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GASTROENTEROLOGY 2004;126:1071–1081

our-Dimensional Elastic Light-Scattering Fingerprintss Preneoplastic Markers in the Rat Modelf Colon Carcinogenesis

EMANT K. ROY,* YANG LIU,‡ RAMESH K. WALI,* YOUNG L. KIM,‡ ALEXEI K. KROMINE,‡

ICHAEL J. GOLDBERG,* and VADIM BACKMAN‡

Department of Internal Medicine, Evanston-Northwestern Healthcare, Evanston, Illinois; and ‡Biomedical Engineering Department,orthwestern University, Evanston, Illinois

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ackground & Aims: Identification of preneoplastichanges in histologically normal epithelium (the “fieldffect”) could provide a powerful screening tool for colo-ectal cancer. However, to date, reliable detection hasot been possible. We have recently developed a neweneration of optical technology, 4-dimensional elasticight-scattering fingerprinting (4D-ELF), which enables uso probe the nanoscale/microscale architecture of livingells. We therefore investigated whether 4D-ELF woulde able to identify preneoplastic changes in the colono-ytes of the azoxymethane (AOM)-treated rat model ofolon carcinogenesis. Methods: Forty-eight Fisher 344ats were randomized to either 2 weekly injections ofOM or saline. Animals were killed 2–20 weeks after theecond injection of AOM. Colons were removed andubjected to 4D-ELF analysis, with a subset undergoingssessment of aberrant crypt foci (ACF). All AOM-treatednimals were compared with age-matched saline-reated controls. Results: AOM-induced ACF became ap-arent at approximately 4–6 weeks and continued toncrease over time. ACF were predominantly located inhe distal colon. At 2 weeks (before development ofCF), there were marked changes in a number of 4D-LF signatures. The relevance to carcinogenesis of theseD-ELF–detected microarchitectural abnormalities isupported by their spatial and temporal correlation withubsequent development of ACF. All changes reportedere highly statistically significant. Conclusions: Wehow that probing the nanoscale cellular architectureith 4D-ELF provided an unprecedented tool for detect-

ng the earliest stages of colon carcinogenesis. Futuretudies are necessary to explore the clinical applicabilityf this technology and elucidate the biological determi-ants of these microarchitectural changes.

olorectal neoplasms are the second-leading cause ofcancer deaths in the United States, underscoring the

ublic health imperative for developing novel strategieso combat this malignancy.1 Screening has been shown toecrease colorectal cancer mortality by both identifying

esions at an early, potentially curable stage and alsohrough prevention of colorectal cancer development byargeting the precursor lesions, the adenomatous polyps.2

owever, there are many barriers to widespread imple-entation of these strategies, including patient noncom-

liance, discomfort, economic constraints, resource avail-bility, and risk of complications.3 Indeed, most eligibleubjects do not receive any type of screening for colorec-al cancer, which is in marked contrast to screening ratesor other common malignancies (e.g., breast, prostate).3,4

Therefore, it is clear that improved screening meth-dologies are essential to decrease the number of fatalitiesue to colorectal cancer. Many screening techniques areesigned to exploit the “field effect” of colon carcinogen-sis, the proposition that the genetic/environmental mi-ieu that results in neoplasia in one region should beetectable throughout the mucosa.5 For instance, theetection of distal adenomatous polyps by flexible sig-oidoscopy is commonly used to risk-stratify patients

or proximal neoplasia and, hence, the need for colonos-opy.6 Furthermore, rectal aberrant crypt foci (ACF) haveeen shown to accurately predict the occurrence of colondenomas and carcinomas.7 From a cellular perspective,poptosis in the uninvolved mucosa (both basal8 and bilealt induced9) has been shown to be a reliable marker forolonic neoplasia. Several biochemical markers have alsoeen evaluated, including colonic protein kinase C ac-ivity10 and mucus disaccharide content.11 Although allf these markers have shown a statistically significantorrelation between rectal assays and colonic neoplasiai.e., the field effect), their performance characteristics are

Abbreviations used in this paper: ACF, aberrant crypt foci; AOM,zoxymethane; 4D-ELF, 4-dimensional elastic light-scattering finger-rinting; LSS, light-scattering spectroscopy; PCA, principal componentnalysis; PC1, principal component 1.

