0
Original Article |

Time-Resolved Fluorescence Spectroscopy as a Diagnostic Technique of Oral Carcinoma:  Validation in the Hamster Buccal Pouch Model FREE

D. Gregory Farwell, MD; Jeremy D. Meier, MD; Jesung Park, PhD; Yang Sun, PhD; Heather Coffman, MD; Brian Poirier, MD; Jennifer Phipps, MD; Steve Tinling, PhD; Danny J. Enepekides, BSc, MD, FRCSC; Laura Marcu, PhD
[+] Author Affiliations

Author Affiliations: Departments of Otolaryngology–Head and Neck Surgery (Drs Farwell, Meier, Coffman, and Tinling), Pathology and Laboratory Medicine (Dr Poirier), and Biomedical Engineering (Drs Park, Sun, Phipps, and Marcu), University of California Davis Medical Center, and NSF Center for Biophotonics Science & Technology, Sacramento, California (Dr Marcu); and Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada (Dr Enepekides).


Arch Otolaryngol Head Neck Surg. 2010;136(2):126-133. doi:10.1001/archoto.2009.216.
Text Size: A A A
Published online

Objective  To investigate the benefit of using time-resolved, laser-induced fluorescence spectroscopy for diagnosing malignant and premalignant lesions of the oral cavity.

Design  The carcinogen 7,12-dimethylbenz[a]anthracene (DMBA) was applied to 1 cheek pouch of 19 hamsters. The contralateral pouch and the cheek pouches of 3 hamsters without DMBA exposure served as controls.

Setting  University of California, Davis.

Participants  Twenty-two golden/Syrian hamsters.

Intervention  A nitrogen pulse laser was used to induce tissue autofluorescence between the wavelengths of 360 and 650 nm.

Main Outcome Measures  Spectral intensities and time-domain measurements were obtained and compared with the histopathologic findings at each corresponding site.

Results  Spectral intensities and lifetime values at 3 spectral bands (SBs; SB1 = 380 ± 10 nm; SB2 = 460 ± 10 nm, and SB3 = 635 ± 10 nm) allowed for discrimination among healthy epithelium, dysplasia, carcinoma in situ, and invasive carcinoma. The lifetime values at SB2 were the most important when distinguishing the lesions using only time-resolved parameters. An algorithm combining spectral fluorescence parameters derived from both spectral and time-domain parameters (peak intensities, average fluorescence lifetimes, and the Laguerre coefficient [zero-order]) for healthy epithelium, dysplasia, carcinoma in situ, and invasive carcinoma provided the best diagnostic discrimination, with 100%, 100%, 69.2%, and 76.5% sensitivity and 100%, 92.2%, 97.1%, and 96.2% specificity, respectively.

Conclusions  The addition of time-resolved fluorescence-derived parameters significantly improves the capability of fluorescence spectroscopy–based diagnostics in the hamster buccal pouch. This technique provides a potential noninvasive diagnostic instrument for head and neck cancer.

Figures in this Article

Despite the significant medical advances of the past several years, the survival rate of patients with head and neck cancer has not improved significantly. In fact, within the oral cavity, survival outcomes may be decreasing.1 Most of these oral and pharyngeal tumors present themselves at an advanced stage despite many of them being easily visible through either direct visualization or simple awake endoscopy.

Patients with oral cavity cancer most often present with a painful lesion in the mouth.2 A diagnosis of head and neck cancer is obtained after this lesion is visualized, biopsied, and then inspected under the microscope. Definitive treatment is then performed with surgery, radiation, and chemotherapy in different combinations, dependent on tumor location and patient preference. The goals of the treatment include complete eradication of the tumor with maximum preservation of function and aesthetics. Despite advances in reconstruction, treatment causes significant morbidity and impairment of many critical functions, such as speech, swallowing, and taste, as well as facial appearance. Earlier detection allows smaller surgical procedures and less aggressive nonsurgical treatment. Subsequently, patients will experience fewer treatment adverse effects and have an improved quality of life and survival. Developing a straightforward, noninvasive diagnostic technique to allow for more accurate and earlier diagnosis would significantly benefit patients.

Fluorescence spectroscopy has shown promise as a noninvasive technique to aid in the diagnosis of head and neck cancer.36 This technique relies on the molecular contrast offered by either endogenous fluorophores present in all tissues or targeted fluorescent exogenous probes. Typically, a light source in the wavelength range of near UV to visible light is used to excite these fluorophores. The fluorescence is then recorded as an emission spectrum. Patterns of peak intensities and spectral line shapes can then be compared for differences among distinct tissues.

