Infrared Spectroscopy in Clinical and Diagnostic Analysis

20 Pages·2000·0.388 MB·English

by  Shaw R.A., Mantsch H.H.

1
INFRAREDSPECTROSCOPYINCLINICALANDDIAGNOSTICANALYSIS
Infrared Spectroscopy in The infrared spectrum of a mixture serves as the basis
to quantitate its constituents, and a number of common
Clinical and Diagnostic
clinicalchemistrytestshaveproventobefeasibleusingthis
approach. This article reviews the infrared spectroscopy-
Analysis
based analytical methods that have been developed for
considerationasclinicalassays,includingserumanalysis,
urine analysis, amniotic fluid assays for the estimation of
R.AnthonyShawandHenryH.Mantsch
fetallungmaturity,andothers.Becauseofthewidespread
InstituteforBiodiagnostics,NationalResearch
interest in the potential for in vivo measurement of
CouncilofCanada,Winnipeg,Canada
bloodglucoseusingnear-infraredspectroscopy,aseparate
section is devoted to the analysis of glucose in whole
blood.
1 Introduction 1 A related technique uses the infrared spectrum of
biomedical specimens directly as a diagnostic tool. For
2 Infrared Spectroscopy of Biological
example, the spectra of serum and of synovial fluid have
Fluids 2
proventobeusefulinthediagnosisofmetabolicdisorders
2.1 Mid-infrared Attenuated Total
and arthritis, respectively, without explicitly recovering
Reflectance Spectroscopy 3
their chemical composition from the spectra. Rather,
2.2 Mid-infrared Spectroscopy of Dried
characteristic spectral features and patterns have been
Films 3
identifiedasthebasistodistinguishspectracorresponding
2.3 Near-infrared Spectroscopy 4
to healthy patients from those corresponding to diseased
3 Calibration Methods 4 patients.Theseapplicationsarereviewedhere.
3.1 Multiple-wavelength Linear Issuessuchaseaseofuse,speed,reliability,samplesize,
Regression 5 and calibration stability all play important roles in gov-
3.2 Principal Component Regression erningthepracticalacceptabilityofinfraredspectroscopy-
and Partial Least Squares 6 based analytical methods. To provide a framework to
3.3 Spectral Preprocessing 6 illustratetheseissues,descriptionsareincludedforthevar-
4 Serum Analysis 6 iousproceduresthathavebeenexploredtowedsuccessfully
4.1 Infrared Spectroscopy of Serum 6 infraredspectroscopytoclinicalchemistry.
4.2 Serum Analysis using Near-infrared
Spectroscopy 7
4.3 Serum Analysis using Mid-infrared
1 INTRODUCTION
Spectroscopy 10
5 Serum and Blood Glucose 14
Infrared (IR) spectroscopy has emerged in recent years
6 Fetal Lung Maturity Determined by
astheanalyticalmethodofchoiceinanenormousvariety
Infrared Spectroscopy 14
of applications. What brought about this revolution?
7 Other Fluids 15 The clearest advantage is that no specific reagents are
7.1 Urine Analysis 15 required.Automated,repetitiveanalysescanthereforebe
7.2 Saliva 16 carriedoutatverylowcost.Theappealofthesefactorshas
8 Disease Diagnosis Based on Infrared spurredthedevelopmentofanewgenerationofanalytical
Spectral Pattern Recognition 17 IR spectrometers that combine high acquisition speed
8.1 Arthritis Diagnosis from Infrared with superb spectral sensitivity. Powerful chemometric
Spectroscopy of Synovial Fluid 17 algorithms and software packages have emerged in
8.2 Disease Pattern Recognition in Mid- parallel with the new hardware, and new applications
infrared Spectra of Serum 18 emergecontinually.
