Abstract
Early screening of breast cancer using new medical imaging technologies can reduce the number of deaths among women. This paper presents a description of the state of the art of the most propagated types of carcinoma in women, as well as the concept and process of cancer cell growth, and the application of more recent imaging modalities for early breast cancer detection. We also present the contribution of our research laboratory to the development of a new embedded thermography system based on innovative technologies.
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pr292_E.pdf. https://www.iarc.who.int/wp-content/uploads/2020/12/pr292_E.pdf
Sung, H., et al.: Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA A Cancer J. Clin. 71, 209–249 (2021). https://doi.org/10.3322/caac.21660
Duncan, W., Kerr, G.R.: The curability of breast cancer. BMJ 2, 781–783 (1976). https://doi.org/10.1136/bmj.2.6039.781
Fisher, C.M., Rabinovitch, R.A.: Breast cancer. In: Nieder, C. et Gaspar, L.E. (éd.) Decision Tools for Radiation Oncology. pp. 77‑89. Berlin, Heidelberg (2013)
Brierley, J., Gospodarowicz, M.K., Wittekind, C. (éd.): TNM classification of malignant tumours. John Wiley & Sons, Inc, Chichester, West Sussex, Hoboken, NJ, UK (2017)
Giuliano, A.E., et al.: Breast cancer-major changes in the American joint committee on cancer eighth edition cancer staging manual: updates to the AJCC Breast TNM staging system: the 8th Edition. CA: A Can. J. Clin. 67, 290–303 (2017). https://doi.org/10.3322/caac.21393
mammary-gland. https://www.britannica.com/science/mammary-gland#/media/1/360922/119198
Moore, K.L., Dalley, A.F., Agur, A.M.R., Milaire, J.: Moore, anatomie médicale: aspects fondamentaux et applications cliniques. De Boeck, Louvain-la-Neuve, Paris (2017)
PMH0072594. https://www.ncbi.nlm.nih.gov/pubmedhealth/PMH0072594/
Ellis, I.O., Galea, M., Broughton, N., Locker, A., Blamey, R.W., Elston, C.W.: Pathological prognostic factors in breast cancer. II. Histological type. Relationship with survival in a large study with long-term follow-up. Histopathology. 20, 479‑489 (2007). https://doi.org/10.1111/j.1365-2559.1992.tb01032.x
El Fouhi, M., Benider, A., Kagambega Zoewendbem, A.G., Mesfioui, A.: Profil épidémiologique et anatomopathologique du cancer de sein au CHU Ibn Rochd, Casablanca. Pan Afr. Med. J. 37 (2020). https://doi.org/10.11604/pamj.2020.37.41.21336
Aznag, F.Z., et al.: Epidemiological and Biological Profiling of Breast Cancer in Southern Morocco. Integr. J. Med. Sci. 5 (2018). https://doi.org/10.15342/ijms.v5ir.240
Riggio, A.I., Varley, K.E., Welm, A.L.: The lingering mysteries of metastatic recurrence in breast cancer. Br. J. Cancer 124, 13–26 (2021). https://doi.org/10.1038/s41416-020-01161-4
Bhushan, A., Gonsalves, A., Menon, J.U.: Current state of breast cancer diagnosis, treatment, and theranostics. Pharmaceutics 13, 723 (2021). https://doi.org/10.3390/pharmaceutics13050723
Egan, R.L.: Experience with mammography in a tumor institution: evaluation of 1,000 studies. Radiology 75, 894–900 (1960). https://doi.org/10.1148/75.6.894
Muller, S.: Full-field digital mammography designed as a complete system. Eur. J. Radiol. 31, 25–34 (1999). https://doi.org/10.1016/S0720-048X(99)00066-2
Bick, U., Diekmann, F.: Digital mammography: what do we and what don’t we know? Eur. Radiol. 17, 1931–1942 (2007). https://doi.org/10.1007/s00330-007-0586-1
Feig, S.: Radiation risk from mammography: is it clinically significant? Am. J. Roentgenol. 143, 469–475 (1984). https://doi.org/10.2214/ajr.143.3.469
Wallyn, J., Anton, N., Akram, S., Vandamme, T.F.: Biomedical imaging: principles, technologies, clinical aspects, contrast agents, limitations and future trends in nanomedicines. Pharm. Res. 36, 78 (2019). https://doi.org/10.1007/s11095-019-2608-5