Fluorescence spectroscopy is generally divided into steady-state (spectrally resolved or intensity measurements) and time-resolved (time-domain and frequency-domain) techniques. Although steady-state approaches have been extensively tested as a diagnostic tool for head and neck tumors,3,79 the potential of time-resolved techniques to improve the diagnostic ability of these tumors has been scarcely investigated. Time-resolved measurements resolve fluorescence intensity decay in terms of lifetimes, thus providing additional information with regard to the underlying fluorescence dynamics. The use of time-resolved (lifetime) fluorescence to study biological systems offers several distinct advantages. For example, biomolecules with overlapping fluorescence emission spectra but different fluorescence decay times can be discriminated. These measurements are more robust to changes in fluorescence excitation-collection geometry, presence of endogenous absorbers (eg, hemoglobin), photobleaching, and changes in fluorophore concentration, light scattering, and excitation intensity, which thus makes them more suitable for clinical investigations. In addition, a complete fluorescence emission spectrum (steady state) can be obtained by recording the time-resolved fluorescence emission at a number of wavelengths across the emission spectrum.

The hamster buccal pouch carcinogenesis model provides a means to evaluate the ability of fluorescence spectroscopy to distinguish healthy, premalignant, and malignant epithelial cells. In this model, a known carcinogen, 7,12-dimethylbenz(a)anthracene (DMBA), is applied to the buccal pouch of immunocompetent animals 3 times a week.1013 Repeated exposure to the carcinogen leads to consistent temporal development of precancerous lesions followed by cancerous growths. Although many animal models involve injection or implantion of tumor cells into the animals, the hamster cheek pouch model allows study of the sequence of events from healthy epithelium to carcinoma in an immunocompetent animal. After visible tumors are generated, the surrounding epithelium may be healthy or dysplastic. This allows sampling using fluorescence spectroscopy of a wide variety of histopathologic specimens. The objectives of this study were to evaluate the ability of time-resolved, laser-induced fluorescence spectroscopy (TR-LIFS) to serve as a noninvasive diagnostic technique for squamous cell carcinoma in the hamster cheek pouch model and to determine whether time-resolved, fluorescence-derived parameters can add diagnostic value to fluorescence spectroscopy intensity measurements in distinguishing normal tissues from premalignant and malignant epithelium.

ANIMAL CARE

Twenty-two male, golden/Syrian hamsters, 5 to 6 weeks of age, were obtained from Charles River Laboratories (Wilmington, Massachusetts). The experiment was approved by the Institution for Animal Care and Use Committee at the University of California, Davis, to ensure humane treatment of the hamsters, and strict adherence to the protocol was observed. The animals were housed 2 to 3 per cage under controlled conditions with a 12-hour light and dark cycle and given water and standard laboratory chow ad libitum. The study was conducted from February 27, 2007, through August 9, 2007.

INTERVENTION

The right buccal pouch of 19 hamsters was painted with 0.5% DMBA (Sigma Aldrich Corporation, St Louis, Missouri) dissolved in mineral oil 3 times per week until lesions developed. In addition, 3 hamsters that were never exposed to DMBA were included as true healthy controls. These animals were used to control for any bystander effect from painting the contralateral cheek.

INSTRUMENTATION, DATA ACQUISITION, AND ANALYSIS

All animals were anesthetized at the time of the procedure with ketamine hydrochloride and xylazine hydrochloride. While the hamsters were anesthetized, the hamster cheek pouch was everted and examined for lesions. Once the desired buccal tissue was exposed, the tissue was spectroscopically investigated with a prototype TR-LIFS apparatus (Figure 1). This apparatus is similar to a previously used system described in detail in other studies.14,15 In brief, tissue autofluorescence was induced with a pulsed nitrogen laser (337 nm, 700-picosecond pulse width). The collected fluorescence was dispersed by an imaging spectrometer/monochromator (Medel MicroHR, f/3.8, 600-g/mm grating; HORIBA Jobin Yvon Inc, Edison, New Jersey) and then detected with a gated multichannel plate photomultiplier tube. The laser triggering, wavelength scanning, and data acquisition, storage, and processing were controlled by means of a computer workstation and custom analytical software written in LabVIEW (National Instruments Corporation, Austin, Texas) and MATLAB (The Mathworks Inc, Natick, Massachusetts).

Place holder to copy figure label and caption
Figure 1.

Instrument setup for time-resolved fluorescence spectroscopy. GS/s indicates gigasamples per second; MCP-PMT, multichannel plate photomultiplier tube; and ps, picosecond.

Graphic Jump Location

The fiber-optic probe was placed perpendicular to the surface of the cheek pouch regions presumed to be healthy tissue and regions suggestive of carcinoma. The probe was held in position with a specially designed, metallic, 3-dimensional micromanipulator, and each sample investigated was 1 mm in diameter. The fluorescence emission of each sample was scanned in the 360-nm to 650-nm range at 5-nm intervals, with a time resolution of 100-picosecond and at a scanning speed of 0.8 second per wavelength. At each wavelength, 16 fluorescence pulses were collected and averaged by the oscilloscope. The total acquisition time was approximately 45 seconds across the scanned emission spectrum. After each measurement sequence, the monochromator was tuned to a wavelength slightly below the excitation laser line. The laser pulses reflected by the sample were measured and used to represent the temporal profile of the laser pulse. This profile was later used as input to the deconvolution algorithm for the estimation of fluorescence lifetimes.

