scholarly journals Brain Stroke Detection by Microwaves Using Prior Information from Clinical Databases

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Natalia Irishina ◽  
Aurora Torrente
Keyword(s):  
Breast Cancer ◽  
Dielectric Properties ◽  
Prior Information ◽  
Brain Mri ◽  
Brain Lesion ◽  
Screening Method ◽  
Clinical Databases ◽  
Structural Inversion ◽  
Brain Stroke ◽  
Brain Stroke Detection

Microwave tomographic imaging is an inexpensive, noninvasive modality of media dielectric properties reconstruction which can be utilized as a screening method in clinical applications such as breast cancer and brain stroke detection. For breast cancer detection, the iterative algorithm of structural inversion with level sets provides well-defined boundaries and incorporates an intrinsic regularization, which permits to discover small lesions. However, in case of brain lesion, the inverse problem is much more difficult due to the skull, which causes low microwave penetration and highly noisy data. In addition, cerebral liquid has dielectric properties similar to those of blood, which makes the inversion more complicated. Nevertheless, the contrast in the conductivity and permittivity values in this situation is significant due to blood high dielectric values compared to those of surrounding grey and white matter tissues. We show that using brain MRI images as prior information about brain's configuration, along with known brain dielectric properties, and the intrinsic regularization by structural inversion, allows successful and rapid stroke detection even in difficult cases. The method has been applied to 2D slices created from a database of 3D real MRI phantom images to effectively detect lesions larger than 2.5 × 10−2 m diameter.

scholarly journals Finite-element analysis of microwave scattering from a three-dimensional human head model for brain stroke detection

2018 ◽  
Vol 5 (7) ◽  
pp. 180319
Author(s):  
Awais Munawar Qureshi ◽  
Zartasha Mustansar ◽  
Samah Mustafa
Keyword(s):  
Finite Element ◽  
Dielectric Properties ◽  
Electric Field ◽  
Three Dimensional ◽  
Human Head ◽  
Head Model ◽  
Different Types ◽  
Brain Stroke ◽  
Human Head Model ◽  
Brain Stroke Detection

In this paper, a detailed analysis of microwave (MW) scattering from a three-dimensional (3D) anthropomorphic human head model is presented. It is the first time that the finite-element method (FEM) has been deployed to study the MW scattering phenomenon of a 3D realistic head model for brain stroke detection. A major contribution of this paper is to add anatomically more realistic details to the human head model compared with the literature available to date. Using the MRI database, a 3D numerical head model was developed and segmented into 21 different types through a novel tissue-mapping scheme and a mixed-model approach. The heterogeneous and frequency-dispersive dielectric properties were assigned to brain tissues using the same mapping technique. To mimic the simulation set-up, an eight-elements antenna array around the head model was designed using dipole antennae. Two types of brain stroke (haemorrhagic and ischaemic) at various locations inside the head model were then analysed for possible detection and classification. The transmitted and backscattered signals were calculated by finding out the solution of the Helmholtz wave equation in the frequency domain using the FEM. FE mesh convergence analysis for electric field values and comparison between different types of iterative solver were also performed to obtain error-free results in minimal computational time. At the end, specific absorption rate analysis was conducted to examine the ionization effects of MW signals to a 3D human head model. Through computer simulations, it is foreseen that MW imaging may efficiently be exploited to locate and differentiate two types of brain stroke by detecting abnormal tissues’ dielectric properties. A significant contrast between electric field values of the normal and stroke-affected brain tissues was observed at the stroke location. This is a step towards generating MW scattering information for the development of an efficient image reconstruction algorithm.

scholarly journals Experimental Validation of Microwave Tomography with the DBIM-TwIST Algorithm for Brain Stroke Detection and Classification

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 840 ◽  
Author(s):  
Olympia Karadima ◽  
Mohammed Rahman ◽  
Ioannis Sotiriou ◽  
Navid Ghavami ◽  
Pan Lu ◽  
...  
Keyword(s):  
Inverse Problem ◽  
Ischemic Stroke ◽  
Dielectric Properties ◽  
Experimental Validation ◽  
Initial Guess ◽  
Microwave Tomography ◽  
Iterative Shrinkage ◽  
Brain Stroke ◽  
Brain Stroke Detection ◽  
Iterative Shrinkage Thresholding

We present an initial experimental validation of a microwave tomography (MWT) prototype for brain stroke detection and classification using the distorted Born iterative method, two-step iterative shrinkage thresholding (DBIM-TwIST) algorithm. The validation study consists of first preparing and characterizing gel phantoms which mimic the structure and the dielectric properties of a simplified brain model with a haemorrhagic or ischemic stroke target. Then, we measure the S-parameters of the phantoms in our experimental prototype and process the scattered signals from 0.5 to 2.5 GHz using the DBIM-TwIST algorithm to estimate the dielectric properties of the reconstruction domain. Our results demonstrate that we are able to detect the stroke target in scenarios where the initial guess of the inverse problem is only an approximation of the true experimental phantom. Moreover, the prototype can differentiate between haemorrhagic and ischemic strokes based on the estimation of their dielectric properties.

scholarly journals Risk factors for hip dislocation in dyskinetic cerebral palsy

2021 ◽  
Vol 29 (1) ◽  
pp. 230949902110011
Author(s):  
Kyoko Okuno ◽  
Yukihiro Kitai ◽  
Toru Shibata ◽  
Hiroshi Arai
Keyword(s):  
Risk Factors ◽  
Cerebral Palsy ◽  
Birth Weight ◽  
Gestational Age ◽  
Brain Mri ◽  
Brain Lesion ◽  
Brain Lesions ◽  
Lesion Location ◽  
Hip Displacement ◽  
Gmfcs Level

