(Circulation. 1996;93:567-576.)
© 1996 American Heart Association, Inc.
Articles |
Accurate Three-Dimensional Reconstruction of Intravascular Ultrasound Data
Spatially Correct Three-Dimensional Reconstructions
From the Departments of Medicine and Pathology, Northwestern University Medical School, Chicago, Ill.
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Abstract |
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 Top Abstract IntroductionMethods Results Discussion References |
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Background The geometrical accuracy of conventional three-dimensional (3D) reconstruction methods for intravascular ultrasound (IVUS) data (coronary and peripheral) is hampered by the inability to register spatial image orientation and by respiratory and cardiac motion. The objective of this work was the development of improved IVUS reconstruction techniques.
Methods and Results We developed a 3D position registration method that identifies the spatial coordinates of an in situ IVUS catheter by use of simultaneous ECG-gated biplane digital cinefluoroscopy. To minimize distortion, coordinates underwent pincushion correction and were referenced to a standardized calibration cube. Gated IVUS data were acquired digitally, and the spatial locations of the imaging planes were matched to their corresponding coordinates. Image points were then transformed relative to their respective 3D coordinates, rendered in binary voxel format, resliced, and displayed on an image-processing workstation for off-line analysis. The method was tested by use of phantoms (straight tube, 360° circle, 240° spiral) and an in vitro coronary artery model. In vivo feasibility was assessed in patients who underwent routine interventional coronary procedures accompanied by IVUS evaluation. Actual versus calculated point locations were within 1.0±0.3 mm of each other (n=39). Calculated phantom volumes were within 4% of actual volumes. Phantom 3D reconstruction appropriately demonstrated complex morphology. Initial patient evaluation demonstrated method feasibility as well as errors if respiratory and ECG gating were not used.
Conclusions These preliminary data support the use of this new method of 3D reconstruction of vascular structures with use of combined vascular ultrasound data and simultaneous ECG-gated biplane cinefluoroscopy.
Key Words: ultrasonics • coronary disease • imaging
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Introduction |
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TopAbstractIntroductionMethods Results Discussion References |
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High-frequency IVUS is a technique that allows visualization of in vivo vascular structures.1 2 3 This technique uses indwelling catheters with diameters as small as 1 mm with distally positioned 20- to 40-MHz piezoelectric transducers. Transverse cross-sectional images of peripheral and coronary arteries are obtained by advancing the 2D imaging plane at the catheter tip into an arterial segment to be visualized. This technique produces high-resolution images that have excellent structural definition of lumen and wall.
In vivo and in vitro validation of intravascular transducers has been performed primarily with straight vascular segments.4 5 6 Evaluation of the morphology and composition of atherosclerotic lesions within straight segments correlates well with pathological specimens.7 The utility of IVUS has been demonstrated during vascular interventional procedures to characterize atheroma size and composition, arterial geometry, results of interventions, and severity of dissections.8 9
There are, however, technical limitations to the procedure.10 IVUS images are obtained in a single plane perpendicular to the longitudinal axis of the catheter. Because only discrete 2D images are displayed at any given time, direct longitudinal vessel information and relationships are not displayed. Consequently, the operator is required to mentally integrate a series of transverse images to determine spatial relationships. The length of lesions and distance between landmarks can only be inferred by movement of the imaging plane.
To overcome the obstacles of 2D IVUS imaging, 3D reconstructions have been generated as a way of providing longitudinal information.11 12 The 3D display format provides a convenient way of integrating the 2D ultrasound data and appears to provide useful information concerning pathology, including dissections after intervention.13 Conventional 3DR algorithms, however, do not provide accurate spatial information. These approaches assume that the IVUS images were acquired from a straight vascular segment as parallel tomographic slices having a known separation distance. 3DR involves volumetric interpolation between adjacent imaging planes to fill in longitudinal image information. Since the sequence of input image files is reconstructed around a fixed, straight axis, the reconstructed vessels are displayed without curves. The slice separation distance is determined by the time required to traverse the segment during catheter withdrawal. With variation in pullback rate, vessel segments may be erroneously displayed as elongated or foreshortened. In addition, Waligora et al14 demonstrated that linear 3DR methods introduce substantial catheter-dependent geometric error in vessels with small radii of curvature.
