Associations between cardio-ankle vascular index score, an indicator of arteriosclerosis and aortic volume and hemodynamic parameters using four-dimensional magnetic resonance imaging

Abstract

Backgroud

The cardio-ankle vascular index (CAVI) is a noninvasive measure of arterial stiffness, but it does not assess blood flow or aortic shape. Four-dimensional (4D) magnetic resonance imaging (MRI) has emerged as a promising tool for evaluating vascular blood flow. This study investigated the correlation between thoracic aortic volume (TAV) and hemodynamic parameters using 4D MRI in patients with and without AA as defined by the CAVI score.

Methods

This retrospective study involved 171 patients (77 with a low CAVI score and 94 with a high CAVI score) who underwent cardiac MRI with a 4D flow sequence.

Thirty-two participants per group were propensity score matched. Hemodynamic parameters—including energy loss (EL), vorticity (Vort), and helicity (Hel)—were obtained.

Results

Patients in the high CAVI group had significantly larger TAV (101.9 ± 29.6 vs. 82.6 ± 29.4 cm3, P < 0.0001). The TAV was positively correlated with the CAVI score (R = 0.4147, P < 0.0001). EL maximum/TAV (P = 0.0005), Vort average/TAV (P = 0.0025), and Hel absolute maximum/TAV (P = 0.0007) were significantly lower in the high CAVI group. Several hemodynamic parameters, including Vort maximum/TAV (R = −0.4082, P < 0.0001) and Hel right screw maximum/TAV (R = −0.4211, P < 0.0001), were moderately negatively correlated with the CAVI score, suggesting that aortic stiffness restricts luminal blood flow, particularly during systole.

Conclusions

Patients with high CAVI scores exhibited a larger TAV and lower voxel-based hemodynamic parameters than those with low CAVI scores. This method represents a novel approach for the noninvasive assessment of atherosclerosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-026-05925-3.

Introduction

Aortic atherosclerosis (AA) is a chronic inflammatory condition characterized by the accumulation of plaques within the arterial wall. This results in arterial wall stiffness and is associated with an increased risk of cardiovascular events [1, 2]. Therefore, early diagnosis, severity grading, and prediction of AA are crucial. The evaluation of patients with suspected or confirmed AA typically relies on imaging techniques. One of the most widely accepted imaging tests for atherosclerosis is computed tomography angiography, which provides anatomical imaging of plaques in coronary heart disease [3]. Magnetic resonance imaging (MRI) is another valuable noninvasive tool for assessing AA, enabling precise measurement and characterization of plaques [4]. Additionally, nuclear imaging techniques using fluorodeoxyglucose can visualize inflammation and macrophage activity within atherosclerotic plaques, offering insights into plaque activity [5].

Despite these advances, AA remains difficult to diagnose in routine clinical practice. A physiological measure known as the cardio-ankle vascular index (CAVI) was developed in Japan to address this. The CAVI measures arterial stiffness from the origin of the aorta to the ankle and is based on the stiffness parameter β, which adjusts the pulse wave velocity for changes in arterial diameter during the cardiac cycle [6]. Although CAVI is independent of blood pressure, it is attributed to an increased vascular tone brought about by smooth muscle contraction [7]. Therefore, the data should be interpreted with caution. On the other hand, the CAVI test is simple, noninvasive, and widely used in clinical medicine as an indicator for evaluating cardiovascular diseases and associated risk factors [8]. However, while the CAVI provides a measure of arterial stiffness, it does not assess the actual shape of the aorta or blood flow dynamics.

Recently, three-dimensional (3D) phase-contrast MRI, commonly referred to as four-dimensional (4D) MRI, has emerged as a noninvasive method for evaluating and characterizing vascular blood flow [9–12]. This technique measures hemodynamic velocity by encoding motion in the x, y, and z directions, resolving these velocities in relation to the 3D anatomy and time over the cardiac cycle (3D + time = 4D).

In this study, we hypothesized that aortic volume and hemodynamic parameters would correlate with the severity of AA because stiffened arterial walls can restrict blood flow through the vessel lumen. Historically, most methods for evaluating AA have focused on the arterial wall, with few approaches available to assess blood flow within the lumen. We believe that evaluating AA from this alternative perspective could provide new insights. Additionally, given that arteriosclerosis is a systemic disease, we sought to develop a method that could quantitatively assess it over a larger area. Therefore, we considered that quantitatively measuring aortic volume and hemodynamic parameters related to AA would be clinically useful.

This study aimed to differentiate changes in aortic volume and blood flow in the thoracic aorta due to atherosclerotic arterial stiffness using 4D MRI-derived hemodynamic parameters in patients with and without AA, as defined by the CAVI. We also investigated the correlation between aortic volume, hemodynamic parameters, and the CAVI.