© 2004 by the American Gastroenterological Association0016-5085/04/$30.00

doi:10.1053/j.gastro.2004.01.009

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1072 ROY ET AL. GASTROENTEROLOGY Vol. 126, No. 4

uboptimal for clinical practice. Novel techniques toetect the field effect are therefore urgently needed.There are several lines of evidence that subtle pertur-

ations in colonic microarchitecture may be a manifes-ation of the field effect. For instance, in the “transitionalucosa” (histologically normal epithelium adjacent to

olon cancer), a number of abnormalities in the celluclei have been noted, including changes in parametersuch as total optical density, nuclear area, chromatinexture, and coarseness.12–14 Although microarchitecturallterations may serve as an excellent marker of the fieldffect of colon carcinogenesis, current technology doesot allow its practical and accurate detection. Advancesn biomedical optics have the potential of enabling real-ime in vivo assessment of intracellular structure. We, inonjunction with others, have pioneered light-scatteringpectroscopy (LSS) for identifying cellular atypia.15–17

he clinical applicability of this technology is indicatedy our demonstration that dysplasia in Barrett’s esoph-gus can be accurately identified using an endoscopicallyompatible LSS probe.18 Moreover, LSS was shown to beble to detect early stages of colorectal carcinogene-is.17,19 However, this relatively basic first-generationechnology relies on detection of altered nuclear size andhromatin content. Therefore, it may be less adept atetecting the more subtle microarchitectural changes ofhe field effect and thus less useful in screening forolorectal cancer.

Light-scattering signals are extremely rich and com-licated, thus having the potential for yielding unprec-dented insights into the microarchitectural organizationf the cell. Light-scattering signals from tissue surfacesepend not only on the size, shape, and internal organi-ation of intracellular structures but also on the positionf these objects in relation to the cell itself or a largerrganelle (the immediate surrounding milieu of solidarticles such as proteins). To realize the full promise ofight scattering, we developed 4-dimensional elasticight-scattering fingerprinting (4D-ELF), a new genera-ion of optical technology.20 This technology allows us tobtain quantitative information about biological struc-ures without the need for tissue biopsy, fixation, stain-ng, or other processing. 4D-ELF enables probing tissuerganization at scales from tens of nanometers to mi-rons, thus encompassing a spectrum of structures rang-ng from macromolecular complexes to whole cells. In-eed, this provides information about objects 20–50imes smaller than can be detected by conventional mi-roscopy. Thus, the light-scattering fingerprints provideheretofore-unattainable insight into the architecture of

iving tissue at the nanoscale organizational level.

The objective of this study was to assess whetherD-ELF would be able to detect the field effect of colonarcinogenesis. In the present studies, we tested 4D-ELFn the azoxymethane (AOM)-treated rat, a well-validatedodel of colorectal carcinogenesis that recapitulatesany of the important morphologic, genetic, and cellu-

ar alterations found in human colon cancer.21 We showhat 4D-ELF is able to accurately identify alterations inhe colonic mucosa at a far earlier stage than any previ-usly described markers. Furthermore, these changes cor-elated well with the carcinogenic progression in thisodel.

Materials and MethodsOverview of 4D-ELF

LSS is based on the principle that the intensity of lightlastically scattered (i.e., without change in wavelength) fromtissue is a function of the composition of both light absorbersnd scatterers within the tissue. Light absorption is governedy molecules such as hemoglobin, whereas scattering is deter-ined by the sizes and densities of space-occupying structures

ncluding cell organelles and macromolecular complexes. Anxtension of LSS, 4D-ELF allows acquisition of light-scatteringata in several dimensions, thus providing unprecedented in-ights into tissue composition. The dimensions of 4D-ELF are1) wavelength of light, (2) the scattering angle (i.e., the angleetween the backward direction and the direction of theropagation of scattered light), (3) azimuthal angle of scatter-ng (i.e., the angle between the incident light polarization andhe projection of the direction of the scattered light propaga-ion onto the plane in which the incident electric field oscil-ates), and (4) polarization of scattered light. Thus, in 4D-ELF,cattered light is analyzed as a function of its wavelength inimension 1, direction of propagation in dimensions 2 and 3,nd polarization in dimension 4.

Light-Scattering Fingerprinting

To obtain the 4D-ELF data, we have developed andvanced light-scattering instrument as previously de-cribed.20 Briefly, our instrument (Figure 1) consists of 2omponents: the light delivery system (used to illuminate aissue site approximately 1 mm in diameter) and the collectionystem (which gathers light scattered by the tissue). In theelivery system, the broadband light emitted by a xenon lightource (Oriel Inc., Strafford, CT) was collimated by means ofhe lamp condenser and a lens system and was linearly polar-zed using a polarizer. Thus, a collimated linearly polarizedeam of broadband light was delivered onto a tissue surface.or each wavelength, the tissue scatterers the incident light inwide range of directions and polarization states. This scat-

ered light was recorded using the light collection system; thecattered light was transmitted through an analyzing polarizerhat selected the desired polarization of the scattered light (seeollowing text), a Fourier lens (Newport, Inc., Irvine, CA)

