Thrombus computed tomography (CT) imaging characteristics may correspond with thrombus mechanical properties and thus predict thrombectomy success. The impact of red blood cell (RBC) content on these properties (imaging and mechanics) has been widely studied. However, the additional effect of platelets has not been considered. The objective of the current study was to examine the individual and combined effects of blood clot RBC and platelet content on resultant CT imaging and mechanical characteristics. Human blood clot analogues were prepared from a combination of preselected RBC volumes and platelet concentrations to decouple their contributions. The resulting clot RBC content (%) and platelet content (%) were determined using Martius Scarlet Blue and CD42b staining, respectively. Non-contrast and contrast-enhanced CT (NCCT and CECT) scans were performed to measure the clot densities. CECT density increase was taken as a proxy for clinical perviousness. Unconfined compressive mechanics were analysed by performing 10 cycles of 80% strain. RBC content is the major determinant of clot NCCT density. However, additional consideration of the platelet content improves the association. CECT density increase is influenced by clot platelet and not RBC content. Platelet content is the dominant component driving clot stiffness, especially at high strains. Both RBC and platelet content contribute to the clot’s viscoelastic and plastic compressive properties. The current in vitro results suggest that CT density is reflective of RBC content and subsequent clot viscoelasticity and plasticity, and that perviousness reflects the clot’s platelet content and subsequent stiffness. However, these indications should be confirmed in a clinical stroke cohort.

Background: X-ray digital subtraction angiography (DSA) is the imaging modality for peri-procedural guidance and treatment evaluation in (neuro-) vascular interventions. Perfusion image construction from DSA, as a means of quantitatively depicting cerebral hemodynamics, has been shown feasible. However, the quantitative property of perfusion DSA has not been well studied. Purpose: To comparatively study the independence of deconvolution-based perfusion DSA with respect to varying injection protocols, as well as its sensitivity to alterations in brain conditions. Methods: We developed a deconvolution-based algorithm to compute perfusion parametric images from DSA, including cerebral blood volume (CBV (Figure presented.)), cerebral blood flow (CBF (Figure presented.)), time to maximum (Tmax), and mean transit time (MTT (Figure presented.)) and applied it to DSA sequences obtained from two swine models. We also extracted the time intensity curve (TIC)-derived parameters, that is, area under the curve (AUC), peak concentration of the curve, and the time to peak (TTP) from these sequences. Deconvolution-based parameters were quantitatively compared to TIC-derived parameters in terms of consistency upon variations in injection profile and time resolution of DSA, as well as sensitivity to alterations of cerebral condition. Results: Comparing to TIC-derived parameters, the standard deviation (SD) of deconvolution-based parameters (normalized with respect to the mean) are two to five times smaller, indicating that they are more consistent across different injection protocols and time resolutions. Upon ischemic stroke induced in a swine model, the sensitivities of deconvolution-based parameters are equal to, if not higher than, those of TIC-derived parameters. Conclusions: In comparison to TIC-derived parameters, deconvolution-based perfusion imaging in DSA shows significantly higher quantitative reliability against variations in injection protocols across different time resolutions, and is sensitive to alterations in cerebral hemodynamics. The quantitative nature of perfusion angiography may allow for objective treatment assessment in neurovascular interventions.

Extracting the cerebral anterior vessel tree of patients with an intracranial large vessel occlusion (LVO) is relevant to investigate potential biomarkers that can contribute to treatment decision making. The purpose of our work is to develop a method that can achieve this from routinely acquired computed tomography angiography (CTA) and computed tomography perfusion (CTP) images. To this end, we regard the anterior vessel tree as a set of bifurcations and connected centerlines. The method consists of a proximal policy optimization (PPO) based deep reinforcement learning (DRL) approach for tracking centerlines, a convolutional neural network based bifurcation detector, and a breadth-first vessel tree construction approach taking the tracking and bifurcation detection results as input. We experimentally determine the added values of various components of the tracker. Both DRL vessel tracking and CNN bifurcation detection were assessed in a cross validation experiment using 115 subjects. The anterior vessel tree formation was evaluated on an independent test set of 25 subjects, and compared to interobserver variation on a small subset of images. The DRL tracking result achieves a median overlapping rate until the first error (1.8 mm off the reference standard) of 100, [46, 100] % on 8032 vessels over 115 subjects. The bifurcation detector reaches an average recall and precision of 76% and 87% respectively during the vessel tree formation process. The final vessel tree formation achieves a median recall of 68% and precision of 70%, which is in line with the interobserver agreement.

