Investigating the early diagnostic value of popliteal artery wall shear stress in lower extremity arterial disease in type 2 diabetes patients using color doppler ultrasound combined with WSS quantitative analysis

doi:10.21203/rs.3.rs-4712099/v1

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Research Article

Investigating the early diagnostic value of popliteal artery wall shear stress in lower extremity arterial disease in type 2 diabetes patients using color doppler ultrasound combined with WSS quantitative analysis

https://doi.org/10.21203/rs.3.rs-4712099/v1

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Background

The global rise in type 2 diabetes mellitus (T2DM) has led to an epidemic of lower extremity arterial disease (LEAD), primarily caused by atherosclerosis and compounded by late detection and high treatment costs. Early detection is key for managing LEAD effectively. Color doppler ultrasound (DUS), a non-invasive and cost-effective technique, enhances early diagnosis through high-resolution imaging. Integrating DUS with proprietary MATLAB-based software for quantitative wall shear stress (WSS) analysis offers a non-invasive method to assess WSS. This approach targets the popliteal artery, using WSS as a reliable marker for early LEAD detection in T2DM patients.

Methods

This study included 202 patients clinically diagnosed with T2DM from March 2019 to November 2023 at Shanghai East Hospital, along with 69 healthy volunteers recruited during the same period. The T2DM group was further divided into three subgroups based on the intima-media thickness (IMT) of the popliteal artery: T2DM IMT normal group (IMT < 0.9 mm), T2DM IMT thickening group (1.0 ≤ IMT < 1.2 mm), and T2DM plaque formation group (IMT ≥ 1.2 mm). Using WSS quantitative analysis software, we calculated the average WSS of the popliteal artery and created two-dimensional WSS distribution maps, three-dimensional WSS spatial distribution maps, and WSS fusion images. Subsequently, we analyzed the WSS and its variation patterns among the control group, the T2DM group, and its various subgroups.

Results

In a study comparing T2DM patients to controls, T2DM groups showed significantly altered blood pressure, blood lipids, and blood viscosity, along with reduced WSS values, indicating advanced arterial damage. Specifically, WSS was lower in T2DM groups with normal and thickening IMT and those with plaque formation compared to controls. The optimal WSS cutoff for predicting LEAD was 1.82 dyne/cm², with a sensitivity of 68% and specificity of 83%. WSS negatively correlated with factors like age and disease duration, and positively with peak systolic velocity (PSV).

Conclusions

Non-invasive WSS measurement using DUS provides a valuable diagnostic tool for early LEAD detection in T2DM patients. Reduced WSS in the popliteal artery is a predictive marker of disease onset, offering potential for earlier intervention and better management of LEAD, ultimately improving patient outcomes.

Type 2 Diabetes Mellitus

Lower Extremity Arterial Disease

Wall Shear Stress

Color Doppler Ultrasound

Popliteal Artery

Atherosclerosis

In recent years, changes in the economy, diet, and social demographics have led to a global increase in the incidence of type 2 diabetes mellitus (T2DM), gradually reaching epidemic proportions[1]. Lower extremity arterial disease (LEAD) is one of the most common complications of T2DM, characterized by prolonged disease duration, high treatment costs, high rates of amputation, and mortality[2]. It has become a serious public health issue that severely threatens human health. Therefore, a safe, economical, and effective method for early diagnosis and prediction of LEAD in T2DM patients, enabling prompt clinical prevention and treatment, is crucial for reversing LEAD and reducing amputation and mortality rates among diabetic patients.

In T2DM patients, LEAD primarily refers to ischemic diseases of the lower limbs caused by atherosclerosis[3]. The clinical manifestations of LEAD primarily depend on the degree of obstruction in the lower limb arteries. In the early stages of the disease, symptoms are often concealed, with many patients showing no clinical symptoms or only experiencing cold limbs and abnormal skin sensations[4]. As the vascular lesions progress, patients gradually develop knee pain, intermittent claudication, limb ulcers, and gangrene. Once LEAD progresses to limb ischemia, reversing it through conventional treatments such as medication and physical rehabilitation becomes difficult. Patients with moderate to severe conditions require vascular reconstruction surgery to restore blood supply, with the cumulative rate of amputation or death within three years post-surgery reaching up to high level[5]. Once LEAD occurs in T2DM patients, merely assessing the risk associated with existing atherosclerotic plaques or the degree of vascular narrowing is too late. At this point, clinical interventions for atherosclerotic plaques are very limited, and non-surgical treatments can only delay plaque progression.