Rather than relying upon reagents to promote color
9 Summary 18
reactions,IR-basedanalysisisfoundeduponthespectrum
Acknowledgments 18 of IR colors characteristic of the analyte itself. If
Abbreviations and Acronyms 18 a particular component provides an IR absorption
spectrum, and its concentration is high enough that the
Related Articles 18
spectrum contributes meaningfully to the IR absorption
References 19
profile, then it may, in principle, be quantified by using
IR spectroscopy. Although the requirement that the
EncyclopediaofAnalyticalChemistry
EditedbyRobertA.Meyers.(cid:211) JohnWiley&SonsLtd,Chichester.ISBN0471976709
2
BIOMEDICALSPECTROSCOPY
componentexhibitsanIRabsorptionspectrumrulesout units,generallyinnanometers.TheNIRspanstherange
thequantitationofsimpleions,anumberofverycommon 780–2500nm,encompassingweaktransitionsthatcorre-
clinical analytical tests may, in principle, be carried out spond to combinations and overtones of the vibrational
usingIRspectroscopy. modes observed in the MIR. Because NIR absorptions
This articlebegins bycomparing andcontrasting mid- are generally broad and therefore strongly overlapping,
infrared (MIR) and near-infrared (NIR) spectroscopy it is difficult or impossible to arrive at specific assign-
in the context of analytical applications. The second ments for individual absorptions in the NIR. Partly for
section describes the general approach to generating that reason, these transitions were long ignored by the
an IR-based quantitation method. Although Beer’s law spectroscopiccommunities(indeedbyallcommunities!),
generally holds true for common analytes in biological although their potential for use in analytical work was
fluids, it is very unusual to find a single absorption noted as early as the mid-1950s..1/ By the end of the
that can be used as the basis to quantify any single followingdecade,thetechniquehadcaughttheattention
component in real-life samples. Analytical methods that of the agricultural community as a possible means to
are based upon IR spectroscopy must nearly always determine protein, oil, and moisture content of agricul-
be calibrated by reference to accepted clinical analyses, tural commodities. In this application and many others
usingmultiple-wavelengthlinearregressionorotherfull- developedsince,theinherentlyweakabsorptionsproved
spectrummethods. advantageous,permittingtheconvenienceoflongeropti-
The function of the clinical chemistry laboratory is to calpathlengthsthanarefeasibleinMIRwork,andhence
perform quantitative and qualitative analyses on body relativelyeasysamplehandling.Sincetheseminalworkof
fluidssuchasserum,blood,urine,andspinalfluid,aswell Norris,.2/ Williams,.3/ and others, NIR spectroscopy has
as other materials such as tissue, calculi, and feces. The largely matured, and now finds acceptance in an enor-
main body of this article describes IR-based methods to mous variety of analytical applications. The majority of
carry out some of the most common clinical analytical NIR spectrometers manufactured today are customized
tests,specificallythoseinvolvingserum,wholeblood,and foranalyticalapplications,includingappropriatesoftware
urine. Fluids that are less commonly assayed (e.g. saliva andsimplifieduserinterfacesforroutineoperation.
and amniotic fluid) are also discussed separately. NIR In considering the use of IR spectroscopy for clinical
spectroscopy has achieved some notoriety in the clinical analyses, we are confronted with the fact that the most
chemistryarenabecauseoftheearlypromisethatitmight abundantspeciesfoundinallbiologicalfluidsiswater,and
serve as the basis for a noninvasive blood glucose test. theIRspectrareflectthisfact.Toillustratethedominance
Some relevant in vitro studies are surveyed briefly here. of water in the IR spectra, Figures1 and 2 depict the
The article closes with a discussion of novel approaches absorptionprofilesfornativeserumintheMIRandNIR
toderivediagnosisdirectly,withoutexplicitquantitative spectral regions. Although some of the stronger solute
analysis,fromthespectraofbiologicalfluids. absorptionsdoemergeintheMIRspectra,waterclearly
dominates the overall appearance. The NIR spectra are
2 INFRAREDSPECTROSCOPYOF
1.6
BIOLOGICALFLUIDS
1.2 · 0.5
The IR spectral region ranges from the red end of e Serum
c
the visible spectrum at 780nm (12820cm(cid:0)1) to the n
a Water
onset of the microwave region at a wavelength of 1mm b 0.8
r
(10cm(cid:0)1). Traditionally, this range isfurther subdivided o
s
into the near-infrared (NIR), mid-infrared (MIR), and b
A 0.4
far-infrared (FIR). The MIR region covers the range · 5
400–4000cm(cid:0)1, and is the region most familiar to the
organicchemistasprovidinga‘‘fingerprint’’characteristic 0.0
800 1600 2400 3200 4000
ofmolecularspecies.Itisthisregionthatincludestherich
spectrum of absorptions corresponding to fundamental Wavenumber (cm- 1)
vibrationsofthespeciesbeingprobed.
Figure1 MIR absorption spectra of serum and of water,
Although MIR absorption positions are almost uni-
collectedwithanopticalpathlengthof6m m.Thelowertraceisa
versally reported in units of wavenumbers (cm(cid:0)1; the
differencespectrum,withthespectrumofwatersubtractedfrom
inverse of the wavelength in centimeters), it remains that of serum. Note the tenfold difference in the absorbance
the norm for NIR spectra to be reported in wavelength scales.
3
INFRAREDSPECTROSCOPYINCLINICALANDDIAGNOSTICANALYSIS
2.1 Mid-infraredAttenuatedTotalReflectance
Spectroscopy
2.0
· 0.5 Attenuated total reflectance (ATR) spectroscopy pro-
e 1.5 Serum videsanalternativemeanstomeasureabsorptionspectra
c
n by using the experimental arrangement illustrated in
a Water
b 1.0 Figure3.Theclearestadvantageofthismethodisthatit
r
o provides a means to measure MIR spectra for strongly
s
Ab 0.5 absorbing aqueous solutions, without the inconvenience
· 35 and imprecision involved in working at very short path
lengths that are required for transmission spectroscopy.