Materials and methods

Patient population

Our institutional review board approved this study and waived the need for written informed consent because of the retrospective study design. From April 2020 to July 2024, 398 consecutive patients (256 men [64.3%] and 142 women [35.7%]; mean age ± SD: 58.0 ± 17.3 years) underwent cardiac contrast-enhanced MRI to investigate cardiomyopathy or cardiac dysfunction for the first time; 317 of these patients also underwent 4D MRI. Data for four patients were unavailable for 4D flow analysis, and 139 patients without CAVI data, as well as three postoperative patients with tetralogy of Fallot or total arch replacement, were excluded from the study. Consequently, the final cohort consisted of 171 consecutive patients (Fig. 1).

Fig. 1.

Flowchart showing patient selection. MRI, magnetic resonance imaging; 4D, four-dimensional; CAVI, cardio-ankle vascular index

After the 4D MRI results were analyzed, the patients were divided into two groups (low CAVI group and high CAVI group) based on their CAVI results. The patient cohort comprised 77 patients with a low CAVI score (48 [62.3%] men and 29 [37.7%] women; mean ± SD age, 49.7 ± 16.1 years) and 94 patients with a high CAVI score (74 [78.7%] men and 20 [21.3%] women; mean ± SD age, 67.4 ± 9.9 years) (Table 1). All of these patients were identified through a retrospective review of the medical records at a single medical institution.

Table 1.

Patients’ demographic and clinical characteristics (n = 171)

Parameter	Low CAVI (n = 77)	High CAVI (n = 94)	P-value
CAVI score	6.5 ± 1.1	9.6 ± 1.1	< 0.0001*
Age, years	49.7 ± 16.1	67.4 ± 9.9	< 0.0001*
Sex, male: female	48:29	74:20	0.018*
BMI, kg/m2	24.8 ± 5.2	22.2 ± 3.4	0.002*
Hypertension	35 (45.5)	55 (58.5)	0.089
Diabetes mellitus	14 (18.2)	24 (25.5)	0.250
Renal failure	4 (5.2)	7 (7.4)	0.550
Smoking	37 (48.1)	59 (62.8)	0.054
LVEF, %	44.7 ± 16.7	48.5 ± 15.2	0.120
Final diagnosis
Unremarkable findings	1 (1.3)	1 (1.1)	0.887
DCM	30 (39.0)	24 (25.5)	0.060
HCM	9 (11.7)	15 (16.0)	0.424
HHD	0 (0.0)	2 (2.1)	0.198
RCM	2 (2.6)	0 (0.0)	0.116
MI	7 (9.1)	12 (12.8)	0.447
VSA	2 (2.6)	1 (1.1)	0.447
Myocarditis	10 (13.0)	6 (6.4)	0.140
Drug-induced myocarditis	0 (0.0)	4 (4.3)	0.067
Arrhythmia	5 (6.5)	7 (7.4)	0.808
Cardiac sarcoidosis	2 (2.6)	2 (2.1)	0.840
Cardiac amyloidosis	1 (1.3)	14 (14.9)	0.002*
LVNC	3 (3.9)	0 (0.0)	0.054
ASD	1 (1.3)	1 (1.1)	0.887
AR	4 (5.2)	1 (1.1)	0.111
MR	0 (0.0)	4 (4.3)	0.067

Data are expressed as n (%) or mean ± standard deviation (range)

CAVI cardio-ankle vascular index, BMI body mass index, LVEF left ventricular ejection fraction, DCM dilated cardiomyopathy, HCM hypertrophic cardiomyopathy, HHD hypertensive heart disease, RCM restrictive cardiomyopathy, MI myocardial infarction, VSA vasospastic angina, LVNC left ventricular noncompaction, ASD atrial septal defect, AR aortic regurgitation, MR mitral regurgitation

*P < 0.05

CAVI score

Within six months of cardiac MRI, CAVI test was performed. The CAVI score was automatically measured using the vascular screening system VaSera VS-1500 (Fukuda Denshi Co., Ltd., Tokyo, Japan). The patients rested in the supine position for at least 10 min while being monitored. Cuffs were attached to both upper arms and ankles, electrocardiogram electrodes were placed on the wrists, and a microphone was positioned on the sternum. The average CAVI values from both sides were used for analysis. A CAVI score of < 8.0, as determined by the vascular screening system, is considered within the normal range [13, 14]. In this study, CAVI scores of < 8.0 were classified as low CAVI, while scores of ≥ 8.0 were classified as high CAVI.

