Contrast Enhancement of Cross-Polarization OCT Images of Breast Cancer by Optical Coefficient Calculation

Dual-energy contrast-enhanced spectral mammography (CESM) is a new promising method for visualizing pathological changes in breast, which combines digital mammography and a functional assessment of vascularization using intravenous contrast ehnancement. According to accumulated experience CESM is well tolerated by patients and is similar to magnetic resonance imaging with dynamic contrast enhancement (MRI with DCE), but at the same time, CESM is more affordable and can be performed in patients with contraindications for MRI. However, few studies have been conducted to evaluate the role of CESM. In the world literature, interpretation of contrast images is based only on the degree of accumulation of the contrast agent, but we propose a more detailed assessment of the structure of the hypervascular lesions by highlighting the contrast enhancement patterns. Objective: to determine the diagnostic effectiveness of CESM using the contrast enhancement patterns in malignant and benign lesions. Materials and methods. 239 women with suspicious for breast cancer lesions were examined from August 2018 to December 2019. The mean age of the women was 51 years. 322 lesions were revealed, 149 (46.3%) were malignant, 173 (53.7%) were benign. All lesions were histologically confirmed. As a result of the analysis of our data, 9 types of contrast enhancement patterns were distinguished: reticulate, granular, annular, diffuse-spherical, lacunar, cloud-like, heterogeneous-annular, point, cotton-like. Results. Using an additional diagnostic feature - contrast enhancement patterns in lesions, increased the sensitivity of CESM from 91.3% to 98.0% (p=0.26), specificity from 80.3% to 93, 6% (p=0.013), accuracy from 85.4 to 95.7% (p=0.004) in comparison with using of only one feature of contrast enhancement intensity in the differential diagnosis of malignant and benign lesions. Conclusion: thus, this approach of interpreting subtraction images allows to increase the efficiency of CESM in diagnosis of breast cancer.

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Tissue optical properties estimation from cross-polarization OCT data for breast cancer margin assessment

Laser Physics Letters ◽

10.1088/1612-202x/ab9091 ◽

2020 ◽

Vol 17 (7) ◽

pp. 075602 ◽

Cited By ~ 1

Author(s):

Ekaterina V Gubarkova ◽

Alexander A Moiseev ◽

Elena B Kiseleva ◽

Dmitry A Vorontsov ◽

Sergey S Kuznetsov ◽

...

Keyword(s):

Breast Cancer ◽

Optical Properties ◽

Cross Polarization ◽

Margin Assessment ◽

Tissue Optical Properties

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Gray level clustering and contrast enhancement (GLC–CE) of mammographic breast cancer images

CSI Transactions on ICT ◽

10.1007/s40012-015-0062-z ◽

2015 ◽

Vol 2 (4) ◽

pp. 279-286 ◽

Cited By ~ 6

Author(s):

Bhagwati Charan Patel ◽

G. R. Sinha

Keyword(s):

Breast Cancer ◽

Contrast Enhancement ◽

Gray Level

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Tumor CT imaging using targeted nanoparticle delivery for contrast enhancement and tumor inhibition using targeted release of carboplatin nanoparticles via radiotherapy

International Journal of PIXE ◽

10.1142/s0129083514400075 ◽

2014 ◽

Vol 24 (03n04) ◽

pp. 137-149

Author(s):

S. Harada ◽

S. Ehara ◽

K. Ishii ◽

T. Sato ◽

M. Koka ◽

...

