sixty-eight patients (38.2% lobar) were retrospectively included. We assessed whole-brain DTI metrics (obtained within 5 days after ICH) in cortical and deep grey matter and white matter. We used univariable logistic regression to assess the associations between DTI and clinical-radiological variables and poor outcome (modified Rankin Scale > 2). We determined the optimal predictive variables (via LASSO estimation) in: model 1 (DTI variables only), model 2 (DTI plus non-DTI variables), model 3 (DTI plus ICH score). Optimism-adjusted C-statistics were calculated for each model and compared (likelihood ratio test) against the ICH score.
Results
Deep grey matter MD (OR 1.04 95% CI 1.01–1.07,
p
= 0.010) and white matter MD (OR 1.11 95% CI 1.01–1.23,
p
= 0.044) were associated (univariate analysis) with poor outcome. Discrimination values for model 1 (0.67 95% CI 0.52–0.83), model 2 (0.71 95% CI 0.57–0.85) and model 3 (0.66 95% CI 0.52–0.82) were all significantly higher than the ICH score (0.62 95% CI 0.49–0.75).
Conclusion
Our exploratory study suggests that whole-brain microstructural disruption measured by DTI is associated with poor 6-month functional outcome after SVD-related ICH. Whole-brain DTI metrics performed better at predicting recovery than the existing ICH score.
The purpose of this study was to obtain quantitative measurements of the apparent diffusion coefficient (ADC1), flow insensitive apparent diffusion coefficient (ADC2) and perfusion fraction (F) of ...colorectal hepatic metastases using DWI and to compare these measurements with those obtained in liver parenchyma. Forty patients with 66 hepatic metastases from colorectal carcinoma were prospectively evaluated using DWI with three b values. Quantitative maps of the ADC1 (using b = 0, 150, 500 s/mm2 images), ADC2 (using b = 150, 500 s/mm2 images) and fractional variation (F) between ADC1 and ADC2, which reflects perfusion fraction, were calculated. The ADC1, ADC2 and F derived from metastases and liver parenchyma were compared. The mean ADC1 values of liver parenchyma and metastases were significantly higher than the mean ADC2 values (P < 0.0001, paired t-test). Colorectal metastases were found to have higher mean ADC1 and ADC2 values compared with liver (P < 0.0001, Mann-Whitney test). However, the estimated F was found to be lower in metastases compared to liver (P = 0.03, Mann-Whitney test). Colorectal hepatic metastases were characterised by higher ADC1 and ADC2 values, but lower F values compared to liver.
There is a need to develop methods that reliably quantify characteristics associated with vulnerable carotid plaque. Greyscale median (GSM) and shear wave elastography (SWE) are two techniques that ...may improve individual plaque risk stratification. SWE, which quantifies Young's Modulus (YM) to estimate tissue stiffness, has been researched in the liver, breast, thyroid and prostate, but its use in carotid plaques is novel.
The aim of this study was to quantify YM and GSM of plaques and compare to histology. 25 patients (64% male) with a mean age of 76 underwent both clinical and SWE imaging. The mean GSM was quantified over a cardiac cycle. The mean YM was quantified in multiple regions within the plaque over 5 frames. Histological features were assessed following carotid endarterectomy.
The mean YM of unstable plaques was significantly lower than that of stable plaques (50.0 kPa vs. 79.1 kPa; p = 0.027). The presence of intra-plaque hemorrhage, thrombus and increasing numbers of foam cells was also associated with a significantly lower YM. Plaque YM did not correlate well with plaque GSM (r = .12). The mean plaque GSM was the same in both unstable and stable plaques. Fibrous plaques had a significantly higher GSM (p = 0.036).
In conclusion, SWE provides additional information on plaque stiffness which may be of clinical benefit to help identify vulnerable plaque, and warrants further study.
The purpose of this study was to determine the efficacy of a novel ultrasound-based carotid plaque risk index (CPRI) in predicting the presence of cerebrovascular symptoms in patients with carotid ...artery stenosis.
This was a cross-sectional, observational study involving 56 patients (mean age 76.6 years, 62.5 % male). Plaque grayscale median (GSM) and surface irregularity indices (SII) were measured in 82 stenosed carotid arteries (range 10 - 95 %) and combined with the degree of stenosis (DOS) in the form of (DOS*SII)/(1 + GSM). A reduced index DOS/(1 + GSM) not incorporating plaque surface irregularities was also investigated. Receiver operating characteristic curves (ROC) were used to study the diagnostic efficacy of CPRI, comparing against DOS and an equivalent risk index constructed using a conventional logistic regression based method with model parameters optimized to the dataset (CPRIlogistic).
There were 42 stenosed carotid arteries with cerebrovascular symptoms, and 40 without symptoms. The presence of symptoms significantly correlated with DOS, GSM and SII (p < 0.01). The median CPRI of the symptomatic (asymptomatic) groups were 23.2 (9.2) compared with 0.71 (0.30) for CPRIlogistic (p < 0.01). The diagnostic performance of CPRI exceeded that of CPRIlogistic and DOS, and demonstrated a better separation of the symptomatic and asymptomatic groups.
Our novel risk index combines quantitative measures of carotid plaque echogenicity and surface irregularities with the degree of stenosis. It is a better predictor of cerebrovascular symptoms than the degree of stenosis and could be valuable in studies and clinical trials aimed at identifying vulnerable carotid artery stenoses.
The frictional contact of elastic solids with thin and moderately thick coatings is analysed by using the finite element method. It is assumed that 2 elastic, homogeneous substrates with elastic ...coatings are perfectly bonded and contact with each other under normal and horizontal forces. The coating and elastic substrate are modelled with 2D and 3D finite elements. After verifying the finite element solutions by analytical solutions, various geometric configurations are analysed such as ball and socket joint, ball on a flat plate, a roller on a guide, and spur gear. Different material combinations and coating thicknesses are considered in the coating-substrate system. Their effects on the total displacement and contact stress distributions along the contact line of coated members are presented.
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