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Biofilms and Impaired Wound Healing … 207
Table 1 (continued)
Type of
marker
Biofilm Ngernpimai
Biofilm Wu et al.
Biofilm Nakagami et al.
Biofilm Ashrafi et al.
References Markers measured Details Tested in
et al. (2017)
(2020)
(2017)
(2018)
Uncharacterised EPS
components
EPS polysaccharides Wound blotting using alcian
EPS
mucopolysaccharides
Volatile organic
compounds
biofilms
specificto
Multichannel polymer sensors in
combination with inter-polymer
FRET between channels
detected various EPS
components,
patterns
species that produced the EPS
blue that stained EPS
polysaccharides, was found to
correlate well with
microbiological results
Wound blotting using ruthenium
red that stained
mucopolysaccharides, was
found to correlate to wound size
and slough production
Gas
used to detect volatile organic
compounds. VOC profiles were
found to be specific for biofilm
growth and even metabolic
activity and biomass. The
method was tested on human
ex vivo skin samples
creating different
depending on the
EPS
chromatography-MS was
humans or
on human
samples?
No
Yes
Yes
Yes
from patients with chronic venous ulcers over the course of 5 weeks (Gao et al.
2021). Although temporal fluctuations amongst the measured markers occurred as
well as conflicting interpatient differences, some common features were evident
amongst all 5 patients, suggesting that the developed multiplexed immunosensor
may serve as a beneficial tool in the future. On top of immune signalling molecules,
the authors also measured temporal changes in temperature and pH. Both of these
markers are commonly measured as they can be quantified using rather cheap and
simple instruments. Handheld infrared thermometers are often utilized to measure
wound temperatures and there is an increasing amount of documentation which
shows that wound temperature and wound infection is closely linked (Dini et al.
2015; Woo and Sibbald 2009; Fierheller and Sibbald 2010). pH is often measured
using colour gradients of different pH-sensitive stains. These can be incorporated
into fibrous dressings in which a visible colour change can be observed in response
to the pH dynamics of the wound (Pan et al. 2019; Tamayol et al. 2016; Vu et al.
2020). Shukla et al. (2014) measured the pH of 50 patients using simple litmus
paper strips. They also performed microbial culturing of the wounds and found an
association between the detected species and the wound pH. An additional
208 I. C. Thaarup and T. Bjarnsholt
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microenvironmental change that can be monitored is the presence or absence of
oxygen. He et al. (2020) created a smart wound dressing with incorporated
methylene blue that turned yellow due to bacterial oxygen depletion. As this colour
change is visible to the naked eye, the authors argued that this made real-time
monitoring of wound infection possible (He et al. 2020). While all of these indirect
markers may indicate whether an infection is present or not, none of them can prove
the establishment of a biofilm.
Measuring microbial markers is a complicated task due to the large variety of
species found in wounds. Very often, a single biological marker will not be present
for all species, and although some commonalities exist, sensors that detect microbes
or microbial produced compounds are often limited by this fact. Yet attempts are
still being made to creat
e sensors that can report on the microbial presence in
wounds.
Smart wound dressings are being developed that responds to the presence of
bacterial toxins, which are commonly utilized as microbial markers. This is often
done by encapsulating dyes in lipid vesicles which are broken down in the presence
of most bacterial toxins or bacterially derived enzymes, thus releasing the dye and
causing a colour change (Thet et al. 2016, 2020; Zhou et al. 2018). It has been
argued that these systems only react to pathog ens, as commensal bacteria are not
known to produce toxins to the same degree. However, some commensal skin
bacteria cause extensive infections despite their limited production of toxins, as is
the case for S. epidermidis (Otto 2009). Some studies maintain that the production
of toxins for certain species is a density regulated action, and can therefore be
correlated to the presence of biofilms (Thet et al. 2016). Other speci es, for example
E. faecalis, are known to produce toxins in the presence of target cells, no matter
the microbial amount (Coburn et al. 2004). For some species, the production of
toxins is believed to be regulated by quorum sensing (QS). However, the role of QS
in wounds is not yet established. In fact, one study that analysed the transcriptome
of P. aerugi nosa obtained from clinical samples found a down-regulation of QS
genes (Cornforth et al. 2018).