0.0
Rather than transmitting IR radiation through the spec-
800 1000 1200 1400 1600 1800 2000 2200 2400 imen, the liquid sample is placed in contact with the
Wavelength (nm) ATR optical element..4;5/ The refractive index of the
element (typically zinc selenide) is high enough that
Figure2 NIR absorption spectra of serum and of water, the IR beam propagating through it undergoes several
collected with an optical path length of 0.5mm. The lower internal reflections as it travels through the crystal. A
trace is a difference spectrum, with the spectrum of water
backgroundspectrumisfirstmeasuredwithnosamplein
subtracted from that of serum. Note the 70-fold difference in
thecell.Thesampleisthenplacedincontactwiththecrys-
theabsorbancescales.
tal. The internally reflected beam effectively penetrates
the sample to depths of 0.5–2m m and hence is attenu-
apparentlydevoidofanyabsorptionsotherthanthoseof atedatwavelengthscorrespondingtosampleabsorptions.
water. Ratioing the resulting single-beam spectrum against the
MIR and NIR spectroscopies in fact offer quite backgroundspectrumresultsinaspectrumthatisnearly
different, complementary, approaches to analysis. The identical to the absorption spectrum, differing only by
richness of the MIR spectrum makes it instinctively virtue of the wavelength dependence of the penetration
appealing as the method of choice for analytical work, depth.
howeverNIRhaspracticalbenefitssuchasconveniencein
samplehandlingandthefactthatthesamplecellsdonot
2.2 Mid-infraredSpectroscopyofDriedFilms
requirespecializedmaterials.WhereasMIRspectroscopy
This approach finesses the difficulties associated with
of aqueous specimens typically requires optical path
strong water absorptions by simply eliminating water
lengthsoftheorderofmicrons,NIRtransmissionspectra
fromthespecimen.Typically5–50m Lofliquidisspread
are generally collected using path lengths of 0.5mm or
on a suitable substrate and allowed to dry, and a
greater. The question of whether to use NIR or MIR
transmissionspectrumisacquiredfortheresultingfilm.In
spectroscopy for analytical purposes then translates to
additiontoeliminatingthespectralinterferenceofwater,
the question of whether the additional effort generally
requiredtoacquireMIRspectraiscompensatedbyother
possible benefits such as greater analytical accuracy or 0.8
smallersamplevolume. Dried serum film
e 0.6
c
n
Sample a
b 0.4
r
o
s
b
A 0.2 -N
C
S
IR in IR out
0.0
800 1600 2400 3200 4000
Wavenumber (cm- 1)
Optical element Figure4 Absorption(transmission)spectrumforaserumfilm
dried onto a barium fluoride window. The specimen was
Figure3 Apparatus to measure the ATR spectrum for a first diluted twofold in aqueous 4gL(cid:0)1 potassium thiocyanate
liquid specimen. The ATR spectrum is derived by ratioing (KSCN) solution. The absorption of SCN(cid:0) at 2060cm(cid:0)1 was
thesingle-beamspectrummeasuredwiththespecimeninplace usedforsubsequentnormalizationofthespectraaspartofthe
againstasingle-beamspectrumforthecleanopticalelement. developmentofquantitationmodels(seeShawetal..23/).
4
BIOMEDICALSPECTROSCOPY
this approach can provide inherently better spectral 3 CALIBRATIONMETHODS
resolution by virtue of eliminating the water/solute
interactions. A representative spectrum of a dry serum Inthevastmajorityofcases,IR-basedanalyticalmethods
filmisillustratedinFigure4. are developed via calibration to accepted reference
analyses.Theterm‘‘calibration’’thereforedescribesthe
derivationofamodelwithwhichtorecoverquantitative
2.3 Near-infraredSpectroscopy analyticalinformationfromtheIRspectra.Althoughthis
step is obviously a trivial one for very simple one- or
Although the NIR is defined as encompassing the two-componentsystems,morecomplexmixturesrequire
780–2500nm spectral range, it is convenient to sub- amoresophisticatedapproach.
divide further this span into natural subregions. The The general procedure is the same regardless of the
2000–2500nm range includes the most intense absorp- detailsoftheprocess.Thefirststageistoaccumulateboth
tions and thus is the region most commonly exploited IR spectra and reference assays for a set of appropriate
for analytical purposes. Absorptions in this region clinicalspecimens.Ideally,thissetofcalibrationsamples
correspond to ‘‘combination bands’’, combining X(cid:0)H should span the range of concentrations expected both
(where XDC, N, O) stretches with other fundamen- fortheanalyteofinterestandforanyinterferingspecies
tal vibrations, whereas practically all of the higher (i.e. any IR absorber other than the target compound).
energy transitions correspond to vibrational first (1400– Separatecalibrationmodelsarethendevelopedforeach
1800nm), second (950–1250nm), and third overtones of the target analytes. Finally, each of the calibration
(Table1). models is validated by comparing IR-predicted levels to
The diversity of transitions in the NIR region has the reference levels determined for an independent set
interestingpracticalconsequences.Foraqueoussolutions, oftestspecimens.Anoutlineofthemodeldevelopment
the 2000–2500nm region is best explored by using processispresentedinTable2.