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ositioned one focal distance from a tissue surface, and themaging spectrometer (SpectraPro-150; Acton Research Corp.,cton, MA), which was positioned one focal distance from theourier lens and coupled to the charge-coupled device (Cool-napHQ; Roper Scientific, Inc., Trenton, NJ), which served ashe scattered light detector. The Fourier lens projects anngular distribution of the scattered light onto the entrancelit of the spectrometer. This light was further diverted by thepectrometer according to its spectral content, now in theirection orthogonal to the slit, and projected onto the charge-oupled device. Thus, the instrument recorded a matrix of theistribution of scattered light intensity for various wave-engths (from 400 to 700 nm) and angles of scattering (within

5° from the backward direction; here the angle of scatterings defined as the angle between the direction opposite to theirection of propagation of the incident light and the directionf propagation of the scattered light). In this matrix, one axisorresponds to the wavelength of light and the other to thengle of scattering for a fixed polarization and the azimuth ofcattering. The azimuth of scattering is selected by rotatinghe polarizer in the delivery arm of the system. The combina-ion of the linear polarizer in the delivery arm of the systemnd the analyzing polarizer allows measurement of the inten-ity of 2 independent components of the light scattered fromhe tissue: scattered light polarized along the direction ofolarization of the incident light (co-polarized component I�)nd the scattered light polarized orthogonally to the polariza-ion of the incident light (the cross-polarized component I�).o compensate for non-uniform spectral profile of the light

ource and other artifacts, the light-scattering intensity mapsere normalized to a reflectance standard (Ocean Optics, Inc.,unedin, FL). The instrument was calibrated and tested using

igure 1. Schematic represen-ation of the 4D-ELF instru-ent: Xe, xenon lamp; Hg, mer-

ury lamp; C, condenser; L,enses; A, apertures; P, polariz-rs; M, mirrors; B, beam split-er; SS, sample stage; SP,pectrograph; CCD, charge-oupled device camera; Lc, cal-bration lenses; Ac, calibrationpertures.

onventional protocol with physical tissue models,20 whichonsisted of suspensions of polystyrene microspheres of differ-nt sizes ranging from 0.2 to 10 �m. The light-scattering dataecorded in these experiments were found to be in excellentgreement with the predictions of Mie theory, which providesxact solution to the light scattering by spheres.

The polarization-sensitive detection has an important ad-antage over conventional unpolarized measurements by al-owing penetration depth selectivity. Most biological tissuesre relatively turbid. Light propagation in such media isominated by the multiple scattering from tissue structuresocated within several millimeters of the tissue surface, whichn the case of colon tissue typically includes both the mucosand submucosa. The single scattering collected by means ofolarization gating is primarily contributed by scatterers lo-ated close to the tissue surface and therefore particularlyensitive to the properties of the superficial tissues (e.g., thepithelia).20,22,23 As shown by our previous work,20 the differ-ntial polarization signal (�I � I��I�) is primarily contrib-ted by the most superficial tissue structures located withinhe first 30–50 �m of the tissue surface, which typicallyncludes the epithelial cell layer. The co-polarized signal I�,iffuse reflectance signal I��I�, and the cross-polarized signal

� provide information about progressively deeper tissues (upo several millimeters below the surface). Light scattering andbsorption by red blood cells may alter the differential polar-zation signals �I, which characterize tissue nanoarchitecturend microarchitecture. Because differential polarized signalsre superpositions of single scattering contributions from var-ous tissue scatterers within the superficial tissue, the signalsrom red blood cells in rat tissue samples were subtracted fromhe unprocessed light-scattering spectra by fitting the red

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Although unpolarized diffuse reflectance tissues have previ-usly been studied,24–29 the information obtained regardingissue structures is averaged over several photon transportaths (approximately several millimeters), which does notllow characterization of epithelial and near-epithelial tissues.n the other hand, polarization gated measurements, as re-orted here, can provide principally new information abouthanges in organization of epithelial cells, which is crucial foretection of the initial stages of carcinogenesis.20,22,23,30

Analysis of Light-Scattering Fingerprints

Briefly, 4-dimensional light-scattering fingerprintsontain the wealth of information about tissue microarchitec-ure and nanoarchitecture.20 A number of light-scatteringignatures can be linked to specific properties of cell architec-ure, including the size distribution of intraepithelialanoscale and microscale structures (from �30–40 to 800m) and the fractal dimension of the cell structure at suprami-ro scales (greater than �1 �m).20,31,32 The combination ofhese measures enables quantitative characterization of epithe-ial architecture in a wide range of scales, from tens of nano-eters to microns.To obtain the complete size distribution of subcellular

