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MRI detection of senescent cells in porcine knee joints with a β-galactosidase responsive Gd-chelate

  • 0Molecular Imaging Program at Stanford (MIPS), Department of Radiology, Stanford University School of Medicine, Stanford, CA 94305 USA.
Npj Imaging +

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May 7, 2025

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May 7, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

Senescent cells drive osteoarthritis. A novel MRI contrast agent detects these cells via beta-galactosidase (β-gal) activity, offering a new tool for diagnosis and treatment monitoring.

Area Of Science

  • Biomedical Imaging
  • Cellular Biology
  • Osteoarthritis Research

Background

  • Senescent cells contribute to osteoarthritis (OA) pathogenesis by releasing inflammatory factors.
  • Senescence-associated beta-galactosidase (β-gal) is a biomarker for senescent cells, but in vivo detection is difficult.
  • Current methods for senescent cell detection in OA are limited, hindering targeted therapies.

Purpose Of The Study

  • To evaluate a novel β-gal responsive gadolinium (Gd) chelate for non-invasive detection of senescent cells using clinical MRI.
  • To assess the probe's efficacy in vitro, ex vivo, and in vivo in a preclinical porcine model of osteoarthritis.

Main Methods

  • Development and testing of a β-gal responsive Gd-chelate contrast agent.
  • In vitro experiments using senescent and viable mesenchymal stromal cells (MSCs).
  • In vivo studies involving intraarticular injection into porcine knee joints with induced cartilage defects, followed by MRI analysis.

Main Results

  • Senescent MSCs showed significant MRI signal enhancement with the Gd-chelate in vitro compared to control cells.
  • In vivo, the probe localized to cartilage defects and was activated by senescent cells, indicated by increased R1 relaxation rates.
  • MRI successfully detected β-gal expressing senescent cells in porcine joints.

Conclusions

  • MRI with a β-gal responsive Gd-chelate can non-invasively detect senescent cells in vivo.
  • This approach shows potential for identifying OA patients who may benefit from senolytic therapies.
  • The technology could enable personalized treatment strategies and real-time monitoring of therapeutic responses.

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