Currently, LEAD diagnosis primarily relies on imaging methods such as digital subtraction angiography (DSA), CT angiography (CTA), magnetic resonance angiography (MRA), and color doppler ultrasound (DUS)[6]. DSA, CTA, and MRA are invasive procedures associated with issues such as contrast agent allergies, radiation exposure, and high examination costs. Furthermore, DSA, CTA, and MRA can only diagnose LEAD when there is significant narrowing or obvious atherosclerotic plaques in the lower extremity vessels, making them less sensitive for early diagnosis. In contrast, DUS is non-invasive, safe, and inexpensive[7]. It produces pseudocolor blood flow images, allowing real-time and dynamic visualization of blood flow within the vessels. DUS has high spatial resolution, clear and detailed image content, and can display even small lesions and intima-media thickness (IMT) within the arteries. This provides a solid foundation for the early diagnosis and prediction of LEAD in T2DM patients.

Wall shear stress (WSS) is the tangential frictional force exerted by the flow of fluid over the surface of a blood vessel per unit area, acting directly on the endothelial cells within arteries[8]. Variations in WSS can induce genetic, molecular, and cellular changes in the vessel wall. WSS is considered a primary signaling factor in the initiation of atherosclerosis, playing a crucial role from the onset of the disease process to plaque formation. Extensive experimental research suggests that low WSS is a significant factor in promoting the occurrence and development of atherosclerosis[9]. Due to its "invisible" and "intangible" nature, measuring WSS presents specific challenges. Currently, MRI and ultrasound are commonly used to measure indirect parameters such as blood flow velocity and vessel diameter within arteries, with WSS being roughly calculated using the Hagen-Poiseuille equation[10]. This platform has developed proprietary WSS quantitative analysis software using MATLAB, integrating WSS with color Doppler flow imaging (CDFI) technology. This integration enables non-invasive quantitative analysis of WSS, making it "visible," and offers new possibilities for the early diagnosis and prediction of LEAD in T2DM patients.

LEAD in T2DM patients primarily refers to atherosclerotic lesions. LEAD is characterized by its staged and selective distribution. While small arteries in the lower limbs are prone to atherosclerosis, narrowing and occlusion of major vessels are the principal causes of adverse outcomes in LEAD [11]. Angiographic analysis of lower limb arteriosclerotic lesion distribution has shown that LEAD atherosclerotic lesions are more likely to occur at sites of stenosis or curvature in the major arteries of the lower limbs, consistent with the anatomical structure and physiological function of the popliteal artery. Traditionally, plaques also develop early at the bifurcation of the common femoral artery due to its unique physiological structure, but these plaques often exhibit independent characteristics and have a weak correlation with LEAD progression[12]. Moreover, the popliteal artery, as the "blood engine" of the calf, directly gives rise to the major arteries of the calf—the anterior tibial, posterior tibial, and peroneal arteries—making it highly significant for LEAD in terms of hemodynamics[13]. Anatomically, the popliteal artery passes through the adductor hiatus and runs behind the knee joint capsule and popliteus muscle, featuring a deep position, regular shape, and fixed, straight course. This makes it closer to the ideal vascular structure assumed in the Hagen-Poiseuille formula used in WSS quantitative analysis software, minimizing interference from other factors on the WSS of the popliteal artery. Therefore, popliteal artery WSS is a stable and continuous indicator for evaluating LEAD. This study selects popliteal artery WSS as a window to explore early diagnosis and prediction of LEAD in T2DM patients.

Clinical & Laboratory results

Clinical and laboratory results for the control group and the T2DM group are summarized in Table 1. Significant differences were observed in SBP, and BMI, with higher values in the T2DM group, and levels of HCT, Fib, TC, TG, LDL-C, FPG, 2h-PBG, HbA1c, and GA were also significantly higher compared to the control group (P < 0.05). There were no significant differences between the groups in terms of age, DBP, MAP and Cr (P > 0.05)

Table 1

Clinical and laboratory Characteristics in the Control Group and the T2DM Group
Variable	Control group	T2DM group	P-value
Age (years)	58.22 ± 10.35	61.56 ± 13.35	0.059
SBP (mmHg)	119.56 ± 12.28	126.13 ± 14.26	< 0.05
DBP(mmHg)	73.01 ± 8.20	79.58 ± 48.46	0.264
MAP(mmHg)	88.53 ± 8.50	95.10 ± 33.37	0.107
BMI (kg/m²)	22.91 ± 3.00	25.16 ± 4.37	< 0.05
HCT(%)	38.79 ± 3.04	40.85 ± 4.66	< 0.05
Fib(g/l)	2.77 ± 0.59	3.11 ± 1.02	< 0.05
TC(mmol/l)	3.45 ± 0.93	3.85 ± 1.17	< 0.05
TG(mmol/l)	1.14 ± 0.43	1.59 ± 1.08	< 0.05
HDL-C(mmol/l)	1.47 ± 0.45	1.23 ± 0.56	< 0.05
LDL-C(mmol/l)	2.13 ± 0.77	2.40 ± 1.05	< 0.05
Cr(mmol/l)	68.86 ± 12.63	72.79 ± 23.89	0.193
FPG(mmol/l)	5.39 ± 0.75	8.63 ± 2.79	< 0.05
2h-PBG(mmol/l)	6.66 ± 0.69	14.40 ± 4.57	< 0.05
HbA1c(%)	5.36 ± 0.57	9.48 ± 2.47	< 0.05
GA(%)	14.76 ± 1.45	25.44 ± 9.88	< 0.05