tructures at each tissue site, the spectra computationallyimulated using Mie theory were fit to the differential polar-zation tissue spectra for a given scattering angle and azimuthf scattering using the conventional least-squares minimiza-ion algorithm.33 In each fitting, several types of size distri-utions (normal, log-normal, or uniform) were assumed. Weound that the spectra recorded by our instrument for scatter-ng angles within �5° from the backward direction hadpectral behavior similar to an inverse power-law, which isonsistent with our previous results31 as well as results ob-ained by other groups.32,34 Our studies confirmed that if theizes of scatterers are widely distributed, as is characteristic ofiological tissues, the log-normal or power-law size distribu-ions provide fits superior to those obtained using a normal orniform size distribution. This agrees well with our observa-ions as well as those of other groups.31,32,34–36 The log-normalrobability distribution depends on 2 parameters: its meani.e., the mean size of tissue structures giving rise to thecattering signal) and the standard deviation of particle sizes,hich characterizes particle size variability. Therefore, we var-

ed these parameters to minimize the �2. The size-sensitivitytudies showed that the differential polarization spectra arerimarily sensitive only to scatterers with sizes ranging from0 to 800 nm. Therefore, these limits provide the range ofalidity of the size distributions obtained using the fittinglgorithm.

We also used principal component analysis (PCA) as one ofhe tools for data analysis.37 For PCA, the light-scatteringpectra were averaged over scattering angles from �5° to 5°.ach spectrum was preprocessed by mean scaling.38 A dataatrix was created in which each row of the matrix contained

he preprocessed spectrum measurement and each columnontained the preprocessed scattering intensity at each wave-ength. The scores of all principal components were calculatedsing Matlab statistics toolbox software version 6.5 (Theathworks, Inc., Natick, MA).

Animals

All animal studies were performed in accordance withhe institutional Animal Care and Use Committee of Evan-ton-Northwestern Healthcare. Forty-eight male Fisher 344ats (150–200 g) were randomized equally to groups thateceived either 2 weekly intraperitoneal injections of AOM (15g/kg) (Sigma Chemical Co., St. Louis, MO) or saline. Ratsere fed standard chow and were killed at various times after

he second injection (2, 4, 5, 6, 8, 12, and 20 weeks). Colonsere removed, flushed with phosphate-buffered saline, andivided into equal proximal and distal segments. 4D-ELFnalysis was performed on fresh tissue. Quantitation of ACFas performed on a subset of animals using methods previ-usly described.39 Briefly, after fixation overnight in 10%uffered formalin, colon segments were stained for 2 minutesn 0.2% methylene blue (Sigma Chemical Co.), rinsed inhosphate-buffered saline, and examined with a dissectingicroscope. ACF (defined as a foci containing �2 crypts) were

cored by an observer blinded to treatment.

ResultsAssessment of ACF

We analyzed the number of ACF on a subset ofnimals in this study to correlate this well-validatediomarker of colon carcinogenesis to the 4D-ELF read-ngs. ACF were detectable at week 4 and progressivelyncreased in both number and complexity over the coursef the experiment. As shown in Figure 2, there was aarked distal predominance in ACF. Although proximalCF occurred, these required longer to develop and were

igure 2. Temporal progression of ACF in a subset of AOM-treatedats. ACF were detected predominantly in the distal colon, and thereas a linear progression over time. There were markedly fewer ACF in

he proximal colon, especially at the early time points.

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ess numerous than distal ACF. No ACF were detected inhe saline-treated animals.

Overview of 4D-ELF Analysis

To analyze the signatures, we assayed a variety ofarameters that span the spectrum of microarchitecturalbnormalities. Fingerprint analysis gives a dramatic, al-eit qualitative, appreciation of AOM-induced alter-tions. The spectral slope analysis evaluates size distri-ution of particles ranging from macromolecules torganelles. Fractal dimension, on the other hand, reflectslterations of the tissue organization at much largercales, ranging from large organelles to groups of cells.CA is a standard data procedure for assessing underly-

ng structure in a data set. To infer a relationship toolon carcinogenesis, we correlated the 4D-ELF signa-ures with the subsequent occurrence of ACF. Specifi-ally, neoplastic signatures should progress over time ande predominantly in the distal colon, especially earlyuring carcinogenesis (mirroring our ACF data). All datarom AOM-related signatures were compared with ange-matched saline-treated rat.

