Activity and Expression of Carboxylesterases and Arylacetamide Deacetylase in Human Ocular Tissues.

As a multitissue organ, the eye possesses unique anatomy and physiology, including differential expression of drug-metabolizing enzymes. Several hydrolytic enzymes that play a major role in drug metabolism and bioactivation of prodrugs have been detected in ocular tissues, but data on their quantitative expression is scarce. Also, many ophthalmic drugs are prone to hydrolysis. Metabolic characterization of individual ocular tissues is useful for the drug development process, and therefore, seven individual ocular tissues from human eyes were analyzed for the activity and expression of carboxylesterases (CESs) and arylacetamide deacetylase (AADAC). Generic and selective human esterase substrates 4-nitrophenyl acetate (most esterases), D-luciferin methyl ester (CES1), fluorescein diacetate and procaine (CES2), and phenacetin (AADAC) were applied to determine the enzymes' specific activities. Enzyme kinetics and inhibition studies were performed with isoform-selective inhibitors digitonin (CES1) and verapamil and diltiazem (CES2). Enzyme contents were determined using quantitative targeted proteomics, and CES2 expression was confirmed by western blotting. The expression and activity of human CES1 among ocular tissues varied by >10-fold, with the highest levels found in the retina and iris-ciliary body. In contrast, human CES2 expression appeared lower and more similar between tissues, whereas AADAC could not be detected. Inhibition studies showed that hydrolysis of fluorescein diacetate is also catalyzed by enzymes other than CES2. This study provides, for the first time, quantitative information on the tissue-dependent expression of human ocular esterases, which can be useful for the development of ocular drugs, prodrugs, and in pharmacokinetic modeling of the eye. SIGNIFICANCE STATEMENT: Novel and comprehensive data on the protein expression and activities of carboxylesterases from individual human eye tissues are generated. In combination with previous reports on preclinical species, this study will improve the understanding of interspecies differences in ocular drug metabolism and aid the development of ocular pharmacokinetics models.

Carboxylesterase Activities and Protein Expression in Rabbit and Pig Ocular Tissues.

Hydrolytic reactions constitute an important pathway of drug metabolism and a significant route of prodrug activation. Many ophthalmic drugs and prodrugs contain ester groups that greatly enhance their permeation across several hydrophobic barriers in the eye before the drugs are either metabolized or released, respectively, via hydrolysis. Thus, the development of ophthalmic drug therapy requires the thorough profiling of substrate specificities, activities, and expression levels of ocular esterases. However, such information is scant in the literature, especially for preclinical species often used in ophthalmology such as rabbits and pigs. Therefore, our aim was to generate systematic information on the activity and expression of carboxylesterases (CESs) and arylacetamide deacetylase (AADAC) in seven ocular tissue homogenates from these two species. The hydrolytic activities were measured using a generic esterase substrate (4-nitrophenyl acetate) and, in the absence of validated substrates for rabbit and pig enzymes, with selective substrates established for human CES1, CES2, and AADAC (d-luciferin methyl ester, fluorescein diacetate, procaine, and phenacetin). Kinetics and inhibition studies were conducted using these substrates and, again due to a lack of validated rabbit and pig CES inhibitors, with known inhibitors for the human enzymes. Protein expression levels were measured using quantitative targeted proteomics. Rabbit ocular tissues showed significant variability in the expression of CES1 (higher in cornea, lower in conjunctiva) and CES2 (higher in conjunctiva, lower in cornea) and a poor correlation of CES expression with hydrolytic activities. In contrast, pig tissues appear to express only CES1, and CES3 and AADAC seem to be either low or absent, respectively, in both species. The current study revealed remarkable species and tissue differences in ocular hydrolytic enzymes that can be taken into account in the design of esterase-dependent prodrugs and drug conjugates, the evaluation of ocular effects of systemic drugs, and in translational and toxicity studies.

Tandem mass spectrometric analysis of S- and N-linked glutathione conjugates of pulegone and menthofuran and identification of P450 enzymes mediating their formation.

