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Clinical Studies

Water Concentration Analysis by RamanSpectroscopy to Determine the Location of theTumor Border in Oral Cancer SurgeryElisa M. Barroso1, Roeland W.H. Smits2, Cornelia G.F. van Lanschot2, Peter J. Caspers3,4,Ivo ten Hove1, Hetty Mast1, Aniel Sewnaik2, Jos�e A. Hardillo2, Cees A. Meeuwis2,Rob Verdijk5, Vincent Noordhoek Hegt5, Robert J. Baatenburg de Jong2,Eppo B.Wolvius1, Tom C. Bakker Schut3,4, Senada Koljenovi�c5, and Gerwin J. Puppels3,4

Abstract

Adequate resection of oral cavity squamous cell carcinoma(OCSCC) means complete tumor removal with a clear marginof more than 5 mm. For OCSCC, 85% of the surgical resectionsappear inadequate. Raman spectroscopy is an objective and fasttool that can provide real-time information about the molecularcomposition of tissue and has the potential to provide an objec-tive and fast intraoperative assessment of the entire resectionsurface. A previous study demonstrated that OCSCC can bediscriminated from healthy surrounding tissue based on thehigherwater concentration in tumor. In this study,we investigatedhow the water concentration changes across the tumorborder toward the healthy surrounding tissue on freshly excised

specimens from the oral cavity. Experiments were performed ontissue sections from 20 patients undergoing surgery for OCSCC.A transition from a high to a lower water concentration, fromtumor (76% � 8% of water) toward healthy surrounding tissue(54%� 24% of water), takes place over a distance of about 4 to 6mm across the tumor border. This was accompanied by anincrease of the heterogeneity of the water concentration in thesurrounding healthy tissue. Thewater concentration distributionsbetween the regions were significantly different (P < 0.0001). Thisnew finding highlights the potential of Raman spectroscopy forobjective intraoperative assessment of the resection margins.Cancer Res; 76(20); 5945–53. �2016 AACR.

IntroductionOral cavity cancer is a major public health issue, with 300,000

new cases per year worldwide (1).Most oral cancers arise from theepitheliumof themucosal surface and are referred to as oral cavitysquamous cell carcinoma (OCSCC). OCSCC mortality is high,with a 5-year survival rate of around 50% and 145,000 deaths peryear worldwide (1, 2). Despite advances in treatment modalities(surgery, radiotherapy, and chemotherapy), these numbers havenot shown significant improvement over the last decades (3, 4).Important determinants of the clinical outcome of patients withOCSCC are tumor subsite, tumor–node–metastasis (TNM) clas-sification, age, comorbidity, and tumor histologic characteristics(5–7). Surgery is themainstay of treatment for OCSCC. Adequatetumor resection with acceptable remaining function and physicalappearance is the main goal. At our institute, we follow the

guidelines of the Royal College of Pathologists (United King-dom). The distance between tumor and the nearest resectionsurface (DBTNRS) determines the adequacy of the surgical pro-cedure. This distance is histologically measured in mm. A resec-tion margin can be classified as clear (>5 mm of DBTNRS), close(1–5 mm of DBTNRS), and positive (<1 mm of DBTNRS; ref. 8).Clear margins are regarded as adequate and close and positivemargins as inadequate. Adequate resectionmargins are crucial fordisease control and survival (8–14). Patients with inadequateresection margins often receive adjuvant therapy (chemotherapyand/or radiation) or re-resection. However, these can have anegative effect on patient morbidity.

Achieving adequate resection margins is challenging. The lackof reliable intraoperative guidance and the proximity of tumors tovital structures are the common causes of inadequate tumorresection. Despite comprehensive preoperative imaging of thetumor (by CT scan, MRI, etc.), the surgeon decides where to cut,based on visual inspection and palpation of the tumor during theoperation. Earlier, we have reported the surgical results obtainedin two Dutch centers (Erasmus Medical Center Rotterdam andLeiden University Medical Center). For OCSCC surgery, adequateresection margins were obtained in only 15% of the cases (9). Asimilar result was recently reported by the Harborview MedicalCenter and the University of Washington Medical Center inSeattle (11).Clearly, visual inspection and palpation of the tumorand surrounding tissue by the surgeon are insufficient to warrantadequate tumor resection.

