Coherence Factor Weighted Third Degree Delay Multiply and Sum Passive Cavitation Mapping for Magnetic Nanoparticle Visualization

Coherent multi-transducer ultrasound (CoMTUS) imaging enables the use of multiple arrays as one large effective aperture. This yields images with enlarged field-of-view, improved resolution, and higher SNR. However, creating a large but discontinuous effective aperture increases the grating and side lobe levels and generates cross-talk artifacts from the direct transmissions between arrays. These additional challenges can degrade the contrast of the images obtained through the classic Delay and Sum (DAS) beamforming algorithm. This study investigates the use of an alternative nonlinear beamforming algorithm, the Delay Multiply and Sum (DMAS), to improve contrast and reduce cross-talk artifacts in CoMTUS. We adapted the original DMAS beamforming algorithm to the specific effective aperture of CoMTUS and tested its performance in a coherent dual-array system for both 2-D and 3-D imaging. The comparison between images obtained through CoMTUS DMAS and DAS was investigated by both 2-D and 3-D simulations and experiments. DMAS was shown effective to lower the side lobes and the noise floor, thus improving the detectability of cystic lesions.

In this research work, a novel framework is proposed as an efficient successor to traditional imaging methods for breast cancer detection in order to decrease the computational complexity. In this framework, the breast is divided into segments in an iterative process and in each iteration, the one having the most probability of containing tumor with lowest possible resolution is selected by using suitable decision metrics. After finding the smallest tumor-containing segment, the resolution is increased in the detected tumor-containing segment, leaving the other parts of the breast image with low resolution. Our framework is applied on the most common used beamforming techniques, such as delay and sum (DAS) and delay multiply and sum (DMAS) and according to simulation results, our framework can decrease the computational complexity significantly for both DAS and DMAS without imposing any degradation on accuracy of basic algorithms. The amount of complexity reduction can be determined manually or automatically based on two proposed methods that are described in this framework.

In photoacoustic imaging, delay-and-sum (DAS) beamformer is a common beamforming algorithm having a simple implementation. However, it results in a poor resolution and high sidelobes. To address these challenges, a new algorithm namely delay-multiply-and-sum (DMAS) was introduced having lower sidelobes compared to DAS. To improve the resolution of DMAS, a beamformer is introduced using minimum variance (MV) adaptive beamforming combined with DMAS, so-called minimum variance-based DMAS (MVB-DMAS). It is shown that expanding the DMAS equation results in multiple terms representing a DAS algebra. It is proposed to use the MV adaptive beamformer instead of the existing DAS. MVB-DMAS is evaluated numerically and experimentally. In particular, at the depth of 45mm MVB-DMAS results in about 31, 18, and 8dB sidelobes reduction compared to DAS, MV, and DMAS, respectively. The quantitative results of the simulations show that MVB-DMAS leads to improvement in full-width-half-maximum about 96%, 94%, and 45% and signal-to-noise ratio about 89%, 15%, and 35% compared to DAS, DMAS, MV, respectively. In particular, at the depth of 33mm of the experimental images, MVB-DMAS results in about 20dB sidelobes reduction in comparison with other beamformers.

Although conventional delay-and-sum (DAS) beam-forming is the most common beamforming method to reconstruct ultrasound images, alternative approaches might provide better image quality. As such, delay multiply and sum (DMAS) beam-forming has recently been proposed. In this paper, we investigate the use of a more efficient approach for the DMAS method together with high frame rate (HFR) imaging and coherent compounding. The proposed beamformer is evaluated on datasets acquired by computer simulation and experimentally in vivo. Imaging results demonstrate that it provides better clutter and noise rejection, and enhances the image quality in terms of resolution and contrast as compared with DAS and DMAS methods, without compromising the computational complexity.

