Simple “Digital Phantom” for Testing Attenuation-Imaging Methods in Optical Coherence Tomography

Alexander A. Sovetsky; Alexander L. Matveyev; Lev A. Matveev; Peter A. Chizhov; Vladimir Y. Zaitsev

doi:10.18287/JBPE24.10.020302

Simple “Digital Phantom” for Testing Attenuation-Imaging Methods in Optical Coherence Tomography

Alexander A. Sovetsky
A.V. Gaponov-Grekhov Institute of Applied Physics of the Russian Academy of Sciences, Nizhny Novgorod, Russia

Alexander L. Matveyev
A.V. Gaponov-Grekhov Institute of Applied Physics of the Russian Academy of Sciences, Nizhny Novgorod, Russia

Lev A. Matveev
A.V. Gaponov-Grekhov Institute of Applied Physics of the Russian Academy of Sciences, Nizhny Novgorod, Russia

Peter A. Chizhov
A.V. Gaponov-Grekhov Institute of Applied Physics of the Russian Academy of Sciences, Nizhny Novgorod, Russia

Vladimir Y. Zaitsev (Login required)
A.V. Gaponov-Grekhov Institute of Applied Physics of the Russian Academy of Sciences, Nizhny Novgorod, Russia

Paper #9085 received 22 Mar 2024; revised manuscript received 10 Apr 2024; accepted for publication 11 Apr 2024; published online 26 Apr 2024.

DOI: 10.18287/JBPE24.10.020302

Abstract

The manuscript describes a simple but realistic and efficient method for generation of OCT scans with fairly correct accounting for optical signal attenuation dominated by scattering. The strong domination of scattering in the optical attenuation coefficient (OAC) is typical of OCT where the illuminating-beam wavelength is intentionally chosen in optical transparently windows with minimal absorption. At the same time the scattering-dominated OAC may strongly differ for various types/states of biological tissues, so that the diagnostic value of OCT examinations can be significantly increased due to spatially-resolved estimation of OAC. However, the results of OAC-reconstruction may be strongly degraded by the “speckle noise” intrinsic to OCT scans, various measurement noises, and some other factors. Verification of OAC-reconstruction accuracy in physical experiments is challenging since controllable variation in the parameters of physical phantoms and OCT systems is often difficult or even impossible. In view of this, realistic numerical simulations may open unprecedented possibilities for testing and comparison of various OAC methods in highly controllable and flexibly variable conditions. Here, we describe a method enabling generation of realistic “digital phantoms” and present instructive examples demonstrating their usefulness for testing OAC-reconstruction approaches.

Keywords

optical coherence tomography; OCT-scan formation modeling; speckle pattern; optical attenuation imaging

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References

1. R. A. Leitgeb, F. Placzek, E. A. Rank, L. Krainz, R. Haindl, Q. Li, M. Liu, M. Liu, A. Unterhuber, T. Schmoll, and W. Drexler, “Enhanced medical diagnosis for dOCTors: a perspective of optical coherence tomography,” Journal of Biomedical Optics 26(10), 100601 (2021).

2. A. Mariampillai, B. A. Standish, E. H. Moriyama, M. Khurana, N. R. Munce, M. K. K. Leung, J. Jiang, A. Cable, B. C. Wilson, I. A. Vitkin, and V. X. D. Yang, “Speckle variance detection of microvasculature using swept-source optical coherence tomography,” Optics Letters 33(13), 1530 (2008).

3. A. Zhang, Q. Zhang, C.-L. Chen, and R. K. Wang, “Methods and algorithms for optical coherence tomography-based angiography: a review and comparison,” Journal of Biomedical Optics 20(10), 100901 (2015).

4. A. Moiseev, S. Ksenofontov, M. Sirotkina, E. Kiseleva, M. Gorozhantseva, N. Shakhova, L. Matveev, V. Zaitsev, A. Matveyev, E. Zagaynova, V. Gelikonov, N. Gladkova, A. Vitkin, and G. Gelikonov, “Optical coherence tomography-based angiography device with real-time angiography B-scans visualization and hand-held probe for everyday clinical use,” Journal of Biophotonics 11(10), e201700292 (2018).

5. K. V. Larin, D. D. Sampson, “Optical coherence elastography – OCT at work in tissue biomechanics [Invited],” Biomedical Optics Express 8(2), 1172–1202 (2017).

6. V. Y. Zaitsev, A. L. Matveyev, L. A. Matveev, A. A. Sovetsky, M. S. Hepburn, A. Mowla, and B. F. Kennedy, “Strain and elasticity imaging in compression optical coherence elastography: The two-decade perspective and recent advances,” Journal of Biophotonics 14(2), e202000257 (2021).