RATIONALE: Menthofuran is a hepatotoxin and a major metabolite of pulegone, a monoterpene found in the essential oils of many mint species. It is bioactivated by cytochrome P450 (CYP) enzymes to reactive metabolites, which may further react with glutathione to form S-linked and N-linked conjugates. The tandem mass spectrometric (MS/MS) fragmentation pathways of rarely observed N-linked conjugates, and the differences to fragmentation of S-linked conjugates, have not been reported in the literature previously, although this information is essential to enable comprehensive MS/MS-based screening methods covering the both types of conjugates. METHODS: (R)-(+)-Pulegone, (S)-(-)-pulegone, and menthofuran were incubated with a human liver S9 fraction with glutathione (GSH) as the trapping agent. Conjugates were searched with ultra-performance liquid chromatography (UPLC)/orbitrap MS and their MS/MS spectra were measured both in the negative and positive ionization polarities. Menthofuran was also incubated with recombinant human CYP enzymes and GSH to elucidate the CYPs responsible for the formation of the reactive metabolites. RESULTS: Four GSH conjugates of menthofuran were detected and identified as S- and N-linked conjugates based on MS/MS spectra. N-linked conjugates lacked the characteristic fragments of S-linked conjugates and commonly produced fragments that retained parts of glutamic acid. CYP1A2, 2B6 and 3A4 were observed to produce more GSH conjugates than other CYP isoforms. CONLUSIONS: Furans can form reactive aldehydes that react in Schiff-base fashion with the free glutamyl-amine of GSH to form N-linked conjugates that have distinct MS/MS spectra from S-linked adducts. This should be taken into account when setting up LC/MS/MS-based detection of glutathione conjugates to screen for reactive metabolites, at least for compounds with a furan moiety. Neutral loss scanning of 178.0412 Da and 290.0573 Da in the positive ionization mode, or neutral loss scanning of 256.0695 Da and 290.0573 Da and precursor ion scanning of m/z 143.0462 in the negative ionization mode, is recommended. Copyright © 2016 John Wiley & Sons, Ltd.

Toxicity of Carboxylic Acid-Containing Drugs: The Role of Acyl Migration and CoA Conjugation Investigated.

Many carboxylic acid-containing drugs are associated with idiosyncratic drug toxicity (IDT), which may be caused by reactive acyl glucuronide metabolites. The rate of acyl migration has been earlier suggested as a predictor of acyl glucuronide reactivity. Additionally, acyl Coenzyme A (CoA) conjugates are known to be reactive. Here, 13 drugs with a carboxylic acid moiety were incubated with human liver microsomes to produce acyl glucuronide conjugates for the determination of acyl glucuronide half-lives by acyl migration and with HepaRG cells to monitor the formation of acyl CoA conjugates, their further conjugate metabolites, and trans-acylation products with glutathione. Additionally, in vitro cytotoxicity and mitochondrial toxicity experiments were performed with HepaRG cells to compare the predictability of toxicity. Clearly, longer acyl glucuronide half-lives were observed for safe drugs compared to drugs that can cause IDT. Correlation between half-lives and toxicity classification increased when "relative half-lives," taking into account the formation of isomeric AG-forms due to acyl migration and eliminating the effect of hydrolysis, were used instead of plain disappearance of the initial 1-O-ß-AG-form. Correlation was improved further when a daily dose of the drug was taken into account. CoA and related conjugates were detected primarily for the drugs that have the capability to cause IDT, although some exceptions to this were observed. Cytotoxicity and mitochondrial toxicity did not correlate to drug safety. On the basis of the results, the short relative half-life of the acyl glucuronide (high acyl migration rate), high daily dose and detection of acyl CoA conjugates, or further metabolites derived from acyl CoA together seem to indicate that carboxylic acid-containing drugs have a higher probability to cause drug-induced liver injury (DILI).

Glutathione trapping of reactive drug metabolites produced by biomimetic metalloporphyrin catalysts.

