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Perfusion Patterns in Patients with Chronic Limb-Threatening Ischemia versus Control Patients Using Near-Infrared Fluorescence Imaging with Indocyanine Green

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In assessing the severity of lower extremity arterial disease (LEAD), physicians rely on clinical judgements supported by conventional measurements of macrovascular blood flow. However, current diagnostic techniques provide no information about regional tissue perfusion and are of limited value in patients with chronic limb-threatening ischemia (CLTI). Near-infrared (NIR) fluorescence imaging using indocyanine green (ICG) has been used extensively in perfusion studies and is a possible modality for tissue perfusion measurement in patients with CLTI. In this prospective cohort study, ICG NIR fluorescence imaging was performed in patients with CLTI and control patients using the Quest Spectrum Platform® (Middenmeer, The Netherlands). The time–intensity curves were analyzed using the Quest Research Framework. Fourteen parameters were extracted. Successful ICG NIR fluorescence imaging was performed in 19 patients with CLTI and in 16 control patients. The time to maximum intensity (seconds) was lower for CLTI patients (90.5 vs. 143.3, p = 0.002). For the inflow parameters, the maximum slope, the normalized maximum slope and the ingress rate were all significantly higher in the CLTI group. The inflow parameters observed in patients with CLTI were superior to the control group. Possible explanations for the increased inflow include damage to the regulatory mechanisms of the microcirculation, arterial stiffness, and transcapillary leakage.
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biomedicines
Article
Perfusion Patterns in Patients with Chronic Limb-Threatening
Ischemia versus Control Patients Using Near-Infrared
Fluorescence Imaging with Indocyanine Green
Pim Van Den Hoven 1, Lauren N. Goncalves 1, Paulus H. A. Quax 1, Catharina S. P. Van Rijswijk 2,
Jan Van Schaik 1, Abbey Schepers 1, Alexander L. Vahrmeijer 1, Jaap F. Hamming 1
and Joost R. Van Der Vorst 1, *


Citation: Van Den Hoven, P.;
Goncalves, L.N.; Quax, P.H.A.;
Van Rijswijk, C.S.P.; Van Schaik, J.;
Schepers, A.; Vahrmeijer, A.L.;
Hamming, J.F.; Van Der Vorst, J.R.
Perfusion Patterns in Patients with
Chronic Limb-Threatening Ischemia
versus Control Patients Using
Near-Infrared Fluorescence Imaging
with Indocyanine Green. Biomedicines
2021,9, 1417. https://doi.org/
10.3390/biomedicines9101417
Academic Editor: Manfredi Tesauro
Received: 14 September 2021
Accepted: 6 October 2021
Published: 9 October 2021
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Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1
Department of Surgery, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, The Netherlands;
p.van_den_hoven@lumc.nl (P.V.D.H.); laurengoncalves9@gmail.com (L.N.G.); p.h.a.quax@lumc.nl (P.H.A.Q.);
j.van_schaik@lumc.nl (J.V.S.); a.schepers@lumc.nl (A.S.); a.l.vahrmeijer@lumc.nl (A.L.V.);
j.f.hamming@lumc.nl (J.F.H.)
2
Department of Radiology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, The Netherlands;
c.s.p.van_rijswijk@lumc.nl
*Correspondence: j.r.van_der_vorst@lumc.nl; Tel.: +31-71-529-9143
Abstract:
In assessing the severity of lower extremity arterial disease (LEAD), physicians rely
on clinical judgements supported by conventional measurements of macrovascular blood flow.
However, current diagnostic techniques provide no information about regional tissue perfusion
and are of limited value in patients with chronic limb-threatening ischemia (CLTI). Near-infrared
(NIR) fluorescence imaging using indocyanine green (ICG) has been used extensively in perfusion
studies and is a possible modality for tissue perfusion measurement in patients with CLTI. In this
prospective cohort study, ICG NIR fluorescence imaging was performed in patients with CLTI and
control patients using the Quest Spectrum Platform
®
(Middenmeer, The Netherlands). The time–
intensity curves were analyzed using the Quest Research Framework. Fourteen parameters were
extracted. Successful ICG NIR fluorescence imaging was performed in 19 patients with CLTI and in
16 control patients. The time to maximum intensity (seconds) was lower for CLTI patients (90.5 vs.
143.3, p= 0.002). For the inflow parameters, the maximum slope, the normalized maximum slope
and the ingress rate were all significantly higher in the CLTI group. The inflow parameters observed
in patients with CLTI were superior to the control group. Possible explanations for the increased
inflow include damage to the regulatory mechanisms of the microcirculation, arterial stiffness, and
transcapillary leakage.
Keywords:
near-infrared; fluorescence imaging; indocyanine green; chronic limb-threatening is-
chemia; peripheral artery disease; perfusion
1. Introduction
Lower-extremity arterial disease (LEAD) is most often caused by atherosclerosis [
1
,
2
].