Our purpose was to develop a method of 3D vascular reconstruction that used simultaneous acquisition of IVUS images and 3D ultrasound transducer coordinates. This method of 3D point registration was based on work originally performed by McKay et al to track left ventricular wall motion15 and augments recent work by Klein et al16 and Slager et al.17 Our method uses a calibrated spatial transformation algorithm applied to ECG-gated, biplane, digital, cinefluoroscopic images to determine the 3D coordinates of an IVUS catheter within the field of view. Gating allows these coordinates to be matched to the appropriate 2D ultrasound image for subsequent spatial orientation and rendering. We then tested the feasibility, accuracy, and clinical applicability of this method to assess accurate 3DR with IVUS data.
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Methods |
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TopAbstractIntroductionMethods Results Discussion References |
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Materials
IVUS Catheter
The IVUS catheter (Cardiovascular Imaging Systems, Inc) incorporates a 30-MHz single-element transducer with a rotating mirror enclosed in an acoustic housing at the distal end of the catheter. The mirror is located 1.8 cm proximal to the distal end of the catheter. The catheter is 135 cm in length and is advanced into position over a 0.014-in guide wire. The maximum outer dimension of the catheter is 5F (1.67 mm). Effective imaging is possible from the surface of the catheter to a depth of 3.2 mm. Lateral resolution of this system is 0.18 mm and axial resolution is 0.07 mm. Nominal two-point structural resolution is 0.1 mm at a focal distance of 2.2 mm.
Calibration Cube
A 1000 cm3
(10x10x10 cm) acrylic resin calibration
cube with 27 embedded steel markers was constructed. The distance from
the center of each marker to a reference corner (defined as the origin)
was measured along each axis. Measurements were made in triplicate with
machinist's calipers and averaged to determine the known
(x,y,z) coordinate locations of each marker (Fig 1A
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Phantoms
A circular phantom was constructed by
wrapping a 3.7-mm (OD),
2-mm (ID) guiding catheter segment around a 77-mm-diameter plastic
film reel. A straight phantom was constructed by mounting another
3.7-mm (OD) guiding catheter segment to a rigid wooden dowel. A spiral
phantom was constructed by spiraling a 4.0-mm (OD) polyethylene tube
around a 24x90-mm cylinder. Before determining in situ accuracy of the
arterial reconstruction, an ex vivo sheep coronary
artery bifurcation was pressure fixed in formalin and used as an
additional vascular phantom. Wire markers were placed on the phantoms
to provide external, radiopaque landmarks. The distance between
landmarks was measured in triplicate with calipers and averaged.
Methods
In Vitro Imaging
The calibration cube
was imaged with biplane digital fluoroscopy
(Coronix Bi-plane System with digital cardiac imaging, Philips
Medical Systems, Inc) in triggered mode (Fig 1B
and
1C). The image
intensifiers remained stationary and were positioned 90° from each
other for all image acquisitions. If other orientations were used, a
separate calibration of the image intensifiers had to be performed. The
phantoms and vessel segment were imaged during pullback of the IVUS
catheter. IVUS data were acquired simultaneously with the
triggered digital biplane fluoroscopy. The fluoroscopic and ultrasound
data were matched by gating the x-ray to an ECG simulator and
simultaneously embedding the pulse signal on the ultrasound
image, which was stored on videotape. Twenty to 31 paired biplane,
digital, fluoroscopic images were obtained during manual pullback of
the IVUS catheter through each phantom. The gated, paired x-ray
images were transferred from the digital memory to hard-disk
storage by use of a screen-digitizing program and network
(CathView, ImageComm Systems).