a transmission cell with an optical path length of Thissectionintroducesthreeofthemorecommontech-
0.5–2.5mm. The optimal path length to observe the niques: multiple-wavelength linear regression (MLR),
first overtone transitions is longer–of the order of
5–10mm–whereasobservationofthesecondovertones Table2 DevelopmentofanIR-basedclinicalanalytical
requires a path length of several centimeters. Where method
sample volume is a consideration, a relatively short
Preparation
path length is a necessity and the combination region
(cid:15) Collectclinicalspecimens
is therefore preferred. Another outgrowth of this trend
(cid:15) Carryoutreferenceanalysesforspeciesofinterest
is that tissue is relatively transparent at shorter NIR (cid:15) MeasurecorrespondingIRspectra
wavelengths. A key consideration in the search for in (cid:15) Designatetwo-thirdsofthetotalnumberofspectraasthe
vivo analytical methods (e.g.blood glucose) is therefore calibrationsetandtheremainingone-thirdofspectraasthe
validationset
toarrangetheexperimentsuchthattheeffectiveoptical
(cid:15) Preprocessspectra
pathlengthisoptimizedfortheappropriateanalyteNIR
Calibration
absorption features. A proposed in vivo method based
(cid:15) Choosemodelingmethod(e.g.MLR,PLS,PCR)
uponthecombinationbandswillrequireashorteffective
(cid:15) Generatemodelsrangingincomplexityfromaveryfew
path length, whereas a method that monitors second
variables(wavelengthtermsforMLR;factorsforPLS,
overtoneabsorptionswouldrequireamuchlongerone. PCR)tomanyvariables
(cid:15) Predictconcentrationsusingallmodelsandcompareto
referenceanalyses
(cid:15) Identifyoutliersandcorrectorremoveasappropriate
Table1 NIRvibrationaltransitions (cid:15) Recalibratemodelswithoutliersremoved
(cid:15) Evaluatestandarderrorsofcalibrationandcross-validation
NIRspectral Natureofvibrational foreachmodelandplotasafunctionofthenumberof
range(nm) transitions variablesinthemodel
2200–2450 C(cid:0)Hstretchcombinations Validation
2000–2200 N(cid:0)H,O(cid:0)Hstretchcombinations (cid:15) Predictconcentrationsusingallmodelsandcompareto
1650–1800 C(cid:0)Hstretch,1stovertones referenceanalyses
1400–1500 N(cid:0)H,O(cid:0)Hstretch,1stovertones (cid:15) Evaluatestandarderrorofpredictionforeachmodeland
1100–1225 C(cid:0)Hstretch,2ndovertones plotasafunctionofthenumberofvariablesinthemodel
950–1100 N(cid:0)H,O(cid:0)Hstretch,2ndovertones
850–950 C(cid:0)Hstretch,3rdovertones Where IR methods are sought for more than one species, the
775–850 N(cid:0)Hstretch,3rdovertones calibration/validationprocedureiscarriedoutindependentlyforeach
analyte.
5
INFRAREDSPECTROSCOPYINCLINICALANDDIAGNOSTICANALYSIS
principal component regression(PCR), and partial least the NIR region of 2050–2500nm, together with the
squares(PLS). spectra of five aqueous urea solutions spanning the
concentration range 30–230mmolL(cid:0)1. In this instance
the spectral features due to urea clearly dominate
3.1 Multiple-wavelengthLinearRegression
the urine spectra, and it is not surprising that a
This approach is simply an extension of Beer’s law single-wavelengthBeer’slawrelationshipprovidedquite
to include multiple wavelengths. The need for several good accuracy in extracting the urea concentrations.
wavelengths is dictated by the inherent richness of the In particular, the intensity of the feature at 2152nm
IR spectra–it is generally difficult or impossible to find proved sufficient to recover urea concentrations with
asingleabsorptioncorrespondingtoaparticularanalyte a standard error of 20mmolL(cid:0)1 over the physiological
that is not overlapped bythe absorptions of atleast one concentrationrangeof100–500mmolL(cid:0)1.Theaccuracy
other constituent. The Beer’s law relationship shown in wasimproved,however,byincludingadditionaltermsas
Equation(1): showninEquation(4):
(cid:20) (cid:21)
ADecL .1/ A.2152nm/
C.urea/D(cid:0)10C68 C1:3
A.1194nm/
isthereforereplacedbythemoregeneralformshownin
Equation(2): (cid:2)105A.1724nm/ .4/
X
AD ecL .2/ There are two new wavelengths in this model. The first,
i i
at 1194nm, corresponds to a weak water absorption.
where A is the absorbance, ei is the molar absorptivity The most common rationale for including such a term
of the ith constituent, ci is the concentration of the as a divisor of the primary wavelength is to correct for
ith constituent, and L is the optical path length. The fluctuationsintheeffectiveopticalpathlength,generally
expression relating the concentration to IR absorption causedbylightscatteringduetoparticulatematterinthe
intensitiesthentakestheformofEquation(3): sample.Thesecondnewterm,at1724nm,correspondsto
aweakproteinabsorption.Thisterm,particularlyinthose
c DK CK A.l /CK A.l /C(cid:1)(cid:1)(cid:1)CK A.l / .3/
i 0i 1i 1 2i 2 Ni N sampleswithunusuallyhighproteinlevels,mayserveto
correctforthecontributionofproteinabsorptionstothe
where K are the calibration coefficients for the ith
Ni
intensityat2152nm.
