0
Research Papers

Generation and Thermal Simulation of a Digital Model of the Female Breast in Prone Position

[+] Author and Article Information
Jose-Luis Gonzalez-Hernandez

Department of Mechanical Engineering,
Rochester Institute of Technology,
76 Lomb Memorial Drive,
Rochester, NY 14623
e-mail: jxg4140@rit.edu

Satish G. Kandlikar

Department of Mechanical Engineering,
Rochester Institute of Technology,
76 Lomb Memorial Drive,
Rochester, NY 14623
e-mail: sgkeme@rit.edu

Donnette Dabydeen

ASME Fellow
Department of Radiology,
Rochester General Hospital,
1425 Portland Avenue,
Rochester, NY 14621
e-mail: Donnette.Dabydeen@rochesterregional.org

Lori Medeiros

Rochester General Breast Center,
1425 Portland Avenue,
Rochester, NY 14621
e-mail: Lori.Medeiros@rochesterregional.org

Pradyumna Phatak

Department of Medicine and Lipson
Cancer Institute,
Rochester General Hospital,
1425 Portland Avenue,
Rochester, NY 14621
e-mail: Pradyumna.Phatak@rochesterregional.org

1Corresponding author.

Manuscript received March 23, 2018; final manuscript received September 6, 2018; published online October 1, 2018. Editor: Ahmed Al-Jumaily.

ASME J of Medical Diagnostics 1(4), 041006 (Oct 01, 2018) (8 pages) Paper No: JESMDT-18-1018; doi: 10.1115/1.4041421 History: Received March 23, 2018; Revised September 06, 2018

Infrared (IR) breast thermography has been associated with the early detection of breast cancer (BC). However, findings in previous studies have been inconclusive. The upright position of subjects during imaging introduces errors in interpretation, because it blocks the optical access in the inframammary fold region and alters the temperature due to contact between breast and chest wall. These errors can be avoided by imaging breasts in prone position. Although the numerical simulations provide insight into thermal characteristics of the female breast with a tumor, most simulations in the past have used cubical and hemispherical breast models. We hypothesize that a breast model with the actual breast shape will provide true thermal characteristics that are useful in tumor detection. A digital breast model in prone position is developed to generate the surface temperature profiles for breasts with tumors. The digital breast model is generated from sequential magnetic resonance imaging (MRI) images and simulations are performed using finite volume method employing Pennes bioheat equation. We investigated the effect of varying the tumor metabolic activity on the surface temperature profile. We compared the surface temperature profile for various tumor metabolic activities with a case without tumor. The resulting surface temperature rise near the location of the tumor was between 0.665 and 1.023 °C, detectable using modern IR cameras. This is the first time that numerical simulations are conducted in a model with the actual breast shape in prone position to study the surface temperature changes induced by BC.

FIGURES IN THIS ARTICLE
<>
Copyright © 2018 by ASME
Your Session has timed out. Please sign back in to continue.