7. M. A. Kirby, I. Pelivanov, S. Song, L. Ambrozinski, S. J. Yoon, L. Gao, D. Li, T. T. Shen, R. K. Wang, and M. O’Donnell, “Optical coherence elastography in ophthalmology,” Journal of Biomedical Optics 22(12), 121720 (2017).

8. D. Zhu, J. Wang, M. Marjanovic, E. J. Chaney, K. A. Cradock, A. M. Higham, Z. G. Liu, Z. Gao, and S. A. Boppart, “Differentiation of breast tissue types for surgical margin assessment using machine learning and polarization-sensitive optical coherence tomography,” Biomedical Optics Express 12(5), 3021 (2021).

9. M. Niemczyk, D. R. Iskander, “Statistical analysis of corneal OCT speckle: a non-parametric approach,” Biomedical Optics Express 12(10), 6407 (2021).

10. S. Chang, A. K. Bowden, “Review of methods and applications of attenuation coefficient measurements with optical coherence tomography,” Journal of Biomedical Optics 24(09), 090901 (2019).

11. P. Gong, M. Almasian, G. Van Soest, D. M. De Bruin, T. G. Van Leeuwen, D. D. Sampson, and D. J. Faber, “Parametric imaging of attenuation by optical coherence tomography: review of models, methods, and clinical translation,” Journal of Biomedical Optics 25(04), 040901 (2020).

12. A. A. Moiseev, K. A. Achkasova, E. B. Kiseleva, K. S. Yashin, A. L. Potapov, E. L. Bederina, S. S. Kuznetsov, E. P. Sherstnev, D. V. Shabanov, G. V. Gelikonov, Y. V. Ostrovskaya, and N. D. Gladkova, “Brain white matter morphological structure correlation with its optical properties estimated from optical coherence tomography (OCT) data,” Biomedical Optics Express 13(4), 2393 (2022).

13. V. Tuchin, D. Zhu, and E. Genina (Eds.), Handbook of tissue optical clearing: New prospects in optical imaging, 1st ed., CRC Press, Boca Raton, FL, USA (2022). ISBN: 978-1-032-11869-7.

14. E. A. Genina, “Tissue optical clearing: State of the art and prospects,” Diagnostics 12(7), 1534 (2022).

15. K. A. Vermeer, J. Mo, J. J. A. Weda, H. G. Lemij, and J. F. de Boer, “Depth-resolved model-based reconstruction of attenuation coefficients in optical coherence tomography,” Biomedical Optics Express 5(1), 322 (2014).

16. J. Liu, N. Ding, Y. Yu, X. Yuan, S. Luo, J. Luan, Y. Zhao, Y. Wang, and Z. Ma, “Optimized depth-resolved estimation to measure optical attenuation coefficients from optical coherence tomography and its application in cerebral damage determination,” Journal of Biomedical Optics 24(03), 035002 (2019).

17. A. Moiseev, E. Sherstnev, E. Kiseleva, K. Achkasova, A. Potapov, K. Yashin, M. Sirotkina, G. Gelikonov, V. Matkivsky, P. Shilyagin, S. Ksenofontov, E. Bederina, I. Medyanik, E. Zagaynova, and N. Gladkova, “Depth-resolved method for attenuation coefficient calculation from optical coherence tomography data for improved biological structure visualization,” Journal of Biophotonics 16(12), e202100392 (2023).

18. A. Weatherbee, M. Sugita, K. Bizheva, I. Popov, and A. Vitkin, “Probability density function formalism for optical coherence tomography signal analysis: a controlled phantom study,” Optics Letters 41(12), 2727–2730 (2016).

19. M. Szkulmowski, A. Szkulmowska, T. Bajraszewski, A. Kowalczyk, and M. Wojtkowski, “Flow velocity estimation using joint Spectral and Time domain Optical Coherence Tomography,” Optics Express 16(9), 6008–6025 (2008).

20. G. Lamouche, B. F. Kennedy, K. M. Kennedy, C.-E. Bisaillon, A. Curatolo, G. Campbell, V. Pazos, and D. D. Sampson, “Review of tissue simulating phantoms with controllable optical, mechanical and structural properties for use in optical coherence tomography,” Biomedical Optics Express 3(6), 1381–1398 (2012).

21. J. M. Schmitt, S. H. Xiang, and K. M. Yung, “Speckle in Optical Coherence Tomography,” Journal of Biomedical Optics 4(1), 95 (1999).

