Medical & Biological Engineering & Computing

, Volume 49, Issue 1, pp 85–96 | Cite as

Can we see epithelium tissue structure below the surface using an optical probe?

  • Fernand S. Cohen
  • Ezgi Taslidere
  • Sreekant Murthy
Original Article


This paper answers the question of whether it is possible to detect changes below the surface in epithelium layered structures using a Stochastic Decomposition Method (SDM) that models the scattered light reflected from the layered structure over an area (2-D scan) illuminated by an optical sensor (fibre) emitting light at either one wavelength or with white light. Our technique correlates the differential changes in the reflected tissue texture with the morphological and physical changes that occur in the tissue occurring inside the structure. This work has great potential for detecting changes in mucosal structures and may lead to enhanced endoscopy when the disease is developing to the outside of the mucosal structure and hence becoming hidden during colonoscopy or endoscopic examination. Tests are performed on layered tissue phantoms, and the results obtained show great effectiveness of the model and method in picking up changes in the morphology of the layered tissue phantoms occurring below the surface. We also establish the robustness of the model to changes in viewing depth by testing it on phantoms viewed at different depths. We show that the model is robust to within a 4-mm-deep viewing range.


Biological signal processing Optical imaging Pattern recognition Optical signal processing Stochastic analysis Spectral analysis Computer-aided diagnosis Modelling biomedical systems 



We would like to thank Photonics Lab members: Ms. Elina Vitol, Dr. Timothy Kurzweg and Dr. Bahram Nabet in the ECE Dept. at Drexel University for providing the optical device (probe, spectrometer and light source) and the phantoms used in this research. Special thanks are also due Ms. Elina Vitol for preparing the multi-layered tissue phantoms. We also thank Dr. Jim Reynolds from Drexel College of Medicine for many useful discussions on the subject of light endoscopy.


