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Renally Excretable and Size-Tunable Silver Sulfide Nanoparticles for Dual-Energy Mammography or Computed Tomography

ABSTRACT: Significant effort has been focused on developing renally-clearable nanoparticle agents since efficient renal clearance is important for eventual clinical translation. Silver sulfide nanoparticles (Ag2S-NP) have recently been identified as contrast agents for dual energy mammography, computed tomography (CT) and fluorescence imaging and probes for drug delivery and photothermal therapy with good biocompatibility. However, most Ag2S-NP reported to date are not renally excretable and are observed in vivo to accumulate and remain in the reticuloendothelial system (RES) organs, i.e. liver and spleen, for a long time, which could negatively impact their likelihood for translation. Herein, we present renally-clearable, 3.1 nm Ag2S-NP with 85% of the injected dose (ID) being excreted within 24 hours of intravenous injection, which is amongst the best clearance of similarly sized nanoparticles reported thus far (mostly between 20-75% of ID). The urinary excretion and low RES accumulation of these nanoparticles in mice were indicated by in vivo CT imaging and biodistribution analysis. In summary, these ultrasmall Ag2S-NP can be effectively eliminated via urine and have high translational potential for various biomedical applications. Graphical Abstract

SUBMITTER: Hsu J

PROVIDER: S-EPMC7523639 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Project description:Consistent pixel sizes are of fundamental importance for assessing texture features that relate intensity and spatial information in radiomics studies. To correct for the effects of variable pixel sizes, we combined image resampling with Butterworth filtering in the frequency domain and tested the correction on computed tomography (CT) scans of lung cancer patients reconstructed 5 times with pixel sizes varying from 0.59 to 0.98 mm. One hundred fifty radiomics features were calculated for each preprocessing and field-of-view combination. Intra-patient agreement and inter-patient agreement were compared using the overall concordance correlation coefficient (OCCC). To further evaluate the corrections, hierarchical clustering was used to identify patient scans before and after correction. To assess the general applicability of the corrections, they were applied to 17 CT scans of a radiomics phantom. The reduction in the inter-scanner variability relative to non-small cell lung cancer patient scans was quantified. The variation in pixel sizes caused the intra-patient variability to be large (OCCC <95%) relative to the inter-patient variability in 79% of the features. However, with the resampling and filtering corrections, the intra-patient variability was relatively large in only 10% of the features. With the filtering correction, 8 of 8 patients were correctly clustered, in contrast to only 2 of 8 without the correction. In the phantom study, resampling and filtering the images of a rubber particle cartridge substantially reduced variability in 61% of the radiomics features and substantially increased variability in only 6% of the features. Surprisingly, resampling without filtering tended to increase the variability. In conclusion, applying a correction based on resampling and Butterworth low-pass filtering in the frequency domain effectively reduced variability in CT radiomics features caused by variations in pixel size. This correction may also reduce the variability introduced by other CT scan acquisition parameters.

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Renally Excretable and Size-Tunable Silver Sulfide Nanoparticles for Dual-Energy Mammography or Computed Tomography

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