A customized multispectral needle probe combined with a virtual photometric setup for in vivo detection of Lewis lung carcinoma in an animal model [original]

Measurement Science and Technology

A customized multispectral needle probe

combined with a virtual photometric

setup for in vivo detection of Lewis lung

carcinoma in an animal model

FrankBraun1, RobertSchalk1, MarcelNachtmann1, AndreasHien1,

RudolfFrank1, ThomasBeuermann2, Frank-JürgenMethner3,

BettinaKränzlin4, MatthiasRädle1,5 and NorbertGretz4,5

1 Center for Mass Spectrometry and Optical Spectroscopy, Mannheim University of Applied Sciences,

Paul-Wittsack-Str. 10, 68163 Mannheim, Germany

2 Institute for Process Control, Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163

Mannheim, Germany

3 Institute of Biotechnology, Technical University of Berlin, Chair of Brewing Science, Berlin, Germany

4 Medical Research Center, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim,

Germany

E-mail: [email protected]

Received 2 January 2019, revised 13 May 2019

Accepted for publication 24 May 2019

Published 8 August 2019

Abstract

Optical systems applied for tissue analysis are primarily based on single spectroscopic

techniques. This paper however presents a multispectral backscattering sensor designed for

in vivo application by a specially formed probe tip which allows side by side monitoring of

ultraviolet, visible, near-infrared and fluorescence spectra. The practical applicability of the

measurement system was demonstrated in vitro (muscle and adipose tissue) and in vivo in an

animal model (mouse). By comparing associated measuring changes in biochemical, physical-

morphological and colorimetric values this procedure allows a differentiation between healthy,

marginal and malignant tissue.

Keywords: multispectral needle probe, UV/VIS/NIR/fluorescence (FL) tissue spectroscopy,

in vivo cancer/carcinoma/diagnostics, animal model for Lewis lung cancer, Nitinol fiber-optic

probe for oncology, photometric setup

Supplementary material for this article is available online

(Some figuresmay appear in colour only in the online journal)

F Braun etal

Printed in the UK

104001

MSTCEP

Meas. Sci. Technol.

MST

10.1088/1361-6501/ab24a1

Paper

Measurement Science and Technology

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Original content from this work may be used under the terms

of the Creative Commons Attribution 3.0 licence. Any further

distribution of this work must maintain attribution to the author(s) and the title

of the work, journal citation and DOI.

5 Norbert Gretz and Matthias Rädle contributed equally to this work.

2019

1361-6501

1361-6501/19/104001+12$33.00

https://doi.org/10.1088/1361-6501/ab24a1

Meas. Sci. Technol. 30 (2019) 104001 (12pp)

F Braun etal

1. Introduction

Cancer ranks number two among the causes of death annu-

ally; more than 14 million new diagnosed cases occurred in

2012 [1]. Estimations forecast that over 22.2 million cases

will occur in 2030 [2]. The challenge is to detect malignant

neoplasia at an early stage to increase the probability of cure.

Therefore, many efforts have been undertaken to improve

the detection of tissue changes. Classical diagnostic methods

range from palpation, imaging methods such as MRI, scintig-

raphy or computed tomography, to immunological methods.

To date, different biopsy techniques with subsequent evalua-

tion by a pathologist based on microscopy images in a labora-

tory are the gold standard for diagnosis of tissue alterations

[3, 4]. The biopsy procedure is one of the most frequently

performed clinical interventions [5]. Each histopathological

examination is usually carried out by hand—not automati-

cally, and generally very cost intensive. In such cases, optical

spectroscopy, especially for prevention and early diagnosis,

offers benefits as a minimally invasive preselection and sup-

porting tool implemented during the biopsy procedure.

Optical spectroscopic techniques for the detection of cancer

have become of increasing interest since the 1990s. The state-

of-the-art of the respective developments is summarized. The

sample preparations range from cooled, shock-frozen [6, 7],

formalin-fixed paraffin-embedded (FFPE) sectionsto unfixed

frozen or fresh tissue [8]. Pancreatic and colorectal cancer

have been detected in fresh biopsies without post-treatment

using near infrared (NIR) spectroscopy [9, 10].

