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Activity Index: A Tool to Identify Active Carotid Plaques 165
well as intra- and inter-center reproducibility [13–23]. Its advantages are wide avail-
ability, low cost, and possibility of repeated examinations without any deleterious
side effects.
Carotid plaque characterization may play a relevant role for clinical decision in
two cohorts of patients: (1) Identification of subgroups of asymptomatic patients
with a high stroke risk thus reducing the number of unnecessary invasive treatments
such as endarterectomy or stenting;
(2) Diagnosis of unstable lesions prone to increased stroke rate during carotid
stenting [24], and (3) Patients with 50–70% stenosis at a higher stroke risk.
The aim of the present investigation [25–28] was to develop High-Definition
Ultrasound (HDU) with computer-assisted plaque analysis to identify new morphological markers of plaque activity in patients with carotid bifurcation disease.
2 Method
All patients were studied with HDU using colour-flow duplex-scan equipment
(ATL – Advanced Technology Laboratories – model HDI 3000) with 7–10 MHz
probe, 60 dB dynamic range and post-processing linear curves. All the HDU
examinations were blindly performed by the same observer (LMP) without knowledge of the clinical and CT-scan evaluation.
Carotid bifurcation was imaged in longitudinal and transverse sections and the
best longitudinal section was chosen and recorded in black and white for further
analysis.
The computer-assisted evaluation used the software Adobe Photoshop
for standardization and echogenicity analysis. Standardization was achieved by
attributing a normalized pre-set value of 190 for the adventitia and 0 for the blood,
thus producing a modification of the characteristics of the entire image equal for all
examinations [14,15].
In this standardized image the plaque was outlined (segmentation) and a
histogram of the gray-scale distribution of pixels of the entire area of the lesion
was obtained. The following parameters were determined from the histogram:
(1) the gray-scale median (GSM); (2) the percentile 40 (P40), which represents
the percentage of “black” pixels (“echolucent” pixels). These two parameters were
considered as a measure of the whole echogenicity of the plaque and were analysed
in all plaques.
Carotid plaques were divided into homogenous and heterogenous according to
its echo-structure and ultrasonographic equivalents of the pathologic findings in
symptomatic lesions that were identified and are shown in Fig. 1.
For each lesion the degree of stenosis was also quantified using end-systolic
and end-diastolic velocity criteria combined with cross-section area reduction was
measured in transverse images of the lesion.
For statistical analysis software STATA 4.0 was used with categorial variables
analyszd by Chi-square and Fisher’s exact test and continuous variables were
analyzed by variance analysis and Student’s test.
3.0
166 L.M. Pedro et al.
Fig. 1 Ultrasonographic equivalents of morphologic and histologic markers of active plaques
The investigation proceeded into three steps:
Step1–Univariate analysis (Chi-square and Fisher exact test for categorial
variables and variance analysis and Student’s T test for continuous variables)
were used to determine the variables that were significant for the identification
of symptomatic plaques.
Step2–Determination of the probability of occurrence of symptomatic plaque
(odds value) for each significant variable:
Odds=number of symptomatic plaques with each significant variable/total
number with each significant variable.
Then, we proceed to a resizing of the odds value to a 0–100 numerical
scale to determine a score for each variable or subgroup inside the variable,
in order to calculate that a plaque with all significant variables present would
have a total score of 100. The Activity Index is the sum of the scores for each
variable.
Step3–Multivariate logistic regression analysis was used to determine the
true statistical significance of different odds for each subgroup or variable when
compared with the respective reference group (lower probability group).
3 Study 1: Relationship Between Global Plaque Echogenicity
and Neurological Symptoms and Cerebral Infarction
3.1 Population
The study included 106 carotid bifurcation plaques from 74 patients: 58 males
and 16 females. The mean age was 67 years (38–80) and all the patients had a
Activity Index: A Tool to Identify Active Carotid Plaques 167
neurologic evaluation. The carotid lesion was considered symptomatic when associated with amaurosis fugax or appropriate neurologic events (transitory, reversible
or established) on the ipsilateral carotid territory. A CT-Scan was obtained for all
the patients and was considered positive when cerebral infarcts were present in the
area of anterior and middle cerebral arteries.
