Commentary on “a microfluidic platform to design crosslinked hyaluronic acid nanoparticles (cHANPs) for enhanced MRI”

Maria Russo, Paolo Bevilacqua, Paolo Antonio Netti, Enza Torino

Research output: Contribution to journalComment/debate

4 Citations (Scopus)

Abstract

Strategies to enhance the relaxometric properties of gadolinium (Gd)-based contrast agents (CAs) for magnetic resonance imaging (MRI), without the chemical modification of chelates, have recently had a strong impact on the diagnostic field. We have taken advantage of the interaction between Gadolinium diethylenetriamine penta-acetic acid (Gd-DTPA) and the hydrogel structure of hyaluronic acid to design cross-linked hyaluronic acid nanoparticles down to 35 nm for use in MRI applications. The proposed bioformulations enable the control of the relaxometric properties of CAs, thus boosting the relaxation rate of T1. Our results led us to identify this approach as an adjustable scenario to design intravascularly injectable hydrogel nanoparticles entrapping Gd-DTPA. This approach overcomes the general drawbacks of clinically approved CAs having poor relaxivity and toxic effects.

Original languageEnglish
JournalMolecular Imaging
Volume16
DOIs
Publication statusPublished - Jan 1 2017

Fingerprint

Hyaluronic acid
Microfluidics
Gadolinium
Hyaluronic Acid
Magnetic resonance
gadolinium
Nanoparticles
Contrast Media
magnetic resonance
platforms
Hydrogel
Magnetic Resonance Imaging
Imaging techniques
Hydrogels
nanoparticles
acids
Gadolinium DTPA
Rubiaceae
Poisons
Chemical modification

Keywords

  • Gadolinium-based contrast agents
  • Imaging
  • Microfluidics
  • MRI
  • Nanoparticles

ASJC Scopus subject areas

  • Biotechnology
  • Molecular Medicine
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging
  • Condensed Matter Physics

Cite this

Commentary on “a microfluidic platform to design crosslinked hyaluronic acid nanoparticles (cHANPs) for enhanced MRI”. / Russo, Maria; Bevilacqua, Paolo; Netti, Paolo Antonio; Torino, Enza.

In: Molecular Imaging, Vol. 16, 01.01.2017.

Research output: Contribution to journalComment/debate

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