constituent, and l are the corresponding analytical
N
Foranalytesthatdonotyieldprominentabsorptionsin
wavelengths.
thespectraofthetargetspecimens,thesimplesingle-term
This approach is most readily applied when the
Beer’slaw relationship fails completely. One solution in
spectra show dominant absorptions corresponding to
this caseis again to assumeasolution of the typerepre-
the analyte of interest. This proved to be the case in
the NIR analysis of urine urea..6/ Figure5 compares sented by Equation(3),whereupon the task becomes to
determinehowmanyandwhichwavelengths/frequencies
the spectra of five representative urine specimens in
should be included in the analysis. One approach is to
regressthesetofspectralintensities,foreachwavelength,
against the analyte concentrations for the calibration
Urea
specimens.The single wavelength that provides the best
correlation with concentration is then taken as the ‘‘pri-
mary’’ wavelength, and further regressions are carried
out holding the primary wavelength fixed to determine
Urine additional terms to complement the single-term model.
Thesameprocessmaybeusedtodeterminedivisorterms
(seethefirsttermofEquation4).
ThestepwiseregressionapproachtodeterminingMLR
terms is not guaranteed to find the optimal set of
wavelengths, particularly for complex specimens where
2000 2100 2200 2300 2400
many terms may be required. The general problem is
Wavelength (nm)
illustratedbythefactthatinasetofcalibrationspectra,
each comprising 2000 absorbance values, there are
Figure5 NIR spectra (second derivatives, inverted) for a
2:5(cid:2)1026 possible eight-term wavelength combinations.
representative set of nine urine specimens (lower traces) and
forfiveaqueousureasamplesrangingfrom30to230mmolL(cid:0)1 Brute-force evaluation of all possible eight-term MLR
(uppertraces). models is clearly out of the question, and there is an
6
BIOMEDICALSPECTROSCOPY
ongoing search for more efficient methods..7/ Recent 3.3 SpectralPreprocessing
developments include genetic algorithms to identify the It is almost always necessary, or at least desirable, to
optimal spectral regions. For example, an algorithm preprocesstheabsorptionspectrainsomefashion;theaim
originally developed to identify diagnostic patterns in istoenhancethespectralfeaturesthatcarryinformation
magneticresonancespectra.8/hasbeenmodifiedrecently regarding the analyte of interest, and effectively to
toseekoutoptimalspectralsubregionsforMLR. suppress or eliminate superfluous features. The simplest
form of ‘‘preprocessing’’ is the selection of appropriate
wavelengthsinMLRmodeldevelopment;theanalogyin
3.2 PrincipalComponentRegressionandPartialLeast
PLSandPCRistheselectionofalimitedspectralregion
Squares
(orregions).
Thefeaturecommontobothoftheseapproachesisthat The most common procedures are mean centering,
each spectrum is reduced to a sum of pseudospectra, or variance scaling, and derivation. Mean centering simply
‘‘loadingvectors’’.Eachspectrumisnewlyrepresentedby subtractstheaverageofthecalibrationspectrafromeach
auniquesetof‘‘scores’’–thesetofcoefficientsrequired of the individual spectra. Variance scaling involves first
to reconstruct the original spectrum from the set of evaluating the standard deviation among spectrafor the
loading vectors. Typically, each of the spectra can be intensityateachwavelength.Allspectraarethendivided
reconstructedtowithinthenoiselimitsbyacombination bythepseudospectrumofstandarddeviations,andhence
of typically 5–15 loading vectors, as compared to the scaled so that the variance is unity at all wavelengths.
hundredsorthousandsofintensityvaluesintheoriginal This operation effectively enhances the prominence of
spectra.Thescoresthenprovidethebasisforquantitation. features due to species of relatively low concentration,
The essential relationship in both the PCR and PLS whilesuppressingtheintensitiesofstrong(andvariable)
modelstakestheformofEquation(5): absorptions.Theprocedureisthereforemostappropriate
for the analysis of minor components. Derivation is
ADTBCE .5/ commonly used to eliminate random fluctuations in the
A
baseline (first derivative) and slope (second derivative)
With m spectra in the calibration set, each having n oftheabsorptionspectra.Anotherbenefitistheeffective
absorbancevalues,Aisthem(cid:2)nmatrixofthecalibration narrowing of spectral features, which may enhance
spectra. The spectra are reconstructed as a product of specificityintheanalyticalmethod.Notethatthefeatures
B (h(cid:2)n), the new basis set of loading vectors, and T inthesecond-derivativespectrumareinvertedrelativeto
(m(cid:2)h),thescores.Toreiterate,thekeytotheprocessis the absorption spectra. Although the second-derivative
thateachspectrumisreducedfromavectoroflengthn(a spectra plotted in Figure5 have been inverted to yield
rowinA)toanewvectoroflengthh(thecorresponding peaks rather than valleys at positions corresponding
rowinT),wherehistypicallybetween5and15. to absorption peaks, this convention is not followed
The column matrix of concentrations c is also related universally.