The analyses are mainly based on the determination of

the tissue composition, such as water [11], fat [12, 13], col-

lagen [14, 15] or hemoglobin (Hb) [16]. In addition, oxygen

satur ation or the oxygen requirement of tissue can be used

[17]. The content of the red blood pigment Hb is an impor-

tant marker in cancer diagnosis and is detectable in vivo via

fiber optical spectroscopy. Solid tumors depend on a growing

capillary network (tumor-induced angiogenesis), which sup-

plies the tumor with oxygen and nutrients. For growth beyond

a volume of 1 to 2 mm3, the formation of new blood vessels

is necessary. Without this opportunity for nourishment, non-

angiogenic neoplasias are restricted to a symptomless and not

clinically relevant size [18]. The results of Chen et al [19]

indicate that within each patient, the average Hb level in a

brain tumor is relatively higher than the average Hb measured

in the normal cortex. The overall average of six patients was

0.37 ± 0.18 g dl−1 in the normal cortex and 0.99 ± 0.57 g dl−1

in tumor tissue [19]. Because Hb is a strong VIS and NIR

radiation absorber, spectral data are used as a reference for

blood flow [20]. To evaluate the concentration of connective

tissue, it is best to choose a spectral range with a low absorb-

ance in the ‘optical window of tissue’ [21, 22] using elastic

light scattering techniques [22].

In addition to absorption methods, fluorescence (FL) emis-

sion diagnostics are commonly used to recognize skin [23],

bladder [24], lung [25], and cervical [26] cancer. In this

spectroscopic technique, nicotinamide adenine dinucleotide

hydrate (NADH) is a significant marker [27–30]. NADH FL

serves as an indicator of cell metabolism and redox state as

well as of oxygen deficiency and disorders in the respiratory

chain [31, 32]. An increase in the NADH concentration and

thus its FL emission signal indicates a decline in tissue activity

and a concomitant low NADH consumption [33]. In contrast,

a decreased concentration in tissue shows an increase in meta-

bolic cell activity [34]. The change of NADH concentrations

are generally used for tumor localization, because tumorous

tissue has a reduced FL compared with normal tissue [26].

In addition, FL-spectroscopy can be combined with diffuse

reflection, as described in a publication relating to the detec-

tion of cervical cancer precursors in vivo [35].

Based on the current state of the art and the various methods

as described we saw great potential in combining several spec-

tral methods (UV/VIS, NIR, FL) in one multispectral in vivo

probing system for several purposes: to shorten the time of

the diagnosis, to reduce the numbers of surgical interventions,

thus making it—if put to practice—less stressful for patients,

and hopefully more economic. As a valuable example and a

model for our evaluations we have chosen mice with Lewis

lung cancer and compared our detection methods with clinical

results.

2. Materials and methods

2.1. Animal model and procedure

As a mice model, the well-known and reproducible model

Lewis lung carcinoma is used. Female SPF NMRI mice

(approximately 12 weeks old) were purchased from Janvier-

Labs (Le Genest St. Isle, France) and provided with free

access to standard food and water. In vivo experiments were

performed according to EC directive 2010/63 EU. Six mice

were injected subcutaneously in the flank region with 5 × 105

LLC P4 cells/mouse (Lewis lung carcinoma cells in 100 µl

of phosphate-buffered saline solution). After approximately

2 weeks, the carcinoma in situ had grown to a size of approxi-

mately 1 cm3, which allowed us to examine the animals under

anesthesia (medetomidine 0.5 mg kg−1 BW (Eurovet/Albrecht

GmbH, Aulendorf, Germany), midazolam 5 mg kg−1 BW

(Ratiopharm GmbH, Ulm, Germany), fentanyl, 0.05 mg kg−1

BW (Janssen Cilag, Neuss, Germany)). After shaving and

disinfection of the skin, a small skin cut of approximately

1–2 mm in the vicinity of the tumor allowed minimal inva-

sive entry of the multispectral needle. Throughout the proce-

dure, the temperature of the animals was kept constant using a

warming plate. In addition, an in vitro pilot test was performed

stitching in adipose and muscle tissue samples. The observed

measurement effects are explained in detail in section 3.2,

performing an in vitro pilot test of tissue samples.

2.2. Measurement setup for multispectral analysis

The multispectral in vivo measurement setup is illustrated

schematically in figure1.

The fluorescence of the sample was excited with a light

emitting diode (purple) (365 nm LED, NCSU 033B, Nichia,

Tokushima, Japan) and the corresponding fluorescence emis-

sion spectrum was detected using a MCS CCD/UV-NIR

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spectrometer from Carl Zeiss AG, Jena in Germany. The LED

is an UV-light emitting diode with an emission maximum at

365 nm and a spectrum half width of 9 nm. The optical power

output measured at the probe head is approximately 160 µW.

The LED was externally triggered and emits light only in the

integration time of the fluorescence measurement sequence.

