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Morphological age-dependent development of the human carotid bifurcation
ARTICLE IN PRESS
Journal of Biomechanics 38 (2005) 453–465
Morphological age-dependent development of the human carotid bifurcation Jaehoon Seonga, Baruch B. Liebera,b,*, Ajay K. Wakhloob,c a
Department of Biomedical Engineering, University of Miami, College of Engineering, Coral Gables, FL, USA b Department of Radiology, University of Miami, School of Medicine, Miami, FL, USA c Department of Neurosurgery, University of Miami, School of Medicine, Miami, FL, USA Accepted 26 April 2004
Abstract The unique morphology of the adult human carotid bifurcation and its sinus has been investigated extensively, but its long-term, age-dependent development has not. It is important fundamentally and clinically to understand the hemodynamics and developmental forces that play a role in remodeling of the carotid bifurcation and maturation of the sinus in association with brain maturation. This understanding can lead to better prognostication and therapy of carotid disease. We analyzed the change of sinus morphology and the angle of the carotid bifurcation in four postnatal developmental stages (Group I: 0–2 years, Group II: 3–9 years, Group III: 10–19 years, and Group IV: 20–36 years, respectively) using multiprojection digital subtraction angiograms and image post-processing techniques. The most significant findings are the substantial growth of the internal carotid artery (ICA) with age and the development of a carotid sinus at the root of the ICA during late adolescence. The bifurcation angle remains virtually unchanged from infancy to adulthood. However, the angle split between the ICA and external carotid artery (ECA) relative to the common carotid artery (CCA) undergoes significant changes. Initially, the ICA appears to emanate as a side branch. Later in life, to reduce hydraulic resistance in response to increased flow demand by the brain, the bifurcation is remodeled to a construct in which both daughter vessels are a skewed continuation of the parent artery. This study provides a new analysis method to examine the development of the human carotid bifurcation over the developmental years, despite the small and sparse database. A larger database will enable in the future a more extensive analysis such as gender or racial differences. r 2004 Elsevier Ltd. All rights reserved. Keywords: Carotid bifurcation; Carotid morphology; Carotid sinus; Vascular remodeling
1. Introduction The structure of the carotid bifurcation is unique in that the root of the internal carotid artery (ICA), which supplies blood to the brain, is usually enlarged. This region is referred to as the carotid sinus. The ICA does not harbor any branches until just before the circle of Willis, where it branches into the ophthalmic artery. Therefore, the root of the ICA can be considered as the origin of the cerebral circulation. *Corresponding author. Department of Biomedical Engineering, University of Miami, 1251 Memorial Drive, Coral Gables, FL 33146, USA. Tel.: +1-305-284-2330; fax: +1-305-284-6494. E-mail address: [email protected] (B.B. Lieber). 0021-9290/$ - see front matter r 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.jbiomech.2004.04.022
The development and the function of the human carotid sinus are not clearly understood yet. The arterial wall of the carotid sinus is densely enervated and contains baroreceptive neural terminals. It has been hypothesized that the dilation serves to support pressure sensing (Arndt et al., 1968). Another hypothesis based on phenomenological observations presumes that the function of the sinus is to slow the blood flow and reduce the pulsatility in order to protect the brain (Cavazzani, 1905). More recently, in vitro and computational models have been used to investigate carotid hemodynamics (Baaijens et al., 1993; Gijsen et al., 1999; Kitney and Giddens, 1983; Ku and Giddens, 1983). Complex flow patterns have been found in the carotid sinus (Bharadvaj et al., 1982a). These patterns have been
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implicated in carotid bulb wall heterogeneity and subsequent development of atherosclerosis at this site. As the atherosclerotic plaque develops, the elicited biological response is an attempt to cover the plaque with a fibrous cap. Unfortunately, over time the fibrous cap may rupture, releasing the underlying debris, i.e., emboli, into the circulation. The circulation carries this debris into the brain, producing a number of different symptoms. The worst complication is blockage of a major cerebral blood vessel, producing an ischemic stroke (Chuang, 1989; Harrison and Marshall, 1983). Studies by McGill (1968) have shown that atherosclerosis of the carotid sinus begins in mid-adolescence. Peterson et al. (1960) found that gross atherosclerotic lesions progress with age and concluded that the common carotid artery (CCA) proximal to the bifurcation and the ICA distal to the bifurcation show a marked increase in size with advancing age. Previous investigations on the geometry of the carotid bifurcation provided important insight into its structure in adults, although each study yielded different morphological information (Adam, 1958; Affeld et al., 1998; Bharadvaj et al., 1982a; Salzar et al., 1995). Specifically, the diameters of the CCA and the sinus in the various investigations vary significantly (Table 1). In a recent study that reviewed 5395 angiograms from 3007 patients (Schulz and Rothwell, 2001), a large variation in carotid bifurcation anatomy was considered as a risk factor for atheroma. However, individuals selected for the study were patients with recent ocular or carotid territory cerebral ischemia; therefore, the study was limited to mature individuals, and the early developmental years were not considered. The long-term remodeling of the carotid bifurcation and its sinus during human developmental stages and its unique structure at maturity has not been investigated. The carotid sinus experiences a remarkable increase in
size from birth to adulthood. Furthermore, the parent and daughter vessels do not lie in the same plane at the bifurcation, as suggested previously by simplified models. Therefore, we investigated the age-dependent morphological changes of the carotid bifurcation during four human developmental stages.
2. Materials and methods 2.1. Patient population Digital subtraction angiograms (DSAs) of carotid bifurcations from various human developmental stages were evaluated. Patients underwent angiographies of their cerebrovascular system for other causes. Informed consent was obtained from the patients or their surrogates for additional imaging of the carotid bulb. No patients presenting with arteriovenous malformations or other vascular disease, which would have potentially altered the carotid bulb morphology, were enrolled. Although DSA procedures are expensive and carry minimal risk of causing a stroke, angiographic spatial resolution is unmatched by other imaging modalities (Schulz and Rothwell, 2001). Biplane DSA was used to obtain the most accurate morphological carotid bifurcation images for analysis. Ninety-five angiograms were obtained from 36 patients ranging in age from newborn infants to 36year-old adults. Fifty-eight lateral (LAT) projections and 37 anterior–posterior (AP) angiographic projections were used in the analysis. To investigate age-dependent changes in morphology, the angiograms were divided into four groups representing various human developmental stages: newborn (Group I: 0–2 years), pediatric (Group II: 3–9 years), adolescent (Group III: 10–19 years), and adult (Group IV: 20–36 years). Additional
Table 1 Diameters and bifurcation angles of human carotid arteries in three often cited studies
Bharadvaj et al. (1982a, b) Salzar et al. (1995) Affeld et al. (1998)
CCA (mm)
ICA sinus (mm)
ICA (mm)
ECA (mm)
Bifurcation angle
8.0 6.4 5.7–5.9
8.9 6.0 6.2–6.9
5.6 4.9 4.7–5.1
4.6 4.5 4.1–4.7
50.5 N/A 56.9 715.2
Table 2 Patient database
Age (years) Average age Number of patients Number of cases (lateral projection) Number of cases (anterior–posterior projection)
Group I
Group II
Group III
Group IV
Total
0–2 0.870.5 9 15 7
3–9 4.071.7 6 10 7
10–19 13.972.3 7 13 10
20–36 26.374.8 14 20 13
36 58 37
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information on the patient population is provided (Table 2). 2.2. Image preparation and calibration Biplane DSAs of the carotid bifurcation were obtained during angiographic procedures for indications of cerebrovascular pathologies other than carotid disease. Angiograms of the left and right carotid bifurcation were acquired in AP and LAT projections using a biplane angiography unit (Toshiba Super Angiorex model G, Toshiba, Tokyo, Japan). After careful review of each angiogram, all cases involving pathology of the carotid arteries were excluded. Cases free of carotid disease were selected for further analysis, and the angiographic images were printed on X-ray film. Using a high-resolution scanner (UMAX Astra 2400S–UMAX Technologies, Inc., Fremont, CA), the films were scanned into a personal computer (Fig. 1A). Binary images (Fig. 1B) of the carotid arteries were constructed from the grayscale images. A threshold operation was used to differentiate between the carotid arteries and the background using Adobe Photoshop 5.0 (Adobe Systems, Inc., San Jose, CA) and Scion Image (shareware NIH image processing program—http:// www.scioncorp.com). Values above the threshold were considered noise and set to white, while values below the threshold were set to black. The calibration of images was performed using either the calibration feature of the angiography unit or a feature of known physical dimensions in the image (such as a metal washer), the mm/pixel ratio of the image was
Fig. 1. (A) Scanned angiographic image and (B) binary image.
