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IVUS-OCT QUANTIFICATIONS:
WHAT TO MEASURE AND HOW TO DO IT?
Vasile Sirbu, Giuseppe Musumeci
Cardiovascular Department, Cardiologia 2, Diagnostica Interventistica, Ospedali Riuniti di Bergamo
Invasive coronary angiography has been the gold standard during the past 50 years for establishing the presence, location, and severity of epicardial coronary artery
lesions. It has the great merit in bringing back the atherosclerotic pathology to one single parameter easy to be
managed: the severity of stenosis.
OCT, and IVUS are invasive intracoronary imaging
techniques. Both use the delay time of echoes, IVUS
directly ultrasound echo, and OCT indirectly-optical
echo using the technique known as interferometry. IVUS
has good penetration in tissue allowing the visualization
of the so called “far field”, OCT has high luminal resolution, and permits to analyze in detail the “near field”
(Figure 1). The combination of these techniques brings
complementary information. Both of them allow data
quantification, and reporting in a standard accepted way.
Measurements in OCT and IVUS can be divided in
qualitative, and quantitative, can be performed pre procedure, post stent implantation, and in follow-up to
assess the vessel response to either stent implantation or
medicamentous treatment.
The analysis of the intracoronary images starts with the
quality screening. During this initial process frames with
poor quality are excluded from further analysis. The reason to exclude a frame from OCT analysis are: a large arc
of the image is out of the screen or a side branch occupied >45° of the cross-section, this usually happens when
large diameter vessels (>4 mm) are present in the scanned
segment. Poor image quality can be caused also by residual blood or artifacts. Large vessels, and blood presence is
not affecting the quality of IVUS scan. Motion artifacts
can decrease the accuracy of measurements. Some of
them are common in both OCT and IVUS, and others
are unique in OCT imaging systems(1).
No uniform rotational distortion “NURD” - focal
image loss or shape distortion, and “sew-up” artifact the result of rapid artery or imaging wire movement in 1
frame’s imaging formation, leading to single point misalignment of the lumen border are common for both
IVUS and OCT.
Artifacts specific for OCT are more numerous. Some of
them like “saturation artifact” signals with amplitudes that
exceed the dynamic range of the data acquisition system
produced by reflected light or “bubble artifact” attenuation of the signal along a region of the vessel wall caused
by small air bubbles in the sheath of the ImageWireTM,
“sunflower effect” or “merry-go-round artifact” caused by
eccentricity of the ImageWire in the vessel lumen does not
affect grossly the image interpretation or quantifications.
Others like “fold-over” artifact- the consequence of the
“phase wrapping” along the Fourier transformation when
structure signals are reflected from outside the system’s
field of view or NURD requires frame removal from subsequent analysis (Figure 2).
No consensus agreement is present in the literature
regarding the “ideal” interval of OCT analysis. It can be
performed at different intervals along the scanned segment, ranging approximately from 0.06 mm up to 1
mm. Continuous assessment of every frame is not recommended because cardiac dynamics introduces forward
and backward longitudinal displacement of the image
wire, a phenomenon that can cause the “persistence” of
Corresponding author:
Dott. Vasile Sirbu
Cardiovascular Department - Cardiologia 2 - Diagnostica Interventistica - Ospedali Riuniti di Bergamo
Largo Barozzi, 1 - 24128 Bergamo (BG) - Italy
Tel. +39.035.266455 - Fax +39.035.400491 - Cell. +39.320.7722456 - E-mail: [email protected]
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B
A
C
D
Figure 1. Very late stent thrombosis.
Corresponding angiographic (A), IVUS long-view reconstruction (B), OCT cross-sectional images (C, D) obtained after
thrombus aspiration. IVUS has good tissue penetration and allows visualization of the positively remodeled vessel, OCT
has high luminal resolution and permits to analyse in detail the presense of coverage, stent apposition and thrombus
classification.
A
B
C
D
E
Figure 2. Most common artifacts in OCT.