References

Siegel, R. L. , Miller, K. D. , and Jemal, A. , 2016, “ Cancer Statistics, 2016,” Ca Cancer J. Clin., 66(1), pp. 7–30. [CrossRef] [PubMed]
Howlader, N. , Noone, A. M. , Krapcho, M. , Neyman, N. , Aminou, R. , Altekruse, S. F. , and Mariotto, A. , 2013, “SEER Cancer Statistics Review, 1975-2009 (Vintage 2009 Populations),” National Cancer Institute. Bethesda, MD, accessed Sept. 20, 2018, https://seer.cancer.gov/archive/csr/1975_2009_pops09/ results_merged/sect_04_breast.pdf
Mary, B. B. , Harris, R. , and Fletcher, W. S. , 1999, “Does This Patient Have Breast Cancer?: The Screening Clinical Breast Examination: Should it be Done? How?,” JAMA., 282(13), pp. 1270–1280.
Brain, K. , Norman, P. , Gray, J. , and Mansel, R. , 1999, “Anxiety and Adherence to Breast Self-Examination in Women With Family History of Breast Cancer,” Psychosom. Med., 61(2), pp. 181–187.
Nelson, H. D. , Tyne, K. , Naik, A. , Bougatsos, C. , Chan, B. , Nygren, P. , and Humphrey, L. , 2009, “Screening for Breast Cancer: Systematic Evidence Review Update for the US Preventive Services Task Force,” U.S. Preventive Services Task Force Evidence Syntheses, formerly Systematic Evidence Reviews. Agency for Healthcare Research and Quality (US), Rockville, MD.
Narod, S. A. , Lubinski, J. , Ghadirian, P. , Lynch, H. T. , Moller, P. , Foulkes, W. D. , Rosen, B. , Kim-Sing, C. , Isaacs, C. , Domcheck, S. , and Sun, P. , 2006, “ Screening Mammography and Risk of Breast Cancer in BRCA1 and BRCA2 Mutation Carriers: A Case-Control Study,” Lancet Oncol., 7(5), pp. 402–406. [CrossRef] [PubMed]
Friedewald, S. M. , Rafferty, E. A. , Rose, S. L. , Durand, M. A. , Plecha, D. M. , Greenberg, J. S. , Hayes, M. K. , Copit, D. S. , Carlson, K. L. , Cink, T. M. , Barke, L. D. , Greer, L. N. , Miller, D. P. , and Conant, E. F. , 2014, “ Breast Cancer Screening Using Tomosynthesis in Combination With Digital Mammography,” JAMA, 311(24), pp. 2499–2507. [CrossRef] [PubMed]
Kuhl, C. K. , Schrading, S. , Leutner, C. C. , Morakkabati-Spitz, N. , Wardelmann, E. , Fimmers, R. , Kuhn, W. , and Schild, H. H. , 2005, “ Mammography, Breast Ultrasound, and Magnetic Resonance Imaging for Surveillance of Women at High Familial Risk for Breast Cancer,” J. Clin. Oncol., 23(33), pp. 8469–8476. [CrossRef] [PubMed]
Lahiri, B. B. , Bagavathiappan, S. , Jayakumar, T. , and Philip, J. , 2012, “ Medical Applications of Infrared Thermography: A Review,” Infrared Phys. Technol., 55(4), pp. 221–235. [CrossRef]
Watmough, D. J. , and Oliver, R. , 1969, “ Wavelength Dependence of Skin Emissivity,” Phys. Med. Biol., 14(2), p. 201. [CrossRef] [PubMed]
Bergman, T. L. , Incropera, F. P. , DeWitt, D. P. , and Lavine, A. S. , 2011, Fundamentals of Heat and Mass Transfer, Wiley, Hoboken, NJ.
Yahara, T. , Koga, T. , Yoshida, S. , Nakagawa, S. , Deguchi, H. , and Shirouzu, K. , 2016, “ Relationship Between Microvessel Density and Thermographic Hot Areas in Breast Cancer,” Surg. Today, 33(4), pp. 243–248.
Gautherie, M. , 1983, “ Thermobiological Assessment of Benign and Malignant Breast Diseases,” Am. J. Obstet. Gynecol., 147(8), pp. 861–869. [CrossRef] [PubMed]
Guidi, A. J. , and Schnitt, S. J. , 1996, “ Angiogenesis in Preinvasive Lesions of the Breast,” Breast J., 2(6), pp. 364–369. [CrossRef]
Gautherie, M. , and Gros, C. M. , 1980, “ Breast Thermography and Cancer Risk Prediction,” Cancer, 45(1), pp. 51–56. [CrossRef] [PubMed]
Kandlikar, S. G. , Perez-Raya, I. , Raghupathi, P. A. , Gonzalez-Hernandez, J. L. , Dabydeen, D. , Medeiros, L. , and Phatak, P. , 2017, “ Infrared Imaging Technology for Breast Cancer Detection—Current Status, Protocols and New Directions,” Int. J. Heat Mass Transfer, 108(Part B), pp. 2303–2320. [CrossRef]
Kennedy, D. A. , Lee, T. , and Seely, D. , 2009, “ A Comparative Review of Thermography as a Breast Cancer Screening Technique,” Integr. Cancer Ther., 8(1), pp. 9–16. [CrossRef] [PubMed]
Bezerra, L. A. , Oliveira, M. M. , Rolim, T. L. , Conci, A. , Santos, F. G. S. , Lyra, P. R. M. , and Lima, R. C. F. , 2013, “ Estimation of Breast Tumor Thermal Properties Using Infrared Images,” Signal Process., 93(10), pp. 2851–2863. [CrossRef]
Pennes, H. H. , 1998, “ Analysis of Tissue and Arterial Blood Temperatures in the Resting Human Forearm,” J. Appl. Physiol., 85(1), pp. 5–34. [CrossRef] [PubMed]