Echocardiographic estimation of Left Ventricular Ejection Fraction (LVEF)

Within 1 week of cardiac MRI, echocardiographic examinations were performed by experienced cardiologists with > 5 years of experience in cardiac echocardiography using the Vivid E95 system version 203 (GE Healthcare Japan, Tokyo, Japan). Images were acquired from standard views and recorded digitally. LVEF values were measured using transthoracic two-dimensional echocardiography, applying the modified Simpson’s rule.

MRI protocol

All patients were scanned using a 3.0-T scanner (MAGNETOM Vida; Siemens, Healthcare, Germany) with a 32-channel cardiac phased-array coil. The scanning parameters were similar to our previous study [15].

All 4D MR images were acquired under free-breathing conditions during the routine electrocardiographically gated cardiac MRI sequence, prior to late gadolinium enhancement imaging, 30 s after the administration of gadolinium at a dose of 0.10 mmol/kg.

MRI analysis

Aorta data were obtained from regions extending from the neck to the upper abdomen using datasets that included multislice sagittal planes from phase-contrast three-axis cine images, magnitude images, and steady-state free precession cine images. Hemodynamic parameters were measured using iTFlow (Cardio Flow Design Inc., Tokyo, Japan). The thoracic aorta segment evaluated in this study extended from the ascending aorta at the level of the right main pulmonary artery to the descending aorta at the level of the pulmonary valve (Fig. 2), as determined from the 3D cine images.

Fig. 2.

Evaluation of segmented thoracic aorta. The green area represents the segmented thoracic aorta in the same cross-section. a Sagittal cine image of the ascending aorta at the level of the upper border of the right main pulmonary artery (white arrow). b Sagittal cine image of the descending aorta at the level of the upper border of the pulmonary valve (white arrow)

One radiologist with 12 years of experience in reading cardiac MRI analyzed the MRI scans. The radiologist was blinded to the patients’ clinical conditions and investigated. Another radiologist with 15 years of experience interpreting cardiac MRI then reviewed the borders of the thoracic aorta to ensure accuracy. The mean thoracic aortic volume (TAV) (cm³) and flow parameters were automatically calculated. The term “mean” referred to the average value across all phases of a single cardiac cycle because the TAV changes throughout the cycle. We then analyzed the TAV and hemodynamic parameters.

Hemodynamic parameters

Energy loss (EL) can be directly assessed by estimating viscous EL and turbulent kinetic energy (KE). Viscous dissipation of energy is a normal characteristic of aortic flow. In normal laminar flow, it is caused by friction between adjacent fluid layers with differing velocities. This friction increases with abnormal flow patterns, such as those due to aortic valve disease, resulting in elevated viscous EL [16].

In this study, the average EL (EL ave) was defined as the average value of EL across all phases of one cardiac cycle. The maximum EL (EL max) represented the EL in the phase with the highest value, and the minimum EL (EL min) indicated the EL in the phase with the lowest value across all phases of the cardiac cycle. These three parameters—ave, max, and min—were calculated automatically.

Similarly, the ave, max, and min values of vorticity (Vort) and helicity (Hel), described below, were calculated as averages across all phases of one cardiac cycle.

Vort is an index that quantifies the strength of the swirl in the velocity vector. High Vort values can increase stress on local blood vessel walls, promoting aneurysmal growth. They may also alter local vascular protective mechanisms, leading to reduced wall shear stress [17, 18].

Hel is an indicator of helical flow, representing corkscrew-like motion along the principal flow direction. Hel in the thoracic aorta can be exacerbated by common pathologies, such as aortic dilatation and alterations in the aortic valve (e.g., aortic valve stenosis or a bicuspid aortic valve) [19, 20]. Using the 4D voxel data, the absolute helicity (Hel abs) was calculated. Hel right screw and Hel left screw, along with their ave, max, and min values, were also calculated. These flow parameters were calculated similar to our previous study [14].

Additionally, we investigated voxel-based values for these flow parameters divided by the TAV because the flow parameters are the sum of the flow in the thoracic aorta and are influenced by TAV. The method of dividing the 4D flow parameters by the TAV was also used in our previous study of aortic calcification and 4D flow MRI [15].

Statistical analysis

All statistical analyses were performed using Prism for Windows, version 8.3.0 (GraphPad Software, San Diego, CA, USA). The D’Agostino–Pearson test was used to assess the normality of the data. Non-normally distributed variables are presented as median (range), while quantitative results are expressed as mean ± SD or median (range), as appropriate.

We analyzed the patients’ CAVI score, age, body mass index (BMI), LVEF, TAV, and 4D hemodynamic parameters using either the paired t-test or the Wilcoxon signed-rank test between the two groups, depending on the data distribution. Sex, hypertension, diabetes mellitus, renal failure, smoking status, and final diagnosis were compared between the two groups using the chi-squared test.

