Quantitative Retardance Imaging by means ofQuadri-wave lateral shearing interferometry for

label-free fiber imaging in tissues

Sherazade Aknoun 1,∗, Michel Aurrand-Lions2, Benoit Wattellier 1 andSerge Monneret3

1PHASICS SA,Espace technologique de Saint Aubin, Route de L’Orme des Merisiers,Saint Aubin, France.

2CNRS, Aix Marseille Université, Centrale Marseille, Institut Fresnel, UMR 7249,Marseille, France.

3Centre de Recherche en Cancérologie de Marseille, Inserm, UMR1068, Marseille,France.

∗Corresponding author: aknoun@phasics.fr

AbstractWe describe the use of quantitative retardance imaging, previously intro-duced in [1], as a label-free method for in situ tissue imaging and extra-cellular matrix fiber organization study. A technical improvement of thisquantitative retardance imaging technique, based on the use of a high-resolutionquadri-wave lateral shearing interferometer, is implemented to perform fastquantitative linear retardance and retardance measurements on biologicaltissues.The technique combines a stack of quantitative phase images with varyingpolarization excitation to create retardance and orientation images at 1 Hz.This technique gives information about local retardance and structure ofanisotropic components. In addition to bringing morphological informationon unstained biopsies, it can reveal tumors development grades thanks tospecific fiber organization imaging. In this present study, we demonstratehow this information can be used as tumor associated signature. We showthe capability of our approach on mouse skin and human breast tissues.Keywords: Label free microscopy, Quantitative retardance imaging, Tissueimaging, Collagen, Specific imaging, TACS

Preprint submitted to Optics Communication February 13, 2018

1. Introduction

1.1. Introduction to tissue imaging (ECM, collagen)Tissue microenvironment plays an important role of support, nutrition

and maintenance of the tissue homeostasis. A major component of this mi-croenvironment is the extracellular matrix (ECM), a complex network ofmacromolecules with distinctive physical, biochemical, and biomechanicalproperties. The ECM is commonly deregulated and highly altered with can-cer development [2], that is why understanding how its composition andstructuration are maintained or how the deregulation influences cancer pro-gression is of high importance. Furthermore, it may help develop new thera-peutic interventions by targeting the tumor microenvironment [3]. In [4, 5],it has been considered that the remodeling of the ECM, and more particu-larly the morphology and orientation of collagen fibers in the extracellularmatrix, may provide a better optical marker of early disease (i.e. tumordevelopment) than currently available imaging methods. Tumor progressionand response to treatment could also be studied thanks to the same opticalmarkers.

1.2. Staining techniquesImmuno-histochemical staining and specific colorations are widely used

for the diagnosis of abnormal tissues. For the studying of tissue morphology,histology remains the ’gold standard’. The principle is to correlate morpho-logic changes with specific diseases by making a qualitative evaluation thatrelies entirely on the tissue staining. However, its accuracy strongly dependson pathologist interpretation skills and staining quality, a staining that canhave inconsistent distribution and can vary depending on the sample prepara-tion [6]. There is a lack of standardized quantitative and automated methodsto assess the nature of biopsies [7]. In this scope, we think label-free tech-niques are of great interest since they remove uncertainties due to stainingpreparations.

1.3. Optical and quantitative techniquesIn literature, several studies have demonstrated the relevance of the use of

quantitative biomarkers obtained on tissue samples to make classification andassess tumor development. The idea is to specifically use the optical birefrin-gence property of fibers and their retardance to reveal quantitatively collagenorganization. Several optical microscopy techniques can give measurements

2

of fiber characteristics (retardance, orientation, organization around tumors)in histological samples without any interference with the tissue (i.e. no con-tact or staining). The most represented techniques in this field are Sec-ond Harmonic Generation (SHG), Mueller matrix imaging and PolarizationSensitive Optical Coherence Tomography (PS-OCT). They all are label-freetechniques.