Spatial Orientation From
Biplane Projections
Spatial orientation is defined as the orientation
of a 2D plane
around a specific point in space. Our method of determining the spatial
location (the position of a point in space) of an IVUS catheter tip
from biplane cinefluoroscopic projections was adapted from the
procedure described by McKay et al.15 This procedure
involves two fundamental stages: (1) transformation matrix calculation
from points having known spatial location and (2) 3DR of arbitrary
points having unknown spatial location. As used in our application, the
result of this procedure was accurate spatial location of the IVUS
imaging plane (the 2D plane in which the IVUS data lay) in 3D space.
This information also defined the centerline along which the discrete
IVUS images were oriented. The spline-fit centerline is defined as
the trajectory of the catheter that is a curve fit through a series of
discrete R-wave–gated catheter mirror locations. Determination of
the spatial orientation of the ultrasonic image required rotation of
the images around the vessel centerline.
Briefly, the relationship between a 3D point (x,y,z) and the appearance of this point in an arbitrary 2D projection (u,v) is given by the equation:
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where k is a scaling factor, T is a 4x3 transformation matrix that describes an arbitrary perspective view (eg, biplane view), and (x,y,z1) and (u,v1) are cartesian coordinate representations of the 3D and 2D points, respectively. In the current application, a unique view transformation matrix (T) was computed for each of the orthogonal cinefluoroscopic views. To determine the transformation matrix associated with the biplane views, the calibration cube (which possesses steel markers of known spatial location) is simultaneously imaged from both perspectives with the setup used to acquire the phantom or patient data. 2D-Projected positions (u1,v1) of the points of calibration object are related to their respective known 3D locations (x1,y1,z1). Each point (1) must satisfy the equation given above. The matrix equation results in a series of three linear equations in which the elements of T are the unknowns. Since the u,v terms can be measured from the projected biplane views and the x,y,z terms are known from the calibration cube, the 12 elements of the view transformation matrix (T) can be determined. For additional details, refer to McKay et al.15
The resulting view transformation matrix (T) allows a mathematical means of mapping arbitrary points with unknown 3D location in a given biplane (2D) projection to their actual position in 3D space. A minimum of 6 markers are required for accurate position identification; however, for the purpose of the present study, 15 markers were identified.
After the transformation matrix for both biplane views has
been
independently determined, the 3D spatial coordinates (x,y,z)
of an arbitrary point (point associated with the imaging plane of an
IVUS catheter) can be reconstructed from the measured location of the
projected 2D points
(u1,v1) and
(u2,v2) in the two
biplane views. This process is known as 3D point reconstruction and
involves the least-squares solution of simultaneous
matrix equations in which the only unknown quantities are
x,y,z (Fig 2).
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3D Reconstruction
Each ECG-gated ultrasound image was manually captured from
videotape by use of the digitizing program on a commercial 3D
workstation (StatView, ImageComm Systems). The raw IVUS image files of
the phantom/vessel structure were processed via gray-scale
thresholding and edited to remove remaining catheter artifact and noise
by use of a commercial graphics utility program (OmniView version 2.1,
Pura Labs). Because the value chosen for the threshold level plays a
role in the 3DR algorithm, gray-scale thresholding was performed by
a single operator (J.L.E.) on all studies. To establish the clinical
reproducibility of our thresholding technique, intraobserver and
interobserver variability was performed on 16 IVUS images by three
blinded observers (M.J.V., W.B.B., and S.G.W.). The resulting image
files were stored on a network file server (80386-based PC with Novell
Advanced Netware 286 software). Fig 3 demonstrates an
image before and after processing.
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The two transformation matrices
(view 1 and view 2) were determined
from the cinefluoroscopic views of the calibration cube (for matrix
transformation calculation). Subsequently, the location of the IVUS
transducer mirror in each gated/paired cinefluoroscopic frame of the
pullback was identified by manually positioning a cursor over the IVUS
mirror and determining the corresponding pixel address (Pixie version
1.5, ImageComm Systems) (Fig 4A). We defined the
location of the IVUS imaging plane as being centered on the midpoint of
the rotating mirror. For images in which the catheter was rotated
around the central axis, rotation correction was added. As catheter
rotation was inhibited in our study, it was assumed to be negligible. A
second-order polynomial correction was then performed to correct
for pincushion distortion by use of a previously described
method.18 Pincushion correction was performed once for the
calibration cube and matrix and once for the image data in which the
transformation matrix was used.