Subsequently, this spectrometer is named as fluorescence

spectrometer (blue). In order to induce the sample’s absorb-

ance, a broadband halogen lamp (yellow) (CLH 600, Carl

Zeiss AG, Jena, Germany) is utilized. The color temperature

of a Planckian radiation illuminant A is 2854 K, as specified

by the International Commission on Illumination (CIE). The

tungsten–halogen luminaire has a similar color temperature

of 2900 K, as specified by the manufacturer. To minimize the

photon flux on the sample the luminaire is operated in a spe-

cial mode: The shutter is only opened for integration time of

the momentary measuring sequence. Furthermore, the light

source is very weak and is strongly attenuated by an SMA

coupling with only 200 microns core-diameter.

The absorbance spectra were calculated based on remission

spectra recorded with the aid of two spectrometers. While one

spectrometer detected the remitted light in the UV/VIS-range

(light red) (MCS 621 VIS II, Carl Zeiss AG, Jena, Germany),

the other spectrometer was used to measure the remission

spectrum in the NIR range (red) (MCS611 NIR 2.2, Carl Zeiss

AG, Jena, Germany). The spectra were recorded with dif-

ferent integration times (100 ms for UV/VIS, 200 ms for NIR

and 250 ms for FL spectroscopy) using the software Aspect

Plus® (Version 2.3, Carl Zeiss AG, Jena, Germany). The ref-

erence material used is a Spectralon® Diffuse Reflectance

Standard (SphereOptics GmbH, Herrsching, Germany), with

a Lambertian reflectance value of 99% and a constant reflec-

tion of ±4% over the wavelength range of 250 nm–2500 nm.

The measurement sequence was started with FL followed by

UV/VIS and NIR measurements with continuous dark current

correction and then by analysis with Unscrambler® X (CAMO

Software AS, Norway) as the multivariate analytical software.

To exclude autoFL in the setup and ambient light, the meas-

uring arrangement was shielded by two layers (black fabric

as the outer layer and carbon black polymer foil as the inner

layer). For a higher signal-to-noise ratio, mean values were

calculated from three measurement data sets.

As a measurement probe, a multispectral needle is used

to obtain the different spectra. This probe was connected to

the light sources and the spectrometers via optical fibers. A

detailed description of the probe is given in the following

section. For precise movement along the axis, the probe was

attached to a linear system (Spindler & Hoyer, Göttingen,

Germany).

The entire setup, including the multispectral needle, was

evaluated by UV/VIS, NIR and FL measurements in a liquid

tissue phantom [22, 36]. Additionally, its MRI capability was

confirmed by measurements tracking the needle position in a

biological phantom [22].

2.3. Design of the needle probe for multispectral in vivo

diagnostics

The probe consisted of seven quartz fibers (numerical aper-

ture (NA) 0.22, core/outer-diameter: 200/250 µm, Edmund

Figure 1. Remission measurement setup for multispectral in vivo tissue analysis. The setup consisted of two light sources, three

spectrometers and a multispectral needle probe to obtain UV/VIS, NIR-remission and fluorescence emission spectra. The coloring and

numbering represents the coding for the connection, see also figure2.

Meas. Sci. Technol. 30 (2019) 104001

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Optics Ltd, York, UK) that were stuck together in the probe

head. Adapted to the application, an epoxy resin (EPO-TEK®

353ND, Epoxy Technology Inc., Billerica, USA certified to

USP Class VI and ISO 10993 biocompatibility standards for

medical implants) was used to fill the gaps and fix the fibers,

shown in figure2. This adhesive is also compatible with the

CIDEX® OPA sterilization standard.

The optical fibers were bundled in one ultrasound- and

MRI-compatible 1.1 mm 19 G needle probe (inner diam-

eter 0.785 mm, stainless steel cannula, Sterican, B. Braun

AG, Melsungen, Germany) or Nitinol capillary [37–39]

(Endosmart® Gesellschaft für Medizintechnik mbH,

Stutensee, Germany) with a special beveled head designed

similarly to a hypodermic needle for efficient penetration

into the tissue. The inner fiber was optimized for the UV/VIS

region (high OH content) and was used for FL excitation, and

the surrounding six fibers were ideally suited for the VIS/

NIR region (low OH content). The combination of different

optical properties in one probe head enabled the application

of various spectroscopic techniques side by side in vivo nearly

simultaneously without changing the setup. Using a distrib-

utor, the seven optical fibers were separated into shielded

channels, which generally enable an individual and simulta-

neous selection of light sources and spectrometers or other

detectors via the SMA connection [40]. The penetration depth

of the needle in a liquid tissue phantom with similar scattering

coefficients, such as human pale forearm skin (Fitzpatrick

scale Type II), was approximately 0.8 mm [22]. The probe

setup was well suited not only for the presented investigation

but also shows benefits for future applications as described:

easy tissue penetration by a plane-ground head cut at a 30°

angle and a back-cut bevel (figure 2), manufactured from

biocompatible materials, which allow multiple use by auto-

claving and re-sharpening. Multi-wavelengths excitations or

the implementation of further detection channels are possible

for real-time measurement during the biopsy procedure. More

details and a local in vivo pulse measurement are shown in

the supporting information (stacks.iop.org/MST/30/104001/

mmedia).