Some sensors are developed to detect specific toxins, as was done in the study by
Simoska et al. (2020). In this study, a flexible carbon ultramicroelectrode array was
developed that could perform quantitative electrochemical detection of pyocyanin,
a toxi n produced solely by P. aeruginosa strains. Pyocyanin has previ ously been
found in varying quantities in wound exudate, and in this study pyocyanin amounts
in the range of 1–250 lM could be detected. In addition to pyocyanin, the developed sensor was also able to detect uric acid and NO. Uric acid is another microbial
marker, which is discussed later on, while NO is a common immune cell signalling
molecule, secreted by both PMNs and macrophages in response to wounding.
However, in the infectious anoxic environment of chronic wounds, NO is often
lacking, and its absence can therefore be used as an infection marker. Jarosova et al.
(2019) also created a sensor for detecting pyocyanin but did so using
polyacrylamide-coated carbon nanotube electrodes, managing to detect pyocyanin
in concentrations as small as 0.1 lM. Their sensor was also developed to detect
uric acid.
Biofilms and Impaired Wound Healing … 209
Uric acid (UA) is a commonly studied wound marker and high levels of UA
have been found in uninfected chronic wounds (Fernandez et al. 2012). The precursor for UA is ATP, which is released in the wound microenvironment when cells
rupture. Cell damage caused by inadequate oxygen supply leads to ATP release and
subsequent build-up of
purine metabolites (Fernandez et al. 2014). The conversion
of UA also causes a release of ROS, further sustaining inflammation. Chronic
wounds are therefore expected to contain an intrinsic high level of UA, however, in
the presence of infectious microbes UA is rapidly metabolised and local levels of
UA are decreased. This decrease in UA is therefore used as a biological marker
signifying the presence of metabolising microbes and several different types of
bandages have been developed to detect UA levels (Sharp et al. 2008; Kassal et al.
2015; Sharifuzzaman et al. 2020). Another microbial marker is lactic acid, which
has also been found in increased amoun ts in infected chronic ulcers (Löffler et al.
2011). Lactate is thought to be produced not only by PMNs during their respiratory
burst but also by several microbial species during fermentation (Löffler et al. 2011).
Sensors which detect the levels of lactate within a woun d have been developed.
Ashley et al. (2019) developed a flexible electrochemical biosensor which could
detect both lactate and oxygen. The sensor was designed to be able to integrate into
wound bandages and in vivo tests of the sensor were reportedly underway.
On top of several immune signalling molecules, the multiplexed immunosensor
developed by Gao et al. (2021) also contained a channel for detecting S. aureus
specifically, as S. aureus is one of the most common wound pathogens. The
aptamers in the device were designed to bind to specific epitopes on the cell wall of
S. a
ureus (Ranjbar a
nd Shahrokhian 2018). However, due to inherent strain differences, it can be speculated if the specific aptamer only shows an affinity for
certain similar strains of S. aureus as the one used in the experiment in the paper.
A different study presented a wound dressing designed to detect the presence of S.
aureus DNA (Roy et al. 2021). The dressing was based on a composite of zeolitic
imidazolate framework and carbon nitride conjugated with S.aureus probe-DNA.
The sensor was tested against human serum and non-complimentary DNA, and
based on this the authors concluded that the chosen probe was selective only
towards S. aureus DNA.
Lastly, sensors that detect biofilm markers such as EPS components are being
developed and tested. In 2014, Li et al. developed a gold-particle based multichannel nanosensor that could detect various EPS components, creating different
patterns depending on the species which produced the EPS (Li et al. 2014)
A multic
hannel output was created via reversible adsorption and subsequently
partial displacement of three distinct fluorescent proteins. The three fluorescent
proteins all contained negative surface charges allowing for electrostatic interactions with two cationic functional groups on gold nanoparticles. When presented
with negatively charged EPS components, competitive interactions occurred, and
distinct patterns were generated based on the specific EPS
tichannel sensor was tested against biofilm produced by fi
each species a
for
distinct fluorescent pattern was observed. The sensor was also
composition. The mul-
ve different species and
tested against two different strains of E. coli and once again produced distinct
.
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fluorescent patterns. Ngernpimai et al. (2017) created a similar multichannel sensor
containing three fluorescent poly(oxanorborneneimide) polymers which each contained a cationic recognition element and an environmentally sensitive transducer,
selected to create two Förster Resonance Energy Transfer (FRET) partners. When
exposed to different biofilms of various species, distinct fluorescent patterns were
observed. In the two studies by Li et al. and Ngernpimai et al., both author groups
recognized that c
reating sensors for specific EPS components would be too
extensive due to the large variety and combination of EPS produced by different
species. Instead, creating multichannel sensors which allow for unspecific EPS
detection increases the likelihood that any encountered biofilm could be detected.
