NON-INVASIVE VASCULAR IMAGING TECHNIQUESNON-INVASIVE VASCULAR IMAGING TECHNIQUES

RuiRui Hu, et al.Hu, et al.Jinshan Hospital, Jinshan Hospital,

Fudan University, Shanghai, ChinaFudan University, Shanghai, China

IN CARDIOVASCULAR RISK ASSESSMENTIN CARDIOVASCULAR RISK ASSESSMENT

IntroductionIntroduction

Non-invasive imaging techniques to detect atherosclerosis have emerged as useful tools for assessing the risk of cardiovascular diseases .

Series studies present the results of two cross-sectional studies, the applications of vascular ultrasound and ophthalmoscope in assessing structure or function in macrovasculature and microvasculature.

Vivid 5 Ultrasound Systems with a 10MHz Linear Array Transducer (GE Medical, Wisconsin, USA).

Diameters and Blood Flow of the Brachial Artery at Baseline and during Hyperaemia

Intima-Medial Thickness

Mean of Maximum Intima-Medial Thicknessfrom 12 Segments in the Carotid Arteries

Ultrasound examination

mmIMT

10 MHz

FMD=100%×(D1-D0)/D0

Flow mediated dilatation

METHODS - Study 1

Subjects279 pts enrolled before angigraphy148(53%) had CAD   

The presence of CAD was defined as angiographic evidence of significant stenosis of any coronary artery >=50%.

Reprinted with permission from Sinha et al., 2002

Table 1. Clinical Characteristics of Women and Men

Women Men P value

n=116 n=163

Age, years 63±11 61±12 0.09

Body mass index, kg/m2 26±4.0 26±3.7 0.80

Coronary artery disease, n (%) 49(42) 99(61) 0.002

Smoker, n (%) 12(10) 93(58) <0.001

Diabetes, n (%) 40(35) 31(19) 0.005

Hypertension, n (%) 69(60) 78(48) 0.09

Hypercholesterolemia, n (%) 62(53) 88(54) 1.00

FMD, % 3.91±3.54 4.06±3.44 0.73

NMD, % 13±6.71 12±5.26 0.21

mmIMT, mm 1.05±0.32 1.13±0.40 0.051

RESULTS

During a median follow up of 16 months, 36 patients (12.8%) experienced spontaneous cardiovascular events

cardiovascular deathacute myocardial infarctionunstable angina pectoris and congestive heart failure

Outcomes in follow-up

FMD>3.5%

FMD<3.5%P=0.0006

mmIMT<1.0mm

mmIMT>1.0mm

P=0.098

EventsEvents WomenWomen MenMen P valueP value

Non-CADNon-CAD 11.9%11.9% 1.6%1.6% 0.033*0.033*

CADCAD 17.2%17.2% 20.4%20.4% 0.660.66

All ptsAll pts 15.5%15.5% 11%11% 0.280.28

Table 2. Predictors of Spontaneous Cardiovascular Events by Cox Regression Model

Univariate Multivariate

Variable HR (95% CI) P value HR (95% CI) P value

Age, years 1.06 (1.03-1.10) 0.001 1.05(1.01-1.09) 0.029

Women 1.40 (0.73-2.69) 0.31 - -

Body mass index (kg/m2) 1.01(0.93-1.11) 0.75 - -

Current smoker 0.70 (0.33-1.36) 0.27 - -

Hypertension 0.90 (0.47-1.73) 0.75 - -

Diabetes 1.23 (0.61-2.51) 0.57 - -

Dyslipideamia 0.65 (0.33-1.26) 0.20 - -

Extent of CAD 1.40(1.06-1.86) 0.02 1.19(0.86-1.64) 0.29

mmIMT mm 1.96(0.98-3.95) 0.057 0.71(0.27-1.88) 0.49

FMD, % 0.82(0.72-0.91) <0.001 0.85(0.75-0.97) 0.012

NMD, % 0.92(0.86-0.98) 0.012 0.99(0.92-1.07) 0.88

FMD/NMD ratio 0.38(0.13-1.15) 0.088

FMD>3.5%

FMD<3.5%P=0.0006

mmIMT>1.0mm

P=0.098

FMD>3.5%

P=0.0006

Table 3 .Gender-specific Significant Predictors of Spontaneous Cardiovascular Events by Univariable Cox Regression Model

Women Men

Variable HR (95% CI) P value HR (95% CI) P value

Age, years 1.09 (1.03-1.17) 0.005 1.04 (1.99-1.09) 0.066

Extent of CAD 1.26(0.89-1.78) 0.19 1.90(1.05-3.44) 0.033

mm IMT, mm 1.79(0.55-5.80) 0.33 2.32(0.95-5.68) 0.066

FMD, % 0.85(0.73-0.98) 0.023 0.78(0.65-0.94) 0.009

NMD, % 0.93(0.86-1.01) 0.082 0.91(0.82-1.00) 0.057

In both men and women, impaired FMD predicted the occurrence of spontaneous cardiovascular events. Nevertheless, age but not the extent of CAD was also shown to be associated with increased risk of spontaneous cardiovascular events in women.