Elastic Light-Scattering Fingerprints

4D-ELF data obtained from each point on a tissueurface have 4 dimensions: wavelength �, scattering an-

igure 3. Representative 4D-LF fingerprints from rats killedweeks after injection of AOM

r saline. The color representsntensity of backscattering light.he horizontal axis is the wave-ength of the backscatteringight. The vertical axis is theackscattering angle. (A) Sa-

ine-treated rat, proximal colon;B) AOM-treated rat, proximalolon; (C) saline-treated rat,istal colon; (D) AOM-treatedat, distal colon. As shown,ven at this very early timeoint, treatment with AOM haddramatic effect on 4D-ELF sig-atures in the distal colon.owever, in the proximal colon,

he changes attributable toreatment with AOM were quiteubtle.

le , azimuth of scattering , and polarization of scat-ered light. These 4-dimensional data provide the mostomplete representation of the scattering properties of aissue. Moreover, these 4-dimensional fingerprints arextremely sensitive to changes in tissue organization atcales ranging from nanometers (�30–40 nm) to tens oficrons (see following text).20

Figure 3 shows representative light-scattering finger-rints recorded from a rat at an early stage of carcino-enesis (2 weeks after carcinogen treatment) and a con-rol animal (2 weeks after saline treatment). For theontrol (saline-treated) animal, there are slight differ-nces between the back-scattering intensity (especially atarger back-scattering angles) as indicated by subtlehanges in color intensity recorded from proximal (Fig-re 3A ) and distal (Figure 3C ) colons, respectively. Thisnding is consistent with our understanding of the bio-ogical differences in the regions of the colon. Moreover,n the proximal colon (Figure 3B), treatment with AOMnduced modest changes in the light-scattering finger-rints (most notably at the longer wavelengths) com-ared with corresponding fingerprints from control ani-als (Figure 3A ). This finding is consistent with theinimal carcinogenic effect of AOM in the proximal

olon, which is supported by data from our group and

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thers.21 However, in the distal colon, the AOM-inducedlterations of the fingerprints were much more dramaticFigure 3D vs. 3C ), paralleling the increased carcino-enic efficacy in this region of the colon. We noted thathe time point for which the alteration of light-scatteringngerprints was detected (i.e., 2 weeks after treatmentith AOM) preceded the formation of ACF or otherreviously described conventional biomarkers.

Spectral Analysis

In the present study, we focused on the analysisf the light-scattering fingerprint data in 2 dimen-ions: wavelength and scattering angle. As discussedn Materials and Methods, the light-scattering spectraI(�) were used to obtain information about the sizeistribution of submicron intraepithelial structures inhe size range from 40 to 800 nm (i.e., from macro-olecular complexes to organelles). Figure 4A shows

epresentative size distribution curves obtained from

istal colon tissue sites of control and AOM-treatednimals at 2, 5, 12, and 20 weeks after the carcinogenreatment, respectively. As carcinogenesis progressed,variety of parameters (i.e., mean size, probable size,

nd relative proportion of larger structures) indicatedn increase in particle dimensions. These findings arendicative of profound changes in the cellularanoscale organization at an early stage of neoplasticransformation. Such alteration of cell nanoarchitec-ure has not been previously reported, most likely dueo methodological limitations. Thus, 4D-ELF– de-ected microarchitectural evaluation in situ representsmajor technological advance with potentially impor-

ant biological and clinical ramifications.Spectral behavior of �I(�) depends on the size distri-

ution of scattering structures. Generally, �I(�) is aeclining function of wavelength and its steepness iselated to the relative portion of structures of different

igure 4. Analysis of spectral information in the light-scattering fin-erprints. (A) Carcinogen-induced alterations in the size distributionsf intracellular structures determined by the spectra collected fromhe distal colons. (B and C) Changes in the spectral slope 2, 4, 5, 6,2, and 20 weeks after treatment with AOM in the (B) distal and (C)roximal colon. Initially, the only significant alterations are in theistal but not the proximal colon. However, as carcinogenesisrogresses, both the distal and proximal colon manifested highlytatistically significant decreases in spectral slope (P �0.0001 and P0.001 for the distal and proximal colon, respectively). In agreementith the ACF data, the effects on spectral slope at the later timeoints was more dramatic in the distal compared with the proximalolon.

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izes. Typically, larger structures tend to reduce theteepness of the decline of �I(�), whereas smaller scat-erers tend to make �I(�) decrease with steeper wave-ength. To analyze the data and characterize the spectralariations of �I(�), we obtained linear fits to �I(�) usinginear regression analysis. The absolute value of the linearoefficient of the fit (in all measurements, the linearoefficient is negative due to the decrease of �I withavelength), which is referred hereafter to as the spectral

lope, quantifies the dependence of the scattering spec-rum on wavelength and may serve as an easily measur-ble marker to characterize the distribution of structuresithin the cells.Figure 4B and C show alterations of the spectral slope

n the AOM-treated rats compared with its control val-es. In the proximal colon, treatment with AOM failedo induce changes in the spectral slope at 2 weeks afterhe carcinogen treatment (P � 0.43). This finding isonsistent with only minimal carcinogenic effect ofOM in the proximal colon. On the contrary, in theistal colon, the spectral slope is dramatically decreaseds early as 2 weeks after carcinogen treatment (P �.0003) and continued to decrease over the course of thexperiment (P �0.0001). Such progressive and highlytatistically significant alteration of the spectral slopendicates that this parameter can be used as a marker forarly precancerous transformations and its change is notue to the acute action of AOM.

