Targeted PET Imaging of Atherosclerosis via Low-Density Lipoprotein Click Chemistry with Nanoparticles

Low-density lipoprotein (LDL) plays a central role in the development of atherosclerosis, making its detection critical for cardiovascular disease management. Radionuclide imaging of LDL offers distinct advantages over other modalities but remains limited by poor specificity and the need for long-lived isotopes. We present a click chemistry-based PET imaging strategy using gallium-68 (68Ga), a short-lived radionuclide, for the specific detection of LDL accumulation in atherosclerotic plaques. The approach relies on a two-step inverse electron-demand Diels–Alder reaction between trans-cyclooctene (TCO)-modified LDL and tetrazine-functionalized iron oxide nanoparticles radiolabeled with 68Ga. In vivo PET/CT imaging in LDL receptor-deficient (LDLr–/–) mice showed selective uptake of the nanoparticles in atherosclerotic lesions, with minimal signal in wild-type controls. This method demonstrated high specificity and sensitivity, while reducing background signal and radiation exposure. Our results support the potential of this approach as a noninvasive and translatable platform for early diagnosis and risk assessment in cardiovascular disease.

Authors

Institutions

Publication Details

Journal
Chemical & Biomedical Imaging
Published
2025-11-06
DOI
https://doi.org/10.1021/cbmi.5c00147
Primary Topic
Cerebrovascular and Carotid Artery Diseases
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Targeted PET Imaging of Atherosclerosis via Low-Density Lipoprotein Click Chemistry with Nanoparticles

Juan Pellico, Jacob Fog Bentzon, Paula Nogales, María Muñoz-Hernando et al.
Chemical & Biomedical Imaging
Cerebrovascular and Carotid Artery Diseases
article

Targeted PET Imaging of Atherosclerosis via Low-Density Lipoprotein Click Chemistry with Nanoparticles

Juan Pellico, Jacob Fog Bentzon, Paula Nogales, María Muñoz-Hernando, Fernando Herranz
article en

Abstract

Low-density lipoprotein (LDL) plays a central role in the development of atherosclerosis, making its detection critical for cardiovascular disease management. Radionuclide imaging of LDL offers distinct advantages over other modalities but remains limited by poor specificity and the need for long-lived isotopes. We present a click chemistry-based PET imaging strategy using gallium-68 (68Ga), a short-lived radionuclide, for the specific detection of LDL accumulation in atherosclerotic plaques. The approach relies on a two-step inverse electron-demand Diels–Alder reaction between trans-cyclooctene (TCO)-modified LDL and tetrazine-functionalized iron oxide nanoparticles radiolabeled with 68Ga. In vivo PET/CT imaging in LDL receptor-deficient (LDLr–/–) mice showed selective uptake of the nanoparticles in atherosclerotic lesions, with minimal signal in wild-type controls. This method demonstrated high specificity and sensitivity, while reducing background signal and radiation exposure. Our results support the potential of this approach as a noninvasive and translatable platform for early diagnosis and risk assessment in cardiovascular disease.

Chemical & Biomedical Imaging
Aarhus University (DK), Spanish National Centre for Cardiovascular Research (ES), Artifex University (RO), Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (ES), Instituto de Química Médica (ES), Institut de Ciència de Materials de Barcelona (ES), Institute for Atherosclerosis Research (RU), National Institute of Design (IN)
Openalex Percentile: Top 53%
Cerebrovascular and Carotid Artery Diseases
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.