Size reproducibility of gadolinium oxide based nanomagnetic particles for cellular magnetic resonance imaging: effects of functionalization, chemisorption and reaction conditions

We developed biofunctionalized nanoparticles with magnetic properties by immobalizing diethyleneglycol [DEG] on Gd[2]O[3], and PEGilation of small particulate gadolinium oxide [SPGO] with two methoxy-polyethyleneglycol-silane [mPEG-Silane 550 and 2000 Da] using a new supervised polyol route, described recently. In conjunction to the previous study to achieve a high quality synthesis and increase in the product yield of nanoparticles; assessment of the effects of functionalization, chemisorption and altered reaction conditions, such as NaOH concentration, temperature, reaction time and their solubility, on size reproducibility were determined as the goals of this study. Moreover, the effects of centrifuga-tion, filtration and dialysis of the solution on the non magnetic particle size values and their stability against aggregation have been evaluated. Optimization of reaction parameters led to strong coating of magnetic nanoparticles with the ligands which increases the reproducibility of particle size measurements. Furthermore, the ligand-coated nanoparticles showed enhanced colloidal stability as a result of the steric stabilization function of the ligands grafted on the surface of particles. The experiments showed that DEG and mPEG-silane [550 and 2000 Dalton] are chemisorbed on the particle surfaces of Gd[2]O[3] and SPGO which led to particle sizes of 5.9 +/- 0.13 nm, 51.3 +/- 1.46 nm and 194.2 +/- 22.1 nm, respectively. The small size of DEG- Gd[2]O[3] is acceptably below the cutoff of 6nm, enabling easy diffusion through lymphatics and filtration from kidney, and thus provides a great deal of potential for further in-vivo and in-vitro application

Platelet-based MPLE algorithm for denoising of SPECT Images: phantom and patient study

In this study the evaluation of a Platelet-based Maximum Penalized Likelihood Estimation [MPLE] for denoising SPECT images was performed and compared with other denoising methods such as Wavelets or Butterworth filtration. Platelet-based MPLE factorization as a multiscale decomposition approach has been already proposed for better edges and surfaces representation due to Poisson noise and inherent smoothness of this kind of images. We applied this approach on both simulated and real SPECT images. Monte Carlo simulations were generated with the SIMSET package to model the physical processes and instrumentation used in emission imaging. Cardiac, brain and NEMA phantom SPECT images were obtained using a single-head, Argus model SPECT system. The performance of this method has been evaluated both qualitatively and quantitatively with power spectrum, SNR and noise level measurements on simulated and real SPECT images. For NEMA phantom images, the measured noise levels before [M[b]] and after [M[a]] denoising with Platelet-based MPLE approach were M[b]=2.1732, M[a]=0.1399. In patient study for 32 cardiac SPECT images, the difference between noise level and SNR before and after the approach were [M[b]=3.7607, SNR[b]=9.7762, M[a]=0.7374, SNR[a]41.0848] respectively. Thus the Coefficient of variance [C.V] of SNR values for denoised images with this algorithm as compared with Butterworth filter, [145/33%] was found. For 32 brain SPECT images the Coefficient Variance of SNR values, [196/17%] was obtained. Our results shows that, Platelet-based MPLE is a useful method for denoising SPECT images considering better homogenous image, improvements in SNR, better radioactive uptake in target organ and reduction of interfering activity from background radiation in comparison to that of other conventional denoising methods