22. V. Y. Zaitsev, A. L. Matveyev, L. A. Matveev, G. V. Gelikonov, V. M. Gelikonov, and A. Vitkin, “Deformation-induced speckle-pattern evolution and feasibility of correlational speckle tracking in optical coherence elastography,” Journal of Biomedical Optics 20(7), 075006 (2015).

23. D. D. Duncan, S. J. Kirkpatrick, “The copula: a tool for simulating speckle dynamics,” Journal of the Optical Society of America A 25(1), 231–237 (2008).

24. M. Y. Kirillin, G. Farhat, E. A. Sergeeva, M. C. Kolios, and A. Vitkin, “Speckle statistics in OCT images: Monte Carlo simulations and experimental studies,” Optics Letters 39(12), 3472–3475 (2014).

25. C. M. Macdonald, P. R. T. Munro, “Approximate image synthesis in optical coherence tomography,” Biomedical Optics Express 12(6), 3323–3337 (2021).

26. A. L. Matveyev, L. A. Matveev, A. A. Moiseev, A. A. Sovetsky, G. V. Gelikonov, and V. Y. Zaitsev, “Semi-analytical full-wave model for simulations of scans in optical coherence tomography with accounting for beam focusing and the motion of scatterers,” Laser Physics Letters 16(8), 085601 (2019).

27. A. L. Matveyev, L. A. Matveev, A. A. Moiseev, A. A. Sovetsky, G. V. Gelikonov, and V. Y. Zaitsev, “Simulating scan formation in multimodal optical coherence tomography: angular-spectrum formulation based on ballistic scattering of arbitrary-form beams,” Biomedical Optics Express 12(12), 7599–7615 (2021).

28. V. Y. Zaitsev, L. A. Matveev, A. L. Matveyev, G. V. Gelikonov, and V. M. Gelikonov, “A model for simulating speckle-pattern evolution based on close to reality procedures used in spectral-domain OCT,” Laser Physics Letters 11(10), 105601 (2014).

29. A. A. Zykov, A. L. Matveyev, L. A. Matveev, A. A. Sovetsky, and V. Y. Zaitsev, “Flexible Computationally Efficient Platform for Simulating Scan Formation in Optical Coherence Tomography with Accounting for Arbitrary Motions of Scatterers,” Journal of Biomedical Photonics & Engineering 7(1), 010304 (2021).

30. R. Leitgeb, C. K. Hitzenberger, and A. F. Fercher, “Performance of Fourier domain vs. time domain optical coherence tomography,” Optics Express 11(8), 889–894 (2003).

31. V. V. Tuchin, “Tissue Optics and Photonics: Light-Tissue Interaction,” Journal of Biomedical Photonics & Engineering 1(2), 98–134 (2015).

32. F. Bergmann, F. Foschum, L. Marzel, and A. Kienle, “Ex Vivo Determination of Broadband Absorption and Effective Scattering Coefficients of Porcine Tissue,” Photonics 8(9), 365 (2021).

33. Y. Alexandrovskaya, O. Baum, A. Sovetsky, A. Matveyev, L. Matveev, E. Sobol, and V. Zaitsev, “Optical Coherence Elastography as a Tool for Studying Deformations in Biomaterials: Spatially-Resolved Osmotic Strain Dynamics in Cartilaginous Samples,” Materials 15(3), 904 (2022).

34. Y. M. Alexandrovskaya, E. M. Kasianenko, A. A. Sovetsky, A. L. Matveyev, and V. Y. Zaitsev, “Spatio-Temporal Dynamics of Diffusion-Associated Deformations of Biological Tissues and Polyacrylamide Gels Observed with Optical Coherence Elastography,” Materials 16(5), 2036 (2023).

35. E. V. Gubarkova, A. A. Sovetsky, V. Yu. Zaitsev, A. L. Matveyev, D. A. Vorontsov, M. A. Sirotkina, L. A. Matveev, A. A. Plekhanov, N. P. Pavlova, S. S. Kuznetsov, A. Yu. Vorontsov, E. V. Zagaynova, and N. D. Gladkova, “OCT-elastography-based optical biopsy for breast cancer delineation and express assessment of morphological/molecular subtypes,” Biomedical Optics Express 10(5), 2244–2263 (2019).

36. F. Zvietcovich, A. Nair, M. Singh, S. R. Aglyamov, M. D. Twa, and K. V. Larin, “In vivo assessment of corneal biomechanics under a localized cross-linking treatment using confocal air-coupled optical coherence elastography,” Biomedical Optics Express 13(5), 2644–2654 (2022).