A: out of screen”; B: blood contamination; C: “fold-over” artifact; D: “bubble” artifact; E: “saturation” artifact. Residual
blood attenuates the OCT signal. Saturation artifact occurs when light reflected from a highly specular surface, such as
stent struts, produces signals with amplitudes that exceed the dynamic range of the data acquisition system. Fold-over
artifact is more specific to the new generation of FD-OCT. It is the consequence of the “phase wrapping” or “alias” along
the Fourier transformation when structure signals are reflected from outside the system’s field of view. Bubble artifact
occurs when small air bubbles are formed in the sheath of the ImageWireTM (LightLab Imaging, Inc. - Westford, MA,
USA), and it can attenuate the signal along a region of the vessel wall.
the previous frame image in the current frame. Conversely, large intervals are to be avoided since strut coverage or
malapposition may occur in clusters. Shorter intervals
were adopted by our group to improve the sensitivity of
the method, and minimize the variability of strut-level
response(2).
Both in IVUS, and in OCT analysis can be performed on
frame, segment or vessel level. On the frame level vessel
morphology and stent vessel interaction can be analyzed.
40
Vessel morphology allows detection of the amount, and
the characteristics of the pathology. The criteria for
plaque characterization in both systems are based on signal interpretation, and are present for 10 years for IVUS,
and recently published for OCT(3,4). A higher sensitivity
and specificity of OCT for tissue characterization of coronary plaques compared to integrated backscatter IVUS,
and conventional IVUS for fibrous, calcium, and lipid
pool has been reported(5) (Figure 3). Still, IVUS is more
IVUS-OCT QUANTIFICATIONS: WHAT
TO
MEASURE
AND HOW
A
B
C
D
E
F
G
H
I
J
TO DO IT?
Figure 3. Coronary plaques seen by OCT.
A: normal vessel wall is characterized by a layered architecture, comprising high backscattering or signal-rich intima
(thin), a media that frequently has low backscattering or is signal-poor, and a heterogeneous and sometimes highly
backscattering adventitia. With OCT, the internal elastic membrane (IEM) is defined as the border between the intima
and media and the external elastic membrane (EEM) is defined as the border between the media and the adventitia).
OCT measurement of intimal thickness, which is the early phase of coronary atherosclerosis, is well correlated to histological examination; B: atheroma from 6 to 13 o’clock with homogeneous signal backscattering; C: microvessels that
supply blood to atheroma (arrow); D: fibrous plaque has high backscattering and a homogeneous OCT signal (arrow);
E: fibrocalcific plaque calcific at 1-3 o’clock: fibrous tissue and calcium characterized as a signal-poor that has a sharply
delineated border; F: thick cap fibroatheroma and, a thick cap (>65 µm) (arrow) with signal attenuation due to necrotic
core behind characterized by a fast optical signal dropoff and little backscattering within the lesion; G: thin cap
fibroatheroma, a delineated necrotic core with an overlying fibrous cap with thickness less than 65 µm and signal attenuation behind due to necrotic core. The bright points of signal enhancement suspect colonies of phoamy cells. Multiple
studies demonstrate these lesions are more commonly found at the culprit site in patients with ACS and AMI; H: ruptured thin cap fibroatheroma identified by a presence of fibrous cap discontinuity and(red arrow) a cavity formation within (asterix), thrombus deposition on top (white arrow); I, J: thrombus identified as abnormal mass protruding into the
lumen, with signal backscattering and various degrees of attenuation. White thrombi were characterized by signal rich
and low-backscattering projections protruding into the lumen (arrows). Sometimes them may be sufficiently large to
obscure the underlying rupture site or luminal defect (J).
able to quantify plaque volumes, and phenomenon of
positive vessel remodeling (Figure 4). A correlation
between the presence of positive vessel remodeling in
IVUS, and higher number of TCFA in OCT in the
examined vessel was found(6). Information about preprocedure plaque type can have prognostic implications.
