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Background: Dysfunctional cellular mechanosensing appears central to aneurysm formation [1]. We aimed to derive material parameters of aneurysm tissue from in vivo deformations, which may increase insight into the underlying structural integrity of the pathological tissue. Methods: Videos of tracking markers (example Video in supplement, screenshot in Figure) placed on ascending aortic segments were captured alongside radial arterial blood pressure in patients undergoing open-thorax ascending thoracic aorta aneurysm (ATAA) repair (n = 5) and coronary bypass (controls; n = 2). Normalised cross-correlation was used to determine marker displacements, resulting in estimates of systolic/diastolic diameters, distensibility, and cyclic axial engineering strain. A thin-walled, cylindrical geometry was assumed, with amorphous (Neo-Hookean) and fibrous (two-family) constitutive contributions [2]. This framework was fitted to individual patient measurements, by varying parameters c (amorphous material constant), k1 and k2 (fiber stiffness and strain stiffening parameter), β (fiber angle w.r.t. circumferential direction), unloaded intact length (L), and internal radius (Ri). FigureLeft: Example of ascending aortic region of interest with tracking markers. Right: Data presented as mean ± standard deviation. SBP/DBP, systolic/diastolic blood pressure. Estimated properties are defined in the text. Results: Axial strain tended to be lower (expected) and distensibility larger (unexpected) in aneurysm than controls (Figure). However, the intrinsic pressure-dependence of distensibility must be considered when drawing conclusions related to differences in structural stiffness between both groups [3]. Material stiffness parameters (c and k1) appeared higher in aneurysm patients than in controls which is in line with previous studies in mice [4]. Conclusion: We are developing a method to determine ATAA material properties from in vivo deformations and observed increased material stiffness in ATAA.

Background: Arterial stiffness is a strong predictor of cardiovascular diseases and all-cause mortality [1]. Increased fasting plasma concentrations of highly reactive dicarbonyl compounds – methylglyoxal (MGO), 3-deoxyglucosone (3-DG), and/or glyoxal (GO) – may cause arterial stiffening via for mation of advanced glycation endproducts, triggering maladaptive responses in vascular tissue, e.g. elastin degradation and collagen cross-linking [2]. We assessed the cross-sectional associations between MGO, 3-DG, and GO concentrations with local carotid stiffness measures (distensibility coefficient (cDC), radius-wall thickness ratio (cRWT), pulse wave velocity (cPWV), and Young’s elastic modulus (cE) using standardized main variables. Methods: Fasting dicarbonyl concentrations were determined by ultra-performance liquid chromatography tandem mass spectrometry in EDTA plasma collected from 2275 participants (age: 60 ± 8 years, mean ± SD; 49% women, 605 with type 2 diabetes mellitus) of the Maastricht Study [3], an observational, population-based cohort study. Cross-sectional associations were assessed using multivariable linear regression analysis adjusting for age, sex, mean arterial pressure (MAP), heart rate, lifestyle factors, and medication. Since arterial stiffness measures are intrinsically pressure dependent, we additionally assessed the associations with pressure-corrected counterparts [4], instead of statistically correcting for MAP. Results: Fasting dicarbonyl concentrations were associated with arterial stiffening (smaller cDC; larger cPWV and cE) in most crude models, but not in adjusted models (Table). cRWT was associated with 3-DG, but only in the crude model. The use of pressure-corrected metrics did not materially change the final models. Model cDC cRWT cPWV cE α (95% CI) α (95% CI) α (95% CI) α (95% CI) MGO 0 –0.104(–0.145;–0.063) 0.011(–0.030;0.052) 0.103(0.062;0.144) 0.099(0.059;0.140) 1 –0.032(–0.070;0.005) 0.010(–0.032;0.052) 0.032(–0.006;0.071) 0.033(–0.007;0.072) 2 0.005(–0.029;0.039) 0.000(–0.042;0.042) –0.004(–0.039;0.030) –0.006(–0.042;0.030) 3 0.003(–0.031;0.037) 0.000(–0. 043; 0.042) –0.003(–0.038;0.032) –0.005(–0.040;0.031) 3-DG 0 –0.164(–0.205;–0.123) 0.067(0.026;0.108) 0.149(0.108;0.190) 0.171(0.131;0.212) 1 –0.102(–0.154;–0.051) 0.024(–0. 033; 0.082) 0.075(0.023;0.127) 0.093(0.039;0.147) 2 –0.037(–0.084;0.009) 0.009(–0.049;0.066) 0.012(–0.036;0.060) 0.027(–0.023;0.076) 3 –0.018(–0.065;0.029) –0. 004(–0.062; 0.054) –0.007(–0.056;0.041) 0.004(–0.045;0.054) GO 0 –0.054(–0.095;–0.013) –0.032(–0.074;0.009) 0.054(0.012;0.095) 0.038(–0.003;0.079) 1 –0.015(–0.051;0.022) –0.014(–0.055; 0.026) 0.015(–0.022;0.052) 0.008(–0.030;0.046) 2 0.002(–0.031;0.035) –0.015(–0.056;0.025) –0.002(–0.035;0.032) –0.008(–0. 042;0. 027) 3 –0.009(–0.042;0.024) –0.013(–0.053; 0.028) 0.011(–0.022;0.045) 0.005(–0.030;0.040) Model 0: crude associations. Model 1: model 0 + age, sex, and glucose metabolism status. Model 2: model 1 + mean arterial pressure and mean heart rate, and anti-hypertensive drugs. Model 3: model 2 + body mass index, smoking status, physical activity, use of lipid-modifying drugs, fasting triglycerides and total-to-high-density lipoprotein cholesterol levels, alcohol use, history of cardiovascular disease, kidney function, and Dutch healthy diet score. MGO, methylglyoxal; 3DG, 3-deoxyglucosone; GO, glyoxal; cDC, carotid distensibility coefficient; cRWT, carotid radius-wall thickness ratio; cPWV, carotid pulse wave velocity; cE, carotid Young’s elastic modulus. Significant associations (p < 0.05) printed in bold. TableAssociations between fasting plasma dicarbonyls and carotid stiffness measures Conclusion: Fasting plasma concentrations of either MGO, 3-DG, or GO are not independently associated with carotid stiffness in this cross-sectional analysis.