3.2 Results
Thirty nine (37%) plaques were symptomatic and 66 (63%) were asymptomatic.
The mean degree of stenosis was 68% with the following distribution:
More than 70% stenosis – 54 lesions (51%)
Stenosis between 51% and 69% – 21 lesions (20%)
Stenosis between 30% and 50% – 30 lesions (29%)
Sixty seven plaques (63%) were classified as homogenous and 38 lesions (37%)
were considered as heterogenous.
By univariate analysis, the significant factors associated with symptomatic
lesions were provided the following (See Table 1):
(a) Homogenous lesions: the GSM and P40 of symptomatic plaques were signifi-
cantly lower than of asymptomatic plaques (respectively 36 versus 46 p = 0.03
and63versus46p = 0.01). This finding was observed in homogenous and
heterogeneous lesions and thebest cut-offto discriminate between symptomatic
and asymptomatic lesions was 32 for the GSM and 43 for the P40. Plaque
surface disruption was also more common in symptomatic plaques (53% versus
12% p < 0.01).
(b) Heterogenous lesions: the GSM and P40 of symptomatic plaques were signif-
icantly lower than of asymptomatic plaques (respectively 31 versus 44 p =
0.02and61versus49p = 0.02). Evidence of plaque surface disruption was
diagnosed in 72% of thesymptomatic plaques but only in 29% of asymptomatic
(p < 0.01). In heterogenoussymptomatic plaques therewas evidence of a juxtaluminal location of the echolucent region in 72% against 28% in asymptomatic
plaques (p < 0.01).
The results of the assessment are relatively important for each significant parameter
to calculatethe probability values that are presentedin Tables 2 and 3. Resizing these
odds value for a 0–100 scale allowed the obtention of a numerical score indicated
in Table 4. The Activity Index (AI) of each plaque is obtained by the sum of the
scores (Fig. 2). A plaque with heterogenous structure, with the echolucent region
juxta-luminal, >90% degree of stenosis, GSM < 32 and P40 > 42 is associated
with maximal AI of 100.
168 L.M. Pedro et al.
Tabl e 1 Results of the univariate analysis of symptomatic and asymptomatic plaques
Symptomatic Asymptomatic p
Homogenous plaque
• GSM 36 46 0.03
• P40 63 46 0.01
• Echogenic cap 28% 41% NS
• Plaque surface disruption 53% 12% <0.01
• Echogenic cap thickness/plaque thickness 12 12 NS
Heterogenous plaque
• GSM 31 44 0.02
• P40 61 49 0.02
• Plaque surface disruption 72% 29% <0.01
• Juxta-luminal location of the echolucent
72% 28% < 0.01
region without echogenic cap
• Echogenic cap thickness/plaque thickness 20 16 NS
• % of echolucent region 59% 57% NS
• Index echogenicity-area 0.5 0.5 NS
Tabl e 2 Calculation of the odds values, odds-ratios and confidence intervals for symptomatic
plaque in the group of HOMOGENOUS PLAQUES (reference groups: no plaque disruption;
stenosis <50%; GSM > 40; P40 < 42)
Odds Odds ratio C.I. 95% p
Homogenous plaque 0.22
Plaque surface disruption
No 0.13 −−
Yes 0.57 8.9 (2.3–32.9) < 0.001
Degree of stenosis
<50 0.11 −−
50–69 0.14 1.25 (0.1–15.8) 0.863
70–79 0.15 1.67 (0.2–1.4) 0.631
80–89 0.40 6.67 (1.9–25.8) 0.032
>90 0.50 10.0 (1.6–33.1) 0.014
GSM
<20 0.80 37.3 (3.1–63.0) < 0.001