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determined and magnified (or reduced) as necessary to a ratio of 0.15 mm/pixel to enable the averaging of different images. The centerline of the binary images was obtained by the application of a parallel symmetric thinning operation (Bourbakis et al., 1997; Lam et al., 1992), and the outline of the bifurcation was found by an edge-detection operation in MATLAB (MathWorks, Natick, MA) (Gonzalez and Woods, 1992). This high performance thinning algorithm executes fully symmetric erosion to obtain the centerline (Fig. 2A). It is not sensitive to minor variations of the edge configuration because it increases the size of the operator support for solving a connectivity problem in the thinned objects (Bourbakis et al., 1997). Therefore, the uncertainty in the location of the skeletonized object is about 7half a pixel, translated to physical dimensions it is about70.07 mm. As can be seen in Fig. 2A, the centerline generated using the above algorithm has spots thicker than one pixel manifesting the uncertainty of the algorithm in determining the exact center at these locations. However, this compensatory mechanism is used to guarantee a continuous line. To eliminate these minor distortions, a polynomial was fit to the centerline (Fig. 2B) and the branch diameters as well as bifurcating angles of the carotid arteries were then calculated from the newly obtained centerline/outline images at 20 pixel intervals (3 mm) along the centerline (Fig. 2C). 2.3. Simultaneous rotation of the projection The three branches at the carotid bifurcation generally do not lie in a flat plane. Furthermore, images were always acquired in the AP/LAT projections of the patients, but these are not necessarily the optimal planes of the bifurcation. An angiogram of a 3-year-old male in which the daughter branches of the CCA are not superposed in either projection is shown in Fig. 3. Cases like the one presented (Fig. 3) required a rotational transformation to obtain a reasonably planar view of the bifurcation in a projection that is orthogonal to the bifurcation plane. Rotation of the views to the bifurcation plane and its orthogonal counterpart affords comparison of the bifurcations of different individuals. To minimize the angle between the daughter branches in one projection, the skeletons of the original projections were rotated simultaneously to overlay the centerline of the two daughter branches in one projection or minimize the angle between them. After the angle of the rotational transformation was determined, the new orthogonal projections were constructed. The projection in which the angle between the daughter branches was minimized was considered the frontal (or AP) projection, and the other was considered the LAT projection. The skeletonized images of the bifurcation requiring rotation provide essentially two orthogonal projections
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40 100
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ECA
80 60 40
D
D
C
C B
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0
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0 DI
A -20
B C
CCA
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(A)
DE
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20 40
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-20
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Fig. 2. (A) Centerline and outline of the carotid bifurcation image. (B) Location along the centerline where the diameters of the branches were calculated, and (C) how the angle of bifurcation was calculated.
After the skeletonized image of the bifurcation was rotated into the desired position, the body of the bifurcation was rebuilt around the centerline using a thickening operation until the rebuilt bifurcation reached the transformed outlines (Fig. 6). 2.4. Phase shift ensemble averaging of the images
Fig. 3. (A) AP and (B) LAT projection angiograms. The daughter branches are not superposed in either projection.
of the three-dimensional (3-D) centerline. The intersection point of the centerline of the CCA and the centerlines of the two daughter branches was selected as the origin of the coordinate system for the transformation. The 3-D coordinates of the centerline were then calculated from the projections, and rotated by the determined angle (Fig. 4). The new orthogonal AP and LAT projections of the centerline are shown with the non-rotated projection shown on the same plot for comparison (Fig. 5). One can clearly see the different appearance of the geometry before and after rotation.
Once the LAT and the AP projections of the bifurcations were judged to be optimal, they were subjected to further analysis to obtain the average morphology of the carotid bifurcation in both projections. The following describes the analysis steps required to obtain the average morphology within each age group. Each image may contain an arbitrary angular shift around an axis through the bifurcation point perpendicular to either projection. Therefore, a constructed ensemble average may not be optimal, but it can be refined in an iterative process using a phase shift averaging technique (Bendat and Piersol, 1986; Kitney and Giddens, 1983). The principle of phase shift averaging is first to construct the ensemble average and then determine the cross correlation function between each individual element in the ensemble and the ensemble average. If the cross correlation function maximum value does not occur at a zero shift, the element in the ensemble is shifted by that amount. The process is repeated for all elements, and a new ensemble average is constructed from the shifted elements. The process continues until the shift between each element and refined ensemble average meets an arbitrary convergence criterion. To obtain the optimal angular shift for each image in the ensemble, all images were first transformed into polar coordinates with an angular resolution of 1 (Fig. 7). This transformation was required because the maximum value of the cross correlation function of the
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Fig. 4. (A) Skeletonized image of the 3-D bifurcation shown in Fig. 3. (B) The skeleton image after it was rotated to minimize the angle between two daughter branches in the AP projection.
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Fig. 5. Comparison between the skeletons of the bifurcation before (dashed line) and after (solid line) rotation in the AP (A) and LAT projection (B). Fig. 7. Transformation of an image from rectangular to polar coordinates.
Fig. 6. Binary images of the bifurcation in the LAT plane before (A) and after (B) rotation.
rectangular images yields only information about the translational shift between the images in the X 2Y direction and not the rotation. By transforming the images into polar coordinates the information obtained from the cross correlation function pertains to translations in R and F; and changes in F are the desired rotational shifts. The origin of a right hand coordinate system was placed at the bifurcation point, and the polar coordinates were defined in the usual manner (Fig. 7). When attempting to obtain the cross correlation between the individual image and the constructed
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assemble average in the polar coordinates, it became apparent that the CCA is the dominant feature at the expense of the daughter branches. To reduce the influence of the CCA, only the daughter branches were transformed into polar coordinates to determine the best angular shift for each image through the iterative process as described before. The construct of the ensemble average prior to shifting of the images is shown in Fig. 8. The convergence criteria for termination of the iterative procedure were selected as follows. First, no individual image was allowed to deviate more than 1 from the final constructed average. Second, the sum of all images that deviated from the constructed ensemble average was not allowed to exceed 50% of the number of images in the ensemble. Because the individual images in the ensemble were binary (0 or 1), the ensemble average divided by the total number of images yielded a range of values between 0 and 1. The ensemble-averaged body of the branches was determined as the locus of all points with a pixel intensity value larger than 0.5, while lower values were set to background (a zero pixel value). For presentation purposes, the foreground value was set to 0.7 rather than 1.0 (Fig. 8). After the convergence criteria were satisfied, each of the rectangular coordinate images was rotated at the calculated angle. In a manner similar to the averaging processing in the polar coordinate, the morphological average images were obtained by summation of all the individually rotated images in rectangular coordinates and dividing these image by the total number of images in the ensemble. Finally, the morphological average bifurcation was determined by setting values above 0.5 to foreground and values below 0.5 to background (Fig. 9). 2.5. Additional consideration for the anterior–posterior projection In the LAT projection, the bifurcation point was readily obtained simply by a thinning operation; however, identifying the bifurcation point in the AP projection is more difficult because ICA and external
Fig. 8. Ensemble-averaged image in polar coordinates before phase shift refinement.
Fig. 9. (A) Grayscale overlay of all images in the ensemble and (B) morphological average image after intensity thresholding and binarization.
carotid artery (ECA) overlap. Therefore, the bifurcation point in the AP projection could not be found by a thinning operation as used in the LAT projection. To locate the bifurcation point in the AP projection, three images from both projections were used: the scanned LAT projection angiogram, the binary image of the LAT projection, and the scanned AP projection angiogram. Before analyzing the AP images, they were calibrated to a ratio of 0.15 mm/pixel in the same way the LAT projection images were calibrated. After image calibration, the length of the segment between the bifurcation point and the bifurcation apex in the LAT projection was calculated. This measurement should be the same for both projections. Nonetheless, both points cannot be directly located on the AP image due to overlap. Therefore, branches of the ECA were used as anatomical landmarks to locate the bifurcation point in the AP projection. The lingual artery and facial artery were selected as identifiable landmarks in both projections, and their separation distances from the bifurcation and apex points in the LAT projection were assigned to the AP projection (Fig. 10). When two arteries of dissimilar diameters are superposed during angiography, the overlapped parts should, in principle, appear darker than the non-overlapped sections. Therefore, grayscale threshold filtering should provide a separation between the overlapped and nonoverlapped sections. In many cases, this operation provided a separation between the branches (Fig. 11). However, in some cases threshold filtering did not yield the desired separation, because of local flow conditions, location of the catheter tip during injection, type of contrast used, and image enhancement parameters when
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Fig. 10. Identification of the bifurcation point and the apex point in the AP projection: (A) AP projection angiogram; (B) LAT projection angiogram; and (C) Binary image of the LAT projection. D1: distance between the facial artery and bifurcation point; D2: distance between the lingual artery and the bifurcation; D3: distance between apex and the bifurcation point.