The data were recorded from regions visually identified as either healthy or suggestive of carcinoma. The suggestive lesions ranged from one to several millimeters in diameter. A total of 96 TR-LIFS measurements were collected from 37 biopsied locations. Between 1 and 4 measurements were taken at each biopsy site, and all spectroscopic measurements from each biopsy specimen were found to be similar. The time-integrated fluorescence (spectral emission) was computed as in previous studies.16

In the context of TR-LIFS, the intrinsic fluorescence impulse response functions, h(n), describe the real dynamics of the fluorescence decay. The impulse response functions were recovered by numerical deconvolution of the measured input laser pulse from the measured fluorescence response transients. The Laguerre expansion technique was used for deconvolution. This analytical approach for characterization of fluorescence decay was recently developed by our research group and described in detail elsewhere.17

HISTOLOGIC ANALYSIS

Once the spectroscopy data had been collected from the desired areas of the cheek pouch, incisional punch biopsies were performed at these locations. By means of the same pathologic classification scheme described in a previous publication by Meier et al,13 a pathologist (B.P.) masked to the study scored standard hematoxylin-eosin–stained slides of these biopsy specimens on a scale 1 to 7 (1, normal; 2, papilloma; 3, mild; 4, moderate; 5, severe dysplasia; 6, carcinoma in situ [CIS]; or 7, invasive carcinoma; the original magnification of all specimens was between ×10 and ×20).

STATISTICAL ANALYSIS

Significant spectral intensity peaks were noted at 3 spectral bands (SBs): SB1, 380 ± 10 nm; SB2, 460 ± 10 nm (SB460); and SB3, 635 ± 10 nm. At these SBs, ratios of the normalized peak intensity were compared among the varying histologic classifications by means of 2-way analysis of variance and significance determined at P < .05. The lifetime values and Laguerre expansion coefficients at SB1, SB2, and SB3 were also analyzed by means of 2-way analysis of variance. As described in previous studies,15,16 a stepwise linear discriminant analysis was used to determine the combination of predictor variables that accounts for most of the differences in the average profiles of the 4 tissue groups (normal epithelium, dysplasia, CIS, and carcinoma) and to generate a classification algorithm for samples classification. The classification accuracy was determined for 5 groups of predictor variables: (1) spectral features only, (2) temporal features only, (3) both spectral and temporal features, (4) spectral and temporal features with the Laguerre coefficients (zero, first, second, and third order), and (5) spectral and temporal features with the Laguerre coefficients (zero order only). A leave-1-out method was used to create the test and training set. The classification accuracy was determined by computation of the sensitivity and specificity. Linear discriminant analysis was performed with the statistical software package SPSS (SPSS Inc, Chicago, Illinois).

HISTOLOGIC ANALYSIS

Histologic examination confirmed healthy tissue in 18 of the 19 specimens presumed to be healthy, with 1 specimen that revealed hyperplasia. In the 18 biopsy specimens taken of lesions suggestive of cancer, 3 were found to have dysplasia, 9 were diagnosed as CIS, and 6 were confirmed to have invasive carcinoma. Of the 96 sites that underwent spectroscopic analysis, 44 were histologically classified as healthy mucosa, 3 as hyperplasia, 5 as moderate dysplasia, 1 as severe dysplasia, 26 as CIS, and 17 as carcinoma. No specimens were categorized as papilloma or mild dysplasia. Because of the small sample of hyperkeratotic and dysplastic lesions, those with hyperkeratosis were included in the healthy group and all grades of dysplasia were pooled, which left 4 histopathologic groups (healthy epithelium, dysplasia, CIS, and carcinoma). The cross-sectional depth of the tissue differed among the groups. Epithelium depth varied from 30 to 100 μm in normal specimens, 120 to 200 μm in dysplastic specimens, 100-1100 μm in CIS specimens, and 100 to 1500 μm in carcinoma specimens.

FLUORESCENCE SPECTROSCOPY

Both steady-state spectra and time-resolved emission features were found to be useful in distinguishing healthy tissue, dysplasia, CIS, and carcinoma. Typical fluorescence impulse response functions for each type of lesion are depicted in Figure 2. The fluorescence decay dynamic was different for healthy epithelium cells, dysplasia, CIS, and carcinoma along the emission spectrum.

Place holder to copy figure label and caption
Figure 2.

Representative of fluorescence impulse response functions. A, Healthy epithelium cells; B, dysplasia; C, carcinoma in situ; and D, carcinoma. AU indicates arbitrary unit; nm, nanometers; and ns, nanoseconds.