Propensity scores were calculated using age, sex, and BMI, and propensity score-matching was performed for the two groups (CAVI < 0.8 or ≥ 0.8). Nearest neighbor matching (1:1 sampling with no replacement) was used with a caliper set to 0.2 times the SD of the propensity score. Appropriate matching was confirmed by calculating the absolute standardized difference (ASD).

Spearman’s rank correlation coefficients were calculated to assess correlations between the CAVI score and the hemodynamic parameters.

A two-sided p-value was used for all statistical tests, and differences with a P-value of < 0.05 were considered statistically significant.

Results

Patient populations in low and high CAVI groups

The quantitative data were confirmed to be normally distributed, and expressed as mean ± SD. Of the 171 patients included in this study, 77 (45.0%) had a low CAVI score and 94 (55.0%) had a high CAVI score (Table 1).

There were no significant differences between the groups in terms of hypertension (P = 0.089), diabetes mellitus (P = 0.250), renal failure (P = 0.550), smoking (P = 0.054), LVEF (P = 0.120), unremarkable findings (P = 0.887), dilated cardiomyopathy (P = 0.060), hypertrophic cardiomyopathy (P = 0.424), hypertensive heart disease (P = 0.198), restrictive cardiomyopathy (P = 0.116), myocardial infarction (P = 0.447), vasospastic angina (P = 0.447), myocarditis (P = 0.140), drug-induced myocarditis (P = 0.067), arrhythmia (P = 0.808), cardiac sarcoidosis (P = 0.840), left ventricular noncompaction (P = 0.054), atrial septal defect (P = 0.887), aortic regurgitation (P = 0.111), or mitral regurgitation (P = 0.067).

The mean CAVI score was 6.5 ± 1.1 in the low CAVI group and 9.6 ± 1.1 in the high CAVI group. Significant differences were found between the groups in age (P < 0.0001), sex (P = 0.018), BMI (P = 0.002), and cardiac amyloidosis (P = 0.002).

Evaluation of the propensity scores

Because the test result for C statistic = 0.5 was P < 0.05, the propensity score estimate was considered to be valid (Table 2).

Table 2.

Evaluation of the propensity scores

C statistic	95% confidence interval	P-value
0.865	0.809, 0.920	< 0.0001

Variables used to match propensity scores: age, body mass index, hypertension, smoking, cardiac amyloidosis

Propensity score matching

The calculation of the ASD is a recommended method for the evaluation of matching. After matching, the ASD for all the items was < 10%, and therefore it was considered to be balanced (Tables 3 and 4). The matched data was then used to compare 32 patients in the low CAVI group with 32 patients in the high CAVI group.

Table 3.

Comparison of the groups before propensity score matching

	CAVI < 0.8 (n = 77)	CAVI ≥ 0.8 (n = 94)	P-value	ASD
Sex, Female	29, 37.7	20, 21.3	0.027a	36.5%
Age	49.7 ± 16.2	67.4 ± 10.0	< 0.0001b	131.4%
BMI	24.7 ± 5.2	22.2 ± 3.5	< 0.0001b	57.4%

Data are n, % or mean ± SD

P-values were generated using a, Fisher’s exact test or b, the unpaired t-test

ASD absolute standardized difference, BMI body mass index, CAVI cardio-ankle vascular index

Table 4.

Comparison of the groups after propensity score matching

	CAVI < 0.8 (n = 32)	CAVI ≥ 0.8 (n = 32)	ASD
Sex, Female	11, 34.3	11, 34.3	0.0%
Age	61.5 ± 13.2	62.3 ± 11.2	6.4%
BMI	23.4 ± 4.2	23.4 ± 3.9	0.8%

Data are n, % or mean ± SD

ASD absolute standardized difference, BMI body mass index, CAVI cardio-ankle vascular index

TAV

The mean TAV was 82.6 ± 29.4 cm³ in the low CAVI group and 101.9 ± 29.6 cm³ in the high CAVI group, with significant differences between the groups (P < 0.0001). The TAV was significantly positively correlated with the CAVI (R = 0.4147, P < 0.0001).

Hemodynamic parameters in patients with low and high CAVI scores (Table 5) (Fig. 3)

Table 5.