Fractal Dimension

The angular distributions of the scattered lightere used to calculate the fractal dimensions of the tissueicroarchitecture. The angular distribution �I() at 550

m for each tissue site was Fourier transformed to yieldhe 2-point mass density correlation function C r�� r� � �r� � r��, where � [r] is a local mass densityt point r, which is proportional to the concentration ofntracellular solids such as proteins, lipids, andNA.20,31,34 C(r) quantifies the correlation between local

issue regions separated by distance r. For example, in aerfect solid, C(r) is a constant. On the other hand, for anbject composed of randomly distributed material, C(r)anishes rapidly with distance. We found that at allissue sites, C(r) closely followed a power-law for severalecades of r ranging from �1 to 50 �m. Such power-lawensity correlation functions have been extensively stud-ed and are characteristic of a fractal-like or statisticallyelf-similar organization. The general form of such C(r) isD � 3, where D is referred to as fractal dimension.34 Webtained D from the linear slopes of C(r) in the linearegions of log-log scale.

As shown in Figure 5A, in the distal colon, fractalimension was noted to be elevated as early as week 2P � 0.005) and continued to markedly increase overime (P �0.0001). On the other hand, in the proximalolon, treatment with AOM failed to induce statisticallyignificant alterations in fractal dimension. However,ractal dimension increased at later time points, albeit more

odestly than that noted in the distal colon (Figure 5B).

PCA

PCA was performed as discussed in Materials andethods. We first determined which principal component

igure 5. Analysis of scattering angle-dependent information in theight-scattering fingerprints through quantitation of the fractal dimen-ion of the superficial mucosa. At the initial stages of carcinogenesis,ractal dimension significantly increased in the distal but not theroximal colon. However, as carcinogenesis progresses, both theistal and proximal colon manifested highly statistically significantncreases in fractal dimension (P �0.0001 for both the distal androximal colon, respectively). However, consonant with the ACF andpectral slope data, the effects on fractal dimension at the later timeoints were more dramatic in the distal compared with the proximalolon.

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as of interest. Typically in PCA, the first few principalomponents are responsible for most of the signal variationsnd the significance of higher-order principal componentsiminishes.37 We found that, in our data, principal com-onent 1 (PC1) accounted for �99.3% of the data variance.hus, PC1 is a convenient means to characterize the light-

cattering fingerprint data. As shown in Figure 6, PC1 wasignificantly increased at 2 weeks in the distal colon (P �� 10�12) and this progressively continued over the course

f the experiment (P � 5 � 10�43). On the other hand,C1 was minimally elevated in the proximal colon (data nothown).

Intersegment Variability

In our protocol, each colonic segment had ateast 4 distinct 1-mm2 areas probed. To assess whetherD-ELF could have a clinical role, it is of considerablemportance to determine the number of measurementsequired to reliably detect premalignancy. We estab-ished thresholds for categorizing an area as preneoplasticsing PC1, linear slope, and fractal dimension. We an-lyzed sensitivity and specificity by applying these cri-eria to AOM- and saline-treated animals, respectively.sing this set of parameters, even at the earliest timeoint (2 weeks after injection of AOM), 90% of areasrobed in the distal colon would correctly classify thenimal as being exposed to carcinogen. This improved to00% as the effects of the carcinogen progressed (weeks2 and beyond). The specificity for all time points was00%. This suggests that even at the earliest stages ofolon carcinogenesis (2 weeks after treatment withOM), 4 readings per colonic segment would provide a9.99% probability of correctly diagnosing premalig-ancy. This accuracy far exceeds the capabilities of anyonventional biomarker.

igure 6. PCA of light-scattering fingerprints: score of PC1 obtainedrom ELF collected for control and AOM-treated distal colon tissues at, 5, 6, 12, and 20 weeks after injection of carcinogen (P � 5 �0�43). There was a minimal increase in PC1 in the proximal colondata not shown).