Intraoperative assessment of resection margins by means of afrozen section procedure can be used (15). This procedure, inwhich the pathologist performsmicroscopic evaluation of a piece

1Department of Oral & Maxillofacial Surgery, Special Dental Care, andOrthodontics, Cancer Institute, Erasmus MC, Rotterdam, The Nether-lands. 2DepartmentofOtorhinolaryngology&HeadandNeckSurgery,Cancer Institute, Erasmus MC, Rotterdam, The Netherlands. 3Centerfor Optical Diagnostics & Therapy, Department of Dermatology, Can-cer Institute, Erasmus MC, Rotterdam,The Netherlands. 4RiverD Inter-national BV, Rotterdam,The Netherlands. 5Department of Pathology,Cancer Institute, Erasmus MC, Rotterdam, The Netherlands.

Corresponding Author: T.C. Bakker Schut, Center for Optical Diagnostics &Therapy, Department of Dermatology, Cancer Institute, Erasmus MC, Room Ee1691, Wytemaweg 80, 3015 CN Rotterdam, The Netherlands. Phone: 31-10-7043117; Fax: 31-10-70; E-mail: [email protected]

doi: 10.1158/0008-5472.CAN-16-1227

�2016 American Association for Cancer Research.

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of suspicious tissue, is currently the gold standard of intraopera-tive diagnostics (15–17). The main limitation of the frozensection procedure is that only a fraction of the resection marginscan be investigated. Themethod is prone to sampling error, whichoften leads to false-negative results (9, 18). As a result, the frozensection procedure is not very effective in improving surgicalsuccess rate. Ideally, the entire resection surface should be eval-uated intraoperatively, which requires an objective and fasttechnology.

Intraoperative assessment of resectionmargins on the resectionspecimen (i.e., specimen-driven approach) has been reported tobe superior to assessment of the wound bed (i.e., defect-drivenapproach) by different groups. Specimen-driven intraoperativeassessment of resection margins leads to a higher surgical successrate and increase of patient survival than defect-driven or nointraoperative assessment at all (11, 17–19).

Various techniques like ultrasonography, imprint cytology, andvarious optical techniques are being explored for intraoperativeuse in surgical oncology (20–28). Some of these techniques arebeing applied for OCSCC, which were recently reviewed by Raviand colleagues (26). Optical techniques like high-resolutionmicroendoscopy (HRME), optical coherence tomography (OCT),fluorescence spectroscopy, elastic light scattering spectroscopy,and Raman spectroscopy are promising because of their ease ofuse, relatively low cost, and high speed in screening large tissueareas (20–28).

Raman spectroscopy is an optical technique that is beinginvestigated for intraoperative evaluation of the surgical margins.Raman spectroscopy can be applied to assess the mucosa, as wellas, the deep soft tissue layers (29–34). It is an objective techniquebasedon inelastic scattering ofmonochromatic light that providesdetailed quantitative and qualitative information about themolecular composition of tissue. The technique is nondestructive,and there is no need for reagents or labeling, which promoteseasier translation to the clinics (35, 36).

The goal of our research is to develop a Raman spectroscopictechnique for objective intraoperative assessment of the entireresection surface, with the ultimate goal to improve the successrate of OCSCC surgery. In a first pilot study, we have dem-onstrated that Raman spectra of resection specimen discrim-inated tumor from healthy surrounding tissue with a sensi-tivity of 99% and a specificity of 92% (37). The primarydiscriminating factor of the Raman spectra proved to be thewater concentration in the tissue. Raman spectroscopy is verysuitable for rapid quantitative determination of the waterconcentration in tissue, as has been demonstrated by ourgroup (38–40). The objectives of the current study were toinvestigate how the change in water concentration correlateswith the border between tumor and surrounding healthy tissueand, consequently, to verify if this information can be used toassess resection margins.