Recent studies suggested that arteriolar retinopathy reflected systemic microvascular disease and was associated with increased risk of cardiovascular events.

In the second cross-sectional study, the relationship between cardiovascular risk factors and arteriolar retinopathy as assessed by ophthalmoscope was investigated in 243 apparently healthy

Chinese subjects during routine health checks.

Study 2

METHODS - Study 2

SubjectSubject 243 subjects were rolled 243 subjects were rolled in in annual health annual health examination;examination;Male/Female: 159 / 84; Male/Female: 159 / 84; Mean age 4Mean age 43.13.1±7.9 yrs (21 - 60 yrs) ±7.9 yrs (21 - 60 yrs) PPrevalencerevalence OOverall arteriolar retinopathyverall arteriolar retinopathy 37.4% 37.4% GGrade 2 retinopathyrade 2 retinopathy 16%16% Risk factor profilesRisk factor profiles MMale ale 65% 65% SSmokers mokers 45% 45% Hyperhomocysteinaemia Hyperhomocysteinaemia 23.923.9%% HHypertension ypertension 30%30% OOverweightverweight 23% 23% DDiabetesiabetes 2%2%

Smoking habits status: Smoking habits status: nonsmokers, smokersnonsmokers, smokers;; -Cigarette consumption= pack per day -Cigarette consumption= pack per day ×× years years -Heavy smokers-Heavy smokers: : cigarette consumption cigarette consumption ≧≧20 pack*yr20 pack*yrss --Light smokers Light smokers : : < 20 pack*yr< 20 pack*yrss

DiagnoDiagnosstic criteria :tic criteria : -Grade 1: Narrowing of the -Grade 1: Narrowing of the arteriolar lumen; arteriolar lumen; -Grade 2: Sclerosis of the -Grade 2: Sclerosis of the adventitia and /or thickening of the adventitia and /or thickening of the arteriolar wall, visible as arteriolar wall, visible as arteriovenous nippingarteriovenous nipping

Grade 1 retinopathyGrade 1 retinopathyGrade 1 retinopathyGrade 1 retinopathyGrade 1 retinopathyGrade 1 retinopathy

Grade 2 retinopathyGrade 2 retinopathyGrade 1 retinopathyGrade 1 retinopathy

TABLE 1. Characteristics of study subjects with grade 1, grade TABLE 1. Characteristics of study subjects with grade 1, grade 2 2 arteriolar retinopathy and without arteriolar retinopathyarteriolar retinopathy and without arteriolar retinopathy

Arteriolar Arteriolar

retinopathyretinopathy Normal Grade 1 Normal Grade 1 Grade Grade 2 2

n=152 n=52 n=39n=152 n=52 n=39

AgeAge (Yrs)(Yrs) 39.3 ± 7.1 49.2± 5.8*** 48.5 ± 4.539.3 ± 7.1 49.2± 5.8*** 48.5 ± 4.5 *** ***

BMI (Kg/mBMI (Kg/m22)) 23.1± 2.6 24.2± 2.5 * 26.1 ± 2.7***23.1± 2.6 24.2± 2.5 * 26.1 ± 2.7***

tHcy(μmol/L)tHcy(μmol/L) 11.5± 1.54 11.1±1.41 11.5± 1.54 11.1±1.41 17.5 ± 1.9217.5 ± 1.92 *** ***

Hypertension%Hypertension% 13.8 42.3 *** 74.4 ***13.8 42.3 *** 74.4 ***

Smoker%Smoker% 42.0 42.3 62.3***42.0 42.3 62.3***

RESULTS

Interactions of plasma tHcy levels with smoking and other risk factors

Table 2 Multiple Linear Regression Model of Fasting tHcy LevelTable 2 Multiple Linear Regression Model of Fasting tHcy Level N=243, RN=243, R22=22.1%=22.1%

BB SE(B)SE(B) PP

MaleMale gendergender 3.49 1.38 0.012 3.49 1.38 0.012

Cigarette consumption Cigarette consumption 0.26 0.07 <0.001 0.26 0.07 <0.001

(Pack*yrs)(Pack*yrs)

Hypertension Hypertension 2.83 1.38 0.0412.83 1.38 0.041

(Constant) (Constant) 9.919.91 6.03 6.03

a Dependent Variable: Hcya Dependent Variable: Hcy

b Independent variables entered: smoking consumption, male gender, and b Independent variables entered: smoking consumption, male gender, and hypertensionhypertension

c Excluded parameters: age, body mass index, diabetes mellitusc Excluded parameters: age, body mass index, diabetes mellitus