Background: Calibration of carotid artery tonometry waveforms needs to account for pulse pressure augmentation [1]. Due to its location nearer to the heart, carotid pulse pressure (carPP) is about 10 mmHg lower than brachial (brachPP) [1]. In practice, perfect applanation is hard to achieve with tonometry and thus tracking-errors may occur, leading to an exaggerated fall in the diastolic limb of the tonometry waveform. Consequently, the mean-to-diastolic difference of the waveform is underestimated, leading to an overestimation of carPP after calibration. We assessed the relationship between brachPP and carPP in 100 subjects, aged 18–80 yrs. Methods and Results: Brachial pressure (Omron) and carotid tonometry (Sphygmocor) measurements were performed by a single, highly skilled vascular technician, according to Artery Society methodological standards. CarPP was 5 ± 13 mmHg lower than brachPP. Bland-Altman analysis revealed a positive trend (r = 0.695, p < 0.0001) between the carPP–brachPP difference and their mean, with carPP being 20 mmHg lower than brachPP at a mean 40 mmHg which extended to carPP being 20 mmHg higher(!) than brachPP at a mean 80 mmHg. Accordingly, 30% of the study population showed unphysiological carPP, indicating an unrealistic i.e. reverse amplification. Even with a tolerance of +5 mmHg, still 20% of cases showed unrealistic values. Conclusion: In practice, calibrated carotid tonometry waveforms may yield unphysiological overestimations of carotid pulse pressure. This finding implies (potential) estimation errors in regression model studies on central pressure and local stiffness, suggesting brachial pulse pressure would be a valid compromise.

This paper aims to summarize and map contemporary views on some contentious aspects of arterial hemodynamics that have remained unresolved despite years of research. These were discussed during a workshop entitled Arterial hemodynamics: past, present and future held in London on June 14 and 15, 2016. To do this we formulated a list of potential consensus statements informed by discussion at the meeting in London and quantified the degree of agreement and invited comments from the participants of the workshop. Overall the responses and comments show a high measure of quantitative agreement with the various proposed 'consensus' statements. Taken together, these statements seem a useful basis for proceeding with a more detailed and comprehensive consensus document on the current understanding and approaches to analysis of the pulse waveform. Future efforts should be directed at identifying remaining areas of dispute and future topics for research. (C) 2017 Association for Research into Arterial Structure and Physiology. Published by Elsevier B.V. All rights reserved.