Tan, T., Quek, C., Ng, G., Ng, E.: A novel cognitive interpretation of breast cancer thermography with complementary learning fuzzy neural memory structure. Expert Syst. Appl. 33, 652–666 (2007). https://doi.org/10.1016/j.eswa.2006.06.012
Baxter, G.C., Graves, M.J., Gilbert, F.J., Patterson, A.J.: A meta-analysis of the diagnostic performance of diffusion MRI for breast lesion characterization. Radiology 291, 632–641 (2019). https://doi.org/10.1148/radiol.2019182510
Kuhl, C.K., et al.: Mammography, breast ultrasound, and magnetic resonance imaging for surveillance of women at high familial risk for breast cancer. JCO. 23, 8469–8476 (2005). https://doi.org/10.1200/JCO.2004.00.4960
Lee, S.H., et al.: Correlation between high resolution dynamic MR features and prognostic factors in breast cancer. Korean J. Radiol. 9, 10 (2008). https://doi.org/10.3348/kjr.2008.9.1.10
Choi, E.J., Choi, H., Choi, S.A., Youk, J.H.: Dynamic contrast-enhanced breast magnetic resonance imaging for the prediction of early and late recurrences in breast cancer. Medicine 95, e5330 (2016). https://doi.org/10.1097/MD.0000000000005330
Cai, H., Liu, L., Peng, Y., Wu, Y., Li, L.: Diagnostic assessment by dynamic contrast-enhanced and diffusion-weighted magnetic resonance in differentiation of breast lesions under different imaging protocols. BMC Cancer 14, 366 (2014). https://doi.org/10.1186/1471-2407-14-366
Tao, W., Hu, C., Bai, G., Zhu, Y., Zhu, Y.: Correlation between the dynamic contrast-enhanced MRI features and prognostic factors in breast cancer: a retrospective case-control study. Medicine 97, e11530 (2018). https://doi.org/10.1097/MD.0000000000011530
Petrillo, A., et al.: Digital breast tomosynthesis and contrast-enhanced dual-energy digital mammography alone and in combination compared to 2D digital synthetized mammography and MR imaging in breast cancer detection and classification. Breast J. 26, 860–872 (2020). https://doi.org/10.1111/tbj.13739
Schelfout, K., et al.: Contrast-enhanced MR imaging of breast lesions and effect on treatment. Eur. J. Surg. Oncol. (EJSO). 30, 501–507 (2004). https://doi.org/10.1016/j.ejso.2004.02.003
Zhang, Y., et al.: The role of contrast-enhanced MR mammography for determining candidates for breast conservation surgery. Breast Cancer 9, 231–239 (2002). https://doi.org/10.1007/BF02967595
Glaser, K.J., Manduca, A., Ehman, R.L.: Review of MR elastography applications and recent developments. J. Magn. Reson. Imaging 36, 757–774 (2012). https://doi.org/10.1002/jmri.23597
Patel, B.K., et al.: MR elastography of the breast: evolution of technique, case examples, and future directions. Clin. Breast Cancer 21, e102–e111 (2021). https://doi.org/10.1016/j.clbc.2020.08.005
Hawley, J.R., Kalra, P., Mo, X., Raterman, B., Yee, L.D., Kolipaka, A.: Quantification of breast stiffness using MR elastography at 3 tesla with a soft sternal driver: a reproducibility study. J. Magn. Reson. Imaging 45, 1379–1384 (2017). https://doi.org/10.1002/jmri.25511
McKnight, A.L., Kugel, J.L., Rossman, P.J., Manduca, A., Hartmann, L.C., Ehman, R.L.: MR elastography of breast cancer: preliminary results. Am. J. Roentgenol. 178, 1411–1417 (2002). https://doi.org/10.2214/ajr.178.6.1781411
Lorenzen, J., et al.: MR elastography of the breast: preliminary clinical results. Rofo Fortschr Geb Rontgenstr Neuen Bildgeb Verfahr. 174, 830–834 (2002). https://doi.org/10.1055/s-2002-32690
Bickel, H., et al.: Quantitative apparent diffusion coefficient as a noninvasive imaging biomarker for the differentiation of invasive breast cancer and ductal carcinoma in situ. Invest. Radiol. 50, 95–100 (2015). https://doi.org/10.1097/RLI.0000000000000104
