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Identification of oral cancer in OCT images based on an optical attenuation model

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Abstract

Surgery is still the first choice to treat oral cancer, where it is important to detect surgical margins in order to reduce cancer recurrence and maintain oral-maxillofacial function simultaneously. As a non-invasive and in situ imaging technique, optical coherence tomography (OCT) can obtain images close to the resolution of histopathology, which makes it have great potential in intraoperative diagnosis. However, it is not enough to find surgical margins accurately just observing OCT images directly and qualitatively. The purpose of this study is to identify oral cancer in OCT images by investigating the quantitative difference of cancer and non-cancer tissue. Based on an available optical attenuation model and the axial confocal PSF of a home-made swept source OCT system, by using fresh ex vivo human oral tissues from 14 patients of oral squamous cell carcinoma (OSCC) as the samples, diagnosis with sensitivity (97.88%) and specificity (83.77%) was achieved at the attenuation threshold of 4.7 mm−1, and the accuracy of identification reached 91.15% in our study. Our preliminary results demonstrated that the oral cancer resection will be guided accurately and the clinical application of OCT will be further promoted by deeply mining the information hidden in OCT images.

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References

  1. Siegel RL, Miller KD, Jemal A (2019) Cancer statistics, 2019. CA Cancer J Clin 69(1):7–34. https://doi.org/10.3322/caac.21551

    Article  Google Scholar 

  2. American Cancer Society (2017) Cancer facts & figures. American Cancer Society, Atlanta

    Google Scholar 

  3. Massano J, Regateiro FS, Januario G, Ferreira A (2006) Oral squamous cell carcinoma: review of prognostic and predictive factors. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 102(1):67–76. https://doi.org/10.1016/j.tripleo.2005.07.038

    Article  Google Scholar 

  4. Azzopardi S, Lowe D, Rogers S (2019) Audit of the rates of re-excision for close or involved margins in the management of oral cancer. Br J Oral Maxillofac Surg 57(7):678–681. https://doi.org/10.1016/j.bjoms.2019.05.006

    Article  CAS  Google Scholar 

  5. Costello F (2017) Optical coherence tomography in neuro-ophthalmology. Neurol Clin 35(1):153–163. https://doi.org/10.1016/j.ncl.2016.08.012

    Article  Google Scholar 

  6. Abdelazeem K, Sharaf M, Saleh MGA, Fathalla AM, Soliman W (2018) Relevance of swept-source anterior segment optical coherence tomography for corneal imaging in patients with flap-related complications after LASIK. Cornea 38(1):93–97. https://doi.org/10.1097/ico.0000000000001773

    Article  Google Scholar 

  7. Yonetsu T, Bouma BE, Kato K, Fujimoto JG, Jang IK (2013) Optical coherence tomography- 15 years in cardiology. Circ J 77(8):1933–1940. https://doi.org/10.1253/circj.cj-13-0643.1

    Article  Google Scholar 

  8. Tsai TH, Leggett CL, Trindade AJ, Sethi A, Swager AF, Joshi V, Bergman JJ, Mashimo H, Nishioka NS, Namati E (2017) Optical coherence tomography in gastroenterology: a review and future outlook. J Biomed Opt 22(12):1–17. https://doi.org/10.1117/1.jbo.22.12.121716

    Article  Google Scholar 

  9. Adabi S, Fotouhi A, Xu Q, Daveluy S, Mehregan D, Podoleanu A, Nasiriavanaki M (2018) An overview of methods to mitigate artifacts in optical coherence tomography imaging of the skin. Skin Res Technol 24(2):265–273. https://doi.org/10.1111/srt.12423

    Article  Google Scholar 

  10. Jerjes W, Hamdoon Z, Hopper C (2019) Structural validation of facial skin using optical coherence tomography: a descriptive study. Skin Res Technol 00:1–10. https://doi.org/10.1111/srt.12791

    Article  Google Scholar 

  11. Van Soest G, Goderie T, Regar E, Koljenovic S, van Leenders GLJH, Gonzalo N, van Noorden S, Okamura T, Bouma BE, Tearney GJ, Oosterhuis JW, Serruys PW, van der Steen AFW (2010) Atherosclerotic tissue characterization in vivo by optical coherence tomography attenuation imaging. J Biomed Opt 15(1):011105. https://doi.org/10.1117/1.3280271