Graphic Jump Location

Figure 3A shows normalized integrated fluorescence emission spectra of the healthy cheek pouch mucosa, dysplasia, CIS, and carcinoma. Well-defined peaks are noted at 380, 460, and 635 nm. These peaks are known18 to correspond to collagen (peak, 380-390 nm), nicotinamide adenine dinucleotide (NADH) (460 nm), and porphyrin (633 nm) fluorescence emission, respectively. The normal mucosa presents a main peak at 380 nm with a smaller peak at 460 nm. However, as carcinogenesis ensues, the peak significantly diminishes at 380 nm and the 460-nm peak becomes more prominent. Carcinoma displays a sharp peak at 635 nm, which is less pronounced in CIS and dysplasia. Figure 3B depicts the intensity ratio at 2 SBs, ISB(635) and ISB(460), for each tissue type. This ratio demonstrates that porphyrin fluorescence intensity increases with disease progression (healthy: ISB(635)/ISB(460) = 0.065 [0.00]; dysplasia: 0.16 [0.01]; CIS: 0.39 [0.08]; and carcinoma: 0.66 [0.13]), and the intensity values at these SBs allow for the discrimination of healthy from diseased tissue and the staging of disease.

Place holder to copy figure label and caption
Figure 3.

Spectral intensities and time-domain measurements of the spectral bands. A, Fluorescence intensity spectra values of healthy cheek mucosa (NOR), dysplasia (DYS), carcinoma in situ (CIS), and carcinoma (CA). B, Ratio of fluorescence intensities at 635-nm and 460-nm spectral bands (ISB[635]:ISB[460]) for each tissue type. C, Lifetime values for each tissue type. D, Average lifetime values at the 460-nm spectral band (τSB[460]) for each tissue type. E, Laguerre expansion coefficient, zero order (LEC-0) for each tissue type. F, LEC-0 at the 460-nm spectral band (τSB[460]) for each tissue type. AU indicates arbitrary unit. Results are presented as mean (SE) of the data from each independent measurement.

Graphic Jump Location

The time-resolved emission features of carcinoma were found to be distinct from those of the healthy mucosa, dysplasia, and CIS. The τf values (lifetime) for each tissue type are depicted in Figure 3C. The τf values at the 3 SBs associated with the fluorescence peak emissions support further that the fluorescence of normal and diseased tissue investigated in this study corresponds also to collagen, NADH, and porphyrins. Reported τf values for collagen, NADH, and porphyrin are 0.4 to 2.4, 0.4, and 9 to 18 nanoseconds, respectively.18 Significant differences were seen among each tissue type in the fluorescence lifetimes at 460 nm (Figure 3D). The mean (SE) lifetimes were 1.44 (0.01) nanoseconds for healthy mucosa, 1.25 (0.02) nanoseconds for dysplasia, 1.28 (0.01) nanoseconds for CIS, and 1.34 (0.02) nanoseconds for carcinoma. Varying lifetimes between healthy tissue and carcinoma were also noted at 380 and 635 nm. However, among all tissue types, the lifetime differences at these wavelengths did not reach statistical significance. Laguerre coefficients (zero order) of normal cheek mucosa, dysplasia, CIS, and carcinoma are portrayed in Figure 3E. The values were noted to be significant at 460 nm (Figure 3F). Laguerre coefficients (first, second, and third order) were also determined (data not shown).

Stepwise linear discriminant analysis was then used to determine which combination of predictor variables provided the most clinically useful information. The classification accuracy (sensitivity and specificity values) is summarized in the Table. On the basis of data derived from the steady-state spectroscopy (peak intensity ratios) only, the sensitivity and specificity for discrimination of healthy from diseased tissue are high at 97.9% and 100%, respectively. However, the classification accuracy for the staging of the disease remains poor (eg, sensitivity of 23% for CIS and 47% for carcinoma). When only fluorescence lifetime data were used, the sensitivity for the CIS (39%) and carcinoma (71%) groups improved. Classification on the basis of a combination of spectral-domain and time-domain parameters (peak intensity ratios, lifetimes, and Laguerre coefficients zero order) resulted in significant improvement of both sensitivity (eg, 69% for CIS and 77% for carcinoma) and specificity for all tissue groups.

Table Graphic Jump LocationTable. Sensitivity, Specificity, and Accuracy of Diagnostic Algorithm

In this study, both spectral-domain and time-domain fluorescence features were helpful in distinguishing healthy from neoplastic tissue. Use of these combined features, along with the Laguerre coefficients derived from the numerical deconvolution of the fluorescence impulse function, significantly improved the diagnostic potential of laser-induced fluorescence spectroscopy in the hamster model. Fluorescence spectroscopy in the hamster cheek pouch model has been studied previously.7,1924 However, this was the first study, to our knowledge, that used the hamster pouch as a model for evaluation of the potential of the time-resolved fluorescence technique to discriminate among distinct pathologic stages in oral carcinoma. Previous studies focused solely on spectrally resolved measurements. Balasubramanian et al19 evaluated ex vivo, minced cheek pouch tissue treated for 16 weeks with DMBA and compared this with control tissue. They found a significant fluorescent peak at 630 nm in the tissue treated with DMBA. Another ex vivo study7 showed significant differences in fluorescence at both 380 and 460 nm. Dhingra et al20 performed in vivo measurements and noted a difference in fluorescence between normal and neoplastic lesions at a peak centered between 630 and 640 nm. Additional in vivo studies21,22 were able to distinguish healthy epithelium from precancerous and cancerous tissue. However, these groups were unable to successfully delineate the various stages of carcinogenesis. Wang et al23 used partial least-squares and logistic regression and had better success in distinguishing the stages of carcinogenesis. In our study, the addition of time-resolved data and the Laguerre coefficients to the spectral intensities significantly improved our ability to discriminate precancerous and cancerous lesions.

