Review on Present-day Breast Cancer Detection Techniques
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Abstract
Breast cancer remains a prevalent health complication among the female population. Early and reliable detection in an individual is necessary for effective treatment. Thus, R&D into techniques for detection of breast cancer continues to the present. Non-invasive techniques include tactile examinations, electromagnetic scanning and checks for chemical markers. Invasive techniques include biopsies that extract tissue and liquid samples. These techniques have limitations and setbacks that are being addressed with supplementary or complementary techniques. Like the pre-existing techniques, these techniques also rely on comparison of data between control samples and afflicted patients to measure their reliability. Therefore, R&D efforts towards detection of breast cancer have resulted in incremental improvements on established methodologies.
[Manuscript received: 25 January 2024 | Accepted: 13 March 2024 | Published: : 30 April 2024]
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References
R. Hong, and B. Xu, “Breast cancer: an up-to-date review and future perspectives,” Cancer Communications, vol. 42, no. 10, pp. 913-936, 2022. DOI: 10.1002/cac2.12358
N. Azamjah, Y. Soltan-Zadeh and F. Zayeri, “Global Trend of Breast Cancer Mortality Rate: A 25-Year Study,” Asian Pacific Journal of Cancer Prevention, vol. 20, no. 7, pp. 2015-2020, 2019. DOI: 10.31557/APJCP.2019.20.7.2015
O. Ginsburg, C.H. Yip, A. Brooks, A. Cabanes, M. Caleffi, J. Dunstan Y., B. Gyawali, V. McCormack, M.M.L. de Anderson, R. Mehrotra, A. Mohar, R. Murillo, L. E. Pace, E. D. Paskett, A. Romanoff, A. F. Rositch, J. Scheel, M. Schneidman, K. Unger-Saldana, V. Vanderpuye, T.Y. Wu, S. Yuma, A. Dvaladze, C. Duggan, and B. O. Anderson, “Breast cancer early detection: a phased approach to implementation,” Cancer, vol. 126, no. 10, pp. 2379-2393, 2021. DOI: 10.1002/cncr.32887
T. Amir, M.P. Hogan, S. Jacobs, V. Sevilimedu, J. Sung and M.S. Jochelson, “Comparison of False-Positive Versus True-Positive Findings on Contrast-Enhanced Digital Mammography,” American Journal of Roentgenology, vol. 218, no. 5, pp. 797-809, 2022. DOI: 10.2214/AJR.21.26847
J.S. Brown, S.R. Amend, R.H. Austin, R. A. Gatenby, E.U. Hammarlund and K.J. Pienta, “Updating the Definition of Cancer,” Molecular Cancer Research, vol. 21, no. 11, pp. 1142-1147, 2023. DOI: 10.1158/1541-7786.MCR-23-0411
L. Tabar, P.B. Dean, F.L. Tucker, A.M.F. Yen, S.L. Chen, G.H.H. Jen, J. W. Wang, R.A. Smith, S.W. Duffy, and T.H. Chen, “A new approach to breast cancer terminology based on the anatomic site of tumour origin: The importance of radiologic imaging biomarkers,” European Journal of Radiology, vol. 149, no. 110189, pp. 1-21, 2022. DOI: 10.1016/j.ejrad.2022.110189
M. Zubair, S. Wang and N. Ali, “Advanced Approaches to Breast Cancer Classification and Diagnosis,” Frontiers in Pharmacology, vol. 11, no. 632079, 2021. DOI: 10.3389/fphar.2020.632079
M.M. Pippin and T. Boyd, “Breast Self-Examination,” StatPearls [Online]. StatPearls Publishing, 2023. PMID: 33351405
R.H. Udoh, M. Ansu-Mensah, M. Tahiru, V. Bawontuo and D. Kuupiel, “Mapping evidence on women’s knowledge and practice of breast self-examination in sub-Saharan Africa: a scoping review protocol,” Systematic Reviews, vol. 9, no. 2, 2020. DOI: 10.1186/s13643-019-1254-7