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The processed 2D image data set was
then converted from ImageComm
format to PC-Matlab format (PC-Matlab version 3.5, The Math Works,
Inc). Each IVUS image was then scaled, translated to its relative 3D
position by use of the previously determined transformation matrices
procedure, and rotated to a plane perpendicular to the centerline as
determined by the best spline-fit curve of the sequence of IVUS
transducer mirror location data. This spline-fit curve effectively
represented the trajectory of the catheter during
withdrawal. The imaging plane of the IVUS catheter was defined as the
plane perpendicular to the longitudinal axis of the catheter shaft
passing through the center (midpoint) of the acoustic mirror. The
midpoint of the acoustic mirror was visually identified in each of the
biplane fluoroscopic views by a human operator. Fig 4B
illustrates
graphically the 3D orientation of the data set before and after
reorientation. Linear interpolation was performed between adjacent
image sets, resulting in a volumetric (voxel) data set. The voxel data
set was resliced along the z axis, creating a new series of
parallel, 2D frames that were then reconverted to ImageComm format.
3D
images were created by processing the data with algorithms developed
specifically for voxel-based image display (Sonoview, Pura Labs).
The resulting images were displayed on a workstation for display and
analysis. Fig 4C illustrates the reconstructed images rotated
in several planes.
Protocols
Initial validation.
The feasibility and accuracy of
the 3DR method was tested with use of phantoms and an isolated sheep
coronary arterial segment. Each preparation was
imaged in a water bath and subsequently reconstructed. The phantom
shape was compared qualitatively with the reconstructed shape. The
distances between markers on the phantoms were determined by processing
the x,y,z coordinates of the IVUS transducer mirror at the
points (P1 and P2) where it crossed the planes
of two marker wires by use of the following equation:
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where P1=(x1,y1,z1) and P2=(x2,y2,z2).
Volume measurements were calculated from the phantoms by summing the product of the known 2D cross-sectional lumen areas and the distance between center points determined by use of the above equation (Simpson's method). For the coronary specimens, histological volume measurements were computed as the product of marker distances and lumen areas determined from histological slides. The corresponding volume from the computer-reconstructed segment was determined as the product of the number of voxels that composed the lumen and the unit volume of each voxel.
Validation—ex vivo specimens. Seven calf coronary arteries were studied in situ, ex vivo. The coronary arteries were cannulated with 9F guiding catheters that were then fixed in position. The arteries were perfusion fixed with formalin at distending pressure (80 mm Hg), then the entire heart was fixed in formalin for 24 hours. After fixation, the coronary arteries were imaged in a water bath simultaneously with IVUS and with biplane digital cinefluoroscopy with use of an ECG simulator for gating. Data from one right, four LAD, and two circumflex coronary arteries were collected with the angiographic position registration system.
After imaging, the arterial segments were filled with a barium, formalin, and gelatin mixture at physiological distending pressure to preserve 3D morphology of the in situ vasculature. The arterial segments were then dissected from the hearts. Histological sections were made at 1.0-mm intervals by use of previously implanted markers on the arterial segments for reference to the 3D IVUS data.
Volume estimates of the coronary specimens were made by summing the product of histologically determined lumen area and the linear intersection distance (Simpson's method).
Distance and volume measurement variability of the histological specimens previously has been shown in our laboratory to be <5% with this technique (unpublished data, 1984).