Fluorescence spectroscopy as a diagnostic instrument has been evaluated in several anatomical sites, including the colon, cervix, esophagus, and upper aerodigestive tract.8,2527 Gillenwater et al3 have extensive research using fluorescence spectroscopy in evaluation of the oral cavity. Early results from their group showed excellent discrimination between healthy and diseased tissue but revealed the limitations of spectrally resolved data in discrimination of precancerous from cancerous lesions. Recently, Mallia et al9 found promising results in distinguishing carcinoma from dysplasia and hyperplasia by comparing spectral intensity ratios at 500 and 685 nm. Müller et al5 were able to distinguish cancerous and dysplastic lesions from healthy epithelium with 96% sensitivity and 96% specificity and discriminate cancerous from dysplastic tissue with 64% sensitivity and 90% specificity by means of trimodal spectroscopy. Trimodal spectroscopy combines intrinsic fluorescence, diffuse reflectance, and light-scattering spectroscopy. Lastly, by means of time-resolved fluorescence spectroscopy at 633 nm, Chen et al18 used time-resolved parameters and could diagnose dysplasia with 93% accuracy and hyperplasia with 75% accuracy.

The discriminant analysis used in this study can distinguish healthy from diseased epithelial cells with 100% sensitivity and specificity. However, lower classification accuracy was encountered when distinguishing among the various stages of carcinogenesis. A few limitations in this study may account for these challenges. Only a small number of preneoplastic lesions were evaluated. To take multiple measurements on several healthy-appearing locations of a DMBA-treated pouch would increase the number of dysplastic specimens and possibly improve the ability to distinguish carcinoma from dysplasia. The diagnostic algorithm also revealed some overlap between carcinoma and CIS. This overlap could be attributed to the way the specimens were processed and read by the histopathologist. Possibly, some of the histologic slides evaluated did not include the actual portion of tumor that contained invasion of the basement membrane, and the histologist unknowingly erred on the side of underscoring the lesions. Future studies could address these limitations. Nevertheless, the use of the time-resolved parameters in the classification model improved the overall classification accuracy from approximately 69% (spectral parameters only) to approximately 87% (spectral and temporal characteristics combined).

The addition of the time-resolved data increased the specificity of the fluorescence measurements, which allowed for greater than 92% specificity across all histopathologic groups. Also, the lifetime fluorescence measurements contribute to a better understanding of the tissue morphologic features and molecular makeup at each stage of carcinogenesis. During carcinogenesis, changes in metabolic activity (NADH concentration and protein binding), stroma (collagen cross-linking), and neovascularization (porphyrin) can be detected with variations in tissue autofluorescence.28

These findings highlight the importance of time-resolved fluorescence data in improvement of the diagnostic potential of laser-induced fluorescence spectroscopy. Studies are currently under way to assess the validity of this algorithm in patients with head and neck cancer. Further development of this technique could lead to a noninvasive diagnostic technique for head and neck squamous cell carcinoma and assist surgeons intraoperatively when evaluating surgical margins.

Correspondence: D. Gregory Farwell, MD, Department of Otolaryngology–Head and Neck Surgery, University of California, Davis Medical Center, 2521 Stockton Blvd, Ste 7200, Sacramento, CA 95817 (gregory.farwell@ucdmc.ucdavis.edu).

Submitted for Publication: March 3, 2009; final revision received June 8, 2009; accepted September 13, 2009.

Author Contributions: Dr Farwell had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Farwell, Meier, Enepekides, and Marcu. Acquisition of data: Farwell, Park, Sun, Coffman, and Tinling. Analysis and interpretation of data: Farwell, Meier, Park, Sun, Poirier, and Phipps. Drafting of the manuscript: Farwell, Meier, Park, and Coffman. Critical revision of the manuscript for important intellectual content: Farwell, Meier, Park, Sun, Poirier, Phipps, Tinling, Enepekides, and Marcu. Statistical analysis: Meier, Park, and Sun. Obtained funding: Farwell. Administrative, technical, and material support: Farwell, Meier, Sun, Coffman, Poirier, and Tinling. Study supervision: Farwell, Enepekides, and Marcu.

Financial Disclosure: None reported.

Funding/Support: This work was supported in part by National Institutes of Health grants R01-HL67377 and UL1 RR024146 and by the NSF Center for Biophotonics Science and Technology and the Cancer Center at University of California, Davis.

