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WP3: Theory for 360 degree FMT Progress during Year 1. Giannis Zacharakis Institute for Electronic Structure and Laser (IESL) Foundation for Research and Technology – Hellas (FORTH). FMT-XCT First Annual Meeting April 24 2009. In Vivo Optical Imaging Group IESL – FORTH.
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WP3: Theory for 360 degree FMTProgress during Year 1 Giannis Zacharakis Institute for Electronic Structure and Laser (IESL) Foundation for Research and Technology – Hellas (FORTH) FMT-XCT First Annual Meeting April 24 2009
In Vivo Optical Imaging Group IESL – FORTH Cellular and Sub-Cellular Whole Animal Whole animal imaging
Ballistic Propagation (OPT) Ballistic Propagation Beer´s Law ~ exp (-a*z)
FMT Fluorescence Molecular Tomography Diffusion ~ exp (-a*r)/r Highly Scattering
Tomographic imaging Forward problem: Xprop = f [Xinc ; F(r) ] F Inverse problem: F(r) = f-1 [Xinc ; Xprop] Normalized Born Approximation + Homogeneous Medium Iterative Methods (ART), SVD
Normalized measurements hCd2-GFP mouse transgenic age ~ 8 weeks non-transgenic age ~ 8 weeks Control GFP
FORTH’s participation • Objectives • 2.2.3.1 To implement direct inversion based on boundary removal method for media with arbitrary boundaries • 2.2.3.2 To research optimal direct inversion approach with simulations and experimental data • 2.2.3.3 To compare the direct inversion performance with conventional, previously developed FMT inversion methods • 2.2.3.4. To incorporate algorithms for multi-spectral imaging • 2.2.3.5. To develop user friendly software for inversion of XCT-FMT data based on direct inversion approaches • 2.2.3.6. To invert training data acquired from FMT-XCT system for algorithmic finalization
Theory for 360 FMT • Objectives • 2.2.3.1 To implement direct inversion based on boundary removal method for media with arbitrary boundaries • 2.2.3.2 To research optimal direct inversion approach with simulations and experimental data • 2.2.3.3 To compare the direct inversion performance with conventional, previously developed FMT inversion methods
Boundary removal Ripoll and Ntziachristos, PRL 2006.
Boundary removal Assuming the interface locally plane at (R,z0), we can propagate the measurement U to anywhere in (diffuse) space: (first Raleigh-Sommerfield integral formula) • - Use of infinite Green’s functions • - Apply direct inversion • Backpropagation • Complete Fourier Approach (R,z) (R,z0) Original Diffuse Volume (infinite Diffuse Medium - virtual)
Complete Fourier Approach Problem in Real space: Problem in Fourier space: Direct Inversion!
Complete Fourier Approach LIMITATIONS: 1) It can only be used with large numbers of sources Grids of 64x64 sources to obtain relatively good data and are still prone to great Fourier artifacts. This is a great problem since all our FMT setups work with numbers of sources in the 100 range. Having more sources in unpractical, since the experiment times will increase unnecessarily.2) Fluorophore concentration in Fourier space. This means that once inverted the data has to be Inverse-Fourier transformed in 3D. This yields significant Fourier artifacts (seen as 'waves' surrounding the main central points of data) that worsen as the number of sources or detectors gets smaller. This means that in practice even larger numbers of sources need to be used.
Conclusion • After developing and implementing the main features of the direct inversion method, we have decided it is not the method to pursue for our FMT setups. • Clearly we need a method that can solve fast the inversion needed but can work with small numbers of sources, in the order of <100 sources. • We therefore opted to change this deliverable, DIRECT INVERSION method to a deliverable called 'ULTRA FAST INVERSION for FMT' that will be delivered on the next reporting period. • In the meantime, the partners have access to an inversion method which is significantly faster that the currently existing ones, based on: • Boundary removal and ART inversion on the infinite homogeneous data.
Multi-color imaging Objective 2.2.3.4. To incorporate algorithms for multi-spectral imaging • A multispectral algorithm has been developed and tested for simultaneous detection of multiple fluorophores and absorbers. • - It will be incorporated in the FMT software in the next reporting period according to the time schedule.