OCT, and IVUS can visualize features related to the culprit lesion such as plaque rupture, and subsequent thrombosis(7,8). Identification of the high-risk plaque for distal
embolization remains a challenge during coronary interventions, and tissue characterization might give unique
information in this scenario. The amount of lipid content
is correlated to the “no reflow phenomenon” in acute
coronary syndrome (ACS)(9). Information about calcium
content, and distribution can help in planning plaque
preparation, and debulking techniques(10).
Pathology studies performed the late 1990s have
changed the primary focus for heart attack prevention
from coronary stenosis to coronary vulnerable plaquethin cap fiboatheroma (TCFA), and TCFA rupture. A
hypothesis that measurements of plaque volume or composition may provide indices that would serve as useful
surrogates for subsequent clinical events was proposed(11).
Recently softwares performing spectral analysis of ultrasound backscattered data were implemented into conventional IVUS systems. These software facilitate the
interpretation tissue components, and allow quantification of the morphological findings like the percent of
necrotic core, lipid burden, and calcium extent in the
examined vessel (Figure 5). Some limitations of IVUS tissue characterization should be acknowledged: the plaque
components identified by each system vary, and a uni41
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A
B
C
D
Figure 4. IVUS calculations.
IVUS has good tissue penetration and allows visualisation of external vessel border and thus permits quantification of
plaque volume. A: long view reconstruction of a stented coronary in follow-up with evidence of sever positive remodeling
that accompanies only the stent and not the rest of the vessel (arrow); B: distal reference segment showing a calcific
plaque from 6 to 8 o’clock (arrow); C: stented segment with quantifications of extenal elastic membrane (arrow), stent
and lumen CSAs; D: proximal reference segment showing a fibrotic plaque from 3 to 7 o’clock (arrow).
form color codification is lacking, and thrombus is not
recognized by the encoding algorithms.
Two different approaches are present in determination of
the lesion responsible for acute coronary events, TCFA:
IVUS uses the amount of necrotic core, and plaque volume, and OCT uses the cap thickness (Figure 6). In
intravascular imaging a ruptured plaque is identified by a
presence of fibrous cap discontinuity, and a cavity formation within(12). Serial examination of vessel morphology,
evaluating the progression/regression of specific atheroma
features under lipid-lowering therapy, demonstrated significantly increase in fibrous-cap thickness by OCT follow-up(13), and reduced amount of necrotic core, and
plaque volume, using IVUS(14).
Thrombus is frequently identified in target lesions, and
depending on its composition is classified on white, and
red with respective optical characteristics in OCT. Red
thrombi have OCT appearance as high-backscattering
protrusions inside the lumen, with signal-free shadowing. White thrombi were characterized by signal rich,
42
and low-backscattering projections protruding into the
lumen(15). Thrombus can also be visualized in IVUS if
appropriate enhancement techniques are applied, but no
classification on thrombus type is present (Figure 7).
Both systems are valuable in detecting the morphometric
characteristics of the vessel as minimum vessel diameters,
and areas, reference segments, stenosis quantification.
(Figure 4, 5). The parameters regarding post stent implantation evaluation are apposition to the vessel wall, the
minimum, and maximum stent diameters, and areas as
well as derived indexes as stent expansion, and simmetricity. The incomplete stent apposition (ISA) can be evaluated by calculating the fraction of the lumen area outside
the stent cross-section area (CSA). A number of derived
morphometric measurements are usually presented: the
minimum stent CSA divided by the average of reference
lumen CSA ratio is usually calculated as a parameter of
stent expansion, while the minimum stent diameter
divided by maximum stent diameter as a parameter of
stent simmetricity. While during BMS era it was impor-
IVUS-OCT QUANTIFICATIONS: WHAT
tant to maximize the final result due to the important
late-loss, nowadays, while using DES, concerns regarding
stent thrombosis has focused attention on optimal stent
deployment(16,17).
Using OCT, a more detailed evaluation of the vessel
TO
MEASURE
AND HOW
TO DO IT?
response to injury after implantation like tissue protrusion, edge dissection, residual reference segment stenosis“geographic miss”, and residual thrombus (Figure 9).