totheloadingvectorsT,accordingtoEquation(6):
cDTvCec .6/ 4 SERUMANALYSIS
Here,visthematrixofcoefficientsthatrelatesthescores
These analyses play a critical role in diagnosing and
totheconcentrations.
monitoring a wide variety of disorders (see Table3),
The reader is referred to several works in the
andatypicalcentralhospitallaboratorytypicallycarries
literature.9–14/ for fuller explanations of PLS and PCR
out many thousands of such tests every month. In order
methods.Forthesakeofthepresentdiscussion,wenote
for a new testing procedure to be accepted clinically it
thefollowingfeaturescommontothetwomethods:
mustmeetwell-definedaccuracyandprecisionstandards.
Although practical considerations such as the degree of
(cid:15) The main challenge in developing a method is to
automation also play a role in the acceptability of novel
decide how many (and, in the case of PCR, which)
methods,theseissueslieoutsidethescopeofthisarticle.
loadingvectorstoinclude.
In this section we present the current state of the art in
(cid:15) The overall performance of either method may be
theIR-basedanalysisofserum.
improvedbyeliminatingsuperfluousspectralregions
fromA.
4.1 InfraredSpectroscopyofSerum
(cid:15) The modeling of the spectra provides a means to
detect outliers (those spectra with extraordinarily Among the most common clinical serum tests are those
largespectralresidualsE ). for the most abundant organic species. For at least
A
7
INFRAREDSPECTROSCOPYINCLINICALANDDIAGNOSTICANALYSIS
Table3 SelectedserumanalytesthatmaybedeterminedusingIRspectroscopy
Analyte Referenceintervalsa Associatedconditionsa
Totalprotein 60–83gL(cid:0)1(adult) " Hypovolemicstates
# Nutritionaldeficiency
Liverdisease
Renaldisease
Fever
Inflammation
Albuminb 32–48gL(cid:0)1(adult) " Dehydration
# Pregnancy
Urea 7–18mgdL(cid:0)1(adult) " Impairedkidneyfunction
(2.5–6.4mmolL(cid:0)1) Congestiveheartfailure
Stress
# Severeliverdamage
Lowproteindiet
Nephroticsyndrome
Glucose 65–105mgdL(cid:0)1 " Diabetesmellitus
(3.6–5.8mmolL(cid:0)1) Acutepancreatitis
Stress/shock
# Pancreaticdisorders
Hepaticdisease
Extrapancreatictumors
Cholesterol 150–235mgdL(cid:0)1(male)c " Idiopathichypercholesterolemia
(3.9–6.1mmolL(cid:0)1) Biliaryobstruction
Pregnancy
141–219mgdL(cid:0)1(female)c Hypothyroidism
(3.6–5.7mmolL(cid:0)1) # Severeliverdamage
Malnutrition
Hyperthyroidism
Triglycerides 48–189mgdL(cid:0)1(male)d " Liverdiseases
(0.5–2.1mmolL(cid:0)1) Familialhyperlipidemia
Alcoholism
40–117mgdL(cid:0)1(female)d Gout
(0.45–1.3mmolL(cid:0)1) # Malnutrition
a FromWallach.15/andTietz:.16/"indicatesconditionsassociatedwithlevelsabovethereferencerange;
#indicatesconditionsassociatedwithlevelsbelowthereferencerange.
bSerumalbuminlevelsgenerallyparalleltototalproteinlevels.
c Desirablerange(5thpercentileto75thpercentile)for40-year-oldindividuals.Formen,theupperlimit
ofthedesirablerangerisesbyapproximately1mgdL(cid:0)1foreveryyearafter40;forwomen,theincrease
is(cid:24)3mgdL(cid:0)1foreveryyearafter40.
dDesirablerange(referenceintervalissomewhatwider).
six of these, the MIR spectra are distinctive enough 4.2 SerumAnalysisusingNear-infraredSpectroscopy
and the concentrations are high enough that they may
Two major systematic investigations have been carried
be determined from the MIR spectra of serum. These
out. The first of these, reported in a pair of publi-
include glucose, total protein, albumin, triglycerides, cations by Hall and Pollard,.17;18/ was based upon a
urea, and cholesterol. The basis for detecting and rapid-scanning NIRspectrometer. Theauthors reported
discriminating among the six analytes is illustrated by analytical methods for urea, triglycerides, total protein,
the spectra of the pure compounds shown in Figure6. andalbumin.