DiscussionExploitation of the field effect in colon carcino-

enesis is a common theme in colon cancer screening. Asreviously discussed, present strategies lack sufficientensitivity and specificity for optimal population screen-ng. For instance, although flexible sigmoidoscopy is aell-established and widely used screening technique,

he problems with this test are underscored by the ob-ervation that less than one half of subjects with ad-anced proximal colon adenomas would also harbor le-ions in the sigmoid and rectum.40 Therefore, flexibleigmoidoscopy would not trigger colonoscopy in theseases and the proximal lesions would have the opportu-ity to evolve into invasive carcinomas. Thus, the findingf an accurate marker for the field effect would be ofajor clinical importance.Application of the newly developed 4D-ELF has great

romise for colon cancer screening because of the remark-ble sensitivity to the earliest changes in carcinogenesis.sing quantitative analysis of tissue microarchitecture,e were able to detect the earliest alterations in neoplas-

ic transformation (at 2 weeks after carcinogen treat-ent), which may reflect the field effect. The relevance of

hese 4D-ELF changes to carcinogenesis is supported byoth the temporal and spatial correlation. Temporally,he marked alterations detected at week 2 progressivelyncreased in magnitude over time consonant with theeoplastic effects of AOM in this model. Spatially, thearly signature alterations were predominantly in theistal colon, the region of the colon most susceptible toCF and tumor development. Moreover, the changesoted with 4D-ELF occurred at 2 weeks after treatmentith AOM, a time point far earlier than seen with other

onventional biomarkers. This time point was of partic-lar importance in that the nonspecific genetic and cel-ular changes associated with acute carcinogen adminis-ration have dissipated.41 Therefore, alterations at thisime reflect the earliest changes related to the field effectf carcinogenesis. The biological plausibility of the here-ofore-undescribed microarchitectural changes is sup-orted by several recent reports cataloging genetichanges in colon carcinogenesis. Indeed, one study re-orted that 4 weeks after treatment with AOM, a de-rease in APC message was detectable with a concomi-ant increase in cyclooxygenase 2 and c-myc expression.42

lthough the architectural consequences of these geneticlterations were not explored, APC, c-myc, and cycloox-genase 2 have been reported to alter cellular structurend function.

We believe our data provide compelling evidence thathe microarchitectural perturbations in the histologically

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ormal mucosa identified by 4D-ELF represent a reliablearker of the field effect of colon carcinogenesis. How-

ver, as opposed to classic definitions of field effect, thelterations we noted occurred before onset of frank neo-lasia. This could potentially have great clinical utilityy accurately identifying individuals at future risk ofeveloping colorectal cancer. An unlikely alternative ex-lanation is that 4D-ELF may actually be detecting earlyysplastic areas in uninvolved colonic mucosa such asCF or �-catenin–filled crypts.43 However, it is implau-

ible that our findings simply reflect a more sensitiveethodology for detecting these conventional early dys-

lastic lesions. Early during carcinogenesis (�10 weeksfter injection of AOM), ACF and �-catenin crypts areelatively infrequently interspersed throughout the distalolon and yet we noted diagnostic abnormalities in 90%f areas assayed at 2 weeks and 100% at 12 weeks afterarcinogen treatment. Moreover, we were unable to de-ect any ACF 2 weeks after injection of AOM, furtherrguing against the proposition that we were simplyetecting dysplastic areas. However, it is possible thatD-ELF may be detecting previously undescribed pre-eoplastic lesions, although such putative lesions wouldave to be remarkably abundant.The microarchitectural changes that we noted early in

olon carcinogenesis encompassed a large spectrum ofarameters. Our results indicate that the size distribu-ion of submicron intraepithelial structures shifts towardarger sizes very early in carcinogenesis. Although theiological determinants of this phenomenon are unclear,t may reflect an increase in the sizes of macromolecularomplexes (i.e., more protein-protein interactions). Frac-al dimension, on the other hand, reflects changes in cellrganization at much larger scales, ranging from largerganelles to cells. Alterations in fractal dimension haveeen postulated to be one of the earliest changes in colonancer.44 The most common way of measuring fractalimension is through box-counting approximations,hich would clearly not be practical for colon cancer

creening.45 Using 4D-ELF, we are able to measure thisarameter rapidly and accurately. We envision that, inhe future, clinical determinations of fractal dimensionnd other microarchitectural parameters could bechieved through use of a probe compatible with aexible sigmoidoscope (or colonoscope). This informa-ion could potentially be used to quantitate an individ-al’s risk for developing colorectal neoplasms and there-ore determine the most appropriate methodology andrequency for colorectal cancer screening.

The voluminous data generated by 4D-ELF were alsonalyzed through PCA. PCA has been used for many bio-

ogical/clinical purposes, including both assessment ofaryotypic alterations46 and distinct biological featurese.g., global molecular phenotype)47 in human colon cancer.his variable reduction procedure is useful in assessingnderlying structure in a complex data set. Because princi-al components are extracted in a stepwise fashion, the firstrincipal component is responsible for the largest amount ofhe variance.48 We show that PC1 is a powerful discrimi-ator between saline- and AOM-treated mucosa. This is ofotentially great clinical significance in that this marker ofhe field effect may be exploited for colorectal cancer screen-ng in the future. Moreover, it is important to note thatespite the extensive “data mining” performed on 4D-ELFignatures, this represents �5% of total information avail-ble. Therefore, it is conceivable that our remarkable find-ngs of early changes in carcinogenesis may be eclipsed byuture ELF analyses.