2.4. Tracking of the needle position with ultrasound

and specific marking with a filament

In our investigation, the needle was tracked using a stan-

dard ultrasound system (Philips Sonos 5500, Philips Medical

System, Hamburg, Germany) with the following attributes:

depth setting 2 cm, frequency 76 Hz; and a Philips 15-6L

linear probe. During the application, the gel layer thickness

between the probe and skin was in the centimeter range to

overcome the minimum clearance for measuring tissue

directly under the surface. To identify the position of the punc-

ture channel, the needle was clearly marked with a polymer

filament (PROLENE, Johnson & Johnson Medical GmbH,

Norderstedt, Germany) attached with UV adhesive (Bondic®,

VIKO UG, Munich, Germany) on the side of the probe head.

The filament remained in the puncture channel for histopa-

thology after the probe was removed.

2.5. Preprocessing and data reduction of the multispectral

information by a virtual photometric structure

The recorded multispectral data (UV/VIS, NIR and FL) are

preprocessed by an application-driven method for data reduc-

tion. This method follows the step of the data acquisition. The

enormous amount of spectroscopic data generated (40 000

bytes per measuring point) is reduced by this specialized vir-

tual photometer structure to five specific measurement chan-

nels (figure3).

Figure 2. Optimized multispectral needle for efficient tissue penetration: cut at a 30° angle, including a back-cut bevel. The circularly

arranged fibers are inside the 19 G cannula, e.g. one UV/VIS fiber for FL excitation and six VIS/NIR fibers; see also figure1. The

dimensions of the needle and the optical fibers are illustrated at the bottom left. The coloring and numbering represents the coding for the

connection; see also figure1.

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The data type is an integer with two bytes per measurement

point and channel. The calculation was performed with basic

mathematical operations to use the hardware as efficiently as

possible. Thus, the spectral amount of data was reduced by

a factor of 4000—shown in figure 3. At a sampling rate of

50 Hz, which corresponds to 3000 measuring points min−1,

the amount of data before reduction is 120 megabytes min−1.

After preprocessing, it was reduced to 0.03 megabytes min−1

of system operating time. The flow chart for the described

application is illustrated in figure 3, including all summed-

up bandpasses and their wavelength-ranges for measurement

(MC) and reference channels (RC).

The channels were systematically selected from spec-

tral regions of high variance and the respective measurement

effect were assigned by literature. All channels, see figure3,

are determined by integration over the wavelength areas and if

necessary factorized for weighting. The measurements chan-

nels subtracted by the reference channel result in each channel.

The auto-FL-365 nm channel is based on a measuring

and a reference channel. The measuring channel detects the

maximum auto fluorescence emission. To compensate the

background a reference channel at longer wavelength region

is chosen.

The measuring channel of the red blood pigment Hb lies

in the green absorption region. As a reference for offset com-

pensation serves the optical window of tissue, which is domi-

nated by physical scattering and minimal absorption effects.

As a result, the matrix effect caused by scattering can be

compensated.

The deoxy form of Hb has a low absorption band within

the optical window of tissue. This absorption has distinct

advantage to other associated bands—no overlapping. The

result is a highly selective measurement. Since the measuring

effect is small, a very good compensation of the background

is important. For this reason, a reference channel was set both

short- and long-wave, and the mean was subtracted from the

measuring channel. In order to capture the tissue scattering as

purely as possible, the optical window between Hb and water

absorption is selected. This region of least tissue absorption is

largely dominated by scattering. Here, one measuring channel

was set, a reference channel would falsify or even eliminate

the target variable scattering. To detect fat, the measuring

channel was placed on the characteristic band of fatty tissue

and a short-wave reference was chosen to compensate the

background. As a result, pseudo-absorption effects caused by

scattering can be compensated.