Greater very short- to mid-term blood pressure variability (BPV) has been associated with an increased CVD risk, especially stroke. However, this link remains incompletely understood. We hypothesized that increased arterial stiffness and maladaptive carotid arterial remodeling may underlie this association. We therefore investigated the association between very short- to mid-term systolic BPV, aortic and carotid stiffness and carotid arterial remodeling using cross-sectional data from The Maastricht Study (aged 60 ± 8 years; 53% men). Aortic (carotid-femoral pulse wave velocity, n = 1671) and carotid stiffness (ultrasonography, n = 1690) were assessed. A composite index of systolic BPV was derived by standardizing and averaging systolic within-visit, 24-hour, and 7-day BPV. We performed linear regression analyses with adjustment for age, sex, glucose metabolism status, mean arterial pressure and cardiovascular risk factors. A 1-SD greater systolic BPV was statistically significantly associated with 0.10 m/s (95%CI: 0.01 – 0.20) greater cfPWV, but not with carotid distensibility (−0.033·10-3/kPa [−0.255 – 0.190]). In addition, a 1-SD greater systolic BPV was statistically significantly associated with greater carotid circumferential wall tension (0.84 dyne/cm [0.51 – 1.17]), circumferential wall stress (0.79 kPa [0.031 – 1.27]) and intima-media thickness (8.6 μm [1.0 – 16.3]). These results are indicative of maladaptive carotid remodeling, as circumferential wall tension and stress were not normalized despite greater intima-media thickness. In conclusion, greater very short- to mid-term BPV is associated with greater aortic stiffness and maladaptive carotid arterial remodeling, but not with carotid stiffness. These findings may explain, at least partially, the increased BPV-associated CVD risk, in particular stroke.

Background: Vascular research demonstrated that pulse wave velocity (PWV), a measure of arterial stiffness, is inherently blood pressure-dependent. Considering the hypothesised pathophysiological chain of increased arterial stiffness leading to increased blood pressure load with consequent left ventricle hypertrophy (LVH) development, we conducted a systematic review of antihypertensive and lifestyle intervention studies to determine the association between on the one hand changes in arterial stiffness and blood pressure, and on the other hand changes in LV mass (LVM). Methods: Using PubMed, EMBASE, Cochrane and Web of Science, we identified 23 studies, containing 2573 patients. Studies reported changes in arterial stiffness (assessed by means of PWV), systolic- and diastolic blood pressure (SBP, DBP), and LVM index (LVMI), respectively. Results: Statistically significant reductions in SBP, PWV and LVMI were reported in 16, 14, and 20 studies, respectively. Pooled analysis of studies showed that the proportion in SBP reduction did not correlate significantly to the proportion in reductions of the other two variables. On the other hand, we found a significant positive correlation (r = 0.58, p = 0.007) between arterial stiffness and LVM regression, expressed as a relevant reduction in LVMI of 6.5 g/m2 per 1.0 m/s reduction in PWV. Conclusions: Our findings provide evidence that a decrease in arterial stiffness is associated with regression of LVH. To investigate whether there exists a causal relation between LVH due to arterial stiffness increases and in turn blood pressure load increases, future studies should strive for a multiple followup design and use of blood pressure-independent or -corrected stiffness indices.

Purpose: Investigating the biomechanical role of smooth muscle cells (SMCs) in arteries requires knowledge of their structural distributions. Compared to histology, 3D microscopy offers non-destructive ex vivo imaging under realistic conditions [1]. Robust 3D segmentation of SMCs, however, is challenging. We propose a method for automatic SMC quantification, and assessed its potential using a murine SMC apoptosis model. Methods: After euthanasia, carotid arteries (control and with induced SMC apoptosis: SM22α-hDTR [2]) were excised and mounted between micropipettes (Figure A). Nuclei were stained with SYTO41. Arteries were imaged using two-photon microscopy [1], while stretched to in vivo length and pressurised to 100 mmHg (Figure B). Image stacks were processed as follows: 1) deconvolution; 2) nuclei segmentation using vesselness filtering [3,4] (Figure C); 3) cylindrical coordinate system identification; 4) splitting of coincident nuclei, based on cores defined from groups of neighbouring voxels with similar orientations [3] (Figure D and E); 5) cylindrical coordinate system re-identification; and 6) cell density-distribution quantification (Figure F). Segmentation performance was assessed by comparing with manual cell counts. Figure(A) Imaging set-up illustrating acquisition of z-stack of slices. (B) Example slice of 3D stack; cell nuclei are shown in blue while elastin fibres are shown in red. (C) Segmentation results from vesselness filtering of example image stack, colours indicate separated nuclei (step 2, Methods). (D) Coinciding nuclei, corresponding with the left orange nuclei in C, shown in grey, with cell cores shown in red and blue (step 4, Methods). (E) Coinciding nuclei splitting results of nuclei shown in C. Non-split nuclei are shown in grey, while split nuclei are shown in red and blue. (F) Transmural SMC densities and cell counts for one control and one SMC apoptosis sample; manual cell counts are given between parentheses. Results: Figure E demonstrates the method’s ability to split undersegmented coinciding nuclei. Cell counts were lower in SM22α-hDTR than in control; algorithm-derived counts were comparable to manual (Figure F). The control sample showed multiple SMC layers, while the SM22α-hDTR sample showed a single SMC layer (Figure F), which was confirmed visually. Conclusion: We developed a precise tool to quantify SMC distributions in ex vivo murine arteries, to facilitate quantitative modelling of SMC biomechanics. We intend to expand the current approach to address cell orientation, shape, and size.