Fig. 11. Separation of internal and external carotid arteries in the AP projection: (A) angiogram of the AP projection; (B) binary image of the ECA in the AP projection; and (C) Binary image of the ICA in the AP projection.
printing to film. Images that did not yield daughter branch separation were excluded from the analysis. The procedure for constructing the phase-shifted ensemble average morphology in the AP projection was the same as that described for the LAT projection. The morphological ensemble average was obtained (Fig. 12). Panel (A) shows the CCA leading into the ICA, panel (B) shows the CCA leading into the ECA, and a composite image of the previous two branches is shown in panel (C), where different grayscale values were used on the non-overlapping parts.
The diameters of the carotid branches and the bifurcation angles were obtained for each image in each group, and average values were determined for each group. These values are compared with values obtained directly from the average morphology image. After calibrating and phase shifting each image, a polynomial was fit to the centerline and the outline of each bifurcation using the bifurcation point as the origin of the coordinate system. From the bifurcation point, vertical intervals of 20 pixels (3 mm) apart were noted on the centerline of each projection. Lines perpendicular to
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Fig. 12. Morphological average image of the bifurcation of Group III in the AP projection: (A) average image of the ICA; (B) average image of the ECA; and (C) combined image of the ICA and ECA.
the local derivative of the polynomial fit at the selected points were constructed; their intersection points with the outlines of the branch determined the branch local diameter. Exceptions to the 20-pixel rule were the points that intersected the root of both the ICA and ECA. For these locations, the measurements on the centerline between the bifurcation origin and the lines determining the roots of the branches were evaluated instead (DI and DE ) (Fig. 2). The bifurcation angle was determined for each image using the polynomial fit as a guide. The line tangent to the terminus of the CCA centerline at the bifurcation point and the tangents to the daughter branches at their origins determined the angles of the branches as yE and yI : The summation of the two angles was considered the bifurcation angle, y (Fig. 2). To minimize the
Fig. 13. Mean and standard error of deviation of the carotid branches from individual images (lateral projection): top, ICA; middle, ECA; and bottom, CCA.
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inaccuracies of the tangents at the edge of the polynomial fits, the finite tangent was determined using a 10-pixel segment of the centerlines in the vicinity of the origin. All the obtained numerical values were averaged with others in the same projection and group, and the results are summarized in the tables presented subsequently.
3. Results The results for the average LAT and AP projection images are shown in Fig. 15. It is evident from the figures that during the developmental stages the overall dimension of the carotid bifurcation increases, but the ICA increases more than the ECA. Also, the geometry of the bifurcation changes considerably. At the begin-
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ning, the ICA appears to emanate as a side branch, while the ECA appears to be a continuation of the CCA. Later in life the junction undergoes a modification that leads to a construction in which both daughter vessels are a skewed continuation of the parent artery. In the AP projection the daughter branches, while initially in line with the parent vessel, change their orientations and appear to follow an out of plane path. While not reflected in the averaged data, there are individuals in Group I for which the origin of the ICA is narrower than its distal dimension, but with time this trend is reversed. An additional comparison is afforded by measuring the values of the predetermined landmarks as before, but now for the average images. Results for the four age groups are summarized in graphs and a table (Figs. 13 and 14 and Table 3). As can be expected, the values
Fig. 14. Mean and standard error of deviation of the carotid branches from individual images (AP projection): top, ICA; middle, ECA; and bottom, CCA.
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Table 3 Diameters of the human carotid arteries calculated from the morphological average images (all measurements are in unit of (mm)) CCA LAT
ICA
ECA
AP
LAT
AP
LAT
AP
Group I A 3.7 B 3.6
3.8 3.7
3.4 3.2
3.6 3.6
2.8 2.4
3.6 3.4
Group II A 5.2 B 5.0 C 5.2
5.4 5.2 5.1
4.2 3.8 3.5
5.5 5.2 4.6
3.5 3.0 3.2
5.0 4.5 4.3
Group III A 7.7 B 6.9 C 6.4 D 6.2
6.3 6.1 6.4 6.5
6.2 5.1 4.9 4.9
6.8 6.4 5.6 5.1
3.9 3.5 3.6 3.3
6.0 5.0 4.3 4.0
Group IV A 8.6 B 7.3 C 6.9 D 7.1
7.0 6.8 7.0 7.0
7.1 6.5 6.2 5.8
8.1 8.3 8.0 7.7
5.2 4.7 4.8 4.5
7.3 6.5 5.7 5.6
obtained by the two separate analysis methods are not exactly the same. However, differences do not exceed half a standard deviation between the two methods of calculation. The results show a significant growth in the diameter of the root of the ICA between Groups II and III at stations A and B (Po0.001) in both the LAT and AP projections (Figs. 13–15). In contrast, there are no statistically significant differences in the diameter of the ICA between Groups I and II in both projections (P>0.05). In addition, changes in the diameter of the ECA between Groups II and III, stations A and B, are statistically insignificant except for the root of the ECA in the AP projection (Po0.05). As the carotid bifurcation matures, the angle between the daughter branches remains largely unchanged at about 77 . However, the angle between each branch and the terminus of the CCA undergoes marked changes (Table 4). The angle between the ICA and the CCA increases during maturation and doubles itself between Groups I and IV. The angle between the ECA and the CCA is undergoing a decrease such that the summation of the two angles remains unchanged. In contradistinction to calculation of diameters, the angles of the bifurcations show a larger departure from the values computed based on individual images. The reason for the larger variability in the calculated angle may be due to the method of angle estimation that relies on derivatives of a polynomial fit to the obtained centerline. Information on the dimensions of the transition zone between the CCA and its daughter branches is provided
Fig. 15. Evolvement of the human carotid bifurcation in AP and LAT projections. For the AP projection, the dark gray area is part of the ICA that does not overlap with the ICA. The black area interposed between the two shades of gray belongs to both the ICA and the ECA.
Table 4 Average angle of the human carotid bifurcation Bifurcation angle (y) (deg)
ICA angle (yI) (deg)
ECA angle (yE) (deg)
Calculated from individual images Group I 73.675.2 Group II 78.175.5 Group III 76.973.3 Group IV 76.779.6
16.179.6 20.3712.9 28.7714.2 34.3718.2
57.6711.4 57.8712.5 48.3715.0 42.4714.6
Calculated from the average image Group I 65.9 Group II 68.6 Group III 72.2 Group IV 68.6
17.1 19.5 26.1 26.5
48.8 49.1 46.1 42.1
(Table 5). A doubling in size of the transition zone corresponds to the overall enlargement of the vessels composing the bifurcation.
ARTICLE IN PRESS J. Seong et al. / Journal of Biomechanics 38 (2005) 453–465 Table 5 Distances between the bifurcation point and the root of the ICA and the ECA (units (mm))
Group Group Group Group
I II III IV
DI
DE
dI
dE
2.670.5 3.070.4 4.070.4 4.771.0
2.670.4 3.270.4 4.270.6 5.071.0
1.770.5 2.170.4 3.170.5 3.770.9
2.270.4 2.8770.4 3.770.6 4.071.0
dI and dE are the distances from the bifurcation point to the root of the CCA branches measured from the AP projection.