Y. Yang, J. Yu, A. Liu, J. Tian, L. Guo, D. Huo, P. Zhao, W. Ji, and B. Luo, “Self-detection remains a primary means of breast cancer detection in Beijing, China,” Translational Breast Cancer Research, vol. 4, no. 27, 2023. DOI: 10.21037/tbcr-22-2
M. Abubakar, S. Fan, E. A. Bowles, L. Widemann, M. A. Duggan, R.M. Pfeiffer, R.T. Falk, S. Lawrence, K. Richert-Boe, A.G. Glass, T.M. Kimes, J.D. Figueroa, T.E. Rohan, and G.L. Gierach, “Relation of Quantitative Histologic and Radiologic Breast Tissue Composition Metrics with Invasive Breast Cancer Risk,” JNCI Cancer Spectrum, vol. 5, no. 3, 2021. DOI: 10.1093/jncics/pkab015
M.S. Al Reshan, S. Amin, M.A. Zeb, A. Sulaiman, H. Alshahrani, A.T. Azar, and A. Shaikh, “Enhancing Breast Cancer Detection and Classification Using Advanced Multi-Model Features and Ensemble Machine Learning Techniques,” vol. 13, no. 10, pp. 2093, 2023. DOI: 10.3390/life13102093
S. Lukasiewicz, M. Czeczelewski, A. Forma, J. Baj, R. Sitarz and A. Stanislawek, “Breast Cancer—Epidemiology, Risk Factors, Classification, Prognostic Markers, and Current Treatment Strategies—An Updated Review,” Cancers (Basel), vol. 13, no. 17, pp. 4287, 2021. DOI: 10.3390/cancers13174287
S. Idrees, S. Mayilvaganan, S. Mishra, G. Chand, A. Mishra, and G. Agarwal, “What makes women receptive to breast self-examination, animation, or simulation? – a comparative study,” Annals of Medicine & Surgery, vol. 85, no. 9, pp. 4228-4233, 2023. DOI: 10.1097/MS9.0000000000000917
S. Hooshmand, W.M. Reed, M.E. Suleiman, and P.C. Brennan, “A review of screening mammography: The benefits and radiation risks put into perspective,” Journal of Medical Imaging and Radiation Sciences, vol. 53, no. 1, pp. 147-158, 2022. DOI: 10.1016/j.jmir.2021.12.002
M. Cai, “A Novel Method for Diagnosis of Breast Cancer Tumors Based on Random Forest,” Journal of Biosciences and Medicines, vol. 11, pp. 252-259, 2023. DOI: 10.4236/jbm.2023.114018
A. Raza, N. Ullah, J.A. Khan, M. Assam, A. Guzzo and H. Aljuaid, “A Novel Deep Learning Model for Breast Cancer Detection Using Ultrasound Images,” Applied Sciences, vol. 13, no. 4, pp. 2082, 2023. DOI: 10.3390/app13042082
H. Zhou, H. Chen, C. Cheng, X. Wu, Y. Ma, J. Han, D. Li, G.H. Lim, W.M. Rozen, N. Ishii, P.G. Roy, and Q. Wang, “A quality evaluation of the clinical practice guidelines on breast cancer using the RIGHT checklist,” Annals of Translational Medicine, vol. 9, no. 14, pp. 1174, 2021. DOI: 10.21037/atm-21-2884
A. Bhushan, A. Gonsalves and J.U. Menon, “Current State of Breast Cancer Diagnosis, Treatment, and Theranostics,” Pharmaceutics, vol. 13, no. 5, pp. 723, 2021. DOI: 10.3390/pharmaceutics13050723
A.A.A. Halim, A.M. Andrew, M.N.M. Yasin, M.A.A. Rahman, M. Jusoh, V. Veeraperumal, H.A. Rahim, U. Illahi, M.K.A, Karim, and E. Scavino, “Existing and Emerging Breast Cancer Detection Technologies and Its Challenges: A Review,” Applied Sciences, vol. 11, no. 22, pp. 10753, 2021. DOI: 10.3390/app112210753
K. Cho, S. Tyldesley, C. Speers, B.P. Lane, K.A. Gelmon and C. Wilson, “The utilization and impact of core needle biopsy diagnosis on breast cancer outcomes in British Columbia,” British Columbia Medical Journal, vol. 56, no. 4, pp. 183-190, 2014.