1.3.1. Second Harmonic generationSHG-based microscopy has become a widely used quantitative modal-

ity for imaging collagen morphology and three-dimensional orientation ofcollagen molecules in tissues [8]. Because of symmetry properties, second-harmonic generation can only occur within anisotropic materials, which makesthis technique specific to fibers in biological samples. SHG is highly sensi-tive to collagen structure and particularly adapted for the study of collagenreorganization that can occur in diseases such as cancer or fibrosis even inthick tissues as it can go deep into thick tissues without need of fluorescence.This imaging technique has been used to elucidate the impact of collagenorganization on tumor progression [9, 10, 11]. In [9], three tumor-associatedcollagen signatures (TACS) were found by quantifying the relative anglesbetween collagen fibers and tumor boundaries. This study assessed changesin collagen fibers organization during progression of breast tumors [12, 5].Implemented in SHG, polarization analysis has already proved to reveal thefine structure of collagen [13, 14], including in vivo with a pixel-resolutionmapping of thick filaments’ orientation [15].The main drawbacks of SHG are the point by point scanning made with ahigh power short-pulse laser and the highly-sensitive camera that are neededto get images. Although SHG systems are already commercially available,the resulting prices and laser safety constraints could make it difficult tobe implemented as a routine diagnostic in hospitals. However combinationof different nonlinear microscopies are currently under development to beapplied to clinical and translational cancer research [16, 17, 4, 18].

1.3.2. Polarimetric techniquesPolarimetric techniques are suitable for tissue investigation as they are

sensitive to morphological changes at microscopic scale. Collagen fibers areoptically birefringent and thus directly imaged with polarization dependenttechniques [19]. Some standard polarization microscopes can provide quan-titative birefringence data on biological samples. In [20], the standard po-

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larized light microscopy is improved by using a liquid crystal universal com-pensator and circular polarization so as to be independent of the orientationof the sample. It provides retardance map and slow axis distribution ofanisotropic components of the sample. However, this system need a ded-icated microscope and needs 4 raw images with different polarizations tomake a retardance image.Mueller matrix imaging allows to deduce all the sample optical properties byanalyzing the light after its propagation through it. By using 16 combina-tions of polarization excitation/detection states, one can fully characterizethe optical properties of a sample. The strength of this technique is its abilityto work with partially polarized light and depolarizing media. Mueller matriximaging has already been applied to tumor imaging in the case of colon andcervical cancers [21, 22, 23] demonstrating its relevance. In the scope of tis-sue imaging, Mueller matrix imaging is now implemented for in vivo imagingof uterine cervix [23]. However, Mueller formalism and its implementationcan be quite heavy to extract full information from the sample. Indeed, itimplies a complex instrument to perform these measurements with differentand numerous polarization combinations and needs matrix decompositions[24]. In [23] imaging time is reduced as only 3 of the 16 terms are extracted:retardance, depolarization and azimuth.

1.3.3. Polarization Sensitive Optical Coherence TomographySince its first report in 1992, Polarized sensitive Optical Coherence To-

mography is now expanded in 3D and well established for the imaging oftissues and its anisotropic components [25]. The advantages of OCT is itsaxial resolution and its ability to image tissues structures in depth (up toone millimetre in the axial direction for semi transparent samples). Thanksto the use of polarization, quantitative information is added to highly con-trasted images of tissues [26, 27]. The main drawback is the point by pointscanning made with a high power short-pulse laser.The last technique that will be described here for tissue imaging is based onQuantitative Phase Imaging. We will show how its combination with polar-ized light can bring morphological and quantitative information comparableto polarimetric techniques for tissues.

1.3.4. Quantitative phase techniquesQuantitative phase imaging techniques are relevant for label-free tissue

imaging as they are in general easily implemented on conventional imaging

4

setups and allow the morphological study of biological components by in-creasing their contrast compared to classical brightfield imaging. Opticalphase microscopy has been largely developed for many years because of thehigh contrast enhancement that is brought in brightfield without any stain-ing or labelling. Based on refractive index differences between the sampleand the surrounding medium, phase techniques lead to specific propertiesmeasurements of semi-transparent samples.

Nomarski or differential interference contrast (DIC) is used routinely inlaboratories as its implementation on microscopes is easy. However, thistechnique is purely qualitative as some spatial frequencies are filtered. Togo one step further, numerous quantitative phase techniques were recentlydeveloped to make phase imaging quantitative.

