Biomedical Imaging

REINER SALZER, PHD, is a professor at the Institute for Analytical Chemistry at Technische Universität in Dresden, Germany.

“This would be highly beneficial to scientists and engineers seeking careers in biomedical imaging.”  (Journalof Biomedical Optics, 1 December 2012) “The text is expertly integrated with high-quality figures and includes an index. This book is suitable for researchers and engineers in a variety of disciplines. I highly recommend it as a comprehensive introduction to nanofabrication techniques.”  (Optics & Photonics News, 1 October 2012)

• Preface xvContributors xvii1 Evaluation of Spectroscopic Images 1Patrick W.T. Krooshof, Geert J. Postma, Willem J. Melssen, and Lutgarde M.C. Buydens1.1 Introduction 11.2 Data Analysis 21.2.1 Similarity Measures 31.2.2 Unsupervised Pattern Recognition 41.2.2.1 Partitional Clustering 41.2.2.2 Hierarchical Clustering 61.2.2.3 Density-Based Clustering 71.2.3 Supervised Pattern Recognition 91.2.3.1 Probability of Class Membership 91.3 Applications 111.3.1 Brain Tumor Diagnosis 111.3.2 MRS Data Processing 121.3.2.1 Removing MRS Artifacts 121.3.2.2 MRS Data Quantitation 131.3.3 MRI Data Processing 141.3.3.1 Image Registration 151.3.4 Combining MRI and MRS Data 161.3.4.1 Reference Data Set 161.3.5 Probability of Class Memberships 171.3.6 Class Membership of Individual Voxels 181.3.7 Classification of Individual Voxels 201.3.8 Clustering into Segments 221.3.9 Classification of Segments 231.3.10 Future Directions 24References 252 Evaluation of Tomographic Data 30Jorg van den Hoff2.1 Introduction 302.2 Image Reconstruction 332.3 Image Data Representation: Pixel Size and Image Resolution 342.4 Consequences of Limited Spatial Resolution 392.5 Tomographic Data Evaluation: Tasks 462.5.1 Software Tools 462.5.2 Data Access 472.5.3 Image Processing 472.5.3.1 Slice Averaging 482.5.3.2 Image Smoothing 482.5.3.3 Coregistration and Resampling 512.5.4 Visualization 522.5.4.1 Maximum Intensity Projection (MIP) 522.5.4.2 Volume Rendering and Segmentation 542.5.5 Dynamic Tomographic Data 562.5.5.1 Parametric Imaging 572.5.5.2 Compartment Modeling of Tomographic Data 572.6 Summary 61References 613 X-Ray Imaging 63Volker Hietschold3.1 Basics 633.1.1 History 633.1.2 Basic Physics 643.2 Instrumentation 663.2.1 Components 663.2.1.1 Beam Generation 663.2.1.2 Reduction of Scattered Radiation 673.2.1.3 Image Detection 693.3 Clinical Applications 763.3.1 Diagnostic Devices 763.3.1.1 Projection Radiography 763.3.1.2 Mammography 783.3.1.3 Fluoroscopy 813.3.1.4 Angiography 823.3.1.5 Portable Devices 843.3.2 High Voltage and Image Quality 853.3.3 Tomography/Tomosynthesis 873.3.4 Dual Energy Imaging 873.3.5 Computer Applications 883.3.6 Interventional Radiology 923.4 Radiation Exposure to Patients and Employees 92References 954 Computed Tomography 97Stefan Ulzheimer and Thomas Flohr4.1 Basics 974.1.1 History 974.1.2 Basic Physics and Image Reconstruction 1004.2 