ArticleMedical & biological engineering & computing2016
Thermal distribution analysis of three-dimensional tumor-embedded breast models with different breast density compositions.
Article in Medical & biological engineering & computing, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 40 citations in OpenAlex.
- Advances in breast cancer diagnosis: a comprehensive review of imaging, biosensors, and emerging wearable technologies.Frontiers in oncology · 2025Review
- Experimental measurement of local high temperature at the surface of gold nanorods using doped ZnGaNanoscale advances · 2021Article
- Plasmonic Nanocomposite Implants for Interstitial Thermotherapy: Experimental and Computational Analysis.Materials (Basel, Switzerland) · 2021Article
- Mathematical Modeling of Breast Tumor Destruction Using Fast Heating during Radiofrequency Ablation.Materials (Basel, Switzerland) · 2019Article
- A novel image processing procedure for thermographic image analysis.Medical & biological engineering & computing · 2018Article
- An interval prototype classifier based on a parameterized distance applied to breast thermographic images.Medical & biological engineering & computing · 2017Article
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer is the most common cancer among women globally, and the number of young women diagnosed with this disease is gradually increasing over the years. Mammography is the current gold-standard technique although it is known to be less sensitive in detecting tumors in woman with dense breast tissue. Detecting an early-stage tumor in young women is very crucial for better survival chance and treatment. The thermography technique has the capability to provide an additional functional information on physiological changes to mammography by describing thermal and vascular properties of the tissues. Studies on breast thermography have been carried out to improve the accuracy level of the thermography technique in various perspectives. However, the limitation of gathering women affected by cancer in different age groups had necessitated this comprehensive study which is aimed to investigate the effect of different density levels on the surface temperature distribution profile of the breast models. These models, namely extremely dense (ED), heterogeneously dense (HD), scattered fibroglandular (SF), and predominantly fatty (PF), with embedded tumors were developed using the finite element method. A conventional Pennes' bioheat model was used to perform the numerical simulation on different case studies, and the results obtained were then compared using a hypothesis statistical analysis method to the reference breast model developed previously. The results obtained show that ED, SF, and PF breast models had significant mean differences in surface temperature profile with a p value <0.025, while HD breast model data pair agreed with the null hypothesis formulated due to the comparable tissue composition percentage to the reference model. The findings suggested that various breast density levels should be considered as a contributing factor to the surface thermal distribution profile alteration in both breast cancer detection and analysis when using the thermography technique.
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