Endovascular thrombectomy procedures are significantly influenced by the mechanical response of thrombi to the multi-axial loading imposed during retrieval. Compression tests are commonly used to determine compressive ex vivo thrombus and clot analogue stiffness. However, there is a shortage of data in tension. This study compares the tensile and compressive response of clot analogues made from the blood of healthy human donors in a range of compositions. Citrated whole blood was collected from six healthy human donors. Contracted and non-contracted fibrin clots, whole blood clots and clots reconstructed with a range of red blood cell (RBC) volumetric concentrations (5–80%) were prepared under static conditions. Both uniaxial tension and unconfined compression tests were performed using custom-built setups. Approximately linear nominal stress–strain profiles were found under tension, while strong strain-stiffening profiles were observed under compression. Low- and high-strain stiffness values were acquired by applying a linear fit to the initial and final 10% of the nominal stress–strain curves. Tensile stiffness values were approximately 15 times higher than low-strain compressive stiffness and 40 times lower than high-strain compressive stiffness values. Tensile stiffness decreased with an increasing RBC volume in the blood mixture. In contrast, high-strain compressive stiffness values increased from 0 to 10%, followed by a decrease from 20 to 80% RBC volumes. Furthermore, inter-donor differences were observed with up to 50% variation in the stiffness of whole blood clot analogues prepared in the same manner between healthy human donors.

Background and aims: Atherosclerotic plaque onset and progression are known to be affected by local biomechanical factors. While the role of wall shear stress (WSS) has been studied, the impact of another biomechanical factor, namely mechanical wall stress (MWS), remains poorly understood. In this study, we investigated the association of MWS, independently and combined with WSS, towards atherosclerosis in coronary arteries. Methods: Thirty-four human coronary arteries were analyzed using near-infrared spectroscopy intravascular ultrasound (NIRS-IVUS) and optical coherence tomography (OCT) at baseline and after 12 months. Baseline WSS and MWS were calculated using computational models, and wall thickness (ΔWT) and lipid-rich necrotic core size (ΔLRNC) change were measured in non-calcified coronary segments. The arteries were further divided into 1.5 mm/45° sectors and categorized as plaque-free or plaque sectors. For each category, associations between biomechanical factors (WSS & MWS) and changes in coronary wall (ΔWT & ΔLRNC) were studied using linear mixed models. Results: In plaque-free sectors, higher MWS (p < 0.001) was associated with greater vessel wall growth. Plaque sectors demonstrated wall thickness reduction over time, likely due to medical therapy, where higher levels of WSS and WMS, individually and combined, (p < 0.05) were associated with a greater reduction. Sectors with low MWS combined with high WSS demonstrated the highest LRNC increase (p < 0.01). Conclusions: In this study, we investigated the association of the (largely-overlooked) biomechanical factor MWS with coronary atherosclerosis, individually and combined with WSS. Our results demonstrated that both MWS and WSS significantly correlate with atherosclerotic plaque initiation and development.