Clinical and laboratory results for the control group, T2DM IMT normal group, T2DM IMT thickening group, and T2DM plaque formation group are summarized in Table 2. Compared to the control group, the T2DM IMT normal group showed increased BMI, HCT, TC, TG, FPG, 2h-PBG, HbA1c, and GA, while age was decreased (P < 0.05). The T2DM IMT thickening group, compared to the control group, exhibited increases in BMI, HCT, FPG, 2h-PBG, HbA1c, and GA, with a decrease in HDL-C (P < 0.05). The T2DM plaque formation group, in comparison to the control group, showed increases in age, SBP, BMI, HCT, TG, FPG, 2h-PBG, HbA1c, and GA, with a decrease in HDL-C (P < 0.05). When comparing the T2DM IMT thickening group to the T2DM IMT normal group, there were increases in age and disease duration, with a decrease in TG (P < 0.05). Comparing the T2DM with plaque formation group to the T2DM IMT normal group, there were increases in age and disease duration (P < 0.05). When comparing the T2DM with plaque formation group to the T2DM IMT thickening group, there was an increase in age (P < 0.05). Between the control group, T2DM normal IMT, T2DM increased IMT, and T2DM plaque formation groups, there were no significant differences in DBP, MAP, Fib, LDL-C, Cr across any of the groups (P > 0.05).

Table 2

Clinical and laboratory Characteristics in the Control Group, T2DM IMT normal group, T2DM IMT thickening group, and T2DM plaque formation group
Variable	Control group	T2DM group
Variable	Control group	IMT normal	IMT thickening	plaque formation
Age (years)	58.22 ± 10.35^b	50.04 ± 13.6^c	61.53 ± 8.83^b	67.17 ± 12.75^a
Disease duration (years)	-	8.27 ± 8.10^b	12.28 ± 7.54^a	14.35 ± 8.75^a
SBP (mmHg)	119.56 ± 12.28^b	124.16 ± 13.54^ab	124.45 ± 12.46^ab	127.93 ± 15.06^a
DBP(mmHg)	73.01 ± 8.20^a	78.81 ± 8.47^a	75.51 ± 7.29^a	82.70 ± 68.77^a
MAP(mmHg)	88.53 ± 8.50^a	93.92 ± 9.39^a	91.82 ± 8.08^a	97.77 ± 46.78^a
BMI (kg/m²)	22.91 ± 3.00^b	25.76 ± 5.0^a	24.80 ± 5.07^a	25.06 ± 3.46^a
HCT(%)	38.79 ± 3.04^b	41.79 ± 5.26^a	41.12 ± 3.95^a	41.00 ± 4.64^a
Fib(g/l)	2.77 ± 0.59^a	3.03 ± 0.91^a	3.13 ± 0.98^a	3.14 ± 1.07^a
TC(mmol/l)	3.45 ± 0.93^b	4.06 ± 1.12^a	3.76 ± 1.22^ab	3.81 ± 1.15^ab
TG(mmol/l)	1.14 ± 0.43^c	1.86 ± 1.02^a	1.36 ± 0.67^bc	1.59 ± 1.25^ab
HDL-C(mmol/l)	1.47 ± 0.45^a	1.25 ± 0.63^ab	1.21 ± 0.44^b	1.23 ± 0.59^b
LDL-C(mmol/l)	2.13 ± 0.77^a	2.48 ± 0.98^a	2.41 ± 1.06^a	2.35 ± 1.07^a
Cr(mmol/l)	68.86 ± 12.63^a	67.45 ± 21.19^a	69.89 ± 14.74^a	76.97 ± 28.00^a
FPG(mmol/l)	5.39 ± 0.75^b	8.82 ± 2.2.79^a	8.49 ± 2.39^a	8.61 ± 2.98^a
2h-PBG(mmol/l)	6.66 ± 0.69^b	14.31 ± 4.38^a	13.74 ± 3.83^a	14.81 ± 4.96^a
HbA1c(%)	5.36 ± 0.57^b	8.95 ± 2.57^a	9.53 ± 2.38^a	9.72 ± 2.42^a
GA(%)	14.76 ± 1.45^b	24.61 ± 9.21^a	25.09 ± 8.16^a	26.04 ± 10.93^a

a, b, c The same letters indicate no significant difference between groups (P > 0.05), while different letters indicate a significant difference between groups (P < 0.05).