Thoracic aortic volume and hemodynamic parameters in patients with low and high CAVI scores after propensity score matching (n = 64)

Parameter	Low CAVI (n = 32)	High CAVI (n = 32)	P-value
TAV (cm3)	82.6 ± 29.4	101.9 ± 29.6	< 0.0001*
Energy loss ave (× 102 mW)	196 ± 379	98 ± 47	0.1438
Energy loss ave/TAV (× 102 mW)	2.3 ± 2.5	1.0 ± 0.5	0.0926
Energy loss max (× 102 mW)	474 ± 869	224 ± 141	0.1953
Energy loss max/TAV (× 102 mW)	5.7 ± 6.8	2.3 ± 1.9	0.0005*
Energy loss min (× 102 mW)	113 ± 230	56 ± 32	0.1646
Energy loss min/TAV (× 102 mW)	1.38 ± 1.54	0.55 ± 0.28	0.1183
Vorticity ave (× 104m3s− 1)	35 ± 11	40 ± 15	0.0344*
Vorticity ave/TAV (× 104m3s− 1)	0.43 ± 0.14	0.39 ± 0.07	0.0025*
Vorticity max (× 104m3s− 1)	57 ± 17	64 ± 44	0.3869
Vorticity max/TAV (× 104m3s− 1)	0.70 ± 0.29	0.63 ± 0.21	< 0.0001*
Vorticity min (× 104m3s− 1)	29 ± 21	25 ± 9	0.2773
Vorticity min/TAV (× 104m3s− 1)	0.35 ± 0.12	0.25 ± 0.06	0.0754
Helicity abs ave (× 106m4s− 2)	11 ± 41	15 ± 29	0.6899
Helicity abs ave/TAV (× 106m4s− 2)	0.13 ± 0.51	0.15 ± 0.32	0.2382
Helicity abs max (× 106m4s− 2)	82 ± 148	31 ± 134	0.5707
Helicity abs max/TAV (× 106m4s− 2)	1.0 ± 2.5	0.3 ± 1.7	0.0007*
Helicity abs min (× 106m4s− 2)	−115 ± 116	−93 ± 104	0.4339
Helicity abs min/TAV (× 106m4s− 2)	−1.4 ± 1.1	−0.9 ± 1.1	0.0566
Helicity right screw ave (× 106m4s− 2)	170 ± 236	145 ± 59	0.1814
Helicity right screw ave/TAV (× 106m4s− 2)	2.1 ± 1.7	1.4 ± 0.6	< 0.0001*
Helicity right screw max (× 106m4s− 2)	401 ± 783	252 ± 217	0.2711
Helicity right screw max/TAV (× 106m4s− 2)	4.9 ± 6.2	2.5 ± 3.2	< 0.0001*
Helicity right screw min (× 106m4s− 2)	73 ± 118	64 ± 22	0.3680
Helicity right screw min/TAV (× 106m4s− 2)	0.89 ± 0.70	0.63 ± 0.19	0.1576
Helicity left screw ave (× 106m4s− 2)	−179 ± 216	−120 ± 47	0.1135
Helicity left screw ave/TAV (× 106m4s− 2)	−2.2 ± 1.4	−1.2 ± 0.5	< 0.0001*
Helicity left screw max (× 106m4s− 2)	−67 ± 114	−51 ± 19	0.1760
Helicity left screw max/TAV (× 106m4s− 2)	−0.82 ± 0.67	−0.50 ± 0.15	0.0826
Helicity left screw min (× 106m4s− 2)	−320 ± 757	−212 ± 210	0.2495
Helicity left screw min/TAV (× 106m4s− 2)	−3.9 ± 5.1	−2.1 ± 2.5	< 0.0001*

Data are expressed as mean ± standard deviation

CAVI cardio-ankle vascular index, TAV thoracic aortic volume, ave average, max maximum, min minimum, abs absolute

 *P < 0.05

Fig. 3.

Individual data for TAV, Energy loss max/TAV, Vorticity max/TAV, Helicity abs max/TAV, Helicity right screw max/TAV, and Helicity left screw min/TAV in patients in the low CAVI and high CAVI groups. a TAV: low CAVI vs high CAVI, P < 0.0001. b Energy loss max/TAV: low CAVI vs high CAVI, P = 0.0005. c Vorticity max/TAV: low CAVI vs high CAVI, P < 0.0001. d Helicity abs max/TAV: low CAVI vs high CAVI, P = 0.0007. e Helicity right screw max/TAV: low CAVI vs high CAVI, P < 0.0001. f Helicity left screw min/TAV: low CAVI vs high CAVI, P < 0.0001. Abbreviations: TAV, thoracic aortic volume; abs, absolute; max, maximum; min, minimum; CAVI, cardio-ankle vascular index

EL between the two groups

EL max/TAV differed significantly between the groups (P = 0.0005). Although EL ave/TAV did not differ significantly, the P-value was very close to significance (P = 0.0926).