TheNIRspectraalsopermitquantitationofthesamesix Because the absorptions of protein overwhelm those
species. of other dissolved species, it proved possible to use a
Fourcomprehensivefeasibilitystudieshavebeenpub- simple MLR model to quantitate serum total protein.
lished, all of which differ in significant ways. Two The absorption spectra of albumin further proved to
were based upon MIR spectroscopy, and two on NIR be clearly distinguishable from those of the remaining
spectroscopy. One MIR investigation used ATR spec- proteins (primarily globulins; see Figure7), so that a
troscopy, and another used dried serum films; the two secondtwo-termMLRmodelwassufficienttodetermine
NIR studies differed in more subtle, yet substantial, albuminlevels.Baseduponthesecondderivativesofthe
details. absorption spectra, the two models were as shown in
8
BIOMEDICALSPECTROSCOPY
Equations(7)and(8):
C D15(cid:0)4419A.2178nm/C3655A.2206nm/
albumin
.7/
Tripalmitin
C D65(cid:0)7821A.2064nm/(cid:0)2373A.1440nm/
totalprotein
.8/
e The protein levels predicted by the NIR model are
c
n Albumin comparedtothereferenceanalyticalresultsinFigure8.
a
b The models for urea and triglyceride quantitation,
r
o
s also based upon the second-derivative spectra, required
Ab Glucose eight and eleven PLS factors, respectively. The spectral
regions employed as the basis for these models dif-
fered slightly: optimal for urea quantitation (Figure8)
was a combination of the ranges 1324–1800 and
Cholesterol
2304–2370nm, whereas triglyceride levels were opti-
mally predicted by combining the ranges 1635–1800
Urea
30
1000 1500 2000 2500 3000
Wavenumber (cm- 1)
Figure6 MIR absorption spectra for selected serum con- 20
a
stituents. The spectra for urea, glucose, and albumin were e
acquiredforaqueoussolutionsusinganopticalpathlengthof ur
6m m (the spectrum of water has been subtracted). Those for R
cholesterol and tripalmitin (tripalmitidoylglycerol) were mea- NI
10
suredforsolutionsincarbontetrachlorideusinganopticalpath
lengthof0.5mm.
Albumin
0 10 20 30
Globulins
R) Reference urea (mmolL- 1)
/
1
( 90
g
o
l
of 80
n
ve ei
ati rot 70
v p
eri Urea al
D ot 60
d t
n R
2 NI 50
2030 2080 2130 2180 2230 2280 2330 2380
Wavelength (nm) 40 50 60 70 80 90
Reference total protein (gL- 1)
Figure7 NIRreflectancespectra(secondderivatives)foralbu-
min,globulins,andurea.Totalserumproteinmaybequantified Figure8 NIR-predictedserumureaandserumproteinlevels
by the intensity of the serum absorption at 2064nm, corre- compared to reference analytical results (see also ‘‘NIRA’’
sponding to minima (absorption maxima) in the albumin and in Table4). The line of identity is included. (Adapted by
globulin second-derivative spectra. (Adapted by permission permission of Elsevier Science from J.W.Hall, A.Pollard,
of Elsevier Science from J.W.Hall, A.Pollard, ‘Near-infrared ‘Near-infrared Spectroscopic Determination of Serum Total
Spectroscopic Determination of Serum Total Proteins, Albu- Proteins,Albumin,Globulins,andUrea’,ClinicalBiochemistry,
min, Globulins, and Urea’, Clinical Biochemistry, 483–490, 483–490,Vol.26, (cid:211) 1993 by the Canadian Society of Clinical
Vol.26,(cid:211) 1993bytheCanadianSocietyofClinicalChemists.) Chemists.)
9
INFRAREDSPECTROSCOPYINCLINICALANDDIAGNOSTICANALYSIS
and 2035–2375nm. The 1850–2025nm range, spanning Figure9demonstratestheaccuracyofthesecondNIR
a very intense water absorption, was explicitly excluded study in assays for triglycerides, urea, and cholesterol.
from both models. This provides an example of how Although the analytical methods for total protein and
PLS modeling benefits from the exclusion of spectral albuminalsoprovedsuccessful,theattempttoquantitate
segments that carry no relevant analytical informa- serum lactate proved to be fruitless. The poor results
tion. These NIR analytical methods for serum total for lactate are largely due to the relatively low serum
protein, albumin, urea, and triglycerides are summa- concentration. Another contributing factor may be that
rized as part of the synopsis of methods presented in the NIR spectrum is not rich enough to differentiate
Table4. lactatefromotherdissolvedspecies(theonlyNIRbands
AmorerecentNIRinvestigationwasidenticalinspirit arise from the methyl group). The analytical methods
totheinauguralstudiesbutincorporatedonesubstantial for the other six analytes are summarized in Table4.
change in the experimental protocol..19/ Although the As indicated in Table4, all methods were based upon
early work was carried out using an optical path length PLSmodelsandallmadeuseofthesame2062–2353nm
of 0.5mm, the more recent work used a path length of spectralregion.