Subsequent hemodynamic alterations leading to hypoxia can trigger a cascade of events
leading to macro- and microvascular changes in the affected limb [
3
]. In the most advanced
stage, chronic limb-threatening ischemia (CLTI), blood supply to the lower extremity is
insufficient to meet metabolic needs [
2
,
4
]. For these patients, a common finding during
physical examination of the lower extremities is the appearance of “dependent rubor” or
“blanching”, which is presumably caused by dysfunction of the venoarteriolar reflex [
5
]. In
assessing the severity of LEAD, physicians often rely on their clinical judgements of the ex-
tremities. The diagnosis is confirmed using conventional measurements of macrovascular
blood flow including the ankle-brachial index (ABI), toe pressure measurement, computed
tomography (CT) angiography, magnetic resonance angiography, and digital subtraction
Biomedicines 2021,9, 1417. https://doi.org/10.3390/biomedicines9101417 https://www.mdpi.com/journal/biomedicines
Biomedicines 2021,9, 1417 2 of 9
angiography. However, these techniques provide no information about regional tissue
perfusion and have been shown to be of limited value in patients with CLTI [
6
]. New
emerging methods for the assessment of regional tissue perfusion include dynamic volume
perfusion CT, laser speckle imaging (LSI), and near-infrared (NIR) fluorescence imaging us-
ing indocyanine green (ICG) [
7
9
]. ICG NIR fluorescence imaging has been used in various
medical fields for the assessment of tissue perfusion, including cardiac and reconstructive
surgery [
10
,
11
]. This imaging technique measures fluorescence in the NIR light spectrum
(700–1000 nm), which is characterized by low tissue autofluorescence and deep tissue
penetration [
12
]. Upon the intravenous administration of ICG, which has a peak emission
of 814 nm, the camera measures the NIR fluorescence intensity over time. The feasibility
of ICG as a fluorophore in perfusion assessment can be explained by its confinement to
the intravascular compartment due to its ability to bind to plasma proteins [
13
]. For skin
perfusion assessment, ICG NIR fluorescence imaging is currently used intraoperatively in
reconstructive surgery to predict flap viability [
14
]. For patients with LEAD, similar results
were seen in predicting skin necrosis following amputation surgery [
15
]. However, these
findings rely on qualitative analyses, meaning that the observer subjectively grades the
visualized NIR fluorescence intensity. To quantify and grade of regional tissue perfusion,
a better understanding of the different perfusion patterns as observed with ICG NIR flu-
orescence imaging is needed. Several studies have been performed to quantify ICG NIR
fluorescence imaging between patients with different stages of LEAD [
16
18
]. However,
inconsistency is seen between stages, and it is unclear whether advanced stages of LEAD
alter the in- and outflow of ICG [
16
]. Furthermore, there is limited information regarding
the perfusion patterns of ICG NIR fluorescence imaging in control patients. Therefore, as a
first step in the quantification of tissue perfusion using ICG NIR fluorescence imaging, the
aim of this study was to analyze the perfusion patterns seen in patients with CLTI and to
compare these to non-LEAD control patients.
2. Materials and Methods
This prospective cohort study was approved by the Medical Research and Ethics
Committee of the Leiden University Medical Center and was registered in the Dutch
Trial Register with number NL7531. Patients with CLTI classified according to the global
vascular guidelines on the management of CLTI, were included [
4
]. These were patients
who had been diagnosed with either Fontaine stage 3 or stage 4 LEAD. The control group
consisted of patients who had undergone intravenous ICG administration prior to liver
metastasectomy. Patients were included from December 2018 until April 2021 in a single
academic hospital in the Netherlands. Exclusion criteria were allergy or hypersensitivity to
sodium iodide, iodide, or ICG; known hyperthyroidism; or autonomous thyroid adenoma,
pregnancy, kidney failure (eGFR < 45) and/or severe liver failure. Informed consent
was obtained from all patients. ABI and toe pressure measurements were performed in
all patients. As an additional measurement for patients with CLTI, duplex ultrasound
measurements of the feet were performed, and the highest acceleration in either the dorsalis
pedis artery or the posterior tibial artery was reported. These acceleration measurements
are described in detail in an earlier study by Brouwers et al. and were performed to
assess the severity of arterial stenosis [
19
]. The Quest Spectrum Platform
®
(Quest Medical
Imaging, Middenmeer, The Netherlands) was used to perform ICG NIR fluorescence
imaging (Figure 1). This imaging system is capable of measuring both visible light as
well as the NIR signal of ICG. Patients with CLTI were administered an intravenous bolus
injection of 0.1 mg/kg ICG (VERDYE 25 mg, Diagnostic Green GmbH, Aschheim-Dornach,
Germany) using a peripheral venous line in the cubital fossa or on the dorsum of the hand.
Patients in the control group were administered a bolus injection of 10 mg ICG according
to local hospital guidelines.
Biomedicines 2021,9, 1417 3 of 9
Biomedicines 2021, 9, x FOR PEER REVIEW 3 of 10
Figure 1. ICG NIR fluorescence imaging setup.
Following the administration of ICG, the NIR fluorescence intensity in both feet was
recorded for 10 min (Figure 2). Measurements were performed on patients in a supine
position following a rest period of at least 10 min in a room cleared of ambient light. The
camera was placed perpendicular to the dorsum of both feet at a distance of 50cm.
Figure 2. ICG NIR fluorescence imaging in a control patient showing the visual (a), merged (b), and
NIR fluorescence (c) output in both feet.
The NIR fluorescence videos were analyzed using the Quest Research Framework®
(Version 4.1, Quest Medical Imaging, Middenmeer, the Netherlands). The whole foot was
selected as the region of interest (ROI). Upon the selection of the ROI, the software creates
a timeintensity curve of the measured intensity in arbitrary units (a.u.). A tracker was
used to ensure that the ROI was synchronized with leg movement. Fourteen parameters
were extracted from these curves, an explanation of which is given in Figure 3. The ingress
rate was defined as the intensity increase per second from baseline to maximum intensity.