Initial clinical studies. This clinical protocol was approved by the Institutional Research Committee of Northwestern University. The feasibility of this method of 3DR was tested in seven patients (12 vessels). After obtaining informed consent, intracoronary ultrasound imaging was obtained in the cardiac catheterization laboratory after or during interventional procedures. In addition to routine intracoronary ultrasound imaging, a pullback through the vessel was recorded during a period of suspended respiration. Biplane digital fluoroscopy triggered by the patient's ECG signal was performed simultaneously with the pullback. The ECG pulse signal was superimposed onto the ultrasound videotape by use of the technique described earlier. The position of the image intensifiers and the table were recorded and fixed during IVUS catheter pullback. As catheter mirror position was used to determine image orientation, the catheter was maintained in a stable rotational position throughout the pullback. After the study was completed, the image intensifier positions were reproduced and the calibration cube was imaged.
Statistical Analysis
Because the data were continuously
matched pairs, linear
regression and correlation were used to describe the data sets. Results
are expressed as mean±SEM. Paired t tests were used to
determine whether there was a consistent error between the
actual versus calculated measurements. A value of P<.05 was
defined as significant for all comparisons.
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Results |
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Validation
Qualitative
The purpose of the initial phase of the project was to develop and test our algorithms.
Fig 4 demonstrates the various
stages of our testing with a
circular phantom. Fig 4A represents two views at two time
sequences of the original phantom with the ultrasound transducer
present within the tube lumen. Fig 4B illustrates our spatially
oriented ultrasound data before and after reorientation of the image
planes. Fig 4C illustrates the final 3DR after interpolation
and
smoothing of data points. The marked similarity of shape and proportion
is easily noted by comparing Fig 4A and 4C. The
opening in the circular
reconstruction represents the start and end of the transducer
pullback.
Fig 5 depicts the reconstruction of the spiral
phantom.
Fig 5A illustrates the digital cinefluoroscopic image of the
contrast-filled phantom and Fig 5B, the corresponding 3D IVUS
reconstruction. The shape and proportion of the 3DR are similar to
those of the phantom.
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We were able to demonstrate with a variety of phantoms that these algorithms could be used to make recognizable reconstructions that were qualitatively geometrically similar.
Quantitative
Phantoms. To aid in quantifying our data, radiopaque markers
were placed on each of our phantoms as noted on Figs 4A and
5A. Table 1 lists and Fig 6
illustrates the
measured intermarker distances on each of the phantoms (straight,
circular, spiral, and coronary bifurcation) compared with the
calculated distances derived from the transducer position registration
data. Twenty-one chords and diameters were measured on the circular
phantom. Ten distance measurements were obtained from the straight
phantom, four from the spiral phantom, and four from the sheep
coronary artery preparation. Actual versus calculated
measurements were very close. All errors were within 2 mm for segments
shorter than 4 cm and within 5 mm for the longer segments
(P=NS). Volumes were determined for each of the tubes used
in phantom reconstruction. Table 2 demonstrates the
close comparison of the measured volume of each tube to our calculated
volume. The calculated errors were within 3%.
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In vitro
specimens. Fig 7 illustrates
comparisons of luminal distances, areas, volumes, and total volumes for
the in situ, ex vivo vascular segments. Total volume was defined as
luminal plus wall volume. The arterial wall was defined by
IVUS from the leading edge of the inner bright specular reflector to
the trailing edge of the outer bright specular reflector that subtended
the arterial segment and by histology from the intima to
the dense adventitia. There was good correlation between IVUS 3DR and
histological (HISTO) measurements, as follows:
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Luminal distances (mm): 3DR=0.9 HISTO-0.6; r=.84; n=22.
Luminal areas (mm2): 3DR=1.0 HISTO+1.0; r=.88; n=27.
Luminal volumes (mm3): 3DR=0.9 HISTO+4.3; r=.81; n=21.
Total volumes (mm3): 3DR=0.9 HISTO+35.0; r=.83; n=21.
Variability
Intraobserver and
interobserver variability of the thresholding
border technique was found to be 8.1% and 9.8%, respectively. These
results were based on three blinded reviewers who each set thresholds
twice on 16 representative IVUS images.
Clinical Studies
A total of 12 vessels (native coronary
arteries and
saphenous vein grafts) were imaged and reconstructed in seven patients.