4. Discussion Only a few investigators have studied the morphology of the carotid bifurcation (Affeld et al., 1998; Bharadvaj et al., 1982a; Rindt et al., 1987; Salzar et al., 1995). Bharadvaj and colleagues studied 57 angiograms of 22 adults between 34 and 77 years of age and 67 angiograms of 50 children below the age of 18. All lengths measured from each bifurcation were rendered dimensionless with respect to the diameter of the CCA measured from the same angiogram because there was no absolute length scale available in the angiograms. To render the normalized values physiological, the representative internal diameter of the CCA in adults was determined to be a value of 8 mm, as suggested by Arndt et al. (1968) and Olson (1974). Based on a representative value of 8 mm of the CCA, Bharadvaj et al. (1982a) determined the other dimensions of their model. The mean value of the carotid sinus was 8.9 mm, the mean value of the ICA was 5.6 mm, and the mean value of the ECA was 4.6 mm. The average bifurcation angle was determined to be 50.5 . Salzar et al. (1995) measured the carotid geometry using six in vitro specimens, MRI slides, and 76 angiograms. The 76 angiograms were adapted from Bharadvaj et al. (1982a). More recently, Affeld et al. (1998) investigated the geometry of the carotid artery using vessel casts of 31 specimens. Cadavers of individuals between 22 and 91 years of age, with a mean age of 67, were used to make the vessel casts. The diameters of carotid arteries were measured manually using a digital caliper (0.05 mm error). The minimum and maximum of each diameter were measured, as the carotid branches at the bifurcation are not round but rather elliptical. Compared with previous studies, the measure of the CCA for adults in our study is comparable to those of Bharadvaj et al. (1982a). However, we did not observe a sinus diameter that is larger than the caliber of the CCA. The sinus dimension in our adult cases is slightly smaller than the dimension of the CCA, as in the study by Salzar et al. The average adult human bifurcation angle that was reported to be in the range of 50–60
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(Bharadvaj et al., 1982a; Affeld et al., 1998) is smaller than the average angle we obtained in our study. We measured the angle always at a predetermined bifurcation point that was a result of image processing and mathematical tools. If one deviates from this point and moves even slightly further into the daughter branches the measured angle will be smaller. Inaccuracies resulting from imprecise determination of the bifurcation point may have contributed to angle values that are lower than those we have obtained. The most significant findings when comparing morphological images of the carotid bifurcation of different age groups are the substantial growth of the ICA with age and the development of a carotid sinus at the root of the ICA. During maturation, the ICA, initially similar in size to the ECA until about 9 years after birth (Groups I and II), experiences a significant growth at its root during adolescence (Group III). The carotid sinus that is common at adulthood can be found in both projections of Group IV (20–36 years). Statistical analysis of the measured diameters in both the LAT and AP projections shows significant growth in the root of the ICA between Groups II and III in both projections (Po0.001). However, no corresponding growth in the root of the ECA was observed for the same age groups. These results suggest that the remodeling of the root of the ICA and the development of the carotid sinus occurs mostly during adolescence. It appears that the carotid bulb in humans is a result of arterial remodeling that coincides with maturation and growth of the brain, and it occurs at about the same time hormonal changes take place during puberty. One hypothesis suggests that the dilation serves to support pressure sensing (Arndt et al., 1968), another presumes that the sinus slows blood flow and reduces the pulsatility to protect the brain (Cavazzani, 1905). While the reasons for its appearance are unknown, it is interesting to speculate why this unique bifurcation develops in this way. To accommodate increasing flow demand by the maturing brain, the natural tendency is to reduce hydraulic resistance by increasing tube caliber. But the exit angle of the carotid branches cannot be changed markedly, because space is limited. And remodeling is confined to the ICA root. The enlarged conduit exposes blood flow to unfavorable complex patterns caused by flow separating from the walls (Bharadvaj et al., 1982b, Part II). Over a long period of time these complex patterns may be responsible for endothelial dysfunction and carotid bulb wall heterogeneity and subsequent development of atherosclerosis. Hemodynamic and hydraulic resistance studies on the evolving geometry of the carotid bifurcation may help to shed light on this question. Understanding the development of the carotid bifurcation can potentially impact how we address the degeneration of the bulb, i.e., atherosclerotic development in adulthood, which
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ultimately increases the risk of thromboembolic ischemic stroke. Stratification of flow within the carotid bulb with a stent-like device could potentially reduce the risk of atherosclerotic degeneration. It is well accepted in the medical literature that the carotid bulb is the ‘‘communicating station’’ between the heart and the cerebrovasculature for blood pressure autoregulation (baroreceptor function) or for conduction of oxygen and CO2 tension. Therefore, it would be of interest to elucidate what impact changes in bulb configuration during development and later on during atherosclerotic degeneration may have on autoregulation. For example, it could be speculated that damage to the otherwise normal bulb configuration and sclerosis/calcification may be two of the reasons for hypertensive brain hemorrhage resulting in inappropriate autoregulation, as is observed infrequently in elderly patients. Furthermore, if a relationship between the morphology of the carotid bulb and the physiology of the cerebrovascular system during brain maturation and development can be demonstrated, the function of the carotid bulb could technically be simulated. This could help to develop sensors and devices to prevent potential carotid bulb related pathology. One of the interesting results of this study is that the bifurcation angle (y) remains virtually unchanged during the growth period and maintains a value of 73.6–78.1 . However, the angle split between the ICA and ECA relative to the CCA does change. The ICA angle (yI ) increases continuously with age, with a corresponding decrease in the angle of the ECA. One of the reasons that the angle of the ICA (yI ) increases is the progressive increase in the diameter of the ICA and the remodeling of the CCA terminus to accommodate a smooth hydraulic transition into a growing ICA, with a higher perfusion demand. One limitation of the current study is the small database. For a more extensive analysis, a larger database is required. The average ICA/ECA angles that were obtained in this study contain standard deviation values that exceed 10 . These large errors preclude the confirmation of the average angle values. Although it is evident that the ICA angle (yI ) increases with age, the number of data points should be larger to determine more accurate average values. Another limitation of this study, again due to a sparse database, is that gender differences in the development of the carotid bifurcation were not evaluated. Since we observed that the major changes occur during puberty, it would be interesting to study if hormonal changes during that period have a differential effect on the development of the carotid arterial bifurcation in men and women. Additionally, no distinction between a left and a right carotid bifurcation was observed. Differences between the two carotids do exist, as pointed out in a study by Peterson et al. (1960). The left carotid
artery is closer to the heart and arises directly from the aorta, while the right carotid arises from the brachiocephalic trunk. However, whether these distinctions induce morphological differences that are either random or systematic will need to be evaluated with a much larger database than that available for this study.
References Adam, W.E., 1958. The Comparative Morphology of the Carotid Body and Carotid Sinus. Thomas, Springfield, IL, pp. 46–64. Affeld, K., Goubergrits, L., Fernandez-Britto, J., Falcon, L., 1998. Variability of the geometry of the human common carotid artery. A vessel cast study of 31 specimens. Pathology Research and Practice 194, 597–602. Arndt, J., Klauske, J., Mersch, F., 1968. The diameter of the intact carotid artery in man and its change with pulse pressure. Pflugers . Archiv-European Journal of Physiology 301, 230–240. Baaijens, J.P.W., van Steenhoven, A.A., Janssen, J.D., 1993. Numerical analysis of steady generalized Newtonian blood flow in a 2D model of the carotid artery bifurcation. Biorheology 30, 63–74. Bendat, J.S., Piersol, A.G., 1986. Random Data: Analysis and Measurement Procedure. Wiley-Interscience, New York, NY, pp. 28–31. Bharadvaj, R.F., Mabon, R.F., Giddens, D.P., 1982a. Steady flow in a model of the human carotid bifurcation. Part I—flow visualization. Journal of Biomechanics 15, 349–362. Bharadvaj, R.F., Mabon, R.F., Giddens, D.P., 1982b. Steady flow in a model of the human carotid bifurcation. Part II—laser-Doppler anemometer measurements. Journal of Biomechanics 15, 363–378. Bourbakis, N., Steffensen, N., Saha, B., 1997. Design of an array processor for parallel skeletonization of images. IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 44 (4), 284–298. Cavazzani, E., 1905. Bulbo carotico. Atti della Accademia delle Scienze Mediche e naturali in Ferrara 79, 23–27. Chuang, S., 1989. Vascular diseases of the brain in children. In: Edward, M.S.B., Harold, J.H. (Eds.), Cerebral Vascular Disease in Children and Adolescents. Williams & Wilkins, Baltimore, MD, pp. 69–94. Gonzalez, R.C., Woods, R.E., 1992. Digital Image Processing. Addison-Wesley, Reading, MA, pp. 518–560. Gijsen, F.J.H., van de Vosse, F.N., Janssen, J.D., 1999. The influence of the non-Newtonian properties of blood on the flow in large arteries: steady flow in a carotid bifurcation model. Journal of Biomechanics 32, 601–608. Harrison, M.J.G., Marshall, J., 1983. Does the geometry of the carotid bifurcation affect its predisposition to atheroma?: letter to the editor. Stroke 14, 117. Kitney, R.I., Giddens, D.P., 1983. Analysis of blood velocity waveforms by phase-shift averaging and autoregressive spectral estimation. Journal of Biomechanical Engineering 105, 398–401. Ku, D.N., Giddens, D.P., 1983. Pulsatile flow in a model carotid bifurcation. Arteriosclerosis 3, 31–39. Lam, L., Lee, S.-W., Suen, C.Y., 1992. Thinning methodologies—a comprehensive survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 14 (9), 869–885. McGill Jr., H.C., 1968. Introduction to the geographic pathology of atherosclerosis. Laboratory Investigation 18 (5), 465–467. Olson, R.M., 1974. Human carotid artery wall thickness, diameter and blood flow by a non-invasive technique. Journal of Applied Physiology 37 (6), 955–960.