20–32 0.38 11.2 (2.2–56.1) < 0.001
33–40 0.18 5.6 (1.2–26.7) 0.031
>40 0.09 −−−
P40
<42 0.07 −−−
42–55 0.18 4.9 (2–35) 0.036
56–63 0.27 6.5 (1.2–32.4) 0.021
>63 0.47 11.4 (2.0–36.1) < 0.001
Activity Index: A Tool to Identify Active Carotid Plaques 169
Tabl e 3 Calculation of the odds values, odds-ratios and confidence intervals for symptomatic
plaque in the group of HETEROGENOUS PLAQUES (reference groups: homogenous plaque;
central echolucent region; no plaque disruption; stenosis < 50%; GSM > 40; P40 < 42)
Odds Odds ratio C.I. 95% p
Heterogenous plaque 0.64 6.19 (2.6–14.8) <0.001
Location of the echolucent region
Central 0.14 −− −
Juxta-luminal 0.72 6.8 (1.8–21.2) 0.021
Plaque surface disruption
No 0.41 −− −
Yes 0.82 6.4 (1.5–27.4) <0.001
Degree of stenosis
<50 0.00 −− −
50–69 0.14 −− −
70–79 0.43 5.9 (2.4–10.7) 0.034
80–89 0.57 6.6 (3.7–12.5) 0.020
<90 1.00 22.1 (4.5–121.7) <0.001
GSM
<20 1.00 7.2 (1.7–29.6) 0.011
20–32 0.57 3.2 (0.9–10.7) 0.061
33–40 0.42 2.5 (0.7–10.1) 0.121
<40 0.12 −− −
P40
<42 0.23 −− −
42–55 0.44 2.7 (0.7–10.9) 0.288
56–63 0.53 3.3 (0.8–12.6) 0.092
<63 1.00 9.7 (1.8–26.6) <0.001
4 Study 2: Evaluation of the Diagnostic Accuracy of the AI
4.1 Population and Method
We studied 109 plaques from 67 patients with a mean age of 69 years (47–88);
27 (25%) were symptomatic, while 82 (75%) were asymptomatic.
The diagnostic accuracy of the AI was assessed and the same factors of plaque
echogenicity and echostructure, mentioned before, have been calculated, leading to
the determination of the AI for each plaque.
Then, the diagnostic parameters (sensitivity, specificity, positive predictivevalue,
negative predictive value, and overall accuracy) for the identification of the symptomatic plaque have been calculated using the ROC curve analysis methodology.
170 L.M. Pedro et al.
Tabl e 4 “Scores” for calculation of the ACTIVITY INDEX (symptomatic plaque)
Activity Index: A Tool to Identify Active Carotid Plaques 171
Fig. 2 Example of the calculation of the Activity Index in two separate plaques
4.2 Results
The mean degree of stenosis was 73% (31–99). Seventy one plaques (65%) were
classified as homogenous and 38 lesions (35%) were considered as heterogenous.
In symptomatic plaques the mean AI was 75 (41–100) and in asymptomatic
plaques the mean AI was 43 (22–100). We observed that 93% of symptomatic
plaques have an AI superior to 50 and 78% superior to 60. Eighty-two percent of
asymptomatic plaques have an AI lower than 60 and 70% lower than 50.The cut-off
point between the two groups, allowing the greater difference between them, is the
value of 52.
The calculation of diagnostic parameters using ROC curve analysis shows that
the best cut-off level for the AI in homogenous plaques is the value 53–60,
associated with sensitivity of 56%, specificity of 92%, positive predictive value of
50%, negative predictive value of 93%, and accuracy of 87%. For heterogenous
plaques the best cut-off levels were the values 52–53, associated with sensitivity
of 89%, specificity of 43–48%, positive predictive value of 59%, and negative
predictive value of 83–100%, and accuracy of 75–76%.