Purpose: There is a need for new tools to screen large populations for cardiovascular disease risk. The CARDIS consortium (European Union H2020 funding) developed an easy-to-use, non-contact device for measuring carotid to femoral pulse wave velocity (cfPWV). It consists in a laser doppler vibrometer (LDV), which measures skin vibrations induced by large artery pulses. Pulse waveforms can be tracked and transit time (TT) can be calculated. This study aimed at comparing LDV-cfPWV with the reference cfPWV measured by applanation tonometry (Sphygmocor). Methods: We included 100 patients with mild to stage 3 hypertension, controlled or not. Reflective tapes were applied on the carotid and femoral arteries to measure LDV-cfPWV 4 times. TT was measured by the foot-to-foot method from the maximum of 2nd derivative using in-house algorithms not requiring ECG, and compared to Sphygmocor (3 acquisitions). Results: LDV-cfPWV was obtained in 100% of patients. Mean age was 47 ± 19 (range 19–85). Hypertensives were well controlled (119/65 mmHg). Mean value of LDV-cfPWV was 6.9 ± 1.7 m/s, compared to 7.5 ± 1.7 m/s with Sphygmocor, bias 0.65 ± 1.27, R value 0.72 (Figure 1), which qualifies agreement as acceptable according to the guidelines from the ARTERY Society [1]. Reproducibility was good with a median coefficient of variation of 5.6%. LDV-cfPWV showed similar associations with age and blood pressure than tonometry (r = 0.68, p < 0.001 and r = 0.44, p < 0.001, respectively). Figure 1 Conclusion: Non-contact measurement of pulse wave velocity by laser doppler vibrometry is feasible, fast and easy to perform, and provides acceptable agreement with reference technique.

Background: Exaggerated exercise systolic blood pressure (SBP) is a modifiable risk factor associated with vascular dysfunction. Vascular dysfunction may contribute to the development of late-life depression, but the association between exercise SBP and incident depressive symptoms is unknown. Therefore, we investigated whether an exaggerated exercise SBP is associated with a higher risk of depressive symptoms over time. Methods: Longitudinal data from the population-based Maastricht Study, with only individuals free of depressive symptoms at baseline included (n = 2,121; 51.3% men; age 59.5 ± 8.5 years). Exercise SBP was measured at baseline with a submaximal exercise cycle test. We calculated a composite score of exercise SBP based on 4 standardized exercise SBP measures: SBP at moderate workload, SBP at peak exercise, SBP change per minute during exercise and SBP 4 minutes after exercise. Clinically relevant depressive symptoms were determined annually at follow-up and defined as a Patient Health Questionnaire score of > = 10. Results: After a mean follow-up of 3.9 years, 175 participants (8.3%) had incident clinically relevant depressive symptoms. A1 standard deviation higher exercise SBP composite score was associated with a higher incidence of clinically relevant depressive symptoms (hazard ratio: 1.27 [95% confidence interval: 1.04–1.54]). Results were adjusted for age, sex, education level, glucose metabolism status, lifestyle, cardiovascular risk factors, resting SBP and cardiorespiratory fitness. Conclusion: A higher exercise SBP response is associated with a higher incidence of clinically relevant depressive symptoms.