However, to believe that such multichannel sensors will be able to recognise the
specific microbial species responsible for a biofilm infection seems unlikely, as this
would r
equire an immense amount of sensor training.
Nakagami et al. (2017) used a different and more simple approach to detect
wound biofilms, termed wound blotting. A nitrocellulose membrane was pressed to
a wound surface to collect biofilm components. The membrane was subsequently
stained using ruthenium red which detects the presence of mucopolysaccharides, a
component commonly found in biofilm EPS. This wound blotting technique was
testedon23
u
re ulcers and a biofilm-positive wound blotting outcome was
press
found to correlate to increased or unchanged slough production. Wu et al. (2020)
performed similar wound blotting but utilised alcian blue staining instead which
also stains EPS polysaccharides. Wound blotting has previously been used to show
the distribution of TNF-a on pressure wound surfaces and the distinct patterns were
found to correlate to the healing process of the wounds (Minematsu et al. 2013).
A common issue for all of the EPS sensors and detection methods presented
above is their ability to only detect biofilms on the surface of wounds. This issue
was averted using the detection method presented in Ash rafi et al. (2018). This
method was based on the detection of volatile organic compounds (VOCs) produced by microbial pathogens. The VOCs were measured using gas chromatography coupled to mass spectrometry on ex vivo samples of human skin which had
been incubated with bacteria. The authors found that the VOC profiles differed
between planktonic and biofilm growing cells, which means that the method could
arguably be used to detect biofilm infections speci fically. For some species, it was
also found that the VOC profiles correlated with metabolic activity and biofilm
biomass. VOC profiles have previously been found to differ between chronic
wounds and healthy skin in individual patients and have been speculated to relate to
the infecting pathog ens (Thomas et al. 2010). The VOC profiles in the study by
Ashrafi et al. (2018) were also found to differ between different species, and
although the authors argued that the profiles could be used to distinguish between
tions caused by
infec
different species, it remains to be seen if this is clinically
feasible.
Biofilms and Impaired Wound Healing … 211
Novel Imaging-Based Detection Methods
An alternative to sensors is non-invasive, non-destructive imaging techniques (see
Table 2 for an overview). Imaging techniques cause little to no interference with the
wound and have a high precision when used for repeated and continuous measurements over longer intervals (Li et al. 2020). Particularly approaches that use
both photography and digital tracings to create a mul tidimensional image that not
only assesses surface conditions are gaining popularity. One such technique is
Table 2 Table presenting the imaging-based detection methods mentioned in this chapter
Imaging
method
Near-infrared
imaging
Near-infrared
imaging
Raman
Spectroscopy
Surface
enhanced
Raman
spectroscopy
Surface
enhanced
Raman
spectroscopy
MSI/HSI
methods
MSI/HSI
methods
References Details Tested in
Dinjaski
et al. (2014)
LópezÁlvarez et al.
(2022)
Bullock et al.
(2020)
Bodelón
et al. (2016)
Nguyen et
(2018)
Nouvong
et al. (2009)
Poosapadi
Arjunan
et al. (2018)
Detection of luciferase produced by
bioengineered bacteria and ROS. The
bacteria were added to implants,
placed into mice and then followed
using an IVIS platform
Detection of a fluorescent tracer
composed
fluorophore. The method was tested on
plates and screws extracted from
human patients who needed revision
surgery following
Raman
measure microbe-induced pH changes
in tissue-engineered skin
Surface Enhanced Raman
Spectroscopy was used to detect
pyocyanin in vivo in a mouse model
al.
Pyocyanin produced by P. aeruginosa
in
surface enhanced Raman spectroscopy
HSI
tissue
deoxyhemoglobin at the
diabetic ulcers. Healing was found to
correlate strongly to tissue
oxygenation status
HSI was
diabetic
reflectance spectrum of pure bacterial
cultures, they managed to discriminate
between infections caused by S. aureus
and E. coli
of vancomycin coupled to
orthopaedic trauma
microscopy was used to
aqueous media was detected using
was used to measure superficial
oxyhemoglobin and
used to investigate infected
ulcers and by comparing the
edge of
humans or on
human
samples?