Instrumentation 1024.2.1 Gantry 1024.2.2 X-ray Tube and Generator 1034.2.3 MDCT Detector Design and Slice Collimation 1034.2.4 Data Rates and Data Transmission 1074.2.5 Dual Source CT 1074.3 Measurement Techniques 1094.3.1 MDCT Sequential (Axial) Scanning 1094.3.2 MDCT Spiral (Helical) Scanning 1094.3.2.1 Pitch 1104.3.2.2 Collimated and Effective Slice Width 1104.3.2.3 Multislice Linear Interpolation and z-Filtering 1114.3.2.4 Three-Dimensional Backprojection and Adaptive Multiple Plane Reconstruction (AMPR) 1144.3.2.5 Double z-Sampling 1144.3.3 ECG-Triggered and ECG-Gated Cardiovascular CT 1154.3.3.1 Principles of ECG-Triggering and ECG-Gating 1154.3.3.2 ECG-Gated Single-Segment and Multisegment Reconstruction 1184.4 Applications 1194.4.1 Clinical Applications of Computed Tomography 1194.4.2 Radiation Dose in Typical Clinical Applications and Methods for Dose Reduction 1224.5 Outlook 125References 1275 Magnetic Resonance Technology 131Boguslaw Tomanek and Jonathan C. Sharp5.1 Introduction 1315.2 Magnetic Nuclei Spin in a Magnetic Field 1335.2.1 A Pulsed rf Field Resonates with Magnetized Nuclei 1355.2.2 The MR Signal 1375.2.3 Spin Interactions Have Characteristic Relaxation Times 1385.3 Image Creation 1395.3.1 Slice Selection 1395.3.2 The Signal Comes Back—The Spin Echo 1425.3.3 Gradient Echo 1435.4 Image Reconstruction 1455.4.1 Sequence Parameters 1465.5 Image Resolution 1485.6 Noise in the Image—SNR 1495.7 Image Weighting and Pulse Sequence Parameters TE and TR 1505.7.1 T2-Weighted Imaging 1505.7.2 T∗2 -Weighted Imaging 1515.7.3 Proton-Density-Weighted Imaging 1525.7.4 T1-Weighted Imaging 1525.8 A Menagerie of Pulse Sequences 1525.8.1 EPI 1545.8.2 FSE 1545.8.3 Inversion-Recovery 1555.8.4 DWI 1565.8.5 MRA 1585.8.6 Perfusion 1595.9 Enhanced Diagnostic Capabilities of MRI—Contrast Agents 1595.10 Molecular MRI 1595.11 Reading the Mind—Functional MRI 1605.12 Magnetic Resonance Spectroscopy 1615.12.1 Single Voxel Spectroscopy 1635.12.2 Spectroscopic Imaging 1635.13 MR Hardware 1645.13.1 Magnets 1645.13.2 Shimming 1675.13.3 Rf Shielding 1685.13.4 Gradient System 1685.13.5 MR Electronics—The Console 1695.13.6 Rf Coils 1705.14 MRI Safety 1715.14.1 Magnet Safety 1715.14.2 Gradient Safety 1735.15 Imaging Artefacts in MRI 1735.15.1 High Field Effects 1745.16 Advanced MR Technology and Its Possible Future 175References 1756 Toward A 3D View of Cellular Architecture: Correlative Light Microscopy and Electron Tomography 180Jack A. Valentijn, Linda F. van Driel, Karen A. Jansen, Karine M. Valentijn, and Abraham J. Koster6.1 Introduction 1806.2 Historical Perspective 1816.3 Stains for CLEM 1826.4 Probes for CLEM 1836.4.1 Probes to Detect Exogenous Proteins 1836.4.1.1 Green Fluorescent Protein 1836.4.1.2 Tetracysteine Tags 1866.4.1.3 Theme Variations: Split GFP and GFP-4C 1876.4.2 Probes to Detect Endogenous Proteins 1886.4.2.1 Antifluorochrome Antibodies 1896.4.2.2 Combined Fluorescent and Gold Probes 1896.4.2.3 Quantum Dots 