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.

Sparse reconstruction for fluorescence molecular tomography via a fast iterative algorithm

Fluorescence molecular tomography(FMT)is a fast-developing optical imaging modalitythat has great potential in early diagnosis of disease and drugs development.However,recon-struction algorithms have to address a highly ill-posed problem to fulfll 3D reconstruction inFMT.In this contribution,we propose an efficient iterative algorithm to solve the large-scalereconstruction problem,in which the sparsity of fluorescent targets is taken as useful a prioriinformation in designing the reconstruction algorithm.In the implementation,a fast sparseapproximation scheme combined with a stage-wise learning strategy enable the algorithm to dealwith the ill-posed inverse problem at reduced computational costs.We validate the proposed fastiterative method with numerical simulation on a digital mouse model.Experimental results demonstrate that our method is robust for different finite element meshes and different Poissonnoise levels.

A SIMULATION STUDY ON DYNAMIC-SAMPLING-MODE FOR FLUORESCENCE MOLECULAR TOMOGRAPHY

Fluorescence tomography can obtain a sufficient dataset and optimal three-dimensional imageswhen projections are captured over 360◦ by CCD camera. Herein a non-stop dynamic samplingmode for fluorescence tomography is proposed in an attempt to improve the optical measurementspeed of the traditional imaging system and stability of the object to be imaged. A series ofsimulations are carried out to evaluate the accuracy of dataset acquired from the dynamicsampling mode. Reconstruction with the corresponding data obtained in the dynamic-modeprocess is also performed with the phantom. The results demonstrate the feasibility of suchan imaging mode when the angular velocity is set to the appropriate value, thus laying thefoundation for real experiments to verify the superiority in performance of this new imagingmode over the traditional one.

Recent methodology advances in fluorescence molecular tomography

Molecular imaging(MI)is a novel imaging discipline that has been continuously developed in recent years.It combines biochemistry,multimodal imaging,biomathematics,bioinformatics,cell&molecular physiology,biophysics,and pharmacology,and it provides a new technology platform for the early diagnosis and quantitative analysis of diseases,treatment monitoring and evaluation,and the development of comprehensive physiology.Fluorescence Molecular Tomography(FMT)is a type of optical imaging modality in MI that captures the three-dimensional distribution of fluorescence within a biological tissue generated by a specific molecule of fluorescent material within a biological tissue.Compared with other optical molecular imaging methods,FMT has the characteristics of high sensitivity,low cost,and safety and reliability.It has become the research frontier and research hotspot of optical molecular imaging technology.This paper took an overview of the recent methodology advances in FMT,mainly focused on the photon propagation model of FMT based on the radiative transfer equation(RTE),and the reconstruction problem solution consist of forward problem and inverse problem.We introduce the detailed technologies utilized in reconstruction of FMT.Finally,the challenges in FMT were discussed.This survey aims at summarizing current research hotspots in methodology of FMT,fromwhich future research may benefit.

OPTIMIZATION OF DESIGN PARAMETERS FOR FLUORESCENCE LAMINAR OPTICAL TOMOGRAPHY

Laminar optical tomography(LOT)is a mesoscopic tomographic imaging technique ranging between confocal microscopy and diffuse optical tomography(DOT).Fluorescence LOT(FLOT)provides depth-resolved molecular information with 100-200μm resolution over 2-3mm depth.In this study,we use Monte Carlo simulation and singular-value analysis(SVA)to optimize the source-detector configurations for potential enhancement of FLOT imaging performance.The effects of different design parameters,including source incidence and detector collection angles,detector number,and sampling density,are presented.The results indicate that angled incidence/detection configuration might improve the imaging resolution and depth sensitivity,especially for low-scattering medium.Increasing the number of detectors and the number of scanning steps will also result in enhanced imaging performance.We also demonstrate that the optimal imaging performance depends upon the background scattering coe±cient.Our result might provide an optimization strategy for FLOT or LOT experimental setup.

IN VIVO VALIDATION OF DUAL-MODALITY SYSTEM FOR SIMULTANEOUS POSITRON EMISSION TOMOGRAPHY AND OPTICAL TOMOGRAPHIC IMAGING

We report on tests of combined positron emission tomography(PET)andfluorescence molecular tomography(FMT)imaging system for in vivo investigation on small animals.A nude mouse was inoculated with MD-MB-231 breast cancer cells which expressed redfluorescent protein(RFP).For FMT system,reflective illumination mode was adopted with full-angle data acquisition.[18F]-Fluorodeoxyglucose([18F]-FDG)was used as radioactive tracer for PET.Both data were acquired simultaneously and then reconstructed separately before fusion.Fluorescent tomography results showed exactly where the tumor was located while PET results offered more metabolic information.Results confirmed feasibility for tumor detection and showed superiority to single modality imaging.