ARTICLE IN PRESS J. Seong et al. / Journal of Biomechanics 38 (2005) 453–465 Peterson, R.E., Livingston, K.E., Escober, A., 1960. Development and distribution of gross atherosclerotic lesions at cervical carotid bifurcation. Neurology 10, 955–959. Rindt, C.C.M., van de Vosse, F.N., van Steenhoven, A.A., Janssen, J.D., 1987. A numerical and experimental analysis of the flow field in a two-dimensional model of the human carotid artery bifurcation. Journal of Biomechanics 20, 499–509.
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Salzar, R.S., Thubrikar, M.J., Eppink, R.T., 1995. Pressure-induced mechanical stress in the carotid artery bifurcation: a possible correlation to atherosclerosis. Journal of Biomechanics 28, 1333–1340. Schulz, U.G.R., Rothwell, P.M., 2001. Major variation in carotid bifurcation anatomy—a possible risk factor for plaque development? Stroke 32, 2522–2529.
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Morphological age-dependent development of the human carotid bifurcation Jaehoon Seonga, Baruch B. Liebera,b,*, Ajay K. Wakhloob,c a
Department of Biomedical Engineering, University of Miami, College of Engineering, Coral Gables, FL, USA b Department of Radiology, University of Miami, School of Medicine, Miami, FL, USA c Department of Neurosurgery, University of Miami, School of Medicine, Miami, FL, USA Accepted 26 April 2004
Abstract The unique morphology of the adult human carotid bifurcation and its sinus has been investigated extensively, but its long-term, age-dependent development has not. It is important fundamentally and clinically to understand the hemodynamics and developmental forces that play a role in remodeling of the carotid bifurcation and maturation of the sinus in association with brain maturation. This understanding can lead to better prognostication and therapy of carotid disease. We analyzed the change of sinus morphology and the angle of the carotid bifurcation in four postnatal developmental stages (Group I: 0–2 years, Group II: 3–9 years, Group III: 10–19 years, and Group IV: 20–36 years, respectively) using multiprojection digital subtraction angiograms and image post-processing techniques. The most significant findings are the substantial growth of the internal carotid artery (ICA) with age and the development of a carotid sinus at the root of the ICA during late adolescence. The bifurcation angle remains virtually unchanged from infancy to adulthood. However, the angle split between the ICA and external carotid artery (ECA) relative to the common carotid artery (CCA) undergoes significant changes. Initially, the ICA appears to emanate as a side branch. Later in life, to reduce hydraulic resistance in response to increased flow demand by the brain, the bifurcation is remodeled to a construct in which both daughter vessels are a skewed continuation of the parent artery. This study provides a new analysis method to examine the development of the human carotid bifurcation over the developmental years, despite the small and sparse database. A larger database will enable in the future a more extensive analysis such as gender or racial differences. r 2004 Elsevier Ltd. All rights reserved. Keywords: Carotid bifurcation; Carotid morphology; Carotid sinus; Vascular remodeling
1. Introduction The structure of the carotid bifurcation is unique in that the root of the internal carotid artery (ICA), which supplies blood to the brain, is usually enlarged. This region is referred to as the carotid sinus. The ICA does not harbor any branches until just before the circle of Willis, where it branches into the ophthalmic artery. Therefore, the root of the ICA can be considered as the origin of the cerebral circulation. *Corresponding author. Department of Biomedical Engineering, University of Miami, 1251 Memorial Drive, Coral Gables, FL 33146, USA. Tel.: +1-305-284-2330; fax: +1-305-284-6494. E-mail address: [email protected] (B.B. Lieber). 0021-9290/$ - see front matter r 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.jbiomech.2004.04.022
The development and the function of the human carotid sinus are not clearly understood yet. The arterial wall of the carotid sinus is densely enervated and contains baroreceptive neural terminals. It has been hypothesized that the dilation serves to support pressure sensing (Arndt et al., 1968). Another hypothesis based on phenomenological observations presumes that the function of the sinus is to slow the blood flow and reduce the pulsatility in order to protect the brain (Cavazzani, 1905). More recently, in vitro and computational models have been used to investigate carotid hemodynamics (Baaijens et al., 1993; Gijsen et al., 1999; Kitney and Giddens, 1983; Ku and Giddens, 1983). Complex flow patterns have been found in the carotid sinus (Bharadvaj et al., 1982a). These patterns have been
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implicated in carotid bulb wall heterogeneity and subsequent development of atherosclerosis at this site. As the atherosclerotic plaque develops, the elicited biological response is an attempt to cover the plaque with a fibrous cap. Unfortunately, over time the fibrous cap may rupture, releasing the underlying debris, i.e., emboli, into the circulation. The circulation carries this debris into the brain, producing a number of different symptoms. The worst complication is blockage of a major cerebral blood vessel, producing an ischemic stroke (Chuang, 1989; Harrison and Marshall, 1983). Studies by McGill (1968) have shown that atherosclerosis of the carotid sinus begins in mid-adolescence. Peterson et al. (1960) found that gross atherosclerotic lesions progress with age and concluded that the common carotid artery (CCA) proximal to the bifurcation and the ICA distal to the bifurcation show a marked increase in size with advancing age. Previous investigations on the geometry of the carotid bifurcation provided important insight into its structure in adults, although each study yielded different morphological information (Adam, 1958; Affeld et al., 1998; Bharadvaj et al., 1982a; Salzar et al., 1995). Specifically, the diameters of the CCA and the sinus in the various investigations vary significantly (Table 1). In a recent study that reviewed 5395 angiograms from 3007 patients (Schulz and Rothwell, 2001), a large variation in carotid bifurcation anatomy was considered as a risk factor for atheroma. However, individuals selected for the study were patients with recent ocular or carotid territory cerebral ischemia; therefore, the study was limited to mature individuals, and the early developmental years were not considered. The long-term remodeling of the carotid bifurcation and its sinus during human developmental stages and its unique structure at maturity has not been investigated. The carotid sinus experiences a remarkable increase in
size from birth to adulthood. Furthermore, the parent and daughter vessels do not lie in the same plane at the bifurcation, as suggested previously by simplified models. Therefore, we investigated the age-dependent morphological changes of the carotid bifurcation during four human developmental stages.