Popliteal artery ultrasound & WSS quantitative analysis results

Popliteal artery ultrasound parameters and quantitative WSS for the control group and the T2DM group are shown in Table 3. Compared to the control group, the T2DM group showed a significant reduction in PSV and WSS (P < 0.05). There were no significant differences in R between the two groups (P > 0.05).

Table 3

Popliteal artery ultrasound and WSS parameters in the Control Group and the T2DM Group
Variable	Control group	T2DM group	P-value
R(mm)	4.56 ± 0.79	4.75 ± 0.89	0.114
PSV(cm/s)	65.35 ± 13.94	51.31 ± 14.81	< 0.05
WSS(dyne/cm²)	2.36 ± 0.43	1.81 ± 0.53	< 0.05

As shown in Table 4, compared to the control group, the T2DM IMT normal group exhibited a significant reduction in WSS (P < 0.05). Both PSV and WSS were significantly reduced in the T2DM IMT thickening group compared to the control group (P < 0.05). Similarly, the T2DM plaque formation group exhibited significant reductions in PSV and WSS compared to the control group (P < 0.05). When comparing the T2DM IMT thickening group to the T2DM IMT normal group, a significant decrease in WSS was observed (P < 0.05). The T2DM plaque formation group showed significant reductions in PSV and WSS compared to the T2DM IMT normal group (P < 0.05). Additionally, PSV was significantly lower in the T2DM plaque formation group compared to the T2DM IMT thickening group (P < 0.05). There were no significant differences in R among the four groups (P > 0.05).

Table 4

Popliteal artery ultrasound and WSS parameters in the Control Group, T2DM IMT normal group, T2DM IMT thickening group, and T2DM plaque formation group
Variable	Control group	T2DM group
Variable	Control group	IMT normal	IMT thickening	plaque formation
R(mm)	4.56 ± 0.79^a	4.70 ± 0.81^a	4.86 ± 0.78^a	4.71 ± 0.97^a
PSV(cm/s)	65.35 ± 13.94^a	60.15 ± 12.16^ab	58.53 ± 13.30^b	43.03 ± 11.83^c
WSS(dyne/cm²)	2.36 ± 0.43^a	2.11 ± 0.60^b	1.81 ± 0.44^c	1.67 ± 0.48^c

a, b, c The same letters indicate no significant difference between groups (P > 0.05), while different letters indicate a significant difference between groups (P < 0.05).

Popliteal artery WSS predicts the occurrence of LEAD in T2DM patients

In the T2DM group, patients with IMT thickening and plaque formation were defined as positive, while those with normal IMT were defined as negative. A ROC curve for WSS in the popliteal artery was constructed, showing an area under the curve (AUC) of 0.81 (P < 0.05) (Table 5 and Fig. 2).

Based on statistical analysis, the Youden index was identified as the optimal cutoff point, with a calculated popliteal artery WSS Youden index of 1.82 dyne/cm². This value is considered the best cutoff for predicting the occurrence of LEAD in T2DM patients (Table 6).

Table 5

AUC for LEAD prediction in T2DM patients through popliteal artery WSS analysis
AUC	Standard Error	P-value	95% CI for OR
AUC	Standard Error	P-value	Lower Upper	Lower Upper
0.81	0.026	< 0.001	0.76	0.86

Table 6

The optimal cutoff value for predicting LEAD in T2DM patients using popliteal artery WSS
Popliteal Artery WSS	Sensitivity	Specificity	Youden's Index
1.82	0.68	0.83	0.50

Factors correlated with popliteal artery WSS in T2DM group

In the T2DM group, popliteal artery WSS was found to be significantly negatively correlated with age, duration of diabetes, and popliteal artery IMT, and positively correlated with PSV (P < 0.001). WSS showed a negative correlation with GA (P < 0.01). Additionally, WSS exhibited weak positive correlations with TC, TG, HCT, and a weak negative correlation with HbA1c (P < 0.05). There were no significant correlations between WSS and SBP, DBP, MAP, BMI, HDL-C, LDL-C, Cr, Fib, FPG, 2h-PBG and radius R (P > 0.05) (Table 7 and Fig. 3).

