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Study the Anti-MUC1 antibody-based iron oxide nanoparticles on three-dimension spheroid and breast cancer (MCF-7) cell imaging

Moradi Khaniabadi Pegah, Shahbazi-Gahrouei Daryoush, Shah Abdul Majid Amin Malik, Moradi Khaniabadi Bita

Polish Journal of Medical Physics and Engineering

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2019

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Vol. 25, Iss. 2

69--77

EN

Non-invasive methods for breast cancer detection in early stages may help to increase the survival rate of patients. This study aimed to evaluate the application of Anti-MUC1 antibody-based iron oxide nanoparticle (SPIONs-C595) which was assessed in vivo as a molecular imaging probe for breast cancer (MCF-7) detection using MRI. Nine groups of female NRC NU/Nu mice (each group of 3), 6 to 8 weeks old were used and MCF-7 cells were injected subcutaneously into both flanks of nude mice. After two weeks the mice received an intravenous injection of different concentrations of SPIONs-C595. The uptake ability of SPIONs-C595 on three-dimension (3D) macrostructure is exploited a modified hanging drop method using Prussian blue for MCF-7 cells. The iron content was measured in liver, kidney, spleen, and tumor. The MR imaging features and biodistribution of nanoprobe was also investigated. The MR images obtained from digested tumor after nanoprobe administration in different time-period revealed that enhancement of T1 and T2 relaxation time. Moreover, the storage stability test was shown great application and no sedimentation of nanoparticles within two months storage at 4°C. Additionally, great validation of SPIONs-C595 on the 3D spheroid of MCF-7 was observed. The biodistribution analysis showed that iron content of the spleen was more than the other studied organs. These results highlighted the feasibility of an in-vivo model for detection of breast cancer MUC1 expression. Current researches are ongoing to further enhancement of relaxation times for classification of MUC1 status using clinical specimens.

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Detecting Pathologies with Homology Algorithms in Magnetic Resonance Images of Brain

Żelawski M.

Machine Graphics and Vision

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2009

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Vol. 18, No. 3

253-266

EN

This paper describes a method for detecting the presence of pathological changes in two-dimensional brain images from magnetic resonance examination. The proposed idea is based on homology theory, which makes it easily extendable to three-dimensional brain images in particular it may be applied to the computer tomography data.

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Interactive object detection using a fuzzy image segmentation approach

Mari M., Smits P. C., Kieś P., Chmielewski L.

Machine Graphics and Vision

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1998

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Vol. 7, No. 4

765-780

EN

In this paper the attention is focused on the processing of digital images, in particular on the segmentation of medical images. A new 3D fuzzy segmentation technique is presented to outline the adventages of a relatively simple software tool that may help the user to find contours of the objects of interest in images. The proposed technique is based on a seed growing approach, which takes into account both contextual and topological information in the image. The uncertainty of the image is considered through the use of fuzzy measures, well suited to represent the characteristics of a medical image. The result is a set of possible contours for the volume of interest at different certainty values. They mey be viewed as alternative comtours of the same object. If the method is used interactively, the user has the possibility to scroll very quickly through the different contours to select the most appropriate one for a specific application, according to his own knowledge.