Background: Pulse wave velocity (PWV) is quantified by time difference of arrival of the blood pressure (BP) wave at two sites along the arterial bed (transit time; TT-PWV), or by combining measured arterial pressure and diameter using the Bramwell-Hill equation (BH-PWV). Besides the dependence of PWV on BP, TT-PWV also depends on heart rate (HR). The present study aimed to also quantify the dependence of BH-PWV’s on HR, as a function of diastolic BP (DBP). Methods: Adult anaesthetised rats (n = 24) were randomly paced at 300–500 bpm, at 50-bpm steps. At each step, aortic TT-PWV (two pressure-tip catheters) and BH-PWV (pressure-tip catheter and ultrasound wall-tracking; abdominal aorta) were measured simultaneously, across a pharmacologically induced DBP range of 60–110 mmHg. Data from 9142 heart beats was analysed using mixed-effects modelling. Results: HR dependence of TT-PWV increased from 0.03 m/s/100 bpm at DBP = 60 mmHg to 0.06 m/s/100 bpm at DBP = 110 mmHg (both p ≤ 0.023). HR dependence of BH-PWV was 0.11 m/s/100 bpm at DBP = 60 and 85 mmHg, but paradoxically decreased to 0 at DBP = 110 mmHg (p = 0.686). This decrease in dependence is explicable in that standard BH-PWV uses an approximate derivative of pressure to diameter, which overestimates PWV with increasing pulse pressure (PP). PP decreases as HR increases, potentially causing a BH-PWV decrease with HR. This effect can be overcome by estimating the full pressure-diameter curve for each HR, and calculating the true derivative at DBP, yielding a BH-PWV that no longer shows significant HR dependence (p ≥ 0.076 at all DBPs). Conclusions: BH-PWV and TT-PWV show a different HR dependence, affected by DBP.

Objectives: Arterial stiffness index β and cardio-ankle vascular index (CAVI) are widely accepted to quantify the blood pressure (BP)-independent, intrinsic exponent (β0) of the BP-diameter relationship. CAVI and β assume an exponential relationship between pressure (P) and diameter (d). We aim (1) to demonstrate that, under this assumption, β and CAVI as currently implemented are inherently BP-dependent and (2) to provide corrected, BP-independent forms of CAVI and β. Methods and results: In P=Pref*exp[β0(d/dref−1)], usually reference pressure (Pref) and reference diameter (dref) are substituted with diastolic BP and diameter to accommodate measurements. Consequently, the resulting exponent is not equal to the pressure-independent β0. CAVI does not only suffer from this reference pressure effect, but also from the approximation of dP/dd. For example, assuming β0=7, an increase of systolic/diastolic BP from 110/70 to 170/120 mmHg increased β by 8.1% and CAVI by 14.3%. We derived corrected forms of β and of CAVI (CAVI0) that did not change with BP and represent the pressure-independent β0. To substantiate the BP effect on CAVI in a typical follow-up study, we realistically simulated patients (n=161) before and following BP-lowering treatment (assuming no follow-up change in intrinsic β0 and therefore in actual P-d relationship). Lowering BP from 160±14/111±11 to 120±15/79±11 mmHg (p

Background: We anticipate that in vascular outpatients followed over time, measured changes in arterial stiffness will be the multifactorial result of pressure-dependence, ageing- related degeneration, wall stress homeostasis, and medical treatment. Carotid ultrasound enables assessment of carotid pulse wave velocity (cPWV, via Bramwell- Hill), geometry (relative wall thickness, RWT = 2*IMT/diameter), and intrinsic material stiffness (Young’s-modulus, via Moens-Korteweg). We investigated changes in these carotid properties over time, and their interrelationship. To check whether the change in measured cPWV could be merely due to pressure-dependence, we calculated based on the stiffness index β0 [2] the theoretical pressure-dependent change in cPWV [3]. Methods: Hypertensive outpatients (n = 147) were assessed at baseline and 3.5±1.1 year follow- up, and were stratified according to baseline-to-follow-up change in diastolic blood pressure (ΔDBP) into three groups: decreasedDBP (ΔDBP < −7 mmHg), constantDBP (−7 mmHg ≤ ΔDBP≤7 mmHg) and increasedDBP (ΔDBP > 7 mmHg), with the cut-off being twice the typical DBP measurement error [1]. Results: The theoretical pressure-dependent change in cPWV was 0.4±1.3 m/s lower (p < 0.001, n = 147), corroborating the anticipated multifactorial conditions. Table 1 shows no changes in cPWV, RWT and Young’s-modulus for decreasedDBP. For constantDBP, both cPWV and Young’s-modulus were increased at follow-up. IncreasedDBP showed increases in cPWV and Young’s-modulus and a decreased RWT. The latter implies a 9.2±10.7 kPa increase in circumferential wall stress (p < 0.001), in contrast to a 5.3±6.9 kPa decrease (p < 0.001) in decreasedDBP (p < 0.05 for between groups). n = 147 ΔcPWV [m/s] ΔRWT [−] ΔYoung’s-modulus [MPa] Mean±sd p Mean±sd p Mean±sd p DecreasedDBP (n = 53) −0.1±1.4 0.72 0.00±0.04 0.38 −0.01±0.32 0.87 ConstantDBP (n = 67) +0.6*±1.4