Photoacoustic imaging (PAI) is a promising medical imaging modality providing the spatial resolution of ultrasound imaging and the contrast of optical imaging. For linear-array PAI, a beamformer can be used as the reconstruction algorithm. Delay-and-sum (DAS) is the most prevalent beamforming algorithm in PAI. However, using DAS beamformer leads to low-resolution images as well as high sidelobes due to nondesired contribution of off-axis signals. Coherence factor (CF) is a weighting method in which each pixel of the reconstructed image is weighted, based on the spatial spectrum of the aperture, to mainly improve the contrast. We demonstrate that the numerator of the formula of CF contains a DAS algebra and propose the use of a delay-multiply-and-sum beamformer instead of the available DAS on the numerator. The proposed weighting technique, modified CF (MCF), has been evaluated numerically and experimentally compared to CF. It was shown that MCF leads to lower sidelobes and better detectable targets. The quantitative results of the experiment (using wire targets) show that MCF leads to for about 45% and 40% improvement, in comparison with CF, in the terms of signal-to-noise ratio and full-width-half-maximum, respectively.

Photoacoustic imaging (PAI), is a promising medical imaging technique that\nprovides the high contrast of the optical imaging and the resolution of\nultrasound (US) imaging. Among all the methods, Three-dimensional (3D) PAI\nprovides a high resolution and accuracy. One of the most common algorithms for\n3D PA image reconstruction is delay-and-sum (DAS). However, the quality of the\nreconstructed image obtained from this algorithm is not satisfying, having high\nlevel of sidelobes and a wide mainlobe. In this paper, delay-multiply-and-sum\n(DMAS) algorithm is suggested to overcome these limitations in 3D PAI. It is\nshown that DMAS algorithm is an appropriate reconstruction technique for 3D PAI\nand the reconstructed images using this algorithm are improved in the terms of\nthe width of mainlobe and sidelobes, compared to DAS. Also, the quantitative\nresults show that DMAS improves signal-to-noise ratio (SNR) and\nfull-width-half-maximum (FWHM) for about 25 dB and 0.2 mm, respectively,\ncompared to DAS.\n

Magnetic nanoparticles can be used in medicine in vivo as contrast agents and as a drug carrier system for chemotherapeutics. Thus local cancer therapy is performed with Magnetic Drug Targeting (MDT) and allows a specific delivery of therapeutic agents to desired targets, i.e., tumors, by using a chemotherapeutic substance bound to magnetic nanoparticles and focused with an external magnetic field to the tumor after intraarterial application. Important for this therapeutic principle is the distribution of the particles in the whole organism and especially in the tumor. Therefore we used magnetorelaxometry to quantify ferrofluids delivered after MDT. Tissue samples of some mm3 volume of a VX2 squamous cell carcinoma were measured by magnetic relaxation and the amount of iron was determined using the original ferrofluid suspension as a reference. From this the distribution of the magnetic particles within the slice of tumor was reconstructed. Histological cross-sections of the respective tumor offer the opportunity to map quantitatively the particle distribution and the vascularisation in the targeted tumor on a microscopic scale. Our data show that the integral method magnetorelaxometry and microscopic histological methods can complete each other efficiently.

Multi-channel magnetorelaxometry (MRX) is demonstrated to locate and quantify several foci of a magnetic nanoparticle (MNP) distribution after magnetic drug targeting (MDT) in an in-vivo rabbit carcinoma model. By this non-invasively technique MNP accumulations of lateral extensions up to 20 x 30 cm2 can easily be accessed in biological tissue. The total measurement duration of about 20 min including preparation of the rabbit and measurement of two regions of interests (ROI), tumor and thorax (liver, lung and spleen), enables a high throughput of animals. Modelling the MNP distribution either by magnetic point dipoles (ROI tumor) or by an extended, homogenously magnetized body (ROI thorax) of simple geometry, e.g. cuboid, the total magnetic moment and location of each focus is determined by minimum norm estimation. Simultaneously, vital functions like respiration and heart activity can be monitored directly and non-invasively during the MRX measurements. Thus, our MRX procedure gains valuable information for monitoring of MDT procedures in large scale animal models.

Over the last years, magnetic nanoparticles have received a great attention in cancer therapy and diagnosis. Magnetic drug targeting, is a particularly promising application in this area as the nanoparticles can be directed to the tumor by external magnetic field and concentrated the drug in this tumor tissue. In addition to this magnetic targeting, their inherent magnetic properties provide sensitive contrast enhancement in magnetic resonance imaging (MRI) and can, therefore, be visualized and used for theranostic purposes. Another important pillar of cancer therapy in which magnetic nanoparticles can be successfully employed is the hyperthermia induced either magnetically or by infrared irradiation. In addition, recent works have suggested that magnetic nanoparticles can be used for mechanical stimulation of cells affecting their viability. Most of these applications require modification of the physiochemical and surface properties of the magnetic nanoparticles to control their biodistribution, toxicity and pharmacokinetics. In relation to this, polymer coatings are probably the preference alternative to cover the magnetic nanoparticles for cancer treatment applications. In this review, we attempt to provide an overview of the recent advances in the development and applications of polymeric magnetic nanoparticles in cancer treatment and diagnosis including MRI, drug delivery, magnetic hyperthermia, photothermia and magnetolysis.