2.6. Grouping of the reduced data via multichannel PCA

PCA is a statistical method used to reduce multidimensional

data to principal components (PCs). The resulting lower

dimensional coordinate system describes the recorded spec-

tral data from the different techniques applied, UV/VIS, NIR

and FL spectroscopy, in the form of five specific measurement

sensors/channels. The impact of each individual channel vari-

able on a PC is expressed in the loading spectra. The channels

themselves are described by their score values in the new PC

coordinate system.

Figure 3. Preprocessing of the multispectral data by a virtual photometric structure and grouping by PCA.

Meas. Sci. Technol. 30 (2019) 104001

F Braun etal

Figure 4. Ultrasonic tracking of the cannula position. The sonograms, labeled 1 and 2, show the needle probe and the typical metal

echogenic artifacts at different positions: position 1 before penetrating the malignant tissue and position 2 after the stitch procedure at the

end position.

Figure 5. Simultaneously generated VIS/NIR absorbance spectra of muscle and adipose tissue using the multispectral needle probe. The

optical window between oxy-hemoglobin and water is illustrated on the top left. In addition, the upper photo shows a direct measurement,

and the lower photo shows the color calculation.

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F Braun etal

The principle is shown in matrix notation [41]:

X=TPT+E

X=data matrix (lines are the samples; columns are the spectral values)

T=scorematrix (describing the samples : weighting)

transposed loadingmatrix

(

summarizes channel data : variables)

E=residual matrix (unexplained share : noise,error).

3. Results

3.1. Tracking of the multispectral needle probe and marking

of the stitch pathway

The live ultrasonic pictures of the probe during the tissue pen-

etration (from right to left) are illustrated in figure4.

The probe position was detectable by echogenic signals

and thus was known at any given time. This is a live in vivo

tracking of the needle in the mouse model study. The two solid

red arrows next to the probe and the pictures indicate the stich

position before and after.

Samples were collected and evaluated by a pathologist

and the spectra were correlated with the respective tissue.

The combination of all three techniques (ultrasound pictures,

measurement of the penetration depth using the scale on the

linear system, and marking of the stitch pathway by a textile

fiber for the subsequent gold standard pathological medical

report) led to the presented correlations. Thus, the verifica-

tion was guaranteed whether the measurement was carried out

inside or outside the tumor or in an intermediate tissue region.

3.2. Performing an in vitro pilot test of tissue samples

Exemplary adipose and muscle tissue probes were stitched,

and spectral information was generated from dead tissue

(figure 5). For the purpose of our investigations untreated pork

tissue was used.

Through illumination with a broadband halogen light

source, the scattering and absorption characteristics over a

wide range from 200–1900 nm were detectable. The dominant

absorption peaks near 430 nm and 560 nm are characteristic

for blood pigment (Hb). In comparison with adipose tissue,

muscle tissue has a higher supply of blood and thus exhibits

a high spectral absorbance in the green spectral range and is

visually recognizable by its red color. The optical window

and the oxygen-loaded Hb spectral data are shown at the top

left. The aqueous highly diluted blood Hb and pure water

spectrum is generated in a transmission setup using a 10 mm

cuvette inserted in a cuvette-holder (Hellma GmbH & Co.

KG, Müllheim, Germany). The backscattering signal inside

the adipose tissue was much stronger than that from muscle

tissue, as demonstrated by the low absorption in the VIS spec-

trum. The three specific and broad water peaks, which appear

at approximately 980, 1444 and 1944 nm [11], can be found

in both tissues; however, they are more dominant in muscle

tissue [42]. The absorption bands of the fatty acids were dis-

tinctive in the NIR region at approximately 920, 1040, 1210,

1730, and 1760 nm [43]. In addition to the spectral data for

muscle and adipose tissue, a supplementary photo, including

calculated RGB color from the spectral data, is provided on

the right side of figure5. The photos were taken with a digital

camera and are used for visualization. Color values are calcu-

lated by using the embedded color-function of ASPECT PLUS

(Carl Zeiss Spectroscopy GmbH, Jena, Germany). These

explained optical (morphological and chemical) properties

are of utmost importance for the subsequent point described

in the next section.

3.3. Proof of concept: multispectral label-free in vivo group-

ing of healthy and malignant tissue

For grouping of healthy and malignant tissue, in vivo mea-

surements were conducted in an animal model using the

multispectral needle probe. Figure 6 shows the spectral

data for the three spectroscopic techniques, UV/VIS, NIR

and FL. These are exemplary spectra of a single mouse.

The spectral information are the first acquired data in the

sequence chain.