5 Discussion
The characterization of subgroups of carotid lesions associated with increased
neurological risk involves the detection of symptomatic plaques and asymptomatic
lesions prone to become symptomatic.
Since the publication of the major multicenter trials for both symptomatic
[1, 2] and asymptomatic [3, 4] carotid disease, the degree of stenosis became the
most important determinant of the therapeutical decision. Nevertheless, information
172 L.M. Pedro et al.
about plaque characteristics is obtained from endarterectomy specimens and from
coronary and carotid histologic studies it is confirmed that features such as intraplaque hemorrhage [29, 30] and ulceration [31], wide- [32, 33] and juxta-luminal
lipid/necrotic center [34], thin or ruptured fibrous cap [31] and an increased
infiltration by inflammatory cells were more frequently present in symptomatic
lesions. These parameters may be considered as markers of plaque instability and
increased neurological risk. Also a higher lipid [35] and blood content may increase
the plaque susceptibility to hemodynamic stress.
The concept of unstable carotid disease should therefore include two subgroups:
plaques with ruptured cap and vulnerable lesions which are prone to rupture,
leading to local thrombosis and appropriate clinical events, by embolization or
ischemia due to artery occlusion. Reported observations from carotid occlusions
[36, 37] suggested an association of moderate degrees of stenosis with markers
of vulnerability or with ruptured fibrous cap, thus reproducing a similar situation
already recognized in acute coronary occlusions.
The importance of morphological characteristics of carotid lesions such as the
presence of plaque surface irregularity on angiography was recognized in the
medical arm of the Europen Carotid Stenosis Trial (ECST) [7] where its presence
increased the risk of neurological events at 2 years irrespective of the severity of
carotid stenosis, thus suggesting that alterations in plaque structure are independent
determinants of clinical risk.
B-mode ultrasonography and duplex scan provide analysis of the structure of
the atheromatous plaque beyond what can be unveiled by angiography, but its
reproducibility and diagnostic efficacy will be clearly improved by standardization
of images and objective and quantitative evaluation.
Newer generation of colour-flow duplex scan equipments, with improved quality
and high definition ultrasonographic image and computer-assisted plaque analysis
through digital image processing, and standardization provides objective study of
plaque structure thus in reducing variability and operator dependency [10].
Low plaque echogenicity demonstrated by the gray-scale median (GSM) [13,26]
obtained from pixel distribution within the plaque standardized image and the
amount of “echolucent” pixels (P40) [26–28] were associated with symptomatic
lesions and with the presence of brain infarcts in the carotid territory. Echolucency
has been related to increased content of blood and lipids, which are known
components of increased plaque vulnerability [38–40].
Our study expands in the evaluation of regional components of the plaque
and its distribution beyond single global echolucency measurements including
features recognized in pathological specimens as markers of plaque instability. Its
distribution within the lesion can be evaluated by measurement of Heterogeneity
Index [41], use of multiple cross-sectional views [42], and detailed plaque texture
analysis (DPTA) [43] but our method provides a unique objective analysis of all
the markers of instability that can be assessed by HDU. In heterogenous lesions,
we have introduced a new parameter – the juxta-luminal location of the echolucent
area – that may correspond to a lipid-necrotic core close to the vessel lumen either
with or without a fibrous (echogenic) cap overlying it as suggested in previous
pathological observations [26,27].
Activity Index: A Tool to Identify Active Carotid Plaques 173
The concept of an Activity Index encompassing the sum of the individual scores
for each significant parameter related with symptomatic (active) plaques including
echogenicity and other components of plaque structure, like surface disruption
and juxta-luminal location of the echolucent region in heterogenous plaques [27]
may provide a more objective evaluation of plaque activity that correlates with the
presence of appropriate neurologic symptoms in the carotid territory.
The Activity Index measurement may also contribute for the identification of
a subset of “dangerous” plaques particularly in asymptomatic patients with higher
neurological risk, thus contributing for a better selection for carotid endarterectomy
and thus reducing the number of unnecessary operations.
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