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Raman spectroscopy as a non-destructive tool to determine the chemical composition of urinary sediments


Abstract and Figures

Urolithiasis is a common disease worldwide, but its causes are still not well understood. In many cases, crystalluria provides an early indication of urinary stone formation, and characterisation of the urinary deposits could help doctors to take early preventative measures to stop their further growth. Nowadays, the gold standard for the analysis of urinary deposits is optical microscopy, but the morphology-based information it provides can often be unreliable and incomplete, particularly for deposits with no defined crystalline structure. In response to the need of a more attested method, we used Raman spectroscopy to determine the chemical composition of urinary deposits and urinary stones of 15 patients with urolithiasis in order to find out whether direct correlation between the composition of the corresponding stones and the deposits exists. We found that the main chemical compounds typically constituting urinary stones also form the deposits and that their composition correlates in eleven out of fifteen cases. However, brushite deposits that we found in two cases did not result in brushite, but mixed calcium oxalate monohydrate and phosphate stones. Overall, Raman spectroscopy is an informative and reliable method that can be used for analysis of urinary sediments for early diagnosis of urinary stone formation.
Comptes Rendus
Sandra Tamosaityte, Milda Pucetaite, Arunas Zelvys, Sonata
Varvuolyte, Vaiva Hendrixson and Valdas Sablinskas
Raman spectroscopy as a non-destructive tool to determine the
chemical composition of urinary sediments
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Comptes Rendus
Online first, 28th September 2021
Microcrystalline pathologies: Clinical issues and nanochemistry /Pathologies
microcristallines : questions cliniques et nanochimie
Raman spectroscopy as a non-destructive tool to
determine the chemical composition of urinary
Sandra Tamosaitytea, Milda Pucetaite a,b, Arunas Zelvys c, Sonata Varvuolyte c,
Vaiva Hendrixson cand Valdas Sablinskas ,a
aFaculty of Physics, Vilnius University, Sauletekio al. 9, LT-10222 Vilnius, Lithuania
bDepartment of Biology, Lund University, Sölvegatan 37, 22362 Lund, Sweden
cFaculty of Medicine, Vilnius University, M.K. Ciurlionio g. 21, LT-03101, Vilnius,
E-mails: (S. Tamosaityte),
(M. Pucetaite), (A. Zelvys),
(S. Varvuolyte), (V. Hendrixson),
(V. Sablinskas)
Abstract. Urolithiasis is a common disease worldwide, but its causes are still not well understood. In
many cases, crystalluria provides an early indication of urinary stone formation, and characterisation
of the urinary deposits could help doctors to take early preventative measures to stop their further
growth. Nowadays, the gold standard for the analysis of urinary deposits is optical microscopy, but the
morphology-based information it provides can often be unreliable and incomplete, particularly for
deposits with no defined crystalline structure. In response to the need of a more attested method, we
used Raman spectroscopy to determine the chemical composition of urinary deposits and urinary
stones of 15 patients with urolithiasis in order to find out whether direct correlation between the
composition of the corresponding stones and the deposits exists. We found that the main chemical
compounds typically constituting urinary stones also form the deposits and that their composition
correlates in eleven out of fifteen cases. However, brushite deposits that we found in two cases did
not result in brushite, but mixed calcium oxalate monohydrate and phosphate stones. Overall, Raman
spectroscopy is an informative and reliable method that can be used for analysis of urinary sediments
for early diagnosis of urinary stone formation.
Keywords. Urolithiasis, Crystalluria, Urinary stones, Urinary sediments, Raman scattering, Spec-
Online first, 28th September 2021
Corresponding author.
ISSN (electronic) : 1878-1543 https://comptes-rendus.academie-
2Sandra Tamosaityte et al.
1. Introduction
Urinary stone disease is a common condition, and
its prevalence is increasing worldwide. Current
incidence varies among dierent countries from
1% to 20% and can constitute major costs for health
care systems as well as significantly decrease the
quality of life for people with the disease [1,2]. Early
diagnosis could aid in prescribing treatment that
prevents urinary stone growth and avoid more ex-
pensive and, in severe cases, invasive stone removal
procedures [3].
Urinary stone formation processes are believed
to be caused by urinary saturation with typical uri-
nary stone forming materials such as calcium ox-
alate, uric acid, various urates, calcium phosphates,
amorphous phosphates, and magnesium ammo-
nium phosphate hexahydrate (struvite). This leads
to formation of urinary deposits (or sediments) that
are indicative of urolithiasis [4–6]. Less commonly,
urinary deposits can also be constituted from cys-
tine [7], various lipids [8], and metabolites of some
drugs [9,10] that contribute to the stone formation
processes. Qualitative chemical analysis of chemi-
cal composition of urinary sediments plays an im-
portant role in taking early preventive measures to
stop urinary stones from forming or growing [4,6,11].
Such analysis is usually challenging because of their
small size, brittleness and inhomogeneity [12]. Opti-
cal microscopy is currently considered the gold stan-
dard for this purpose, and it is the only method used
in clinical practice [10,13]. Visual morphology-based
inspection of urinary sediments is, however, not pre-
cise enough, since it is based on the examination
of the shapes of sediments and cannot be reliable
when the structure of these sediments is atypical or
amorphous or consists of multiple components.
Alternative methods to optical microscopy are
still in high demand in the medical field for qual-
itative and quantitative chemical analysis of uri-
nary deposits. The chemical composition of urinary
stones is routinely analysed using vibrational spec-
troscopy [12,14–20], X-ray diraction [19,21], and
scanning electron microscopy with element distri-
bution analysis (SEM-EDAX) [22]. For urinary sedi-
ments, SEM-EDAX experiments have also been car-
ried out, but information about the chemical com-
position of the sample provided by such experi-
ments are not accurate enough [23]. More reliable
results have been obtained by means of infrared
(IR) microspectroscopy, but the quality of the re-
sults is very dependent on the size of the sediment
under study, which is also limited to approximately
10 µm [12,24,25]. In addition, IR spectra of urinary
deposits can be significantly aected by Mie scatter-
ing, which seriously obstructs analysis [24]. Finally,
larger crystals cannot be measured in the transmis-
sion mode of the IR microscope without additional
sample preparation, and the specular reflection sig-
nal that could be used instead suers from spectral
distortions that are dicult to correct for [14]. Ra-
man spectroscopy is a method complementary to IR
microspectroscopy, but it oers higher spatial reso-
lution, meaning that smaller samples can be anal-
ysed [25,26]. It also allows the challenges posed by
analyzing Mie scattering or reflectance IR spectra to
be overcome. The main disadvantage of the method,
fluorescence that can overwhelm the Raman scatter-
ing signal, can be suppressed or even eliminated by
using a Fourier transform (FT) Raman spectrometer
that employs a near-IR (NIR) laser for excitation of
Raman scattering.