Through the identification of differences in the optical

properties of healthy, marginal and malignant tissue the chan-

nels in figure 3 are selected. The multispectral information

content is described above. The following biochemical and

morphological properties were determined using the multi-

spectral measuring system. The FL spectra include excitation

by the 365 nm LED light source as additional information.

The LED shows strong absorption in malignant tissue, which

is mainly caused by the enhanced Hb absorption. The FL

emission at approximately 460 nm is much lower for malig-

nant tissue than for marginal and surrounding healthy tissue.

Furthermore, the UV/VIS, NIR spectral data exhibit differ-

ences. A higher absorbance generally indicates less backscat-

tering signal. In contrast, more scattering, which depends on

the morphology of the involved components (size, structure,

inner surface of the tissue) results in lower absorption (almost

untouched by the chemical absorption in the optical window

of the tissue between 650–900 nm). The interaction of scat-

tering effects and the overlying spectrum of blood (mainly

Hb) reveals that the total Hb content in malignant tissue is

increased in contrast to the surrounding tissue. Additional

information is provided by the reduced oxygen saturation in

this tissue. The effects are summarized in the following sec-

tionand are demonstrated visually in figure6: the increased

peak at 560 nm indicates higher Hb loading. The absorption

maximum at approximately 430 nm is shifted to the right,

which indicates less oxygen saturation due to a decreased oxy-/

deoxy-Hb ratio. The two pronounced peaks between 500 and

600 nm are typical for high oxygen saturation. The absorption

in the 760 nm region is characteristic for deoxy-Hb. Finally,

the colorimetric in vivo measurement results show a more

intense dark red color inside the malignant tissues (RGB data

not shown but are recognizable in the VIS spectral data). The

water and fat concentrations can be estimated by NIR spec-

tral data. In tissue measurements, water is the predominant

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F Braun etal

molecule. In our case, the O–H-stretch first overtone absorp-

tion peak at 1470 nm is too strong for quantitative analysis.

The high absorption leads to very low remission signals due to

artificial saturation caused by the instruments. Nevertheless,

the slope at the flanks could be evaluated and demonstrated

a higher water content in the healthy tissue compared with

the malignant tissue. The clearly identifiable absorption in the

structured region of the spectrum at approximately 1750 nm

was assigned to fat (see also figure5), which had a reduced

concentration inside the tumor.

The second step in the sequence chain is the extraction of

the relevant information from the whole multispectral data per-

formed by a five-sensor photometer setup. This virtual setup is

described in figure3. This extracted data allowed the differenti-

ation of the respective tissues using 2D PCA, shown in figure7.

Which is the third and last step in the sequence chain.

The practical applicability of the measurement system was

demonstrated in an animal model (N = 6, female SPF NMRI

mice) by penetrating the needle in vivo through healthy and

malignant tissue (Lewis lung carcinoma cells). The recorded

multispectral data are reduced by a virtual photometer setup

using 10 significant channels. They result in five sensors with

a total data-amount of 10 bytes per measurement point. In

order to sort tissue into groups, a principal component analysis

(PCA) is used. The model consists of two components, which

contain 85% of the total photometric variation (PC1 = 67%/

PC2 = 18%). By comparing associated measuring changes

in biochemical, physical-morphological and colorimetric

values all 96 measurement points are shown. Three resulting

groups—healthy, marginal and malignant tissue—are visible

and highlighted in the score plot. The influence of the respec-

tive sensor is shown in the loading-plot.

The first two components explain 85% of the total pho-

tometric variation (PC1 = 67% and PC2 = 18%). The load-

ings represent the weighted influence of the respective virtual

specialized sensors, as shown in figure7. Exemplary for one

stitch the signals of the five sensors are given in the supporting

information.

Figure 6. Exemplary in vivo absorbance spectra from simultaneous UV/VIS, NIR and FL spectroscopy measurements in columns 1, 2.

Resulting further information added in column 3.

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4. Discussion

Cancer is characterized by uncontrolled proliferation and

therefore by excessive consumption of nutrients such as glu-

cose, glutamine and fatty acids to support rapid growth. An

overview of the fundamental pathways of nutrient acquisition

and cancer metabolism has been provided by DeBerardinis

and Chandel [44]. Based on these features, changes in metab-

olism and morphology can be diagnosed using multispec-

tral in vivo spectroscopy techniques. Hb, NADH, water, fat,

color, and scattering characteristics are important detectable

endogenous markers. Of particular interest in blood supplied

tissue of animal models is the pigment Hb. This serves as an

oxygen carrier molecule (loaded and unloaded), allowing the

determination of both the local oxygen saturation and the

total Hb concentration. In our investigations, the oxygen con-

centration in tumors was reduced. Thus, the tumor was not

adequately supplied with oxygen despite initiation of angio-

genesis activity, which generally results in higher Hb loading

in malignant tissue. Consequently, more oxygen is converted

than provided from the surrounding tissue (despite better

blood supply), which can result in an oxygen gradient from

malignant to healthy tissue caused by diffusion, as shown in

figure6 and the supporting information. This observation sup-

ports different/increased metabolic activity inside and in the

marginal zone of the evaluated tumor tissues. Fadaka etal [45]