Materials and MethodsMedical ethical approval

This study was approved by the Medical Ethics Committee(MEC-2013-345) of the Erasmus MC Cancer Institute, UniversityMedical Center Rotterdam. Prior to the operation, informedconsent was obtained from the patients. Measurements wereconducted ex vivo on resection specimen of patients undergoingsurgery for OCSCC. The allowed time for the experiments was 60

minutes, after which the resection specimen was put in formalinfor routine histopathologic evaluation.

Tissue samples and handlingImmediately after resection, the surgeon brought the spec-

imen to the cutting room of the pathology department, which isin close proximity to the operating room. A dedicated pathol-ogist and surgeon inspected the specimen together. This processincluded labeling of the anatomic sites and documentation ofthe specimen with diagrams and digital images (Fig. 1A). Afterorienting and defining the resection margins, the pathologistand the surgeon surveyed all resection planes by visual inspec-tion and palpation. After this, the pathologist cut the specimenin 3 to 5 cross-sections (with a thickness of about 5–10 mm),perpendicular to the resection margin plane (Fig. 1B). Forspecimens comprising bone (i.e., mandibular resection speci-mens in patients with OCSCC invading the bone), the softtissue was cut till the bone. The pathologist measured thedistance between tumor and resection surface. Often, thismacroscopic assessment only was sufficient to decide on thefurther course of the operation without the need for frozensections. In case of an unclear tumor border, the pathologistmay decide to further refine the information by microscopicexamination of frozen sections. Provided with this intraopera-tive information regarding inadequate margins, the surgeoncontinues to harvest more tissue from the wound bed (e.g.,immediate re-resection) to achieve an adequate surgical result.

After this intraoperative diagnostic procedure, one of the spec-imen cross-sections was chosen for Raman experiments (furthercalled "Raman tissue section"). The cross-section was regardedsuitable when containing tumor and >5 mm of healthy lookingsurrounding tissue (Fig. 1B). The remaining specimen cross-sec-tions were immersed in formalin.

Blood was rinsed from the Raman tissue section using phys-iological salt solution (0.9% NaCl) and gently patted dry withgauze. The area of interest (i.e., tumor and >5mmof surroundinghealthy tissue) was macroscopically chosen by the pathologist.The Raman tissue section was inserted in a closed cartridge toavoid drying of the tissue. The upper side of the cartridge consistsof a fused silica window. This cartridge allows the scanning of a 3� 3 cm2 tissue area. The Raman tissue section was placed in thecartridge with the surface to bemeasured in contact with the fusedsilica window. Digital images of all handling steps were made,including images for the macroscopic representation of the tissuearea measured (Fig. 1C).

After the experiment, the Raman tissue section was removedfrom the cartridge and immersed in formalin, together with therest of the specimen to follow the routine procedure for finalpathological processing.

Raman instrumentation and mapping experimentsRaman ex vivo mapping experiments were performed using a

confocal Raman microscope (CRM), built in-house. The equip-ment was placed in a laboratory close to the operating room. Thesetup, as explained in our previous work (37), comprised amultichannel RamanModule (HPRM2500, RiverD InternationalBV), a 671-nm laser (CrystaLaser, CL671-150-SO), and a charge-coupled device (CCD) camera fittedwith a back-illuminated deepdepletion CDD-chip (Andor iDus 401, DU401A BR-DD, AndorTechnology Ltd.). A microscope (Leica DM RXA2, Leica Micro-systemsWetzlar GmbH) and a computer-controlled sample stage

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Figure 1.