2D Shape-based Fluorescence Molecular Tomography Through Hybrid Genetic Algorithm Based Optimization

Fluorescence molecular tomography(FMT) aims at tomographicallyresolving the fluorescent targets deeply inside small animal based on transmission boundary measurements. The image reconstruction of FMT isknown to be highlyill-posed, due to the highly scatteringnatureofbiologicaltissue.Hence,priorinformationisusuallyrequired for successful reconstruction. In this paper, a novel reconstruction method incorporating shape priors is proposed for 2D FMT. The fluorescent targets were assumed of round shape, which was practically appropriate for approximating various shapes inside diffusive medium. Compared to the traditional pixel based reconstruction, the number of unknowns was greatly reduced to a few control parameters of round shapes. A hybrid genetic algorithm was proposed to recover the shape parameters. The numerical experiments showed that the proposed method significantly improves the imaging accuracy, offering clearer target boundaries and better resolution. Comparison results also demonstrated that the hybridization of genetic algorithm and Newton-typesearchwaspivotalandimportantforrobustlyfindingthegloballyoptimalshape parameters.

On the road towards the global analysis of human synapses

Synapses are essential units for the flow of information in the brain.Over the last 70 years,synapses have been widely studied in multiple animal models including worms,fruit flies,and rodents.In comparison,the study of human synapses has evolved significantly slower,mainly because of technical limitations.However,three novel methods allowing the analysis of molecular,morphological,and functional properties of human synapses may expand our knowledge of the human brain.Here,we briefly describe these methods,and evaluate how the information provided by each unique approach may contribute to the functional and anatomical analysis of the synaptic component of human brain circuitries.In particular,using tissue from cryopreserved human brains,synaptic plasticity can be studied in isolated synaptosomes by fluorescence analysis of single-synapse long-term potentiation（FASS-LTP）,and subpopulations of synapses can be thoroughly assessed in the ribbons of brain tissue by array tomography（AT）.Currently,it is also possible to quantify synaptic density in the living human brain by positron emission tomography（PET）,using a novel synaptic radio-ligand.Overall,data provided by FASS-LTP,AT,and PET may significantly contribute to the global understanding of synaptic structure and function in both healthy and diseased human brains,thus directly impacting translational research.

Recent Developments in Numerical Techniques for Transport-Based Medical Imaging Methods

The objective of this paper is to review recent developments in numerical reconstruction methods for inverse transport problems in imaging applications,mainly optical tomography,fluorescence tomography and bioluminescence tomography.In those inverse problems,one aims at reconstructing physical parameters,such as the absorption coefficient,the scattering coefficient and the fluorescence light source,inside heterogeneous media,from partial knowledge of transport solutions on the boundaries of the media.The physical parameters recovered can be used for diagnostic purpose.Numerical reconstruction techniques for those inverse transport problems can be roughly classified into two categories:linear reconstruction methods and nonlinear reconstruction methods.In the first type of methods,the inverse problems are linearized around some known background to obtain linear inverse problems.Classical regularization techniques are then applied to solve those inverse problems.The second type of methods are either based on regularized nonlinear least-square techniques or based on gradient-driven iterative methods for nonlinear operator equations.In either case,the unknown parameters are iteratively updated until the solutions of the transport equations with the those parameters match the measurements to a certain extent.We review linear and nonlinear reconstruction methods for inverse transport problems in medical imaging with stationary,frequency-domain and time-dependent data.The materials presented include both existing and new results.Meanwhile,we attempt to present similar algorithms for different problems in the same framework to make it more straightforward to generalize those algorithms to other inverse(transport)problems.

A strategy for enhanced tumor targeting of photodynamic therapy based on Escherichia coli-driven drug delivery system

Escherichia coli(E. coli) DH5α has been recognized as a non-pathogenic bacterial strain with tumor colonization ability. However, whether such a bacteria-driven drug-delivery system can improve the targeting of tumor therapy or not remains essentially untouched. Herein, a series of zinc phthalocyanine(ZnPc) photosensitizers with different numbers of charges were prepared and their electrostatic adhesion properties on E. coli were investigated via measuring their fluorescence intensities by flow cytometer. Among these ZnPc photosensitizers investigated, the ZnPc conjugate with four positive charges(named ZnPc-IR710) exhibited the highest loading capacity and the best fluorescence imaging performance of E. coli. With the help of E. coli, E. coli@ZnPcIR710 presented a significantly enhanced cytotoxicity on human breast cancer MCF-7 cells compared with ZnPc-IR710(survival rate of tumor cells was 39% vs. 57% at a concentration of 50 nmol L-1). Moreover, in vivo study showed that E. coli@ZnPc-IR710 remarkably inhibited the tumor growth and resulted in a complete tumor growth suppress in subcutaneous mouse 4T1 breast tumor model. These results demonstrated the great promise of bacterial-guided photodynamic therapy(PDT) in the treatment of solid tumors, and provide a unique strategy to enhance the antitumor efficacy of PDT by utilizing bacterial vectors in tumors.