In Raman spectroscopy experiments [27], a
monochromatic light source, usually a laser, is em-
ployed to excite the molecules of a sample. Fluores-
cence that interferes with the Raman signal origi-
nates when a molecule is excited to higher electronic
energy states. It happens when the energy of the laser
photons exceeds the gap between the electronic en-
ergy levels of the molecule. This is especially criti-
cal issue for “real life samples the molecular com-
pounds of which might not possess electronic tran-
sition in the visible spectral region but very often
are contaminated with fluorescent impurities such
as various pigments. Such impurities cannot always
be removed from the sample, as is the case for uri-
nary sediments [28,29]. Using lasers of longer wave-
length reduces the probability of such electronic
excitation and, in turn, occurrence of fluorescence.
Since over the past decades NIR laser sources have
become widely available, their implementation in
Raman spectroscopy experiments has been gaining
popularity in various fields, especially in biology and
medicine [30]. It has been used in a few case stud-
ies for identification of unrecognized crystals in the
urine of patients suering from gout [31] and pso-
riatic arthritis [32]. It has also been recently shown
that a dispersive Raman spectroscopy system using
C. R. Chimie Online first, 28th September 2021
Sandra Tamosaityte et al. 3
785 nm excitation can be useful for the identification
of small urinary crystals in patients with urolithia-
sis [33,34]. Automatic analysis of single-component
deposits has also proven to be possible [33]. In
this work, we specifically examined the potential of
FT–Raman spectroscopy with 1064 nm laser excita-
tion to explore the chemical composition of urinary
sediments. This approach can further improve the
sensitivity for identifying such sediments by reduc-
ing fluorescence background. Importantly, we inves-
tigated the chemical composition of urinary stones
from the same patients with urolithiasis to determine
whether direct correlation between the composition
of the corresponding stones and the deposits exists.
2. Material and methods
For the duration of one year of the project de-
scribed here, urine samples of every patient with
acute uronephrolithiasis hospitalised at the Urology
Centre of Vilnius University Santaros Clinics were
collected—fifteen in total. The samples were inves-
tigated with NIR Raman spectroscopy. The chemical
composition of the urinary stones removed from the
same patients was also checked by means of FTIR
spectroscopy. For the stones, this bulk analysis tech-
nique allows better identification of overall compo-
sition than Raman spectroscopy, which yields infor-
mation on micrometer-sized areas that are analysed.
Urine samples were centrifuged in order to sep-
arate the urinary crystals. The precipitates were fil-
tered on Whatman ashless grade 542 filters for 24 h
at room temperature to remove the remaining liquid.
All particles larger than 2.7 µm in diameter remained
on the surface of the filter, but only the larger ones
(typically >100 µm in size) were collected with the
aid of a small needle. Those particles were transferred
to the surface of a silver mirror, a typical substrate in
spectroscopic analysis that does not produce any Ra-
man signal of its own [35]. This procedure is suitable
to collect single crystallites for Raman spectroscopic
analysis. The use of artificially synthesised magnetic
nanoparticles which adhere to the crystallites in
urine solution has been shown to provide possibil-
ity to automatically detect, hold and release them for
Raman analysis [33], which provides potential for fast
identification of many urinary deposits in the future.
Spectra were recorded with a MultiRAM (Bruker
Optik GmbH, Ettlingen, Germany) FT–Raman
spectrometer equipped with microscope stage and
a gold-plated mirror objective (focal length 33 mm)
which yields the diameter of the focused laser beam
on the sample equal to 100 µm. Samples were excited
with a Nd:YAG laser having a wavelength of 1064 nm
to produce Raman scattered radiation, which was
collected by a liquid-nitrogen–cooled Ge diode de-
tector. The spectra were collected at a resolution of
5 cm1. Depending on the size and morphology of
the urinary deposits, 200 to 170,000 scans were ac-
quired and averaged for a single resultant spectrum.
Also, the power of the excitation laser was varied be-
tween 5 and 600 mW in order to avoid thermal dam-
age caused by focused NIR laser radiation in the sam-
ples more sensitive to heating. The eects of heating
in such samples were observed in the spectra as a
broad band of black-body radiation in the wavenum-
ber region above 2500 cm1. Reference spectra of
pure chemical compounds (Sigma Aldrich) typically
constituting urinary sediments were recorded for
the qualitative evaluation of the spectra allowing us
to identify all constituents in the analysed deposits
with high chemical sensitivity. Spectral analysis was
performed on raw spectra with no pre-processing
procedures applied. Optical images of the urinary
crystals were recorded using the visible mode of
the same instrument, which includes a visible light
source and a CCD camera for this purpose.
For the FTIR studies, the urinary stones were
ground with an agate mortar, mixed with IR-
transparent KBr powder (ratio 1:100) and pressed
into a pellet using a hydraulic press. The KBr pellets
were analysed with a Vertex 70 IR spectrometer
(Bruker Optik GmbH, Ettlingen, Germany) equipped
with a liquid nitrogen cool mercury cadmium tel-
luride (MCT) detector. The spectra were recorded
with 4 cm1spectral resolution. One hundred
twenty-eight (128) interferograms were obtained,
averaged, and converted into a resulting spectrum
using the three-term Blackman–Harris apodization
function and a zero-filling factor of 2. The spectra
were analysed by comparing them with pure chem-
ical component reference spectra recorded in the
same way.
