scholarly journals Patient/Breast-Specific Detection of Breast Tumor Based on Patients’ Thermograms, 3D Breast Scans, and Reverse Thermal Modelling

2021 ◽  
Vol 11 (14) ◽  
pp. 6565
Author(s):  
Olzhas Mukhmetov ◽  
Aigerim Mashekova ◽  
Yong Zhao ◽  
Anna Midlenko ◽  
Eddie Yin Kwee Ng ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Tissue ◽  
Thermal Modeling ◽  
Blood Perfusion ◽  
Patient Specific ◽  
Element Analysis ◽  
Ir Camera ◽  
Tissue Properties ◽  
Tissue Density ◽  
Density Methods

Background: Mammography is the preferred method for the diagnosis of breast cancer. However, this diagnostic technique fails to detect tumors of small sizes, and it does not work well for younger patients with high breast tissue density. Methods: This paper proposes a novel tool for the early detection of breast cancer, which is patient-specific, non-invasive, inexpensive, and has potential in terms of accuracy compared with existing techniques. The main principle of this method is based on the use of temperature contours from breast skin surfaces through thermography, and inverse thermal modeling based on Finite Element Analysis (FEA) and a Genetic Algorithm (GA)-based optimization tool to estimate the depths and sizes of tumors as well as patient/breast-specific tissue properties. Results: The study was conducted by using a 3D geometry of patients’ breasts and their temperature contours, which were clinically collected using a 3D scanner and a thermal imaging infrared (IR) camera. Conclusion: The results showed that the combination of 3D breast geometries, thermal images, and inverse thermal modeling is capable of estimating patient/breast-specific breast tissue and physiological properties such as gland and fat contents, tissue density, thermal conductivity, specific heat, and blood perfusion rate, based on a multilayer model consisting of gland and fat. Moreover, this tool was able to calculate the depth and size of the tumor, which was validated by the doctor’s diagnosis.

Outcomes after Surgery for Early Stage Breast Cancer in Women Staged With Preoperative Breast Magnetic Resonance Imaging According to Breast Tissue Density

2019 ◽  
Vol 1 (2) ◽  
pp. 115-121
Author(s):  
Renata Faermann ◽  
Jonathan Weidenfeld ◽  
Leonid Chepelev ◽  
Wayne Kendal ◽  
Raman Verma ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Tissue ◽  
Early Stage ◽  
Disease Free Survival ◽  
Breast Mri ◽  
Early Stage Breast Cancer ◽  
Free Survival ◽  
Tissue Density ◽  
Breast Tissue Density ◽  
Preoperative Breast Mri

Abstract Purpose To determine surgical outcomes and breast cancer disease-free survival outcomes of women with early stage breast cancer with and without use of preoperative breast MRI according to breast tissue density. Methods Women with early stage breast cancer diagnosed from 2004 to 2009 were classified into 2 groups: 1) those with dense and heterogeneously dense breasts (DB); 2) those with nondense breasts (NDB) (scattered fibroglandular and fatty replaced tissue). The 2 groups were reviewed to determine who underwent preoperative MRI. Breast tissue density was determined with mammography according to ACR BI-RADS. Patients were compared according to tumor size, grade, stage, and treatment. Survival analysis was performed using Kaplan-Meier estimates. Results In total, 261 patients with mean follow-up of 85 months (25–133) were included: 156 DB and 105 NDB. Disease-free survival outcomes were better in the DB group in patients with MRI than in those without MRI: patients with MRI had significantly fewer local recurrences (P < 0.016) and metachronous contralateral breast cancers (P < 0.001), but this was not the case in the NDB group. Mastectomies were higher in the DB group with preoperative MRI than in those without MRI (P < 0.01), as it was in the NDB group (P > 0.05). Conclusions Preoperative breast MRI was associated with reduced local recurrence and metachronous contralateral cancers in the DB group, but not in the NDB group; however, the DB patients with MRI had higher mastectomy rates.

A COMPREHENSIVE TISSUE PROPERTIES DATABASE PROVIDED FOR THE THERMAL ASSESSMENT OF A HUMAN AT REST

2010 ◽  
Vol 05 (03) ◽  
pp. 129-151 ◽  
Author(s):  
ROBERT L. MCINTOSH ◽  
VITAS ANDERSON
Keyword(s):  
Thermal Conductivity ◽  
Heat Capacity ◽  
Thermal Properties ◽  
Thermal Modeling ◽  
Blood Perfusion ◽  
Human Tissues ◽  
Tissue Properties ◽  
Future Studies ◽  
Average Value ◽  
Metabolic Heat

Accurate numerical calculation of the thermal profile in humans requires reliable estimates of the following five tissue properties: specific heat capacity (c), thermal conductivity (k), blood perfusion rates (m), metabolic heat production (A0), and density (ρ). A sixth property, water content (w, as a %), can also be used to estimate c and k. To date, researchers have used various and inconsistent estimates of these parameters, which hinders comparison of the corresponding results. In an effort to standardize and improve the accuracy of these parameters for future studies, we have documented over 150 key papers and books and developed a database of the six thermal properties listed above for 43 human tissues. For each tissue and each property the following were obtained: the average value, the number of source values, the minimum and maximum of source values, and the reference for each source value. A key premise for the development of the database was to only use references that provided the original measurements. This database is offered for use by the biological thermal modeling community to help improve the accuracy and consistency of thermal modeling results.