A mathematical model is presented for predicting magnetic targeting of multifunctional carrier particles that deliver therapeutic agents to malignant tissue in vivo. These particles consist of a nonmagnetic core material that contains embedded magnetic nanoparticles and therapeutic agents such as photodynamic sensitizers. For in vivo therapy, the particles are injected into the micro vascular system upstream from malignant tissue, and captured at the tumor using an applied magnetic field. In this paper, a mathematical model is developed for predicting noninvasive magnetic targeting of therapeutic carrier particles in a micro vessel. The flow of blood in the micro vessel is described by a two phase Herschel-Bulkley fluid model. The Brinkmann model is used to characterize the permeable nature of the inner wall of the micro-vessel. The fluidic force on the carrier traversing the micro-vessel and the magnetic force due to the external magnetic field is taken into account. The model enables rapid parametric analysis of magnetic targeting as a function of key variables including the size of the carrier particle, the properties and volume fraction of the imbedded magnetic nanoparticles, the properties of the magnet, the micro vessel and the permeability of the micro vessel.

Magnetorelaxometry imaging (MRXI) [1] enables a quantitative and specific localization of magnetic nanoparticles (MNPs) inside living organisms [2] which is required by several novel therapeutic approaches such as magnetic hyperthermia therapy and magnetic drug targeting. MRXI involves aligning the MNPs’ magnetic moments using electromagnetic coils and subsequently recording their decaying net magnetization (relaxation). The recorded signals are connected to the MNP iron masses inside the discretized region of interest (ROI) via a system of linear equations [3]. The MNP distribution is recovered by solving the corresponding ill-posed inverse problem. However, the ROI discretization is limited to rather large voxel sizes. Finer voxel grids increase the number of unknowns and aggravate accurate reconstructions of MNP distributions. To date, finer voxel resolutions with reliable reconstruction accuracies are still necessary to obtain clinically relevant MRXI reconstructions. Standard MRXI provides only information about the MNP distributions and every voxel can contain MNPs with equal probability. Obviously, this is not realistic in clinical practice due to the different anatomical structures inside a human body. Accompanying traditional medical imaging techniques such as CT are necessary to gain anatomical information about the ROI. Here, we develop a multimodal reconstruction using CT data as prior for MRXI reconstructions, enabling a distinction between voxels with impossible, improbable and probable MNP occurrences. We test the approach on a cylindrical ROI (see Fig. 1) containing objects that produce different radiographic density (meat, wood, water, etc.) as well as MNPs. CT and MRXI measurements were conducted and the incorporation of the CT data allows us to reconstruct MNP distributions more accurately with half the voxel edge lengths than with mere MRXI (see Fig. 2). Our multimodal approach demonstrates that resolution and quantification accuracy of MRXI substantially benefits from anatomical data provided by alternative techniques such as CT or MRI.

Ferrofluids are being investigated for cancer treatments such as magnetic drug targeting (MDT) and magnetic heating treatments with the aim of treating the cancer locally, since magnetic nanoparticles with attached drugs are concentrated within the target region. Thus, the side effects are considerably reduced. One of the crucial factors for the success of these therapies is the magnetic nanoparticle distribution. Microcomputed X‐ray tomography (XμCT) has been introduced as adequate technique for non‐destructive three‐dimensional analysis of biological samples enriched with magnetic nanoparticles. The biological tissue specimens, in this case tumor bearing mice after intra‐tumoral magnetic nanoparticle injection, have been analyzed by means of XμCT. Complementary measurements have been performed by magnetorelaxometry (MRX). This technique enables a sensitive quantification of magnetic nanoparticles down to few nanograms. For multi‐phase samples, such as biological tissue enriched with magnetic nanoparticles the polychromasy and beam hardening artifacts occurring in XμCT with conventional X‐ray tubes cause severe problems for quantitative density determination. This problem requires an appropriate calibration of the polychromatic tomography equipment enabling a semi‐quantitative analysis of the data. For this purpose a phantom system has been implemented. These phantoms consist of a tissue substitute containing different amounts of magnetic nanoparticles. Since the attenuation of the beam also depends on the thickness i.e. the path length of the beam transmitting the object, the reference sample has been defined to a cone shape. Thus, with one phantom the information about the magnetic nanoparticle concentration as well as the attenuation in dependence of the path length can be determined. Two phantom systems will be presented, one based on agarose‐gel and one based on soap.