Table 7 Analysis of the correlation between different parameters and WSS in T2DM group

Variable		Age	Duration	SBP	DBP	MAP
Variable		(years)	(years)	(mmHg)	(mmHg)	(mmHg)
WSS	r	-0.50^***	-0.34^***	-0.10	0.01	0
WSS	P^	<0.001	<0.001	0.18	0.84	0.99

Variable		BMI	TC	TG	HDL-C	LDL-C
Variable		(kg/m²)	(mmol/l)	(mmol/l)	(mmol/l)	(mmol/l)
WSS	r	0.08	0.14^*	0.17^*	-0.1	0.09
WSS	P^	0.26	0.04	0.01	0.17	0.21

Variable		Cr	HCT	Fib	FPG	PBG
Variable		(mmol/l)	(%)	(%)	(mmol/l)	(mmol/l)
WSS	r	-0.02	0.18^*	-0.09	0.09	0.02
WSS	P^	0.75	0.01	0.23	0.21	0.82

Variable		HbAlc	GA	IMT	R	PSV
Variable		(%)	(%)	(mm)	(mm)	(cm/s)
WSS	r	-0.21^*	-0.18^**	-0.53^***	-0.04	0.57^***
WSS	P^	0.01	<0.01	<0.001	0.61	<0.001

r correlation coefficient; ^ denotes Pearson correlation analysis; *P<0.05; **P<0.01; ***P<0.001

Multiple linear regression analysis of popliteal artery WSS in the T2DM group

Using WSS as the dependent variable, and age, duration of disease, TC, TG, HCT, HbA1c, GA, popliteal artery IMT, and PSV as independent risk factors, a multiple linear regression analysis was conducted. The positive correlation coefficient R = 0.707 indicates a closely linear relationship and good model fit. WSS is positively correlated with PSV and negatively correlated with age, duration of disease, and popliteal artery IMT, all of which can serve as independent influencing factors affecting WSS (P < 0.05) (Tables 8 and 9).

Table 8

multiple linear regression model
R	R²	Adjusted R²	Se
0.707a	0.499	0.476	0.387
a Predictive variables include age, duration of disease, TC, TG, HCT, HbA1c, GA), popliteal artery IMT, PSV

Table 9

multiple linear regression coefficients of variables
Variable	Standardized Coefficients	t	P-value
Age(years)	-0.246	-4.125	<0.05
Duration(years)	-0.15	-2.585	<0.05
TC(mmol/l)	0.028	0.51	0.611
TG(mmol/l)	0.094	1.738	0.084
HCT(%)	-0.04	-0.731	0.466
HbA1c(%)	-0.109	-1.451	0.148
GA(%)	-0.004	-0.048	0.962
IMT(mm)	-0.23	-3.959	<0.05
PSV(cm/s)	0.312	5.076	<0.05

Diabetes is a systemic metabolic disorder characterized primarily by chronic hyperglycemia, with complications causing the main damage. T2DM accounts for 90% of all diabetes cases. The risk of LEAD in patients with T2DM is twice that of non-diabetic individuals[14]. LEAD in T2DM primarily refers to atherosclerotic changes, which, once established, are difficult to reverse. The treatment options available clinically are very limited, generally only capable of slowing the progression of atherosclerotic plaques[15]. Importantly, the early symptoms of LEAD are mild and insidious, and the disease progression often coincides with the progression of atherosclerosis[16]. Once the stage of limb ischemia is reached, the patient's condition can deteriorate rapidly, and the means of clinical intervention at this stage are extremely limited. Moderate to severe patients require vascular reconstruction to restore blood supply, and nearly half face amputation or mortality within three years post-surgery[17]. Currently, early diagnosis and prediction of atherosclerotic changes are the core components in the treatment of LEAD.

T2DM affects all body systems, leading to abnormalities in blood glucose, blood pressure, blood lipids, and blood viscosity[18]. By comparing clinical data of the control group and the T2DM group, we found that T2DM patients had higher FPG, 2h-PBG, HbA1c, GA, SPB, HCT, Fib, TC, TG, LDL-C, and FPG than the normal group, while HDL-C was lower (P < 0.05). Comparing three T2DM subgroups: IMT normal group, IMT thickening group, and plaque formation group, we found no significant statistical difference or linear relationship in FPG, 2h-PBG, HbA1c, GA, SPB, DBP, MAP, HCT, Fib, TC, and LDL-C (P > 0.05). However, HDL-C in the IMT thickening and plaque formation groups was lower than in the IMT normal group (P < 0.05), with no significant linear relationship. Although T2DM patients show significant changes in blood glucose, blood pressure, blood lipids, and blood viscosity compared to normal individuals, these do not fully reflect the progression of LEAD atherosclerosis. Currently, non-invasive imaging techniques like ultrasound can detect atherosclerotic plaques but cannot predict or dynamically assess atherosclerosis. Therefore, we need other sensitive and accurate indicators to predict the occurrence and development of atherosclerosis[19].

