Gamma-Camera Direct Imaging of the Plasma and On/Intra Cellular Distribution of the 99m Tc-DPD-Fe 3 O 4 Dual-Modality Contrast Agent in Peripheral Human Blood.
Maria-Argyro KarageorgouAdamantia ApostolopoulouMina-Ermioni TomazinakiDragana StankovićEfstathios StiliarisPenelope BouziotisDimosthenis StamopoulosPublished in: Materials (Basel, Switzerland) (2024)
The radiolabeled iron oxide nanoparticles constitute an attractive choice to be used as dual-modality contrast agents (DMCAs) in nuclear medical diagnosis, due to their ability to combine the benefits of two imaging modalities, for instance single photon emission computed tomography (SPECT) with magnetic resonance imaging (MRI). Before the use of any DMCA, the investigation of its plasma extra- and on/intra cellular distribution in peripheral human blood is of paramount importance. Here, we focus on the in vitro investigation of the distribution of 99m Tc-DPD-Fe 3 O 4 DMCA in donated peripheral human blood (the ligand 2-3-dicarboxypropane-1-1-diphosphonic-acid is denoted as DPD). Initially, we described the experimental methods we performed for the radiosynthesis of the 99m Tc-DPD-Fe 3 O 4 , the preparation of whole blood and blood plasma samples, and their incubation conditions with 99m Tc-DPD-Fe 3 O 4 . More importantly, we employed a gamma-camera apparatus for the direct imaging of the 99m Tc-DPD-Fe 3 O 4 -loaded whole blood and blood plasma samples when subjected to specialized centrifugation protocols. The direct comparison of the gamma-camera data obtained at the exact same samples before and after their centrifugation enabled us to clearly identify the distribution of the 99m Tc-DPD-Fe 3 O 4 in the two components, plasma and cells, of peripheral human blood.
Keyphrases
- endothelial cells
- magnetic resonance imaging
- computed tomography
- high resolution
- induced pluripotent stem cells
- contrast enhanced
- pluripotent stem cells
- healthcare
- drug delivery
- palliative care
- high speed
- machine learning
- induced apoptosis
- mass spectrometry
- convolutional neural network
- oxidative stress
- cell death
- cell proliferation
- deep learning
- pet imaging
- decision making
- density functional theory
- pi k akt