Background: Mathematical modelling of pressure and flow waveforms in blood vessels using pulse wave propagation (PWP) models could support clinical decision-making. For a personalised model outcome, measurements of all modelled vessel radii and wall thicknesses are required. In clinical practice, however, datasets are often incomplete. To overcome this problem, we hypothesised that the adaptive capacity of blood vessels in response to mechanical load can be utilised to fill in the gaps of incomplete patient-specific datasets. Methods: We implemented homeostatic feedback loops in a validated PWP model [1] to allow adaptation of vessel geometry to maintain wall stress and wall shear stress. To evaluate our approach, we utilised complete datasets of 10 patients scheduled for vascular access surgery. Datasets comprised of wall thicknesses and radii of 7 central and 11 arm arterial segments. We simulated reference models (RefModel, n = 10) using complete data and adapted models (AdaptModel, n = 10) using data of one brachial artery segment only. The remaining AdaptModel geometries were estimated using adaptation. In both models, mean brachial pressure, brachial artery distensibility, heart rate and aortic inflow were prescribed. We evaluated agreement between RefModel and AdaptModel geometries, as well as between pressure and flow waveforms of both models. Results: Limits of agreement (bias±1.96SD) between AdaptModel and RefModel radii and wall thicknesses were 0.029±1.3mm and 28±230μm, respectively. AdaptModel pressure and flow waveform characteristics across the proximal-to-distal arterial domain were within the uncertainty bounds of the RefModel (Fig. 1). Figure 1AdaptModel and RefModel pressure and flow waveforms at three arterial locations. For adequate comparison between the AdaptModel and the RefModel a total of 100 RefModel realisations were generated within the measurement uncertainty. The median RefModel is indicated by the blue dotted curves. Conclusions: Our adaptation-based PWP model enables personalisation even when not all required data is available.

Background: We recently found in patients that the pressure dependency of arterial stiffness is age-dependent, explaining clinically observed changes in stiffness with blood pressure (BP) lowering. Pulse wave velocity, BP and age found in the Reference Values for Arterial Stiffness Collaboration show a corresponding pattern. We hypothesised that the impact of age on the pressure-dependency of arterial stiffness actually reflects changes in wall constituent properties and adaptation to mechanical stress Methods and results: We applied a constitutive model of arterial wall biomechanics (Zulliger, AJP-Heart 2004) to simulate ageing, based on detailed pressure-area curves obtained in our younger (mean age 40 yrs, n=6) and older (65 yrs, n=7) hypertensive patients. Ageing was simulated by adapting the model (initially fitted to the "young" pressure-area curve) to fit the "old" curve (Figure); allowing for elastin degradation, collagen rearrangement and wall thickness adaptation, but not for changes in fractional volumes. The simulation showed a physiologically significant transfer of pressure-load bearing from elastin to collagen, caused by a 40% loss in elastin stiffness and a 5-fold increase in collagen recruitment (Table). Presuming normalisation and homogeneous distribution of wall stress with ageing, the predicted increase in wall thickness was in accordance with intima-media thickness Reference Values (2010 data; 25-yr increment, corresponding risk category). Conclusion: Ageing influences observed arterial stiffness values at given blood pressures through underlying changes in the properties and mechanical loading of arterial wall constituents.