RATIONALE: Metalloporphyrins can be useful in the production of drug metabolites, as they enable easier production of oxidative metabolites usually produced by the cytochrome P450 enzymes. Our aim was to test metalloporphyrin-based biomimetic oxidation (BMO) methods for production and S-glutathione trapping of reactive drug metabolites in addition to phase I metabolites. METHODS: Clozapine, ticlopidine and citalopram were selected as model compounds. These were incubated with the BMO assay and the incubations were analyzed with high-resolution liquid chromatography/mass spectrometry (LC/MS) and tandem mass spectrometry (LC/MS/MS). Additionally, incubations with human liver S9 fraction were performed to compare the results with the BMO assay. RESULTS: Six glutathione conjugates were identified for clozapine from the S9 incubation, while the BMO assay produced four of these. Four out of the five phase I metabolites produced by S9 were detected using the BMO assay. For ticlopidine, four glutathione conjugates were detected from the S9 incubation, but none of these were observed using the BMO assay. Eight of the nine phase I metabolites produced by S9 incubation were detected in the BMO assay. As expected, no glutathione conjugates were detected for citalopram, and the same three phase I metabolites were detected in both S9 and BMO incubations. CONLUSIONS: Differences in formation of GSH-trapped reactive metabolites by BMO assay between clozapine and ticlopidine are probably due to different reactive intermediates and reaction mechanisms. The reactive intermediate of clozapine, the nitrenium ion was generated, but the reactive intermediates of ticlopidine, S-oxide and epoxide, were not detected from the incubations. However, the results show that for selected cases the use of biomimetic assays can be used to produce high amounts of S-glutathione conjugates identical to those from liver subfraction incubations, on a scale that is relevant for purification and subsequent identification by NMR spectroscopy; which is often difficult using incubations with liver subfractions.

Accelerated simulation methodologies for computational vascular flow modelling.

Vascular flow modelling can improve our understanding of vascular pathologies and aid in developing safe and effective medical devices. Vascular flow models typically involve solving the nonlinear Navier-Stokes equations in complex anatomies and using physiological boundary conditions, often presenting a multi-physics and multi-scale computational problem to be solved. This leads to highly complex and expensive models that require excessive computational time. This review explores accelerated simulation methodologies, specifically focusing on computational vascular flow modelling. We review reduced order modelling (ROM) techniques like zero-/one-dimensional and modal decomposition-based ROMs and machine learning (ML) methods including ML-augmented ROMs, ML-based ROMs and physics-informed ML models. We discuss the applicability of each method to vascular flow acceleration and the effectiveness of the method in addressing domain-specific challenges. When available, we provide statistics on accuracy and speed-up factors for various applications related to vascular flow simulation acceleration. Our findings indicate that each type of model has strengths and limitations depending on the context. To accelerate real-world vascular flow problems, we propose future research on developing multi-scale acceleration methods capable of handling the significant geometric variability inherent to such problems.

Reduced order modelling of intracranial aneurysm flow using proper orthogonal decomposition and neural networks.

Reduced order modelling (ROMs) methods, such as proper orthogonal decomposition (POD), systematically reduce the dimensionality of high-fidelity computational models and potentially achieve large gains in execution speed. Machine learning (ML) using neural networks has been used to overcome limitations of traditional ROM techniques when applied to nonlinear problems, which has led to the recent development of reduced order models augmented by machine learning (ML-ROMs). However, the performance of ML-ROMs is yet to be widely evaluated in realistic applications and questions remain regarding the optimal design of ML-ROMs. In this study, we investigate the application of a non-intrusive parametric ML-ROM to a nonlinear, time-dependent fluid dynamics problem in a complex 3D geometry. We construct the ML-ROM using POD for dimensionality reduction and neural networks for interpolation of the ROM coefficients. We compare three different network designs in terms of approximation accuracy and performance. We test our ML-ROM on a flow problem in intracranial aneurysms, where flow variability effects are important when evaluating rupture risk and simulating treatment outcomes. The best-performing network design in our comparison used a two-stage POD reduction, a technique rarely used in previous studies. The best-performing ROM achieved mean test accuracies of 98.6% and 97.6% in the parent vessel and the aneurysm, respectively, while providing speed-up factors of the order 10 5 $$ {10}^5 $$ .

Extrahepatic in vitro metabolism of peptides; comparison of human kidney and intestinal S9 fraction, human plasma and proximal tubule cells, using cyclosporine A, leuprorelin, and cetrorelix as model compounds.