All patients were undergoing an interventional coronary
procedure at the time of IVUS collection. The time added for data
collection was generally <4 minutes (maximum for 2 vessels was 10
minutes), with actual imaging lasting 20 to 30 seconds. Fig 8
depicts an angiogram of a LAD coronary artery
and the corresponding reconstruction. The reconstruction qualitatively
depicts vascular geometry and the proximal curve.
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Gating for ECG and
respirations was important to avoid introducing
motion artifacts into the reconstruction. Fig 9
illustrates an example of a saphenous vein graft angiogram (Fig
9A) and
3DR (outer wall, Fig 9B) distorted by breathing. The angiogram
demonstrates no tortuosity.
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Of the 12 vessels that were initially reconstructed, 7 visually demonstrated luminal geometry similar to the angiographic segment (1 proximal LAD; 2 mid-LAD coronary arteries; 1 first obtuse marginal; and 3 saphenous vein grafts to a LAD, right coronary, and first obtuse marginal, respectively). Respiratory motion resulted in distorted 3DR of 3 segments (1 saphenous vein graft, 1 obtuse marginal, and 1 right coronary). IVUS image dropout hampered good 3DR of 2 saphenous vein grafts (to a diagonal and right coronary artery). As our present thresholding algorithm does not add missing information, image dropout was demonstrated in the reconstructions if present in the original data.
Overall, if respiration motion was suspended and image borders could be detected on the IVUS data, the 3DR visually described the relationship of each segment as displayed by the angiogram.
Additional unexpected
information was found. Fig 10
illustrates a 3DR (Fig 10B) of a saphenous vein graft to an
obtuse
marginal branch with the angiogram on the left (Fig 10A).
Because the
saphenous vein graft is untethered, there is straightening of the
vessel due to the presence of the catheter in the graft during pullback
through the curve (arrow in Fig 10B). This type of logical
information
would be missed with traditional 3DR techniques.
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Discussion |
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TopAbstractIntroductionMethods Results Discussion References |
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IVUS provides in vivo information regarding vascular morphology and pathology. The present utility of IVUS is limited by the display format, which demonstrates only single transverse or oblique vascular sections at a single time and provides only indirect longitudinal information.
Our data has demonstrated the accuracy and initial clinical applicability of a method that allows spatially correct 3DR and display of IVUS data in the coronary bed. The discussion will focus on previous methods of 3DR, advantages of our technique, potential sources of error, and applications.
Previous Methods of 3DR
Studies have demonstrated the
feasibility and benefits of 3DRs of
vascular segments.11 12 13 Despite
anatomic limitations,
clinically useful information can be obtained with near real-time
reconstruction of IVUS images acquired in the
catheterization laboratory. The resulting
reconstructions appear straight but can be rotated around each axis and
electronically sectioned to reveal internal structure. These images can
visually provide an estimate of lesion length, dissections, and vessel
segment morphology. Although this technique may be useful in many
peripheral vascular beds, which are relatively straight, or
in very small coronary artery segments, inherent tortuosity of
the vasculature degrades the geometric accuracy of conventional 3D
IVUS. Atheroma provides further tortuosity and may add to
the inaccuracy of nonspatially correct 3DR.10 Klein et
al16 described a method that used biplane angiography to
define the vessel midline in 3D space. Serially, collected IVUS images
from the target vessel were aligned perpendicular to the vessel
midline, subjected to longitudinal interpolation, and displayed as a 3D
structure. Recent work by Slager et al17 extended the
concept of combining biplane angiography and IVUS for vascular 3DR.
Their technique involved estimation of the trajectory of the IVUS
catheter. Corresponding image data were then arranged perpendicularly
around the trajectory axis, and 3DR was performed. Both
methods16 17 produced accurate renderings of vascular
geometry and are promising analogues to the method we report.
Attributes of our method are the inclusion of cardiac and respiratory
gating to minimize 3DR motion artifacts, the extension into the
coronary bed, and extensive validation.