Overview of the experimental protocol. A, immediately after surgical resection, the specimen (excision of tongue SCC) was transferred to the pathology roomand orientation was digitally recorded [anterior (A), posterior (P), and medial (M)]. B, specimen was cut perpendicular to the resection surface in three sections forintraoperative assessment of the resection margins. Thereafter, a tissue section was chosen for the Raman experiment. C, Raman tissue section was insertedinto a cartridge. The area to be measured was defined by the pathologist, containing tumor and >5 mm of surrounding healthy tissue, at least in onedirection.D, Ramanmapping experiments were performed on a grid. The water concentration for eachmeasured point was calculated. A 2D image was obtained byusing a nonlinear color scale to represent the water concentrations. E, after Raman measurement, the specimen was routinely processed. H&E-stained slidewas made from the whole Raman tissue section, within which, pathologists identified the tissue area that was measured. The histopathologic annotationof the tumor (T), healthy tissue (H), and of the tumor border (red line) was performed. F, on the basis of the annotated tumor border in the H&E image (red line),the position of the adequate surgical margin (>5 mm of distance to the tumor border) was determined within the water map (green line).

Water Concentration Analysis of the Surgical Margin

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(Leica DM STC) were coupled with the Raman Module. EightymW of laser light was focused in the tissue by means of amicroscope objective (0.4numerical aperture)with a freeworkingdistance of 1.1 mm (N PLAN 11566026, Leica Microsystems BV).The depth resolution was 40 mm, experimentally determined.Spectral information was collected in the wavenumber range2,500 to 4,000 cm�1 with a resolution <5 cm�1.

For each measurement, the cartridge with the tissue sectionwas fixed on the microscope stage. The selected area wasmeasured point-by-point using a grid. The grid cell size wasbetween 300 mm per 300 mm to 1,000 mm per 1,000 mm,depending on the size of the tissue section and on the allowedtime of 60 minutes to perform the experiment. In some cases,more than one map per specimen was measured depending onthe size of the tissue section and on the allowed time. Theacquisition time per spectrum was 1 second. Laser light wasfocused in the tissue at about 50 mm below the fused silicawindow surface.

Calibration and processing of spectraAll spectra were calibrated on the relative wavenumber axis and

corrected for thewavelength-dependent detection efficiencyof thesetup, according to instructions of the spectrometer supplier(RiverD International BV). Preprocessing of the spectral data wasperformed by removal of cosmic ray events and subtraction of thesignal background generated in the optical path of the setup itself(39). MATLAB R2014b was used for data processing and datavisualization.

The tissue Raman spectra showed varying levels of backgroundsignal originating from tissue autofluorescence. For the calcula-tion of tissue water concentrations, the autofluorescent back-ground signal was estimated by a third-order polynomial andsubtracted from the measured spectra.

Spectra with a relative intensity lower than 5% of the averageintensity of all spectra measured from the sample were discarded.Intensity of the spectra was determined for the range 2,700 to3,100 cm�1, in which almost all spectral signatures from lipidsand proteins are localized. Low signal intensities were encoun-

tered in cases where the tissue was locally not fully in contact withthe measurement window.

The ratio of the Raman bands at 3,390 cm�1 and 2,935 cm�1

was used to determine the concentration of water per spectrumaccording to the method developed by Caspers and colleagues(40) and described in detail in our previous study (38, 40).

Raman water mapsRaman water maps were created by plotting the water concen-

tration as a 2D map using pseudo colors to represent the waterconcentration range. A convolution of the water map with a 3� 3averaging filter was applied, as shown in Fig. 1D, to obtain valuesthat are more representative of the local water concentration(reducing noise in the image), and for better visualization of thedifference in water concentration between tumor and the surgicalmargins (41).

HistopathologyHistopathologic evaluation of the measured areas was per-

formed by two dedicated pathologists on routine hematoxylinand eosin (H&E)-stained thin tissue sections. Subsequently, theH&E-stained section was digitized and the pathologists delineat-ed healthy tissue, tumor, and tumor border (Fig. 1E).

Data analysisOn the basis of the projection of the tumor border in the H&E

image (red line) onto the Raman water map, each pixel waslabeled as tumor border, tumor, or healthy (Fig. 1F). The precisionwith which the individual pixels could be annotated in this way islimited by the much lower resolution of the Raman map com-pared with the microscopic image. The error was estimated to behalf of the Ramanmap pixel size. Thereafter, the minimal Euclid-ean distance between each Raman map pixel and the tumorborder was calculated. On the basis of these distances, the posi-tion of the adequate surgical margin (all pixels with distance >5mm to the tumor border) was obtained (Fig. 1F).