Digital Holography, first demonstrated by [28], is the most representedphase technique in the community. Thanks to technical improvements, thistechnique get an increased interest in 1999 [29] with the first application tobiological imaging. Several teams are still using this technique, with variousimplementations to increase the resolution, the sensitivity or the practicality[30, 31, 32, 33, 34, 35]. Diffraction phase microscopy invented in 2006 [36]is an adaptation of a digital holography setup on axis. This technique wasmodified to get one measurement with one interferogram using a diffractiongrating and a filtering system [37] and get in compacity [38]. We can alsocite Fourier phase microscopy (FPM) [39], spiral phase microscopy [40] andspatial light interference microscopy (SLIM)[41] where a phase modulationis implemented to get phase information thanks to several images recordedsuccessively. Finally, we can cite Tomographic bright-field imaging (TBFI)based on the transport on intensity equation (TIE) [42] that allows phasemeasurements thanks to electromagnetic field propagation from images takenin one plane.

Thanks to numerous studies, it was shown that the optical thicknessdistribution can be directly used for refractive index measurements [43, 32,44, 45], leading to various measurements on different cell lines getting growthrates, morphological responses to infection [46], or inflammatory processes intissues [47] and dry mass [48, 49, 50, 51].

Though imaging fibers and cells is immediate with QPI, this contrast isnot specific. For instance, discriminating cells from fibers and other tissuecomponents is difficult and fiber organization studies are possible only frommorphological information. In this paper we propose taking benefit of phasechanges with illumination polarization (retardance) which takes place for

5

anisotropic components such as fibers to separate cells and fibers in tissueimages. Several phase techniques have been developed using polarimetricproperties so as to quantify retardance [52, 53, 54]. In the following, wepropose to use Quadri wave lateral shearing interferometry (QWLSI) asso-ciated with a high speed polarizing system to create fiber specific contrastenhancement in tissues.

2. Retardance measurement with QWLSI (Material and methods)

2.1. IntroductionQuantitative Retardance measurement using QWLSI was proposed in [1].

In this paper, we show that for the small birefringence levels which are en-countered in tissues, the Optical Path Difference (OPD) measured with ourwave front sensor is a sinusoidal function of the incident polarization direc-tion. Therefore we illuminated our samples with varying linearly polarizedlight and recorded the Quantitative Phase Images with our wave front sensorbased on QWLSI. If we consider that light propagates through a birefringentmedium with ordinary and extraordinary refractive index respectively no andne, the measured OPD as a function of the incident polarization direction θ,as defined in [1], is given by:

OPDmeasured(θ) = OPDavg + (∆δ2 ) cos 2(θ − θ0). (1)

where OPDavg =∫(no+ne

2 − nmedium)dz is the OPD that would be measuredwith unpolarized light, ∆OPD =

∫(no−ne

2 )dz is the retardance, and θ0 thedirection of the birefringence optical axis.For isotropic objects, the measured OPD remains identical for any polariza-tion direction. Therefore OPDavg leads to morphological information on thesample whereas anisotropy specific information is contained in ∆OPD × θ0.The latest is also a very useful parameter since it relates to the fiber orien-tation. By measuring polarization dependent phase-shifts, we can measurethe refractive index variation which can be directly linked to retardance andorientation (see Figure 1).

6

Figure 1: Illustration of the post processing principle of the OPD polarized stack of imagesto create retardance and orientation images. (left) Stack of quantitative phase images.(top right) Retardance (∆OPD). Only anisotropic objects generate signal in this image.(bottom right) Orientation map. We plot here the value of θ0. The more uniform thecolors the more organized the fibers are.

The new contrast created comes directly from the anisotropic nature ofthe components inside the sample. The theoretical justification of the prin-ciple is demonstrated in [1]. Phase images are processed pixel by pixel. Thephase value variation for the different images is fitted by a sinusoidal curvefrom which we extract local retardance and orientation (see Figure 2).

θ00 2̟

OPD (nm)

Ѳ(rad)

Δn thickness

(retardance)

x

x

x

x

x

x

x Experimental point

Fit

.

Figure 2: Illustration of the polarization dependent OPD measurement. Experimentaldata points obtained for different polarization angles θ are fitted to extract retardanceand main optical orientation θ0.