Peptide therapeutics showcase number of advantages compared to the traditional small molecule drugs, e,g. they usually have higher affinity to target and lower toxicity profiles. Endogenous peptides are mostly cleared from the body through renal clearance or proteolytic hydrolysis. As a part of drug discovery, metabolite identification is an important part in their development to identify metabolic hot spots and to further improve their stability. As the catabolism of the peptides and peptide-like drugs is often considered to be extrahepatic, the use of in vitro systems derived from these organs might be beneficial. In this study, multiple extrahepatic metabolic systems were evaluated for the applicability for peptide metabolism studies. Three peptide drugs (leuprorelin, cetrorelix, cyclosporin) were incubated in kidney and intestinal S9 fraction ( ± NADPH), fresh plasma (anticoagulants EDTA and heparin separately), and plated proximal tubule cells. Additionally, leuprorelin was also incubated with human kidney microsomes and cytosol to further investigate the NADPH-dependent metabolism detected in kidney S9 fraction. Both substrate disappearance and metabolite formation were monitored, using UPLC/HR-MS analysis of the collected samples.Overall, the largest number of metabolites was formed in the incubation with kidney S9 fraction, followed by intestinal S9, while incubations with proximal tubule cells produced lower number of metabolites All investigated peptides were stable in plasma and only a few metabolites were detected, likely because the studied peptide drugs have been optimized to be stable in plasma. Leuprorelin showed NADPH-dependent metabolite formation in kidney S9 fraction, while the metabolism of cetrorelix was more NADPH independent. As expected, formation of cytochrome P450 (CYP) catalyzed metabolism of cyclosporine was not observed with the employed extrahepatic systems. The NADPH-dependent metabolism of leuprorelin was detected also in the incubation with kidney cytosol, but not with kidney microsomes, and was thus not caused by CYPs or FMOs, but with cytosolic NADPH-dependent drug metabolizing enzymes. These enzymes could, in principle, activate the amide bond via reductive or oxidative metabolism outside the amide bond. The identity of the involved drug metabolizing enzymes in this process is still unknown.

Virtual high-resolution MR angiography from non-angiographic multi-contrast MRIs: synthetic vascular model populations for in-silico trials.

Despite success on multi-contrast MR image synthesis, generating specific modalities remains challenging. Those include Magnetic Resonance Angiography (MRA) that highlights details of vascular anatomy using specialised imaging sequences for emphasising inflow effect. This work proposes an end-to-end generative adversarial network that can synthesise anatomically plausible, high-resolution 3D MRA images using commonly acquired multi-contrast MR images (e.g. T1/T2/PD-weighted MR images) for the same subject whilst preserving the continuity of vascular anatomy. A reliable technique for MRA synthesis would unleash the research potential of very few population databases with imaging modalities (such as MRA) that enable quantitative characterisation of whole-brain vasculature. Our work is motivated by the need to generate digital twins and virtual patients of cerebrovascular anatomy for in-silico studies and/or in-silico trials. We propose a dedicated generator and discriminator that leverage the shared and complementary features of multi-source images. We design a composite loss function for emphasising vascular properties by minimising the statistical difference between the feature representations of the target images and the synthesised outputs in both 3D volumetric and 2D projection domains. Experimental results show that the proposed method can synthesise high-quality MRA images and outperform the state-of-the-art generative models both qualitatively and quantitatively. The importance assessment reveals that T2 and PD-weighted images are better predictors of MRA images than T1; and PD-weighted images contribute to better visibility of small vessel branches towards the peripheral regions. In addition, the proposed approach can generalise to unseen data acquired at different imaging centres with different scanners, whilst synthesising MRAs and vascular geometries that maintain vessel continuity. The results show the potential for use of the proposed approach to generating digital twin cohorts of cerebrovascular anatomy at scale from structural MR images typically acquired in population imaging initiatives.

Aldehyde oxidase 1 activity and protein expression in human, rabbit, and pig ocular tissues.

