Stimulated Raman scattering tomography for rapid three-dimensional chemical imaging of cells and tissue

Three-dimensional(3D)imaging is essential for understanding intricate biological and biomedical systems,yet live cell and tissue imaging applications still face challenges due to constrained imaging speed and strong scattering in turbid media.Here,we present a unique phase-modulated stimulated Raman scattering tomography(PM-SRST)technique to achieve rapid label-free 3D chemical imaging in cells and tissue.To accomplish PM-SRST,we utilize a spatial light modulator to electronically manipulate the focused Stokes beam along the needle Bessel pump beam for SRS tomography without the need for mechanical z scanning.We demonstrate the rapid 3D imaging capability of PM-SRST by real-time monitoring of 3D Brownian motion of polystyrene beads in water with 8.5 Hz volume rate,as well as the instant biochemical responses to acetic acid stimulants in MCF-7 cells.Further,combining the Bessel pump beam with a longer wavelength Stokes beam(NIR-II window)provides a superior scattering resilient ability in PM-SRST,enabling rapid tomography in deeper tissue areas.The PM-SRST technique providestwofold enhancement in imaging depth in highly scattering media(e.g.,polymer beads phantom and biotissue like porcine skin and brain tissue)compared with conventional point-scan SRS.We also demonstrate the rapid 3D imaging ability of PM-SRST by observing the dynamic diffusion and uptake processes of deuterium oxide molecules into plant roots.The rapid PM-SRST developed can be used to facilitate label-free 3D chemical imaging of metabolic activities and functional dynamic processes of drug delivery and therapeutics in live cells and tissue.

Material discrimination using cosmic ray muon scattering tomography with an artificial neural network

Introduction Muon scattering tomography(MST)can be employed to scan cargo containers and vehicles for special nuclear materials by using cosmic muons.However,the flux of cosmic ray muons is relatively low for direct detection.Thus,the detection has to be done in a short timescale with small numbers of muons to satisfy the demands of practical applications.Method In this paper,we propose an artificial neural network(ANN)algorithm for material discrimination using MST.The muon scattering angles were simulated using Geant4 to formulate the training set,and the muon scatter angles were measured by Micromegas detection system to create the test set.Results The ANN-based algorithm presented here ensures a discrimination accuracy of 98.0%between aluminum,copper and tungsten in a 5 min measurement of 4×4×4 cm^(3)blocks.

A Compton scattering image reconstruction algorithm based on total variation minimization

Compton scattering imaging is a novel radiation imaging method using scattered photons.Its main characteristics are detectors that do not have to be on the opposite side of the source,so avoiding the rotation process.The reconstruction problem of Compton scattering imaging is the inverse problem to solve electron densities from nonlinear equations,which is ill-posed.This means the solution exhibits instability and sensitivity to noise or erroneous measurements.Using the theory for reconstruction of sparse images,a reconstruction algorithm based on total variation minimization is proposed.The reconstruction problem is described as an optimization problem with nonlinear data-consistency constraint.The simulated results show that the proposed algorithm could reduce reconstruction error and improve image quality,especially when there are not enough measurements.

Simultaneous fluorescence and Compton scattering computed tomography based on linear polarization X-ray

Purpose To propose a method for simultaneous fluorescence and Compton scattering computed tomography by using linearly polarized X-rays.Methods Monte Carlo simulations were adopted to demonstrate the feasibility of the proposed method.In the simulations,the phantom is a polytetrafluoroethylene cylinder inside which are cylindrical columns containing aluminum,water,and gold(Au)-loaded water solutions with Au concentrations ranging between 0.5 and 4.0 wt%,and a parallel-hole collimator imaging geometry was adopted.The light source was modeled based on a Thomson scattering X-ray source.The phantom images for both imaging modalities were reconstructed using a maximumlikelihood expectation maximization algorithm.Results Both the X-ray fluorescence computed tomography(XFCT)and Compton scattering computed tomography(CSCT)images of the phantom were accurately reconstructed.A similar attenuation contrast problem for the different cylindrical columns in the phantom can be resolved in the XFCT and CSCT images.The interplay between XFCT and CSCT was analyzed,and the contrast-to-noise ratio(CNR)of the reconstruction was improved by correcting for the mutual influence between the two imaging modalities.Compared with K-edge subtraction imaging,XFCT exhibits a CNR advantage for the phantom.Conclusion Simultaneous XFCT and CSCT can be realized by using linearly polarized X-rays.The synergy between the two imaging modalities would have an important application in cancer radiation therapy.