Several other optical techniques have been used toetect cells undergoing neoplastic transformation. Fornstance, we and others have previously shown thatSS, the precursor technology to 4D-ELF, was able toetect cells in several human organs, including theolon, through evaluation of nuclear size and chroma-in density.15,17,30 Other bio-optics techniques (opticaloherence tomography, Raman spectroscopy, angle-esolved low-coherence interferometry, and so on) havelso been shown to be useful in detecting pathologi-ally apparent dysplasia.19,25,27,35,49 However, previousnvestigations using these techniques have focused onhe diagnosis of more advanced, histologically appar-nt stages of neoplastic transformation and none ofhese techniques have been shown to allow identifica-ion of predysplastic epithelium.

The data obtained from light-scattering fingerprintinghould not be considered a mere substitution for the mor-hologic tissue analysis using light microscopy. The 4-di-ensional information extracted from ELF provides much

reater biological insights than the previously used tech-ologies. The critical advantages are related to the quanti-ative information regarding nanoscale architecture on liv-ng tissues. 4D-ELF gives information at the level oflectron microscopy and yet keeps the levels of cellularrganization that may be lost with staining/fixation, allow-ng heretofore-undiscovered insights regarding microarchi-ectural changes that occur early in neoplastic transforma-ion. Given the complexity of the signatures, some signalsay not allow direct correlation to a specific feature of the

ellular architecture but still may serve as valuable inter-ediate biomarkers for carcinogenesis.Although our data are compelling, caution always needs

o be exercised when extrapolating findings from an exper-

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mental model to humans. However, the AOM-treated rats an established, robust, and well-validated model of hu-an colon carcinogenesis. This model replicates the pro-

ression of the genetic, cellular, and morphologic events ofuman sporadic colon cancer. Furthermore, our preliminarytudies using the other major experimental model, theultiple intestinal neoplasia mouse, also noted marked

D-ELF alterations occurring at the pretumorigenic stage,ispelling the possibility that our findings are model spe-ific (unpublished data, September 2003). Another caveatelates to the distal predominance seen in the AOM-treatedat. Although most human colon cancers are also located inhe distal colon, there are increasing data suggesting thateoplasms that form in the proximal colon are quite distinctrom those that form distally. For instance, proximal colonancers have a much higher rate of microsatellite instability25% vs. 2%), are more likely to occur in older and femaleatients, and, stage for stage, have a better prognosis thaneft-sided tumors.50 Thus, the AOM-treated rat may notdequately represent the subset of human colon cancers thatccur in the right colon. Nevertheless, epigenetic fieldhanges are a hallmark of proximal cancers, as evident byhe observation of frequent promoter hypermethylation inumor-suppressor genes (including the DNA mismatch re-air enzyme hMLH-1) in both right-sided colon cancers andhe uninvolved mucosa.51 Whether right-sided fieldhanges will be detectable in the left colon remains to beetermined. Our results in the AOM-treated rat indicatehat 4D-ELF clearly identified changes in the colonic regionistant from the predominant site of carcinogenesis (e.g.,ignatures in the proximal rat colon were also altered),uggesting that there should be distal microarchitecturalorrelates of proximal neoplasia.

In summary, this report shows that the newly devel-ped technology 4D-ELF was able to detect heretofore-nrecognized subtle microarchitectural perturbationsrom the field effect of colon carcinogenesis. This tech-ology has the promise of allowing accurate risk strati-cation and identifying patients who would benefit fromolonoscopic screening and, of equal importance, deter-ining who may not require intensive colorectal cancer

creening. One can envision the rapid “bench-to-bed-ide” transition of this technology through the develop-ent of an endoscopically compatible probe with real-

ime signature determination. Moreover, 4D-ELF canive unparalleled insights into biological changes earlyn carcinogenesis. Further studies are being performed toranslate this technology into clinical practice and toetermine the biological determinants of these microar-hitectural alterations.

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Received September 28, 2003. Accepted December 29, 2003.Address requests for reprints to: Hemant K. Roy, M.D., Feinberg

chool of Medicine at Northwestern University, Evanston Northwesternealthcare Research Institute, 1001 University Place, Evanston, Illi-ois 60201. e-mail: [email protected]; fax: (847) 570-8011.Supported by research grants from the National Institutes of Health

1R21CA102750-01), National Science Foundation (BES-0238903),eneral Motors Cancer Research Foundation, and American Cancerociety/Illinois Division.Presented in part in abstract form at the 104th Digestive Diseaseeek meetings, May 17–21, 2003, in Orlando, Florida (Gastroenter-

logy 2003;124(Suppl 1):A5).

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