MnFe2O4-Fe3O4 core-shell nanoparticles as a potential contrast agent for magnetic resonance imaging

In recent years, magnetic core-shell nanoparticles have received widespread attention due to their unique properties that can be used for various applications. We introduce here a magnetic core-shell nanoparticle system for potential application as a contrast agent in magnetic resonance imaging (MRI). MnFe2O4-Fe3O4 core-shell nanoparticles were synthesized by the wet-chemical synthesis method. Detailed structural and compositional charaterization confirmed the formation of a core-shell microstructure for the nanoparticles. Magnetic charaterization revealed the superparamagnetic nature of the as-synthesized core-shell nanoparticles. Average size and saturation magnetization values obtained for the as-synthesized core-shell nanoparticle were 12.5 nm and 69.34 emu g(-1) respectively. The transverse relaxivity value of the water protons obtained in the presence of the core-shell nanoparticles was 184.1 mM(-1) s(-1). To investigate the effect of the core-shell geometry towards enhancing the relaxivity value, transverse relaxivity values were also obtained in the presence of separately synthesized single phase Fe3O4 and MnFe2O4 nanoparticles. Average size and saturation magnetization values for the as-synthesized Fe3O4 nanoparticles were 12 nm and 65.8 emu g(-1) respectively. Average size and saturation magnetization values for the MnFe2O4 nanoparticles were 9 nm and 61.5 emu g(-1) respectively. The transverse relaxivity value obtained in the presence of single phase Fe3O4 and MnFe2O4 nanoparticles was 96.6 and 83.2 mM(-1) s(-1) respectively. All the nanoparticles (core-shell and single phase) were coated with chitosan by a surfactant exchange reaction before determining the relaxivity values. For similar nanoparticle sizes and saturation magnetization values, the highest value of the transverse relaxivity in the case of core-shell nanoparticles clearly illustrated that the difference in the magnetic nature of the core and shell phases in the core-shell nanoparticles creates greater magnetic inhomogeneity in the surrounding medium yielding a high value for proton relaxivity. The MnFe2O4-Fe3O4 core-shell nanoparticles exhibited extremely low toxicity towards the MCF-7 cell line. Taken together, this opens up new avenues for the use of core-shell nanoparticles in MRI.

Ray tracing based path-length calculations for polarized light tomographic imaging

A ray tracing based path length calculation is investigated for polarized light transport in a pixel space. Tomographic imaging using polarized light transport is promising for applications in optical projection tomography of small animal imaging and turbid media with low scattering. Polarized light transport through a medium can have complex effects due to interactions such as optical rotation of linearly polarized light, birefringence, diattenuation and interior refraction. Here we investigate the effects of refraction of polarized light in a non-scattering medium. This step is used to obtain the initial absorption estimate. This estimate can be used as prior in Monte Carlo (MC) program that simulates the transport of polarized light through a scattering medium to assist in faster convergence of the final estimate. The reflectance for p-polarized (parallel) and s-polarized (perpendicular) are different and hence there is a difference in the intensities that reach the detector end. The algorithm computes the length of the ray in each pixel along the refracted path and this is used to build the weight matrix. This weight matrix with corrected ray path length and the resultant intensity reaching the detector for each ray is used in the algebraic reconstruction (ART) method. The proposed method is tested with numerical phantoms for various noise levels. The refraction errors due to regions of different refractive index are discussed, the difference in intensities with polarization is considered. The improvements in reconstruction using the correction so applied is presented. This is achieved by tracking the path of the ray as well as the intensity of the ray as it traverses through the medium.

Limited-view light sheet fluorescence microscopy for three dimensional volume imaging

We propose and demonstrate a limited-view light sheet microscopy (LV-LSM) for three dimensional (3D) volume imaging. Realizing that longer and frequent image acquisition results in significant photo-bleaching, we have taken limited angular views (18 views) of the macroscopic specimen and integrated with maximum likelihood (ML) technique for reconstructing high quality 3D volume images. Existing variants of light-sheet microscopy require both rotation and translation with a total of approximately 10-fold more views to render a 3D volume image. Comparatively, LV-LSM technique reduces data acquisition time and consequently minimizes light-exposure by many-folds. Since ML is a post-processing technique and highly parallelizable, this does not cost precious imaging time. Results show noise-free and high contrast volume images when compared to the state-of-the-art selective plane illumination microscopy. (C) 2015 AIP Publishing LLC.