Figure 1: Fasting plasma tHcy levels related tosmoking in a dose-dependent manner in male gender

12.4

15.1

17.6

0

5

10

15

20

1 2 3

Smoker

mean tHcy

1 nonsmoker1 nonsmoker2 light 2 light smokersmoker3 3 heavy heavy smokersmoker

Table 3: Comparison of characteristicsTable 3: Comparison of characteristics of smokers and nonsmokers in maleof smokers and nonsmokers in male

VariablesVariables NONSMOKERNONSMOKER SMOKERSMOKER

N=43N=43 N=114N=114

AgeAge yrs yrs 44.9±8.744.9±8.7 44.1±7.644.1±7.6

BMIBMI kg/m2 kg/m2 24.2±2.8024.2±2.80 24.3±2.9224.3±2.92

tHcy tHcy μmol/L μmol/L 12.4±1.4512.4±1.45 15.6 ±1.5615.6 ±1.56**

SBPSBP mmHg mmHg 118.6 ±12.2118.6 ±12.2 124.0±16.6124.0±16.6

DBPDBP mmHg mmHg 81.9±9.5181.9±9.51 84.0±11.184.0±11.1

TriglyceridesTriglycerides mmol/L mmol/L 2.44±2.512.44±2.51 2.18±1.242.18±1.24

Cholesterol Cholesterol mmol/L mmol/L 4.60±0.874.60±0.87 4.59±0.704.59±0.70

Blood glucose Blood glucose mmol/Lmmol/L 4.99±0.744.99±0.74 5.05±0.785.05±0.78

HyperhomocysteinaemiaHyperhomocysteinaemia 14%14% 40.4%40.4%******

HypertensionHypertension 39.5%39.5% 40.5%40.5%

Grade 2 arteriolar retinopathyGrade 2 arteriolar retinopathy

OverallOverall arteriolar retinopathyarteriolar retinopathy

9.3%9.3%

42%42%

26.326.3****

45%45%

VariablesVariables All retinopathy All retinopathy Grade Grade retinopathyⅡretinopathyⅡ

OR ( 95% CI ) OR ( 95% CI ) OR ( 95% CI ) OR ( 95% CI )

AgeAge (per 10 year )(per 10 year ) 8.958.95 (4.14-19.4) (4.14-19.4)****** 2.25 2.25 (1.17-4.32)(1.17-4.32)****

Male gender Male gender 0.70 (0.22-2.17) 0.33 (0.73-1.53) 0.70 (0.22-2.17) 0.33 (0.73-1.53)

Overweight Overweight 1.94 (0.92-4.06) 1.94 (0.92-4.06) 3.103.10 (1.35-7.13) (1.35-7.13)* *

HypertensionHypertension 5.455.45(2.45-12.1) (2.45-12.1) ****** 5.405.40 (2.24-13.0) (2.24-13.0)******

Cigarette Smoking Cigarette Smoking 1.56(0.55-4.46) 1.56(0.55-4.46) 4.194.19 (1.17-15.0) (1.17-15.0)**

Hyperhomocysteinaema Hyperhomocysteinaema 1.01(0.41-2.47) 2.14 (0.85-5.41) 1.01(0.41-2.47) 2.14 (0.85-5.41)

TABLE 4. Logistic regression analysis for TABLE 4. Logistic regression analysis for predicting arteriolar retinopathypredicting arteriolar retinopathy

In this study, aging, hypertension, smoking and being overweight were identified as important risk factors for the presence of arteriolar retinopathy.

Conclusion

In conclusion, structural or functional measurement in macrovasculature and microvasculature with various non-invasive techniques could provide valuable information for the assessment of patients with cardiovascular diseases or risk factors.

In addtion, aging is an important risk factor of cardiovascular disease in both study.

Aging : A Global Challenge

Implications in the prevention and treatment of cardiovascular disease

Coping strategy remains largely unknown

Unprecedented

Pervasive

Enduring

Increasing burden of cardiovascular diseases globally.

Vascular disease also have become the leading causes of death among Chinese adults.

http://www.un.org/esa/population/publications/worldageing19502050/

He J, Gu D, Wu X, Reynolds K, Duan X, Yao C, Wang J, Chen CS, Chen J, Wildman RP, Klag MJ, Whelton PK. Major causes of death among men and women in China. N Engl J Med. 2005; 353:1124-1134.

Yusuf S, Reddy S, Ôunpuu S, Anand S. Global burden of cardiovascular diseases: part I: general considerations, the epidemiologic transition, risk factors, and impact of urbanization. Circulation. 2001; 104: 2746-2753.