No
No
a
No
No
No
Yes
Yes
(continued)
212 I. C. Thaarup and T. Bjarnsholt
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Table 2 (continued)
Imaging
method
MSI/HSI
methods
MSI/HSI
methods
MSI/HSI
related
methods
MSI/HSI
related
methods
Spatial
frequency
domain
imaging
X-ray CT Carrel et al.
X-ray PET Sellmyer
Ultrasound Anastasiadis
References Details Tested in
Chang et al.
(2018)
Herrmann
et al. (2020)
Raizman
et al. (2021)
Rennie et al.
(2017)
Nguyen et al.
(2013)
(2017)
et al. (2017)
et al. (2014)
HSI was combined with 3D wound
size measurements and thermal
profiling. This was employed on 23
patients suffering pressure ulcers
HSI was combined with UV excitation
and fluorescence profiling from
diabetic ulcers was recorded
infected
MolecuLight i:X technology that
detected pyoverdine fluorescence in
chronic wounds was linked to biofilm
formation
MolecuLight i:X technology was used
to detect red porphyrin production of
bacteria
An expansion of an MSI/HSI
technique termed spatial frequency
domain imaging was used to determine
the infection status of rodent burn
wounds in situ. The authors could
follow blood flow, oxygenation and
tissue changes over time
X-ray computed tomography was
performed in combination with the use
of iron sulphate as a contrast agent.
The authors were able to distinguish
biofilm biomass from the surroundings
Positron emission tomography
imaging was performed using a
radio-labelled antibiotic as the contrast
agent and enabled the visualisation of
infections in rodents
Method not specifically
wounds. Ultrasound and ultrasound
contrast agents, which bound to
biofilm specific ligands were
developed. Only tested on S. aureus
developed for
humans or on
human
samples?
Yes
Yes
Yes
Yes
No
No
No
No
near-infrared imaging. In Vivo Imaging Systems (IVIS) that use near-infrared
imaging in combination with optical imaging are able to visualize bioluminescenc e
and fluorescence signals in live tissue. Near-infrared imaging has the advantage that
it can provide high-resolution images deep within a tissue, up to several centimetres
(Dang et al. 2019). One study utilised an IVIS system in combination with a
bioluminescent strain in a mouse model to follow the establishment of an
implant-related infection in vivo (Dinjaski et al. 2014). A different study used an
Biofilms and Impaired Wound Healing … 213
IVIS system to detect fracture-related infections following orthopaedic trauma
surgery. The authors used vancomycin coupled to a near-infrared fluorophore as an
optical trace r, which was found to bind well to biofilms of gram-positive microbes,
although the visualisation was only performed on plates and screws that had already
been removed from the patients (López-Álvarez et al. 2022
). In the future, using
biofilm-specific fluorescent compounds in combi nation with this method could
provide a novel non-invasive detection method to visualise biofilms within wounds
and other infections, although un iversal biofilm-specific compounds h ave yet to be
found.
Another popular imaging technique is Raman Spectroscopy which detects the
energy change of photons when scattering off a material. Raman spectroscopy is
highly sensitive and can detect biomolecules
Bullock et
al. (2020) used
changes in tissue-engineere
Raman Spectroscopy to detect bacteria-induced pH
d human skin. They managed to measure the pH to a
in low abundances (Xu et al. 2020).
depth of 600 um into the skin. Specific microenvironments were observed within
the skin in a patchy distribution when the skin had been infected with S. aureus and
P. aeruginosa. Interestingly, the authors noted that when they averaged all pH
measurements across the infected skin model, the net pH value was not significantly
different to a control model. This finding emphasizes how single point pH measurements or average measurements across a wound might overlook pockets of
alkalinity occurring due to microbial actions. Surface-Enhanced Raman Scattering
spectroscopy (SERS) is an enhanced method of Raman Spectroscopy and can
detect even smaller amounts of biomolecules. Nguyen et al. (2018) used SERS to
detect pyocyanin produced by P. aeruginosa in aqueous media and Bodelon et al .
(2016) detected pyocyanin in vivo in a mouse model. The authors argued that SERS
could be used to detect P. aeruginosa infections in very early stages.
