Modeling the SIGMA-Eye Applicator for Hyperthermia via Multiple Infinitesimal Dipoles

Over the past several decades, cancer is still one of the leading causes of human deaths. Hyperthermia treatment, which is mostly performed in clinic as an assistant therapy method combined with chemotherapy or radiation therapy, has been also playing a more and more important role in tumor therapy. Driven by the developments of computing power and computational techniques, personalized hyperthermia treatment planning (HTP) is becoming possible and essential for clinical practice, aimed at achieving maximum treatment effects for tumor targets and minimal side effects for the surrounding tissues simultaneously. As an essential step of Electromagnetic Hyperthermia Treatment Planning, electromagnetic simulation with the phased-array applicator, SIGMA-Eye hyperthermia applicator, was explored. The approach of the basic-building-block-based modified Infinitesimal Dipole Model (IDM) as a virtual source model was developed and used for modeling the hyperthermia SIGMA-Eye applicator (BSD Medical Corporation) in this work. The basic idea of the IDM [1] is to replace the antenna with a series of infinitesimal dipoles which generates the same electric field as the antenna does. On the basis of the conventional IDM, a modified IDM is proposed, in which number and locations of dipoles are predefined. The reduced set of dipole parameters leads to a simpler objective function of the modified IDM in comparison to the conventional IDM concerning parameter fitting. In addition, the concept of a ‘basic building block’ [2] is introduced: the antenna under test (active antenna) and its neighboring antenna elements (passive antennas) are considered as a basic building block. The dipole model of the antenna under test will be fit by approximating the electric field of the block in order to correctly treat the mutual coupling between antenna elements. Therefore, electric fields generated by a phased-array applicator (with significant mutual coupling between elements) can be modeled. In this work, each antenna of the SIGMA-Eye applicator was modelled using the basic-building-block-based modified IDM. Taking the electric field data of the basic building block computed from the software COMSOL Multiphysics as reference, the global optimization algorithm OQNLP (OptQuest Nonlinear Programming) [3] was used for parameter fitting of the dipole models. And then the SIGMA-Eye applicator was simulated by the superposition of each simulated antenna. Electromagnetic simulations with different phase combinations of the antenna elements of the applicator were performed. The resulted electromagnetic energy deposition patterns were compared to the measurement data presented in the reference paper [4], where the electric field measurement within the phantom placed inside the SIGMA-Eye applicator was performed. The relative differences of energy deposition patterns ranged from 1.40% to 17.90% with an average at 5.07%. The agreement of energy deposition patterns between simulation data and measurement data justified the applicability of our virtual source model to hyperthermia forward planning and further to the commissioning of new systems. In addition, the frequency dependence and water-bolus permittivity and conductivity dependence of the block-based modified IDM was explored, and it was found that this approach is applicable for a narrow-band frequency, and is adaptable to the uncertainty of the water-bolus permittivity and conductivity. When operating at a frequency further away from the reference frequency, or the surrounding environment of the antennas changes a lot, the applicator needs to be simulated using a new equivalent model. [1] Mikki, S.M. and A.A. Kishk, Theory and applications of infinitesimal dipole models for computational electromagnetics. Ieee Transactions on Antennas and Propagation, 2007. 55(5): p. 1325-1337. [2] Mikki, S.M. and Y.M.M. Antar, Near-Field Analysis of Electromagnetic Interactions in Antenna Arrays Through Equivalent Dipole Models. Ieee Transactions on Antennas and Propagation, 2012. 60(3): p. 1381-1389. [3] Ugray, Z., Lasdon, L., Plummer, J., Glover, F., Kelly, J. and Martí, R, Scatter Search and Local NLP Solvers: A Multistart Framework for Global Optimization. INFORMS Journal on Computing, 2007. 19(3): p. 328-340. [4] F.Turner, P., Technical Aspect of the BSD-2000 and BSD-2000∙3D, in European Society for Hyperthermia Oncology and BSD Medical Corporation User’s Conference. 1997

3D Matting: A Soft Segmentation Method Applied in Computed Tomography

Three-dimensional (3D) images, such as CT, MRI, and PET, are common in medical imaging applications and important in clinical diagnosis. Semantic ambiguity is a typical feature of many medical image labels. It can be caused by many factors, such as the imaging properties, pathological anatomy, and the weak representation of the binary masks, which brings challenges to accurate 3D segmentation. In 2D medical images, using soft masks instead of binary masks generated by image matting to characterize lesions can provide rich semantic information, describe the structural characteristics of lesions more comprehensively, and thus benefit the subsequent diagnoses and analyses. In this work, we introduce image matting into the 3D scenes to describe the lesions in 3D medical images. The study of image matting in 3D modality is limited, and there is no high-quality annotated dataset related to 3D matting, therefore slowing down the development of data-driven deep-learning-based methods. To address this issue, we constructed the first 3D medical matting dataset and convincingly verified the validity of the dataset through quality control and downstream experiments in lung nodules classification. We then adapt the four selected state-of-the-art 2D image matting algorithms to 3D scenes and further customize the methods for CT images. Also, we propose the first end-to-end deep 3D matting network and implement a solid 3D medical image matting benchmark, which will be released to encourage further research.Comment: 12 pages, 7 figure