1906.4.2.4 Dendrimers 1916.4.3 Probes to Detect Nonproteinaceous Molecules 1926.5 CLEM Applications 1936.5.1 Diagnostic Electron Microscopy 1936.5.2 Ultrastructural Neuroanatomy 1946.5.3 Live-Cell Imaging 1966.5.4 Electron Tomography 1976.5.5 Cryoelectron Microscopy 1986.5.6 Immuno Electron Microscopy 2016.6 Future Perspective 202References 2057 Tracer Imaging 215Rainer Hinz7.1 Introduction 2157.2 Instrumentation 2167.2.1 Radioisotope Production 2167.2.2 Radiochemistry and Radiopharmacy 2197.2.3 Imaging Devices 2207.2.4 Peripheral Detectors and Bioanalysis 2257.3 Measurement Techniques 2287.3.1 Tomographic Image Reconstruction 2287.3.2 Quantification Methods 2297.3.2.1 The Flow Model 2307.3.2.2 The Irreversible Model for Deoxyglucose 2307.3.2.3 The Neuroreceptor Binding Model 2337.4 Applications 2347.4.1 Neuroscience 2347.4.1.1 Cerebral Blood Flow 2347.4.1.2 Neurotransmitter Systems 2357.4.1.3 Metabolic and Other Processes 2387.4.2 Cardiology 2407.4.3 Oncology 2407.4.3.1 Angiogenesis 2407.4.3.2 Proliferation 2417.4.3.3 Hypoxia 2417.4.3.4 Apoptosis 2427.4.3.5 Receptor Imaging 2427.4.3.6 Imaging Gene Therapy 2437.4.4 Molecular Imaging for Research in Drug Development 2437.4.5 Small Animal Imaging 244References 2448 Fluorescence Imaging 248Nikolaos C. Deliolanis, Christian P. Schultz, and Vasilis Ntziachristos8.1 Introduction 2488.2 Contrast Mechanisms 2498.2.1 Endogenous Contrast 2498.2.2 Exogenous Contrast 2518.3 Direct Methods: Fluorescent Probes 2518.4 Indirect Methods: Fluorescent Proteins 2528.5 Microscopy 2538.5.1 Optical Microscopy 2538.5.2 Fluorescence Microscopy 2548.6 Macroscopic Imaging/Tomography 2608.7 Planar Imaging 2608.8 Tomography 2628.8.1 Diffuse Optical Tomography 2668.8.2 Fluorescence Tomography 2668.9 Conclusion 267References 2689 Infrared and Raman Spectroscopic Imaging 275Gerald Steiner9.1 Introduction 2759.2 Instrumentation 2789.2.1 Infrared Imaging 2789.2.2 Near-Infrared Imaging 2819.3 Raman Imaging 2829.4 Sampling Techniques 2839.5 Data Analysis and Image Evaluation 2859.5.1 Data Preprocessing 2879.5.2 Feature Selection 2879.5.3 Spectral Classification 2889.5.4 Image Processing Including Pattern Recognition 2929.6 Applications 2929.6.1 Single Cells 2929.6.2 Tissue Sections 2929.6.2.1 Brain Tissue 2949.6.2.2 Skin Tissue 2959.6.2.3 Breast Tissue 2989.6.2.4 Bone Tissue 2999.6.3 Diagnosis of Hemodynamics 300References 30110 Coherent Anti-Stokes Raman Scattering Microscopy 304Annika Enejder, Christoph Heinrich, Christian Brackmann, Stefan Bernet, and Monika Ritsch-Marte10.1 Basics 30410.1.1 Introduction 30410.2 Theory 30610.3 CARS Microscopy in Practice 30910.4 Instrumentation 31010.5 Laser Sources 31110.6 Data Acquisition 31410.7 Measurement Techniques 31610.7.1 Excitation Geometry 31610.7.2 Detection Geometry 31810.7.3 Time-Resolved Detection 31910.7.4 Phase-Sensitive Detection 31910.7.5 Amplitude-Modulated Detection 32010.8 Applications 32010.8.1 Imaging of Biological Membranes 32110.8.2 