Multispectral and Hyperspectral Imaging (MSI/HSI) are other imaging techniques which have been used to monitor wound progression. The imaging systems
contain the ability to split light into multiple narrow bands, and thereby recognise
and differentiate spectrally distinctive materials (Saiko et al. 2020)
sed to quantify oxygenation levels in wound tissue, and a few commercial
often u
he method is
. T
systems developed for this purpose already exist, although more complex HSI
systems are also being developed. Nouvong et al. (2009) used HSI to measure
superficial tissue oxyhemoglobin and deoxyhemoglobin at the edge of diabetic
ulcers from 54 patients. After 24 weeks all wounds were re-evaluated and the rate
of healing was found to correlate strongly to tissue oxygenation status. Poosapadi
Arjunan et al. (
performed HSI on infected diabetic ulcers and by comparing
2018)
the reflectance spectrum of pure bacterial cultures, they managed to discriminate
between infections caused by S. aureus and E. coli. Some studies integrate multispectral and hyperspectral imaging with other imaging technologies. Chang et al.
(2018) combined hyperspectral imaging with 3D wound size measurements and
thermal profiling and employed this clinically on 23 patients suffering pressure
ulcers. Finally, in a study by Herrmann et al. (2020
combined with
was
UV excitation and fluorescence profiling from infected diabetic
) a hyperspectral imaging system
ulcers was recorded. The authors argued that fluorescent substances naturally
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produced by bacteria would be visible on the wound surface. A commercial device
termed MolecuLight i:X has been developed which is based on the same concept as
the one presented in Herrmann et al. (2020). This handheld imaging device has
been tested to measure different fluorescent biomolecules such as porphyrin and
pyoverdine (Raizman et al. 2021; Jones et al. 2020). The creators of the device
argue that the amount of fluorescent biomolecules increases when the microbes are
in the biofilm mode of growth, hence functioning as a specific biofilm detection
device. Yet, care should be taken when measuring fluorescent signals in human
tissue, as autofluorescence from tendons, slough and other human tissues can
interfere with the bacterial fluorescent signals (Rennie et al.
2019). Moreover, the
maximum depth of excitation for UV light has been estimated to be 1 mm in human
tissue, hence any bacteria found deeper than this will not be visualised (Jones et al.
2020). Finally, the device has a limit of detection of around 10
4
CFU/g, as lower
amounts than this do not produce enough fluorescent signal to be detected (Rennie
et al. 2017).
Another expansion of MSI/HSI techniques is Spatial Frequency Domain
Imaging (SFDI), which can measure the optical properties over a large field of view
with increased depth sensitivity and resolution. SFDI separates and quantifies
absorbed and scattered light by imparting a structural pattern to the tissue illumination (Li et al. 2020; Tha
tcher et al. 2016). Nguyen et al. (2013) used SFDI to
determine the infection status of rodent burn wounds in situ. The wounds were
imaged daily over a period of 10 days, and by using SFDI the authors could follow
blood flow, oxygenation and tis sue changes. In the future, a combination of
fluorescence profiling together with the depth resolution of SFDI might allow for
greater biofilm detection in wounds. This combination o f methods is already being
investigated for use in cancer surgery (Sibai et al. 2019).
Recently, novel types of fluorescent molecules that attempt to target some of the
most ubiquitous EPS components have gained a lot of traction. The method is
known as optotracing and it is based on conformation-sensitive fluorescent tracer
molecules that bind to amyloids, polysaccharides and cell wall glycan strands
(Choong et al. 2016; Butina et al. 2020). Optotracers are small anionic fluorescent
tracer molecules that interact with their target via electrostatic interactions. For
now, the fluorescent molecules have been visualized using standard fluorescent
microscopy and spectrophotometric methods, but if the optotracers were to be used
in combination with some of the newer visualisation techniques presented here,
their use in infection diagnosis could prove very relevant. However, their usefulness
relies on the matrix components being expressed in the wounds.
While standard X-ray computed tomography scans can determine the presence
of infections, specific biofilm detection will require a contrast agent (Xu et al.
2020). Carrel et al. (2017) performed X-ray computed tomography in combination
with iron sulphate as the contrast agent and were able to distinguish biofilm biomass
from the surrounding porous media, despite the high water content observed in
biofilms. An expansion to this is to use X-ray microforce computed tomography
instead, which has a higher resolution. Sellmyer et al. (2017) performed positron
emission tomography (PET) imaging using a radio-labelled antibiotic as the
Biofilms and Impaired Wound Healing … 215
contrast agent and were able to visualise rodent infections caused by several different species. They did however observe a decreased and delayed uptake of the
contrast agent in resistant bacterial strains and while labelled antibiotics are often
shown to be very specific in targeting microbes, the spread of antibiotic resistance
can diminish the use of such tracers.
The biofilm detection method presented in Anastasiadis et al. (2014) was not
developed for wounds specifically, yet it could easily be adapted to fit this situation.