The dominant Anopheles vectors of human malaria in Africa, Europe and the Middle East: occurrence data, distribution maps and bionomic précis

<p>Abstract</p> <p>Background</p> <p>This is the second in a series of three articles documenting the geographical distribution of 41 dominant vector species (DVS) of human malaria. The first paper addressed the DVS of the Americas and the third will consider those of the Asian Pacific Region. Here, the DVS of Africa, Europe and the Middle East are discussed. The continent of Africa experiences the bulk of the global malaria burden due in part to the presence of the <it>An. gambiae </it>complex. <it>Anopheles gambiae </it>is one of four DVS within the <it>An. gambiae </it>complex, the others being <it>An. arabiensis </it>and the coastal <it>An. merus </it>and <it>An. melas</it>. There are a further three, highly anthropophilic DVS in Africa, <it>An. funestus</it>, <it>An. moucheti </it>and <it>An. nili</it>. Conversely, across Europe and the Middle East, malaria transmission is low and frequently absent, despite the presence of six DVS. To help control malaria in Africa and the Middle East, or to identify the risk of its re-emergence in Europe, the contemporary distribution and bionomics of the relevant DVS are needed.</p> <p>Results</p> <p>A contemporary database of occurrence data, compiled from the formal literature and other relevant resources, resulted in the collation of information for seven DVS from 44 countries in Africa containing 4234 geo-referenced, independent sites. In Europe and the Middle East, six DVS were identified from 2784 geo-referenced sites across 49 countries. These occurrence data were combined with expert opinion ranges and a suite of environmental and climatic variables of relevance to anopheline ecology to produce predictive distribution maps using the Boosted Regression Tree (BRT) method.</p> <p>Conclusions</p> <p>The predicted geographic extent for the following DVS (or species/suspected species complex*) is provided for Africa: <it>Anopheles </it>(<it>Cellia</it>) <it>arabiensis</it>, <it>An. </it>(<it>Cel.</it>) <it>funestus*</it>, <it>An. </it>(<it>Cel.</it>) <it>gambiae</it>, <it>An. </it>(<it>Cel.</it>) <it>melas</it>, <it>An. </it>(<it>Cel.</it>) <it>merus</it>, <it>An. </it>(<it>Cel.</it>) <it>moucheti </it>and <it>An. </it>(<it>Cel.</it>) <it>nili*</it>, and in the European and Middle Eastern Region: <it>An. </it>(<it>Anopheles</it>) <it>atroparvus</it>, <it>An. </it>(<it>Ano.</it>) <it>labranchiae</it>, <it>An. </it>(<it>Ano.</it>) <it>messeae</it>, <it>An. </it>(<it>Ano.</it>) <it>sacharovi</it>, <it>An. </it>(<it>Cel.</it>) <it>sergentii </it>and <it>An. </it>(<it>Cel.</it>) <it>superpictus*</it>. These maps are presented alongside a bionomics summary for each species relevant to its control.</p

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Ultrasound Common Carotid Artery Segmentation Based on Active Shape Model

Carotid atherosclerosis is a major reason of stroke, a leading cause of death and disability. In this paper, a segmentation method based on Active Shape Model (ASM) is developed and evaluated to outline common carotid artery (CCA) for carotid atherosclerosis computer-aided evaluation and diagnosis. The proposed method is used to segment both media-adventitia-boundary (MAB) and lumen-intima-boundary (LIB) on transverse views slices from three-dimensional ultrasound (3D US) images. The data set consists of sixty-eight, 17 × 2 × 2, 3D US volume data acquired from the left and right carotid arteries of seventeen patients (eight treated with 80 mg atorvastatin and nine with placebo), who had carotid stenosis of 60% or more, at baseline and after three months of treatment. Manually outlined boundaries by expert are adopted as the ground truth for evaluation. For the MAB and LIB segmentations, respectively, the algorithm yielded Dice Similarity Coefficient (DSC) of 94.4% ± 3.2% and 92.8% ± 3.3%, mean absolute distances (MAD) of 0.26 ± 0.18 mm and 0.33 ± 0.21 mm, and maximum absolute distances (MAXD) of 0.75 ± 0.46 mm and 0.84 ± 0.39 mm. It took 4.3 ± 0.5 mins to segment single 3D US images, while it took 11.7 ± 1.2 mins for manual segmentation. The method would promote the translation of carotid 3D US to clinical care for the monitoring of the atherosclerotic disease progression and regression