  1. 1.
    Cohen FS, Taslidere E, Murthy S (2008) Classification of layered tissue phantoms for detection of changes in epithelial tissue below the surface using a stochastic decomposition model for scattered signal In: 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro. ISBI 2008, Paris, France, May 14–17, 2008, pp 1211–1214Google Scholar
  2. 2.
    Dacosta RS, Wilson BC, Marcon NE (2002) New optical technologies for earlier endoscopic diagnosis of premalignant gastrointestinal lesions. J Gastroenterol Hepatol 17(Suppl):S85–S104CrossRefPubMedGoogle Scholar
  3. 3.
    DaCosta RS, Wilson BC, Marcon NE (2005) Optical techniques for the endoscopic detection of dysplastic colonic lesions. Curr Opin Gastroenterol 21:70–79PubMedGoogle Scholar
  4. 4.
    Dacosta RS, Wilson BC, Marcon NE (2006) Spectroscopy and fluorescence in esophageal diseases. Best Pract Res Clin Gastroenterol 20:41–57CrossRefPubMedGoogle Scholar
  5. 5.
    Kiesslich R, Neurath MF (2006) Chromoendoscopy and other novel imaging techniques. Gastroenterol Clin North Am 35:605–619CrossRefPubMedGoogle Scholar
  6. 6.
    Taylor JC, Kendall CA, Stone N, Cook TA (2007) Optical adjuncts for enhanced colonoscopic diagnosis. Br J Surg 94:6–16CrossRefPubMedGoogle Scholar
  7. 7.
    Van Dam J (2003) Novel methods of enhanced endoscopic imaging. Gut 52(Suppl 4):12–16Google Scholar
  8. 8.
    Hurlstone DP, Sanders DS, Thomson M (2007) Detection and treatment of early flat and depressed colorectal cancer using high-magnification chromoscopic colonoscopy: a change in paradigm for Western endoscopists? Dig Dis Sci 52:1387–1393CrossRefPubMedGoogle Scholar
  9. 9.
    Moreaux J, Catala M (1987) Carcinoma of the colon—long-term survival and prognosis after surgical-treatment in a series of 798 patients. World J Surg 11:804–808CrossRefPubMedGoogle Scholar
  10. 10.
    Kiesslich R, Burg J, Vieth M, Gnaendiger J, Enders M, Delaney P, Polglase A, McLaren W, Janell D, Thomas S, Nafe B, Galle PR, Neurath MF (2004) Confocal laser endoscopy for diagnosing intraepithelial neoplasias and colorectal cancer in vivo. Gastroenterology 127:706–713CrossRefPubMedGoogle Scholar
  11. 11.
    Kiesslich R, Neurath MF (2005) Endoscopic detection of early lower gastrointestinal cancer. Best Pract Res Clin Gastroenterol 19:941–961CrossRefPubMedGoogle Scholar
  12. 12.
    Osdoit A, Lacombe F, Cavé C, Loiseau S, Peltier E (2007) To see the unseeable: confocal miniprobes for routine microscopic imaging during endoscopy In: Proc. SPIE 6432, 64320F 2007Google Scholar
  13. 13.
    Viellerobe B, Osdoit A, Cavé C, Lacombe F, Loiseau S, Abrat B (2006) Mauna Kea technologies’ F400 prototype: a new tool for in vivo microscopic imaging during endoscopy In: Proc SPIE 6082, 60820C, 2006Google Scholar
  14. 14.
    Hidovic-Rowe D, Claridge E (2005) Modelling and validation of spectral reflectance for the colon. Phys Med Biol 50:1071–1093CrossRefPubMedGoogle Scholar
  15. 15.
    Liu Y, Kim YL, Backman V (2005) Development of a bioengineered tissue model and its application in the investigation of the depth selectivity of polarization gating. Appl Opt 44:2288–2299CrossRefPubMedGoogle Scholar
  16. 16.
    Liu Q, Ramanujam N (2006) Sequential estimation of optical properties of a two-layered epithelial tissue model from depth-resolved ultraviolet-visible diffuse reflectance spectra. Appl Opt 45:4776–4790CrossRefPubMedGoogle Scholar
  17. 17.
    Wang A, Nammalvar V, Drezek R (2007) Experimental evaluation of angularly-variable fiber geometry for targeting depth-resolved reflectance from layered epithelial tissue phantoms In: Proc. SPIE Optical Fibers and Sensors for Medical Diagnostics and Treatment Applications VII 64330BGoogle Scholar
  18. 18.
    Arifler D, Guillaud M, Carraro A, Malpica A, Follen M, Richards-Kortum R (2003) Light scattering from normal and dysplastic cervical cells at different epithelial depths: finite-difference time-domain modeling with a perfectly matched layer boundary condition. J Biomed Opt 8:484–494CrossRefPubMedGoogle Scholar
  19. 19.
    Liu Q, Ramanujam N (2007) Scaling method for fast Monte Carlo simulation of diffuse reflectance spectra from multilayered turbid media. J Opt Soc Am a Opt Image Sci Vis 24:1011–1025CrossRefPubMedGoogle Scholar
  20. 20.
    Fockens P (2002) Future developments in endoscopic imaging. Best Pract Res Clin Gastroenterol 16:999–1012CrossRefPubMedGoogle Scholar
  21. 21.
    Hagblad J, Lindberg LG, Andersson AK, Bergstrand S, Lindgren M, Ek AC, Folke M, Linden M (2010) A technique based on laser Doppler flowmetry and photoplethysmography for simultaneously monitoring blood flow at different tissue depths. Med Biol Eng Comput 48:415–422CrossRefPubMedGoogle Scholar
  22. 22.
    Pandian PS, Kumaravel M, Singh M (2009) Multilayer imaging and compositional analysis of human male breast by laser reflectometry and Monte Carlo simulation. Med Biol Eng Comput 47:1197–1206CrossRefPubMedGoogle Scholar
  23. 23.
