Archives of Acoustics, 48, 1, pp. 25–38, 2023
10.24425/aoa.2023.144263

Numerical Simulation of Breast Cancer in the Early Diagnosis with Actual Dimension and Characteristics Using Photoacoustic Tomography

Maryam AHANGAR DARBAND
Sahand University of Technology
Iran, Islamic Republic of

Esmaeil NAJAFI AGHDAM
http://fa.ee.sut.ac.ir/
Sahand University of Technology
Iran, Islamic Republic of

Arash GHARIBI
Shanxi Normal University
China

A numerical study and simulation of breast imaging in the early detection of tumors using the photoacoustic (PA) phenomenon are presented. There have been various reports on the simulation of the PA phenomenon in the breast, which are not in the real dimensions of the tissue. Furthermore, the different layers of the breast have not been considered. Therefore, it has not been possible to rely on the values and characteristics of the resulting data and to compare it with the actual state. Here, the real dimensions of the breast at three-dimensional and different constituent layers have been considered. After reviewing simulation methods and software for different stages of the PA phenomenon, a single suitable platform, which is commercially available finite element software (COMSOL), has been selected for simulating. The optical, thermal, elastic, and acoustic characteristics of different layers of breast and tumor at radiated laser wavelength (800 nm) were accurately calculated or obtained from a reliable source. Finally, by defining an array of 32 ultrasonic sensors on the breast cup at the defined arcs of the 2D slices, the PA waves can be collected and transmitted to MATLAB software to reconstruct the images. We can study the resulting PA wave and its changes in more detail using our scenarios.
Keywords: photoacoustic (PA); photoacoustic imaging (PAI); photoacoustic tomography; breast cancer; early diagnosis
Full Text: PDF
Copyright © The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0).

References

Ai M., Shu W., Salcudean T., Rohling R., Abolmaesumi P., Tang S. (2017), Design of high energy laser pulse delivery in a multimode fiber for photoacoustic tomography, Optics Express, 25(15): 17713–17726, doi: 10.1364/OE.25.017713.

Akhlaghi N., Pfefer T.J., Wear K.A., Garra B.S., Vogt W.C. (2019), Multidomain computational modeling of photoacoustic imaging: Verification, validation, and image quality prediction, Journal of Biomedical Optics, 24(12): 121910, doi: 10.1117/1.JBO.24.12.121910.

American Cancer Society (2019), Breast cancer facts & figures 2019–2020, American Cancer Society, Inc., https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/breast-cancer-facts-andfigures/breast-cancer-facts-and-figures-2019-2020.pdf.

Bengtson B.P., Glicksman C.A. (2015), The standardization of bra cup measurements: Redefining brasizing language, Clinics in Plastic Surgery, 42(4): 405–411, doi: 10.1016/j.cps.2015.06.002.

Bhatti S.N., Sridhar-Keralapura M. (2012), A novel breast software phantom for biomechanical modeling of elastography, Medical Physics, 39(4): 1748–1768, doi: 10.1118/1.3690467.

Boppart S.A., Luo W., Marks D.L., Singletary K.W. (2004), Optical coherence tomography: feasibility for basic research and image-guided surgery of breast cancer, Breast Cancer Research and Treatment, 84(2): 85–97, doi: 10.1023/B:BREA.0000018401.13609.54.

Cassidy J., Nouri A., Betz V., Lilge L. (2018), High-performance, robustly verified Monte Carlo simulation with FullMonte, Journal of Biomedical Optics, 23(8): 085001, doi: 10.1117/1.JBO.23.8.085001.

Corlu A. et al. (2007), Three-dimensional in vivo fluorescence diffuse optical tomography of breast cancer in humans, Optics Express, 15(11): 6696–6716, doi: 10.1364/OE.15.006696.

Dehghani H., Brooksby B.A., Pogue B.W., Paulsen K.D. (2005), Effects of refractive index on near-infrared tomography of the breast, Applied Optics, 44(10): 1870–1878, doi: 10.1364/AO.44.001870.