Figure 1. ICG NIR fluorescence imaging setup.
Following the administration of ICG, the NIR fluorescence intensity in both feet was
recorded for 10 min (Figure 2). Measurements were performed on patients in a supine
position following a rest period of at least 10 min in a room cleared of ambient light. The
camera was placed perpendicular to the dorsum of both feet at a distance of 50 cm.
Biomedicines 2021, 9, x FOR PEER REVIEW 3 of 10
Figure 1. ICG NIR fluorescence imaging setup.
Following the administration of ICG, the NIR fluorescence intensity in both feet was
recorded for 10 min (Figure 2). Measurements were performed on patients in a supine
position following a rest period of at least 10 min in a room cleared of ambient light. The
camera was placed perpendicular to the dorsum of both feet at a distance of 50cm.
Figure 2. ICG NIR fluorescence imaging in a control patient showing the visual (a), merged (b), and
NIR fluorescence (c) output in both feet.
The NIR fluorescence videos were analyzed using the Quest Research Framework®
(Version 4.1, Quest Medical Imaging, Middenmeer, the Netherlands). The whole foot was
selected as the region of interest (ROI). Upon the selection of the ROI, the software creates
a timeintensity curve of the measured intensity in arbitrary units (a.u.). A tracker was
used to ensure that the ROI was synchronized with leg movement. Fourteen parameters
were extracted from these curves, an explanation of which is given in Figure 3. The ingress
rate was defined as the intensity increase per second from baseline to maximum intensity.
Figure 2.
ICG NIR fluorescence imaging in a control patient showing the visual (
a
), merged (
b
), and NIR fluorescence
(c) output in both feet.
The NIR fluorescence videos were analyzed using the Quest Research Framework
®
(Version 4.1, Quest Medical Imaging, Middenmeer, the Netherlands). The whole foot was
selected as the region of interest (ROI). Upon the selection of the ROI, the software creates
a time–intensity curve of the measured intensity in arbitrary units (a.u.). A tracker was
used to ensure that the ROI was synchronized with leg movement. Fourteen parameters
were extracted from these curves, an explanation of which is given in Figure 3. The ingress
rate was defined as the intensity increase per second from baseline to maximum intensity.
The Tmax was measured starting at the point of a 10% intensity increase at baseline. The
time–intensity curves were also analyzed after normalization for maximum intensity. The
curves extracted from these curves were, in percentage per second, the maximum slope
Biomedicines 2021,9, 1417 4 of 9
ingress and the maximum slope egress. The starting time was defined as an increase of
one arbitrary unit for the intensity curves and 1% for the normalized curves. Statistical
analyses were performed using IBM SPSS Statistics 25 (IBM Corp. Released 2017 and IBM
SPSS Statistics for Windows, Version 25.0. IBM Corp., Armonk, NY, USA). Parameters were
compared using the Mann–Whitney U test.
Biomedicines 2021, 9, x FOR PEER REVIEW 4 of 10
The Tmax was measured starting at the point of a 10% intensity increase at baseline. The
timeintensity curves were also analyzed after normalization for maximum intensity. The
curves extracted from these curves were, in percentage per second, the maximum slope
ingress and the maximum slope egress. The starting time was defined as an increase of
one arbitrary unit for the intensity curves and 1% for the normalized curves. Statistical
analyses were performed using IBM SPSS Statistics 25 (IBM Corp. Released 2017 and IBM
SPSS Statistics for Windows, Version 25.0. IBM Corp., Armonk, NY, USA). Parameters
were compared using the MannWhitney U test.
Figure 3. Timeintensity curve with extracted parameters. Abbreviations: a.u, arbitrary unit; AUC,
area under the curve.
3. Results
3.1. Patient Characteristics
Successful ICG NIR fluorescence imaging measurements were performed in 35 pa-
tients. Nineteen patients presented with LEAD, from whom 28 limbs were classified as
CLTI. The control group consisted of 16 patients with a total of 32 limbs. The characteris-
tics for each group are displayed in Table 1. For the CLTI group, 10 limbs were classified
as Fontaine stage 4. Compared to the control group, patients in the CLTI group were more
likely to present with diabetes, hypertension, and smoking. The mean ABI in the CLTI
group was 0.77 versus 1.11 in the control group. The ABI in the CLTI group was not meas-
urable in 9 out of 28 limbs. The acceleration measured on duplex ultrasonography was
measured in 22 CLTI limbs with a mean of 0.93 m/s2.
Figure 3.
Time–intensity curve with extracted parameters. Abbreviations: a.u, arbitrary unit; AUC,
area under the curve.
3. Results
3.1. Patient Characteristics
Successful ICG NIR fluorescence imaging measurements were performed in
35 patients. Nineteen patients presented with LEAD, from whom 28 limbs were clas-
sified as CLTI. The control group consisted of 16 patients with a total of 32 limbs. The
characteristics for each group are displayed in Table 1. For the CLTI group, 10 limbs were
classified as Fontaine stage 4. Compared to the control group, patients in the CLTI group
were more likely to present with diabetes, hypertension, and smoking. The mean ABI in
the CLTI group was 0.77 versus 1.11 in the control group. The ABI in the CLTI group was
not measurable in 9 out of 28 limbs. The acceleration measured on duplex ultrasonography
was measured in 22 CLTI limbs with a mean of 0.93 m/s2.