Metal stent struts are opaque, and act for light as a mirror, thus only the luminal surface of individual struts is
Figure 5. IVUS tissue characterization softwares.
The software uses post processing of the backscattered radio frequency IVUS signal in order to characterize plaque
composition. The iMap by iLab System Software (Boston Scientific Corp) does tissue characterization based on pattern
recognition and integrated backscattered ultrasound signals. Values are calculated as average power of the backscattered signal using a fast Fourier transformation.
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A
C
N. 1• 2011
B
D
E
Figure 6. Thin Cap Fibro Atheroma in OCT.
A: evidence of TCFA with cap thickness of 60 µm (arrow); B: TFCA erosion with evidence of discontinuity of thin cap and
connection of the cavity with lumen of the vessel (arrow); C: distal and proximal (E) reference segments. The site with
the largest lumen proximal to a stenosis but within the same segment (usually within 10 mm of the stenosis with no
major intervening branches). Reference segments with large CSAs; D: segment containing TCFA with intermediate narrowing of lumen area and stenosis of 30%.
visualized by OCT. The opacity of metal struts causes a
shadow that obscures deeper structures within the vessel
wall(18). Strut apposition to vessel wall was classified in
protruding, where the strut boundary is located above
the level of the luminal surface, and embedded, where
the strut boundary is below the level of the luminal surface(1). ISA-separation of the stent strut from the lumen
border by a distance greater than the width of the stent
strut according to each stent specification, plus a compensation factor of 20 µm to correct for “strut blooming”
44
according to some authors or resolution of the current
OCT technology to the others(19,20). In case of data analysis by independent core laboratory, a blinding of the
operator to the treatment assignment is usually performed. To allow this the OCT calculations are stored in
an integrated database system, and corrected for strut
(polymer) thickness of different stent types after the data
analysis is completed(21). A relatively high proportion of
malapposed struts after stent deployment were reported
in regions of stent overlap, and severe calcified lesions(22).
IVUS-OCT QUANTIFICATIONS: WHAT
TO
MEASURE
A
B
C
D
E
F
AND HOW
TO DO IT?
Figure 7. IVUS and OCT visualisation of stented coronary artery.
Corresponding IVUS (A-C) and OCT (D-F) cross-sections of a stented coronary artery in follow-up. OCT has a higher
capacity in evaluating the thin coverage (D vs A); both techniques are able to detect large degrees of stent malapposition but IVUS has the possibility to evaluate the EEM (B vs E); large amount of thrombus can be equally detected by
IVUS, and OCT when special enhansement procedures (blood removal by contrast medium) (C vs F).
Tissue protrusion is defined as a tissue prolapse between
stent struts extending inside a circular arc connecting
adjacent struts(23). During primary percutaneous coronary interventions (PCI) thrombus is easily visualized by
OCT, and can protrude in-between or overly stent struts.
The classification of the dissection is equal for IVUS,
and OCT, and is divided into: intimal, medial, adventitial. To quantify the severity of a dissection its depth, circumferential extent, length, size of residual lumen (CSA)
is quantified(3).
Although small degrees of dissection, tissue protrusion,
and incomplete stent apposition following stent deployment (24) are more frequent findings in OCT than in
IVUS the clinical significance of these non flow obstructing defects is not known (Figure 7). The quantification
or grading of these findings may be important to predict
lesion outcomes after PCI.
Differences in the chronology, and morphology of biological processes among species raised significant challenges to translating pre clinical results to humans(25), and
resulted in the need for the in vivo imaging surrogate
endpoints. Longitudinal studies (pre/post intervention
vs. follow-up) can potentially be used to evaluate the
response of the artery to treatment strategies. For these
studies, serial examinations are usually required by performing imaging at baseline, and in follow-up. The
OCT, and IVUS datasets are then registered using landmarks such as the stent edges, and side branches, distance
from coronary ostia if available(23). Following registration,
the data are then compared, using qualitative or quantitative measurements.
