Patient sociodemographic and disease characteristics
Variable
Total
Patients
3,337
Age (years)
54 ± 10
BMI (kg/m2)
28.15 ± 4.73
Underweight
13 (0.4%)
Normal
896 (26.9%)
Overweight
1,396 (41.8%)
Obesity
1,032 (30.9%)
Premenopausal
1,038 (31.1%)
Postmenopausal
2,299 (68.9%)
Age of menopause (years), n = 2,999
47 ± 5
Family history BC/OC
No
2,655 (79.6%)
Yes
682 (20.4%)
Breast pain
No
2,435 (73%)
Yes
902 (27%)
Activities and conditions that affect body temperature*
No
1,163 (34.9%)
Yes
2,174 (65.1%)
Breast density
A
194 (5.8%)
B
2,584 (77.4%)
C
476 (14.3%)
D
12 (0.4%)
N/A
76 (2.1%)
Histopathological test, n = 300
Benign
171 (57%)
Malignant
129 (43%)
BC grade, n = 129
I
9 (7%)
II
69 (53.5%)
III
36 (27.9%)
N/A
15 (11.6%)
Tumor size#, n = 129
T1
68 (52.7%)
T2
49 (38%)
T3
10 (7.8%
T4
2 (1.6%)
BMI: body mass index; OC: ovarian cancer; N/A: information not available; *: physical activity, drug and stimulant consumption, menstrual cycle phase; tumor size according to the American Cancer Society classification
Thanks are due to FUCAM A.C. for facilitating communication with patients and for those little details given in this research, especially to the Department of Radiology.
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: PASM, AHS, JAJA, LEHG, JAMG, and YGM report a relationship with Hearthcore SAPI de CV as associates, but declare to only have a scientific interest in this research. EMDCM reports a relationship with Hearthcore that includes non-financial support as a medical advisor. There are no further conflicts of interest to be declared.
Ethical approval
This research was conducted in accordance with the standards of the Research, Bioethics, and Biosafety Committee from FUCAM A.C. [PI 19-05], as well as with the 1964 Declaration of Helsinki and its later amendments.
Consent to participate
Informed consent to participate in the study was obtained from all participants.
Consent to publication
Informed consent to publication was obtained from relevant participants.
Availability of data and materials
The electronic patient record data used to support the findings of this research are restricted by FUCAM A.C. in order to protect patient’s privacy, also, the database of infrared images generated in this trial are property of Heathcore SAPI de CV. Requests for accessing the datasets should be directed to [Eva Ruvalcaba-Limon, evaruvalcaba@yahoo.com.mx] and [Pedro A. Sánchez-Méndez, pedro.sanchez@thermy.com.mx] if the researcher meets the criteria for access to confidential data.
Funding
This work was supported by the Social Responsibility Program of Avon Cosmetics S. de R.L. de C.V. [Cruzada Avon contra el Cáncer de Mama]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Meneses-García A, Ramírez T, Ruiz-Godoy L, Chiquete E, Mohar A.Cost of breast cancer treatment prior to the introduction of immune-based therapy in Mexico. Rev Med Inst Mex Seguro Soc. 2012;50:19–24. [PubMed]
Garg T, Bajaj S, Dayan MJ, Makary MS, Smirniotopoulos JB, Silk M, et al. Temporal and geospatial variations among the interventional radiology physician workforce in the United States. Clin Imaging. 2021;78:105–9. [DOI] [PubMed]
Yao X, Wei W, Li J, Wang L, Xu Z, Wan Y, et al. A comparison of mammography, ultrasonography, and far-infrared thermography with pathological results in screening and early diagnosis of breast cancer. Asian Biomed. 2014;8:11–9. [DOI]
Sella T, Sklair-Levy M, Cohen M, Rozin M, Shapiro-Feinberg M, Allweis TM, et al. A novel functional infrared imaging system coupled with multiparametric computerised analysis for risk assessment of breast cancer. Eur Radiol. 2012;23:1191–8. [DOI] [PubMed]
Keyserling JR, Ahlgren PD, Yu E, Belliveau N.Infrared imaging of the breast: initial reappraisal using high-resolution digital technology in 100 succesive cases of stage I and II breast cancer. Breast J. 1998;4:245–51. [DOI] [PubMed]
Carmeliet P, Jain RK.Angiogenesis in cancer and other diseases. Nature. 2000;407:249–57. [DOI] [PubMed]
Kandlikar SG, Perez-Raya I, Raghupathi PA, Gonzalez-Hernandez JL, Dabydeen D, Medeiros L, et al. Infrared imaging technology for breast cancer detection–current status, protocols and new directions. Int J Heat Mass Transf. 2017;108:2303–20. [DOI]
American College of Radiology. Breast imaging reporting and data system: BI-RADS Atlas. 5th ed. Reston, VA: American College of Radiology; 2013.
