Red blood cells as the main source of scattering in blood

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Table of contents

List of symbols
List of acronyms
INTRODUCTION
I Theoretical part
1 State of the art: scattering modeling for ultrasound blood characterization
1.1 Phenomenon of RBC aggregation
1.2 Quantitative ultrasound techniques based on backscatter coefficient measurements
1.3 Assumptions for modeling ultrasound backscattering by blood
1.3.1 Red blood cells as the main source of scattering in blood
1.3.2 The Born approximation
1.4 Ultrasonic scattering model for a single RBC
1.5 Ultrasonic scattering models for an ensemble of RBCs
1.5.1 Particle model
1.5.2 Simplified models for disaggregated RBCs
1.5.3 Simplified models for aggregated RBCs
1.5.3.1 Structure factor size estimator (SFSE)
1.5.3.2 Effective medium theory combined with the structure factor model (EMTSFM) 14
1.6 Motivation: limitations of current models
2 Ultrasonic scattering modeling of red blood cells aggregates taking into account anisotropy
2.1 Backscattering cross-section by a single prolate-shaped aggregate of RBCs
2.1.1 Theory: coherent and incoherent ultrasound backscatter from a single prolate-shaped aggregate
2.1.1.1 The coherent component
2.1.1.2 The incoherent component
2.1.2 3D simulation method
2.1.3 Results and discussion: comparison between theoretical and simulated ag
2.2 Backscattering by an ensemble of prolate-shaped aggregates
2.2.1 Effective Medium Theory combined with the Local Monodisperse Approximation (EMTLMA) for perfectly aligned prolate ellipsoids
2.2.2 Methods
2.2.2.1 Computer simulations based on the Structure Factor Model
2.2.2.2 QUS parameter estimation
2.2.3 Results
2.2.3.1 Influence of structural parameters on the frequency-dependent BSC when using the anisotropic EMTLMA
2.2.3.2 Forward problem: comparison between simulated and theoretical BSCs
2.2.3.2.1 Influence of the polydispersity in terms of aggregate sizes
2.2.3.2.2 Influence of the alignment: randomly oriented versus perfectly aligned prolate ellipsoids
2.2.3.3 Inverse problem: estimation of QUS parameters
2.2.4 Discussion
2.2.4.1 Limitation to estimate QUS parameters for randomly oriented prolate ellipsoids
2.2.4.2 On the behavior of the cost function
2.2.4.3 On the use of the anisotropic EMTLMA in vivo
2.3 Conclusion
3 Evaluation of the anisotropic EMTLMA in estimation of structural parameters of partially aligned aggregates
3.1 Material and Methods
3.1.1 Experiments on porcine blood sheared in microfluidic shearing system
3.1.2 Computer simulations based on the Structure Factor Model
3.1.3 Theoretical EMTLMA modeling for partially aligned prolate ellipsoids
3.1.4 QUS parameter estimation
3.2 Results
3.2.1 Actual size and orientation distributions of RBC aggregates
3.2.2 Forward problem: comparison between simulated and theoretical BSCs
3.2.3 Inverse problem: estimation of QUS parameters
3.3 Discussion
3.3.1 Limitations of numerical simulations
3.3.2 Qualitative comparison between the simulated and measured BSCs
3.3.3 On the assumption of perfectly aligned aggregates in the estimation of QUS parameters
3.3.4 On the assumption of gamma (truncated) size distribution
3.3.5 On the cost function behavior
3.4 Conclusion
II Experimental part
4 State of the art: Measuring the BSC in soft tissues using an ultrasound imaging system
4.1 Ultrasound imaging system and transducers
4.1.1 Ultrasonic transducers
4.1.2 Ultrasound beamforming
4.2 Measurement techniques of the BSC in soft tissues
4.2.1 The substitution method
4.2.2 The reference phantom technique
4.2.3 Selection of the ROI to compute the BSC
4.3 Measurement techniques of local attenuation in soft tissues
4.4 Measure of BSC and other spectral-based quantitative ultrasound (QUS) parameters using medical ultrasound imaging systems
4.5 Motivation: Evaluation of the performance of a CMUT probe and a piezoelectric probe in measuring tissue anisotropy
5 Performance comparison between piezoelectric and CMUT probes in measuring the backscattering coefficient
5.1 Material and Methods
5.1.1 Hydrophone system, ultrasound scanner and transducers
5.1.2 Transmit beam pattern measurements
5.1.2.1 Estimation of the beam steering direction
5.1.2.2 Sources of error and uncertainty in the beam direction estimation
5.1.3 Measurements of spectrum-based parameters on tissue-mimicking phantoms
5.1.3.1 Tissue-mimicking phantoms
5.1.3.2 Acoustical parameters of the tissue-mimicking phantoms
5.1.3.3 Acquisition of the backscattered raw radio frequency signals
5.1.3.4 Measurement of the backscatter coefficient and integrated backscatter coefficient
5.1.3.5 Analysis of spectrum-based parameter measurements
5.2 Results
5.2.1 Estimation of the beam steering direction
5.2.1.1 Beam pattern measurements
5.2.2 Measurements of the spectrum-based parameters
5.2.2.1 Isotropic medium
5.2.2.2 Anisotropic medium
5.3 Discussion
5.3.1 Limitation in hydrophone measurements
5.3.2 Estimation of the beam steering direction
5.3.3 Limitation in spectrum-based parameter measurements
5.3.3.1 Attenuation measurements
5.3.3.2 Measured and theoretical BSCs
5.3.4 Spectrum-based parameters measurements
5.3.4.1 Power spectral densities
5.3.4.2 BSC and iBSC
5.3.4.3 On the use of piezoelectric probe for anisotropic backscatter measurements .
5.4 Conclusion
General conclusion and perspectives
References