2.5mm. It is quite counter-intuitive to expect improved The NIR quantitation of glucose is of extraordinary
accuracy at this relatively long path length, because the interest. This interest stems from the early promise
region richest in solute absorptions (2050–2450nm) is of NIR spectroscopy as a means of monitoring blood
borderedbytwostrongwaterabsorptions(seeFigure2). glucoselevels noninvasively. Indeed,one oftheprimary
The accessible range within this window is substantially aims of the in vitro study.19/ was to delineate better the
reducedastheopticalpathlengthisincreased,byvirtue ability of NIR spectroscopy to quantitate serum glucose
of the further encroachment of the shoulders of the two under ideal experimental conditions. The success of this
water absorptions. It emerged, however, that this effect endeavorissummarizedinFigure10,whichsuperimposes
wasmorethancompensatedforbytheenhancedsignal- aClarkeerrorgrid.20/ onthescatterplotcomparingNIR
to-noise for solute absorptions in the spectral window to reference glucose levels. The error grid serves as a
thatremainedaccessible. template indicating regions corresponding to acceptable
Table4 SerumanalysesusingMIRandNIRspectroscopy
Analyte Methoda PLSspectralregion(s) No.ofPLS SEP
factors (mmolL(cid:0)1)b
Glucose ATR 950–1200cm(cid:0)1 9 0.58
FilmMIR 925–1250cm(cid:0)1 10 0.41
NIRB 2062–2353nm 13 1.3
Triglycerides ATR 1100–1500,1700–1800cm(cid:0)1 13 0.11
FilmMIR 900–1500,1700–1800,2800–3000cm(cid:0)1 7 0.23
NIRA 1635–1800,2035–2375nm 8 0.19
NIRB 2062–2353nm 13 0.11
Totalprotein ATR 1350–1700cm(cid:0)1 3 1.4
FilmMIR 900–1800cm(cid:0)1 13 2.8
NIRA 2064,1440nm(MLRmodel) (2)c 1.7
NIRB 2062–2353nm 10 2.3
Albumin FilmMIR 1100–1800cm(cid:0)1 12 2.2
NIRA 2178,2206nm(MLRmodel) (2)c 1.1
NIRB 2062–2353nm 7 2.0
Cholesterol ATR 2800–3000cm(cid:0)1 8 0.22
FilmMIR 1100–1300,1700–1800,2800–3000cm(cid:0)1 11 0.28
NIRB 2062–2353nm 13 0.32
Urea ATR 1130–1800cm(cid:0)1 20 0.48
FilmMIR 1400–1800cm(cid:0)1 13 1.1
NIRA 1324–1800,2304–2370nm 11 0.8
NIRB 2062–2353nm 12 0.46
a ‘‘ATR’’DMIR ATR spectroscopy of native serum;.21/ ‘‘Film MIR’’DMIR spectroscopy of dried serum films;.23/
‘‘NIRA’’DNIRspectroscopyofnativeserumat0.5-mmpathlength;.17;18/‘‘NIRB’’DNIRspectroscopyofnativeserumat
2.5-mmpathlength..19/
bStandard error of prediction (SEP) for independent test sets except for ‘‘ATR’’ study, where the standard error of
cross-validationforthecalibrationsetisgiven.
c TwowavelengthtermswererequiredforthealbuminandtotalproteinMLRcalibrationmodels.
10
BIOMEDICALSPECTROSCOPY
900
350
s
e ol
d 600 r
eri ste 250
c e
gly hol
ri c
t
R 300 R
I NI 150
N
0 300 600 900 50 150 250 350
Reference triglycerides Reference cholesterol
(mgdL- 1) (mgdL- 1)
160
50
40
120
e
ea at 30
ur 80 act
R l
NI IR 20
N
40
10
0 40 80 120 160 0 10 20 30 40 50
Reference urea Reference lactate
(mgdL- 1) (mgdL- 1)
Figure9 ComparisonofNIR-predictedserumanalytelevelstoreferenceanalyticalresults(seealso‘‘NIRB’’inTable4).Open
circlescorrespondtothecalibration(training)set,solidcirclestothevalidation(test)setandthesolidlineisthelineofidentity.
(AdaptedfromK.H.Hazen,M.A.Arnold,G.W.Small,‘MeasurementofGlucoseandOtherAnalytesinUndilutedHumanSerum
withNear-infraredTransmissionSpectroscopy’,AnalyticaChimicaActa,255–267,Vol.371,(cid:211) 1998,withpermissionfromElsevier
Science.)
analytical errors (A, B) and regions corresponding to these made use of ATR spectroscopy of the liquid, and
errors that would lead to dangerous or fatal clinical the second was based upon transmittance spectroscopy
decisions (C, D, E). As the authors point out, this ofdriedserumfilms.
analyticalmethodisnotaccurateenoughtomeetclinical
demandsbutitisaccurateenoughtosuggestthatfurther
4.3.1 AttenuatedTotalReflectanceSpectroscopyof
investigationiswarranted.
NativeSerum
Inthisworktheinvestigatorssoughttoquantifyglucose,
4.3 SerumAnalysisusingMid-infraredSpectroscopy
total protein, cholesterol, triglycerides, urea, and uric
Thetwocomprehensivefeasibilitystudieshavefollowed acid on the basis of the MIR ATR spectra collected
twodifferentpathstoavoidtheproblemsassociatedwith using a CIRCLE ATR cell (Spectra-Tech Inc., Shelton,
transmission spectroscopy of the native serum. One of CT, USA)..21/ It had been concluded on the basis of