Vascular ultrasound is the most common method for measuring vascular IMT and plaques. Vascular ultrasound was used to record the diameter, IMT, PSV, and RI of the popliteal artery, and WSS was calculated using Hagen-Poiseuille. Compared to the control group, the T2DM group had significantly lower PSV and WSS (P < 0.05). There was no significant difference in R between the two groups (P > 0.05). All three T2DM subgroups had lower WSS than the control group (P < 0.05), indicating that WSS is a sensitive indicator for early assessment of lower limb atherosclerosis. Among the three T2DM subgroups (IMT normal group, IMT thickening group, and plaque formation group), the plaque formation group had significantly lower PSV compared to the IMT normal group and IMT thickening groups (P < 0.05). A decrease in blood flow velocity in the popliteal artery of the lower limb indicates hemodynamic changes. The center of the vessel has the highest blood flow velocity, which gradually decreases toward the vessel wall, forming a velocity gradient. When PSV decreases, the velocity gradient is affected, and the velocity near the vessel wall also decreases, which mechanically aligns with changes in WSS[20].

The IMT thickening group and the plaque formation group had lower WSS compared to the IMT normal group (P < 0.05), with no significant differences in R among the three subgroups (P > 0.05). In T2DM patients, WSS decreased even when the popliteal artery IMT was normal, and further decreased when IMT thickened. WSS, the mechanical force exerted by blood flow on the vessel wall, acts parallel to the vessel wall. WSS directly affects endothelial cells, having both physiological and pathological significance for the vessel wall. Hemodynamic changes drive alterations in WSS. This study shows that popliteal artery WSS decreases in T2DM patients before the onset of LEAD. When LEAD progresses to the IMT thickening stage, popliteal artery WSS further decreases, providing a hemodynamic basis for atherosclerotic plaque formation. Thus, a decrease in popliteal artery WSS can serve as an early warning indicator for LEAD before atherosclerosis occurs. Additionally, in this study, although WSS in the T2DM plaque formation group was lower than in the T2DM IMT thickening group, the difference was not significant (P > 0.05). The WSS quantitative analysis framework used in this study was developed using MATLAB. Our software extracts color flow signals from CDFI using digital image processing technology, converts color data of each pixel in CDFI to blood flow velocity data, and then converts it to shear stress data based on the WSS definition formula. Theoretically, it can analyze the WSS distribution in any vascular region of interest. This has been confirmed in previous studies by Wang et al[21]. However, the presence of plaques creates irregular and uneven surface structures in the vessel, significantly disrupting the ideal straight, regular, and rigid vessel structure required by the Hagen-Poiseuille formula for calculating WSS, causing the WSS in the T2DM plaque formation group to deviate from the ideal state[22].

In this study, WSS decreased even when the popliteal artery IMT was normal in T2DM patients. The area under the ROC curve (AUC) for predicting LEAD in T2DM patients using popliteal artery WSS was 0.81 (P < 0.05). Based on the Youden index, the optimal cutoff value for popliteal artery WSS was determined to be 1.82 dyne/cm², with a sensitivity of 68% and a specificity of 83%. When popliteal artery WSS is ≤ 1.82 dyne/cm², the likelihood of LEAD in T2DM patients is high, making it a critical indicator for LEAD occurrence.

This study analyzed the correlation and multiple regression between popliteal artery WSS and various variables in the diabetic group, finding that WSS is closely related to indicators causing severe endothelial dysfunction, changing blood viscosity, and affecting vascular compliance. In the T2DM group, WSS was negatively correlated with age, disease duration, GA, HbA1c, and popliteal artery IMT, and positively correlated with PSV, TC, TG, and HCT (P < 0.05). PSV, age, disease duration, and popliteal artery IMT were independent risk factors affecting WSS (P < 0.05). WSS, the tangential force directly contacting endothelial cells parallel to the vessel wall, can be influenced by blood flow velocity, blood viscosity, vascular compliance, and endothelial cell function. Age and diabetes duration are independent risk factors for WSS. As age increases, endothelial regulation and vascular compliance tend to show varying degrees of impairment. When blood flows through relatively straight and regular vessels, it can be considered a Newtonian fluid. In this case, WSS generated by adjacent fluid layers is proportional to the velocity gradient in the perpendicular direction. Therefore, PSV, an independent risk factor for WSS, can partly reflect WSS magnitude. When blood flow velocity decreases, WSS decreases, prolonging blood component residence time along the vessel wall, which low WSS more easily promotes atherosclerosis formation[23]. Identifying independent risk factors for WSS can help clinicians further investigate lipid levels, blood viscosity, and other WSS-related indicators in T2DM patients with reduced popliteal artery WSS for early clinical treatment. Patients with independent risk factors for WSS can be considered high-risk for LEAD and should undergo regular screening.

