Ex–vivo and In–vivo Optical Molecular Pathology

The result of a unique collaboration between clinicians, chemists and physicists, this book provides an unparalleled overview of a new generation of diagnostic tools in clinical pathology. The introductory chapters cover the present status and limitations of currently used methods, followed by an outline of promising novel spectroscopy–based technologies either under development or recently available on the market. The input from both technologists developing these new methods as well as routine clinicians familiar with practical aspects and medical relevance guarantees that this practical work is a valuable asset for a wide audience, including technical personnel and decision makers in treatment centers, experts working in companies developing diagnostic devices, and clinicians specializing in advanced diagnostic methods. Since basic researchers are increasingly adopting novel diagnostic tools developed for human use as well, this will also be of interest for biomedical research institutions with large animal facilities.

List of Contributors XI Preface XV 1 Clinical Pathology 1 Masoud Mireskandari and Iver Petersen 1.1 Introduction 1 1.2 Pathology as a Medical and Research Discipline 1 1.3 Historical Perspectives 2 1.4 Specimens 3 1.4.1 Biopsies, Resections, and Cytology 3 1.5 Conventional Diagnostic Methods in Pathology 4 1.5.1 Cytology 5 1.5.2 Histology 6 1.5.3 Microscopy 8 1.5.4 Intraoperative Assessment (Frozen Section Examination) 9 1.5.5 Why Pathologists Do Not Like Frozen Tissue Examination? 11 1.5.6 Microdissection 12 1.6 Nonconventional (Ancillary) Diagnostic Methods in Pathology (Molecular Assessment of Tissues) 13 1.6.1 In Situ Reactions 13 1.6.1.1 Immunofluorescence (IF) 13 1.6.1.2 Immunohistochemistry (IHC) 14 1.6.1.3 Fluorescent In Situ Hybridization (FISH) 14 1.6.2 Non–In Situ Methods 15 1.7 Summary of Major Terms in Clinical Pathology 17 1.7.1 Injury and Adaptation 17 1.7.2 Inflammation and Repair 18 1.7.3 Neoplastic Diseases 20 1.8 Limitations of Clinical and Diagnostic Pathology 23 1.8.1 Prediction of Tumor Behavior 24 1.8.2 Diagnosis of Tumor Origin in a Case with Metastatic Tumor Disease 24 1.8.3 Individualized Medicine and Targeted Therapy 25 Further Readings 26 2 Clinical Endoscopy in Gastrointestinal Diseases 27 Martin Goetz, Joerg Felber, and Andreas Stallmach 2.1 Introduction 27 2.2 White–Light Endoscopy 29 2.3 Chromoendoscopy 30 2.4 Virtual Chromoendoscopy 32 2.5 Endomicroscopy and Endocytoscopy 33 2.6 Endoscopic Spectroscopy 34 2.6.1 Autofluorescence Imaging 36 2.6.2 Raman Spectroscopy 36 2.7 Perspectives and Conclusions 37 References 38 3 Molecular Pathology via Infrared and Raman Spectral Imaging 45 Max Diem, Antonella Mazur, Kathleen Lenau, Jen Schubert, Jennifer Fore, Benjamin Bird, Milos Miljkovíc, Christoph Krafft, and Jürgen Popp 3.1 Introduction 45 3.2 Background 47 3.3 Methods 52 3.3.1 Sample Preparation 53 3.3.2 Collection of Hyperspectral Data Cubes 54 3.3.3 Data Preprocessing 56 3.3.4 Presorting (Cluster Analysis) 57 3.3.5 Visual Imaging 57 3.3.6 Annotation 58 3.3.7 Diagnostic Data Analysis 59 3.3.8 Visual Data Analysis: Factor Methods 61 3.4 Results and Discussion 62 3.4.1 IR–SHP: Detection of Metastases and Micro–Metastases in Lymph Nodes 62 3.4.1.1 IR–SHP of Micro–Metastases in Lymph Nodes 64 3.4.1.2 IR–SHP of Lymphocyte Activation in Lymph Nodes 66 