We reviewed a total of 17 different techniques that described 3DR of vascular and ventricular structure with IVUS, B-mode ultrasound, and radiographic modalities. The method that we chose was originated by McKay et al.15 Our adaptation of this technique is unique and applicable when ease of implementation, compatibility of the technique with our facilities, and the efficacy of a least-squares error fit are considered. It does not require other resources except a calibration cube and gated biplane cineangiography.
McKay's algorithm15 was never intended to provide 3DR of the coronary tree, although he did estimate the geometry of these structures in schematic fashion. Rather, he was interested in cardiac wall motion ascertained through 3D motion branch points of the coronary circulation. However, this algorithm, as we have demonstrated, can be well adapted for the vascular bed.
Potential Advantages
Our reconstruction technique has several
potential advantages. By
using 3D coordinates, we can track the position and vector of the
transducer in 3D space. This allows placement of the ultrasound image
data into a 3D matrix in a position that is
representative of its true position and spatial
orientation.
Cardiac and respiratory motion influence our results and
are the
primary reason for ECG gating and respiratory suspension. The time
required to implement the spatially correct algorithm is 
4 minutes
per vessel added to the cardiac catheterization
procedure. Additionally, 15 minutes is required for setup before the
procedure and 60 minutes for the 3DR. More sophisticated processing
equipment could further reduce the 3DR time. In fact, with current
trends in computing power, on-line data collection, orientation,
and display should be achievable.
The mean ultrasonic image slice distance depends, to some extent, on the pullback time. With our very slow manual pullback and use of centerline geometry, our distance is presently 1 mm. If a much slower pullback occurred, the number of image slices per millimeter could be increased. Newer, motorized pullback devices allow IVUS data collection at constant pullback rates as low as 0.5 mm/s. Automated pullback devices allow a standard, uniform pullback of the catheter at the proximal:distal end. In tortuous vascular beds and especially in the coronary beds, a linear pullback 1:1 ratio cannot be obtained even with use of these automated pullback devices. In addition, accordioning (vessel peel off) as the catheter is pulled back causes further difficulty in systems that require uniform pullback for 3DR. Our algorithm does not require the assumption that 1:1 matching has occurred. Recent development of sheath-type IVUS catheters, in which the IVUS imaging element can be withdrawn through the body of the catheter shaft while the catheter itself remains stationary, may improve the reliability of timed pullback techniques, reduce accordioning distortion, and improve 3DR IVUS accuracy.
A major problem
with present linear reconstruction techniques,
especially in the coronary bed, is their lack of true image
orientation. Research conducted by our laboratory suggests that there
is an inverse relation between vessel curvature and the volumetric
accuracy of 3DR IVUS.14 Despite the use of slow, motorized
catheter withdrawal and sheath-type IVUS catheters, important
errors may be incorporated into 3DR IVUS techniques that do not account
for the true image orientation. This is displayed graphically in our
example (Fig 10) of the saphenous vein graft 3DR that, by
angiography,
has one small curve but that demonstrates a much larger iatrogenically
induced curve when the catheter is pulled through the vascular
segment.
We have demonstrated with a variety of phantoms that our reconstructions are representative in shape and accurate in position. Since we use this method to position the long axis of the IVUS catheter, which will move several centimeters, an error introduced by this technique should be within an acceptable range.
Potential Sources of Error and Study Limitations
Several
factors were noted that influenced our results. Our in
vitro vascular imaging results were limited by movement of the
arterial segment in the water bath during pullback, with
accordioning (vessel peel off) of the segment over the catheter. This
movement artifactually caused a systematic error in the distance
calculations determined from the foreshortened segment when compared
with actual measurements made with the artery fully extended.