described a large dependence on the blood supply: ‘Hypoxia

and glucose shortage are rapidly generated in the inner mass

of a growing tumor. In the early carcinogenesis phase, uncon-

trolled cell proliferation moves tumor cells away from blood

vessels and, therefore, from oxygen and nutrient supply. The

only way oxygen and glucose can reach the inner cells of a

non-vascularized tumor is by diffusion across the basement

membrane and through the peripheral tumor-cell layers.’

In 1924, Warburg already proposed a hypothesis for cancer

metabolism [46] in which cancer cells preferentially gain nec-

essary energy through glycolysis upregulation, leading to the

conclusion that oxygen is not inevitably necessary for cancer

growth [47]. The amount of water is qualitatively higher in

healthy subcutaneous tissue than in tumor tissue. The same

phenomenon is valid for fat, which is reduced in tumors due

to the increase in fatty acid synthesis [45]. Simultaneously,

Figure 7. Principal component analysis (PCA) of the photometric data. The preprocessed and reduced information acquired from the

sample points using UV/VIS, NIR and FL spectroscopy. The results are illustrated by a score- (including the highlighted classes) and a

loadings-plot.

Meas. Sci. Technol. 30 (2019) 104001

F Braun etal

the measured stimulated tissue autoFL in tumors with a good

blood supply is more reduced in comparison to subcutaneous

tissue in the immediate vicinity. However, an increase in

absorption attributable to higher Hb loading in the spectral

range of FL excitation and emission was measured by the

introduced setup. Morphological changes were detectable

by reduced backscattering in the optical window of tissue

in comparison with the increase in light scattering in the

surrounding healthy subcutaneous tissue. In summary, our

invest igations have shown that fat and water can be detected

in the near NIR based on characteristic bands. Fluorophores,

such as NADH, can be better observed in FL emission signals

with the higher sensitivity than using absorption spectroscopy.

For determining blood concentration, the characteristic bands

in the visual range allow a clear interpretation. Furthermore,

the scattering characteristics of the analyzed malignant tissue

differ from the high scattering in the surrounding subcuta-

neous tissue, which can clearly be observed in the optical

window of tissue.

The goal of our work was to achieve an easy to use meas-

uring system for in vivo tissue analysis with high monitoring

frequency. With this mind compromises in the sensor design,

optical arrangement and even in the data evaluation had to

be accepted. The chosen design and backscattering measure-

ment principle allowed reduction of the clinical tool to the

size of a needle. In the present study, only relative changes in

concentration linked to FL emission are shown. The evalu-

ation of absolute values for fluorophores cannot be easily

conducted. However, to overcome these problems, an auto

correction algorithm is required that compensates these

effects. In a first step, quantitative NADH FL measurements

were performed in a tissue phantom with adjustable scat-

tering parameters [22, 36].

Diagnosis of tumorous tissue cannot be achieved solely

by spectral data and an evaluation algorithm. Medically

trained personnel must provide input as to whether (and to

what extent) changes in a tissue deviate from normal values,

regardless of whether the values are for fat, blood concentra-

tion, color, scattering characteristics, water content, oxygen

satur ation, metabolic intermediates (such as NADH) or other

values and symptoms that provide clinical evidence. More

correlations with histological changes are needed in the future.

5. Summary and conclusion

The basic idea of the presented work was to develop a setup

that can simultaneously detect various spectroscopic tech-

niques (UV/VIS, NIR, FL) for the detection and evaluation

of malignant tissue in real-time. The setup was composed of

a customized multispectral needle probe and an integrated set

of different light sources as well as spectrometers all of which

are described in detail. The head of the multispectral needle

has an optimized shape especially for in vivo measurements.

The measured data were processed by a virtual photometric

setup and combined and clustered into groups. To handle the

recorded spectral data, a virtual photometer converts spectral

data into channels and in a next step into sensors. These spe-

cific sensors explain change-related tissue alterations by mon-

itoring morphological properties and metabolic parameters:

Hb, deoxy Hb, scattering, fat and auto FL. In a next sequence

the information of each channel are the variables of a 2D PCA.