3. Results
The chemical composition of the urinary sediments
of fifteen patients suering from urolithiasis was
C. R. Chimie Online first, 28th September 2021
4Sandra Tamosaityte et al.
investigated by means of Raman spectroscopy. The
characteristic Raman spectra and optical images of
the sediments are shown in Figures 1–4. In the spec-
tra that are presented in the figures, the spectral re-
gion varies depending on the valuable spectral infor-
mation of interest. The most characteristic spectral
bands are also indicated in the spectra. Although the
samples in some cases also contained cells, all the
analysed deposits yielded clear signal of the consti-
tuting minerals. This could be explained by the fact
that the Raman scattering cross-section of minerals is
typically much higher while also predominantly con-
taining spectral bands in lower wavenumber region
compared to organic compounds constituting cells.
Analysis of the Raman spectra of urinary sedi-
ments confirmed that the main urinary stone form-
ing materials were present at elevated concentra-
tions in the urine of patients with urolithiasis: (i) cal-
cium oxalate monohydrate CaC2O4·H2O (n=5,
33%); (ii) urates: uric acid C5H4N4O3, uric acid dihy-
drate C5H4N4O3·2H2O, and ammonium acid urate
C5H7N5O3(n=4, 27%); (iii) brushite CaHPO4·2H2O
(n=4, 27%); (iv) struvite (NH4)MgPO4·6H2O (n=1,
7%). Those were single-component sediments. One
of the urinary deposits was composed of three dier-
ent components: calcium oxalate monohydrate, hy-
droxyapatite, and calcite. We did not find crystals of
calcium oxalate dehydrate nor the rare compounds,
such as N-acetylsulfametoxazole or other drugs, in
any of the analysed sediments. Since Raman spectra
of sediment constituting materials are distinct, this
likely due to the small size of the sample set limited
by the duration of the project and the low prevalence
of acute neprolithiasis patients in Lithuania, and not
due to limitations of the technique.
Table 1 summarizes the 15 cases of the chem-
ical composition of urinary sediments and chem-
ical composition of urinary stones from the same
patients. At least one molecular compound was the
same among samples coming from the same pa-
tient. However, oxalate stones were always accom-
panied by phosphatic additives, amorphous phos-
phates and hydroxyapatite being the most common.
The phosphates were not found in corresponding
urinary sediments. Instead, brushite and struvite
were found in five urinary sediment samples. Par-
ticularly in the case of brushite sediments, low cor-
relation was observed with the composition of cor-
responding urinary stones, which were constituted
from amorphous phosphates, hydroxyapatite and
calcium oxalate instead. Dierent urates were found
in the urinary sediments, but the urinary stones of
all those patients were composed of uric acid anhy-
drous. In this case, we still consider that the chemical
composition of urinary deposits correlates since uric
acid dihydrate and ammonium acid urate are less
stable forms of urates and can recrystallize into uric
acid anhydrous under decrease in urine pH [36,37].
4. Discussion
Urine saturation with some specific chemical
elements—usually oxalates, phosphates, ammo-
nium ions, and magnesium—is a primary and re-
quired factor for increased risk of urinary stone for-
mation [38]. Nevertheless, initial crystallisation re-
sulting in 10–12 µm single urinary crystals does not
necessarily lead to the formation of a urinary stones
and is common for healthy people [39,40]. Precipi-
tation of significant amounts of crystals and/or suit-
able conditions in the urinary tract is, however, very
likely to lead to the aggregation of small crystals typ-
ically bound by a protein matrix. Such sediments,
which are made of small crystals or are mixed with
an organic matrix, are larger and usually have an
obscure morphology [40]. In addition, some aggre-
gates can consist of several chemical compounds.
Urinary stone formation is much more frequent in
patients with larger size crystals and aggregates in
their urine [41]. Particular attention should be paid
when investigating the chemical composition of such
larger crystals and aggregates. Here we used a FT–
Raman spectrometer that allowed us analysing uri-
nary crystals and aggregates approximately 100 µm
in size. However, even smaller sediments as small
as 1 µm could and should in the future be analysed
using the method by employing objectives of higher
magnification and numerical aperture for tighter
focusing of laser radiation.
Optical microscopy, which is nowadays used in
laboratory medicine, is unable to recognize large sin-
gle or multi-chemical aggregates because of their un-
usual morphology [10,13,41]. The crystals having the
most clinical significance are often left unidentified
or incorrectly identified during routine urinalysis.
FT–Raman spectroscopy proved to be a suitable
method to determine the exact molecular com-
pounds of urinary sediments independent of their
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Sandra Tamosaityte et al. 5
Table 1. Presence of chemical components in urinary sediments and urinary stones among 15 patients
suering from urinary stone disease
Chemical composition
of urinary sediments
Chemical composition of urinary stones Number
of cases
Calcium oxalate monohydrate Calcium oxalate monohydrate +amorphous phosphates 3
Calcium oxalate monohydrate Calcium oxalate monohydrate +hydroxyapatite 2
Uric acid anhydrous Uric acid anhydrous 1
Uric acid dihydrate Uric acid anhydrous 2
Ammonium acid urate Uric acid anhydrous 1
Brushite Calcium oxalate monohydrate +amorphous phosphates 3
Brushite Calcium oxalate monohydrate +hydroxyapatite 1
Struvite Struvite 1
Calcium oxalate monohydrate +
calcite +hydroxyapatite
Struvite +hydroxyapatite +calcium oxalate monohydrate 1
morphology. Figures 1 and 2 illustrate cases when
both typical and atypical crystals of brushite and
struvite were found in samples. Brushite tends to
form crystals shaped as long prisms with one sharp
end and combine into spiky star-like formations as
shown in the upper image of Figure 1. The bottom
image, however, reveals morphologically indescrib-
able sediment. Raman spectra were found to be the
same for both and the sediments were identified as
brushite. A very similar situation was encountered
for atypical sediments and sediments having a de-
fined morphology, both corresponding to struvite
when investigated by means of Raman scattering
It turned out to be challenging to record Ra-
man spectrum of high quality in terms of signal-
to-noise ratio for deposits of calcium oxalate, which
were heated when exposed to the laser radiation
and subsequently thermally damaged. The heating
could be caused by a typically brown colour of the
larger calcium oxalate crystals suggesting presence
of pigments or other types of organic contaminants,
which increase the absorption of the laser radia-
tion and makes them more susceptible to heating.