Table 1. Patient characteristics.
CLTI Controls
N (limbs) 19 (28) 16 (32)
Age (SD) 70.4 (7.5) 66.6 (12.3)
Diabetes Mellitus (%) 9 (47.4) 3 (18.8)
Hypertension (%) 15 (78.9) 7 (43.8)
Active smoking (%) 5 (26.3) 1 (6.3)
Fontaine stage limbs, n (%)
318 (64.3) -
410 (35.7) -
Mean ABI (SD) 0.77 (0.34) 1.11 (0.10)
Mean TP (SD) 44 (25) 106 (22)
Acceleration (SD) 0.93 (1.23) -
Abbreviations: CLTI, chronic limb-threatening ischemia; SD, standard deviation; ABI, ankle-brachial index; TP,
Toe Pressure.
Biomedicines 2021,9, 1417 5 of 9
3.2. ICG NIR Fluorescence Parameters
The results of ICG NIR fluorescence imaging for the 14 extracted parameters are
displayed in Table 2.
Table 2. ICG NIR fluorescence imaging parameters.
Parameter CLTI Controls p-Value
Maximum intensity (SD) 37.9 (14.4) 25.8 (10.8) 0.000
Maximum slope ingress (SD) 2.0 (2.5) 0.6 (0.4) 0.000
Normalized maximum slope (SD) 4.2 (3.1) 2.4 (1.2) 0.000
Ingress rate (SD) 1.0 (1.7) 0.2 (0.2) 0.000
AUC ingress 10 (SD) 47.4 (2.2) 48.8 (3.3) 0.073
AUC ingress (SD) 71.4 (6.3) 70.6 (3.8) 0.213
Tmax (SD) 90.5 (53.4) 143.3 (64.5) 0.002
Maximum slope egress (SD) 0.5 (0.7) 0.2 (0.1) 0.005
Normalized maximum slope egress (SD)
1.0 (0.9) 0.8 (0.3) 0.733
AUC egress 60 (SD) 92.8 (10.0) 96.7 (1.8) 0.113
AUC egress 120 (SD) 87.9 (11.9) 92.8 (2.3) 0.127
AUC egress 180 (SD) 82.9 (12.9) 88.3 (4.3) 0.164
AUC egress 240 (SD) 78.2 (13.3) 83.8 (5.4) 0.168
AUC egress 300 (SD) 73.7 (13.5) 73.3 (6.0) 0.271
Abbreviations: SD, standard deviation; CLTI, chronic limb-threatening ischemia; AUC, area under the curve.
The mean maximum intensity was significantly lower in the control group (37.9 vs.
25.8 a.u., p< 0.001). Furthermore, the time to maximum intensity (i.e., Tmax) was reached
earlier in the CLTI group (90.5 vs. 143.3 s, p= 0.002). When taking a closer look at the
inflow parameters, the maximum slope, the normalized maximum slope, and the ingress
rate were all significantly higher in the CLTI group (2.0 vs. 0.6 a.u./s, p< 0.001; 4.2 vs.
2.4%/s, p< 0.001; 1.0 vs. 0.2 a.u./s, p< 0.001). For the outflow parameters, a significant
difference was seen for the maximum slope egress, which was higher in the control group
(0.5 vs. 0.2 a.u./s, p= 0.005). No significant difference was observed for the normalized
maximum slope egress (1.0 vs. 0.8%/s, p= 0.733). A comparison of the AUC for different
intervals following the Tmax displayed no significant difference between the CLTI and
control the group.
3.3. Time–Intensity Curves
The time–intensity curves for the control group and CLTI group are displayed in
Figure 4. Results for the absolute intensity– and the normalized time–intensity curves for
both groups are displayed.
Time–intensity curves displaying the absolute intensity change over time show an
overall higher absolute intensity for the CLTI group. Following a steep incline in the inten-
sity increase for the CLTI group, the outflow seems comparable with the control patients.
The absolute time–intensity curves show a widespread distribution, especially in the CLTI
group. In this group, the maximum slope ingress (2.0%/s) has a standard deviation of
2.5 (Table 2). For the AUC egress parameters, standard deviations between 10.0% and
13.5% were observed. When normalizing these time–intensity curves for maximum inten-
sity, both groups display a narrower distribution in all parameters. For the normalized
maximum slope in the CLTI group (4.2%/s), a standard deviation of 3.1% was observed.
When looking at the AUC egress parameters, the standard deviations had a distribution of
1.8 to 6.1%.
Biomedicines 2021,9, 1417 6 of 9
Biomedicines 2021, 9, x FOR PEER REVIEW 6 of 10
3.3. TimeIntensity Curves
The timeintensity curves for the control group and CLTI group are displayed in
Figure 4. Results for the absolute intensity and the normalized timeintensity curves for
both groups are displayed.
Figure 4. Absolute intensity and normalized timeintensity curves for the CLTI group and control
group: (a) Absolute timeintensity curve for the CLTI group; (b) absolute timeintensity curve for
control group; (c) normalized timeintensity curve for the CLTI group; (d) normalized timeinten-
sity curve for the control group.