    Cohen FS, Taslidere E, Hari DS, Murthy S (2008) Stochastic decomposition method (SDM) for modeling the scattered signal reflected of mucosal tissues. J Biomed Opt 13:14–054039CrossRefGoogle Scholar
  24. 24.
    Cohen FS, Taslidere E, Hari DS (2006) Tissue characterization and detection of dysplasia using scattered light In: 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro. ISBI 2006, Arlington, Virginia, USA, April 6–9, 2006, pp 590–593Google Scholar
  25. 25.
    Taslidere E, Cohen FS (2006) Stochastic decomposition method for detection of epithelium dysplasia and inflammation using white light spectroscopy imaging,” In: 28th annual international conference of the IEEE Engineering in Medicine and Biology Society. EMBS ‘06, New York City, New York, USA, August 30-Sept. 3, 2006, pp 1956–1959Google Scholar
  26. 26.
    Zangaro RA, Silveira L, Manoharan R, Zonios G, Itzkan I, Dasari RR, Van Dam J, Feld MS (1996) Rapid multiexcitation fluorescence spectroscopy system for in vivo tissue diagnosis. Appl Opt 35:5211–5219CrossRefPubMedGoogle Scholar
  27. 27.
    Kudo S, Kashida H, Tamura T, Kogure E, Imai Y, Yamano H, Hart AR (2000) Colonoscopic diagnosis and management of nonpolypoid early colorectal cancer. World J Surg 24:1081–1090CrossRefPubMedGoogle Scholar
  28. 28.
    Matsui T, Yao T, Iwashita A (2000) Natural history of early colorectal cancer. World J Surg 24:1022–1028CrossRefPubMedGoogle Scholar
  29. 29.
    Wolber RA, Owen DA (1991) Flat adenomas of the colon. Hum Pathol 22:70–74CrossRefPubMedGoogle Scholar
  30. 30.
    Waye JD, Rex DK, Williams CB, (2003) Flat and Depressed Colorectal Neoplasia in the Western Hemisphere In: Raju GS, Pasricha PJ (eds) Colonoscopy: principles and practice, 1st edn. Malden, Mass, Blackwell, pp x, 655 pGoogle Scholar
  31. 31.
    Zonios GI, Cothren RM, Arendt JT, Wu J, VanDam J, Crawford JM, Manoharan R, Feld MS (1996) Morphological model of human colon tissue fluorescence. IEEE Trans Biomed Eng 43:113–122CrossRefPubMedGoogle Scholar
  32. 32.
    Fenoglio-Preiser CM, Hutter RV (1985) Colorectal polyps: pathologic diagnosis and clinical significance. CA Cancer J Clin 35:322–344CrossRefPubMedGoogle Scholar
  33. 33.
    Varma JR, Mills LR (1992) Colon polyps. J Fam Pract 35:194–200PubMedGoogle Scholar
  34. 34.
    Brookner CK, Follen M, Boiko I, Galvan J, Thomsen S, Malpica A, Suzuki S, Lotan R, Richards-Kortum R (2000) Autofluorescence patterns in short-term cultures of normal cervical tissue. Photochem Photobiol 71:730–736CrossRefPubMedGoogle Scholar
  35. 35.
    Huang ZW, Zheng W, Xie SS, Chen R, Zeng HS, McLean DI, Lui H (2004) Laser-induced autofluorescence microscopy of normal and tumor human colonic tissue. Int J Oncol 24:59–63PubMedGoogle Scholar
  36. 36.
    Marchesini R, Pignoli E, Tomatis S, Fumagalli S, Sichirollo AE, Dipalma S, Dalfante M, Spinelli P, Croce AC, Bottiroli G (1994) Ex-vivo optical-properties of human colon tissue. Lasers Surg Med 15:351–357CrossRefPubMedGoogle Scholar
  37. 37.
    Picinbono B (1993) Random signals and systems. Englewood Cliffs, Prentice HallGoogle Scholar
  38. 38.
    Porat B (1994) Digital processing of random signals: theory and methods. Englewood Cliffs, Prentice HallGoogle Scholar
  39. 39.
    Cohen FS, Georgiou G, Halpern EJ (1997) WOLD decomposition of the backscatter echo in ultrasound images of soft tissue organs. IEEE Trans Ultrason Ferroelectr Freq Control 44:460–472CrossRefPubMedGoogle Scholar
  40. 40.
    Desai UB (1986) Modelling and application of stochastic processes. Kluwer Academic Publishers, BostonGoogle Scholar
  41. 41.
    Papoulis A, Pillai SU (2002) Probability, random variables, and stochastic processes, 4th edn. McGraw-Hill, BostonGoogle Scholar
  42. 42.
    Ross SM (1996) Stochastic processes, 2nd edn. Wiley, New YorkGoogle Scholar
  43. 43.
    Georgiou G, Cohen FS (2001) Tissue characterization using the continuous wavelet transform Part I: Decomposition method. IEEE Trans Ultrason Ferroelectr Freq Control 48:355–363CrossRefPubMedGoogle Scholar
  44. 44.
    Taslidere E, Cohen FS, Georgiou G (2008) Classification of simulated hyperplastic stages in the breast ducts based on ultrasound RF echo. IEEE Trans Ultrason Ferroelectr Freq Control 55:50–63PubMedGoogle Scholar
  45. 45.
    Vitol EA, Kurzweg TP, Nabet B (2005) Using white-light spectroscopy for size determination of tissue phantoms In: Proc. SPIE Photonics North, Toronto, CanadaGoogle Scholar
  46. 46.
    Sambongi M, Igarashi M, Obi T, Yamaguchi M, Ohyama N, Kobayashi M, Sano Y, Yoshida S, Gono K (2002) Analysis of spectral reflectance using normalization method from endoscopic spectroscopy system. Opt Rev 9:238–243CrossRefGoogle Scholar

Copyright information

© International Federation for Medical and Biological Engineering 2010

Authors and Affiliations

  • Fernand S. Cohen
    • 1
  • Ezgi Taslidere
    • 1
  • Sreekant Murthy
    • 2
  1. 1.Department of Electrical and Computer EngineeringDrexel UniversityPhiladelphiaUSA
  2. 2.Division of Gastroenterology and Hepatology, College of MedicineDrexel UniversityPhiladelphiaUSA

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