1,655 research outputs found

    Artificial intelligence in mammographic phenotyping of breast cancer risk: A narrative review

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    BACKGROUND: Improved breast cancer risk assessment models are needed to enable personalized screening strategies that achieve better harm-to-benefit ratio based on earlier detection and better breast cancer outcomes than existing screening guidelines. Computational mammographic phenotypes have demonstrated a promising role in breast cancer risk prediction. With the recent exponential growth of computational efficiency, the artificial intelligence (AI) revolution, driven by the introduction of deep learning, has expanded the utility of imaging in predictive models. Consequently, AI-based imaging-derived data has led to some of the most promising tools for precision breast cancer screening. MAIN BODY: This review aims to synthesize the current state-of-the-art applications of AI in mammographic phenotyping of breast cancer risk. We discuss the fundamentals of AI and explore the computing advancements that have made AI-based image analysis essential in refining breast cancer risk assessment. Specifically, we discuss the use of data derived from digital mammography as well as digital breast tomosynthesis. Different aspects of breast cancer risk assessment are targeted including (a) robust and reproducible evaluations of breast density, a well-established breast cancer risk factor, (b) assessment of a woman\u27s inherent breast cancer risk, and (c) identification of women who are likely to be diagnosed with breast cancers after a negative or routine screen due to masking or the rapid and aggressive growth of a tumor. Lastly, we discuss AI challenges unique to the computational analysis of mammographic imaging as well as future directions for this promising research field. CONCLUSIONS: We provide a useful reference for AI researchers investigating image-based breast cancer risk assessment while indicating key priorities and challenges that, if properly addressed, could accelerate the implementation of AI-assisted risk stratification to future refine and individualize breast cancer screening strategies

    Adenoid cystic carcinoma intermingled with ductal carcinoma of the breast: a case report and review of the literature

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    <p>Abstract</p> <p>Introduction</p> <p>Adenoid cystic cancer of the breast is a rare condition, and even rarer are the cases where it is histologically mixed with other variants of cancer within a single lesion. In this report, one of the few cases of mixed adenoid cystic breast cancer intermingled with the infiltrating ductal variant is presented. A subsequent review of the relevant literature presents the existing experience in treating mixed breast cancers with adenoid cystic components with regard to diagnosis, treatment, and prognosis.</p> <p>Case presentation</p> <p>We describe a case of mixed adenoid cystic cancer of the breast with infiltrating ductal carcinoma in a 67-year-old Caucasian woman who underwent mastectomy with sentinel node biopsy.</p> <p>Conclusion</p> <p>Surgery remains the cornerstone of treatment of these patients, and radiotherapy is administered when breast-conserving treatment is undertaken or a large tumor with affected lymph nodes is present. Hormonal treatment does not have a role, as estrogen receptors are always absent from both tumor components. Chemotherapy is nearly always administered on the basis of estrogen receptor and progesterone negativity and the more aggressive potential of the non-adenoid cystic component. The de-differentiation of an indolent type of cancer to a more aggressive one may affect the prognosis.</p

    Local density of states in superconductor-strong ferromagnet structures

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    We study the dependence of the local density of states (LDOS) on coordinates for a superconductor-ferromagnet (S/F) bilayer and a S/F/S structure assuming that the exchange energy h in the ferromagnet is sufficiently large: >>1,% h\tau >>1, where τ\tau is the elastic relaxation time. This limit cannot be described by the Usadel equation and we solve the more general Eilenberger equation. We demonstrate that, in the main approximation in the parameter (hτ)1% (h\tau)^{-1}, the proximity effect does not lead to a modification of the LDOS in the S/F system and a non-trivial dependence on coordinates shows up in next orders in (hτ)1.(h\tau) ^{-1}. In the S/F/S sandwich the correction to the LDOS is nonzero in the main approximation and depends on the phase difference between the superconductors. We also calculate the superconducting critical temperature TcT_{c} for the bilayered system and show that it does not depend on the exchange energy of the ferromagnet in the limit of large h and a thick F layer.Comment: 9 pages, 5 figure

    Layered ferromagnet-superconductor structures: the π\pi state and proximity effects

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    We investigate clean mutilayered structures of the SFS and SFSFS type, (where the S layer is intrinsically superconducting and the F layer is ferromagnetic) through numerical solution of the self-consistent Bogoliubov-de Gennes equations for these systems. We obtain results for the pair amplitude, the local density of states, and the local magnetic moment. We find that as a function of the thickness dFd_F of the magnetic layers separating adjacent superconductors, the ground state energy varies periodically between two stable states. The first state is an ordinary "0-state", in which the order parameter has a phase difference of zero between consecutive S layers, and the second is a "π\pi-state", where the sign alternates, corresponding to a phase difference of π\pi between adjacent S layers. This behavior can be understood from simple arguments. The density of states and the local magnetic moment reflect also this periodicity.Comment: 12 pages, 10 Figure

    Spontaneous Spin Polarized Currents in Superconductor-Ferromagnetic Metal Heterostructures

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    We study a simple microscopic model for thin, ferromagnetic, metallic layers on semi-infinite bulk superconductor. We find that for certain values of the exchange spliting, on the ferromagnetic side, the ground states of such structures feature spontaneously induced spin polarized currents. Using a mean-field theory, which is selfconsistent with respect to the pairing amplitude χ\chi, spin polarization m\vec{m} and the spontaneous current js\vec{j}_s, we show that not only there are Andreev bound states in the ferromagnet but when their energies EnE_n are near zero they support spontaneous currents parallel to the ferromagnetic-superconducting interface. Moreover, we demonstrate that the spin-polarization of these currents depends sensitively on the band filling.Comment: 4 pages, 5 Postscript figures (included

    Density of states in SF bilayers with arbitrary strength of magnetic scattering

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    We developed the self-consistent method for the calculation of the density of states N(ϵ)N(\epsilon) in the SF bilayers. It based on the quasi-classical Usadel equations and takes into account the suppression of superconductivity in the S layer due to the proximity effect with the F metal, as well as existing mechanisms of the spin dependent electron scattering. We demonstrate that the increase of the spin orbit or spin flip electron scattering rates results in completely different transformations of N(ϵ)N(\epsilon) at the free F layer interface. The developed formalism has been applied for the interpretation of the available experimental data.Comment: 5 pages, 8 figure
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