Ethical statement

Ethical approval was provided by Cardiff Metropolitan University’s School of Sport and Health Sciences Research Ethics Committee (17/3/01S), and the study conformed to the Declaration of Helsinki (2008) except for registration in a database. All participants were informed of the methods and study design verbally and in writing before providing written informed consent.

Study participants

Data collection for this study was conducted as part of a wider investigation examining cardiac-specific training adaptations in men (Dawkins et al. 2020). However, the present study addresses a distinct a-priori hypothesis that directly relates to central artery-specific training adaptations in young men. In order to control for the well-documented independent effects of age on central artery stiffness, and focus our analysis exclusively on young males, only participants aged ≤ 35 years were included in the analysis of the present study (n = 40) (Segers et al. 2007; Mattace-Raso et al. 2012; Scuteri et al. 2012). Two recordings displayed inadequate tracking of the wall-lumen interface (n = 1 endurance; n = 1 untrained), so were unsuitable for analysis. Accordingly, 38 young males were included in the study analysis, comprising of 12 endurance-trained (runners, cyclists, triathletes; [mean age, 95% confidence interval (CI); 27 years, 95% CI (24, 29)], 14 resistance-trained [24 years, 95% CI (23, 26)] and 12 untrained [23 years, 95% CI (22, 24)] men. Average weekly training distance for endurance-trained men was 51 km for runners, 101 km for cyclists and 202 km for triathletes. All resistance-trained men exclusively performed moderate-to-high intensity full-body resistance-training and did not engage in any structured aerobic exercise. Untrained men engaged in ≤ 150 min of structured physical activity per week (Bull et al. 2020). Exclusion criteria: the use of cardioactive drugs and prescribed medications; the use of performance-enhancing drugs; history of cardiovascular, musculoskeletal, metabolic, or renal disease; any contraindications to exercise, asthma and smoking.

Study design

Participants visited the laboratory on two separate occasions. Participants were asked to abstain from alcohol, caffeine and vigorous physical activity for 24 h prior to each visit and were asked to fast for ≥ 6 h prior to testing for the second visit. The first visit involved the completion of health and training questionnaires, anthropometric measurements and acquisition of resting blood pressure. A strength assessment was performed with a one-repetition maximum (1RM) seated leg-press. After a minimum 30 min recovery period, an assessment of cardiorespiratory fitness was carried out via a peak oxygen consumption (\(\dot}_}}}\)) incremental cycling test. For the second visit, participants rested supine for 10 min before PWV and central blood pressure were assessed. Subsequently, short-axis ultrasound images of the CCA were recorded at rest, during a three-minute IHG protocol at 40% of maximal voluntary contraction and after a one-minute recovery period.

Exercise testing

The 1RM seated leg-press was performed on a commercially available leg-press machine (Linear Leg Press, Life Fitness, Ltd., Queen Adelaide, UK). The 1RM protocol for the 45°-inclined double leg press was determined according to the National Strength and Conditioning Association guidelines (Baechle 2008). Participants initially completed a 5 to 10 repetition warm-up against light resistance. After a 2 min rest period, the first attempt was performed using a load that was ~ 50% of the participants’ weight-predicted 1RM. Following a 3–5 min rest, participants repeated the exercise with an increased load. This process was repeated until participants could only perform a single repetition and required between three and five attempts to achieve the correct load. \(\dot}_}}}\) and peak power output (PPO) was determined using an incremental cycling test on an upright cycle ergometer (Lode Corival, Groningen, Netherlands). Exercise was started at 50W for both the resistance-trained individuals and the controls, at 120W for endurance-trained individuals, and was subsequently increased by 20W every minute until volitional exhaustion. Measurements of ventilatory gas exchange were obtained using a mask-based, breath-by-breath analyser (Jaeger, Oxycon Pro, Warwick, UK) and heart rate was measured using a Polar heart rate monitor (Polar Electro, RS400, Kemple, Finland). Peak oxygen uptake was defined as the highest \(\dot}_}\) achieved over a 30 s consecutive period.

Aortic pulse wave velocity

In accordance with applanation tonometry guidelines, a high-fidelity micromanometer-tipped probe was used to obtain sequential ECG-gated pressure waveforms at the site of maximal arterial pulsation of the carotid and femoral arteries to calculate aortic PWV (Van Bortel et al. 2012). Central blood pressure was estimated by applying a validated transfer function (Van Bortel et al. 2012) to radial artery waveforms collected via the same probe (SphygmoCor; AtCor Medical, Sydney, NSW, Australia).

Common carotid artery ultrasonography

Short-axis grey-scale cine loops of the right CCA were acquired on a commercially available high-resolution ultrasound system (Vivid q, GE Healthcare, Chalfont, UK), using a 12 MHz multi-frequency linear array probe. CCA images were recorded ~ 2 cm proximal to the carotid bifurcation over a minimum of five consecutive cardiac cycles. Cardiac cycles were measured continuously using a 3-lead ECG connected to the ultrasound machine. Frame rate (92.3 frames per second), imaging depth and probe orientation was standardised for all participants and all images were acquired by a single trained technician.