Timeintensity curves displaying the absolute intensity change over time show an
overall higher absolute intensity for the CLTI group. Following a steep incline in the in-
tensity increase for the CLTI group, the outflow seems comparable with the control pa-
tients. The absolute timeintensity curves show a widespread distribution, especially in
the CLTI group. In this group, the maximum slope ingress (2.0%/s) has a standard devia-
tion of 2.5 (Table 2). For the AUC egress parameters, standard deviations between 10.0%
and 13.5% were observed. When normalizing these timeintensity curves for maximum
intensity, both groups display a narrower distribution in all parameters. For the normal-
ized maximum slope in the CLTI group (4.2%/s), a standard deviation of 3.1% was ob-
served. When looking at the AUC egress parameters, the standard deviations had a dis-
tribution of 1.8 to 6.1%.
Figure 4.
Absolute intensity– and normalized time–intensity curves for the CLTI group and control group: (
a
) Absolute
time–intensity curve for the CLTI group; (
b
) absolute time–intensity curve for control group; (
c
) normalized time–intensity
curve for the CLTI group; (d) normalized time–intensity curve for the control group.
4. Discussion
This study demonstrates the different perfusion patterns as seen on ICG NIR fluores-
cence imaging between patients with CLTI and control patients. Interestingly, most of the
inflow parameters observed in patients with CLTI were higher compared to the control
group. Concerning the outflow of ICG, however, no significant differences were observed.
Furthermore, there was a widespread distribution of measured intensity over time in both
groups. There are several earlier studies reporting the use of ICG NIR fluorescence imaging
for perfusion assessment in patients with LEAD as well as control patients [
7
,
16
,
18
,
20
25
].
In these studies, an abundance of parameters has been examined, which have been com-
pared to varying diagnosis measurements, including ABI, TP, and transcutaneous oxygen
pressure measurements. Patterns of foot perfusion in non-LEAD control patients were
analyzed in one study [
18
]. Regarding inflow parameters, Igari et al. found a prolonged
time to maximum intensity for patients with LEAD compared to control patients [
18
].
No statistical differences were seen for the maximum intensity and T1/2 between the
two groups. The differences in the perfusion patterns amongst various stages of LEAD
were analyzed in several studies. When comparing inflow parameters between different
stages of LEAD, Terasaki et al. observed a prolonged T1/2 for Fontaine stage 3 compared
to stage 2; however, this was not observed for stage 4. Regarding outflow, their study
Biomedicines 2021,9, 1417 7 of 9
concluded that a percentage decrease of 90% in the maximum measured intensity was the
most accurate parameter in diagnosing LEAD. For patients with CLTI, Venermo et al. found
an increase in the inflow, the PDE10, to be strongly correlated to the transcutaneous oxygen
pressure in patients with diabetes mellitus [
23
]. The same parameter was moderately
correlated in patients without diabetes mellitus, suggesting a difference in the perfusion
patterns between these groups.
According to the findings in these earlier studies and the results found in this study,
the hypothesis that LEAD progression leads to the diminished in- and outflow of ICG is
debatable. Several mechanisms might contribute to the increased inflow of ICG seen in
patients with CLTI in this study. First, ICG NIR fluorescence imaging is able to penetrate
tissue to a depth of several millimeters [
26
]. Therefore, this imaging technique mainly
visualizes the skin with superficial vessels and the superior part of the subcutaneous tissue,
i.e., the microcirculation. The nutritional capillaries of this microcirculation in the foot
account for approximately 15% of total foot blood flow, which is regulated by various
mechanisms, including arteriovenous (AV) shunts [
27
]. For patients with LEAD and CLTI
in particular, this diminished blood flow can lead to hypoxia altering microcirculatory
function and can damage these regulatory mechanisms [
3
,
5
]. The dysfunction of AV shunts
might lead to a relative increase of the blood flow to the skin in patients with CLTI, which
also explains the “dependent rubor” seen in this group. Secondly, atherosclerosis leads to
stiffness of the arterial wall, which is a common finding in patients with CLTI and that can to
an increased pulse wave velocity [
28
]. In a healthy arterial system, blood flow is gradually
transmitted to the peripheral tissue due to the compliance of the vessel wall [
29
]. This
might explain the more gradual perfusion pattern seen in the control group. Furthermore,
damage to the microcirculation in CLTI leads to transcapillary leakage, which might further
enhance the measured NIR fluorescence intensity. Although a higher dosage of ICG was
administered in the majority of patients in the control group, it is unlikely that this would
have influenced the perfusion pattern. Moreover, an overall lower absolute intensity was
seen in this group. To confirm these findings on increased inflow, a larger cohort of patients
with CLTI is needed. Therefore, due to the small sample size, the conclusions in this study
must be perceived as a proof of concept. Besides the small cohort size of patients with
CLTI, this study is limited by the heterogenous aspect of the CLTI population. In particular,
for patients with diabetes mellitus, skin perfusion follows a different pattern than LEAD
Fontaine stage 4 patients without diabetes mellitus. Therefore, future studies should
distinguish between CLTI patients with and without diabetes mellitus. Furthermore, the
control group used in the present study were patients scheduled for liver metastasectomy
and therefore might not resemble healthy volunteers in terms of comorbidities. Although
LEAD was excluded based on medical history and ABI measurements, there could be
differences in the perfusion patterns with healthy volunteers. Therefore, in future patient
selection and to further understand perfusion patterns, healthy volunteers should be taken
into account as well. With regard to the NIR fluorescence intensity analysis, the use of
normalized time–intensity curves seems rational since intensity-related parameters are
prone to multiple influencing factors, including camera distance and ICG dosage [
30
,
31
].