Vort between the two groups

Vort ave, Vort ave/TAV, and Vort max/TAVdiffered significantly between the groups (P = 0.0344, P = 0.0025, and P < 0.0001, respectively).

Hel between the two groups

Hel abs max/TAV differed significantly between the groups (P = 0.0007). Although Hel abs min/TAV did not differ significantly between the groups, the P-values were very close to significance (P = 0.0566).

Both Hel right screw ave/TAV and Hel right screw max/TAV showed significant differences between the groups (P < 0.0001 for both). Additionally, Hel left screw ave/TAV and Hel left screw min/TAV also differed significantly (P < 0.0001 for both).

Representative 4D hemodynamic images are shown in Figs. 4 and 5. Figure 4 shows images of a patient with a low CAVI score, in whom the EL, Vort, and Hel values increased gradually as the systolic phase progressed. Figure 5 shows images of a patient with a high CAVI score, in whom the EL, Vort, and Hel values also increased during systole. However, the changes were smaller than those in the patient from Fig. 4, especially during systole, with overall lower values. Notably, in the patient with the high CAVI score (Fig. 5), the flow parameter values were higher near the arterial wall than near the lumen (indicated by white arrows), likely reflecting the impact of blood flow on the stiffened arterial wall.

Fig. 4.

Four-dimensional flow map imaging of a 38-year-old man with hypertrophic cardiomyopathy in the low CAVI group. The left ventricular ejection fraction was 48%, and the CAVI score was 6.3. a EL in the end-diastolic phase. b EL in the early systolic phase. c EL in the end-systolic phase. d EL in the early diastolic phase. e Vort in the end-diastolic phase. f Vort in the early systolic phase. g Vort in the end-systolic phase. h Vort in the early diastolic phase. i Hel in the end-diastolic phase. j Hel in the early systolic phase. k Hel in the end-systolic phase. l Hel in the early diastolic phase. Abbreviations: CAVI, cardio-ankle vascular index; EL, energy loss; Vort, vorticity; Hel, helicity

Fig. 5.

Four-dimensional flow map imaging of a 58-year-old man with myocarditis in the high CAVI group. The left ventricular ejection fraction was 47%, and the CAVI score was 9.8. a EL in the end-diastolic phase. b EL in the early systolic phase. c EL in the end-systolic phase. d EL in the early diastolic phase. e Vort in the end-diastolic phase. f Vort in the early systolic phase. g Vort in the end-systolic phase. h Vort in the early diastolic phase. i Hel in the end-diastolic phase. j Hel in the early systolic phase. k Hel in the end-systolic phase. l Hel in the early diastolic phase. Abbreviations: CAVI, cardio-ankle vascular index; EL, energy loss; Vort, vorticity; Hel, helicity

Correlations between CAVI score and hemodynamic parameters

EL ave/TAV and EL max/TAV were weakly but significantly negatively correlated with the CAVI score (R = − 0.1731, P = 0.0236 and R = − 0.2785, P = 0.0002, respectively). By contrast, EL ave, EL max, EL min, and EL min/TAV were not significantly correlated with the CAVI score (R = − 0.06954, P = 0.3195; R = − 0.1498, P = 0.0505; R = 0.003303, P = 0.9658; and R = − 0.06389, P = 0.4064, respectively).

Vort ave/TAV was significantly but weakly negatively correlated with the CAVI score (R = − 0.2856, P = 0.0002). Vort max/TAV was moderately negatively correlated with the CAVI score (R = − 0.4082, P < 0.0001).　Conversely, Vort min was weakly positively correlated with the CAVI score (R = 0.1574, P = 0.0398). However, Vort ave, Vort max, and Vort min/TAV were not significantly correlated with the CAVI score (R = 0.1087, P = 0.1571; R = 0.01243, P = 0.8718; and R = − 0.1097, P = 0.1531, respectively).

Hel abs ave/TAV, Hel abs max, and Hel abs max/TAV were weakly but significantly negatively correlated with the CAVI score (R = − 0.2439, P = 0.0013; R = − 0.2248, P = 0.0031; and R = − 0.3777, P < 0.0001, respectively). Hel abs min/TAV was weakly positively correlated with the CAVI score (R = 0.2081, P = 0.0063). By contrast, Hel abs ave and Hel abs min were not significantly correlated with the CAVI score (R = − 0.1101, P = 0.1518 and R = 0.1471, P = 0.0549, respectively).