Using non-invasive, quantitative analysis of popliteal artery WSS in T2DM patients with color Doppler ultrasound provides imaging methods and evidence for the early diagnosis of LEAD; the reduction in popliteal artery shear stress occurs before the onset of LEAD in T2DM patients, showing good predictive value for the occurrence of such diseases. It is expected to become a new indicator for clinical prevention and early diagnosis and treatment of LEAD in T2DM patients.

Study participants and grouping

From March 2019 to November 2023, T2DM patients treated at Shanghai East Hospital and healthy volunteers from a health examination center were selected and divided into two groups: the type 2 diabetes mellitus group (T2DM group) and the control group (Control group). This study was approved by the Research Ethics Board of East Hospital, Tongji University (Shanghai, China) [Approval 2017 (No.030)].

(1) T2DM group: Participants in this group met the 1999 WHO criteria for diabetes diagnosis and classification[24]; those with type 1 diabetes, secondary diabetes, primary hyperlipidemia, hypertension, smoking history, lower limb arterial surgery, severe functional or organic heart disease, renal failure, stroke, or malignant tumors were excluded. Patients who had recently taken lipid-lowering, anticoagulant, or antiplatelet aggregation medications, or had recent adjustments in their diabetes treatment plans were also excluded. A total of 202 T2DM patients were selected for the study, including 126 males and 76 females, with an average age of 61.56 ± 13.35 years. Ultrasound was used to measure the intima-media thickness (IMT) of the popliteal artery. Based on the IMT, the T2DM group was divided into: T2DM IMT normal group: IMT < 0.9 mm (48 cases, 24 males and 24 females, average age 50.04 ± 13.6 years), T2DM IMT thickening group: 0.9 ≤ IMT < 1.2 mm (55 cases, 38 males and 17 females, average age 61.53 ± 8.83 years), and T2DM Plaque formation group: IMT ≥ 1.2 mm (99 cases, 64 males and 35 females, average age 67.17 ± 12.75 years).

(2) Control group: Participants with a history of diabetes, hypertension, primary hyperlipidemia, lower limb vascular disease, lower limb surgery, heart failure, organic heart disease, renal failure, stroke, or malignant tumors were excluded, as well as those who had recently taken any medications. A total of 69 healthy volunteers were selected for the study, including 32 males and 37 females, with an average age of 58.22 ± 10.35 years.

Clinical Data & Laboratory Findings

Clinical data collected included participant records of gender, age, medical history, and duration of diabetes for the T2DM group. Mean arterial pressure (MAP), body mass index (BMI), systolic blood pressure (SBP), and diastolic blood pressure (DBP) were measured for all subjects in both the control group and the T2DM group. The formula for calculating MAP is: MAP = (SBP + 2×DBP) / 3. SBP and DBP were manually measured using a mercury sphygmomanometer after a 10-minute rest period. All participants fasted for 12 hours and had venous blood drawn the following morning to test for glycated hemoglobin (HbA1c), fasting plasma glucose (FPG), two-hour postprandial blood glucose (2h-PBG), glycated albumin (GA), fibrinogen (Fib), hematocrit (HCT), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and creatinine (Cr).

Inspection methods

The Philips EPIQ7 system (Philips Medical Systems, Andover, MA, USA) with an L11-3 linear array transducer was used in our study. Before the examination, subjects were required to rest for 10 minutes, maintain a constant room temperature of 24°C, and fully expose their lower limbs. During the examination, subjects were instructed to lie in a prone position, breathe calmly, and relax their knee joints. Continuous scanning of the popliteal artery was performed from the adductor hiatus to the origin of the anterior tibial artery, ensuring an image frame rate of ≥ 30 frames/s. To ensure accuracy, all data were collected at least three times.

