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Multiplex K-Edge Nanoprobe Imaging Enables 3D Volumetric Molecular Phenotyping of Human Hematoma Membranes

Sep 2026 · ACS Nano · Vol 20, pp. 25318-25334 · 36 references
Advanced X-ray and CT Imaging

Abstract

Abstract Spectral photon-counting computed tomography (SPCCT) enables material-resolved imaging through K-edge discrimination, yet its application to multiplexed molecular mapping of human surgical specimens remains underexplored. Here, we report a clinically relevant multiplex K-edge imaging strategy and demonstrate its utility directly in human chronic subdural hematoma (CSDH) membranes. SPCCT-derived human data was obtained by treating patient tissues with a rationally designed and engineered dual K-edge nanopair composed of hafnium oxide (K-edge 65.3 keV) and gold (K-edge 80.3 keV) nanoparticles to simultaneously and ratiometrically map angiogenic (αvβ3) and fibrotic (fibrin) markers in the CSDH microenvironment. This nanopair provides optimized spectral separation necessary for multiplexed molecular phenotyping in human samples with high accuracy. Guided by signal separation physics, the nanopair was designed to minimize energy bin overlaps and maximize the signal-to-noise ratio in quantitative material decomposition maps. Using a calibrated phantom protocol on a Medipix3RX-based SPCCT system, we achieved accurate quantification of both elements at low millimolar concentrations. Surface-engineered hafnium nanoprobes functionalized with cyclic RGD peptides and gold nanoprobes conjugated to antifibrin antibodies enabled target-specific accumulation in distinct pathological microenvironments. Human data was analyzed as three-dimensional multicolor reconstructions that revealed simultaneous, voxel-level mapping of spatially distinct angiogenic and fibrotic microenvironments, which were validated by machine-learning-assisted immunohistochemistry quantification. These findings demonstrate the utility of a nanomaterial-driven, multiplex K-edge imaging framework for volumetric molecular phenotyping of human tissues and advance SPCCT toward quantitative, multicontrast translational imaging.

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