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2.2. Experimental setup2.2.1. Introduction

We work with a non-modified inverted microscope (TE2000-U, Nikon,Japan) on which we added a 632±22 nm bandpass filter (AHF, Germany)in order to avoid sample refractive index dispersion and work in accordancewith the polarizing optics. We used a Nikon objective (magnification 40x,NA = 0.75) and a transmission Köhler illumination with closed aperture di-aphragm to ensure a high spatial light coherence. This is necessary to assumethat a plane wave propagating along the optical axis illuminates the sampleorthogonally to its (x,y) plane. The wave front sensor (SID4Bio, Phasics SA,Palaiseau, France), based on QWLSI, was mounted on a C-mount adapter onone microscope’s exit port so that the detector plane matches the microscopeimage plane (see Figure 3).

The wave front sensor is a quadri wave lateral shearing interferometerbased on the recording of 4 replicas self-interferences of an incident beam.The replicas are created by the diffraction of the electromagnetic field thanksto a diffraction grating (Modified Hartmann Mask (MHM)) [55]. These in-terferences, occurring in the microscope image plane, are analyzed by a nu-merical Fourier transform and integrated to retrieve intensity and phase in aquantitative way [56]. To be able to measure the birefringence retardance weshowed in [1] that we only need to illuminate the sample with linearly polar-ized light and record the transmitted wave front without any further analyzerpolarizer. This makes the technique very easy to implement since there is noneed to synchronize the source and the analyzer polarizing directions.

To generate varying linearly-polarized states, we previously used a lin-ear polarizer in a rotating mount, which is placed in the microscope fieldstop plane. However this means was very slow and it took more than 10s torecord a retardance image stack. We introduce here a new polarizing systemto excite the sample with linear polarization. It is based on the ability ofliquid crystal to change their birefringence properties when they are locatedwithin an electric field. The used polarizing system associates a linear po-larizer (LPVIS100-MP2, Thorlabs, USA), a liquid crystal cell (LCC1223-B,Thorlabs, USA) and a quarter wave plate (WPQ10M-694, Thorlabs, USA).The system is placed in a cage support into the illumination light path beforethe sample and preferably as close as possible to the microscope field stop.

To drive the liquid crystal, an electronic device composed by a signalgenerator (NIDaQ, National Instruments, Austin, USA) is used to generate

8

CCD Camera

MHM

QWLSI

Tube lens

Microscope

objec!ve

Sample

Spa!ally coherent

Köhler illumina!on

Condenser

x

z

y

Linear polarizer

Closed aperture diaphragm

Liquid crystalQuarter wave plate

45° Rota!ng linear polariza!on

Optical axes

relative angles

-+

Figure 3: Experimental setup scheme to measure retardance signal of anisotropic compo-nents in biological samples

a 2kHz modulated square signal whose amplitude determines the voltageat the liquid crystal terminals. This device is driven by a computer usinghomemade LabView (National Instruments, Austin, USA) software to choosethe voltages and finally the polarization angles.

2.2.2. Arbitrary linearly-polarized light generation principleThe relative orientation of the three polarizing components is set so as

the polarization at the exit is linear and controlled by changing the voltageon the liquid crystal cell. The optical axes of the linear polarizer and thequarter wave plate are aligned and oriented at 45◦ of the optical axes of theliquid crystal, so that the output polarization is linear (see Figure 3). We

9

can explain this alignment thanks to Jones formalism as follows:

(Jsystem) = (JQWP ) · (JLC) · (JP ) (2)

where (J) refers the Jones matrices of the system and its optical components.

JQWP is the quarter wave plate Jones matrix such as (JQWP ) =( 1 0

0 −i

),

(JP ) is the polarizer jones matrix such as(JP ) =( 1 0

0 0

)and (JLC) is the

Jones matrix of the liquid crystal cell written as a general phase retarder ofamplitude α, which axis is rotated by an angle θ with respect to the X-axis:

(J) = ( cos θ sin θ− sin θ cos θ )

( 1 00 eiφ

)( cos θ − sin θsin θ cos θ

)(3)

(J) = eiφ2

( cos(φ2 ) + i cos 2θ sin(φ2 ) i sin 2θ sin(φ2 )i sin 2θ sin(φ2 ) cos(φ2 ) − i cos 2θ sin(φ2 )

)(4)

The resulting system Jones matrix is

(J) = eiφ2

( cos(φ2 ) + i cos 2θ sin(φ2 ) 0i sin 2θ sin(φ2 ) 0

)(5)

Therefore an arbitrary input polarization exits the system with a linearlypolarized state as soon as the too components of the Jones matrix first columnhave the same complex argument. This is true for any phase retardance φas soon as 2θ=π

2 or θ = π4 .