Aldehyde oxidase (AOX) is a cytosolic drug-metabolizing enzyme which has attracted increasing attention in drug development due to its high hepatic expression, broad substrate profile and species differences. In contrast, there is limited information on the presence and activity of AOX in extrahepatic tissues including ocular tissues. Because several ocular drugs are potential substrates for AOX, we performed a comprehensive analysis of the AOX1 expression and activity profile in seven ocular tissues from humans, rabbits, and pigs. AOX activities were determined using optimized assays for the established human AOX1 probe substrates 4-dimethylamino-cinnamaldehyde (DMAC) and phthalazine. Inhibition studies were undertaken in conjunctival and retinal homogenates using well-established human AOX1 inhibitors menadione and chlorpromazine. AOX1 protein contents were quantitated with targeted proteomics and confirmed by immunoblotting. Overall, DMAC oxidation rates varied over 10-fold between species (human ˃˃ rabbit ˃ pig) and showed 2- to 6-fold differences between tissues from the same species. Menadione seemed a more potent inhibitor of DMAC oxidation across species than chlorpromazine. Human AOX1 protein levels were highest in the conjunctiva, followed by most posterior tissues, whereas anterior tissues showed low levels. The rabbit AOX1 expression was high in the conjunctiva, retinal pigment epithelial (RPE), and choroid while lower in the anterior tissues. Quantification of pig AOX1 was not successful but immunoblotting confirmed the presence of AOX1 in all species. DMAC oxidation rates and AOX1 contents correlated quite well in humans and rabbits. This study provides, for the first time, insights into the ocular expression and activity of AOX1 among multiple species.

Hemodynamics of thrombus formation in intracranial aneurysms: An in silico observational study.

How prevalent is spontaneous thrombosis in a population containing all sizes of intracranial aneurysms? How can we calibrate computational models of thrombosis based on published data? How does spontaneous thrombosis differ in normo- and hypertensive subjects? We address the first question through a thorough analysis of published datasets that provide spontaneous thrombosis rates across different aneurysm characteristics. This analysis provides data for a subgroup of the general population of aneurysms, namely, those of large and giant size (>10 mm). Based on these observed spontaneous thrombosis rates, our computational modeling platform enables the first in silico observational study of spontaneous thrombosis prevalence across a broader set of aneurysm phenotypes. We generate 109 virtual patients and use a novel approach to calibrate two trigger thresholds: residence time and shear rate, thus addressing the second question. We then address the third question by utilizing this calibrated model to provide new insight into the effects of hypertension on spontaneous thrombosis. We demonstrate how a mechanistic thrombosis model calibrated on an intracranial aneurysm cohort can help estimate spontaneous thrombosis prevalence in a broader aneurysm population. This study is enabled through a fully automatic multi-scale modeling pipeline. We use the clinical spontaneous thrombosis data as an indirect population-level validation of a complex computational modeling framework. Furthermore, our framework allows exploration of the influence of hypertension in spontaneous thrombosis. This lays the foundation for in silico clinical trials of cerebrovascular devices in high-risk populations, e.g., assessing the performance of flow diverters in aneurysms for hypertensive patients.

In-silico trial of intracranial flow diverters replicates and expands insights from conventional clinical trials.

The cost of clinical trials is ever-increasing. In-silico trials rely on virtual populations and interventions simulated using patient-specific models and may offer a solution to lower these costs. We present the flow diverter performance assessment (FD-PASS) in-silico trial, which models the treatment of intracranial aneurysms in 164 virtual patients with 82 distinct anatomies with a flow-diverting stent, using computational fluid dynamics to quantify post-treatment flow reduction. The predicted FD-PASS flow-diversion success rates replicate the values previously reported in three clinical trials. The in-silico approach allows broader investigation of factors associated with insufficient flow reduction than feasible in a conventional trial. Our findings demonstrate that in-silico trials of endovascular medical devices can: (i) replicate findings of conventional clinical trials, and (ii) perform virtual experiments and sub-group analyses that are difficult or impossible in conventional trials to discover new insights on treatment failure, e.g. in the presence of side-branches or hypertension.

Population-specific modelling of between/within-subject flow variability in the carotid arteries of the elderly.

Computational fluid dynamics models are increasingly proposed for assisting the diagnosis and management of vascular diseases. Ideally, patient-specific flow measurements are used to impose flow boundary conditions. When patient-specific flow measurements are unavailable, mean values of flow measurements across small cohorts are used as normative values. In reality, both the between-subjects and within-subject flow variabilities are large. Consequently, neither one-shot flow measurements nor mean values across a cohort are truly indicative of the flow regime in a given person. We develop models for both the between-subjects and within-subject variability of internal carotid flow. A log-linear mixed effects model is combined with a Gaussian process to model the between-subjects flow variability, while a lumped parameter model of cerebral autoregulation is used to model the within-subject flow variability in response to heart rate and blood pressure changes. The model parameters are identified from carotid ultrasound measurements in a cohort of 103 elderly volunteers. We use the models to study intracranial aneurysm flow in 54 subjects under rest and exercise and conclude that OSI, a common wall shear-stress derived quantity in vascular CFD studies, may be too sensitive to flow fluctuations to be a reliable biomarker.

