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Enhancing the Throughput of FT Mass Spectrometry Imaging Using Joint Compressed Sensing and Subspace Modeling
journal contribution
posted on 2022-03-24, 20:29 authored by Yuxuan
Richard Xie, Daniel C. Castro, Stanislav S. Rubakhin, Jonathan V. Sweedler, Fan LamMass
spectrometry imaging (MSI) allows for untargeted mapping of
the chemical composition of tissues with attomole detection limits.
MSI using Fourier transform (FT)-based mass spectrometers, such as
FT-ion cyclotron resonance (FT-ICR), grants the ability to examine
the chemical space with unmatched mass resolution and mass accuracy.
However, direct imaging of large tissue samples using FT-ICR is slow.
In this work, we present an approach that combines the subspace modeling
of ICR temporal signals with compressed sensing to accelerate high-resolution
FT-ICR MSI. A joint subspace and spatial sparsity constrained model
computationally reconstructs high-resolution MSI data from the sparsely
sampled transients with reduced duration, allowing a significant reduction
in imaging time. Simulation studies and experimental implementation
of the proposed method in investigation of brain tissues demonstrate
a 10-fold enhancement in throughput of FT-ICR MSI, without the need
for instrumental or hardware modifications.
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sparsely sampled transientsion cyclotron resonanceattomole detection limitsicr temporal signalsicr ), grantsunmatched mass resolutionbrain tissues demonstrateresolution msi datamass accuracyicr msiresolution ftuntargeted mappingsubspace modelingsimulation studiessignificant reductionreduced durationproposed methodjoint subspaceimaging timehardware modificationsfold enhancementexperimental implementationdirect imagingcompressed sensingchemical spacechemical compositionaccelerate high