scholarly journals Towards clinical grating-interferometry mammography

2019 ◽  
Vol 30 (3) ◽  
pp. 1419-1425 ◽  
Author(s):  
Carolina Arboleda ◽  
Zhentian Wang ◽  
Konstantins Jefimovs ◽  
Thomas Koehler ◽  
Udo Van Stevendaal ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Dark Field ◽  
Breast Cancer Detection ◽  
Field Of View ◽  
Large Field ◽  
Clinical Environment ◽  
Conventional Mammography ◽  
Grating Interferometer ◽  
Set Up

Abstract Objectives Grating-interferometry-based mammography (GIM) might facilitate breast cancer detection, as several research works have demonstrated in a pre-clinical setting, since it is able to provide attenuation, differential phase contrast, and scattering images simultaneously. In order to translate this technique to the clinics, it has to be adapted to cover a large field-of-view within a clinically acceptable exposure time and radiation dose. Methods We set up a grating interferometer that fits into a standard mammography system and fulfilled the aforementioned conditions. Here, we present the first mastectomy images acquired with this experimental device. Results and conclusion Our system performs at a mean glandular dose of 1.6 mGy for a 5-cm-thick, 18%-dense breast, and a field-of-view of 26 × 21 cm2. It seems to be well-suited as basis for a clinical-environment device. Further, dark-field signals seem to support an improved lesion visualization. Evidently, the effective impact of such indications must be evaluated and quantified within the context of a proper reader study. Key Points • Grating-interferometry-based mammography (GIM) might facilitate breast cancer detection, since it is sensitive to refraction and scattering and thus provides additional tissue information. • The most straightforward way to do grating-interferometry in the clinics is to modify a standard mammography device. • In a first approximation, the doses given with this technique seem to be similar to those of conventional mammography.

scholarly journals Incoherent Radar Imaging for Breast Cancer Detection and Experimental Validation against 3D Multimodal Breast Phantoms

2021 ◽  
Vol 7 (2) ◽  
pp. 23
Author(s):  
Antonio Cuccaro ◽  
Angela Dell’Aversano ◽  
Giuseppe Ruvio ◽  
Jacinta Browne ◽  
Raffaele Solimene
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Breast Imaging ◽  
Experimental Validation ◽  
Reconstruction Algorithm ◽  
Breast Cancer Detection ◽  
Beam Forming ◽  
Clutter Rejection ◽  
Breast Phantom ◽  
Set Up

In this paper we consider radar approaches for breast cancer detection. The aim is to give a brief review of the main features of incoherent methods, based on beam-forming and Multiple SIgnal Classification (MUSIC) algorithms, that we have recently developed, and to compare them with classical coherent beam-forming. Those methods have the remarkable advantage of not requiring antenna characterization/compensation, which can be problematic in view of the close (to the breast) proximity set-up usually employed in breast imaging. Moreover, we proceed to an experimental validation of one of the incoherent methods, i.e., the I-MUSIC, using the multimodal breast phantom we have previously developed. While in a previous paper we focused on the phantom manufacture and characterization, here we are mainly concerned with providing the detail of the reconstruction algorithm, in particular for a new multi-step clutter rejection method that was employed and only barely described. In this regard, this contribution can be considered as a completion of our previous study. The experiments against the phantom show promising results and highlight the crucial role played by the clutter rejection procedure.

An Information-theoretical Model for Breast Cancer Detection

2008 ◽  
Vol 47 (04) ◽  
pp. 322-327 ◽  
Author(s):  
D. Blokh ◽  
N. Zurgil ◽  
I. Stambler ◽  
E. Afrimzon ◽  
Y. Shafran ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Hamming Distance ◽  
Formal Model ◽  
Methodological Approach ◽  
Breast Cancer Detection ◽  
Receptor Expression ◽  
Diagnostic Model ◽  
Model Parameters ◽  
Two Stages

Summary Objectives: Formal diagnostic modeling is an important line of modern biological and medical research. The construction of a formal diagnostic model consists of two stages: first, the estimation of correlation between model parameters and the disease under consideration; and second, the construction of a diagnostic decision rule using these correlation estimates. A serious drawback of current diagnostic models is the absence of a unified mathematical methodological approach to implementing these two stages. The absence of aunified approach makesthe theoretical/biomedical substantiation of diagnostic rules difficult and reduces the efficacyofactual diagnostic model application. Methods: The present study constructs a formal model for breast cancer detection. The diagnostic model is based on information theory. Normalized mutual information is chosen as the measure of relevance between parameters and the patterns studied. The “nearest neighbor” rule is utilized for diagnosis, while the distance between elements is the weighted Hamming distance. The model concomitantly employs cellular fluorescence polarization as the quantitative input parameter and cell receptor expression as qualitative parameters. Results: Twenty-four healthy individuals and 34 patients (not including the subjects analyzed for the model construction) were tested by the model. Twenty-three healthy subjects and 34 patients were correctly diagnosed. Conclusions: The proposed diagnostic model is an open one,i.e.it can accommodate new additional parameters, which may increase its effectiveness.

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