The role of ventricular–arterial hemodynamic interaction in the occurrence of arterial dissection and rupture in vascular Ehlers–Danlos syndrome (vEDS) is unknown. We recently introduced an ultrasound-based method to extract, from common carotid artery (CCA) diameter waveforms, central arterial properties and left ventricular (LV) systolic time intervals. We obtained CCA diameters, compliance and distensibility coefficients, and LV isovolumic contraction and ejection periods (ICP and EP) of 19 vEDS patients (aged 27–65 yrs) and 19 age-matched healthy controls. CCA distension and compliance tended to be lower in vEDS subjects (p = 0.062 and p = 0.073), especially in younger patients. ICP (−12 ms) and EP (−24 ms) were shorter (p < 0.001), while heart rate was increased (+10 bpm; p < 0.001) in vEDS. The ICP/EP ratio and estimated isovolumic dPLV/dt indicated increased LV contractility in vEDS. In conclusion, vascular EDS patients tend to have a lower CCA compliance but a normal pulse pressure, most likely reflecting reduced physical fitness.

Results: As expected, clinic blood pressure values and media to lumen ratio were higher in essential hypertensive patients than in normotensive controls. Fibronectin media content was significantly greater in essential hypertensive patients (7.41 2.28 %), compared with normotensive controls (5.62 0.40, P

Background: The relative content and loading of collagen and elastin in the arterial wall determine in vivo longitudinal pre-stretch. Assessment of arterial distensibility at varying longitudinal pre-stretch could improve characterisation of arterial collagen-elastin matrix properties. We introduce a technique to impose extra longitudinal pre-stretch (Δstretch) to the carotid artery in vivo and investigate whether we can predict Δstretch from ultrasound distensibility measurements using a constitutive model. Methods: In 11 healthy volunteers (22±3 yrs, mean±SD, 6m/5f) we obtained right common carotid artery bifurcation-to-bifurcation length by phase-contrast MR-angiography in two positions: head facing forward (relaxed, R) and head facing up and rotated to the left (stretched, S). We estimated Δstretch from the MR images by two independent operators (Bland-Altman inter-operator bias = 0.5±3%, mean±2SD). Additionally, we obtained brachial blood pressures and carotid diameter-distension (considered as cross-sectional area) by ultrasound echo-tracking. We fitted a constitutive model [Spronck et al., AJP-Heart 2015] to average single-exponential pressure-area curves for both R and S states. We predicted Δstretch using the model, assuming constant axial force over the cardiac cycle. Results: MRI-estimated Δstretch was +2% while constitutive model-predicted Δstretch was +6%. To check these estimates, we additionally predicted Δstretch based on echo-derived intima-media-thickness measurements, yielding +6%. Conclusion: Measured and predicted Δstretch values were of the same order of magnitude. Assessment of carotid artery distensibility at varying longitudinal pre-stretch could improve model-based in vivo assessment of arterial wall collagen-elastin matrix properties, which are relevant in age- and disease-related arterial remodelling.

s 125 Conclusions: Significant Bra-Rad-SBPAmp exists during light-moderate exercise. This will result in underestimation of central SBP unless Bra-Rad-SBPAmp is considered and is influenced by variation in peak blood flow velocity magnitude between the brachial and radial arteries.

Although the clinical relevance of arterial stiffness is increasingly recognized, the applicability of arterial stiffness for individual cardiovascular risk assessment is hampered due to technical and physiological difficulties. Arterial stiffness is not constant with blood pressure and not constant over the arterial tree. Currently, stiffness is commonly assessed in individuals over a long trajectory and neglects the pressure dependency. To circumvent these problems, we developed a technique to measure pulse wave velocity (PWV) locally using multiple M-line ultrasound. In the common carotid artery, PWV can only be measured using the dicrotic notch of the distension waveform as fiducial time-point, because the systolic foot is subjected to reflective interference. Dicrotic notch PWV provides a measure of stiffness at near systolic pressure level, which is intrinsically different from systolic foot PWV measured at diastolic pressure. To investigate the effect of pressure on local stiffness, we quantified carotid distensibility coefficients for the diastolic and systolic pressure ranges separately. We found that the diastolic-systolic difference in carotid distensibility varies significantly between individuals and is an independent determinant of left ventricular mass index. Moreover, this pressure dependency appears to increase with age (like arterial diameter), suggesting that this property could be used as a marker for structural remodeling of the artery wall. Biomechanically, the pressure dependency of stiffness directly affects pressure and flow waveform characteristics and their phase relation. Ignoring this may lead to overestimation of the impact of wave reflections on central blood pressure. Our work shows that pressure dependency of arterial stiffness can and should be accounted for to evaluate its implication for pressure augmentation and wave separation analysis.