Clean localization super-resolution microscopy for 3D biological imaging

We propose clean localization microscopy (a variant of fPALM) using a molecule filtering technique. Localization imaging involves acquiring a large number of images containing single molecule signatures followed by one-to-one mapping to render a super-resolution image. In principle, this process can be repeated for other z-planes to construct a 3D image. But, single molecules observed from off-focal planes result in false representation of their presence in the focal plane, resulting in incorrect quantification and analysis. We overcome this with a single molecule filtering technique that imposes constraints on the diffraction limited spot size of single molecules in the image plane. Calibration with sub-diffraction size beads puts a natural cutoff on the actual diffraction-limited size of single molecules in the focal plane. This helps in distinguishing beads present in the focal plane from those in the off-focal planes thereby providing an estimate of the single molecules in the focal plane. We study the distribution of actin (labeled with a photoactivatable CAGE 552 dye) in NIH 3T3 mouse fibroblast cells. (C) 2016 Author(s).

Framework for morphometric classification of cells in imaging flow cytometry

Imaging flow cytometry is an emerging technology that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy. It allows high-throughput imaging of cells with good spatial resolution, while they are in flow. This paper proposes a general framework for the processing/classification of cells imaged using imaging flow cytometer. Each cell is localized by finding an accurate cell contour. Then, features reflecting cell size, circularity and complexity are extracted for the classification using SVM. Unlike the conventional iterative, semi-automatic segmentation algorithms such as active contour, we propose a noniterative, fully automatic graph-based cell localization. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using custom fabricated cost-effective microfluidics-based imaging flow cytometer. The proposed system is a significant development in the direction of building a cost-effective cell analysis platform that would facilitate affordable mass screening camps looking cellular morphology for disease diagnosis. Lay description In this article, we propose a novel framework for processing the raw data generated using microfluidics based imaging flow cytometers. Microfluidics microscopy or microfluidics based imaging flow cytometry (mIFC) is a recent microscopy paradigm, that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy, which allows us imaging cells while they are in flow. In comparison to the conventional slide-based imaging systems, mIFC is a nascent technology enabling high throughput imaging of cells and is yet to take the form of a clinical diagnostic tool. The proposed framework process the raw data generated by the mIFC systems. The framework incorporates several steps: beginning from pre-processing of the raw video frames to enhance the contents of the cell, localising the cell by a novel, fully automatic, non-iterative graph based algorithm, extraction of different quantitative morphological parameters and subsequent classification of cells. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using cost-effective microfluidics based imaging flow cytometer. The cell lines of HL60, K562 and MOLT were obtained from ATCC (American Type Culture Collection) and are separately cultured in the lab. Thus, each culture contains cells from its own category alone and thereby provides the ground truth. Each cell is localised by finding a closed cell contour by defining a directed, weighted graph from the Canny edge images of the cell such that the closed contour lies along the shortest weighted path surrounding the centroid of the cell from a starting point on a good curve segment to an immediate endpoint. Once the cell is localised, morphological features reflecting size, shape and complexity of the cells are extracted and used to develop a support vector machine based classification system. We could classify the cell-lines with good accuracy and the results were quite consistent across different cross validation experiments. We hope that imaging flow cytometers equipped with the proposed framework for image processing would enable cost-effective, automated and reliable disease screening in over-loaded facilities, which cannot afford to hire skilled personnel in large numbers. Such platforms would potentially facilitate screening camps in low income group countries; thereby transforming the current health care paradigms by enabling rapid, automated diagnosis for diseases like cancer.

Ultrafine graphene oxide-CoFe2O4 nanoparticle composite as T-1 and T-2 contrast agent for magnetic resonance imaging

Graphene oxide-CoFe2O4 nanoparticle composites were synthesized using a two step synthesis method in which graphene oxide was initially synthesized followed by precipitation of CoFe2O4 nanoparticles in a reaction mixture containing graphene oxide. Samples were extracted from the reaction mixture at different times at 80 degrees C. All the extracted samples contained CoFe2O4 nanoparticles formed over the graphene oxide. It was observed that the increase in the reflux time significantly increased the saturation magnetization value for the superparamagnetic nanoparticles in the composite. It was also noticed that the size of the nanoparticles increased with increase in the reflux time. Transverse relaxivity of the water protons increased monotonically with increase in the reflux time. Whereas, the longitudinal relaxivity value initially increased and then decreased with the reflux time. Graphene oxide-CoFe2O4 nanoparticle composites also exhibit biocompatibility towards the MCF-7 cell line.