Dehghani H. et al. (2009), Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction, Communications in Numerical Methods in Engineering, 25(6): 711–732, doi: 10.1002/cnm.1162.

Dobrucki A.B., Opielinski K.J. (2000), Adaptation of image reconstruction algorithm for purposes of ultrasound transmission tomography (UTT), Archives of Acoustics, 25(4): 395–422.

Downing J. (2008), Effects of light absorption and scattering in water samples on OBS measurements, Campbell Scientific, Inc., pp. 1–4.

Gefen A., Dilmoney B. (2007), Mechanics of the normal woman’s breast, Technology and Health Care, 15(4): 259–271, doi: 10.3233/THC-2007-15404.

Grimal Q., Naïli S., Watzky A. (2005), A high-frequency lung injury mechanism in blunt thoracic impact, Journal of Biomechanics, 38(6): 1247–1254, doi: 10.1016/j.jbiomech.2004.06.010.

Hale G.M., Querry M.R. (1973), Optical constants of water in the 200-nm to 200-_m wavelength region, Applied Optics, 12(3): 555–563, doi: 10.1364/AO.12.000555.

Hammer C., Fanning A., Crowe J. (2008), Overview of breast cancer staging and surgical treatment options, Cleveland Clinic Journal of Medicine, 75: S10–S16, doi: 10.3949/ccjm.75.Suppl_1.S10.

Hasgall P.A. et al. (2018), IT’IS Database for thermal and electromagnetic parameters of biological tissues, Version 4.0, IT’IS Foundation, doi: 10.13099/VIP21000-04-0.

Jacques S.L. (2013), Optical properties of biological tissues: A review, Physics in Medicine & Biology, 58(11): R37, doi: 10.1088/0031-9155/58/11/R37.

Jacques S.L., Wang L. (1995), Monte Carlo modeling of light transport in tissues, [in:] Optical-Thermal Response of Laser-Irradiated Tissue, Welch A.J., van Gemert M. [Eds.], pp. 73–100, Springer, Boston, MA, doi: 10.1007/978-1-4757-6092-7_4.

Lan H., Duan T., Jiang D., Zhong H., Zhou M., Gao F. (2019), Dual-contrast nonlinear photoacoustic sensing and imaging based on single high-repetitionrate pulsed laser, [in:] IEEE Sensors Journal, 19(14): 5559–5565, doi: 10.1109/JSEN.2019.2902849.

Laufer J., Elwell C., Delpy D., Beard P. (2006), Absolute measurements of local chromophore concentrations using pulsed photoacoustic spectroscopy, [in:] Photons Plus Ultrasound: Imaging and Sensing 2006: The Seventh Conference on Biomedical Thermoacoustics, Optoacoustics, and Acousto-optics, Vol. 6086, pp. 398–405, doi: 10.1117/12.657372.

Li C., Duric N., Littrup P., Huang L. (2009), In vivo breast sound-speed imaging with ultrasound tomography, Ultrasound in Medicine & Biology, 35(10): 1615–1628, doi: 10.1016/j.ultrasmedbio.2009.05.011.

Li C., Wang L.V. (2009), Photoacoustic tomography and sensing in biomedicine, Physics in Medicine & Biology, 54(19): R59, doi: 10.1088/0031-9155/54/19/R01.

Lin L. et al. (2018), Single-breath-hold photoacoustic computed tomography of the breast, Nature communications, 9(1): 2352, doi: 10.1038/s41467-018-04576-z.

Lynch P.J., Jaffe C.C. (1987), Generated for multimedia teaching projects by the Yale University School of Medicine, Center for Advanced Instructional Media.

Metwally M.K. et al. (2014), Influence of optical fluence distribution on photoacoustic imaging, International Journal of Mathematical, Computational, Physical, Electrical and Computer Engineering, 8(8): 1108–1112.

Oraevsky A.A., Karabutov A.A., Savateeva E.V. (2001), Enhancement of optoacoustic tissue contrast with absorbing nanoparticles, [in:] Hybrid and Novel Imaging and New Optical Instrumentation for Biomedical Applications, Vol. 4434, pp. 60–69, doi: 10.1117/12.446693.