2. Materials and methods 2.1. Patient population Digital subtraction angiograms (DSAs) of carotid bifurcations from various human developmental stages were evaluated. Patients underwent angiographies of their cerebrovascular system for other causes. Informed consent was obtained from the patients or their surrogates for additional imaging of the carotid bulb. No patients presenting with arteriovenous malformations or other vascular disease, which would have potentially altered the carotid bulb morphology, were enrolled. Although DSA procedures are expensive and carry minimal risk of causing a stroke, angiographic spatial resolution is unmatched by other imaging modalities (Schulz and Rothwell, 2001). Biplane DSA was used to obtain the most accurate morphological carotid bifurcation images for analysis. Ninety-five angiograms were obtained from 36 patients ranging in age from newborn infants to 36year-old adults. Fifty-eight lateral (LAT) projections and 37 anterior–posterior (AP) angiographic projections were used in the analysis. To investigate age-dependent changes in morphology, the angiograms were divided into four groups representing various human developmental stages: newborn (Group I: 0–2 years), pediatric (Group II: 3–9 years), adolescent (Group III: 10–19 years), and adult (Group IV: 20–36 years). Additional
Table 1 Diameters and bifurcation angles of human carotid arteries in three often cited studies
Bharadvaj et al. (1982a, b) Salzar et al. (1995) Affeld et al. (1998)
CCA (mm)
ICA sinus (mm)
ICA (mm)
ECA (mm)
Bifurcation angle
8.0 6.4 5.7–5.9
8.9 6.0 6.2–6.9
5.6 4.9 4.7–5.1
4.6 4.5 4.1–4.7
50.5 N/A 56.9 715.2
Table 2 Patient database
Age (years) Average age Number of patients Number of cases (lateral projection) Number of cases (anterior–posterior projection)
Group I
Group II
Group III
Group IV
Total
0–2 0.870.5 9 15 7
3–9 4.071.7 6 10 7
10–19 13.972.3 7 13 10
20–36 26.374.8 14 20 13
36 58 37
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information on the patient population is provided (Table 2). 2.2. Image preparation and calibration Biplane DSAs of the carotid bifurcation were obtained during angiographic procedures for indications of cerebrovascular pathologies other than carotid disease. Angiograms of the left and right carotid bifurcation were acquired in AP and LAT projections using a biplane angiography unit (Toshiba Super Angiorex model G, Toshiba, Tokyo, Japan). After careful review of each angiogram, all cases involving pathology of the carotid arteries were excluded. Cases free of carotid disease were selected for further analysis, and the angiographic images were printed on X-ray film. Using a high-resolution scanner (UMAX Astra 2400S–UMAX Technologies, Inc., Fremont, CA), the films were scanned into a personal computer (Fig. 1A). Binary images (Fig. 1B) of the carotid arteries were constructed from the grayscale images. A threshold operation was used to differentiate between the carotid arteries and the background using Adobe Photoshop 5.0 (Adobe Systems, Inc., San Jose, CA) and Scion Image (shareware NIH image processing program—http:// www.scioncorp.com). Values above the threshold were considered noise and set to white, while values below the threshold were set to black. The calibration of images was performed using either the calibration feature of the angiography unit or a feature of known physical dimensions in the image (such as a metal washer), the mm/pixel ratio of the image was
Fig. 1. (A) Scanned angiographic image and (B) binary image.
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determined and magnified (or reduced) as necessary to a ratio of 0.15 mm/pixel to enable the averaging of different images. The centerline of the binary images was obtained by the application of a parallel symmetric thinning operation (Bourbakis et al., 1997; Lam et al., 1992), and the outline of the bifurcation was found by an edge-detection operation in MATLAB (MathWorks, Natick, MA) (Gonzalez and Woods, 1992). This high performance thinning algorithm executes fully symmetric erosion to obtain the centerline (Fig. 2A). It is not sensitive to minor variations of the edge configuration because it increases the size of the operator support for solving a connectivity problem in the thinned objects (Bourbakis et al., 1997). Therefore, the uncertainty in the location of the skeletonized object is about 7half a pixel, translated to physical dimensions it is about70.07 mm. As can be seen in Fig. 2A, the centerline generated using the above algorithm has spots thicker than one pixel manifesting the uncertainty of the algorithm in determining the exact center at these locations. However, this compensatory mechanism is used to guarantee a continuous line. To eliminate these minor distortions, a polynomial was fit to the centerline (Fig. 2B) and the branch diameters as well as bifurcating angles of the carotid arteries were then calculated from the newly obtained centerline/outline images at 20 pixel intervals (3 mm) along the centerline (Fig. 2C). 2.3. Simultaneous rotation of the projection The three branches at the carotid bifurcation generally do not lie in a flat plane. Furthermore, images were always acquired in the AP/LAT projections of the patients, but these are not necessarily the optimal planes of the bifurcation. An angiogram of a 3-year-old male in which the daughter branches of the CCA are not superposed in either projection is shown in Fig. 3. Cases like the one presented (Fig. 3) required a rotational transformation to obtain a reasonably planar view of the bifurcation in a projection that is orthogonal to the bifurcation plane. Rotation of the views to the bifurcation plane and its orthogonal counterpart affords comparison of the bifurcations of different individuals. To minimize the angle between the daughter branches in one projection, the skeletons of the original projections were rotated simultaneously to overlay the centerline of the two daughter branches in one projection or minimize the angle between them. After the angle of the rotational transformation was determined, the new orthogonal projections were constructed. The projection in which the angle between the daughter branches was minimized was considered the frontal (or AP) projection, and the other was considered the LAT projection. The skeletonized images of the bifurcation requiring rotation provide essentially two orthogonal projections
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40 100
ICA
ECA
80 60 40
D
D
C
C B
A
0
I
0 DI
A -20
B C
CCA
-40 -20 0
(A)
DE
A
-20
-60
E
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20
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20
(B)
20 40
-40
(C)
-20
0
20
Fig. 2. (A) Centerline and outline of the carotid bifurcation image. (B) Location along the centerline where the diameters of the branches were calculated, and (C) how the angle of bifurcation was calculated.
After the skeletonized image of the bifurcation was rotated into the desired position, the body of the bifurcation was rebuilt around the centerline using a thickening operation until the rebuilt bifurcation reached the transformed outlines (Fig. 6). 2.4. Phase shift ensemble averaging of the images
Fig. 3. (A) AP and (B) LAT projection angiograms. The daughter branches are not superposed in either projection.
of the three-dimensional (3-D) centerline. The intersection point of the centerline of the CCA and the centerlines of the two daughter branches was selected as the origin of the coordinate system for the transformation. The 3-D coordinates of the centerline were then calculated from the projections, and rotated by the determined angle (Fig. 4). The new orthogonal AP and LAT projections of the centerline are shown with the non-rotated projection shown on the same plot for comparison (Fig. 5). One can clearly see the different appearance of the geometry before and after rotation.
Once the LAT and the AP projections of the bifurcations were judged to be optimal, they were subjected to further analysis to obtain the average morphology of the carotid bifurcation in both projections. The following describes the analysis steps required to obtain the average morphology within each age group. Each image may contain an arbitrary angular shift around an axis through the bifurcation point perpendicular to either projection. Therefore, a constructed ensemble average may not be optimal, but it can be refined in an iterative process using a phase shift averaging technique (Bendat and Piersol, 1986; Kitney and Giddens, 1983). The principle of phase shift averaging is first to construct the ensemble average and then determine the cross correlation function between each individual element in the ensemble and the ensemble average. If the cross correlation function maximum value does not occur at a zero shift, the element in the ensemble is shifted by that amount. The process is repeated for all elements, and a new ensemble average is constructed from the shifted elements. The process continues until the shift between each element and refined ensemble average meets an arbitrary convergence criterion. To obtain the optimal angular shift for each image in the ensemble, all images were first transformed into polar coordinates with an angular resolution of 1 (Fig. 7). This transformation was required because the maximum value of the cross correlation function of the
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80
80
60
60
40
40
20
20
0
0
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-20
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-60
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-80
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20
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0 -20
-40
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-20
0
20 AP
40
40 20
LAT (B)
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Fig. 4. (A) Skeletonized image of the 3-D bifurcation shown in Fig. 3. (B) The skeleton image after it was rotated to minimize the angle between two daughter branches in the AP projection.
80
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Fig. 5. Comparison between the skeletons of the bifurcation before (dashed line) and after (solid line) rotation in the AP (A) and LAT projection (B). Fig. 7. Transformation of an image from rectangular to polar coordinates.
