Abstract

Histology is a long standing and well-established gold standard for pathological characterizations. In recent years however, synchrotron radiation-based micro-computed tomography (SRμCT) has become a tool for extending the imaging of two-dimensional thin sections into three-dimensional imaging of tissue blocks, enabling so-called virtual histology with arbitrary clipping planes, volumetric rendering and automatic segmentation. In this study, we present a thorough characterization of human carotid plaques after endarterectomy of patients with stroke or transient ischemic attack (TIA), investigating several different pathologic structures using both SRμCT and histology. Phase-contrast SRμCT was performed with two different magnifications (voxel sizes 6.5 μm and 0.65 μm, respectively), and histology was performed with multiple different stainings (Alpha-actin, Glycophorin A, von Kossa, Movat, CD68). The 0.65 μm high-resolution SRμCT was performed on selected areas with plaque typical relevant morphology, identified on the 6.5 μm low-resolution SRμCT. The tomography datasets were reconstructed with additional 3D volume rendering and compared to histology. In total, nine different regions with typical pathologic structures were identified and imaged with high-resolution SRμCT. The results show many characteristics typical for advanced atherosclerotic plaques, clinically relevant, namely ruptures with thrombosis, neo-vascularization, inflammatory infiltrates in shoulder regions, lipid rich necrotic cores (LRNC), thin fibrous cap, calcifications, lumen irregularities, and changes in vessel wall structures such as the internal elastic membrane. This method’s non-destructive nature renders details of micro-structures with an excellent visual likeness to histology, with the additional strength of multiplanar and 3D visualization and the possibility of multiple re-scans.
Original languageEnglish
Article numbere0265598
Pages (from-to)1-18
JournalPLoS ONE
Volume17
Issue number4
DOIs
Publication statusPublished - 2022

Subject classification (UKÄ)

  • Medical Image Processing
  • Otorhinolaryngology

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