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Multi-Spectral Optoacoustic Tomography: Methods and Applications

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Multi-Spectral Optoacoustic Tomography: Methods and Applications TECHNISCHE UNIVERSITÄT MÜNCHEN Lehrstuhl für Biologische Bildgebung Multi-Spectral Optoacoustic Tomography: Methods and Applications Andreas B. Bühler Vollständiger Abdruck der von der Fakultät für Elektrotechnik und Informationstechnik der Technischen Universität München zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften (Dr. rer. nat.) genehmigten Dissertation. Vorsitzender: Univ.-Prof. Dr. Samarjit Chakraborty Prüfer der Dissertation: 1. Univ.- Prof. Vasilis Ntziachristos, Ph. D. 2. Univ.- Prof. Dr. Axel Haase Die Dissertation wurde am 26.07.2013 bei der Technischen Universität München eingereicht und durch die Fakultät für Elektrotechnik und Informationstechnik am 09.06.2014 angenommen. ii Abstract Macroscopic optical small animal imaging plays an increasingly important role in biomedical research, as it can noninvasively examine structural, physiological, and molecular tissue features in vivo. A novel modality that emerged in the last decade is optoacoustic (photoacoustic) imaging, which combines versatile optical absorption contrast with high ultrasonic resolution and real-time imaging capabilities by capitalizing on the optoacoustic (photoacoustic) effect. Using illumination with multiple wavelengths and spectral unmixing methods, multispectral optoacoustic tomography (MSOT) has the potential to specifically resolve tissue chromophores or administered extrinsic molecular agents non- invasively in deep tissue with unprecedented resolution performance and in real- time. The presented work explores MSOT in the context of small animal imaging. Different instrumentation and detection geometry related effects are analyzed regarding their influence on the imaging performance. Based on the findings, two dedicated MSOT imaging platforms for 2D and 3D real-time imaging of small animals and tissue samples are conceived, implemented and imaging performance is characterized by simulation, on phantoms and ex vivo in mice. Beside instrumentation, the utilized signal processing, image reconstruction and spectral unmixing strategy is of great importance for achieving best imaging results. The research presented shows how reconstruction artifacts can be reduced by compensating for the electrical impulse response of the system and that the calculation of intermediate projections can alleviate artifacts due to sparse angular sampling. Moreover, two regularization approaches for 2D limited view reconstructions are presented and a 3D model-based inversion scheme for improving 3D reconstructions in the developed systems by modeling the shape of the detection elements. Finally, the challenges of multispectral unmixing in deep tissue are discussed; two unmixing schemes for detection of molecular agents are presented and a method to partially compensate for the effect of light attenuation is proposed. Using the unique imaging performance of the developed methods, it is further established that MSOT can actually resolve anatomical, dynamic and molecular information in mice and that it can be used for assessing biodistribution and pharmacokinetic parameters of molecular probes and contrast agents in tissue. A complete whole-body mouse scan is shown, resolving anatomical hemoglobin- based contrast. Functional imaging is presented by tracking contrast enhancement in the kidneys due to perfusion of systemically administered Indocyanine green (ICG). Also the clearance rate of ICG and liposomal ICG from the blood pool is determined by means of MSOT. Molecular imaging performance is shown by detecting optical reporter agents (here a phosphatidylserine targeting fluorescent dye) within mouse xenograft tumors. i ii List of abbreviations AF750 AlexaFluo750 GN Gold nanoparticles BP Backprojection algorithm CT Computed tomography DOT Diffuse optical tomography EFR Electrical frequency response EIR Electrical impulse response FMT Fluorescent molecular tomography FWHM Full width at half maximum GSVD Generalized singular value decomposition Hb Oxygenated hemoglobin HbO2 Deoxygenated hemoglobin ICA Independent component analysis ICG Indocyanine green IMMI Interpolated matrix model-based inversion LSQR Algorithm for solving sparse linear equations MB Model-based algorithm 3D MB+SIR 3D model-based algorithm with incorporated spatial impulse response 3D MB1SP+SIR 3D MB+SIR reconstructions using data from only one scanning position MPE Maximal permissible skin exposure MIP Maximum intensity projection MRI Magnetic resonance imaging MSE Mean square error MSOT Multispectral optoacoustic tomography NIR Near-infrared OPO Optical parametric oscillator PCA Principal component analysis PET Positron emission tomography PLSQR Preconditioned LSQR PSF Point spread function PSS-794 Phosphatidylserine targeting fluorescent probe ROI Region of interest RMSD Root mean square deviation SIR Spatial impulse response SNR Signal-to-noise ratio SPECT Single photon emission computed tomography SVD Singular value decomposition TGSVD Truncated generalized singular value decomposition TIR Total impulse response TSVD Truncated singular value decomposition XCT X-ray computed tomography iii iv Contents Abstract .................................................................................................................... i List of abbreviations ........................................................................................................ iii 1 Introduction ............................................................................................... 1 1.1 Motivation .......................................................................................................... 1 1.2 Preclinical imaging today .................................................................................... 2 1.3 MSOT – Principle of operation ........................................................................... 4 1.4 Questions addressed in this work ...................................................................... 5 1.5 Outline of this work ............................................................................................ 6 2 Theoretical and technical background ......................................................... 9 2.1 Introduction ........................................................................................................ 9 2.2 The physics of optoacoustic imaging .................................................................. 9 2.2.1 Light in tissue .............................................................................................. 9 2.2.2 Sound in tissue .......................................................................................... 11 2.2.3 Combining light with sound – the optoacoustic effect ............................ 13 2.3 Technological aspects of multispectral optoacoustic tomography.................. 19 2.3.1 Illumination ............................................................................................... 19 2.3.2 Detection of optoacoustic signals............................................................. 21 2.3.3 Electrical impulse response ...................................................................... 23 2.3.4 Spatial impulse response .......................................................................... 24 2.3.5 Sensitivity .................................................................................................. 26 2.4 Optoacoustic image formation ......................................................................... 27 2.4.1 Focused transducer-based techniques ..................................................... 27 2.4.2 Computed reconstruction techniques ...................................................... 28 2.4.3 Spatial resolution ...................................................................................... 32 2.4.4 Effects of a limited detection bandwidth on images ................................ 35 2.4.5 Effects of a finite detector size ................................................................. 36 2.4.6 Effects of a limited view detection ........................................................... 37 2.4.7 Effects of insufficient spatial sampling ..................................................... 38 2.4.8 Thin slice illumination vs. broad beam illumination ................................. 40 2.5 Summary and Conclusion ................................................................................. 41 3 An innovative preclinical MSOT system ...................................................... 43 3.1 Introduction ...................................................................................................... 43 3.2 State of the art preclinical optoacoustic imaging systems ............................... 44 3.2.1 Single transducer scanning-based systems .............................................. 44 3.2.2 Array-based systems ................................................................................. 46 3.3 System implementation ................................................................................... 47 3.3.1 Illumination unit ....................................................................................... 47 3.3.2 Ultrasound detection ................................................................................ 49 3.3.3 Imaging chamber and animal positioning ................................................ 49 v 3.3.4 Data acquisition and control unit ............................................................. 50 3.4 Performance characterization .........................................................................
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