Therefore, the power of the laser had to be low and
the number of spectra averaged had to be increased
substantially to achieve a signal-to-noise ratio suf-
ficient for spectral analysis. This in turn increased
the time required for the experiment. Importantly,
Raman spectroscopy allows one to distinguish dif-
ferent hydrates of calcium oxalate, which can be
indicative of the dierent aetiology of the urinary
stone and provide important information for sub-
sequent treatment [20]. The most intense spectral
bands of calcium oxalate monohydrate are a doublet
at 1490 cm1and 1463 cm1assigned to symmetrical
νs(COO) stretch vibrations. On the other hand, cal-
cium oxalate dihydrate yields only one spectral band
in this spectral region near 1477 cm1[16]. The Ra-
man spectrum in Figure 3 clearly shows the urinary
sediment to be calcium oxalate monohydrate. It is
not possible to obtain such information from the op-
tical image, since the large, likely aggregated deposit
does not appear in the typical shape of calcium ox-
alate crystals.
Raman spectra are also useful for distinguishing
various types of urates. Uric acid anhydrous and uric
acid dihydrate are the most common urates consti-
tuting urinary stones and urinary sediments. Uric
acid monohydrate is also reported as a possible con-
stituent [42]. Of note, both hydrates are rarely found
in urinary stones, with the hydration possibly lost
during stone growth. We have, however, discerned
the presence of uric acid dihydrate in urinary de-
posits. An example of the atypical morphological
structure of a uric acid dihydrate urinary deposit is
shown in Figure 4 together with the Raman spec-
trum of the deposit. Uric acid anhydrous and ammo-
nium acid urate were also identified as constituents
of urinary sediments in this work. The varying inten-
sities and Raman shifts of the spectral bands related
to the in-plane bending motions of purine rings can
be used as spectral markers for recognition of various
C. R. Chimie Online first, 28th September 2021
6Sandra Tamosaityte et al.
Figure 1. FT–Raman spectrum of brushite urinary sediments (laser power: 180 mW, number of averaged
spectra: 2000) (left) and optical images of typical (top) and atypical (bottom) urinary deposits composed
of brushite.
Figure 2. FT–Raman spectrum of struvite urinary sediments (laser power: 180 mW, number of averaged
spectra: 2000) (left) and optical images of typical (top) and atypical (bottom) urinary deposits composed
of struvite.
FT–Raman scattering spectroscopy proved to be
a reliable method to determine the chemical com-
position of multi-component urinary sediments. As
can be seen from the optical image of the urinary
deposit in Figure 5, it has irregular morphology and
no crystal structure, which makes it very dicult
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Sandra Tamosaityte et al. 7
Figure 3. FT–Raman spectrum (laser power: 9 mW, number of averaged spectra: 170,000) (left) and
optical image (right) of calcium oxalate monohydrate urinary sediment.
Figure 4. FT–Raman spectrum (laser power: 80 mW, number of averaged spectra: 20,000) (left) and
optical image (right) of uric acid urinary sediment.
to determine its chemical composition. On the
contrary, the Raman spectrum of this deposit in-
dicates the three dierent chemical compounds:
calcium oxalate monohydrate, hydroxyapatite, and
calcite. The most intensive spectral band, which is
at 1085 cm1and is characteristic of the vibrations
of the CO2
3group, and the one at 280 cm1repre-
sent CaCO3(calcite) in the sample [43]. A spectral
band at 960 cm1characteristic of hydroxyapatite
can also be observed. All other spectral bands in the
Raman spectrum of this urinary deposit are assigned
to calcium oxalate monohydrate.
The close similarity of the chemical composi-
tion of urinary sediments of patients with the same
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8Sandra Tamosaityte et al.
Figure 5. Optical image of urinary deposit (top left corner), Raman spectra of the deposit (bottom),
and reference chemical compounds indicating calcium oxalate monohydrate, calcite, and hydroxyapatite
Raman spectra.
urinary stone disease indicates that saturation of
urine with specific chemical elements can result in
urinary stone formation. For patients in the risk
group, such as those with increased possibility of re-
currence or with a family history of urinary stones,
the exact evaluation of the chemical components in
urinary sediments could be crucial for prevention
The dierences between the chemical composi-
tion of urinary sediments and urinary stones can also
provide valuable information concerning the pro-
cesses of urinary stone formation. In our study, uric
acid urinary stones were composed of uric acid anhy-
drous, but the urinary deposits of the same patients
were also found to be uric acid dihydrate or ammo-
nium acid urate. This suggests the occurrence of de-
hydration and ion separation processes at the time of
stone formation.
The most significant dierences were found in the
patients having urinary sediments of brushite and
stones having a mixture of calcium oxalate monohy-
drate with amorphous phosphates or with hydrox-
yapatite. Brushite and amorphous phosphates, as
well as calcium oxalate, are formed in high calcium
concentrations. Hydroxyapatite can occur via phase
transformation from brushite [44]. Thus, the exis-
tence of brushite in urine can suggest the exis-
tence of hypercalciuria and formation of calcium
oxalate-phosphate stones. On the other hand, as a
constituent in multicomponent urinary stones, pure
brushite occurrence varies from less than 1% to
about 20% according to various authors [12,45], and
in general it is considered a rare component [16]. For
single component calcium oxalate stones, only cal-
cium oxalate urinary sediments were found.
In this work we provide pilot evidence for the cor-
relation between the chemical composition of uri-
nary sediments and stones, but more patients need
to be included in the study for the results to be statis-
tically reliable. We show that FT–Raman spectroscopy
is suitable for reliably identifying urinary deposits
larger than 100 µm in size with no significant influ-
ence of fluorescence as observed in previous stud-
ies [31,33]. The long spectral acquisition time is the
main limiting factor for the method to be used in a
routine way in clinical practice. This can be alleviated
in the future by using high magnification and numer-
ical aperture objectives (which would also result in
C. R. Chimie Online first, 28th September 2021
Sandra Tamosaityte et al. 9
ability to analyse samples as small as 1 µm) or apply-
ing mathematical noise reduction procedures for low
signal-to-noise spectra [46–48].