For each map, the average and SD of the water concentrationwere separately calculated for tumor, for the inadequate margin

Table 1. Patient and tumor characteristics

Patient Age, y Gender Maps Primary tumor location pTNM

1 71 F 1 Lateral side of tongue T2N2bM02 72 M 1 Floor of mouth T2N2bM03 52 F 1 Floor of mouth T3N2bM04 52 F 1 Lateral side of tongue T1N0M05 54 M 1 Lateral side of tongue T1N0M06 42 M 1 Lateral side of tongue T1N0M07 59 F 1 Lateral side of tongue T2N0M08 91 M 2 Lateral side of tongue T1N1M09 52 F 1 Lateral side of tongue T1N0M010 42 F 1 Lateral side of tongue T4aN2bM011 67 M 2 Inferior alveolar process T4aN0M012 60 F 1 Lateral side of tongue T1N0M013 69 M 2 Lateral side of tongue T1N0M014 61 M 1 Lateral side of tongue T1N0M015 68 M 1 Lateral side of tongue T1N0M016 79 M 2 Lateral side of tongue T1N0M017 68 M 2 Retromolar trigone T4aN2bM018 72 F 1 Tongue and floor of the mouth T3N1M019 58 M 1 Lateral side of tongue T2N0M020 61 F 1 Lateral side of tongue T2N0M0

NOTE: Number ofmapsmeasured per patient (Maps). Primary tumor location and pathologic TNM classification (pTNM) ofmalignant tumors (42). Tumor size variedfrom less than 1 cm (T1) tomore than 4 cm. In some patients, tumor had extended into themandible (T4a). N stage varied from no regionalmetastasis in lymph nodesto multiple lymph nodes with metastasis of 6 cm or less in greatest dimension (N0–N2b). Distant metastasis was not encountered (M0).

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(i.e., distance from tumor border � 5 mm), and for the adequatemargin.

The Mann–Whitney U test was used to determine whether thedistribution of the water concentrations in tumor, in inadequatemargins, and in adequate margins are significantly different fromeach other.

Next, we calculated the average water concentration of thetissue as a function of the distance to the tumor border. This wasdone by calculating themeanwater concentration of pixels fallingwithin a 0.5-mm distance interval and moving this interval from�15 mm (inside the tumor) to þ10 mm (in the healthy tissue).Likewise, the SD in the water concentration was calculated asfunction of distance to the tumor border.

ResultsTwenty-five ex vivo Raman mapping experiments were per-

formed on fresh resection specimens from 20 patients treatedby surgery for OCSCC. Table 1 shows patient and tumorcharacteristics.

Each map had an average of 406 spectra (range compre-hended between 97 and1,250 spectra) and an average area of240 mm2 (from 18.9 to 624 mm2). The average tumor areaper map was 84 mm2 (range was between 13 and 390 mm2),the average inadequate margin area per map was 85 mm2

(minimum value was 27.9 mm2 and maximum value was 237mm2), and the average adequate margin area per map was 71mm2 (minimum and maximum values were, respectively, 4mm2 and 379.2 mm2).

In total, 3,526 Raman spectra from tumor were obtained. Fromthe surrounding healthy tissue, 3,620 spectra were obtained at adistance of less than 5mm from the tumor border (i.e., within thearea of inadequate margin) and 3,001 spectra were obtained at adistance greater than 5 mm from the tumor border (i.e., from thearea of adequate margins).

As an example, the results for 3 experiments performed onfresh resection specimens from 3 patients are shown in Fig. 2.The macroscopic images of the measured areas are shown incolumn A. Column B shows the water concentration maps.These maps were interpolated to a pixel size of 300 mm, whichwas the smallest step size used for mapping. In column C, theaveraged water maps after interpolation to the same pixel sizeare presented. Column D shows the annotated H&E-stainedsections. Column E shows the average water concentration(blue line) and SD(black line).