This normalization minimizes the effect of these influencing factors on the measured
intensity and contributes to a narrower distribution, as seen in the time–intensity curves
in this study. The use of this normalization might be of use in future research on the
quantification of tissue perfusion with ICG NIR fluorescence imaging.
5. Conclusions
An increase in the inflow parameters was observed with ICG NIR fluorescence imag-
ing in patients with CLTI compared to control patients. This can possibly be explained by
damage to the regulatory mechanisms of microcirculation and arterial stiffness. In order to
provide cut-off values for adequate perfusion, more research in lager cohorts is needed on
the in- and outflow patterns of control patients and various stages of LEAD.
Biomedicines 2021,9, 1417 8 of 9
Author Contributions:
Conceptualization, P.V.D.H., L.N.G., P.H.A.Q., C.S.P.V.R., J.V.S., A.S., A.L.V.,
J.F.H. and J.R.V.D.V.; methodology, P.V.D.H., L.N.G., P.H.A.Q., C.S.P.V.R., J.V.S., A.S., A.L.V., J.F.H. and
J.R.V.D.V.; software, P.V.D.H., L.N.G. and J.R.V.D.V.; validation, P.V.D.H., L.N.G., J.F.H. and J.R.V.D.V.;
formal analysis, P.V.D.H., L.N.G. and J.R.V.D.V.; investigation, P.V.D.H., L.N.G., P.H.A.Q., C.S.P.V.R.,
J.V.S., A.S., A.L.V., J.F.H. and J.R.V.D.V.; resources, P.H.A.Q., C.S.P.V.R., J.V.S., A.S., A.L.V., J.F.H. and
J.R.V.D.V.; data curation, P.V.D.H., L.N.G. and J.R.V.D.V.; writing—original draft preparation, P.V.D.H.,
L.N.G. and J.R.V.D.V.; writing—review and editing, P.V.D.H., L.N.G., P.H.A.Q., C.S.P.V.R., J.V.S., A.S.,
A.L.V., J.F.H. and J.R.V.D.V.; visualization, P.V.D.H., L.N.G., J.F.H. and J.R.V.D.V.; supervision, J.V.S.,
A.S., A.L.V., J.F.H. and J.R.V.D.V.; project administration, P.V.D.H., L.N.G. and J.R.V.D.V.; funding
acquisition, A.L.V., J.F.H. and J.R.V.D.V. All authors have read and agreed to the published version of
the manuscript.
Funding:
The collaboration project is co-funded by the PPS Allowance made available by Health~Holland,
Top Sector Life Sciences & Health, to stimulate public-private partnerships and by the H2020 project
Phootonics grant agreement ID: 871908.
Institutional Review Board Statement:
The study was conducted according to the guidelines of the
Declaration of Helsinki and was approved by the Institutional Review Board (or Ethics Committee)
of the Leiden University Medical Center (NL65455.058.18, 12 December 2018).
Informed Consent Statement:
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement:
The data presented in this study are available upon request from the
corresponding author.
Conflicts of Interest: The authors declare no conflict of interest.
References
1.
Weitz, J.I.; Byrne, J.; Clagett, G.P.; Farkouh, M.E.; Porter, J.M.; Sackett, D.L.; Strandness, D.E., Jr.; Taylor, L.M. Diagnosis and
treatment of chronic arterial insufficiency of the lower extremities: A critical review. Circulation
1996
,94, 3026–3049. [CrossRef]
[PubMed]
2.
Aboyans, V.; Ricco, J.B.; Bartelink, M.E.L.; Bjorck, M.; Brodmann, M.; Cohnert, T.; Collet, J.P.; Czerny, M.; De Carlo, M.; Debusa, S.;
et al. 2017 ESC Guidelines on the Diagnosis and Treatment of Peripheral Arterial Diseases, in collaboration with the European
Society for Vascular Surgery (ESVS). Rev. Esp. Cardiol. 2018,71, 111. [CrossRef] [PubMed]
3.
Krishna, S.M.; Moxon, J.V.; Golledge, J. A review of the pathophysiology and potential biomarkers for peripheral artery disease.
Int. J. Mol. Sci. 2015,16, 11294–11322. [CrossRef]
4.
Conte, M.S.; Bradbury, A.W.; Kolh, P.; White, J.V.; Dick, F.; Fitridge, R.; Mills, J.L.; Ricco, J.B.; Suresh, K.R.; Murad, M.H.; et al.
Global vascular guidelines on the management of chronic limb-threatening ischemia. J. Vasc. Surg.
2019
,69, 3S–125S.e40.
[CrossRef] [PubMed]
5.
Abularrage, C.J.; Sidawy, A.N.; Aidinian, G.; Singh, N.; Weiswasser, J.M.; Arora, S. Evaluation of the microcirculation in vascular
disease. J. Vasc. Surg. 2005,42, 574–581. [CrossRef] [PubMed]
6.