Urinary stones are usually diagnosed in an already
late stage of their formation, e.g., only when the pa-
tient starts feeling pain. Regular tests of urinary sed-
iments to determine its exact chemical composition
could be key to early prevention of urinary stone dis-
ease. In this work, Raman spectroscopy proved to be
informative for the chemical identification of both
typical and atypical urinary crystals and crystal clus-
ters. Although this is a pilot study and more patient
cases need to be investigated for the results to be
statistically reliable, spectral analysis of the deposits
could help in prescribing the appropriate preventive
measures, such as diet and lifestyle changes, for peo-
ple at risk of urinary stones. In addition, distinguish-
ing chemical compounds of even the smallest chem-
ical dierences can be of high value in determining
the causes and conditions of the initial formation and
growth processes of urinary stones.
5. Conclusions
FT–Raman spectroscopy is an eective and very sen-
sitive method to determine the chemical composi-
tion of urinary sediments no matter their morpho-
logical structure and is especially useful for the inves-
tigation of unusual crystals and amorphous clusters,
which cannot be identified by optical microscopy
widely used in standard medical practice. Use of
1064 nm NIR laser for excitation of Raman scatter-
ing ensures suppression of fluorescence background
common in biological samples. In contrast to optical
microscopy, the method does not rely on the skills of
laboratory personnel since the Raman spectra pro-
vides direct chemical information at molecular level.
We found correlation between the chemical compo-
sition of urinary stones and urinary sediments, which
suggests that the examination of the sediments by
FT–Raman spectroscopy can be considered a relevant
approach for early diagnosis of urinary stone forma-
tion and determination of appropriate action to pre-
vent this process.
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... For example, it has been used to detect organic compounds, such as additives, pigments, and preservatives in food, as well as in water quality testing, environmental monitoring, and medical fields (Auner et al., 2018). Tamosaityte et al. applied Raman spectroscopy technology to detect and analyze different types of urinary stones, and the results showed that Raman technology can accurately identify different types of urinary stones and achieve a quantitative analysis of their chemical components with high accuracy and reliability (Sandra et al., 2022). Zhu et al. (2022) used a portable Raman system to analyze urine stone samples obtained from 300 patients and demonstrated that Raman spectroscopy can be applied to portable automated analysis systems, which have the characteristics of simple operation, easy automation, and rapid detection in on-site clinical environments. ...
... A small amount of ground test sample was spread on a microscope slide and subjected to Raman spectroscopy. The tested samples were numbered sequentially as S 1 -S 21 , among which the Raman spectrum of uric acid (UA) is shown in Figure 2. The Raman peak at 1,476 cm -1 in (a) was due to the symmetric stretching vibration of C-O in calcium oxalate dihydrate (COD); the Raman peak at 1,463 cm -1 in (b) was due to the C=O vibration of calcium oxalate monohydrate (COM); the Raman peaks at 1,458 cm -1 and 1,490 cm -1 in (c) were both due to the C=O vibration of COM; the Raman peaks at 626 cm -1 in (d), (e), and (f) were due to the ring breathing vibration of the UA molecule; the peaks at 997 cm -1 and 1,037 cm -1 were due to the highly mixed vibration of UA; the Raman peak at 1,648 cm -1 in (e) was due to the C=O stretching vibration of UA; the Raman peak at 1,476 cm -1 in (f) was due to the symmetric stretching of C-O-O in COD; the Raman peak at 896 cm -1 in (g) was due to the C-C stretching of COM, and the Raman peak at 1,630 cm -1 in S 19 was due to the symmetric stretching vibration of C-O in COM; the Raman peak at 910 cm -1 in (h) was due to the C-C shift stretching of COD (Sandra et al., 2022;Selvaraju et al., 2013;Cui et al., 2018). ...
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This contribution is a concise review of nanomaterials in medicine, those designed to treat pathology, those which are induced by pathology, and those which provoke pathology. Clearly, there is a vast family of therapeutic and medically relevant nanomaterials, to which numerous excellent journals and books are dedicated. The purpose of the first section is to illustrate the chemical complexity of research into therapeutic nanomaterials and the challenges in their characterisation. The second section treats that family of nanomaterials induced by diverse pathologies, such as metabolic disorders , infection, or cancer. Here, the challenge is to find characterisation techniques able to provide chemical information at the nanometer scale to enable and enhance early medical diagnosis. Finally, various nanomaterials injected into the human body for esthetic purposes are discussed, specifically tattoo inks which can provoke severe pathologies such as skin cancer.
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This contribution aims to define an analysis procedure for abnormal deposits in human tissues starting from in vivo characterization, down to the nanoscale using major instrumentation. Such an integrated approach is based on recent literature, but particularly on our research over the last twenty years on pathological calcifications. To this end, we begin by describing four successive analytical steps, on the injury site or physician’s surgery, at the hospital, at a typical physicochemical laboratory, and finally at a large scale (possibly multinational) facility. For the first step, we present various techniques which can be implemented on portable instruments. For the second step, commercial analytical setups are used. In a physicochemical laboratory, prototype or commercial setups are used and finally on large scale instruments, characterization techniques with better spatial resolution and/or higher sensitivity or techniques specific to synchrotron radiation are employed.