Background: Accumulating evidence highlights the existence of distinct morphological subtypes of intracranial carotid arteriosclerosis. So far, little is known on the prevalence of these subtypes and subsequent stroke risk in the general population. We determined the prevalence of morphological subtypes of intracranial arteriosclerosis and assessed the risk of stroke associated with these subtypes. Methods: Between 2003 and 2006, 2391 stroke-free participants (mean age 69.6, 51.7% women) from the population-based Rotterdam Study underwent noncontrast computed tomography to visualize calcification in the intracranial carotid arteries as a proxy for intracranial arteriosclerosis. Calcification morphology was evaluated according to a validated grading scale and categorized into intimal, internal elastic lamina (IEL), or mixed subtype. Follow-up for stroke was complete until January 1, 2016. We used multivariable Cox regression to assess associations of each subtype with incident stroke. Results: The prevalence of calcification was 82% of which 39% had the intimal subtype, 48% IEL subtype, and 13% a mixed subtype. During a median follow-up of 10.4 years, 155 participants had a stroke. All 3 subtypes were associated with a higher risk of stroke (adjusted hazard ratio [95% CI] for intimal: 2.11 [1.07-4.13], IEL: 2.66 [1.39-5.11], and mixed subtype 2.57 [1.18-5.61]). The association of the IEL subtype with stroke was strongest among older participants. The association of the intimal subtype with stroke was noticeably stronger in women than in men. Conclusions: Calcification of the IEL was the most prevalent subtype of intracranial arteriosclerosis. All 3 subtypes were associated with an increased risk of stroke, with noticeable age and sex-specific differences.

Purpose: The assessment of collateral status may depend on the timing of image acquisition. The purpose of this study is to investigate whether there are optimal time points in CT Perfusion (CTP) for collateral status assessment, and compare collaterals scores at these time points with collateral scores from multiphase CT angiography (mCTA). Methods: Patients with an acute intracranial occlusion who underwent baseline non-contrast CT, mCTA and CT perfusion were selected. Collateral status was assessed using an automatically computed Collateral Ratio (CR) score in mCTA, and predefined time points in CTP acquisition. CRs extracted from CTP were correlated with CRs from mCTA. In addition, all CRs were related to baseline National Institutes of Health Stroke Scale (NIHSS) and Alberta Stoke Program Early CT Score (ASPECTS) with linear regression analysis to find the optimal CR. Results: In total 58 subjects (median age 74 years; interquartile range 61–83 years; 33 male) were included. When comparing the CRs from the CTP vs. mCTA acquisition, the strongest correlations were found between CR from baseline mCTA and the CR at the maximal intensity projection of time-resolved CTP (r = 0.81) and the CR at the peak of arterial enhancement point (r = 0.78). Baseline mCTA-derived CR had the highest correlation with ASPECTS (β = 0.36 (95%CI 0.11, 0.61)) and NIHSS (β = − 0.48 (95%CI − 0.72, − 0.16)). Conclusion: Collateral status assessment strongly depends on the timing of acquisition. Collateral scores obtained from mCTA imaging is close to the optimal collateral score obtained from CTP imaging.

Structural brain markers are studied extensively in the field of neurodegeneration, but are thought to occur rather late in the process. Functional measures such as functional connectivity are gaining interest as potentially more subtle markers of neurodegeneration. However, brain structure and function are also affected by ‘normal’ brain ageing. More information is needed on how functional connectivity relates to aging, particularly in the absence of overt neurodegenerative disease. We investigated the association of age with resting-state functional connectivity in 2878 non-demented persons between 50 and 95 years of age (54.1% women) from the population-based Rotterdam Study. We obtained nine well-known resting state networks using data-driven methodology. Within the anterior default mode network, ventral attention network, and sensorimotor network, functional connectivity was significantly lower with older age. In contrast, functional connectivity was higher with older age within the visual network. Between resting state networks, we found patterns of both increases and decreases in connectivity in approximate equal proportions. Our results reinforce the notion that the aging brain undergoes a reorganization process, and serves as a solid basis for exploring functional connectivity as a preclinical marker of neurodegenerative disease.