Purpose: To investigate the risk factors for hip displacement in patients with dyskinetic cerebral palsy (DCP). Methods: We evaluated 81 patients with DCP, 45 males and 36 females, aged 10–22 years, risk factors for hip displacement were evaluated using multivariate logistic regression analysis with primary brain lesions, Gross Motor Function Classification System (GMFCS) level, gestational age, birth weight, Cobb’s angle, and complication of epilepsy as independent factors. Hip displacement was defined as migration percentage >30%. Primary brain lesions were classified into globus pallidus (GP), thalamus and putamen (TP), and others using brain magnetic resonance imaging (MRI). Perinatal and clinical features were compared between patients with GP lesions and those with TP lesions. Results: Hip displacement was observed in 53 patients (67%). Higher GMFCS levels (p = 0.013, odds ratio [OR] 2.6) and the presence of GP lesions (p = 0.04, OR 16.5) were independent risk factors for hip displacement. Patients with GP lesions showed significantly higher GMFCS levels, more frequent hip displacement, and lower gestational age and birth weight than those with TP lesions. Conclusion: Primary brain lesion location may be an important factor in predicting hip displacement among patients with DCP. Appropriate risk assessment using brain MRI may contribute to the early detection and intervention of hip displacement because brain lesion location can be assessed during infancy before GMFCS level is decided.

scholarly journals Cyanuric Chloride Containing Chalcones for Possible Breast Cancer Treatment: Synthesis, Antimicrobial and in silico Screening

2019 ◽  
Vol 32 (2) ◽  
pp. 408-414
Author(s):  
Revathy Selvaraj ◽  
J. Suresh ◽  
A. Arun
Keyword(s):  
Breast Cancer ◽  
In Silico ◽  
Topoisomerase Ii ◽  
Excellent Result ◽  
Screening Method ◽  
Cyanuric Chloride ◽  
Gram Negative Bacteria ◽  
In Silico Screening ◽  
Gram Negative ◽  
Mic Value

In this work, we have synthesized efficient antibacterial compounds with anticancer novel molecules based on cyanuric chloride containing chalcone moiety. For this, novel triazine-based organic molecules were synthesized by using cyanuric chloride and 2,4-dichloro-1-ene(4-hydroxyphenyl)phenone and characterized by elemental analysis, FT-IR, NMR and UV-visible spectrometry techniques. Melting point of the molecules were increased with an increase in substitution on cyanuric chloride. The minimum inhibitory concentration (MIC) value of the synthesized compounds showed an excellent result on Gram-negative bacteria with low MIC value of 1.95 μg/mL. Gram-positive bacteria showed little resistance to the synthesized drug. The synthesized compounds were tested for their use as an anticancer drug using in silico screening method. The synthesized compounds in silico molecular docking method using breast cancer protein (BRCA2) confirms that triazine derivative with all three chlorine molecules replaced by 2,4-dichloro-1-ene(4-hydroxyphenyl)phenone showed highest binding energy with the value of -9.1900 Kcal/mol which is in agreement with the observed high MIC value obtained for Gram-negative bacteria. The synthesized molecules preferentially targeted the topoisomerase II of the bacteria. Overall, an efficient antimicrobial drug is synthesized using a simple preparation method.

scholarly journals Risk factors for the development of brain metastases in patients with HER2-positive breast cancer

ESMO Open ◽  
2018 ◽  
Vol 3 (6) ◽  
pp. e000440 ◽  
Author(s):  
Christian Maurer ◽  
Lorraine Tulpin ◽  
Michel Moreau ◽  
Cristina Dumitrescu ◽  
Evandro de Azambuja ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Brain Metastases ◽  
Cox Regression ◽  
Lung Metastases ◽  
Screening Method ◽  
Outcome Analysis ◽  
Asymptomatic Patients ◽  
Number Of Patients ◽  
Positive Breast Cancer

BackgroundPatients with metastatic human epidermal growth factor receptor 2-positive breast cancer (HER2+ BC) frequently experience brain metastases (BM). We aimed to define risk factors for the development of BM in patients with HER2+ BC and to report on their outcome.MethodsThis is a retrospective analysis of patients diagnosed with HER2+ BC between January 2000 and December 2014 at Institut Jules Bordet, Belgium. Statistical analyses were conducted with SAS V.9.4 using Kaplan-Meier method and Cox regression analyses.ResultsA total of 483 patients were included of whom 108 (22.4%) developed metastases and 52 (10.8%) BM. Among 96 metastatic patients without BM at diagnosis, 40 (41.7%) developed BM in the course of their disease. In multivariate analysis, risk factors for the development of BM were age ≤40 years (HR 2.10, 95 % CI 1.02 to 4.36), tumour size >2 cm (HR 4.94, 95% CI 1.69 to 14.47), nodal involvement (HR 3.48, 95% CI 1.47 to 8.25), absence or late start (≥6 months after initial diagnosis) of adjuvant anti-HER2 treatment (HR 3.79, 95% CI 1.52 to 9.43 or HR 2.65, 95% CI 1.03 to 6.82) and the development of lung metastases as first site of relapse (HR 6.97, 95% CI 3.41 to 14.24). Twenty-two patients with HER2+ BC and BM sent to our institute for further treatment were included in the outcome analysis. Asymptomatic patients at the time of BM diagnosis showed a better overall survival than symptomatic patients (HR 0.49, 95% CI 0.25 to 0.94).ConclusionA considerable number of patients with metastatic HER2+ BC will develop BM. Screening of patients with risk factors for BM might lead to early detection and better outcome. However, randomised controlled trials examining the use of MRI as a screening method for BM in patients with metastatic BC are warranted before such an approach can be recommended.

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