In magnetic drug targeting (MDT), micro- or nanoparticles are injected into the human body to locally deliver therapeutics. These magnetic particles can be guided from a distance by external magnetic fields and gradients from electromagnets. During the particles' movement through the vascular network, they are affected by magnetic forces, fluid (drag) forces, particle interactions, diffusion, etc. Adequate targeting is hindered when drag forces overcome the magnetic forces and particles present in vessels are carried away from the targeted region. Moreover, the magnetic force directions and diffusion mechanisms can cause particles to scatter, while they should remain together for an effective targeting performance. In this work, these adverse effects are tackled using optimizationmethods. We formulate an optimization problem with respect to the currents in surrounding electromagnets that aims to maximize the magnetic force on a particle along a predefined direction. A boundary on the magnetic force divergence is introduced as a constraint to limit particle spreading. We also consider particles to be moved from an initial to a target location in a finite-time interval. To this end dynamic optimization isapplied. Simulations for particles in a bifurcated vessel show an increase of particle speed by 20% and a successful movement towards the targeted regions without spreading. For the dynamic optimization, simulation results demonstrate that particle collections are accurately guided with 10 times less scattering and 10 times more particles at the target than without the divergenceconstraint. The proposed methods significantly improve the steering and capturing of particles in a region of interest. They are applicable to any magnetic drug targeting configuration withelectromagnets.

Delivery of tiny aerosol droplets containing magnetic nanoparticles (MNP) to specific regions in the lungs guided by an external magnetic gradient field is a novel way of Magnetic Drug Targeting, which should allow to deposit high drug doses to a cancerous lung region together with reduced side-effects in unaffected tissue. Currently, this method is investigated in a pig lung model, a model being very similar to the human lung. The development of this procedure requires detailed knowledge about the biodistribution of MNP in different parts of the lung. Magnetorelaxometry (MRX) as a quantitative detection technique is used to determine the MNP distribution throughout the pig lungs after the aerosol targeting application. To this end, we extended our MRX measurement procedure to quantify the magnetic nanoparticle uptake in larger tissue samples with inhomogeneous particle distribution. Here, we present the results of the MRX quantification for an isolated pig lung. The absolute MNP uptake for individual lung lobes and the tissue concentration distribution over the whole lung is provided.Keywordsmagnetic drug targetingmagnetorelaxometrymagnetic nanoparticlesquantificationaerosol therapy

In this paper, we report the design and development of a metamaterial (MTM)-based directional coplanar waveguide (CPW)-fed reconfigurable textile antenna using radiofrequency (RF) varactor diodes for microwave breast imaging. Both simulation and measurement results of the proposed MTM-based CPW-fed reconfigurable textile antenna revealed a continuous frequency reconfiguration to a distinct frequency band between 2.42 GHz and 3.2 GHz with a frequency ratio of 2.33:1, and with a static bandwidth at 4–15 GHz. The results also indicated that directional radiation pattern could be produced at the frequency reconfigurable region and the antenna had a peak gain of 7.56 dBi with an average efficiency of more than 67%. The MTM-based reconfigurable antenna was also tested under the deformed condition and analysed in the vicinity of the breast phantom. This microwave imaging system was used to perform simulation and measurement experiments on a custom-fabricated realistic breast phantom with heterogeneous tissue composition with image reconstruction using delay-and-sum (DAS) and delay-multiply-and-sum (DMAS) algorithms. Given that the MWI system was capable of detecting a cancer as small as 10 mm in the breast phantom, we propose that this technique may be used clinically for the detection of breast cancer.