Introduction: Typical brain development is characterized by specific patterns of maturation of functional networks. Cortico-cortical connectivity generally increases, whereas subcortico-cortical connections often decrease. Little is known about connectivity changes amongst different subcortical regions in typical development. Methods: This study examined age- and gender-related differences in functional connectivity between and within cortical and subcortical regions using two different approaches. The participants included 411 six- to ten-year-old typically developing children sampled from the population-based Generation R study. Functional connectomes were defined in native space using regions of interest from subject-specific FreeSurfer segmentations. Connections were defined as: (a) the correlation between regional mean time-series; and (b) the focal maximum of voxel-wise correlations within FreeSurfer regions. The association of age and gender with each functional connection was determined using linear regression. The preprocessing included the exclusion of children with excessive head motion and scrubbing to reduce the influence of minor head motion during scanning. Results: Cortico-cortical associations echoed previous findings that connectivity shifts from short to long-range with age. Subcortico-cortical associations with age were primarily negative in the focal network approach but were both positive and negative in the mean time-series network approach. Between subcortical regions, age-related associations were negative in both network approaches. Few connections had significant associations with gender. Conclusions: The present study replicates previously reported age-related patterns of connectivity in a relatively narrow age-range of children. In addition, we extended these findings by demonstrating decreased connectivity within the subcortex with increasing age. Lastly, we show the utility of a more focal approach that challenges the spatial assumptions made by the traditional mean time series approach.

Objectives: To assesses whether automated brain image analysis with quantification of structural brain changes improves diagnostic accuracy in a memory clinic setting. Methods: In 42 memory clinic patients, we evaluated whether automated quantification of brain tissue volumes, hippocampal volume and white matter lesion volume improves diagnostic accuracy for Alzheimer's disease (AD) and frontotemporal dementia (FTD), compared to visual interpretation. Reference data were derived from a dementia-free aging population (n = 4915, aged >45 years), and were expressed as age- and sex-specific percentiles. Experienced radiologists determined the most likely imaging-based diagnosis based on structural brain MRI using three strategies (visual assessment of MRI only, quantitative normative information only, or a combination of both). Diagnostic accuracy of each strategy was calculated with the clinical diagnosis as the reference standard. Results: Providing radiologists with only quantitative data decreased diagnostic accuracy both for AD and FTD compared to conventional visual rating. The combination of quantitative with visual information, however, led to better diagnostic accuracy compared to only visual ratings for AD. This was not the case for FTD. Conclusion: Quantitative assessment of structural brain MRI combined with a reference standard in addition to standard visual assessment may improve diagnostic accuracy in a memory clinic setting.

Purpose: To investigate the association between N-terminal pro-Btype natriuretic peptide (NT-proBNP), which is a marker of heart disease, and markers of subclinical brain damage on magnetic resonance (MR) images in community-dwelling middle-aged and elderly subjects without dementia and without a clinical diagnosis of heart disease. Materials and Methods: This prospective population-based cohort study was approved by a medical ethics committee overseen by the national government, and all participants gave written informed consent. Serum levels of NT-proBNP were measured in 2397 participants without dementia or stroke (mean age, 56.6 years; age range, 45.7-87.3 years) and without clinical diagnosis of heart disease who were drawn from the population-based Rotterdam Study. All participants were examined with a 1.5-T MR imager. Multivariable linear and logistic regression analyses were used to investigate the association between NT-proBNP level and MR imaging markers of subclinical brain damage, including volumetric, focal, and microstructural markers. Results: A higher NT-proBNP level was associated with smaller total brain volume (mean difference in z score per standard deviation increase in NT-proBNP level, -0.021; 95% confidence interval [CI]: -0.034, -0.007; P = .003) and was predominantly driven by gray matter volume (mean difference in z score per standard deviation increase in NT-proBNP level, -0.037; 95% CI: -0.057, -0.017; P < .001). Higher NT-proBNP level was associated with larger white matter lesion volume (mean difference in z score per standard deviation increase in NT-proBNP level, 0.090; 95% CI: 0.051, 0.129; P < .001), with lower fractional anisotropy (mean difference in z score per standard deviation increase in NT-proBNP level, -0.048; 95% CI: -0.088, -0.008; P = .019) and higher mean diffusivity (mean difference in z score per standard deviation increase in NT-proBNP level, 0.054; 95% CI: 0.018, 0.091; P = .004) of normal-appearing white matter. Conclusion: In community-dwelling persons, higher serum NT-proBNP levels are associated with volumetric and microstructural MR imaging markers of subclinical brain damage.