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2 Dominique Bazin et al. Abstract. Understanding the physico-chemistry related to cristalline pathologies constitutes a challenge in several medical specialities such as nephrology, dermatology or oncology. Regarding nephrol-ogy, the chemical diversity of concretions such as kidney stones calls for characterization techniques to determine the chemical composition of concretions. The starting point of this contribution is given by Fourier Transform InfraRed (FTIR) spectroscopy which is routinely used at the hospital to determine the chemical composition of kidney stones as well as ectopic calcifications present in kidney biopsy. For kidney stones, the quantity of sample is sufficient to perform a significant analysis through classical FTIR. For ectopic calcifications, µFTIR can be inefficient in the case of µcalcification in the tissue when their size is less than 10 µm. For such samples, Optical PhotoThermal IR (OPT-IR) spec-troscopy may constitute a way to overcome this experimental difficulty through the acquisition of IR spectrum with a spatial resolution close to 500 nm. To illustrate such opportunity, we first compare the IR spectrum acquired with a classical experimental setup related to classical IR spectroscopy to IR spectrum collected with a OPT-IR one for different compounds namely calcium oxalate monohydrate, calcium oxalate dehydrate, calcium phosphate apatite and magnesium ammonium phosphate hexahydrate. Such comparison helps us to assess specificity of OPT-IR. Then, we consider several pathological calcifications associated to hyperox-aluria, adenine phosphoribosyltransferase (APRT) deficiency or the presence of Randall's plaque. We will see that the nanometer spatial resolution constitutes a major advantage versus a micrometre one. Also, in the case of Randall's plaque, we show that OPT-IR can determine the chemical composition of microscopic concretion without any kind of preparation. Such experimental fact is clearly a major advantage. Finally, we also extended this first investigation in nephrology by considering breast calci-fications. In that case, if the number of chemical phases is quite low compared to the number of chemical phases identified in ectopic calcifications present in kidney (four instead of 24), the challenge is related to the possibility to distinguish between the different calcium phosphate namely amorphous carbonated calcium phosphate, CA and whitlockite. The complete set of data indicates the limitations and the advantages of OPT-IR spectroscopy.
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This contribution underlines the key role of physicochemical characterisation techniques in the area of medical research. The starting point centres on the Mid-InfraRed platform located at the Tenon hospital and dedicated to multidisciplinary functional investigations. In the last two decades, we have enhanced this platform by creating a network combining researchers from varied disciplines such as physicists, chemists, and clinicians. The resultant research dynamism is underscored by metrics such as 71 references in Pubmed and 129 in Web of Science, and the high impact of the journals in which we have published (New England Journal of Medicine, Kidney International, Chemical Review...). It is of paramount importance to disseminate these physicochemical techniques among young doctors, and to establish collaborations with appropriate private companies.
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Epidermal necrolysis (EN) is a rare life-threatening condition, usually drug-induced and characterised by a diffuse epidermal and mucosal detachment. Calcinosis cutis is reported in various skin diseases, occurring preferentially with tissue damage, but has never been described in EN. Clinical, biological and histopathological characteristics of three patients were retrospectively obtained from medical charts. Immunohistochemistry of classical osteogenic markers was used to explore the pathogenesis of the calcifications; their chemical composition was determined by µFourier transform infra-red (µFTIR) spectroscopy and their localization and morphology by field-emission scanning electron microscopy (FE-SEM). In a recent letter, part of the results of this investigation has been already presented. In this contribution, we have added original data to this previous letter. We have investigated a set of biopsies corresponding to patients who presented atypical healing retardation due to calcinosis cutis. Through FE-SEM observations at the nanometre scale, we describe different areas where are present voluminous calcifications at the surface, submicrometre spherical entities within the papillary dermis and then large “normal” fibres. FE-SEM observations show clearly that “large” calcifications are the result of an agglomeration of small spherical entities. Moreover, micrometre scale spherical entities are the results of an agglomeration of nanometer scale spherical entities. Finally, the last set of data seems to show that the starting point of the calcifications process is “distant” from the epidermis in part of the dermis which appears undamaged. Regarding the chemical composition of large calcifications, different µFTIR maps which underlined the presence of calcium-phosphate apatite have been gathered. Moreover, histopathology indicates that these pathological calcifications are not induced following a trans-differentiation of the skin cells into an osteochondrogenic phenotype. The association of caspofungin administration, known to induce in vitro intracellular calcium influx, and inflammation, induced by EN, known to favor dystrophic calcifications in various inflammatory skin diseases, could explain this never-before reported occurrence of calcinosis cutis.
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This contribution emphasizes the chemical complexity of abnormal cartilaginous deposits. First, we briefly describe some key techniques used to precisely describe their physicochemical characteristics. Then, we present the main chemical and structural characteristics of these two chemical phases, of either biological or synthetic origins. Finally, we discuss selected examples of calcification characterization.
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Although numerous pathologies are associated with abnormal skin deposits, these remain poorly described, as accurate characterization continues to present a challenge for dermatologists. Their submicrometer size as well as their diverse chemistry require various characterization tools.We aim to exemplify characterization of endogenous and exogenous skin deposits in some selected skin diseases using different physico-chemical techniques. We begin with a presentation of selected diseases associated with skin deposits. We then present those of our results which show their variety of structure, location and chemical composition, obtained with various tools: Field Emission Scanning Electron Microscopy coupled with Energy Dispersive X-ray Spectroscopy, X-ray fluorescence, vibrational spectroscopies, as well as techniques specific to synchrotron radiation. Our results constitute a real opportunity to improve diagnosis, and to understand the pathogenesis of many skin diseases, and opportunities for therapeutic intervention.
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Aims: Acute and chronic kidney dysfunction is common in patients with end-stage liver disease. Differentiation between acute kidney injury (AKI) due to hepatorenal syndrome (HRS) or acute tubular necrosis (ATN) remains difficult, however urine cast scoring systems using renal tubular epithelial cells (RTECs) and granular casts (GCs) can help to identify intrinsic kidney diseases. The objective of this study was to evaluate the urine sediment profile of patients with liver disease and hyperbilirubinemia/hyperbilirubinuria and the use of a urine sediment scoring system to identify the most common score in AKI patients and high urine bilirubin concentrations. Materials and methods: A retrospective study in the database of a large laboratory that assists a hospital-complex in Brazil was performed. Results: Urinary casts, in particular GCs, as well as RTECs were observed more frequently in patients with hyperbilirubinemia/hyperbilirubinuria, while hyaline casts were observed in patients without hyperbilirubinemia/hyperbilirubinuria. Regardless of the AKI or non-AKI condition, the relative risk for scores 2 or 3 (sediment consistent with tubular damage, with GCs and/or RTECs in different quantities) in group 4 was 3.61 times higher compared to patients in group 1. Conclusion: In patients with higher urinary bilirubin levels, the urine sediment had greater numbers of GCs and RTECs and higher urine sediment scores (scores 2 or 3). The presence of a larger number of urine particles (RTECs and GCs) originating in the kidneys in the groups with higher levels of urinary bilirubin suggests an association between hyperbilirubinemia/hyperbilirubinuria and tubular injury independent of AKI or non-AKI. .