A computational model for prediction of clot platelet content in flow-diverted intracranial aneurysms.

Treatment of intracranial aneurysms with flow-diverting stents is a safe and minimally invasive technique. The goal is stable embolisation that facilitates stent endothelialisation, and elimination of the aneurysm. However, it is not fully understood why some aneurysms fail to develop a stable clot even with sufficient levels of flow reduction. Computational prediction of thrombus formation dynamics can help predict the post-operative response in such challenging cases. In this work, we propose a new model of thrombus formation and platelet dynamics inside intracranial aneurysms. Our novel contribution combines platelet activation and transport with fibrin generation, which is key to characterising stable and unstable thrombus. The model is based on two types of thrombus inside aneurysms: red thrombus (fibrin- and erythrocyte-rich) can be found in unstable clots, while white thrombus (fibrin- and platelet-rich) can be found in stable clots. The thrombus generation model is coupled to a CFD model and the flow-induced platelet index (FiPi) is defined as a quantitative measure of clot stability. Our model is validated against an in vitro phantom study of two flow-diverting stents with different sizing. We demonstrate that our model accurately predicts the lower thrombus stability in the oversized stent scenario. This opens possibilities for using computational simulations to improve endovascular treatment planning and reduce adverse events, such as delayed haemorrhage of flow-diverted aneurysms.

Pharmacokinetics of intra-articular vitamin D analogue calcipotriol in sheep and metabolism in human synovial and mesenchymal stromal cells.

Calcipotriol (MC903) is a side chain analogue of the biologically active 1,25-dihydroxyvitamin D3 [1,25(OH)2D3]. Due to its anti-inflammatory and anti-proliferative effects on stromal cells, calcipotriol is a promising candidate for the local treatment of arthritis. In this preliminary work, we studied the pharmacokinetics and safety of calcipotriol after an IV (0.1 mg/kg given to one sheep) and intra-articular dose (0.054 mg/kg, 0.216 mg/kg and 0.560 mg/kg given to three sheep). The terminal half-life of calcipotriol was approximately 1 h after an IV dose. After intra-articular dosing, the systemic absorption was between 1 and 13% during the observed 24 h. Hypercalcemia or other clinical adverse effects did not occur in any animal during the study, and no macroscopic or microscopic alterations were seen in the synovium of the calcipotriol-injected knees compared to the vehicle knees. The in vitro metabolism of calcipotriol was analyzed with LC-MS from human synovial and mesenchymal stromal cell cultures. Both cell types were able to metabolize calcipotriol with MC1080 and MC1046 as the main metabolites. CYP24A1 transcripts were strongly induced by a 48-hour calcipotriol exposure in mesenchymal stromal cells, but not consistently in synovial stromal cells, as determined by RT-qPCR. Calcipotriol proved to be safe after a single intra-articular dose with applied concentrations, and it is metabolized by the cells of the joint. Slow dissolution of calcipotriol crystals in the joint can extend the pharmaceutical impact on the synovium, cartilage and subcortical bone.

Screening for Cognitive Impairment by Model-Assisted Cerebral Blood Flow Estimation.

OBJECTIVE: Alzheimer's disease (AD) is a progressive and debilitating neurodegenerative disease; a major health concern in the ageing population with an estimated prevalence of 46 million dementia cases worldwide. Early diagnosis is therefore crucial so mitigating treatments can be initiated at an early stage. Cerebral hypoperfusion has been linked with blood-brain barrier dysfunction in the early stages of AD, and screening for chronic cerebral hypoperfusion in individuals has been proposed for improving the early diagnosis of AD. However, ambulatory measurements of cerebral blood flow are not routinely carried out in the clinical setting. In this study, we combine physiological modeling with Holter blood pressure monitoring and carotid ultrasound imaging to predict 24-h cerebral blood flow (CBF) profiles in individuals. One hundred and three participants [53 with mild cognitive impairment (MCI) and 50 healthy controls] underwent model-assisted prediction of 24-h CBF. Model-predicted CBF and neuropsychological tests were features in lasso regression models for MCI diagnosis. RESULTS: A CBF-enhanced classifier for diagnosing MCI performed better, area-under-the-curve (AUC) = 0.889 (95%-CI: 0.800 to 0.978), than a classifier based only on the neuropsychological test scores, AUC = 0.818 (95%-CI: 0.643 to 0.992). An additional cohort of 25 participants (11 MCI and 14 healthy) was recruited to perform model validation by arterial spin-labeling magnetic resonance imaging, and to establish a link between measured CBF that predicted by the model. CONCLUSION: Ultrasound imaging and ambulatory blood pressure measurements enhanced with physiological modeling can improve MCI diagnosis accuracy.