N. Huang, L. Chen, J. He and Q.D. Nguyen, “The Efficacy of Clinical Breast Exams and Breast Self-Exams in Detecting Malignancy or Positive Ultrasound Findings,” Cureus, vol. 14, no. 2, e22464, 2022. DOI: 10.7759/cureus.22464
C.R. Baxter, T.A. Crittenden & N.R. Dean, “Self-reported breast size, exercise habits and BREAST-Q data – an international cross-sectional study of community runners,” JPRAS Open, vol. 37, pp. 92-101, 2023. DOI: 10.1016/j.jpra.2023.06.013
L. Nicosia, G. Gnocchi, I. Gorini, M. Venturini, F. Fontana, F. Pesapane, I. Abiuso, A.C. Bozzini, M. Pizzamiglio, A. Latronico, F. Abbate, L. Meneghetti, O. Battaglia, G. Pellegrino, and E. Cassano, “History of Mammography: Analysis of Breast Imaging Diagnostic Achievements over the Last Century,” Healthcare (Basel), vol. 11, no. 11, pp. 1596, 2023. DOI: 10.3390/healthcare11111596
S.D. Maria, S. Vedantham & P. Vaz, “X-ray dosimetry in breast cancer screening: 2D and 3D mammography,” European Journal of Radiology, vol. 151, no. 110278, 2023. DOI: 10.1016/j.ejrad.2022.110278
L. Choridah, A.V. Icanervilia, A.A. Rengganis, J. At Thobari, M.J. Postma, and A.D.I. van Asselt, “Comparing the performance of three modalities of breast cancer screening within a combined programme targeting at-risk women in Indonesia: An implementation study,” vol. 18, no. 1, 2023. DOI: 10.1080/17441692.2023.2284370
M. Nu Nu Htay, M. Donnelly, D. Schliemann, S.Y. Loh, M. Dahlui, S. Somasundaram, N.S. Binti Ibrahim Tamin, and T.T. Su, “Breast Cancer Screening in Malaysia: A Policy Review,” Asian Pacific Journal of Cancer Prevention, vol. 22, no. 6, pp. 1685–1693, 2021. DOI: 10.31557/APJCP.2021.22.6.1685
E.K.J. Pauwels, N. Foray & M.H. Bourguignon, “Breast Cancer Induced by X-Ray Mammography Screening? A Review Based on Recent Understanding of Low-Dose Radiobiology,” Medical Principles and Practice, vol. 25, no. 2, pp. 101-109, 2016. DOI: 10.1159/000442442
O. Catalano, R. Fusco, F.D. Muzio, I. Simonetti, P. Palumbo, F. Bruno, A. Borgheresi, A. Agostini, M. Gabelloni, C. Varelli, A. Barile, A. Giovagnoni, N. Gandolfo, V. Miele & V. Granata, “Recent Advances in Ultrasound Breast Imaging: From Industry to Clinical Practice,” Diagnostics (Basel), vol. 13, no. 5, pp. 980, 2023. DOI: 10.3390/diagnostics13050980
E. Patel, M.R. Clench, A. West, P.S. Marshall, N. Marshall, and S. Francese, “Alternative Surfactants for Improved Efficiency of In Situ Tryptic Proteolysis of Fingermarks,” Journal of the American Society for Mass Spectrometry, vol. 26, no. 6, pp. 862-872, 2015. DOI: 10.1007/s13361-015-1140-z
C. Russo, L. Wyld, M.D.C. Aubreu, C.S. Bury, C. Heaton, L.M. Cole, and S. Francese, “Non-invasive screening of breast cancer from fingertip smears - a proof of concept study,” Scientific Reports, vol. 13, no. 1868, 2023. DOI: 10.1038/s41598-023-29036-7
M. Koopaie, S. Kolahdooz, M. Fatahzadeh and S. Manifar, “Salivary biomarkers in breast cancer diagnosis: A systematic review and diagnostic meta analysis,” Cancer Medicine, vol. 11, no. 13, pp. 2644-2661, 2022. DOI: 10.1002/cam4.4640
V.K. Sarhadi, and G. Armengol, “Molecular Biomarkers in Cancer,” Biomolecules, vol. 12, no. 8, pp. 1021, 2022. DOI: 10.3390/biom12081021
Z. He, Z. Chen, M. Tan, S. Elingarami, Y. Liu, T. Li, Y. Deng, N. He, S. Li, J. Fu & W. Li, “A review on methods for diagnosis of breast cancer cells and tissues,” Cell Proliferation, vol. 53, no. 7, e12822. DOI: 10.1111/cpr.12822
C.H. Barrios, “Global challenges in breast cancer detection and treatment,” The Breast, vol. 62, no. 1, pp. S3-S6, 2022. DOI: 10.1016/j.breast.2022.02.003
H.D. Nelson, E.S. O’Meara, and K. Kerlikowske, “Factors Associated with Rates of False-Positive and False-Negative Results from Digital Mammography Screening: An Analysis of Registry Data,” Annals of Internal Medicine, vol. 164, no. 4, pp. 226-235. DOI: 10.7326/M15-0971