Two-dimensional strain and conventional ultrasound image analysis

Speckle-tracking software quantifies vascular tissue motion throughout the cardiac cycle by automatically identifying speckles in the short-axis ultrasound image (Pugh et al. 2018; Bjallmark et al. 2010). To quantify arterial strain and strain-rate, a region of interest (ROI) was manually placed over the entire CCA wall circumference, ensuring accurate circumferential alignment with the lumen-wall interface. The ROI comprised six evenly distributed segments in which movement of speckles were tracked frame-by-frame throughout the cardiac cycle using a speckle-tracking algorithm inherent to the software (EchoPac Version 112, GE Vingmed Ultrasound, Horten Norway). The software (automatic verification) and operator (visual verification) both verified suitable positioning of the ROI for optimal wall tracking, whereby images included within the analysis demonstrated successful tracking across all six ROI segments. This generates strain and strain rate curves. Peak circumferential strain (PCS), systolic strain-rate (S-SR) and diastolic strain-rate (D-SR) were expressed as ‘global’ values reflecting the average values obtained between the six ROI segments of the CCA over three consecutive cardiac cycles; therefore representing circumferential motion of the entire CCA wall. PCS was identified as the greatest peak in the interpolated circumferential strain curve and represents the magnitude of arterial deformation. S-SR was identified as the largest positive peak in the strain-rate curve that occurred after the QRS-complex, and D-SR was defined as the largest negative peak on the strain-rate curve that occurred after the T-wave of the ECG.

CCA diameters were measured by obtaining an M-mode trace through the centre of the short-axis image. Systolic and diastolic diameters were defined as the maximal and minimal diameters during the cardiac cycle, respectively, and were measured from the leading edge of the intima–lumen interface of the anterior wall to the leading edge of the lumen–intima interface of the posterior wall.

To characterize local CCA stiffness, Peterson’s Elastic Modulus (Ep; kilopascal [kPa]), β1 (arbitrary units [AU]), β2-stiffness-index (β2; AU) and distensibility (mmHg × 10−3) (the inverse of Ep) were calculated. β1, Ep and distensibility are conventional measures of CCA stiffness and adjust changes in arterial diameter throughout the cardiac cycle for changes in distending pressure (Laurent et al. 2006). β2 relates PCS to distending pulse pressure (Oishi et al 2008). Increases in β1, β2 and Ep are associated with greater arterial stiffness (Laurent et al. 2006), conversely increases in distensibility indicate a greater magnitude of arterial distension per unit of pressure. Stiffness measures were calculated using the following formulae:

Distensibility = [(SD−DD)/(SBP−DBP)]/DD (mmHg × 10−3)

β1 = ln(SBP/DBP)/[(SD−DD)/DD] (AU)

β2 = ln(SBP/DBP/PCS) (AU)

Ep = (SBP−DBP)/[(SD−DD)/DD] (kPa)

where ln refers to the natural logarithm function, SBP and DBP relate to peripheral systolic and diastolic pressure respectively, and SD and DD relate to systolic and diastolic diameter respectively.

Isometric hand-grip exercise

Participants performed three left-handed maximal voluntary contraction using a handgrip force transducer device (MLT004/D, ADInstruments, Oxford, UK), with the highest achieved value of the three maximal efforts used to calculate exercise intensity. After a 10 min period of supine rest, whilst still lying supine, participants performed IHG exercise at 40% of this maximum contraction for 3 min. The individualised target force zone and real-time contraction force was continuously displayed on a computer screen and visually monitored by both the participant and an assessor to ensure adherence to the prescribed intensity throughout the protocol. This IHG exercise protocol was used as it has been previously shown to elicit transient increases in systemic blood pressure and evoke arterial responses (Campbell et al. 2023). CCA ultrasound measurements were obtained at rest (resting), 1 min 30 s following the onset of contraction (mid), immediately prior to release of contraction (end), and 1 min after release (recovery). Beat-by-beat peripheral (brachial) blood pressure was recorded continuously throughout the protocol via finger plethysmography (FinometerPro, FMS, Groningen, Netherlands), and calibrated against manual brachial blood pressure measurements obtained at rest.

Statistical analysis

In the absence of available data on the effects of resistance-training on 2D-Strain parameters, power analysis was conducted by sampling pooled data from our two previous studies examining the impact of regular endurance exercise on 2D-Strain parameters (Pugh et al. 2018; Talbot et al. 2020). A mean difference in PCS of 2% (Cohen’s d effect size = 0.76) was detected between endurance-trained and untrained young men. Accordingly, we estimated that a sample of 38 participants within a three-group cross-sectional study design would detect a 2% (d = 0.76) difference in PCS with 80% power at a two-sided 0.05 significance level. All data were checked and confirmed for normality of distribution using a Shapiro–Wilk test and visual inspection of histogram. A one-way analysis of variance (ANOVA) was performed to assess differences in resting parameters between the three groups. A two-factor, repeated-measures ANOVA was used to determine the main effects of training status, time and any interaction between these factors (training status x time) at baseline, during IHG exercise and upon recovery. Where a significant interaction was observed, post-hoc comparisons with Bonferroni corrections were conducted to identify significant differences among group mean values. Additionally, if group differences were observed at rest, analysis of covariance (ANCOVA) was conducted on the IHG data with resting values set as a covariate. All data were analysed using the statistical package SPSS (Ver.27 for Windows, Chicago, SPSS Inc) and presented as means and 95% confidence intervals (95% CI) unless otherwise stated. Statistical significance was set at P < 0.05.