The detection method uses high-frequency acoustic microscopy in conjunction with
ultrasound contrast agents (UCAs) developed to target biofilm specific ligands of S.
aureus. The authors argue that since
available in most clinical settings, implementing this detection method should prove
fairly easy. Gas microbubbles in combination with ultrasound are already being
investigated extensively for their use in the controlled delivery of drugs to infectious biofilms (LuTheryn et al. 2020). While this detection method seems
promising, to our knowledge, tests have yet to be performed on humans. Moreover,
similar to other detection methods developed, this method focuses solely on S.
aureus infections. The development of universal UCAs against biofilm components
would surely be valuable in the detection of infectious biofilms.
ultrasound imaging devices are already readily
Discussion
The aim of this chapter is to elucidate methods used to detect biofilms in
wounds
is it relevant to know whether or not there is a biofilm present in a wound? Or
rather: could it not just be assumed that a non-healing wound always contains a
certain amount of biofilm? The purpose of this book is to address the topic of
significance of evidence and technology in the context of wound management. The
burden of chronic wounds is enormous as discussed widely in this book: technology is used to generate evidence which, appropriately applied, should permit
better wound healing in the context of standardised care, and generate better
evidence.
this number is often thought to be an underestimation (Malone et al. 2017a)
Perhaps m
biofilm-based wound care treatment in carefully designed studies using a presumptive hypothesis which is that a chronic wound with impaired healing will
contain a biofilm: on the contrary a freshly cleansed and debrided wound should be
free of biofilms. In this situation, it would be useful to have a fast, non-invasive
method to detect if the debridement left the wound free of biofilm. At any rate,
sharp debridement guided by an initial biofilm detection could lead to more
accurate and efficient biofilm removal without collateral damage to nearby granu-
l
ation
detection methods may have their merits both before and after such treatments.
(see Table 3 for a summary) . Thus, it is important to address the question:
Most recent studies find that 80% of all chronic wounds contain biofilms, but
any of these detection methods could be used in combination with a
tissue. The same is true for other biofilm-based wound care treatments, as
.
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Table 3 Summary of the biofilm detection methods presented in this chapter
Method based on References Was the method
tested in humans or
on human samples?
Sensor-based detection methods
Indirect
infection
markers
pH Gao et al. (2021), Pan et al. (2019),
Tamayol et al. (2016), Vu et al.
(2020), Shukla et al. (2014),
Yes
Sharifuzzaman et al. (2020)
Oxygen (He et al. (2020), Ashley et al.
No
(2019)
Temperature Dini et al. (2015), Woo and Sibbald
Yes
(2009), Gao et al. (2021), Fierheller
and Sibbald
(2010), Sharifuzzaman
et al. (2020)
Immune signals Gao et al. (2021), Simoska et al.
Yes
(2020)
Microbe
markers
Uric acid Simoska et al. (2020), Jarošová et al.
(2019), Sharp et al. (2008), Kassal
Yes
et al. (2015), Sharifuzzaman et al.
(2020)
Lactic acid Ashley et al. (2019)No
Cell wall epitopes Gao et al. (2021) Yes
DNA Roy et al. (2021)N
Pyocyanin Simoska et al. (2020), Jarošová et al.
o
No
(2019)
Biofilm
markers
Uncharacterised
toxins
Uncharacterised EPS
components
Polysaccharides and
mucopolysaccharides
Volatile Organic
Thet et al. (2016), (2020), Zhou et al.
No
(2018)
Li et al. (2014), Ngernpimai et al.
No
(2017)
Nakagami et al. (2017), Wu et al.
Yes
(2020)
Ashrafi et al. (2018) Yes
Compounds
Imaging-based detection methods
Near-infrared imaging and
related methods
Raman Spectroscopy and
Surface Enhanced Raman
Dinjaski et al. (2014), López-Álvarez
et al. (2022)
Bullock et al. (2020), Bodelón et al.
(2016), Nguyen et al. (2018)
No
No
Spectroscopy
MSI/HSI and related methods Nouvong et al. (2009), Poosapadi
Arjunan et al. (2018), Chang et
Yes
al.
(2018), Herrmann et al. (2020),
Raizman et al. (2021), Rennie et al.
(2017), Nguyen et al. (2013)
X-ray CT and X-ray PET Carrel et al. (2017), Sellmyer et al.
No
(2017)
Ultrasound Anastasiadis e
t al. (2014)No
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