Ding, J.-R., Wang, D.-N., Pan, J.-L.: Apparent diffusion coefficient value of diffusion-weighted imaging for differential diagnosis of ductal carcinoma in situ and infiltrating ductal carcinoma. J. Can. Res. Ther. 12, 744 (2016). https://doi.org/10.4103/0973-1482.154093
Pereira, N.P., et al.: Diffusion-weighted magnetic resonance imaging of patients with breast cancer following neoadjuvant chemotherapy provides early prediction of pathological response – a prospective study. Sci. Rep. 9, 16372 (2019). https://doi.org/10.1038/s41598-019-52785-3
Bolan, P.J., et al.: In vivo quantification of choline compounds in the breast with1H MR spectroscopy. Magn. Reson. Med. 50, 1134–1143 (2003). https://doi.org/10.1002/mrm.10654
Jagannathan, N.R., et al.: Evaluation of total choline from in-vivo volume localized proton MR spectroscopy and its response to neoadjuvant chemotherapy in locally advanced breast cancer. Br. J. Cancer 84, 1016–1022 (2001). https://doi.org/10.1054/bjoc.2000.1711
Podo, F., et al.: Abnormal choline phospholipid metabolism in breast and ovary cancer: molecular bases for noninvasive imaging approaches. CMIR. 3, 123–137 (2007). https://doi.org/10.2174/157340507780619160
Tozaki, M., Fukuma, E.: 1 H MR spectroscopy and diffusion-weighted imaging of the breast: are they useful tools for characterizing breast lesions before biopsy? Am. J. Roentgenol. 193, 840–849 (2009). https://doi.org/10.2214/AJR.08.2128
Stanwell, P., Mountford, C.: In vivo proton MR spectroscopy of the breast. RadioGraphics. 27, S253–S266 (2007). https://doi.org/10.1148/rg.27si075519
Fardanesh, R., Marino, M.A., Avendano, D., Leithner, D., Pinker, K., Thakur, S.B.: Proton MR spectroscopy in the breast: technical innovations and clinical applications. J. Magn. Reson. Imaging 50, 1033–1046 (2019). https://doi.org/10.1002/jmri.26700
Kadoya, T., Aogi, K., Kiyoto, S., Masumoto, N., Sugawara, Y., Okada, M.: Role of maximum standardized uptake value in fluorodeoxyglucose positron emission tomography/computed tomography predicts malignancy grade and prognosis of operable breast cancer: a multi-institute study. Breast Cancer Res. Treat. 141, 269–275 (2013). https://doi.org/10.1007/s10549-013-2687-7
Lavayssière, R., Cabée, A.-E., Filmont, J.-E.: Positron emission tomography (PET) and breast cancer in clinical practice. Eur. J. Radiol. 69, 50–58 (2009). https://doi.org/10.1016/j.ejrad.2008.07.039
Narayanan, D., Berg, W.A.: Dedicated breast gamma camera imaging and breast PET. PET Clinics. 13, 363–381 (2018). https://doi.org/10.1016/j.cpet.2018.02.008
Hsu, D.F.C., Freese, D.L., Levin, C.S.: Breast-dedicated radionuclide imaging systems. J. Nucl. Med. 57, 40S-45S (2016). https://doi.org/10.2967/jnumed.115.157883
Liu, H., Zhan, H., Sun, D.: Comparison of 99mTc-MIBI scintigraphy, ultrasound, and mammography for the diagnosis of BI-RADS 4 category lesions. BMC Cancer 20, 463 (2020). https://doi.org/10.1186/s12885-020-06938-7
Gong, Z., Williams, M.B.: Comparison of breast specific gamma imaging and molecular breast tomosynthesis in breast cancer detection: evaluation in phantoms: Comparison of BSGI and MBT in cancer detection. Med. Phys. 42, 4250–4259 (2015). https://doi.org/10.1118/1.4922398
Surti, S.: Radionuclide methods and instrumentation for breast cancer detection and diagnosis. Semin. Nucl. Med. 43, 271–280 (2013). https://doi.org/10.1053/j.semnuclmed.2013.03.003
Brem, R.F., Ruda, R.C., Yang, J.L., Coffey, C.M., Rapelyea, J.A.: Breast-specific γ-imaging for the detection of mammographically occult breast cancer in women at increased risk. J. Nucl. Med. 57, 678–684 (2016). https://doi.org/10.2967/jnumed.115.168385