Hel right screw ave/TAV and Hel right screw max were weakly negatively correlated with the CAVI score (R = − 0.3752, P < 0.0001 and R = − 0.2080, P = 0.0063, respectively). Hel right screw max/TAV showed a moderate negative correlation with the CAVI score (R = − 0.4211, P < 0.0001). By contrast, Hel right screw ave, Hel right screw min, and Hel right screw min/TAV were not significantly correlated with the CAVI score (R = − 0.1221, P = 0.1116; R = 0.06518, P = 0.3970; and R = − 0.02836, P = 0.7127, respectively).

Hel left screw ave/TAV, Hel left screw min, and Hel left screw min/TAV were significantly positively correlated with the CAVI score (R = 0.3211, P < 0.0001; R = 0.1645, P = 0.0315; and R = 0.3776, P < 0.0001, respectively). By contrast, Hel left screw ave, Hel left screw max, and Hel left screw max/TAV were not significantly correlated with the CAVI score (R = 0.09810, P = 0.2018; R = − 0.04128, P = 0.5919; and R = 0.04988, P = 0.5171, respectively) (Fig. S1).

Discussion

This study was retrospective and included only patients who underwent cardiac MRI for suspected heart disease. This may introduce selection bias and limit the generalizability of the findings to the general population.

Aortic dilatation in older patients is associated with atherosclerosis [21, 22]. In this study, patients with a high CAVI score had a larger TAV and were older than patients with a low CAVI score. Furthermore, there was a relatively strong correlation between the CAVI score and TAV, suggesting a relationship between TAV and arterial stiffness.

We evaluated two types of hemodynamic parameters: those not divided by the TAV and voxel-based parameters that were divided by the TAV. We presumed that the hemodynamic parameters not divided by the TAV were strongly influenced by the TAV because they were calculated as the sum of the flow across the entire thoracic aorta. Specifically, since the blood flow parameters calculated using 4D flow MRI were the sum of the entire artery, the increase in value due to dilation and the decrease in value due to blood flow restriction canceled each other out in patients with arteriosclerosis. Therefore, hemodynamic parameter normalization was important. Notably, some hemodynamic parameters, such as Vort ave tended to have higher values in the high CAVI group than in the low CAVI group. However, most hemodynamic parameters not divided by the TAV did not show significant differences between the groups. Despite the larger TAV in the high CAVI group, there were no significant differences in hemodynamic parameter values compared with the low CAVI group, suggesting that hemodynamic parameters per unit volume were reduced in the high CAVI group. Therefore, we concluded that voxel-based flow parameters divided by the TAV better reflected the flow characteristics in the thoracic aorta related to AA.

4D MRI can provide various hemodynamic parameters, such as EL, Vort, and Hel [23]. In this study, there were significant differences in EL max/TAV between the groups. KE refers to the energy contained in the flow of blood due to its motion, while EL represents the KE lost as a result of frictional forces caused by fluid viscosity within the blood flow [24].

There were significant differences in Vort ave/TAV and Vort max/TAV between the groups. Vort is an indicator of spatial velocity gradients that may reveal complex hemodynamic phenomena [25].

Significant differences were also observed between the groups in Hel abs ave/TAV, Hel abs max/TAV, Hel right screw ave/TAV, Hel right screw max/TAV, Hel left screw ave/TAV, and Hel left screw min/TAV. Hel is an indicator of helical flow and was calculated by integrating the voxel-based absolute value of Vort × velocity. Hel describes corkscrew-like motion along the principal flow direction and is considered a normal feature in healthy individuals [26–28]. Helical flow increases as a result of altered aortic blood flow, often due to aortic valve disease [20, 29, 30].

In this study, the values for these voxel-based hemodynamic parameters tended to be lower in the high CAVI group than in the low CAVI group. The hemodynamic values were higher near the arteriosclerotic vessel walls. This may be due to turbulent blood flow on the side of the wall where arterial stiffness is severe. However, the overall lower values in the high CAVI group suggest that AA restricted blood flow within the lumen. Based on these findings, we propose that the primary pathogenesis of AA could involve the restriction of luminal blood flow rather than arterial wall sclerosis alone. Furthermore, many voxel-based parameters (e.g., max values) were lower in the high CAVI group, especially during the systolic phase, suggesting that AA may affect hemodynamic parameters, particularly during systole. Although previous research has shown that hemodynamic parameters can vary depending on the LVEF [31], and differences in the LVEF may influence these parameters. Superficially, a decrease in LVEF may result in a decrease in 4D flow parameters. However, there was no difference in the LVEF between the groups in this study. On the other hand, other decreased aortic compliance or age-related changes may also decrease in 4D flow parameters. There was difference in the age between the groups in this study, and the age-related changes may influence the results.