Keyword(s):

Breast Cancer ◽

Computed Tomography ◽

Hyaluronic Acid ◽

Contrast Enhancement ◽

Tumor Cells ◽

Antitumor Effect ◽

X Ray ◽

Nanoparticle Delivery ◽

Targeted Nanoparticles ◽

Targeted Release

In this paper, we used microcapsules releasing liposome-protamine-hyaluronic acid nanoparticles (LPH-NP) with/without carboplatin in response to radiation to image and treat MM48 breast cancer in C3He/N mice in two radiation sessions. The micro-particle-induced X-ray emission (PIXE) camera and quantitative PIXE were used to image and measure the release of nanoparticles from the microcapsules. In session one, iopamiron and computed tomography (CT)-detectable microcapsules containing P-selectin and LPH-NP were mixed with a solution of alginate, hyaluronate, ascorbate, and P-selectin. This solution was sprayed into an FeCl2 solution containing VEGFR-1/2 antibodies (Abs). The microcapsules obtained were injected intravenously into mice, and after 9 h, the mice were exposed to 10 or 20 Gy (140 keV) of X-ray radiation. Anti-VEGFR-1/VEGFR-2 microcapsules accumulated around tumors and released P-selectin and the iopamiron-labeled LPH-NP in response to the first radiation. The iopamiron-containing nanoparticles were detected by CT, allowing detection of MM48 tumors by CT. In the second session, the microcapsules released LPH-NH that delivered carboplatin into the tumor cells. This treatment had a significant antitumor effect [Formula: see text]. The micro-PIXE camera and quantitative PIXE successfully imaged and measured the release of contents from microcapsules. Our results indicate that targeted nanoparticles allow for accurate detection and treatment of tumors.

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DIGITAL MAMMOGRAM ENHANCEMENT USING KAPUR MEASURE OF ENTROPY AND MATHEMATICAL MORPHOLOGY

Biomedical Engineering Applications Basis and Communications ◽

10.4015/s1016237213500294 ◽

2013 ◽

Vol 25 (03) ◽

pp. 1350029 ◽

Cited By ~ 1

Author(s):

Baljit Singh Khehra ◽

Amar Partap Singh Pharwaha

Keyword(s):

Breast Cancer ◽

Image Analysis ◽

Early Detection ◽

Contrast Enhancement ◽

Mathematical Morphology ◽

Signal To Noise Ratio ◽

Histogram Equalization ◽

Signal To Noise ◽

Mammogram Image ◽

Background Contrast

Mammography is the most reliable, effective, low cost and highly sensitive method for early detection of breast cancer. Mammogram analysis usually refers to the processing of mammograms with the goal of finding abnormality presented in the mammogram. Mammogram enhancement is one of the most critical tasks in automatic mammogram image analysis. Main purpose of mammogram enhancement is to enhance the contrast of details and subtle features while suppressing the background heavily. In this paper, a hybrid approach is proposed to enhance the contrast of microcalcifications while suppressing the background heavily, using fuzzy logic and mathematical morphology. First, mammogram is fuzzified using Gaussian fuzzy membership function whose bandwidth is computed using Kapur measure of entropy. After this, mathematical morphology is applied on fuzzified mammogram. Mathematical morphology provides tools for the extraction of microcalcifications even if the microcalcifications are located on a nonuniform background. Main advantage of Kapur measure of entropy over Shannon entropy is that Kapur measure of entropy has α and β parameters that can be used as adjustable values. These parameters can play an important role as tuning parameters in the image processing chain for the same class of images. Experiments have been conducted on images of mini-Mammogram Image Analysis Society (MIAS) database (UK). Experiment results of the proposed approach are compared with histogram equalization (HE), contrast limited adaptive histogram equalization (CLAHE) and fuzzy histogram hyperbolization (FHH) which are well-established image enhancement techniques. In order to validate the results, several different kinds of standard test images (fatty, fatty-glandular and dense-glandular) of mini-MIAS database are considered. Objective image quality assessment parameters: Target-to-background contrast enhancement measurement based on standard deviation (TBCSD), target-to-background contrast enhancement measurement based on entropy (TBCE), contrast improvement index (CII), peak signal-to-noise ratio (PSNR) and average signal-to-noise ratio (ASNR) are used to evaluate the performance of proposed approach. The experimental results show that the proposed approach performs well. This study can be a part of developing a computer-aided diagnosis (CAD) system for early detection of breast cancer.

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