Studies of Functional Nutrients 32110.8.3 Lipid Dynamics and Metabolism in Living Cells and Organisms 32210.8.4 Cell Hydrodynamics 32410.8.5 Tumor Cells 32510.8.6 Tissue Imaging 32510.8.7 Imaging of Proteins and DNA 32610.9 Conclusions 326References 32711 Biomedical Sonography 331Georg Schmitz11.1 Basic Principles 33111.1.1 Introduction 33111.1.2 Ultrasonic Wave Propagation in Biological Tissues 33211.1.3 Diffraction and Radiation of Sound 33311.1.4 Acoustic Scattering 33711.1.5 Acoustic Losses 33811.1.6 Doppler Effect 33911.1.7 Nonlinear Wave Propagation 33911.1.8 Biological Effects of Ultrasound 34011.1.8.1 Thermal Effects 34011.1.8.2 Cavitation Effects 34011.2 Instrumentation of Real-Time Ultrasound Imaging 34111.2.1 Pulse-Echo Imaging Principle 34111.2.2 Ultrasonic Transducers 34211.2.3 Beamforming 34411.2.3.1 Beamforming Electronics 34411.2.3.2 Array Beamforming 34511.3 Measurement Techniques of Real-Time Ultrasound Imaging 34711.3.1 Doppler Measurement Techniques 34711.3.1.1 Continuous Wave Doppler 34711.3.1.2 Pulsed Wave Doppler 34911.3.1.3 Color Doppler Imaging and Power Doppler Imaging 35111.3.2 Ultrasound Contrast Agents and Nonlinear Imaging 35311.3.2.1 Ultrasound Contrast Media 35311.3.2.2 Harmonic Imaging Techniques 35611.3.2.3 Perfusion Imaging Techniques 35711.3.2.4 Targeted Imaging 35811.4 Application Examples of Biomedical Sonography 35911.4.1 B-Mode, M-Mode, and 3D Imaging 35911.4.2 Flow and Perfusion Imaging 362References 36512 Acoustic Microscopy for Biomedical Applications 368Jurgen Bereiter-Hahn12.1 Sound Waves and Basics of Acoustic Microscopy 36812.1.1 Propagation of Sound Waves 36912.1.2 Main Applications of Acoustic Microscopy 37112.1.3 Parameters to Be Determined and General Introduction into Microscopy with Ultrasound 37112.2 Types of Acoustic Microscopy 37212.2.1 Scanning Laser Acoustic Microscope (LSAM) 37312.2.2 Pulse-Echo Mode: Reflection-Based Acoustic Microscopy 37312.2.2.1 Reflected Amplitude Measurements 37912.2.2.2 V(z) Imaging 38012.2.2.3 V(f) Imaging 38212.2.2.4 Interference-Fringe-Based Image Analysis 38312.2.2.5 Determination of Phase and the Complex Amplitude 38612.2.2.6 Combining V (f) with Reflected Amplitude and Phase Imaging 38612.2.2.7 Time-Resolved SAM and Full Signal Analysis 38812.3 Biomedical Applications of Acoustic Microscopy 39112.3.1 Influence of Fixation on Acoustic Parameters of Cells and Tissues 39112.3.2 Acoustic Microscopy of Cells in Culture 39212.3.3 Technical Requirements 39312.3.3.1 Mechanical Stability 39312.3.3.2 Frequency 39312.3.3.3 Coupling Fluid 39312.3.3.4 Time of Image Acquisition 39412.3.4 What Is Revealed by SAM: Interpretation of SAM Images 39412.3.4.1 Sound Velocity, Elasticity, and the Cytoskeleton 39512.3.4.2 Attenuation 40012.3.4.3 Viewing Subcellular Structures 40112.3.5 Conclusions 40112.4 Examples of Tissue Investigations using SAM 40312.4.1 Hard Tissues 40412.4.2 Cardiovascular Tissues 40512.4.3 Other Soft Tissues 406References 406