37. A. A. Plekhanov, M. A. Sirotkina, A. A. Sovetsky, E. V. Gubarkova, S. S. Kuznetsov, A. L. Matveyev, L. A. Matveev, E. V. Zagaynova, N. D. Gladkova, and V. Y. Zaitsev, “Histological validation of in vivo assessment of cancer tissue inhomogeneity and automated morphological segmentation enabled by Optical Coherence Elastography,” Scientific Reports 10(1), 11781 (2020).

38. V. Demidov, A. Maeda, M. Sugita, V. Madge, S. Sadanand, C. Flueraru, and I. A. Vitkin, “Preclinical longitudinal imaging of tumor microvascular radiobiological response with functional optical coherence tomography,” Scientific Reports 8(1), 38 (2018).

39. M. A. Sirotkina, A. A. Moiseev, L. A. Matveev, V. Y. Zaitsev, V. V. Elagin, S. S. Kuznetsov, G. V. Gelikonov, S. Y. Ksenofontov, E. V. Zagaynova, F. I. Feldchtein, N. D. Gladkova, and A. Vitkin, “Accurate early prediction of tumour response to PDT using optical coherence angiography,” Scientific Reports 9(1), 6492 (2019).

40. V. Demidov, L. A. Matveev, O. Demidova, A. L. Matveyev, V. Y. Zaitsev, C. Flueraru, and I. A. Vitkin, “Analysis of low-scattering regions in optical coherence tomography: applications to neurography and lymphangiography,” Biomedical Optics Express 10(8), 4207–4219 (2019).

41. E. V. Gubarkova, A. A. Moiseev, E. B. Kiseleva, D. A. Vorontsov, S. S. Kuznetsov, A. Y. Vorontsov, G. V. Gelikonov, M. A. Sirotkina, and N. D. Gladkova, “Tissue optical properties estimation from cross-polarization OCT data for breast cancer margin assessment,” Laser Physics Letters 17(7), 075602 (2020).

42. K. A. Achkasova, A. A. Moiseev, K. S. Yashin, E. B. Kiseleva, E. L. Bederina, M. M. Loginova, I. A. Medyanik, G. V. Gelikonov, E. V. Zagaynova, and N. D. Gladkova, “Nondestructive label-free detection of peritumoral white matter damage using cross-polarization optical coherence tomography,” Frontiers in Oncology 13, 1133074 (2023).

43. A. A. Moiseev, M. A. Sirotkina, A. L. Potapov, L. A. Matveev, N. N. Vagapova, I. A. Kuznetsova, and N. D. Gladkova, “Lymph vessels visualization from optical coherence tomography data using depth-resolved attenuation coefficient calculation,” Journal of Biophotonics 14(9), e202100055 (2021).

44. P. Gong, S. Es’haghian, K.-A. Harms, A. Murray, S. Rea, F. M. Wood, D. D. Sampson, and R. A. McLaughlin, “In vivo label-free lymphangiography of cutaneous lymphatic vessels in human burn scars using optical coherence tomography,” Biomedical Optics Express 7(12), 4886–4898 (2016).

45. A. Potapov, L. Matveev, A. Moiseev, E. Sedova, M. Loginova, M. Karabut, I. Kuznetsova, V. Levchenko, E. Grebenkina, S. Gamayunov, S. Radenska-Lopovok, M. Sirotkina, and N. Gladkova, “Multimodal OCT Control for Early Histological Signs of Vulvar Lichen Sclerosus Recurrence after Systemic PDT: Pilot Study,” International Journal of Molecular Sciences 24(18), 13967 (2023).

46. V. Y. Zaitsev, L. A. Matveev, A. L. Matveyev, G. V. Gelikonov, and V. M. Gelikonov, “Elastographic mapping in optical coherence tomography using an unconventional approach based on correlation stability,” Journal of Biomedical Optics 19(2), 021107 (2014).

47. A. L. Matveyev, L. A. Matveev, A. A. Sovetsky, G. V. Gelikonov, A. A. Moiseev, and V. Y. Zaitsev, “Vector method for strain estimation in phase-sensitive optical coherence elastography,” Laser Physics Letters 15(6), 065603 (2018).

48. V. Y. Zaitsev, S. Y. Ksenofontov, A. A. Sovetsky, A. L. Matveyev, L. A. Matveev, A. A. Zykov, and G. V. Gelikonov, “Real-Time Strain and Elasticity Imaging in Phase-Sensitive Optical Coherence Elastography Using a Computationally Efficient Realization of the Vector Method,” Photonics 8(12), 527 (2021).

49. A. A. Zykov, A. L. Matveyev, L. A. Matveev, D. V. Shabanov, and V. Y. Zaitsev, “Novel Elastography-Inspired Approach to Angiographic Visualization in Optical Coherence Tomography,” Photonics 9(6), 401 (2022).