Enabling in vivo imaging in low‐resource settings: Computed tomography imaging of gold‐loaded polymersomes for the detection of glioblastoma

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Authors: Emily Barnett, Joey Lavalla, Pranavi Thatavarthi, Isabel Ray, Taylor Hamas, Jessica Jager, Vaishnavi Kanduri, Jasmine White, Elizabeth Singleton, Jordan Drinks, Megan Pitz, Angela Alexander‐Bryant
+1 more Jessica Larsen
Cited by: 2
References: 63

Abstract

Glioblastoma (GBM) is one of the most aggressive and rapidly progressing brain tumors, characterized by a low survival rate, in part due to insufficient diagnostic tools. Computed tomography (CT), although widely available, is limited in use for GBM diagnosis by the suboptimal performance of current clinically approved contrast agents. This study focuses on the development of gold nanoparticle (AuNP)-loaded polymersomes (AuPs) to improve the detection of GBM. We synthesized polyethylene glycol-b-polylactic acid (PEG-b-PLA) polymersomes with high AuNP loading. Increasing the concentrations of AuNPs in polymersomes resulted in enhanced contrast using clinical CT. Furthermore, AuPs bound to cell-penetrating peptide TAT were cytocompatible with U87-MG GBM cells at concentrations up to 100 mg/mL. Uptake studies using both fluorescence microscopy and flow cytometry confirmed the internalization of AuPs into GBM cells, with a direct correlation between AuP concentration and uptake efficiency. MicroCT imaging also confirmed a similar trend; >300% enhanced contrast compared to PBS controls was observed with increasing concentrations of AuPs and was maintained in vivo at 337-863 HU. Overall, these results demonstrate that a polymersome-based system for AuNPs enhances CT image contrast, suggesting that this approach could be feasible for improving GBM detection via CT.

Fields of Study & Subjects

Nanoparticle-Based Drug Delivery Gold and Silver Nanoparticles Synthesis and Applications Nanoplatforms for cancer theranostics

Publication details

Journal / source
Bioengineering & Translational Medicine
Publisher
Wiley
Volume
11
Issue
3
Pages
e70109–e70109
Publication date
27 January 2026
Language
EN