    Article  Google Scholar 

  12. Zhang Q, Wu X, Tang T, Zhu S, Yao Q, Gao B, Yuan X (2012) Quantitative analysis of rectal cancer by spectral domain optical coherence tomography. Phys Med Biol 57(16):5235–5244. https://doi.org/10.1088/0031-9155/57/16/5235

    Article  CAS  Google Scholar 

  13. Xu C, Schmitt JM, Carlier SG, Virmani R (2008) Characterization of atherosclerosis plaques by measuring both backscattering and attenuation coefficients in optical coherence tomography. J Biomed Opt 13(3):034003

    Article  Google Scholar 

  14. Kah JCY, Chow TH, Ng BK, Razul SG, Olivo M, Sheppard CJR (2009) Concentration dependence of gold nanoshells on the enhancement of optical coherence tomography images: a quantitative study. Appl Opt 48(10):D96–D108. https://doi.org/10.1364/AO.48.000D96

    Article  CAS  Google Scholar 

  15. Yuan W, Kut C, Liang W, Li XD (2017) Robust and fast characterization of OCT-based optical attenuation using a novel frequency-domain algorithm for brain cancer detection. Sci Rep 7:44909. https://doi.org/10.1038/srep44909

    Article  CAS  Google Scholar 

  16. Kut C, Chaichana KL, Xi J, Raza SM, Ye X, McVeigh ER, Rodriguez FJ, Quiñones-Hinojosa A, Li XD (2015) Detection of human brain cancer infiltration ex vivo and in vivo using quantitative optical coherence tomography. Sci Transl Med 7(292):292ra100. https://doi.org/10.1126/scitranslmed.3010611

    Article  Google Scholar 

  17. Tes D, Aber A, Zafar M, Horton L, Fotouhi A, Xu Q, Moiin A, Thompson AD, Moraes Pinto Blumetti TC, Daveluy S, Chen W, Nasiriavanaki M (2018) Granular cell tumor imaging using optical coherence tomography. Biomed Eng Comput Biol 9:1–9. https://doi.org/10.1177/1179597218790250

    Article  Google Scholar 

  18. Adabi S, Hosseinzadeh M, Noei S, Conforto S, Daveluy S, Clayton A, Mehregan D, Nasiriavanaki M (2017) Universal in vivo textural model for human skin based on optical coherence tomograms. Sci Rep 7(1):17912. https://doi.org/10.1038/s41598-017-17398-8

    Article  CAS  Google Scholar 

  19. Jung W, Zhang J, Chung J, Wilder-Smith P, Brenner M, Nelson JS, Chen Z (2005) Advances in oral cancer detection using optical coherence tomography. IEEE J Sel Top Quantum Electron 11(4):811–817. https://doi.org/10.1109/JSTQE.2005.857678

    Article  CAS  Google Scholar 

  20. Wilder-Smith P, Hammer-Wilson MJ, Zhang J, Wang Q, Osann K, Chen Z, Wigdor H, Schwartz J, Epstein J (2007) In vivo imaging of oral mucositis in an animal model using optical coherence tomography and optical Doppler tomography. Clin Cancer Res 13(8):2449–2454. https://doi.org/10.1158/1078-0432.CCR-06-2234

    Article  CAS  Google Scholar 

  21. Jerjes W, Upile T, Betz CS, Abbas S, Sandison A, Hopper C (2008) Detection of oral pathologies using optical coherence tomography. Eur Oncol Haematol 4(1):57–59. https://doi.org/10.17925/eoh.2008.04.1.57

    Article  Google Scholar 

  22. Davoudi B, Lindenmaier A, Standish BA, Allo G, Bizheva K, Vitkin A (2012) Noninvasive in vivo structural and vascular imaging of human oral tissues with spectral domain optical coherence tomography. Biomed Opt Express 3(5):826–839. https://doi.org/10.1364/BOE.3.000826

    Article  Google Scholar 

  23. Hamdoon Z, Jerjes W, Upile T, McKenzie G, Jay A, Hopper C (2013) Optical coherence tomography in the assessment of suspicious oral lesions: an immediate ex vivo study. Photodiagnosis and Photodynamic Therapy 10(1):17–27. https://doi.org/10.1016/j.pdpdt.2012.07.005