Misra, S.; Shishehbor, M.H.; Takahashi, E.A.; Aronow, H.D.; Brewster, L.P.; Bunte, M.C.; Kim, E.S.H.; Lindner, J.R.; Rich, K.;
American Heart Association Council on Peripheral Vascular Disease; et al. Perfusion Assessment in Critical Limb Ischemia:
Principles for Understanding and the Development of Evidence and Evaluation of Devices: A Scientific Statement From the
American Heart Association. Circulation 2019,140, e657–e672. [CrossRef]
7.
van den Hoven, P.; Ooms, S.; van Manen, L.; van der Bogt, K.E.A.; van Schaik, J.; Hamming, J.F.; Vahrmeijer, A.L.; van der Vorst, J.R.;
Mieog, J.S.D. A systematic review of the use of near-infrared fluorescence imaging in patients with peripheral artery disease.
J. Vasc. Surg. 2019,70, 286–297.e1. [CrossRef]
8.
Kikuchi, S.; Miyake, K.; Tada, Y.; Uchida, D.; Koya, A.; Saito, Y.; Ohura, T.; Azuma, N. Laser speckle flowgraphy can also be used
to show dynamic changes in the blood flow of the skin of the foot after surgical revascularization. Vascular
2019
,27, 242–251.
[CrossRef]
9.
Cindil, E.; Erbas, G.; Akkan, K.; Cerit, M.N.; Sendur, H.N.; Zor, M.H.; Ilgit, E. Dynamic Volume Perfusion CT of the Foot in
Critical Limb Ischemia: Response to Percutaneous Revascularization. AJR Am. J. Roentgenol. 2020,214, 1398–1408. [CrossRef]
10.
Driessen, C.; Arnardottir, T.H.; Lorenzo, A.R.; Mani, M.R. How should indocyanine green dye angiography be assessed to best
predict mastectomy skin flap necrosis? A systematic review. J. Plast. Reconstr. Aesthet. Surg. 2020,73, 1031–1042. [CrossRef]
11.
Dupree, A.; Riess, H.; Detter, C.; Debus, E.S.; Wipper, S.H. Utilization of indocynanine green fluorescent imaging (ICG-FI) for the
assessment of microperfusion in vascular medicine. Innov. Surg. Sci. 2018,3, 193–201. [CrossRef] [PubMed]
12.
Vahrmeijer, A.L.; Hutteman, M.; van der Vorst, J.R.; van de Velde, C.J.; Frangioni, J.V. Image-guided cancer surgery using
near-infrared fluorescence. Nat. Rev. Clin. Oncol. 2013,10, 507–518. [CrossRef] [PubMed]
Biomedicines 2021,9, 1417 9 of 9
13.
Schaafsma, B.E.; Mieog, J.S.; Hutteman, M.; van der Vorst, J.R.; Kuppen, P.J.; Lowik, C.W.; Frangioni, J.V.; van de Velde, C.J.;
Vahrmeijer, A.L. The clinical use of indocyanine green as a near-infrared fluorescent contrast agent for image-guided oncologic
surgery. J. Surg. Oncol. 2011,104, 323–332. [CrossRef] [PubMed]
14.
Parmeshwar, N.; Sultan, S.M.; Kim, E.A.; Piper, M.L. A Systematic Review of the Utility of Indocyanine Angiography in
Autologous Breast Reconstruction. Ann. Plast. Surg. 2020,85, 601–606. [CrossRef]
15.
Zimmermann, A.; Roenneberg, C.; Wendorff, H.; Holzbach, T.; Giunta, R.E.; Eckstein, H.H. Early postoperative detection of tissue
necrosis in amputation stumps with indocyanine green fluorescence angiography. Vasc. Endovascular. Surg.
2010
,44, 269–273.
[CrossRef] [PubMed]
16.
Terasaki, H.; Inoue, Y.; Sugano, N.; Jibiki, M.; Kudo, T.; Lepantalo, M.; Venermo, M. A quantitative method for evaluating local
perfusion using indocyanine green fluorescence imaging. Ann. Vasc. Surg. 2013,27, 1154–1161. [CrossRef]
17.
Kang, Y.; Lee, J.; Kwon, K.; Choi, C. Application of novel dynamic optical imaging for evaluation of peripheral tissue perfusion.
Int. J. Cardiol. 2010,145, e99–e101. [CrossRef]
18.
Igari, K.; Kudo, T.; Uchiyama, H.; Toyofuku, T.; Inoue, Y. Indocyanine green angiography for the diagnosis of peripheral arterial
disease with isolated infrapopliteal lesions. Ann. Vasc. Surg. 2014,28, 1479–1484. [CrossRef]
19.
Brouwers, J.; van Doorn, L.P.; van Wissen, R.C.; Putter, H.; Hamming, J.F. Using maximal systolic acceleration to diagnose and
assess the severity of peripheral artery disease in a flow model study. J. Vasc. Surg. 2020,71, 242–249. [CrossRef]
20.
Kang, Y.; Lee, J.; Kwon, K.; Choi, C. Dynamic fluorescence imaging of indocyanine green for reliable and sensitive diagnosis of
peripheral vascular insufficiency. Microvasc. Res. 2010,80, 552–555. [CrossRef]
21.
Zimmermann, A.; Roenneberg, C.; Reeps, C.; Wendorff, H.; Holzbach, T.; Eckstein, H.H. The determination of tissue perfusion
and collateralization in peripheral arterial disease with indocyanine green fluorescence angiography. Clin. Hemorheol. Microcirc.
2012,50, 157–166. [CrossRef]
22.