Fig. 6. Binary images of the bifurcation in the LAT plane before (A) and after (B) rotation.
rectangular images yields only information about the translational shift between the images in the X 2Y direction and not the rotation. By transforming the images into polar coordinates the information obtained from the cross correlation function pertains to translations in R and F; and changes in F are the desired rotational shifts. The origin of a right hand coordinate system was placed at the bifurcation point, and the polar coordinates were defined in the usual manner (Fig. 7). When attempting to obtain the cross correlation between the individual image and the constructed
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assemble average in the polar coordinates, it became apparent that the CCA is the dominant feature at the expense of the daughter branches. To reduce the influence of the CCA, only the daughter branches were transformed into polar coordinates to determine the best angular shift for each image through the iterative process as described before. The construct of the ensemble average prior to shifting of the images is shown in Fig. 8. The convergence criteria for termination of the iterative procedure were selected as follows. First, no individual image was allowed to deviate more than 1 from the final constructed average. Second, the sum of all images that deviated from the constructed ensemble average was not allowed to exceed 50% of the number of images in the ensemble. Because the individual images in the ensemble were binary (0 or 1), the ensemble average divided by the total number of images yielded a range of values between 0 and 1. The ensemble-averaged body of the branches was determined as the locus of all points with a pixel intensity value larger than 0.5, while lower values were set to background (a zero pixel value). For presentation purposes, the foreground value was set to 0.7 rather than 1.0 (Fig. 8). After the convergence criteria were satisfied, each of the rectangular coordinate images was rotated at the calculated angle. In a manner similar to the averaging processing in the polar coordinate, the morphological average images were obtained by summation of all the individually rotated images in rectangular coordinates and dividing these image by the total number of images in the ensemble. Finally, the morphological average bifurcation was determined by setting values above 0.5 to foreground and values below 0.5 to background (Fig. 9). 2.5. Additional consideration for the anterior–posterior projection In the LAT projection, the bifurcation point was readily obtained simply by a thinning operation; however, identifying the bifurcation point in the AP projection is more difficult because ICA and external
Fig. 8. Ensemble-averaged image in polar coordinates before phase shift refinement.
Fig. 9. (A) Grayscale overlay of all images in the ensemble and (B) morphological average image after intensity thresholding and binarization.
carotid artery (ECA) overlap. Therefore, the bifurcation point in the AP projection could not be found by a thinning operation as used in the LAT projection. To locate the bifurcation point in the AP projection, three images from both projections were used: the scanned LAT projection angiogram, the binary image of the LAT projection, and the scanned AP projection angiogram. Before analyzing the AP images, they were calibrated to a ratio of 0.15 mm/pixel in the same way the LAT projection images were calibrated. After image calibration, the length of the segment between the bifurcation point and the bifurcation apex in the LAT projection was calculated. This measurement should be the same for both projections. Nonetheless, both points cannot be directly located on the AP image due to overlap. Therefore, branches of the ECA were used as anatomical landmarks to locate the bifurcation point in the AP projection. The lingual artery and facial artery were selected as identifiable landmarks in both projections, and their separation distances from the bifurcation and apex points in the LAT projection were assigned to the AP projection (Fig. 10). When two arteries of dissimilar diameters are superposed during angiography, the overlapped parts should, in principle, appear darker than the non-overlapped sections. Therefore, grayscale threshold filtering should provide a separation between the overlapped and nonoverlapped sections. In many cases, this operation provided a separation between the branches (Fig. 11). However, in some cases threshold filtering did not yield the desired separation, because of local flow conditions, location of the catheter tip during injection, type of contrast used, and image enhancement parameters when
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Fig. 10. Identification of the bifurcation point and the apex point in the AP projection: (A) AP projection angiogram; (B) LAT projection angiogram; and (C) Binary image of the LAT projection. D1: distance between the facial artery and bifurcation point; D2: distance between the lingual artery and the bifurcation; D3: distance between apex and the bifurcation point.
Fig. 11. Separation of internal and external carotid arteries in the AP projection: (A) angiogram of the AP projection; (B) binary image of the ECA in the AP projection; and (C) Binary image of the ICA in the AP projection.
printing to film. Images that did not yield daughter branch separation were excluded from the analysis. The procedure for constructing the phase-shifted ensemble average morphology in the AP projection was the same as that described for the LAT projection. The morphological ensemble average was obtained (Fig. 12). Panel (A) shows the CCA leading into the ICA, panel (B) shows the CCA leading into the ECA, and a composite image of the previous two branches is shown in panel (C), where different grayscale values were used on the non-overlapping parts.
The diameters of the carotid branches and the bifurcation angles were obtained for each image in each group, and average values were determined for each group. These values are compared with values obtained directly from the average morphology image. After calibrating and phase shifting each image, a polynomial was fit to the centerline and the outline of each bifurcation using the bifurcation point as the origin of the coordinate system. From the bifurcation point, vertical intervals of 20 pixels (3 mm) apart were noted on the centerline of each projection. Lines perpendicular to
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Fig. 12. Morphological average image of the bifurcation of Group III in the AP projection: (A) average image of the ICA; (B) average image of the ECA; and (C) combined image of the ICA and ECA.
the local derivative of the polynomial fit at the selected points were constructed; their intersection points with the outlines of the branch determined the branch local diameter. Exceptions to the 20-pixel rule were the points that intersected the root of both the ICA and ECA. For these locations, the measurements on the centerline between the bifurcation origin and the lines determining the roots of the branches were evaluated instead (DI and DE ) (Fig. 2). The bifurcation angle was determined for each image using the polynomial fit as a guide. The line tangent to the terminus of the CCA centerline at the bifurcation point and the tangents to the daughter branches at their origins determined the angles of the branches as yE and yI : The summation of the two angles was considered the bifurcation angle, y (Fig. 2). To minimize the
Fig. 13. Mean and standard error of deviation of the carotid branches from individual images (lateral projection): top, ICA; middle, ECA; and bottom, CCA.
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inaccuracies of the tangents at the edge of the polynomial fits, the finite tangent was determined using a 10-pixel segment of the centerlines in the vicinity of the origin. All the obtained numerical values were averaged with others in the same projection and group, and the results are summarized in the tables presented subsequently.
3. Results The results for the average LAT and AP projection images are shown in Fig. 15. It is evident from the figures that during the developmental stages the overall dimension of the carotid bifurcation increases, but the ICA increases more than the ECA. Also, the geometry of the bifurcation changes considerably. At the begin-
461
ning, the ICA appears to emanate as a side branch, while the ECA appears to be a continuation of the CCA. Later in life the junction undergoes a modification that leads to a construction in which both daughter vessels are a skewed continuation of the parent artery. In the AP projection the daughter branches, while initially in line with the parent vessel, change their orientations and appear to follow an out of plane path. While not reflected in the averaged data, there are individuals in Group I for which the origin of the ICA is narrower than its distal dimension, but with time this trend is reversed. An additional comparison is afforded by measuring the values of the predetermined landmarks as before, but now for the average images. Results for the four age groups are summarized in graphs and a table (Figs. 13 and 14 and Table 3). As can be expected, the values
Fig. 14. Mean and standard error of deviation of the carotid branches from individual images (AP projection): top, ICA; middle, ECA; and bottom, CCA.
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Table 3 Diameters of the human carotid arteries calculated from the morphological average images (all measurements are in unit of (mm)) CCA LAT
ICA
ECA
AP
LAT
AP
LAT
AP
Group I A 3.7 B 3.6
3.8 3.7
3.4 3.2
3.6 3.6
2.8 2.4
3.6 3.4
Group II A 5.2 B 5.0 C 5.2
5.4 5.2 5.1
4.2 3.8 3.5
5.5 5.2 4.6
3.5 3.0 3.2
5.0 4.5 4.3
Group III A 7.7 B 6.9 C 6.4 D 6.2
6.3 6.1 6.4 6.5
6.2 5.1 4.9 4.9
6.8 6.4 5.6 5.1
3.9 3.5 3.6 3.3
6.0 5.0 4.3 4.0
Group IV A 8.6 B 7.3 C 6.9 D 7.1
7.0 6.8 7.0 7.0
7.1 6.5 6.2 5.8
8.1 8.3 8.0 7.7
5.2 4.7 4.8 4.5
7.3 6.5 5.7 5.6
obtained by the two separate analysis methods are not exactly the same. However, differences do not exceed half a standard deviation between the two methods of calculation. The results show a significant growth in the diameter of the root of the ICA between Groups II and III at stations A and B (Po0.001) in both the LAT and AP projections (Figs. 13–15). In contrast, there are no statistically significant differences in the diameter of the ICA between Groups I and II in both projections (P>0.05). In addition, changes in the diameter of the ECA between Groups II and III, stations A and B, are statistically insignificant except for the root of the ECA in the AP projection (Po0.05). As the carotid bifurcation matures, the angle between the daughter branches remains largely unchanged at about 77 . However, the angle between each branch and the terminus of the CCA undergoes marked changes (Table 4). The angle between the ICA and the CCA increases during maturation and doubles itself between Groups I and IV. The angle between the ECA and the CCA is undergoing a decrease such that the summation of the two angles remains unchanged. In contradistinction to calculation of diameters, the angles of the bifurcations show a larger departure from the values computed based on individual images. The reason for the larger variability in the calculated angle may be due to the method of angle estimation that relies on derivatives of a polynomial fit to the obtained centerline. Information on the dimensions of the transition zone between the CCA and its daughter branches is provided
Fig. 15. Evolvement of the human carotid bifurcation in AP and LAT projections. For the AP projection, the dark gray area is part of the ICA that does not overlap with the ICA. The black area interposed between the two shades of gray belongs to both the ICA and the ECA.