Subject-specific multi-poroelastic model for exploring the risk factors associated with the early stages of Alzheimer's disease.

There is emerging evidence suggesting that Alzheimer's disease is a vascular disorder, caused by impaired cerebral perfusion, which may be promoted by cardiovascular risk factors that are strongly influenced by lifestyle. In order to develop an understanding of the exact nature of such a hypothesis, a biomechanical understanding of the influence of lifestyle factors is pursued. An extended poroelastic model of perfused parenchymal tissue coupled with separate workflows concerning subject-specific meshes, permeability tensor maps and cerebral blood flow variability is used. The subject-specific datasets used in the modelling of this paper were collected as part of prospective data collection. Two cases were simulated involving male, non-smokers (control and mild cognitive impairment (MCI) case) during two states of activity (high and low). Results showed a marginally reduced clearance of cerebrospinal fluid (CSF)/interstitial fluid (ISF), elevated parenchymal tissue displacement and CSF/ISF accumulation and drainage in the MCI case. The peak perfusion remained at 8 mm s-1 between the two cases.

Virtual endovascular treatment of intracranial aneurysms: models and uncertainty.

Virtual endovascular treatment models (VETMs) have been developed with the view to aid interventional neuroradiologists and neurosurgeons to pre-operatively analyze the comparative efficacy and safety of endovascular treatments for intracranial aneurysms. Based on the current state of VETMs in aneurysm rupture risk stratification and in patient-specific prediction of treatment outcomes, we argue there is a need to go beyond personalized biomechanical flow modeling assuming deterministic parameters and error-free measurements. The mechanobiological effects associated with blood clot formation are important factors in therapeutic decision making and models of post-treatment intra-aneurysmal biology and biochemistry should be linked to the purely hemodynamic models to improve the predictive power of current VETMs. The influence of model and parameter uncertainties associated to each component of a VETM is, where feasible, quantified via a random-effects meta-analysis of the literature. This allows estimating the pooled effect size of these uncertainties on aneurysmal wall shear stress. From such meta-analyses, two main sources of uncertainty emerge where research efforts have so far been limited: (1) vascular wall distensibility, and (2) intra/intersubject systemic flow variations. In the future, we suggest that current deterministic computational simulations need to be extended with strategies for uncertainty mitigation, uncertainty exploration, and sensitivity reduction techniques. WIREs Syst Biol Med 2017, 9:e1385. doi: 10.1002/wsbm.1385 For further resources related to this article, please visit the WIREs website.

Uncertainty quantification of wall shear stress in intracranial aneurysms using a data-driven statistical model of systemic blood flow variability.

Adverse wall shear stress (WSS) patterns are known to play a key role in the localisation, formation, and progression of intracranial aneurysms (IAs). Complex region-specific and time-varying aneurysmal WSS patterns depend both on vascular morphology as well as on variable systemic flow conditions. Computational fluid dynamics (CFD) has been proposed for characterising WSS patterns in IAs; however, CFD simulations often rely on deterministic boundary conditions that are not representative of the actual variations in blood flow. We develop a data-driven statistical model of internal carotid artery (ICA) flow, which is used to generate a virtual population of waveforms used as inlet boundary conditions in CFD simulations. This allows the statistics of the resulting aneurysmal WSS distributions to be computed. It is observed that ICA waveform variations have limited influence on the time-averaged WSS (TAWSS) on the IA surface. In contrast, in regions where the flow is locally highly multidirectional, WSS directionality and harmonic content are strongly affected by the ICA flow waveform. As a consequence, we argue that the effect of blood flow variability should be explicitly considered in CFD-based IA rupture assessment to prevent confounding the conclusions.