C.K.S. Park, T. Trumpour, A. Aziz, J.S. Bax, D. Tessier, L. Gardi & A. Fenster, “Cost-effective, portable, patient-dedicated three-dimensional automated breast ultrasound for point-of-care breast cancer screening,” Scientific Reports, vol. 13, no. 14390, 2023. DOI: 10.1038/s41598-023-41424-7
Y. Shen, F.E. Shamout, J.R. Oliver, J. Witowski, K. Kannan, J. Park, N. Wu, C. Huddleston, S. Wolfson, A. Millet, R. Ehrenpreis, D. Awal, C. Tyma, N. Samreen, Y. Gao, C. Chhor, S. Gandhi, C. Lee, S. Kumari-Subaiya, C. Leonard, R. Mohammed, C. Moczulski, J. Altabet, J. Babb, A. Lewin, B. Reig, L. Moy, L. Heacock and K.J. Geras, “Artificial intelligence system reduces false-positive findings in the interpretation of breast ultrasound exams,” Nature Communications, vol. 12, no. 5645, 2021. DOI: 10.1038/s41467-021-26023-2
Y. Wen, X. Li, F. Zeng, J. Lei, and S. Chen, “Application of Medical Record Quality Control System Based on Artificial Intelligence,” Journal of Sichuan University (Medical Sciences), vol. 54, no. 6, pp. 1263-1268, 2023. DOI: 10.12182/20231160206
J.D. Lewis, A. Groszkiewicz, L. Hefelfinger, A. Doherty, A. Foringer, E. Shaughnessy, A. Heelan and A.L. Brown, “Clinically significant bleeding complications of percutaneous breast biopsy: 10-year analysis and a proposed management algorithm,” Clinical Imaging, vol. 104, no. 110017, 2023. DOI: 10.1016/j.clinimag.2023.110017
Y.C. Kong, N. Bhoo-Pathy, M. O’Rorke, S. Subramaniam, N. Bhoo-Pathy, T. Nanthini, M.H. See, S. Jamaris, K.H. Teoh, A. Bustam, L.M. Looi, N.A. Taib, and C.H. Yip, “The association between methods of biopsy and survival following breast cancer: A hospital registry-based cohort study,” Medicine, vol. 99, no. 6, pp. e19093, 2020. DOI: 10.1097/MD.0000000000019093
I. Teberian, T. Kaufman, J. Shames, V.M. Rao, L. Liao, and D.C. Levin, “Trends in the Use of Percutaneous Versus Open Surgical Breast Biopsy: An Update,” Journal of the American College of Radiology, vol. 17, no. 8, pp. 1004-1010, 2020. DOI: 10.1016/j.jacr.2020.02.015
M. Park, D. Kim, S. Ko, A. Kim, K. Mo, and H. Yoon, “Breast Cancer Metastasis: Mechanisms and Therapeutic Implications,” International Journal of Molecular Sciences, vol. 23, no. 12, pp. 6806, 2022. DOI: 10.3390/ijms23126806
J.M. Chang, J.W.T. Leung, L. Moy, S.M. Ha, and W.K. Moon, “Axillary Nodal Evaluation in Breast Cancer: State of the Art,” Radiology, vol. 295, no. 3, pp. 500-515, 2020. DOI: 10.1148/radiol.2020192534
H. Isozaki, Y. Yamamoto, S. Murakami, S. Matsumoto, and T. Takama, “Impact of the surgical modality for axillary lymph node dissection on postoperative drainage and seroma formation after total mastectomy,” Patient Safety in Surgery, vol. 13, no. 20, pp. 1-9, 2019. DOI: 10.1186/s13037-019-0199-z
F. Parvin and M. Al Mehedi Hasan, “A Comparative Study of Different Types of Convolutional Neural Networks for Breast Cancer Histopathological Image Classification,” 2020 IEEE Region 10 Symposium, TENSYMP 2020, pp. 945–948, Jun. 2020. DOI: 10.1109/TENSYMP50017.2020.9230787.
N. M. a/l Loorutu, H. Yazid and K.S. Abdul Rahman, “Prostate Cancer Classification Based on Histopathological Images,” International Journal on Robotics, Automation and Sciences, vol. 5, no. 2, pp. 43-53, 2023. DOI: 10.33093/ijoras.2023.5.2.5
E.R.M. van Haaren, I.G.M. Poodt, M.A.S. van Weezelenburg, J. van Bastelaar, A. Janssen, B. de Vries, M.B.I. Lobbes, L.H. Bouwman, and Y.L.J. Vissers, “Impact of analysis of the sentinel lymph node by one-step nucleic acid amplification (OSNA) compared to conventional histopathology on axillary and systemic treatment: data from the Dutch nationwide cohort of breast cancer patients,” Breast Cancer Research and Treatment, vol. 202, pp. 245-255, 2023.