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In Asia, about 1%–19.1% of the population suffer from urolithiasis. However, due to variations in socio-economic status and geographic locations, the prevalence and incidence have changed in different countries or regions over the years. The research for risk factors of urinary tract stones is of predominant importance. In this review, we find the prevalence of urolithiasis is 5%–19.1% in West Asia, Southeast Asia, South Asia, as well as some developed countries (South Korea and Japan), whereas, it is only 1%–8% in most part of East Asia and North Asia. The recurrence rate ranges from 21% to 53% after 3–5 years. Calcium oxalate (75%–90%) is the most frequent component of calculi, followed by uric acid (5%−20%), calcium phosphate (6%−13%), struvite (2%−15%), apatite (1%) and cystine (0.5%−1%). The incidence of urolithiasis reaches its peak in population aged over 30 years. Males are more likely to suffer from urinary calculi. Because of different dietary habits or genetic background, differences of prevalence among races or nationalities also exist. Genetic mutation of specific locus may contribute to the formation of different kinds of calculi. Dietary habits (westernized dietary habits and less fluid intake), as well as climatic factors (hot temperature and many hours of exposure to sunshine) play a crucial role in the development of stones. Other diseases, especially metabolic syndrome, may also contribute to urinary tract stones.
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Background and objectives The kidney stone’s structure might provide clinical information in addition to the stone composition. The Raman chemical imaging is a technology used for the production of two-dimension maps of the constituents' distribution in samples. We aimed at determining the use of Raman chemical imaging in urinary stone analysis. Material and methods Fourteen calculi were analyzed by Raman chemical imaging using a confocal Raman microspectrophotometer. They were selected according to their heterogeneous composition and morphology. Raman chemical imaging was performed on the whole section of stones. Once acquired, the data were baseline corrected and analyzed by MCR-ALS. Results were then compared to the spectra obtained by Fourier Transform Infrared spectroscopy. Results Raman chemical imaging succeeded in identifying almost all the chemical components of each sample, including monohydrate and dihydrate calcium oxalate, anhydrous and dihydrate uric acid, apatite, struvite, brushite, and rare chemicals like whitlockite, ammonium urate and drugs. However, proteins couldn't be detected because of the huge autofluorescence background and the small concentration of these poor Raman scatterers. Carbapatite and calcium oxalate were correctly detected even when they represented less than 5 percent of the whole stones. Moreover, Raman chemical imaging provided the distribution of components within the stones: nuclei were accurately identified, as well as thin layers of other components. Conversion of dihydrate to monohydrate calcium oxalate was correctly observed in the centre of one sample. The calcium oxalate monohydrate had different Raman spectra according to its localization. Conclusion Raman chemical imaging showed a good accuracy in comparison with infrared spectroscopy in identifying components of kidney stones. This analysis was also useful in determining the organization of components within stones, which help locating constituents in low quantity, such as nuclei. However, this analysis is time-consuming, making it more suitable for research studies rather than routine analysis.
The examination of the urinary sediment of a 64-year-old woman showed the presence of three different types of crystals, all with unusual morphology, which could not be identified with bright field microscopy, polarized light, and the knowledge of urine pH (7.5). The use of microscopic infrared spectroscopy, Raman spectroscopy and energy dispersive X-ray spectroscopy led to the identification of the three types of crystals as calcite, vaterite and aragonite, which are all variants of calcium carbonate crystals. This paper confirms the complex morphology and nature that urinary crystals may at times have and the utility of advanced infrared spectroscopy techniques for their identification.
Raman spectroscopy is a non-destructive technique utilizing lasers to observe scattered light in order to determine things such as vibrational modes in the molecular system. A major problem inherent to this technique is that due to their short exposure time and the low power of the excitation laser, Raman signals are very weak. They tend to be much weaker than the noise and can even be drowned out. Conventional denoising methods are currently unable to extract Raman peaks with precision so it is necessary to specifically study Raman signal extraction methods that involve a low signal-to-noise ratio (SNR). In this study, a denoising method for Raman spectra with low SNR based on feature extraction was proposed. Based on the Hilbert Vibration Decomposition (HVD) method, the Raman spectra was decomposed into two components. The peaks were located in the first component and compensated by those in the second component. Then based on the position and height of the peaks, their full widths at half maximum (FWHM) are calculated. Finally, based on the position, height and FWHM of the peaks, Gaussian signals are used to reconstruct the Raman peaks from strong noise and baseline. In the data simulation experiment, the denoising method used improved the SNR from 3.5316 to 130.6386 and the mean square error (MSE) was reduced from 213.8635 to 14.0404. In the actual experiment, this method successfully extracted the characteristic peaks of melamine despite the noise from employing a low excitation laser (10 mW). The characteristics such as the amplitude and position of the peaks were identical to those obtained under a high excitation laser (150 mW). The error of the FWHM under different excitation laser powers (10 and 150 mW) was less than the spectral resolution. Using the method proposed in this paper, the Raman signal of biological samples such as rice leaves were extracted from the raw spectrum, and information on the spectral peak position, amplitude and FWHM were obtained with clarity. The characteristic peaks of the carotene molecule, protein amide I, protein phenylalanine, nucleic acid cytosine, cellulose, DNA phosphodiester, RNA phosphodiester, D-glucose, α-D glucose, chlorophyll, lignin and cellulose were all accurate as well. The results from the simulation data and actual experiments show that a method based on feature extraction can effectively extract Raman peaks even when they are submerged in background noise. It should be noted that the practicality of this method lies in the fact that it requires few parameters and is simple to operate and implement.