Urbano, N., Scimeca, M., Tancredi, V., Bonanno, E., Schillaci, O.: 99mTC-sestamibi breast imaging: Current status, new ideas and future perspectives. Semin. Cancer Biol. 84, 302–309 (2022). https://doi.org/10.1016/j.semcancer.2020.01.007
Liu, H., Zhan, H., Sun, D., Zhang, Y.: Comparison of BSGI, MRI, mammography, and ultrasound for the diagnosis of breast lesions and their correlations with specific molecular subtypes in Chinese women. BMC Med. Imaging 20, 98 (2020). https://doi.org/10.1186/s12880-020-00497-w
Kaplan, S.S.: Automated whole breast ultrasound. Radiol. Clin. North Am. 52, 539–546 (2014). https://doi.org/10.1016/j.rcl.2014.01.002
Candelaria, R., Fornage, B.D.: Second-look us examination of MR-detected breast lesions. J. Clin. Ultrasound 39, 115–121 (2011). https://doi.org/10.1002/jcu.20784
Siu, A.L.: On behalf of the U.S. Preventive services task force: screening for breast cancer: U.S. preventive services task force recommendation statement. Ann Intern Med. 164, 279 (2016). https://doi.org/10.7326/M15-2886
Morales-Cervantes, A., et al.: An automated method for the evaluation of breast cancer using infrared thermography. EXCLI J. 17:Doc989; ISSN 1611–2156 (2018). https://doi.org/10.17179/EXCLI2018-1735
Kennedy, D.A., Lee, T., Seely, D.: A comparative review of thermography as a breast cancer screening technique. Integr. Cancer Ther. 8, 9–16 (2009). https://doi.org/10.1177/1534735408326171
Hakim, A., Awale, R.N.: Thermal imaging - an emerging modality for breast cancer detection: a comprehensive review. J. Med. Syst. 44, 136 (2020). https://doi.org/10.1007/s10916-020-01581-y
Santana, M.A.: Breast cancer diagnosis based on mammary thermography and extreme learning machines. Res. Biomed. Eng. 34, 45‑53 (2018). https://doi.org/10.1590/2446-4740.05217
Bahramiabarghouei, H., Porter, E., Santorelli, A., Gosselin, B., Popovic, M., Rusch, L.A.: Flexible 16 antenna array for microwave breast cancer detection. IEEE Trans. Biomed. Eng. 62, 2516–2525 (2015). https://doi.org/10.1109/TBME.2015.2434956
Wang, F., Arslan, T., Wang, G.: Breast cancer detection with microwave imaging system using wearable conformal antenna arrays. In: 2017 IEEE International Conference on Imaging Systems and Techniques (IST), pp. 1‑6. IEEE, Beijing (2017)
Porter, E., Bahrami, H., Santorelli, A., Gosselin, B., Rusch, L.A., Popovic, M.: A wearable microwave antenna array for time-domain breast tumor screening. IEEE Trans. Med. Imaging 35, 1501–1509 (2016). https://doi.org/10.1109/TMI.2016.2518489
Preece, A.W., Craddock, I., Shere, M., Jones, L., Winton, H.L.: MARIA M4: clinical evaluation of a prototype ultrawideband radar scanner for breast cancer detection. J. Med. Imag. 3, 033502 (2016). https://doi.org/10.1117/1.JMI.3.3.033502
Duijm, L., Guit, G., Zaat, J., Koomen, A., Willebrand, D.: Sensitivity, specificity and predictive values of breast imaging in the detection of cancer. Br. J. Cancer 76, 377–381 (1997). https://doi.org/10.1038/bjc.1997.393
Elouerghi, A., Bellarbi, L., Khomsi, Z., Jbari, A., Errachid, A., Yaakoubi, N.: A flexible wearable thermography system based on bioheat microsensors network for early breast cancer detection: IoT technology. J. Electr. Comput. Eng. 2022, 1–13 (2022). https://doi.org/10.1155/2022/5921691
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Elouerghi, A., Khomsi, Z., Bellarbi, L. (2024). A Review of Recent Medical Imaging Modalities for Breast Cancer Detection: Active and Passive Method. In: Ezziyyani, M., Kacprzyk, J., Balas, V.E. (eds) International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD’2023). AI2SD 2023. Lecture Notes in Networks and Systems, vol 904. Springer, Cham. https://doi.org/10.1007/978-3-031-52388-5_27
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