A. Khalid, A. Mehmood, A. Alabrah, B.F. Alkhamees, F. Amin, H. Al-Salman, and G.S. Choi, “Breast Cancer Detection and Prevention Using Machine Learning,” Diagnostics, vol. 13, no. 19, 2023. DOI: 10.3390/diagnostics13193113
F.F. Ting, Y.J. Tan, and K.S. Sim, “Convolutional neural network improvement for breast cancer classification,” Expert Systems with Applications, vol. 120, pp. 103-115, 2019. DOI: 10.1016/j.eswa.2018.11.008
K.S. Sim, S.S. Chong, C.P. Tso, M.E. Nia, A.K. Chong, and S.F. Abbas, “Computerized database management system for breast cancer patients,” Springerplus, vol. 3, no. 268, 2014. DOI: 10.1186/2193-1801-3-268
S. Goudreau, L.J. Grimm, A. Srinivasan, J. Net, R. Yang, V. Dialani, and K. Dodelzon, “Bleeding Complications After Breast Core-needle Biopsy—An Approach to Managing Patients on Antithrombotic Therapy,” Journal of Breast Imaging, vol. 4, no. 3, pp. 241-252, 2022. DOI: 10.1093/jbi/wbac020
J. Pollard, H. Rose, R. Mullen, and N. Abbott, “Breast Core Biopsy Information and Consent: Do we Prepare or do we Scare?,” Journal of Patient Experience, vol. 8, 2021. DOI: 10.1177/23743735211049658
D.S. Seah, J.P. Leone, T.H. Openshaw, S.M. Scott, N. Tayob, J. Hu, R.I. Lederman, E.S. Frank, J.J. Sohl, Z.K. Stadler, T.K. Erick, S.G. Silverman, J.M. Peppercorn, E.P. Winer, S.E. Come, and N.U. Lin, “Perceptions of patients with early stage breast cancer toward research biopsies,” Cancer, vol. 127, no. 8, pp. 1208-1219, 2021. DOI: 10.1002/cncr.33371
A. Bayle, F. Peyraud, L. Belcaid, M. Brunet, M. Aldea, R. Clodion, P. Dubos, D. Vasseur, C. Nicotra, A. Geraud, M. Sakkal, L. Cerbone, F. Blanc-Durand, F. Mosele, P. Martin Romano, M. Ngo Camus, I. Soubeyran, E. Khalifa, M. Alame, L. Blouin, D. Dinart, C. Bellera, A. Hollebecque, S. Ponce, Y. Loriot, B. Besse, L. Lacroix, E. Rouleau, F. Barlesi, F. Andre, and A. Italiano, “Liquid versus tissue biopsy for detecting actionable alterations according to the ESMO Scale for Clinical Actionability of molecular Targets in patients with advanced cancer: a study from the French National Center for Precision Medicine (PRISM),” Annals of Oncology, vol. 33, no. 12, pp. 1328-1331, 2022. DOI: 10.1016/j.annonc.2022.08.089
S. Park, S. Ahn, J.Y. Kim, J. Kim, H.J. Han, D. Hwang, J. Park, H.S. Park, S. Park, G.M. Kim, J. Sohn, J. Jeong, Y.U. Song, H. Lee, and S.I. Kim, “Blood Test for Breast Cancer Screening through the Detection of Tumor-Associated Circulating Transcripts,” International Journal of Molecular Sciences, vol. 23, no. 16, pp. 9140, 2022. DOI: 10.3390/ijms23169140
P. Bhat-Nakshatri, B. Kumar, E. Simpson, K.K. Ludwig, M.L. Cox, H. Gao, Y. Liu, and H. Nakshatri, “Breast cancer cell detection and characterization from breast milk-derived cells,” Cancer Research, vol. 80, no. 21, pp. 4828-4839, 2020. DOI: 10.1158/0008-5472.CAN-20-1030
M.A. Naji, S. El Filali, K. Aarika, E.H. Benlahmar, R. Ait Abdelouhahid, and O. Debauche, “Machine Learning Algorithms for Breast Cancer Prediction and Diagnosis,” vol. 191, pp. 487-492, 2021. DOI: 10.1016/j.procs.2021.07.062
Y. Jin, W. Junren, J. Jingwen, S. Yajing, C. Xi, and Q. Ke, “Research on the Construction and Application of Breast Cancer-Specific Database System Based on Full Data Lifecycle,” Frontiers in Public Health, vol. 9, no. 712827, 2021. DOI: 10.3389/fpubh.2021.712827