This analysis allows a grouping of 96 label-free measurement

points generated in vivo. The first two components of the PCA

explain 85% of the total photometric variation. All samples

can be clearly attributed to three groups (malignant, mar-

ginal and healthy tissue) visible in the PCA score-plot. This

goal was successfully accomplished in a mouse tumor model

(Lewis lung carcinoma) and verified by classical histology.

5.1. Scope and potential future application

The applied methods and the reported results are highly prom-

ising and will serve as an entry point for potential future direc-

tions. Our goals for the development of the probe setup and

evaluation system are multiple use, easy cleaning, sterilization

capability, and professional (i.e. commercial) applicability.

The typical conventional biopsy procedure requires up to 24

core saturation tissue fragments (biopsy to obtain tissue sam-

ples in a systematic manner). This process supported by the

optical needle could reduce the number of samples collected.

As a result, histology costs could be lowered together with

the benefit of a real-time preselection during the procedure

guided by ultrasound or MRI. Currently, a cancer is diagnosed

by a combination of results from different techniques and dis-

ciplines: detection of cancerous tissue, localization, tissue

sampling, biopsy and verification by a specialist/pathologist.

In general, this sequence is time consuming. Our goal is to

allow smart real-time in vivo detection and to facilitate the

work of medical personnel by providing them with multi-

spectral pre-information during the procedure. By using our

setup, morphological, metabolic and other PCA parameters

are immediately available in vivo, allowing a secure diagnosis

in combination with of medical knowledge. In future work,

the presented setup will be tested for the investigation of other

cancer types or other medically relevant tissue changes such as

inflammation. The optical measurement head is applicable for

analysis in vivo. Various steps for optimization and applica-

tion of the fiber optic needle are planned: advanced materials

will be used for the probe head (e.g. hardened or hard metal

or ceramic) with the benefit of multiple needle uses without

grinding, development of a disposable probe based on plastic

and polymer optical fibers to avoid cleaning and sterilization

procedures. The use of further fibers as backup channels are

planned. Those lead to higher safety integrity and an increased

availability by hot-spare redundancy. Finally, an aim in the

future is the implementation of Raman measurements using a

sensitive spectrometer with adjustable resolution and imple-

mented filter units for high photon flux [48]. This technique

will increase the multispectral information. This approach

may provide access to assessment of other key molecules:

ATP, glutamine, glucose, and lactic acid (lower glucose and

higher lactic acid concentrations are observed in the tumor

microenvironment [49]). Exogenous fluorophores are also

Meas. Sci. Technol. 30 (2019) 104001

F Braun etal

detectable using a suitable excitation light-source, regardless

of whether it is static or tunable. The fields of application will

be expanded through the use of endogenous or exogenous

labeling with FL marker molecules, such as indocyanine

green (ICG), PpIX, and sinistrin, which has a demonstrated

potential for determination of glomerular filtration rate (GFR)

[50, 51]).

Furthermore, reduction of the necessary instrumentation

effort by lowering the recorded number of wavelengths is pos-

sible. The elaborated method can be integrated into robust,

compact and low-cost embedded computing systems, photo-

metric setups with appropriate bandpass filters, light sources

and sensitive detectors. Egly etal [52] presented a compact

multichannel FL sensor equipped with ambient light sup-

pression through a lock-in procedure that resulted in detec-

tion limits of 4 × 10−11 mol l−1 and 4 × 10−9 mol l−1 for the

fluorophores PpIX and NADH, respectively [51]. Our goal

is to develop a self-learning instrument including an adapted

algorithm introduced by Garcia etal [53] that combines diag-

nostics and therapy to assist medical doctors and pathologists.

Their experience, interpretation and knowledge of a patient’s

clinical status, combined with the aforementioned fiber optic

setup, will result in a smart in vivo human-sensor expert

system for rapid grouping and characterization of tissue, fol-

lowed by potential curative treatment and therapy.

Acknowledgment

This work was funded by the German Federation of Indus-

trial Research Associations (AiF Project GmbH). The authors

would especially like to express their thanks to Julia Selten-

reich (University of Applied Sciences, Mannheim, Germany)

and Viktoria Skude (Medical Research Center, University of

Heidelberg, Mannheim, Germany) for support during the mul-

tispectral in vivo measurements.

Notes

Frank Braun, Norbert Gretz and Matthias Rädle are the inven-

tors and have submitted a patent application regarding the

described needle probe (DE102014107342A1).

ORCID iDs

Frank Braun https://orcid.org/0000-0002-2906-8493

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