    Article  Google Scholar 

  24. Choi WJ, Wang RK (2014) In vivo imaging of functional microvasculature within tissue beds of oral and nasal cavities by swept-source optical coherence tomography with a forward/side-viewing probe. Biomed Opt Express 5(8):2620–2634. https://doi.org/10.1364/BOE.5.002620

    Article  Google Scholar 

  25. Maslennikova AV, Sirotkina MA, Moiseev AA, Finagina ES, Ksenofontov SY, Gelikonov GV, Matveev LA, Kiseleva EB, Zaitsev VY, Zagaynova EV, Feldchtein FI, Gladkova ND, Vitkin A (2017) In-vivo longitudinal imaging of microvascular changes in irradiated oral mucosa of radiotherapy cancer patients using optical coherence tomography. Sci Rep 7(1):16505. https://doi.org/10.1038/s41598-017-16823-2

    Article  CAS  Google Scholar 

  26. Tsai M-T, Chen Y, Lee C-Y, Huang B-H, Trung NH, Lee Y-J, Wang Y-L (2017) Noninvasive structural and microvascular anatomy of oral mucosae using handheld optical coherence tomography. Biomed Opt Express 8(11):5001–5012. https://doi.org/10.1364/BOE.8.005001

    Article  CAS  Google Scholar 

  27. Maslennikova A, Sirotkina M, Sedova E, Moiseev A, Ksenofontov S, Gelikonov G, Matveev L, Kiseleva E, Zaitsev V, Zagaynova E, Feldstein F, Gladkova N, Vitkin A (2018) In vivo imaging of microvascular changes in irradiated oral mucosa by optical coherence tomography. Radiother Oncol 127:E586–E586

    Article  Google Scholar 

  28. Surlin P, Camen A, Stratul SI, Roman A, Gheorghe DN, Herascu E, Osiac E, Rogoveanu I (2018) Optical coherence tomography assessment of gingival epithelium inflammatory status in periodontal - systemic affected patients. Ann Anat 219:51–56. https://doi.org/10.1016/j.aanat.2018.04.010

    Article  Google Scholar 

  29. Heidari AE, Sunny SP, James BL, Lam TM, Tran AV, Yu J, Ramanjinappa RD, Uma K, Birur P, Suresh A, Kuriakose MA, Chen Z, Wilder-Smith P (2019) Optical coherence tomography as an oral cancer screening adjunct in a low resource settings. IEEE J Sel Top Quantum Electron 25(1):1–8. https://doi.org/10.1109/JSTQE.2018.2869643

    Article  Google Scholar 

  30. Tsai M-T, Lee H-C, Lee C-K, Yu C-H, Chen H-M, Chiang C-P, Chang C-C, Wang Y-M, Yang CC (2008) Effective indicators for diagnosis of oral cancer using optical coherence tomography. Opt Express 16(20):15847–15862. https://doi.org/10.1364/OE.16.015847

    Article  Google Scholar 

  31. Tsai M-T, Lee C-K, Lee H-C, Chen H-M, Chiang C-P, Wang Y-M, Yang CC (2009) Differentiating oral lesions in different carcinogenesis stages with optical coherence tomography. J Biomed Opt 14(4):044028. https://doi.org/10.1117/1.3200936

    Article  Google Scholar 

  32. Adegun OK, Tomlins PH, Hagi-Pavli E, McKenzie G, Piper K, Bader DL, Fortune F (2012) Quantitative analysis of optical coherence tomography and histopathology images of normal and dysplastic oral mucosal tissues. Lasers Med Sci 27(4):795–804. https://doi.org/10.1007/s10103-011-0975-1

    Article  Google Scholar 

  33. Faber DJ, van der Meer FJ, Aalders MCG, van Leeuwen TG (2004) Quantitative measurement of attenuation coefficients of weakly scattering media using optical coherence tomography. Opt Express 12(19):4353–4365. https://doi.org/10.1364/OPEX.12.004353

    Article  Google Scholar 

  34. Adegun OK, Tomlins PH, Hagi-Pavli E, Bader DL, Fortune F (2012) Quantitative optical coherence tomography of fluid-filled oral mucosal lesions. Lasers Med Sci 28(5):1249–1255. https://doi.org/10.1007/s10103-012-1208-y