For each map, the mean and SD of the water concentrationfor tumor, inadequate, and adequate margins were calculated(Table 2). The averagewater concentration in tumor is 76%� 8%,in the inadequate margin it is 59% � 24%, and in the adequatemargin it is 54% � 24%.

Figure 2.

Rows 1–3, examples of the data obtainedbymeans ofmapping experiments on three Raman tissue sections from three patients.A,photograph of themeasured freshtissue surface. B, Ramanwater map with indication of tumor border (red; based on final histopathology shown in panels of column D) and adequate surgical margin(green). C, averaged Raman water map with indication of tumor border (red; based on final histopathology shown in panels of column D) and adequatesurgical margin (green). D, H&E–stained section obtained from the measured tissue surface, with tumor border (red), tumor (T), healthy surroundingtissue (H) indicated by pathologist. E, graphs showing water concentration as function of the distance to the tumor border. Blue line, average water concentrationcalculated per 0.5-mm distance interval. Black line, SD of the water concentration, per 0.5-mm distance interval. The red line at 0 mm represents the tumorborder, and the green line represents a distance of 5 mm from tumor border.






Mann–Whitney U tests show that these difference in waterconcentration between tumor, inadequate margin, and adequatemargin are all significantly different with P < 0.0001.

In Fig. 3, the water concentration (blue line) is shown, calcu-lated as the mean and SD over all experiments, as a function ofdistance to the tumor border, using 0.5-mm distance intervals.From this figure, it is clear that thewater concentration in tumor ismuch higher than in the surrounding healthy tissue. The figurealso shows that the decrease inwater concentration coincideswiththe tumor border. The water concentration starts to decreaseinside the tumor mass, close to the tumor border and continuesto decrease steeply until about 4mm into the surrounding healthytissue. From there, the decline in water concentration continueswith a smaller gradient. Interestingly, the SD in water concentra-tion values also differs between tumor and surrounding healthytissue; from less than 10% inside the tumor tomore than 15% justoutside the tumor.

DiscussionThe aim of our research is the development of a clinical tool for

intraoperative guidance of surgical–oncological procedures moti-vated by the main goal of surgery: adequate tumor resection andpreservation of function and physical appearance. Of the manyfactors that affect the clinical outcome of patients with OCSCC,only the resection margins can be influenced by the surgeon andpathologist. The objective intraoperative assessment of resectionmargins is the key to increase thenumber of adequate resections insurgical oncology, therefore, an objective tool for assessment andguidance is needed.

Multiple techniques are being explored for intraoperative use insurgical oncology (20–28). Until now, fluorescence spectroscopy(20), diffuse reflectance spectroscopy (21), elastic light spectros-

copy (22), HRME (23), and OCT (24) have explored in vivodelineation of the tumor at the mucosal surface, prior to surgery.However, 87% of inadequate margins are found in the deeper(submucosal) soft tissue layers (43). Therefore, the design of thesestudies is not perfect to be applied at the submucosal layers of softtissue, which is where the majority of inadequate margins arefound.

OCT is a promising technique that has been used to investigateOCSCC resectionmargins. A recent study published byHamdoonand colleagues (44) concluded that OCT is a valuable tool in theassessment of surgical margins. This study reported that thediagnostic accuracy was about 85%. However, they mentionedthat the use of OCT technology is limited because the createdimage can be affected by the lack of normal tissue perfusion.Therefore, the resolution and contrast of the OCT images areinfluenced by the "ex-vivo nature" of the approach (44, 45).Moreover, not only OCT but also HRME has as disadvantage thatit requires complicated subjective image interpretation (23, 24,44, 45).