Carvalho  ALNishimoto  INCalifano  JAKowalski  LP Trends in incidence and prognosis for head and neck cancer in the United States: a site-specific analysis of the SEER database. Int J Cancer 2005;114 (5) 806- 816
PubMed
Myers  ENSimental  AACancer of the oral cavity. Myers  ENSuen  JYMyers  JNHanna  EYCancer of the Head and Neck. Philadelphia, PA Saunders2003;
Gillenwater  AJacob  RGaneshappa  R  et al.  Noninvasive diagnosis of oral neoplasia based on fluorescence spectroscopy and native tissue autofluorescence. Arch Otolaryngol Head Neck Surg 1998;124 (11) 1251- 1258
PubMed
Poh  CFZhang  LAnderson  DW  et al.  Fluorescence visualization detection of field alterations in tumor margins of oral cancer patients. Clin Cancer Res 2006;12 (22) 6716- 6722
PubMed
Müller  MGValdez  TAGeorgakoudi  I  et al.  Spectroscopic detection and evaluation of morphologic and biochemical changes in early human oral carcinoma. Cancer 2003;97 (7) 1681- 1692
PubMed
De Veld  DCWitjes  MJSterenborg  HJRoodenburg  JL The status of in vivo autofluorescence spectroscopy and imaging for oral oncology. Oral Oncol 2005;41 (2) 117- 131
PubMed
Chen  CTChiang  HKChow  SN  et al.  Autofluorescence in normal and malignant human oral tissues and in DMBA-induced hamster buccal pouch carcinogenesis. J Oral Pathol Med 1998;27 (10) 470- 474
PubMed
Heintzelman  DLUtzinger  UFuchs  H  et al.  Optimal excitation wavelengths for in vivo detection of oral neoplasia using fluorescence spectroscopy. Photochem Photobiol 2000;72 (1) 103- 113
PubMed
Mallia  RJThomas  SSMathews  A  et al.  Laser-induced autofluorescence spectral ratio reference standard for early discrimination of oral cancer. Cancer 2008;112 (7) 1503- 1512
PubMed
Shklar  G Experimental oral pathology in the Syrian hamster. Prog Exp Tumor Res 1972;16518- 538
PubMed
Gimenez-Conti  I The hamster cheek pouch carcinogenesis model. Acta Odontol Latinoam 1993;7 (1) 3- 12
PubMed
Salley  JJ Experimental carcinogenesis in the cheek pouch of the Syrian hamster. J Dent Res 1954;33 (2) 253- 262
PubMed
Meier  JDEnepekides  DJPoirier  BBradley  CAAlbala  JSFarwell  DG Treatment with 1-alpha,25-dihydroxyvitamin D3 (vitamin D3) to inhibit carcinogenesis in the hamster buccal pouch model. Arch Otolaryngol Head Neck Surg 2007;133 (11) 1149- 1152
PubMed
Fang  QPapaioannou  TJo  JAVaitha  RShastry  KMarcu  L Time-domain laser-induced fluorescence spectroscopy apparatus for clinical diagnostics. Rev Sci Instrum 2004;75 (1) 151- 162
Marcu  LFang  QJo  JA  et al.  In-vivo detection of macrophages in a rabbit atherosclerotic model by time-resolved laser-induced fluorescence spectroscopy. Atherosclerosis 2005;181 (2) 295- 303
PubMed
Butte  PVPikul  BKHever  AYong  WHBlack  KLMarcu  L Diagnosis of meningioma by time-resolved fluorescence spectroscopy. J Biomed Opt 2005;10 (6) 064026
PubMed
Jo  JAFang  QPapaioannou  TMarcu  L Fast model-free deconvolution of fluorescence decay for analysis of biological systems. J Biomed Opt 2004;9 (4) 743- 752
PubMed
Chen  HMChiang  CPYou  CHsiao  TCWang  CY Time-resolved autofluorescence spectroscopy for classifying normal and premalignant oral tissues. Lasers Surg Med 2005;37 (1) 37- 45
PubMed
Balasubramanian  SElangovan  VGovindasamy  S Fluorescence spectroscopic identification of 7,12-dimethylbenz[a]anthracene-induced hamster buccal pouch carcinogenesis. Carcinogenesis 1995;16 (10) 2461- 2465
PubMed
Dhingra  JKZhang  X McMillan  K  et al.  Diagnosis of head and neck precancerous lesions in an animal model using fluorescence spectroscopy. Laryngoscope 1998;108 (4, pt 1) 471- 475
PubMed
Wang  CYTsai  TChen  HCChang  SCChen  CTChiang  CP Autofluorescence spectroscopy for in vivo diagnosis of DMBA-induced hamster buccal pouch pre-cancers and cancers. J Oral Pathol Med 2003;32 (1) 18- 24
PubMed
Coghlan  LUtzinger  URichards-Kortum  R  et al.  Fluorescence spectroscopy of epithelial tissue throughout the dysplasia-carcinoma sequence in an animal model: spectroscopic changes precede morphologic changes. Lasers Surg Med 2001;29 (1) 1- 10
PubMed
Wang  CYChen  CTChiang  CPYoung  STChow  SNChiang  HK A probability-based multivariate statistical algorithm for autofluorescence spectroscopic identification of oral carcinogenesis. Photochem Photobiol 1999;69 (4) 471- 477
PubMed
Coghlan  LUtzinger  UDrezek  R  et al.  Optimal fluorescence excitation wavelengths for detection of squamous intra-epithelial neoplasia: results from an animal model. Opt Express 2000;7 (12) 436- 446
PubMed
Schomacker  KTFrisoli  JKCompton  CC  et al.  Ultraviolet laser-induced fluorescence of colonic tissue: basic biology and diagnosis potential. Lasers Surg Med 1992;12 (1) 63- 78
PubMed
Ramanujam  NMitchell  MFMahadevan  A  et al.  In vivo diagnosis of cervical intraepithelial neoplasia using 337-nm-excited laser induced fluorescence. Proc Natl Acad Sci U S A 1994;91 (21) 10193- 10197
PubMed
Panjehpour  MOverholt  BFVo-Dinh  THaggitt  RCEdwards  DHBuckley  FP  III Endoscopic fluorescence detection of high-grade dysplasia in Barrett's esophagus. Gastroenterology 1996;111 (1) 93- 101
PubMed
Schwarz  RAGao  WDaye  DWilliams  MDRichards-Kortum  RGillenwater  AM Autofluorescence and diffuse reflectance spectroscopy of oral epithelial tissue using a depth-sensitive fiber-optic probe. Appl Opt 2008;47 (6) 825- 834
PubMed