Finally for any incident polarization, the output beam is linearly polarizedwith a polarization angle making an angle φ

2 with the X-axis.

2.2.3. CharacterizationThe optical system was characterized to evaluate the measurement errors

on retardance and orientation for this application. The errors and uncertain-ties were discussed in [1]. Here, three sources were identified.

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Reference and acquisition noise. While using QWLSI, in order to take intoaccount static effects introduced by the optical components (objective, illu-mination optics) which contribute to the final measurement, we record atthe beginning of any experiment a reference interferogram that will be sub-tracted from the image interferogram [56]. In this case, a stack of polarizedreference wave fronts, corresponding to the exact same polarizations that areused for images, is recorded in an element-free region of the sample [1]. Thisstatic OPD distribution will be systematically subtracted to all subsequentacquisitions.

The main source of noise comes from the OPD imaging (i.e. cameranoise). Its effect is to reduce the OPD resolution. To limit this noise, wechoose to make image averaging.In [1], we measured for different conditions of reference and image averag-ing, the OPD standard deviation. Interferograms for reference and imageare respectively averaged 30 and 5 times. In this case, the OPD standarddeviation is of 0.25 nm.

The second source of noise is linked to the polarizing system.

Polarization purity. A rotating linear polarizer and a photodiode were usedto analyze the polarization at the exit of the system and measure the quantityof light transmitted. The analysis angle was changed step by step and a powermeasurement was done. By analyzing the polarization at different angles, weobtained a sine curve characteristic of the Malus law. The contrast calculatedfor this polarization angle was 0.995. The same experiment was done fordifferent voltages (i.e. different incident polarization angles). Results areshown in the Figure 4. By changing the voltage and rotate step by step theanalyzer, we measured the contrast for different polarization angles findingcontrast values always superior to 0.98.

Polarization fluctuation. For this new setup, the effect of the liquid crystalwas considered. Its contribution to the noise is essentially the polarizationfluctuations. The polarization stability was characterized by two ways: first,by changing the voltage to create a sequence of polarizations from 0◦ to 180◦.Repeating this sequence 5 times, we found a standard deviation less than 0.2◦

(see Figure 5). Then, without any voltage changes, we measured intensityfluctuations at the exit of the system and convert these changes in degrees.The fluctuation is less than 0.1◦.

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3400 150 25050 200100 300

Po

we

r a

t th

e s

yste

m e

xit

(µW

)

Analyzer angle (°)

1

0.99

0.98

0.97

0.96

0.95

Voltage at LC terminals (V)

Co

ntr

ast

Polarization angle (°)

0 270 340 370 375 380 390

Figure 4: Photodiode signal variation with continuous variation of the analyzer orientationat the exit of the polarizing system (left) and contrast measurements for different voltagesapplied to the liquid crystal (LC) (i.e. different incident polarizations) (right).

Po

lari

sati

on

an

gle

sta

nd

ard

de

via

tio

n (

°)

Voltage at LC terminals (V)

0 205 10 15

0.2

0.4

0.6

0.8

1

Figure 5: Polarization standard deviation over 5 measurements at the system exit fordifferent voltages applied to the liquid crystal.

The consequences of these fluctuations are negligible on retardance mea-surement as it induces a difference inferior to 0.01nm on OPD standarddeviation [1].

Polarization state switching time. The system rapidity and the retardanceresolution were measured.

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0 500 1000250 750

Am

pli

tud

e (

AU

)

Time (msec)

Experimental data with overdrive

Experimental data without overdrive

Figure 6: Example of switch time optimization while using overdrive (10 V during 0.001sec)to go from 1.8 to 2V (i.e. polarization rotation of 30◦).