Urolithiasis is a common urological disease with a very high recurrence rate, within 5 years. Urine stones are formed by urine crystals. Although the relationship between the composition of the urine stone and the type of urine crystal has been recognized, the efficient collection and accurate identification of the type of urine crystal in clinics remains a challenge. In this study, we develop an automatic Raman spectroscopic urine crystal collection and identification system. Custom‐developed Fe3O4 crystal violet nanoclusters are used for (a) separating the urine crystals from the urine samples by a custom‐developed urine processing system and for (b) fluorescent labeling, image guiding, and the Raman spectroscopic measurement of the urine crystals on a 2D scanning stage. The control of the system and the Raman spectroscopic analysis are developed in a LabVIEW environment. This system is a fast and convenient method for the efficient collection and analysis of urinary crystals from urine samples, within 9 min. This automatic urine crystal identification system can enable the early prediction of the types of urine stones and the diet management for urolithiasis patients. In this study, we develop an automatic Raman spectroscopic urine crystal collection and identification system. Custom‐developed Fe3O4 crystal violet nanoclusters are used for (a) separating the urine crystals from the urine samples by a custom‐developed urine processing system and for (b) fluorescent labeling, image guiding, and the Raman spectroscopic measurement of the urine crystals on a 2D scanning stage. Raman spectra from urine crystal obtained with the LabVIEW platform (a). The bright field and the fluorescence field as shown in (b), the surface of the urine crystals displayed a dark color in the bright field because of the coating of the Fe3O4 nanoclusters.
Automated urine technology and centralized laboratory testing are becoming the standard for providing urinalysis data to clinicians, including nephrologists. This trend has had the unintended consequence of making examination of urine sediment by nephrologists a relatively rare event. In addition, the nephrology community appears to have lost interest in and forgotten the utility of provider-performed urine microscopy. However, it is critical to remember that urine sediment examination remains a time-honored test that provides a wealth of information about the patient's underlying kidney disease. This test performs very favorably as a urinary "biomarker" for a number of acute kidney diseases. When used properly, urine sediment findings alert health care providers to the presence of kidney disease, while also providing diagnostic information that often identifies the compartment of kidney injury. Urine sediment findings may also guide therapy and assist in prognostication. In this review of the role of urine sediment examination in the diagnosis and management of kidney disease, we seek to help experienced nephrologists maintain their competency in performing this test and encourage ongoing training of nephrology fellows and others less experienced in such analyses.
The number of patients with kidney stones worldwide is increasing, and it is particularly important to facilitate accurate diagnosis methods. Accurate analysis of the type of kidney stones plays a crucial role in the patient's follow-up treatment. This study used microscopic Raman spectroscopy to analyze and classify the different mineral components present in kidney stones. There were several Raman changes observed for the different types of kidney stones and the four types were oxalates, phosphates, purines and L-cystine kidney stones. We then combined machine learning techniques with Raman spectroscopy. KNN and SVM combinations with PCA (PCA-KNN, PCA-SVM) methods were implemented to classify the same spectral data set. The results show the diagnostic accuracies are 96.3% for the PCA-KNN and PCA-SVM methods with high sensitivity (0.963, 0.963) and specificity (0.995,0.985). The experimental Raman spectra results of kidney stones show the proposed method has high classification accuracy. This approach can provide support for physicians making treatment recommendations to patients with kidney stones.
Raman spectroscopy has been demonstrated to have diagnostic potential in areas such as urine and cervical cytology, whereby different disease groups can be classified based on subtle differences in the cell or tissue spectra using various multi-variate statistical classification tools. However, Raman scattering is an inherently weak process, which often results in low signal to noise ratios, thus limiting the method's diagnostic capabilities under certain conditions. A common approach for reducing the experimental noise is Savitzky-Golay smoothing. While this method is effective in reducing the noise signal, it has the undesirable effect of smoothing the underlying Raman features, compromising their discriminative utility. Maximum Likelihood Estimation is a method for estimating the parameters of a statistical model given an available dataset and a priori knowledge of the model type. In this paper, we demonstrate how Savitzky-Golay smoothing may be enhanced with Maximum Likelihood Estimation in order to prevent significant deviation from the 'true' Raman signal yet retain the robust smoothing properties of the Savitzky-Golay filter. The algorithm presented here is demonstrated to have a lower impact on Raman spectral features at known spectral peaks while providing superior denoising capabilities, when compared with established smoothing algorithms; artificially noised databases and experimental data are used to evaluate and compare the performance of the algorithms in terms of the signal to noise ratio. The proposed method is demonstrated to typically provide at least a 50% increase in the signal to noise ratio when compared to the raw data, and consistently out-performs two alternative smoothing filters. MATLAB code is provided in the appendix.
Noise, especially high‐level noise, is a severe problem in Raman spectral analysis. It smears informative Raman peaks, distorts spectral features, and therefore affects final analytical results, particularly in multivariate analysis, which is frequently used in Raman spectroscopy. This becomes even worse when it comes to optical Raman probe‐based biological applications due to limited acquisition time, laser power, and collection efficiency. Noise suppression is usually the first step in the preprocessing procedure of Raman spectral analysis. It is crucial to reduce noise effectively before performing further analysis. Discrete wavelet transform is a useful tool for noise reduction. However, it only provides limited and fixed filter banks, which may not be optimal for the data under investigation. In this paper, a novel adaptive denoising method based on lifting wavelet transform is presented for improving the signal‐to‐noise ratio for a Raman probe‐based system. It enables users to develop an infinite number of lifting schemes from a base wavelet, and with the help of genetic algorithm, the optimal one can be easily found. This method is examined by a set of simulated Raman spectra with various noise level and a set of experimental Raman spectra. Performance comparison with other commonly used denoising methods is made. The results indicate that the proposed method is able to remove noise effectively while retaining informative Raman peaks satisfactorily. A novel method based on lifting wavelet transform for random noise reduction in Raman spectroscopy is presented. By applying genetic algorithm, an optimal elementary lifting step is obtained to form the second generation from a chosen base wavelet using lifting scheme. The newly generated wavelet is more suitable to the spectral data at hand than the base wavelet. Test results on single Raman spectra and a classification dataset show the effectiveness of this denoising method.