Igari, K.; Kudo, T.; Uchiyama, H.; Toyofuku, T.; Inoue, Y. Quantitative evaluation of microvascular dysfunction in peripheral
neuropathy with diabetes by indocyanine green angiography. Diabetes Res. Clin. Pract. 2014,104, 121–125. [CrossRef]
23.
Venermo, M.; Settembre, N.; Alback, A.; Vikatmaa, P.; Aho, P.S.; Lepantalo, M.; Inoue, Y.; Terasaki, H. Pilot Assessment of the
Repeatability of Indocyanine Green Fluorescence Imaging and Correlation with Traditional Foot Perfusion Assessments. Eur. J.
Vasc. Endovasc. Surg. 2016,52, 527–533. [CrossRef]
24.
Nishizawa, M.; Igari, K.; Kudo, T.; Toyofuku, T.; Inoue, Y.; Uetake, H. A Comparison of the Regional Circulation in the Feet
between Dialysis and Non-Dialysis Patients using Indocyanine Green Angiography. Scand. J. Surg.
2016
,106, 249–254. [CrossRef]
[PubMed]
25.
Goncalves, L.N.; van den Hoven, P.; van Schaik, J.; Leeuwenburgh, L.; Hendricks, C.H.F.; Verduijn, P.S.; van der Bogt, K.E.A.;
van Rijswijk, C.S.P.; Schepers, A.; Vahrmeijer, A.L.; et al. Perfusion Parameters in Near-Infrared Fluorescence Imaging with
Indocyanine Green: A Systematic Review of the Literature. Life 2021,11, 433. [CrossRef] [PubMed]
26. Frangioni, J.V. In vivo near-infrared fluorescence imaging. Curr. Opin. Chem. Biol. 2003,7, 626–634. [CrossRef] [PubMed]
27.
Rossi, M.; Carpi, A. Skin microcirculation in peripheral arterial obliterative disease. Biomed. Pharmacother.
2004
,58, 427–431.
[CrossRef]
28.
Mendes-Pinto, D.; Rodrigues-Machado, M.D.G.; Navarro, T.P.; Dardik, A. Association Between Critical Limb Ischemia, the Society
for Vascular Surgery Wound, Ischemia and Foot Infection (WIfI) Classification System and Arterial Stiffness. Ann. Vasc. Surg.
2020,63, 250–258.e2. [CrossRef]
29.
Yu, S.; McEniery, C.M. Central Versus Peripheral Artery Stiffening and Cardiovascular Risk. Arterioscler. Thromb. Vasc. Biol.
2020
,
40, 1028–1033. [CrossRef]
30.
Pruimboom, T.; van Kuijk, S.M.J.; Qiu, S.S.; van den Bos, J.; Wieringa, F.P.; van der Hulst, R.; Schols, R.M. Optimizing Indocyanine
Green Fluorescence Angiography in Reconstructive Flap Surgery: A Systematic Review and Ex Vivo Experiments. Surg. Innov.
2020,27, 103–119. [CrossRef]
31. Lutken, C.D.; Achiam, M.P.; Svendsen, M.B.; Boni, L.; Nerup, N. Optimizing quantitative fluorescence angiography for visceral
perfusion assessment. Surg. Endosc. 2020,34, 5223–5233. [CrossRef] [PubMed]
... Future studies on NIRF assessment of bone perfusion should report objective outcome measures, including maximum and relative bone fluorescence intensity, after their use is confirmed in fundamental studies. When reporting absolute perfusion parameters, van den Hoven et al. propagated the normalization of the time-intensity curves to minimize the effect of multiple influencing factors, including camera distance and ICG dosage [30]. Bipartite bone perfusion raises the question on ideal NIRF camera position in relation to the evaluated bone. ...
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Objective In the diagnosis of peripheral artery disease (PAD), the ankle-brachial index plays an important role. However, results of the ankle-brachial index are unreliable in patients with severe media sclerosis. Near-infrared (NIR) fluorescence imaging using indocyanine green (ICG) can provide information about tissue perfusion and has already been studied in oncologic, reconstructive, and cardiac surgery. For patients with PAD, this technique might give insight into skin perfusion and thereby guide treatment. We performed a systematic review of the literature on the use of NIR fluorescence imaging in patients with PAD. Methods PubMed, MEDLINE, Embase, and Cochrane were searched for articles and abstracts on the application of NIR fluorescence imaging using ICG as fluorescent dye in patients with PAD. Our search strategy combined the terms “fluorescence,” “ICG,” or synonyms and “peripheral artery disease” or synonyms. The extracted data included fluorescence parameters and test characteristics for diagnosis of PAD. Results Twenty-three articles were found eligible for this review using 18 different parameters for evaluation of the fluorescence signal intensity. NIR fluorescence imaging was used for four main indications: diagnosis, quality control in revascularization, guidance in amputation surgery, and visualization of vascular structures. For the diagnosis of PAD, NIR fluorescence imaging yields a sensitivity ranging from 67% to 100% and a specificity varying between 72% and 100%. Significant increases in multiple fluorescence parameters were found in comparing patients before and after revascularization. Conclusions NIR fluorescence imaging can be used for several indications in patients with PAD. NIR fluorescence imaging seems promising in diagnosis of PAD and guidance of surgeons in treatment, especially in patients in whom current diagnostic methods are not applicable. Further standardization is needed to reliably use this modality in patients with PAD.