Similarly, respiratory suspension limited this study to short and
medium-length arterial segments. Newer techniques of
respiratory gating should allow accurate 3DR of relatively long
segments. Our cube, although custom made, was not precision
instrumented. The accuracy of our transformation matrix should improve
further with a precision-instrumented cube. We determined all of
our x,y,z coordinate locations by using the pixel address of
the point on digitized images. The pixel density was 512x480 for a
9-in digital fluoroscopic image. The higher line density (1024x1024)
of many angiographic monitors should increase accuracy. Likewise, the
process of manually identifying the catheter mirror in the fluoroscopic
images was a source of variability. Scaling was required to display the
entire reconstruction on our video screen, and this necessitated
reduction of ultrasound image data points for reconstruction. Although
this data reduction clearly decreases the quality of the ultrasound
image, it is likely that continued improvements in computing speed and
memory will necessitate less scaling in future adaptations. Full
gray-scale resolution, which provides additional visual cues
regarding vessel composition, was difficult with our present image
processing system. Full gray-scale 3DR is available on many newer
image processing systems and will allow better identification of plaque
load and atheroma components.
The results in Fig 7
demonstrate a better correlation of our technique
to histology when lumen distance and area measurements are compared
than when volume measurements are compared. The larger volume error can
be attributed to the difference in methods of volume computation.
Histological volume was computed as a direct
product of lumen distance (ie, a straight line) and area, whereas
the IVUS 3DR volume was calculated as the interpolation between each
set of lumen areas by use of a spline-fit curve technique. This
discrepancy in volume measurements is greater in tortuous and curved
segments, in part because of curvature that cannot be accounted for
with most methods of histological volume calculation,
including our own.
An additional source of 3DR error was the presence of structural mirror artifacts ("strut" artifacts) in the 2D IVUS images. These artifacts are inherent in the rotating mirror catheter design used in the current protocol and should be reduced with newer-generation imaging devices. Although this artifact did not affect the accuracy of catheter coordinate locations, it could result in lumen and wall area and volume errors, because it tends to obscure and distort a sector of visualized arterial wall. This can be demonstrated by our variability measurements of the threshold technique for IVUS edge detection. Although intraobserver and interobserver variability both were within 10%, which is acceptable for ultrasound image data, the variability in measurements may be due to edge clarity of the IVUS image data. Further improvements in IVUS presentation of image data may decrease this variability. Our method used respiratory suspension, which limits the present method to short or moderate-length coronary and peripheral vascular segments. Newer methods of respiratory gating should allow adaptation of this technique to large arterial segments.
Despite these limitations, our results are very promising. Our study was primarily designed to test the feasibility of this technique for obtaining spatially correct 3DRs, to validate the technique, and to demonstrate feasibility in the clinical setting. A larger clinical study will be required to determine utility.
Applications
True 3DR of vascular studies will have multiple
basic and clinical
applications. The potential exists to quantify the volume load of
atheroma that is present within a vessel segment.
Atheroma removal or displacement of this material can be
evaluated after an interventional procedure in either a
coronary artery or a peripheral vessel. In
addition, the evaluation of complications of interventions, such as the
length and depth of a dissection, should be quantifiable.
There are numerous basic applications for this technique. Accurate geometric reconstructions of arterial wall and lumen will allow true evaluation of changes in segmental vascular reactivity with atheroma and hypertension and after intervention.
Conclusions
We have demonstrated that spatially correct 3DRs
of IVUS data with
simultaneous biplane-triggered fluoroscopy is possible.
In phantoms, the reconstructions have been shown to appear correct,
with accurate distances and volume calculations. We also have
demonstrated the feasibility of applying this technique in patients at
catheterization. With this method, the potential exists
for accurate display and analysis of vascular wall and luminal
anatomy.
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Selected Abbreviations and Acronyms |
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Acknowledgments |
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This study was supported in part by the Chicago Heart Association, the Feinberg Cardiovascular Research Institute, and the National Institutes of Health (grant No. HL-46550). The authors gratefully acknowledge manuscript preparation by Jean Waller and Cynthia Shane.
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Footnotes |
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Reprint requests to James L. Evans, MD, Tucson Medical Center, 2355 N Ferguson Ave, Ste 111, Tucson, AZ 85712, or David D. McPherson, MD, Wesley - Ste 524, Northwestern Memorial Hospital, 250 E Superior, Chicago, IL 60611.
Received April 24, 1995; revision received September 12, 1995; accepted September 17, 1995.
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