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

Abstract

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 invivo detect and monitor IPH. 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 7TT1-weighted magnetic resonance imaging (MRI) were performed on TS ApoE-/- mice. Plaque specimens were analyzed histologically. Human carotid endarterectomy samples exhibited endogenous MPI signals, which histologically colocalized with IPH. Invitro 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, 7TT1-weighted MRI did not detect the small-size IPH (329.91±226.82μm2) 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. 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. 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).