Raman spectroscopy has proved to be a reliable technique thatcan be applied to assess mucosa as well as the deep soft tissuelayers (31, 36–38). This objective and nondestructive techniquewas used in our first study, where it showed to be accurate indiscriminating OCSCC from the surrounding healthy tissue. Inthis previous study, we showed, by means of high-wavenumberRaman spectroscopy, that water concentration within the tumor(OCSCC) is significantly higher than in the surrounding healthytissue enabling discrimination between tumor and healthy tissuewith 98% accuracy (37). The notion that certain tumors containmore water than surrounding healthy tissue was not new; alreadyin 1971, water content was described as one of the discriminatorsbetween tumor and healthy tissue. Diagnostic instruments likeMRI use the differences in water between the relaxation times of

Table 2. Average water concentration and respective SD for each map

Concentration of water (%)Tumor Inadequate margins Adequate margins

pTNM Map Patient Mean SD Mean SD Mean SD

T1N0M0 1 4 71 5 66 12 55 14T1N0M0 2 5 71 5 65 20 62 19T1N0M0 3 6 76 8 62 24 61 25T1N0M0 4 12 76 6 54 28 58 24T1N0M0 5 13 75 14 53 30 61 24T1N0M0 6 13 76 11 49 30 57 31T1N0M0 7 14 81 5 62 25 69 16T1N0M0 8 15 77 4 66 21 61 26T1N0M0 9 16 81 5 59 26 44 30T1N0M0 10 16 77 12 57 26 43 32T1N0M0 11 9 79 6 69 21 61 24T1N1M0 12 8 73 10 55 26 46 33T1N1M0 13 8 75 10 46 31 37 30T2N0M0 14 7 78 5 60 24 55 24T2N0M0 15 19 69 18 63 21 62 25T2N0M0 16 20 81 3 70 23 62 24T2N2bM0 17 1 80 9 65 25 55 30T2N2bM0 18 2 76 6 54 20 60 22T3N1M0 19 18 77 9 56 27 49 26T3N2bM0 20 3 74 9 53 26 58 28T4aN0M0 21 11 77 5 58 27 61 27T4aN0M0 22 11 75 4 62 25 50 28T4aN2bM0 23 10 76 8 64 18 42 21T4aN2bM0 24 17 74 14 58 25 44 28T4aN2bM0 25 17 75 13 52 27 43 27

NOTE: The water concentration was calculated specifically for the tumor, inadequate margin, and adequate margin. Maps were ordered according to the TNMclassification of tumors (42).

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normal and malignant tissues to generate contrast between thetwo (46).

In the current study, we investigated how the water concentra-tion changes from inside the tumor toward the adequate surgicalmargin. The results show a clear correlation between the tumorborder and the change in water concentration. The transitionfrom a high water concentration inside the tumor to a lowerwater concentration in the surrounding tissue takes place as anegative gradient over a distance of about 4 to 6 mm across theborder of the tumor. By analyzing this negative water concen-tration gradient (Fig. 3), we observed that the decrease in waterconcentration from tumor toward the adequate margin isaccompanied by an increase in the SD of the water concentra-tion, that is, the heterogeneity increases. Inside the tumor, thewater concentration was higher than 69%, with a relatively lowSD of less than 15%. This low SD indicates that OCSCC ishomogeneous concerning water concentration, regardless ofpTNM classification (Table 2). Inside the tumor, at about 1.5

mm distance to the tumor border, the water concentration ofthe tumor starts to decrease and the SD starts to increase (Fig. 3).The average precision with which the Raman image could beannotated with the image of the H&E-stained section was�0.38 mm (from �0.15 to �0.5 mm) and was determined bythe resolution of the Raman measurements as explained inMaterials and Methods. The increase in the SD can indicate thatclose to the tumor border, the water concentration heteroge-neity increases, possibly explained by the presence of stroma,blood vessels, and lymphatic vessels (47). Another interestingfinding is that at approximately 4 mm beyond the tumorborder, the SD of the water concentration levels off at about26%. This high variance of the water concentration in thesurrounding healthy tissue is due to the heterogeneity in theseareas comprising fat tissue, muscle (M), and vessels (Fig. 4).

In this study, we show the water concentration distributionacross the tumorborder. The shapeof thewater profile from insidethe tumor toward the adequate margin for OCSCC is a new

Figure 4.

H&E-stained section obtained from ameasured tissue surface, with tumorborder (red line), tumor (T), and healthysurrounding tissue (H) indicated bypathologist. A representative region ofthe adequate margin was enlarged andthe tissue structures annotated. Tissuestructures present are muscle (M),adipose tissue (A), and bloodvessels (B).