The switching time was measured and optimized to decrease as much aspossible the time needed to establish the wanted polarization. An exampleof optimization is shown in the Figure 6. An optimized sequence (finding therelevant voltage steps corresponding to polarization rotations of about 30◦

between each steps) and overdrive implementation (i.e. application of highvoltage during a limited time to increase the rising time) lead to switchingtimes inferior to one millisecond. The polarizing system is no longer the lim-iting factor for the retardance imaging system in terms of time and possiblycompatible with live imaging.

One retardance image is now recorded in 0.3 second (versus 10 secondsusing a polarizer in a rotating mount). This is mainly due to the cameraintegration time (classically, about 45 msec using this setup with 40× mag-nification).

Quantitative Retardance Imaging accuracy. Thanks to a simulation tool de-veloped in [1], we showed that, for typical retardance values in biologicalsamples of about 10 nm to 100 nm, by taking into account the way interfer-ograms are generated in QWLSI while using polarized light, the error madeis 0.08 nm for 100 nm and about 0.015nm for 20 nm (see Figure 4).

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Ab

solu

te e

rro

r o

n r

eta

rda

nce

(µ

m)

Theoretical retardance (µm)

Ab

solu

te e

rro

r o

n r

eta

rda

nce

(µ

m)

Theoretical retardance (µm)

(x 10-3)

(a) (b)

Figure 7: Calculated absolute errors on retardance measurements obtained with a simu-lation tool for theoretical retardance values from 0 to 3µm (left) and from 0 to 0.10µm(right).

2.3. Image processing from slide scansThe image stitching of 1mm2 requires 10.5 seconds using 40×magnification

and 10%overlapping. This magnification allows to keep a nice resolution onOPD images and the overlapping is optimized to avoid stitching reconstruc-tions problems. For the different polarization angles, a 400 x 300 pixels OPDimage is recorded. At 40× magnification, one pixel measures 0.74 µm. To re-construct a 1 x 1 mm2 area thanks to image stitching, 35 images are needed.The acquisitions post processed to create OPD images. The stitching is au-tomatically reconstructed thanks to a Fiji plugin (Image Stitching Plugin,Fiji, USA).

Different images can be processed from the polarized stack of images:

• Averaged OPD: morphology information thanks to OPD. Visualizationof cells, fibers and other tissue components. For each pixel, the contrastequal to (nsample − nmedium) × thickness.

• Retardance: anisotropic response of fibers. For each pixel, the contrastis directly (ne − no) × thickness.

• Orientation: main orientation of the fibers optical axis. For each pixel,the color codes for the orientation and the signal intensity is linkedto the retardance value. The brighter, the more birefringent. Theorientation is also plotted in a polar plot. Each pixel orientation isconsidered to create a histogram of orientations.

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3. Results

3.1. Hematoxylin and Eosin (H&E) stained mouse skin tissueThis technique was applied on three different samples of mouse skin tis-

sue of 14µm thickness. The samples were stained and embedded in paraffinto create slices and deparaffined to be imaged. We showed in [1] that re-tardance imaging has the sensitivity and the specificity to reveal isolatedcollagen fibers in Paraformaldehyde-fixed mouse tail tissue. Here, we can seequalitative evidence of the ability to image collagen fibrillar assemblies incomplex tissues.

0

20

nm

0

250

nm

90°-

90°

OPD Retardance

Orientation Composite Polar plot

Bright!eld

Figure 8: Normal stained mouse skin slice tissue of 14µm thick. Brightfield (top left), OPD(top center), retardance (top right), composite (bottom left), orientation (bottom center)images and polar plot (bottom right). 455 x 717 pixels, 340 x 530 µm. Retardance andorientation images were processed from 6 OPD images obtained with different polarizationsgoing from 0◦ to 150◦. Scale bar = 35 µm.

Figure 8 presents the different information that can be extracted from ourQPI images. We can see that the OPD image is very similar to the brightfieldimage of the stained tissue as every morphological elements can be clearlyidentified (holes and collagen fibers in this case). Few cells are present in themiddle of collagen fibers. They represent the darkest points on the image,meaning that they introduce a higher phase shift (e.g. higher optical density)than the fibers. On the retardance image, the contrast created is specific to

15

the fibers. The cells and parts without any fiber are no longer visible on thisimage. The retardance and the orientation are directly coded in false colorsin two different images. On the retardance image, the more birefringent, thebrighter the fibers are on the image. The local orientation is coded in colorson the image and a histogram of orientations is plotted to give a statisticalrepresentation of the global orientation of the collagen fibers in the tissue.We can see that the collagen is organized in curve shaped bundles. We canvisualize the degree of orientation randomness in a polar plot histogram ofthe orientation angles found in the image. Their orientation in the tissue ismostly isotropic (see Figure 8).