The optimal time for assessing stent coverage in followup is to be defined according to stent type. In BMS tissue
with homogeneous optical characteristics was observed
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A
B
C
D
N. 1• 2011
Figure 8. Automated contour detection algorithm for coronary OCT.
A: frame level calculation with determination of lumen and stent CSAs, diameter stenosis, and NIH areas in FU;
B: same frame strut level analysis that allows to determine NIH value at each strut. Once strut identified the standard
OCT software export to a exel file - “CSV file” and precise position of each strut, each strut level NIH, the arc between
each struts, and the number of analyzed struts per frame is available for reporting; C: frame level calculation of malapposition distance, and areas. D: same frame with calculation at “strut level”. The software allows reporting the number,
arc, and distance of malapposition.
six months after stent implantation, while during an
extended period of time (≥5 yrs), OCT presented signal
patterns of atherosclerotic progression(26). While analyzing vessel response to drug eluting or bioabsorbable
stents the presence/absence of polymer, its degradation
46
kinetics, and/or drug elution kinetics must be taken in
consideration in establishing the time point for imaging
follow-up(27,28).
The parameters that usually are reported in follow-up
intravascular imaging stent studies are: external elastic
IVUS-OCT QUANTIFICATIONS: WHAT
membrane (EEM), stent, and lumen cross-sectional area
(CSA), plaque plus media CSA (counted as EEM minus
TO
MEASURE
AND HOW
TO DO IT?
lumen), neointimal hyperplasia (NIH) (calculated as the
difference between stent, and lumen), percent NIH vol-
A
B
C
D
E
F
G
H
Figure 9. Stent vessel interaction post PCI.
A: edge strut malapposition (arrow); B: edge plaque dissection (arrow); C: intraluminal protrusion of soft plaque material (asterix); D: intraluminal protrusion of calcific plaque and stent underexpansion (arrow); E: embolization of plaque
matherial to stent struts at the ostium of side branch (arrow); F: 360° stent malapposition due to underexpansion;
G: stent underexpansion due to severe vessel wall pathology (Ca); H: stent overexpansion and media rupture (arrow).
A
B
C
D
E
Figure 10. Stent strut classification by intracoronary Optical Coherence Tomography (OCT).
A: covered embedded strut; B: protruding/covered strut; C: malapposed covered strut; D: well apposed uncovered
strut; E: malapposed strut uncovered struts.
A
B
C
D
Figure 11. Abnormal intraluminal tissue (AIT) Classification.
A: floating flap; B: related to neointimal proliferation; C: related to uncovered strut; D: related to malapposed strut.
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ume obstruction (computed as NIH divided by stent
volume). The detection of late malapposition requires
the comparison of post-intervention, and follow-up
images. Stent malapposition (defined as blood speckle
behind stent struts) is categorized as persistent -visible at
post-procedure, and follow-up, resolved -visible only at
post-procedure, and late acquired -visible only at followup. ISA due to positive vessel remodeling was demonstrated as a substrate for DES late stent thrombosis
(LST), but no data on post intervention IVUS were
available in the study(29). By using serial OCT, Ozaki
demonstrated that ISA observed at follow-up in SES is
more frequently derived from post intervention persistent ISA without neointimal growth, rather than acquired
ISA due to vascular remodeling(30).