Figures

Place holder to copy figure label and caption
Figure 1.

Instrument setup for time-resolved fluorescence spectroscopy. GS/s indicates gigasamples per second; MCP-PMT, multichannel plate photomultiplier tube; and ps, picosecond.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Representative of fluorescence impulse response functions. A, Healthy epithelium cells; B, dysplasia; C, carcinoma in situ; and D, carcinoma. AU indicates arbitrary unit; nm, nanometers; and ns, nanoseconds.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3.

Spectral intensities and time-domain measurements of the spectral bands. A, Fluorescence intensity spectra values of healthy cheek mucosa (NOR), dysplasia (DYS), carcinoma in situ (CIS), and carcinoma (CA). B, Ratio of fluorescence intensities at 635-nm and 460-nm spectral bands (ISB[635]:ISB[460]) for each tissue type. C, Lifetime values for each tissue type. D, Average lifetime values at the 460-nm spectral band (τSB[460]) for each tissue type. E, Laguerre expansion coefficient, zero order (LEC-0) for each tissue type. F, LEC-0 at the 460-nm spectral band (τSB[460]) for each tissue type. AU indicates arbitrary unit. Results are presented as mean (SE) of the data from each independent measurement.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable. Sensitivity, Specificity, and Accuracy of Diagnostic Algorithm