    Article  Google Scholar 

  35. Fatakdawala H, Poti S, Zhou F, Sun Y, Bec J, Liu J, Yankelevich DR, Tinling SP, Gandour-Edwards RF, Farwell DG, Marcu L (2013) Multimodal in vivo imaging of oral cancer using fluorescence lifetime, photoacoustic and ultrasound techniques. Biomed Opt Express 4(9):1724–1741. https://doi.org/10.1364/BOE.4.001724

    Article  Google Scholar 

  36. Izzetti R, Fantoni G, Gelli F, Faggioni L, Vitali S, Gabriele M, Caramella D (2018) Feasibility of intraoral ultrasonography in the diagnosis of oral soft tissue lesions: a preclinical assessment on an ex vivo specimen. Radiol Med 123(2):135–142. https://doi.org/10.1007/s11547-017-0817-8

    Article  Google Scholar 

  37. Simonato LE, Tomo S, Miyahara GI, Navarro RS, Villaverde AGJB (2017) Fluorescence visualization efficacy for detecting oral lesions more prone to be dysplastic and potentially malignant disorders: a pilot study. Photodiagn Photodyn Ther 17:1–4. https://doi.org/10.1016/j.pdpdt.2016.10.010

    Article  Google Scholar 

  38. Lu G, Wang D, Qin X, Muller S, Wang X, Chen AY, Chen ZG, Fei B (2018) Detection and delineation of squamous neoplasia with hyperspectral imaging in a mouse model of tongue carcinogenesis. J Biophotonics 11(3). https://doi.org/10.1002/jbio.201700078

  39. Wang J, Zheng W, Lin K, Huang Z (2018) Characterizing biochemical and morphological variations of clinically relevant anatomical locations of oral tissue in vivo with hybrid Raman spectroscopy and optical coherence tomography technique. J Biophotonics 11(3). https://doi.org/10.1002/jbio.201700113

  40. Tsai M-R, Shieh D-B, Lou P-J, Lin C-F, Sun C-K (2012) Characterization of oral squamous cell carcinoma based on higher-harmonic generation microscopy. J Biophotonics 5(5–6):415–424. https://doi.org/10.1002/jbio.201100144

    Article  Google Scholar 

  41. Turani Z, Fatemizadeh E, Blumetti T, Daveluy S, Moraes AF, Chen W, Mehregan D, Andersen PE, Nasiriavanaki M (2019) Optical radiomic signatures derived from optical coherence tomography images to improve identification of melanoma. Cancer Res 79(8):2021–2030

    Article  CAS  Google Scholar 

  42. Yang Z, Shang J, Liu C, Zhang J, Hou F, Liang Y (2020) Intraoperative imaging of oral-maxillofacial lesions using optical coherence tomography. J Innov Opt Health Sci:2050010. https://doi.org/10.1142/s1793545820500108

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Funding

This study was supported in part by the National Natural Science Foundation of China (61875092 and 11374167), Science and Technology Support Program of Tianjin (17YFZCSY00740), and Fundamental Research Funds for the Central Universities.

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Authors and Affiliations

  1. Institute of Modern Optics, Nankai University, 38 Tongyan Road, Tianjin, 300350, China

    Zihan Yang & Yanmei Liang

  2. Department of Oral Pathology, Tianjin Stomatological Hospital; Hospital of Stomatology, Nankai University, Tianjin, 300041, China

    Jianwei Shang

  3. Department of Oral Medicine, Tianjin Stomatological Hospital; Hospital of Stomatology, Nankai University, Tianjin, 300041, China

    Chenlu Liu

  4. Department of Oral-Maxillofacial Surgery, Tianjin Stomatological Hospital; Hospital of Stomatology, Nankai University, Tianjin, 300041, China

    Jun Zhang

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  1. Zihan Yang
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  2. Jianwei Shang
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  5. Yanmei Liang
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Correspondence to Yanmei Liang.

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All procedures performed in this study involving human participants were in accordance with the ethical standards of the Ethics Committee of Tianjin Stomatological Hospital.

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Yang, Z., Shang, J., Liu, C. et al. Identification of oral cancer in OCT images based on an optical attenuation model. Lasers Med Sci 35, 1999–2007 (2020). https://doi.org/10.1007/s10103-020-03025-y

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