Unlike BMS which develop circumferential coverage easily measured by IVUS, and angiography, the smaller
amount of neointimal growth after DES implantation is
largely under the limit of resolution of these imaging
techniques(31). Due to higher resolution OCT allows the
so called “strut level” analysis. A semi automated stent
contour algorithm applies 360 radial chords for detailed
quantification of NIH thickness at every degree of the
A
N. 1• 2011
cross section (Figure 8). Its ability to appropriately identify uncovered, and covered stent struts was demonstrated
by Murata et al. based on analysis of 3,000 struts(32). Close
degree of correlation between OCT, and scanning electron microscopy (SEM) in detection of strut coverage was
recently reported(33). This capability has been used to evaluate the response to stent implantation in series of
prospective randomized clinical trials(27,28). Struts are normally classified in types based upon the coverage value of
strut-intimal thickness (SIT): struts covered by tissue have
positive SIT values, while uncovered or malapposed struts
have negative SIT. Depending on tissure coverage, and
apposition we classified the struts in four types: covered
by tissue where the strut boundary is below the luminal
surface are defined as embedded covered struts; those covered by tissue where the boundary is above the lumen are
defined as protruding covered struts; those not covered by
tissue but abutting the vessel wall are classified as uncovered apposed struts; and those not covered by tissue, and
not abutting the vessel wall are classified as uncovered,
and malapposed struts(19,22) (Figure 10). The number of
struts without coverage is counted for each frame analyzed, and the total number, and percentage struts, and
B
Figure 12. Tissue coverage in follow-up.
A: tissue with non homogeneous characteristics of the backscattering, a clear delimitation can be seen between the
light characteristics (not homogeneous and with light attenuation) of the tissue covering the stent, and the tissue of the
vessel behind stent struts ( homogeneous, and with more bright appearance); B: no difference in optic characteristics
between the tissue covering stent struts, and tissue behind stent strut with bright, and homogeneous apperarance.
48
IVUS-OCT QUANTIFICATIONS: WHAT
frames with uncovered struts are recorded. The stent
length lacking neointimal coverage or having malapposed
struts is counted as maximum length (in consecutive
frames), and total length (in cumulative frames). The
length of the phenomenon in mm is calculated by the
pullback rate (mm/s) times the frame rate (s)(1). Derived
from direct measurements indexes regarding uniformity
of stent coverage can be calculated: neointimal unevenness score (NUS)-calculated by dividing the maximum
neointimal thickness to the average neointimal thickness
in each analyzed frame, and RUTTS-proportion of
frames with >30% uncovered struts per frame. These
indexes have been associated to the presence of subclinical
thrombus (NUS), and to late stent thrombosis in preclinical studies (RUTTS)(34,35). Measurements for strut apposition, and strut coverage are highly reproducible at the
core laboratory (36).
DES OCT assessment at different time points demonstrated a significant rate of uncovered stent struts at early,
and late follow-up, ranging from 15% at 3 months to
5% at 2 years, and high degree of heterogeneity. Despite
the fact that neointimal coverage in DES may progress
overtime, previous long-term OCT studies have shown
that uncovered stent struts decreased but not disappear
from 6 to 12 months(37).
The distinction between fibrin clot, and neointimal
hyperplasia is not always possible. A more descriptive
term of abnormal intraluminal tissue (AIT) defined as
TO
MEASURE
AND HOW
TO DO IT?
any irregular mass protruding beyond the stent strut into
the lumen was adopted by us for qualitative assessment.
In order to avoid misclassification of small image artifacts, only AIT >0.25 mm diameter should be included.
AIT can be further classified in 4 categories according to
its relationship with strut coverage, apposition, presence
of underlying NIH, and it’s amount (27) (Figure 11). The
described frequency of this phenomenon is much higher
than the reported incidence of clinical stent thrombosis.
Several OCT studies shown that the presence of subclinical OCT evidence of intracoronary thrombus has not
been associated with thrombotic clinical events(34).
Neither IVUS nor OCT has tissue characterization software regarding stent coverage since stent struts represent
an important artifact. Even with 10 fold higher resolution
OCT is not able to discriminate between the natures of
tissue coverage, be it fibrin, endothelium, thrombus or
neointima. The significance of the tissue characteristics
such as reflectivity, and texture is unknown, and densitometry analysis may be a promising method to overcome
this limitation(33) (Figure 12). The relationship between all
these OCT morphometric findings, and subsequent clinical events has to be determined in a larger number of
patients, and with additional years of clinical follow-up.
The routine clinical use of OCT will require further clinical trials to validate the technology, establish standard
definitions/measurements, and to test its safety, and utility in improving clinical outcomes.
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