References

Carvalho  ALNishimoto  INCalifano  JAKowalski  LP Trends in incidence and prognosis for head and neck cancer in the United States: a site-specific analysis of the SEER database. Int J Cancer 2005;114 (5) 806- 816
PubMed
Myers  ENSimental  AACancer of the oral cavity. Myers  ENSuen  JYMyers  JNHanna  EYCancer of the Head and Neck. Philadelphia, PA Saunders2003;
Gillenwater  AJacob  RGaneshappa  R  et al.  Noninvasive diagnosis of oral neoplasia based on fluorescence spectroscopy and native tissue autofluorescence. Arch Otolaryngol Head Neck Surg 1998;124 (11) 1251- 1258
PubMed
Poh  CFZhang  LAnderson  DW  et al.  Fluorescence visualization detection of field alterations in tumor margins of oral cancer patients. Clin Cancer Res 2006;12 (22) 6716- 6722
PubMed
Müller  MGValdez  TAGeorgakoudi  I  et al.  Spectroscopic detection and evaluation of morphologic and biochemical changes in early human oral carcinoma. Cancer 2003;97 (7) 1681- 1692
PubMed
De Veld  DCWitjes  MJSterenborg  HJRoodenburg  JL The status of in vivo autofluorescence spectroscopy and imaging for oral oncology. Oral Oncol 2005;41 (2) 117- 131
PubMed
Chen  CTChiang  HKChow  SN  et al.  Autofluorescence in normal and malignant human oral tissues and in DMBA-induced hamster buccal pouch carcinogenesis. J Oral Pathol Med 1998;27 (10) 470- 474
PubMed
Heintzelman  DLUtzinger  UFuchs  H  et al.  Optimal excitation wavelengths for in vivo detection of oral neoplasia using fluorescence spectroscopy. Photochem Photobiol 2000;72 (1) 103- 113
PubMed
Mallia  RJThomas  SSMathews  A  et al.  Laser-induced autofluorescence spectral ratio reference standard for early discrimination of oral cancer. Cancer 2008;112 (7) 1503- 1512
PubMed
Shklar  G Experimental oral pathology in the Syrian hamster. Prog Exp Tumor Res 1972;16518- 538
PubMed
Gimenez-Conti  I The hamster cheek pouch carcinogenesis model. Acta Odontol Latinoam 1993;7 (1) 3- 12
PubMed
Salley  JJ Experimental carcinogenesis in the cheek pouch of the Syrian hamster. J Dent Res 1954;33 (2) 253- 262
PubMed
Meier  JDEnepekides  DJPoirier  BBradley  CAAlbala  JSFarwell  DG Treatment with 1-alpha,25-dihydroxyvitamin D3 (vitamin D3) to inhibit carcinogenesis in the hamster buccal pouch model. Arch Otolaryngol Head Neck Surg 2007;133 (11) 1149- 1152
PubMed
Fang  QPapaioannou  TJo  JAVaitha  RShastry  KMarcu  L Time-domain laser-induced fluorescence spectroscopy apparatus for clinical diagnostics. Rev Sci Instrum 2004;75 (1) 151- 162
Marcu  LFang  QJo  JA  et al.  In-vivo detection of macrophages in a rabbit atherosclerotic model by time-resolved laser-induced fluorescence spectroscopy. Atherosclerosis 2005;181 (2) 295- 303
PubMed
Butte  PVPikul  BKHever  AYong  WHBlack  KLMarcu  L Diagnosis of meningioma by time-resolved fluorescence spectroscopy. J Biomed Opt 2005;10 (6) 064026
PubMed
Jo  JAFang  QPapaioannou  TMarcu  L Fast model-free deconvolution of fluorescence decay for analysis of biological systems. J Biomed Opt 2004;9 (4) 743- 752
PubMed
Chen  HMChiang  CPYou  CHsiao  TCWang  CY Time-resolved autofluorescence spectroscopy for classifying normal and premalignant oral tissues. Lasers Surg Med 2005;37 (1) 37- 45
PubMed
Balasubramanian  SElangovan  VGovindasamy  S Fluorescence spectroscopic identification of 7,12-dimethylbenz[a]anthracene-induced hamster buccal pouch carcinogenesis. Carcinogenesis 1995;16 (10) 2461- 2465
PubMed
Dhingra  JKZhang  X McMillan  K  et al.  Diagnosis of head and neck precancerous lesions in an animal model using fluorescence spectroscopy. Laryngoscope 1998;108 (4, pt 1) 471- 475
PubMed
Wang  CYTsai  TChen  HCChang  SCChen  CTChiang  CP Autofluorescence spectroscopy for in vivo diagnosis of DMBA-induced hamster buccal pouch pre-cancers and cancers. J Oral Pathol Med 2003;32 (1) 18- 24
PubMed
Coghlan  LUtzinger  URichards-Kortum  R  et al.  Fluorescence spectroscopy of epithelial tissue throughout the dysplasia-carcinoma sequence in an animal model: spectroscopic changes precede morphologic changes. Lasers Surg Med 2001;29 (1) 1- 10
PubMed
Wang  CYChen  CTChiang  CPYoung  STChow  SNChiang  HK A probability-based multivariate statistical algorithm for autofluorescence spectroscopic identification of oral carcinogenesis. Photochem Photobiol 1999;69 (4) 471- 477
PubMed
Coghlan  LUtzinger  UDrezek  R  et al.  Optimal fluorescence excitation wavelengths for detection of squamous intra-epithelial neoplasia: results from an animal model. Opt Express 2000;7 (12) 436- 446
PubMed
Schomacker  KTFrisoli  JKCompton  CC  et al.  Ultraviolet laser-induced fluorescence of colonic tissue: basic biology and diagnosis potential. Lasers Surg Med 1992;12 (1) 63- 78
PubMed
Ramanujam  NMitchell  MFMahadevan  A  et al.  In vivo diagnosis of cervical intraepithelial neoplasia using 337-nm-excited laser induced fluorescence. Proc Natl Acad Sci U S A 1994;91 (21) 10193- 10197
PubMed
Panjehpour  MOverholt  BFVo-Dinh  THaggitt  RCEdwards  DHBuckley  FP  III Endoscopic fluorescence detection of high-grade dysplasia in Barrett's esophagus. Gastroenterology 1996;111 (1) 93- 101
PubMed
Schwarz  RAGao  WDaye  DWilliams  MDRichards-Kortum  RGillenwater  AM Autofluorescence and diffuse reflectance spectroscopy of oral epithelial tissue using a depth-sensitive fiber-optic probe. Appl Opt 2008;47 (6) 825- 834
PubMed

Correspondence

CME
Meets CME requirements for:
Browse CME for all U.S. States
Accreditation Information
The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
Note: You must get at least of the answers correct to pass this quiz.
You have not filled in all the answers to complete this quiz
The following questions were not answered:
Sorry, you have unsuccessfully completed this CME quiz with a score of
The following questions were not answered correctly:
Commitment to Change (optional):
Indicate what change(s) you will implement in your practice, if any, based on this CME course.
Your quiz results:
The filled radio buttons indicate your responses. The preferred responses are highlighted
For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.
NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).
Submit a Comment

Multimedia

Some tools below are only available to our subscribers or users with an online account.

Web of Science® Times Cited: 8

Related Content

Customize your page view by dragging & repositioning the boxes below.

Articles Related By Topic
Related Topics
PubMed Articles