A second tissue was imaged corresponding to an early tumoral develop-ment in mouse skin. A large section of the tissue was imaged. Different

0

20

nm

0

390

nm

90°-

90°

OPD Retardance

OrientationComposite Polar plot

Bright!eld

OPD Retardance Orientation Polar plot

(a)(b) (c)

(d) (e) (f )

(g)

(e)

(h) (i) (j)

Figure 9: Early stage of tumoral stained mouse skin slice tissue of 14µm thick. Brightfield(top left), OPD (top center), retardance (top right), composite (bottom left), orientation(bottom center) images and polar plot (bottom right). 1866 x 1428 pixels, 1380 x 1056µm. Retardance and orientation images were processed from 6 OPD images obtained withdifferent polarizations going from 0◦ to 150◦. Scale bars = 60 µm.

16

morphological elements can be clearly identified (cells organized in clusters,holes and collagen fibers). The cells represent the darkest areas on the image,introducing a high phase shift. On the retardance image, the contrast createdis specific to the fibers. The cells and parts without any fiber are no longervisible on this image. This allows us focusing only on the fibers and theirorientation. A zoom on collagen fibers at the tumor boundaries was madeto highlight the modification in fiber orientations (see Figure 9). We can seethat the fibers are more oriented in this tissue (see the polar plot in Figure9) than it was in the normal tissue previously described. Around the tumor,the fibers are parallel to its boundaries and stretched. This first modificationof the collagen structuration was described in [9] corresponding to the TACS1 and 2 i.e. denser fibers and parallel organization around tumor boundaries.

A more advanced stage of tumoral tissue was imaged. We can find on thebrightfield and phase images similar morphological information. We see densegroups of tumoral cells assembled in clusters within the ECM. Collagen fibersare now stretched in the tissue between tumoral cells and showing two mainorientations. They are now oriented orthogonally to the tumor boundaries(see Figure 10). This was previously described in [9] as TACS 3 where theECM fibers are remodeled to help the tumor invasion and characterize themost invasive tumors.

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0

20

nm

0

390

nm

90°-

90°

OPD Retardance

OrientationCompositePolar plot

Bright!eld

OPD Retardance Orientation Polar plot

(a)

(b) (c)

(d) (e)(f )

(g) (h) (i) (j)

Figure 10: Advanced stage of tumoral mouse skin slice tissue of 14µm thick. Brightfield(a), OPD (b) &(g), retardance (c) &(h), composite (d), orientation (e) &(i) images andpolar plot (f) &(j). 4152 x 2136 pixels, 3072 x 1580 µm for (a) to (e) images and Zoomon the blue dotted area (OPD image) of 660 x 597 pixels, 488 x 441 µm. Retardance andorientation images were processed from 6 OPD images obtained with different polarizationsgoing from 0◦ to 150◦. Scale bars = 120 µm.

3.2. Unstained human breast tissueWe also applied our technique to human breast tissue imaging. In this

case, we imaged unstained slices to avoid any effect of the staining on theretardance imaging. In addition, adjacent slices were stained with hema-toxylin and eosin to compare and correlate the results of our observations.The brightfield image is obtained on the stained sample and the phase imag-ing was done on the unstained adjacent slide of the same tissue. We can seethat, even on unstained tissues, the contrast on the OPD image remains high.

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We first study healthy tissue. Two areas of this normal tissue are imagedand shown in Figure 11.

0

20

nm

0

250

nm

90°-

90°

OPD Retardance

Orientation Composite

Polar plot

Figure 11: Normal unstained human breast slice tissue. Brightfield (top left), OPD (topcenter), retardance (top right), composite (bottom left), orientation (bottom center) im-ages and polar plot (bottom right). 1070 x 818 pixels, 791 x 605 µm. Retardance andorientation images were processed from 6 OPD images obtained with different polariza-tions going from 0◦ to 150◦. Scale bars = 40 µm.