Table 4 Average angle of the human carotid bifurcation Bifurcation angle (y) (deg)
ICA angle (yI) (deg)
ECA angle (yE) (deg)
Calculated from individual images Group I 73.675.2 Group II 78.175.5 Group III 76.973.3 Group IV 76.779.6
16.179.6 20.3712.9 28.7714.2 34.3718.2
57.6711.4 57.8712.5 48.3715.0 42.4714.6
Calculated from the average image Group I 65.9 Group II 68.6 Group III 72.2 Group IV 68.6
17.1 19.5 26.1 26.5
48.8 49.1 46.1 42.1
(Table 5). A doubling in size of the transition zone corresponds to the overall enlargement of the vessels composing the bifurcation.
ARTICLE IN PRESS J. Seong et al. / Journal of Biomechanics 38 (2005) 453–465 Table 5 Distances between the bifurcation point and the root of the ICA and the ECA (units (mm))
Group Group Group Group
I II III IV
DI
DE
dI
dE
2.670.5 3.070.4 4.070.4 4.771.0
2.670.4 3.270.4 4.270.6 5.071.0
1.770.5 2.170.4 3.170.5 3.770.9
2.270.4 2.8770.4 3.770.6 4.071.0
dI and dE are the distances from the bifurcation point to the root of the CCA branches measured from the AP projection.
4. Discussion Only a few investigators have studied the morphology of the carotid bifurcation (Affeld et al., 1998; Bharadvaj et al., 1982a; Rindt et al., 1987; Salzar et al., 1995). Bharadvaj and colleagues studied 57 angiograms of 22 adults between 34 and 77 years of age and 67 angiograms of 50 children below the age of 18. All lengths measured from each bifurcation were rendered dimensionless with respect to the diameter of the CCA measured from the same angiogram because there was no absolute length scale available in the angiograms. To render the normalized values physiological, the representative internal diameter of the CCA in adults was determined to be a value of 8 mm, as suggested by Arndt et al. (1968) and Olson (1974). Based on a representative value of 8 mm of the CCA, Bharadvaj et al. (1982a) determined the other dimensions of their model. The mean value of the carotid sinus was 8.9 mm, the mean value of the ICA was 5.6 mm, and the mean value of the ECA was 4.6 mm. The average bifurcation angle was determined to be 50.5 . Salzar et al. (1995) measured the carotid geometry using six in vitro specimens, MRI slides, and 76 angiograms. The 76 angiograms were adapted from Bharadvaj et al. (1982a). More recently, Affeld et al. (1998) investigated the geometry of the carotid artery using vessel casts of 31 specimens. Cadavers of individuals between 22 and 91 years of age, with a mean age of 67, were used to make the vessel casts. The diameters of carotid arteries were measured manually using a digital caliper (0.05 mm error). The minimum and maximum of each diameter were measured, as the carotid branches at the bifurcation are not round but rather elliptical. Compared with previous studies, the measure of the CCA for adults in our study is comparable to those of Bharadvaj et al. (1982a). However, we did not observe a sinus diameter that is larger than the caliber of the CCA. The sinus dimension in our adult cases is slightly smaller than the dimension of the CCA, as in the study by Salzar et al. The average adult human bifurcation angle that was reported to be in the range of 50–60
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(Bharadvaj et al., 1982a; Affeld et al., 1998) is smaller than the average angle we obtained in our study. We measured the angle always at a predetermined bifurcation point that was a result of image processing and mathematical tools. If one deviates from this point and moves even slightly further into the daughter branches the measured angle will be smaller. Inaccuracies resulting from imprecise determination of the bifurcation point may have contributed to angle values that are lower than those we have obtained. The most significant findings when comparing morphological images of the carotid bifurcation of different age groups are the substantial growth of the ICA with age and the development of a carotid sinus at the root of the ICA. During maturation, the ICA, initially similar in size to the ECA until about 9 years after birth (Groups I and II), experiences a significant growth at its root during adolescence (Group III). The carotid sinus that is common at adulthood can be found in both projections of Group IV (20–36 years). Statistical analysis of the measured diameters in both the LAT and AP projections shows significant growth in the root of the ICA between Groups II and III in both projections (Po0.001). However, no corresponding growth in the root of the ECA was observed for the same age groups. These results suggest that the remodeling of the root of the ICA and the development of the carotid sinus occurs mostly during adolescence. It appears that the carotid bulb in humans is a result of arterial remodeling that coincides with maturation and growth of the brain, and it occurs at about the same time hormonal changes take place during puberty. One hypothesis suggests that the dilation serves to support pressure sensing (Arndt et al., 1968), another presumes that the sinus slows blood flow and reduces the pulsatility to protect the brain (Cavazzani, 1905). While the reasons for its appearance are unknown, it is interesting to speculate why this unique bifurcation develops in this way. To accommodate increasing flow demand by the maturing brain, the natural tendency is to reduce hydraulic resistance by increasing tube caliber. But the exit angle of the carotid branches cannot be changed markedly, because space is limited. And remodeling is confined to the ICA root. The enlarged conduit exposes blood flow to unfavorable complex patterns caused by flow separating from the walls (Bharadvaj et al., 1982b, Part II). Over a long period of time these complex patterns may be responsible for endothelial dysfunction and carotid bulb wall heterogeneity and subsequent development of atherosclerosis. Hemodynamic and hydraulic resistance studies on the evolving geometry of the carotid bifurcation may help to shed light on this question. Understanding the development of the carotid bifurcation can potentially impact how we address the degeneration of the bulb, i.e., atherosclerotic development in adulthood, which
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ultimately increases the risk of thromboembolic ischemic stroke. Stratification of flow within the carotid bulb with a stent-like device could potentially reduce the risk of atherosclerotic degeneration. It is well accepted in the medical literature that the carotid bulb is the ‘‘communicating station’’ between the heart and the cerebrovasculature for blood pressure autoregulation (baroreceptor function) or for conduction of oxygen and CO2 tension. Therefore, it would be of interest to elucidate what impact changes in bulb configuration during development and later on during atherosclerotic degeneration may have on autoregulation. For example, it could be speculated that damage to the otherwise normal bulb configuration and sclerosis/calcification may be two of the reasons for hypertensive brain hemorrhage resulting in inappropriate autoregulation, as is observed infrequently in elderly patients. Furthermore, if a relationship between the morphology of the carotid bulb and the physiology of the cerebrovascular system during brain maturation and development can be demonstrated, the function of the carotid bulb could technically be simulated. This could help to develop sensors and devices to prevent potential carotid bulb related pathology. One of the interesting results of this study is that the bifurcation angle (y) remains virtually unchanged during the growth period and maintains a value of 73.6–78.1 . However, the angle split between the ICA and ECA relative to the CCA does change. The ICA angle (yI ) increases continuously with age, with a corresponding decrease in the angle of the ECA. One of the reasons that the angle of the ICA (yI ) increases is the progressive increase in the diameter of the ICA and the remodeling of the CCA terminus to accommodate a smooth hydraulic transition into a growing ICA, with a higher perfusion demand. One limitation of the current study is the small database. For a more extensive analysis, a larger database is required. The average ICA/ECA angles that were obtained in this study contain standard deviation values that exceed 10 . These large errors preclude the confirmation of the average angle values. Although it is evident that the ICA angle (yI ) increases with age, the number of data points should be larger to determine more accurate average values. Another limitation of this study, again due to a sparse database, is that gender differences in the development of the carotid bifurcation were not evaluated. Since we observed that the major changes occur during puberty, it would be interesting to study if hormonal changes during that period have a differential effect on the development of the carotid arterial bifurcation in men and women. Additionally, no distinction between a left and a right carotid bifurcation was observed. Differences between the two carotids do exist, as pointed out in a study by Peterson et al. (1960). The left carotid
artery is closer to the heart and arises directly from the aorta, while the right carotid arises from the brachiocephalic trunk. However, whether these distinctions induce morphological differences that are either random or systematic will need to be evaluated with a much larger database than that available for this study.
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