Figure 3.

Water concentration profile from insidethe tumor toward adequate margin. Allindividual water concentrationpercentages of the 25 maps wereaveraged per interval to calculate themean (blue) and SD (black) of the waterconcentration as a function of thedistance to the tumor border. The redline at 0mm indicates the tumor border.The green line at 5 mm indicates thebeginning of the adequate surgicalmargin.






finding, as well as the increase in water concentration heteroge-neity at the tumor border.

We are currently devising fiber optic probe configurations andfiber optic probe measurement strategies to capture this informa-tion in a way that can be implemented for rapid intraoperativeassessment of resection specimens.

We believe that Raman spectroscopy is a promising candidatefor comprehensive intraoperative inspection of the surgical mar-gins for OCSCC resection specimens, which will fit in the surgicalworkflow and can help to significantly improve the percentage ofadequate resections.

We expect that water concentration analysis will prove equallyuseful in localizing the tumor border in other locations of thebody and plan to expand this line of investigation accordingly.

Disclosure of Potential Conflicts of InterestP.J. Caspers is employed with RiverD International BV as a senior applicant

and R&D scientist. V. Noordhoek Hegt, S. Koljenovi�c, and G.J. Puppels haveownership interest (including patents) in RiverD International BV. R.J. Baaten-burg de Jong reports receiving other commercial research support from share-holder River D. T.C. Bakker Schut is an employee of RiverD International BV.G.J. Puppels is employed with RiverD International BV as a CTO & ManagingDirector. No potential conflicts of interest were disclosed by the other authors.

Authors' ContributionsConception and design: E.M. Barroso, R.W.H. Smits, I. ten Hove, J.A. Hardillo,V. Noordhoek Hegt, R.J. Baatenburg de Jong, E.B. Wolvius, T.C. Bakker Schut,S. Koljenovi�c, G.J. Puppels

Development of methodology: E.M. Barroso, P.J. Caspers, V. Noordhoek Hegt,T.C. Bakker Schut, S. Koljenovi�c, G.J. PuppelsAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): E.M. Barroso, R.W.H. Smits, C.G.F. van Lanschot,I. ten Hove, H. Mast, J.A. Hardillo, R. Verdijk, S. Koljenovi�cAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): E.M. Barroso, C.G.F. van Lanschot, P.J. Caspers,A. Sewnaik, V. Noordhoek Hegt, T.C. Bakker Schut, S. Koljenovi�c, G.J. PuppelsWriting, review, and/or revision of the manuscript: E.M. Barroso, R.W.H.Smits, C.G.F. van Lanschot, P.J. Caspers, I. ten Hove, H. Mast, A. Sewnaik,J.A. Hardillo, R. Verdijk, V. Noordhoek Hegt, T.C. Bakker Schut, S. Koljenovi�c,G.J. PuppelsAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): E.M. Barroso, R.W.H. Smits, C.G.F. vanLanschot, R. Verdijk, E.B. Wolvius, S. Koljenovi�cStudy supervision: C.A. Meeuwis, R.J.B. de Jong, E.B. Wolvius, T.C. BakkerSchut, S. Koljenovi�c, G.J. Puppels

AcknowledgmentsThe authors would like to thank the technical support from the Department

of Pathology of Erasmus MC for their help processing the oral cavity specimensand scanning the H&E-stained slides.

Grant SupportWe thank ATOS Medical for providing financial support.The costs of publication of this articlewere defrayed inpart by the payment of

page charges. This article must therefore be hereby marked advertisement inaccordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received May 4, 2016; accepted July 6, 2016; published OnlineFirst August16, 2016.

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2016;76:5945-5953. Published OnlineFirst August 16, 2016.Cancer Res Elisa M. Barroso, Roeland W.H. Smits, Cornelia G.F. van Lanschot, et al.

SurgeryDetermine the Location of the Tumor Border in Oral Cancer Water Concentration Analysis by Raman Spectroscopy to

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