Multi-color imaging • Two or more fluorophores with overlapping emissions • Detect fluorescence in equal number of channels • In microscopy it is performed pixel-by-pixel • on the so-called spectral cube • In tomography we must perform it voxel-by-voxel • on the Reconstructed Data
Multi-color imaging Tomographic calculations Absorption reconstruction Fluorescence reconstruction In the case of two fluorophores
Phantom study Slab phantom: Intralipid + ink + Agar μs = 16 cm-1, μa = 1.5 cm-1
Phantom study Multicolor Quantification study CFSE: 4μM ATTO590: 5μM, 10μM and 15μM Recover the correct concentrations only when applied on reconstructions
In vivo tissue phantom CFSE: 4μM ATTO590: 5μM, 10μM and 15μM
Tissue oxygenation Use fluorec to segment the oxyrec data
Tissue oxygenation • Image concurrently in 3D • - Fluorescence activity • - Oxygenation in hypoxic regions • - Neo-vascular factors related to tumor proliferation • - Measure dynamic parameters (BV and OxySat) • - Identify cancer stage and phenotype (benign or malignant)
Software development Objective 2.2.3.5. To develop user friendly software for inversion of XCT-FMT data based on direct inversion approaches • Custom developed software based on Labview suitable for: • Data acquisition • Data analysis (OPT and FMT) • Automated user-friendly software for data analysis • Uses open source application for visualization • e.g. ImageJ, Amide, Osirix
Mini-FMT Automated software for FMT acquisition and analysis The main goal of the FMT software is to provide a user-friendly interface to take the measurement data and later perform the 3D reconstruction providing an image that can be analyzed with Open Source applications. e.g. ImageJ, Amide, Osirix There is a complete manual available to the partners with detailed information and guidance for all the functions and parameters. One button reconstruction
FMT data to be shared Objective 2.2.3.6. To invert training data acquired from FMT-XCT system for algorithmic finalization • A large number of experimental measurements have been acquired that are available to all partners for optimization and finalization of algorithms. These measurements involve phantoms as well as in vivo experiments: • Quantification • Resolution • Multispectral • In vivo studies (lymph nodes, tumor progression, oxygenation)
FMT – TOAST comparison Exchange of data with Partner 4UCL Reconstructions by: Athanasios Zacharopoulos
FORTH – LIME data Experiments performed with FORTH-FMT for comparison with LIME-FMT Visit of Anikitos Garofalakis to FORTH
Second Year • Ultra fast inversion for FMT (new Deliverable) • Test and compare the performance • Optimize and finalize Mini-FMT • (feedback from Partners) • Incorporate the multispectral algorithm • (absorption & fluorescence) • Increase the exchange of data! • (essential for joint progress)
In vivo Imaging Group Funding E.U. Integrated Project - “Molecular Imaging” E.U. STREP - “TRANS-REG” E.U. EST – MOLEC IMAG E.U. Collaborative Project – “FMT-XCT” FORTH – IESL/IMBB: E. N. Economou Clio Mamalaki Sifis Papamatheakis Nektarios Tavernarakis IN-VIVO IMAGING GROUP Jorge Ripoll Giannis Zacharakis (Post-doc) Ana Sarasa (Post-doc) Udo Birk (Post-doc) Rosy Favicchio (PhD student) Alex Darell (PhD student) Maria Simantiraki (Msc) Past members Juan Aguirre Abraham Martin Anikitos Garofalakis Heiko Meyer Stelios Psycharakis Sascha Atrops (EST trainee) Olga Kravtsenyuk (Post-doc) Lucie Lambert (EST trainee) Collaborations Dimitris Kioussis Vasilis Ntziachristos Simon Arridge Athanasios Zacharopoulos Bertrand TAvitian Anikitos Garofalakis LIME - CEA
Geometry On going • Inversion: • Use spectra • Wavelength dependent W • Depth dependent W • Spectral unmixing
In vivo tissue phantom ATTO590 (20μM) CFSE (20μM)
Following T-cell numbers Same number of GFP & DsRed T-cells injected Only DsRed cells recognize an antigen peptide Repetitive imaging of cervical lymph nodes