Sensitive magnetic particle imaging of haemoglobin degradation for the detection and monitoring of intraplaque haemorrhage in atherosclerosis.

BACKGROUND

Intraplaque haemorrhage (IPH) drives atherosclerosis progression and is a key imaging biomarker of unstable plaques. Non-invasive and sensitive monitoring of IPH is challenging due to the compositional complexity and dynamic nature of atherosclerotic plaques. Magnetic particle imaging (MPI) is a highly sensitive, radiation-free, and no-tissue-background tomographic technique that detects superparamagnetic nanoparticles. Thus, we aimed to investigate whether MPI can in vivo detect and monitor IPH.

METHODS

Thirty human carotid endarterectomy samples were collected and scanned with MPI. The tandem stenosis (TS) model was employed to establish unstable plaques with IPH in ApoE mice. MPI and 7 T T1-weighted magnetic resonance imaging (MRI) were performed on TS ApoE mice. Plaque specimens were analyzed histologically.

FINDINGS

Human carotid endarterectomy samples exhibited endogenous MPI signals, which histologically colocalized with IPH. In vitro experiments identified haemosiderin, a haemoglobin degradation product, as a potential source of MPI signals. Longitudinal MPI of TS ApoE mice detected IPH at unstable plaques, of which MPI signal-to-noise ratio values increased from 6.43 ± 1.74 (four weeks) to 10.55 ± 2.30 (seven weeks) and reduced to 7.23 ± 1.44 (eleven weeks). In contrast, 7 T T1-weighted MRI did not detect the small-size IPH (329.91 ± 226.82 μm) at four weeks post-TS. The time-course changes in IPH were shown to correlate with neovessel permeability providing a possible mechanism for signal changes over time.

INTERPRETATION

MPI is a highly sensitive imaging technology that allows the identification of atherosclerotic plaques with IPH and may help detect and monitor unstable plaques in patients.

FUNDING

This work was supported in part by the Beijing Natural Science Foundation under Grant JQ22023; the National Key Research and Development Program of China under Grant 2017YFA0700401; the National Natural Science Foundation of China under Grant 62027901, 81827808, 81730050, 81870178, 81800221, 81527805, and 81671851; the CAS Youth Innovation Promotion Association under Grant Y2022055 and CAS Key Technology Talent Program; and the Project of High-Level Talents Team Introduction in Zhuhai City (Zhuhai HLHPTP201703).