Mital, M. , and Pidaparti, R. M. , 2008, “ Breast Tumor Simulation and Parameters Estimation Using Evolutionary Algorithms,” Modell. Simul. Eng., 2008, p. 6.
Hatwar, R. , and Herman, C. , 2017, “ Inverse Method for Quantitative Characterisation of Breast Tumours From Surface Temperature Data,” Int. J. Hyperthermia, 33(7), pp. 741–757. [PubMed]
Das, K. , and Mishra, S. C. , 2013, “ Estimation of Tumor Characteristics in a Breast Tissue With Known Skin Surface Temperature,” J. Therm. Biol., 38(6), pp. 311–317. [CrossRef]
Amri, A. , Pulko, S. H. , and Wilkinson, A. J. , 2016, “ Potentialities of Steady-State and Transient Thermography in Breast Tumour Depth Detection: A Numerical Study,” Comput. Methods Programs Biomed., 123, pp. 68–80. [CrossRef] [PubMed]
Osman, M. M. , and Afify, E. M. , 1984, “ Thermal Modeling of the Normal Woman's Breast,” ASME J. Biomech. Eng., 106(2), pp. 123–130. [CrossRef]
Osman, M. M. , and Afify, E. M. , 1988, “ Thermal Modeling of the Malignant Woman's Breast,” ASME J. Biomech. Eng., 110(4), pp. 269–276. [CrossRef]
Sudharsan, N. M. , Ng, E. Y. K. , and Teh, S. L. , 1999, “ Surface Temperature Distribution of a Breast With and Without Tumour,” Comput. Methods Biomech. Biomed. Eng., 2(3), pp. 187–199. [CrossRef]
Sudharsan, N. M. , and Ng, E. Y. K. , 2000, “ Parametric Optimization for Tumour Identification: Bioheat Equation Using ANOVA and the Taguchi Method,” Proc. Inst. Mech. Eng., Part H, 214(5), pp. 505–512. [CrossRef]
González, F. J. , 2007, “ Thermal Simulation of Breast Tumors,” Rev. Mex. Física, 53(4), pp. 323–326.
Sudharsan, N. M. , and Ng, E. Y. K. , 2001, “ Numerical Computation as a Tool to Aid Thermographic Interpretation,” J. Med. Eng. Technol., 25(2), pp. 53–60. [CrossRef] [PubMed]
Ng, E.-K. , and Sudharsan, N. M. , 2001, “ Effect of Blood Flow, Tumour and Cold Stress in a Female Breast: A Novel Time-Accurate Computer Simulation,” Proc. Inst. Mech. Eng., Part H, 215(4), pp. 393–404. [CrossRef]
Jiang, L. , Zhan, W. , and Loew, M. , 2008, “ Combined Thermal and Elastic Modeling of the Normal and Tumorous Breast,” Proc. SPIE, 6916, p. 69161E.
Jiang, L. , Zhan, W. , and Loew, M. H. , 2011, “ Modeling Static and Dynamic Thermography of the Human Breast Under Elastic Deformation,” Phys. Med. Biol., 56(1), p. 187. [CrossRef] [PubMed]
Canny, J. , 1986, “ A Computational Approach to Edge Detection,” IEEE Trans. Pattern Anal. Mach. Intell., PAMI-8(6), pp. 679–698. [CrossRef]
Lorensen, W. E. , and Cline, H. E. , 1987, “ Marching Cubes: A High Resolution 3D Surface Construction Algorithm,” 14th Annual Conference on Computer Graphics and Interactive Techniques, New York, pp. 163–169.
Hess, R. , 2007, The Essential Blender: Guide to 3D Creation With the Open Source Suite Blender, No Starch Press, San Francisco, CA.
Versteeg, H. K. , and Malalasekera, W. , An Introduction to Computational Fluid Dynamics—The Finite Volume Method, Pearson Education Limited, London, UK.
Gautherie, M. , 1980, “ Thermopathology of Breast Cancer: Measurement and Analysis of In Vivo Temperature and Blood Flow,” Ann. N. Y. Acad. Sci., 335(1), pp. 383–415. [CrossRef] [PubMed]
Francis, S. V. , Sasikala, M. , Bhavani Bharathi, G. , and Jaipurkar, S. D. , 2014, “ Breast Cancer Detection in Rotational Thermography Images Using Texture Features,” Infrared Phys. Technol., 67(Suppl. C), pp. 490–496. [CrossRef]
Duck, F. A. , 2013, Physical Properties of Tissues: A Comprehensive Reference Book, Academic Press, Amsterdam, The Netherlands.
Ng, E. Y.-K. , 2009, “ A Review of Thermography as Promising Non-Invasive Detection Modality for Breast Tumor,” Int. J. Therm. Sci., 48(5), pp. 849–859. [CrossRef]

Figures

Grahic Jump Location
Fig. 1

Approach to generate breast geometry

Grahic Jump Location
Fig. 2

Steps required to generate breast geometry in prone position

Grahic Jump Location
Fig. 3

Computational domain with the actual breast shape

Grahic Jump Location
Fig. 4

Validation of the UDF with clinical data [37] using a hemispherical breast model

Grahic Jump Location
Fig. 5

Surface temperature distribution for six cases with different tumor metabolic activities

Grahic Jump Location
Fig. 6

Surface temperature profiles along centerline of tumor

Grahic Jump Location
Fig. 7

Temperature distribution on a vertical plane passing though the tumor center

Tables

Errata

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In