Vort min was significantly weakly positively correlated with the CAVI score in this study. Flow parameters not divided by the TAV may be influenced by AA-induced increases in the TAV. Helical parameters such as Hel abs max, Hel right screw max, and Hel left screw min (not divided by TAV) were weakly correlated with the CAVI score, but those divided by the TAV showed stronger correlations with the CAVI score. EL ave/TAV, EL max/TAV, Vort ave/TAV, Hel abs ave/TAV, Hel abs max/TAV, Hel abs min/TAV, Hel right screw ave/TAV, Hel left screw ave/TAV, and Hel left screw min/TAV were significantly weakly correlated with the CAVI, whereas Vort max/TAV and Hel right screw max/TAV showed moderate negative correlations with the CAVI score. Notably, these max (or partial min) parameters exhibited stronger correlations with the CAVI score than did their ave counterparts. These results suggest that the CAVI score is associated with greater restriction of blood flow within the lumen, especially during systole.

Blood flow in the thoracic aorta can be quantitatively evaluated using 4D MRI. To date, only one study has reported a correlation between the CAVI score and aortic distensibility using cardiovascular MRI [32]. However, to the best of our knowledge, no previous studies have examined the relationship between the CAVI score and hemodynamic parameters using MRI.

The global burden of ischemic atherosclerotic cardiovascular disease has risen, making it one of the leading causes of morbidity, loss of life years, and mortality [33]. Importantly, atherosclerosis is a condition that can be prevented through lifestyle changes and early intervention. Thus, the early diagnosis, severity grading, and prediction of atherosclerosis are crucial. The results of this study may be clinically useful because noninvasive quantitative evaluation of aortic volume and hemodynamic parameters could aid in diagnosing and evaluating patients with AA. Additionally, compared to CAVI test alone, 4D flow MRI may have the advantage of being able to visually evaluate arterial morphology and blood flow. Moreover, incorporating a 4D MR sequence into routine cardiac MRI, as done in this study, could help detect AA early because there is a relationship between heart failure and AA [34, 35]. However, this study does not demonstrate that 4D flow MRI parameters provide incremental value over CAVI alone. Future studies are needed to assess prognostic or reclassification ability. On the other hand, since this study used CAVI values ​​to determine arterial stiffness, caution is required when applying these results directly to the evaluation of arteriosclerosis. CAVI can evaluate arterial stiffness, but, arterial stiffness is not the same as arteriosclerosis although correlated.

This study had several limitations. First, it included patients from a single institution and lacked an external validation cohort. Second, patients with an interval between MRI and CAVI examination were included. Third, most patients underwent cardiac MRI with a 4D flow sequence because of suspected heart disease. We did not consider potential influence of heart rate, blood pressure, and medication use on CAVI between the groups. These factors could influence both CAVI and 4D parameters; thus, the results may not be generalizable to the entire population. Forth, dividing hemodynamic parameters by TAV was used in this study, and strong positive correlation between CAVI and TAV may introduce mathematical coupling. Finally, although we used the CAVI score to assess AA, we were unable to directly evaluate AA within the thoracic aorta.

Conclusions

The TAV was larger, and the voxel-based hemodynamic parameters (EL, Vort, and Hel/TAV), were lower in the high CAVI group than in the low CAVI group. Moreover, these hemodynamic parameters were correlated with the CAVI score, which may reflect restricted luminal blood flow in the thoracic aorta due to AA. Thus, simultaneously measuring aortic volume and hemodynamic parameters using 4D MRI could represent a novel method for evaluating atherosclerosis.

Abbreviations

AA

Aortic atherosclerosis

CAVI

Cardio-ankle vascular index

3D

Three-dimensional

4D

Four-dimensional

MRI

Magnetic resonance imaging

LVEF

Left ventricular ejection fraction

EL

Energy loss

KE

Kinetic energy

Vort

Vorticity

Hel

Helicity

TAV

Thoracic aortic volume

BMI

Body mass index

SD

Standard deviation

ave

Average

min

Minimum

max

Maximum

abs

Absolute

Authors’ contributions

HK: Conception and design of the research, Writing of the manuscript. ES: Critical Review of the Manuscript. RT: Manuscript drafting. TN, MM, SM: Acquisition of data. All authors read and approved the final draft.

Funding

JSPS KAKENHI (Granted No. 21K07733).

Data availability

Data will be provided upon reasonable request by the corresponding author.

Declarations

Ethics approval and consent to participate

This study was approved by the Institutional Review Board of the Nagasaki University Hospital (The date of approval (16/9/2020) and the project identification code (20091416)) and adhered to the ethical standards of the Declaration of Helsinki. Informed consent was waived because of the retrospective study design, and patient records and information were anonymized and de-identified prior to analysis.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.