We can see that collagen fibers have an isotropic orientation in the tissue(see Polar plot of figures 11 & 12). On the first area (Figure 11), we focusedon collagen fibers. We can see that the fibers have a shape similar that whatwas already observed on the healthy mouse skin tissue. In the second figure(Figure 12), we imaged a heterogeneous area including luminal and basal cells(area outlined in blue) adipocytes (area outlined in red) and muscle (areaoutlined in green). All those components do not appear on the retardanceimage as they are not anisotropic. We can see that collagen fibers have arandom orientation in the ECM. A zoom on a chosen area is shown in thesame Figure where we can see that there is no main orientation thanks tothe orientation image and polar plot.

19

0

20

nm

0

330

nm

90°-

90°

OPD Retardance

OrientationComposite Polar plot

Bright!eld

OPD Retardance Orientation Polar plot

(a)(b) (c)

(d) (e) (f )

(g) (h) (i) (j)

Figure 12: Normal unstained human breast slice tissue. Brightfield (a), OPD (b) &(g),retardance (c) &(h), composite (d), orientation (e) &(i) images and polar plot (f) &(j).1000 x 832 pixels, 740 x 615 µm. Zoom on an area of 300 x 300 pixels, 222 x 222 µm of thetissue. Retardance and orientation images were processed from 6 OPD images obtainedwith different polarizations going from 0◦ to 150◦. Scale bars = 70 µm.

A tumoral breast tissue was imaged to compare collagen signals betweentumorous and healthy tissues. We can find on the brightfield and phaseimages dense groups of cells (darker points on the phase image) corresponding

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to normal cells (area outlined in blue) and less organized tumoral cells (areaoutlined in red). The collagen fibers are thinner and located at the edges ofthe two areas in the ECM. They show a preferential orientation which canbe seen on the zoom in Figure 13 thanks to the polar plot.

0

20

nm

0

235

nm

90-

90

OPD Retardance

OrientationComposite Polar plot

Bright!eld

OPD Retardance Orientation Polar plot

(a)

(b) (c)

(d) (e) (f )

(g) (h) (i) (j)

Figure 13: Tumoral unstained human breast slice tissue. Brightfield (a), OPD (b) &(g),retardance (c) &(h), composite (d), orientation (e) &(i) images and polar plot (f) &(j).689 x 857 pixels, 509 x 634 µm. Zoom on an area of 499 x 211 pixels, 369 x 156 µm of thetissue. Retardance and orientation images were processed from 6 OPD images obtainedwith different polarizations going from 0◦ to 150◦. Scale bars = 60 µm.

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4. Conclusion & Perspectives

We demonstrated that our technique is sensitive enough to image col-lagen fibrillary assemblies in tissues. Using phase and retardance imagingby adding a single polarizing system in the illumination path, we obtaincomplementary information about the tissue. Morphological and quanti-tative parameters and measurements are brought by phase and retardanceallows to specifically study collagen fibers and their organization. Using 40 xmagnification, we can achieve a lateral resolution of 0.74 µm which appearssufficient in this study to image most of the tissues components of interest(individual cells and collagen fibers). The sensitivity of our retardance de-tection was quantified: the standard deviation on our retardance images is0.015 nm for structures of 20 nm (i.e. thin collagen fibers) and of 0.08 nmfor thicker assemblies of about 100 nm retardance.

The use of this technique on various tissues showed that objective differ-ences between normal and different stages of tumor development in tumoraltissues can be quantified . Some known collagen structures associated withtumors previously described using SHG techniques were highlighted thanksto our technique. This first feasibility study opens perspectives for the au-tomatic processing and classification of characteristic features of fibers intissues. The plans for the future is to make an automatic imaging and anal-ysis tool to scan a larger number of tissues to define the most specific andrelevant features describing the different states (i.e. healthy or tumoral) andthe different stages in tumoral development. Additional quantitative datassuch as average retardance and orientation over large areas of the tissue couldhelp to automatically detect and segment tumoral developments accordingto differences in texture or homogeneity. It could be of high interest to seeif we can discriminate between different types of collagen according to theirrefractive index or composition.

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Conflict of Interest: The authors declare the following competing finan-cial interest: financial support came from the Phasics company as SA is aR& D engineer in the latter.

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