Parameters of popliteal artery ultrasound

The conventional data of popliteal artery ultrasound was collected. The transducer was positioned transversely, clearly displaying the anterior and posterior walls of the popliteal artery. At the thickest part of the IMT, the vascular image was locally magnified, and measurements were taken at the thickest part of the popliteal artery's posterior wall IMT and its maximum diameter. The transducer was then rotated to the longitudinal plane at the thickest part of the IMT, ensuring the vessel course was straight. The ultrasound plane passed through the vessel's central axis, clearly displaying the anterior and posterior walls of the popliteal artery, with the thickest part of the IMT centered in the image. Color Doppler flow was initiated, with the beam angle to the popliteal artery kept below 60°. The velocity range and sample box size were adjusted to 2 cm, and the blood flow gain was regulated to ensure the blood flow filled the lumen without aliasing or overflow. The peak systolic velocity (PSV) of the popliteal artery during systole, along with a 5-second dynamic color Doppler flow image of the lower limb popliteal artery, were collected, with the dynamic images stored in DICOM format.

WSS quantitative analysis by CDFI

Long-axis dynamic images of the popliteal artery spanning at least three cardiac cycles were obtained, and all CDFI images were saved in DICOM format (image matrix: 600×800; pixel spacing: 0.085×0.085 mm) and imported into a WSS (Wall Shear Stress) quantitative analysis software on the MATLAB platform (The Mathworks Inc., Natick, MA, USA). The software determined the coordinates of the color Doppler velocity scale from the image information to define the color blood flow pixels and the wall grayscale pixels. It converted the color pixel gradient into a velocity gradient based on the velocity scale. This allowed for the calculation of WSS values for each pixel on the image. The calculation formula for WSS is \(\:{\tau\:}_{w}=\mu\:{\gamma\:}_{w}=\mu\:\frac{du}{dr}|r=wall\).In this equation, \(\:{\tau\:}_{w}\) is the wall shear stress, which is the shear stress near the vessel wall. \(\:\mu\:\) is the viscosity of the blood, and \(\:\frac{du}{dr}\) represents the velocity gradient (or shear rate). \(\:r=wall\) means that \(\:r\) is near the boundary of tube. It was important to note that this formula assumed that blood is a Newtonian fluid. The WSS analysis software generated fusion images of WSS Doppler blood flow distribution, segmentation maps, and two-dimensional WSS distribution maps, further enabling the creation of three-dimensional blood flow velocity profiles and three-dimensional spatial distribution maps of WSS.As shown in Fig. 1. This ultimately facilitated the quantitative analysis and visualization of WSS.

Statistical analysis

Data statistical analysis was conducted using SPSS 24.0. (SPSS Inc., Chi cago, IL, USA). Quantitative and count data were expressed as mean ± standard deviation (x̄ ± s) and number of cases, respectively. The Shapiro-Wilk test was used to assess the distribution of continuous variables, while group comparisons were made using t-tests, non-parametric tests, chi-square (χ²) tests, and LSD multiple comparison methods. The predictive value of popliteal artery WSS for LEAD in patients with T2DM was analyzed using ROC curve analysis. The correlation between variables was assessed using Pearson correlation analysis. Multivariate linear regression was employed to analyze the relationship between popliteal artery WSS and various variables. A p-value < 0.05 was considered statistically significant.

Ethics approval and consent to participate

The study was performed in accordance with the Declaration of Helsinki. The Ethical approval of this study was provided by The East Hospital, Tongji University (Shanghai, China) [Approval 2017 (No.030)]. Written informed consent for publication was obtained from all participants

Consent for publication

All authors approved the final manuscript and the submission to this journal

Availability of data and materials

The datasets used during the current study are available from the corresponding author on reasonable request.

Competing interests

Competing interests the authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article

Funding

This study was funded by Important Weak Subject Construction Project of the Pudong Health and Family Planning Commission of Shanghai (Grant No. PWZbr2017-09)

Authors’ contributions

Performed the literature review: YXZ; Carried out Ultrasound measurements: JYG, YQS; Checked the validity of data: BZ, YXZ, HW; Data analysis: YXZ, HW; Supported the experiments financially: BZ; Wrote and revised the manuscript: BZ, YXZ, HW. All authors read and approved the final manuscript.

Competing Interests

The authors declared that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.

Acknowledgements

Not applicable.

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Investigating the early diagnostic value of popliteal artery wall shear stress in lower extremity arterial disease in type 2 diabetes patients using color doppler ultrasound combined with WSS quantitative analysis

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Abstract

Figures

Background

Results

Clinical & Laboratory results

Popliteal artery ultrasound & WSS quantitative analysis results

Popliteal artery WSS predicts the occurrence of LEAD in T2DM patients

Factors correlated with popliteal artery WSS in T2DM group

Multiple linear regression analysis of popliteal artery WSS in the T2DM group

Discussion

Conclusion

Methods

Study participants and grouping

Clinical Data & Laboratory Findings

Inspection methods

Parameters of popliteal artery ultrasound

WSS quantitative analysis by CDFI

Statistical analysis

Declarations

References

Additional Declarations

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Version 1