Pogorzelski S.J., Szurkowski J., Śliwiński A. (1999), Detection of micellar structures in oil-water-surfactant systems with a photoacoustic method, Archives of Acoustics, 24(3): 319–330.

Polyanskiy M.N. (2016), Refractive index database (access: 2020).

Ponikwicki N. et al. (2019), Photoacoustic method as a tool for analysis of concentration-dependent thermal effusivity in a mixture of methyl alcohol and water, Archives of Acoustics, 44(1): 153–160, doi: 10.24425/aoa.2019.126361.

Prahl S. (2017), Assorted Spectra (assess: 2020).

Silverman R.H. et al. (2010), High-resolution photoacoustic imaging of ocular tissues, Ultrasound in Medicine & Biology, 36(5): 733–742, doi: 10.1016/j.ultrasmedbio.2010.02.006.

Singh S., Repaka R. (2018), Numerical investigation of convective cooling in minimizing skin burns during radiofrequency ablation of breast tumor, Sādhanā, 43(90): 1–8, doi: 10.1007/s12046-018-0872-4.

Soltani, M., Rahpeima R., Kashkooli F.M. (2019), Breast cancer diagnosis with a microwave thermoacoustic imaging technique – a numerical approach, Medical & Biological Engineering & Computing, 57(7): 1497–1513, doi: 10.1007/s11517-019-01961-8.

Sowmiya C., Thittai A.K. (2017), Simulation of photoacoustic tomography (PAT) system in COMSOL and comparison of two popular reconstruction techniques, [in:] Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging, 10137: 435–445, doi: 10.1117/12.2254450.

Tasinkevych Y., Lewandowski M., Klimonda Z., Walczak M. (2018), Synthetic aperture cardiac imaging with reduced number of acquisition channels. A feasibility study, Archives of Acoustics, 43(3): 437–446, doi: 10.24425/123915.

Treeby B.E., Cox B.J., (2010), k-Wave: MATLAB toolbox for the simulation and reconstruction of photoacoustic wave fields, Journal of Biomedical Optics, 15(2): 021314, doi: 10.1117/1.3360308.

Wang L., Jacques S.L. (1992), Monte Carlo Modeling of Light Transport in Multi-Layered Tissues in Standard C., University of Texas, MD Anderson Cancer Center.

Wang L.V. [Ed.] (2017), Photoacoustic Imaging and Spectroscopy, CRC Press.

Wang L.V. (2004), Ultrasound-mediated biophotonic imaging: A review of acousto-optical tomography and photo-acoustic tomography, Disease Markers, 19(2–3): 123–138, doi: 10.1155/2004/478079.

Wang L.V. (2008), Prospects of photoacoustic tomography, Medical Physics, 35(12): 5758–5767, doi: 10.1118/1.3013698.

Wang Z., Ha S., Kim K. (2012), Evaluation of finite-element-based simulation model of photoacoustics in

biological tissues, [in:] Medical Imaging 2012: Ultrasonic Imaging, Tomography, and Therapy, 8320: 470–478, doi: 10.1117/12.912152.

Wilkie D.R. (1953), The coefficient of expansion of muscle, The Journal of Physiology, 119(4): 369–375, doi: 10.1113/jphysiol.1953.sp004852.

Zho Q., Ji X., Xing D. (2011), Full-field 3D photoacoustic imaging based on plane transducer array and spatial phase-controlled algorithm, Medical Physics, 38(3): 1561–1566, doi: 10.1118/1.3555036.

Zhutovsky S., Kovler K. (2015), Evaluation of the thermal expansion coefficient using non-destructive testing, [in:] Proceedings of 110th International Conference on Mechanics and Physics of Creep, Shrinkage, and Durability of Concrete and Concrete Structures, CONCREEP, 10: 1137–1146, doi: 10.1061/9780784479346.136.




DOI: 10.24425/aoa.2023.144263