Antonini S, Kolarić D, Herceg Ž, Ferenčić Ž, Kuliš T, Borojević N, et al. Simplified description and interpretation of pathological thermography signs in malignant breast lesions. Period Biol. 2011;113:425–32.
Pedraza RS, Raad JE.Aspectos sobre diseño y tamaño de muestra en estudios de prueba diagnóstica. Revista de la Facultad de Medicina: Universidad Nacional de Colombia. 2001;49:175–80. Spanish.
Duffy S, Vulkan D, Cuckle H, Parmar D, Sheikh S, Smith E, et al. Annual mammographic screening to reduce breast cancer mortality in women from age 40 years: long-term follow-up of the UK Age RCT. Health Technol Assess. 2020;24:1–23. [DOI] [PMC]
Uscanga-Sánchez S, Torres-Mejía G, Ángeles-Llerenas A, Domínguez-Malpica R, Lazcano-Ponce E.Breast cancer screening process indicators in Mexico: a case study. Salud Publica Mex. 2014;56:528–37. Spanish. [PubMed]
Ulloa-Pérez E, Mohar-Betancourt A, Reynoso-Noverón N.Estimation of the cost-effectiveness of breast cancer screening using mammography in Mexico through a simulation. Rev Invest Clin. 2016;68:184–91. [PubMed]
Brandan ME, Navarro YV.Detección del cáncer de mama: estado de la mamografía en México. Cancerología. 2006;1:147–62. Spainish.
Parisky YR, Sardi A, Hamm R, Hughes K, Esserman L, Rust S, et al. Efficacy of computerized infrared imaging analysis to evaluate mammographically suspicious lesions. AJR Am J Roentgenol. 2003;180:263–9. [DOI] [PubMed]
Arora N, Martins D, Ruggerio D, Tousimis E, Swistel AJ, Osborne MP, et al. Effectiveness of a noninvasive digital infrared thermal imaging system in the detection of breast cancer. Am J Surg. 2008;196:523–6. [DOI] [PubMed]
Gautherie M.Thermobiological assessment of benign and malignant breast diseases. Am J Obstet Gynecol. 1983;147:861–9. [DOI] [PubMed]
Villarreal-Garza C, Aguila C, Magallanes-Hoyos MC, Mohar A, Bargalló E, Meneses A, et al. Breast cancer in young women in Latin America: an unmet, growing burden. Oncologist. 2013;18:26–34. [DOI] [PubMed]
Sechopoulos I, Mann RM.Standalone artificial intelligence - the future of breast cancer screening?Breast. 2020;49:254–60. [DOI] [PubMed] [PMC]
Gogoi UR, Bhowmlk MK, Bhattacharjee D, Ghosh AK.Singular value based characterization and analysis of thermal patches for early breast abnormality detection. Australas Phys Eng Sci Med. 2018;41:861–79. [DOI] [PubMed]
Zuluaga-Gomez J, Al Masry Z, Benaggoune K, Meraghni S, Zerhouni N.A CNN-based methodology for breast cancer diagnosis using thermal images. Comput Methods Biomech Biomed Eng Imaging Vis. 2020;9:131–45. [DOI]
Visual Lab DMR [Internet]. Niterói: Database of mastologic images; c2021 [cited 2021 Nov 28]. Available from: https://visual.ic.uff.br/dmi/
Bhowmik MK, Gogoi UR, Majumdar G, Bhattacharjee D, Datta D, Ghosh AK.Designing of ground-truth-annotated DBT-TU-JU breast thermogram database toward early abnormality prediction. IEEE J Biomed Health Inform. 2018;22:1238–49. [DOI] [PubMed]
Singh D, Singh AK.Role of image thermography in early breast cancer detection - past, present and future. Comput Methods Programs Biomed. 2020;183:105074. [DOI] [PubMed]
Hakim A, Awale RN.Thermal imaging - an emerging modality for breast cancer detection: a comprehensive review. J Med Syst. 2020;44:136. [DOI] [PubMed]
Rassiwala M, Mathur P, Mathur R, Farid K, Shukla S, Gupta PK, et al. Evaluation of digital infra-red imaging as an adjunctive screening method for breast carcinoma: a pilot study. Int J Surg. 2014;12:1439–43. [DOI] [PubMed]
Yamashita R, Nishio M, Do RKG, Togashi K.Convolutional neural networks: an overview and application in radiology. Insights Imaging. 2018;9:611–29. [DOI] [PubMed] [PMC]