Effect of Tamoxifen on Breast Tissue Density in Premenopausal Breast Cancer

2004 ◽  
Vol 10 (1) ◽  
pp. 27-32 ◽  
Author(s):  
Priscilla J. Slanetz ◽  
Lauren E. Grandpre ◽  
Eren D. Yeh ◽  
Daniel B. Kopans ◽  
Jeffrey B. Mendel
Keyword(s):  
Breast Cancer ◽  
Breast Tissue ◽  
Premenopausal Breast Cancer ◽  
Tissue Density ◽  
Breast Tissue Density

Reevaluation of annexin I expression in benign breast tissue and breast cancer

2006 ◽  
Vol 66 (S 01) ◽  
Author(s):  
R Speer ◽  
JD Wulfkuhle ◽  
D Wallwiener ◽  
E Solomayer ◽  
LA Liotta ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Tissue ◽  
Annexin I ◽  
Benign Breast Tissue

Copper Concentrations in Breast Cancer: A Systematic Review and Meta-Analysis

2020 ◽  
Vol 27 (37) ◽  
pp. 6373-6383 ◽  
Author(s):  
Leila Jouybari ◽  
Faezeh Kiani ◽  
Farhad Islami ◽  
Akram Sanagoo ◽  
Fatemeh Sayehmiri ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Systematic Review ◽  
Breast Tissue ◽  
Reference Lists ◽  
Meta Analysis ◽  
Cancer Risks ◽  
Hair Samples ◽  
Significant Difference ◽  
Mean Differences ◽  
Very High

: Breast cancer is the most common neoplasm, comprising 16% of all women's cancers worldwide. Research of Copper (Cu) concentrations in various body specimens have suggested an association between Cu levels and breast cancer risks. This systematic review and meta-analysis summarize the results of published studies and examine this association. We searched the databases PubMed, Scopus, Web of Science, and Google Scholar and the reference lists of relevant publications. The Standardized Mean Differences (SMDs) between Cu levels in cancer cases and controls and corresponding Confidence Intervals (CIs), as well as I2 statistics, were calculated to examine heterogeneity. Following the specimens used in the original studies, the Cu concentrations were examined in three subgroups: serum or plasma, breast tissue, and scalp hair. We identified 1711 relevant studies published from 1984 to 2017. There was no statistically significant difference between breast cancer cases and controls for Cu levels assayed in any studied specimen; the SMD (95% CI) was -0.01 (-1.06 - 1.03; P = 0.98) for blood or serum, 0.51 (-0.70 - 1.73; P = 0.41) for breast tissue, and -0.88 (-3.42 - 1.65; P = 0.50) for hair samples. However, the heterogeneity between studies was very high (P < 0.001) in all subgroups. We did not find evidence for publication bias (P = 0.91). The results of this meta-analysis do not support an association between Cu levels and breast cancer. However, due to high heterogeneity in the results of original studies, this conclusion needs to be confirmed by well-designed prospective studies.

scholarly journals Patient-Specific Network for Personalized Breast Cancer Therapy with Multi-Omics Data

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 225
Author(s):  
Claudia Cava ◽  
Soudabeh Sabetian ◽  
Isabella Castiglioni
Keyword(s):  
Breast Cancer ◽  
Cancer Therapy ◽  
Protein Interaction Network ◽  
Copy Number ◽  
Tumor Heterogeneity ◽  
Copy Number Alteration ◽  
Interaction Network ◽  
Computational Approach ◽  
Patient Specific ◽  
Basal Breast Cancer

The development of new computational approaches that are able to design the correct personalized drugs is the crucial therapeutic issue in cancer research. However, tumor heterogeneity is the main obstacle to developing patient-specific single drugs or combinations of drugs that already exist in clinics. In this study, we developed a computational approach that integrates copy number alteration, gene expression, and a protein interaction network of 73 basal breast cancer samples. 2509 prognostic genes harboring a copy number alteration were identified using survival analysis, and a protein–protein interaction network considering the direct interactions was created. Each patient was described by a specific combination of seven altered hub proteins that fully characterize the 73 basal breast cancer patients. We suggested the optimal combination therapy for each patient considering drug–protein interactions. Our approach is able to confirm well-known cancer related genes and suggest novel potential drug target genes. In conclusion, we presented a new computational approach in breast cancer to deal with the intra-tumor heterogeneity towards personalized cancer therapy.

scholarly journals The Expression Pattern of Epidermal Differentiation Marker Keratin 10 in the Normal Human Breast and Breast Cancer Cells

2020 ◽  
Vol 68 (8) ◽  
pp. 561-570
Author(s):  
Jiyoung Kim ◽  
René Villadsen
Keyword(s):  
Breast Cancer ◽  
Expression Pattern ◽  
Breast Tissue ◽  
Normal Breast ◽  
Epidermal Differentiation ◽  
Breast Cancer Patients ◽  
Human Breast ◽  
Normal Human Breast ◽  
Differentiation Marker ◽  
Breast Gland

Cells of the human breast gland express an array of keratins, of which some are used for characterizing both normal and neoplastic breast tissue. However, the expression pattern of certain keratins has yet to be detailed. Here, the expression of a differentiation marker of epidermal epithelium, keratin 10 (K10), was investigated in the human breast gland. While in normal breast tissue generally less than 1% of luminal epithelial cells expressed K10, in women >30 years of age glandular structures with K10-positive (K10pos) cells were found at higher frequency than in younger women. K10pos cells belong to a mature luminal compartment as they were negative for cKIT, positive for Ks20.8, and mostly non-cycling. In breast cancer, around 16% of primary breast carcinomas tested were positive for K10 by immunohistochemistry. Interestingly, K10pos tumor cells generally exhibit features of differentiation similar to their normal counterparts. Although this suggests that K10 is a marker of tumor differentiation, data based on gene expression analysis imply that high levels of K10 dictate a worse outcome for breast cancer patients. These findings can form the basis of future studies that should unravel which role K10 may play as a marker of breast cancer:

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