3.4.2 SHP of Squamous Cell Carcinoma and Adenocarcinomas 70 3.4.2.1 Distinction of Different Cancer Types by IR–SHP 70 3.4.2.2 Diagnosis of Lung SqCC and Lung ADC via IR–SHP 72 3.4.2.3 Diagnosis of Cervical SqCC and Cervical ADC via SHP 74 3.4.3 Results from Infrared Spectral Cytopathology (SCP) 76 3.4.3.1 Background 76 3.4.3.2 Design and Methods of the Preclinical Trial for Oral Screening 77 3.4.3.3 SCP Results for the Oral Mucosa 78 3.4.3.4 SCP Results for the Cervical Mucosa 81 3.4.4 IR and Raman–SHP of Brain Metastases 81 3.4.4.1 IR and Raman Spectra of Brain Tissue 82 3.4.4.2 Identification of Tumor Margins 83 3.4.4.3 Determination of Primary Tumor 84 3.4.5 Raman–SCP of Circulating Tumor Cells 86 3.4.5.1 Dried Cells 86 3.4.5.2 Tweezed Cells in Buffer 88 3.4.5.3 Trapped Cells in Microfluidic Chips 90 3.4.6 High–Resolution Confocal Raman Imaging of Individual Cells 92 3.5 Conclusions 95 References 96 4 Coherent Raman for Medical Diagnosis 103 Jeffrey L. Suhalim and Eric Potma 4.1 Introduction 103 4.2 Raman Contrast for Tissue Imaging 104 4.2.1 Origin of Chemical Contrast 104 4.2.2 Endogenous Targets for Raman–Based Imaging in Tissues 107 4.3 Coherent Raman Scattering 109 4.3.1 Basic Principle 109 4.3.2 Coherent Anti–Stokes Raman Scattering (CARS) versus Stimulated Raman Scattering (SRS) 112 4.4 Advantage of CRS Imaging 115 4.4.1 Speed Advantage 115 4.4.2 Speed versus Spectral Information 116 4.4.2.1 Single–Channel CRS Imaging 116 4.4.2.2 Hyperspectral CRS Imaging 118 4.4.2.3 Narrowband CRS 118 4.4.2.4 Hybrid of CRS Microscopy and Microspectroscopy 120 4.5 Applications of CRS in Cellular and Tissue Imaging 122 4.5.1 Following Dynamics of Biological Processes 122 4.5.2 Specific Detection of Lipophilic Molecules 123 4.5.3 Stain–Free Histopathological Imaging 126 4.5.4 Quantification of Lipids in Tissue Samples 129 4.5.5 Quantifying Relative Abundance of Multiple Biomolecules 132 4.5.6 Determining Absolute Concentration of Biomolecules 133 4.5.7 Classifying Diseased Tissue Based on Morphological Parameters 133 4.6 CRS Imaging In Vivo 136 4.7 Prospects and Challenges 138 Funding Source and Acknowledgments 141 References 141 5 Multimodal Morphochemical Tissue Imaging 147 Riccardo Cicchi and Francesco S. Pavone 5.1 Introduction 147 5.2 Morphological Techniques 149 5.2.1 Two–Photon Excited Fluorescence (TPEF) Microscopy 149 5.2.2 Second–Harmonic Generation (SHG) Microscopy 149 5.3 Functional Techniques 151 5.3.1 Fluorescence Lifetime Imaging Microscopy (FLIM) 151 5.3.2 Multispectral TPEF Imaging (MTPEF) 152 5.3.3 Raman–Based Microscopy (Raman–CARS–SRS) 152 5.4 Morphological Imaging 154 5.4.1 Cell Imaging by TPEF Microscopy 155 5.4.2 Collagen Organization Probed by Pattern Analysis of SHG Images 156 5.4.3 Multimodal TPEF–SHG Microscopy of Skin Dermis 158 5.5 Functional Imaging 161 5.5.1 MTPEF Imaging of NADH and FAD 161 5.5.2 Polarization–Scanning SHG Microscopy of Collagen 163 5.5.3 Multimodal TPEF–SHG–CARS Microscopy for the Morphochemical Characterization of Tissues 166 5.6 Conclusion 169 Acknowledgments 169 References 170 6 Molecular Endospectroscopic Approaches 179 Nick Stone, Charlotte Kallaway, Laurence Maximillian Almond, James Wood, Joanne Hutchings, Catherine Kendall, and Hugh Barr 6.1 Introduction 179 6.1.1 Clinical Need 179 6.1.1.1 Esophagus 180 6.1.1.2 Colon 181 6.1.1.3 Bladder 182 6.2 Endoscopic Imaging Techniques: Sampling Tissue Morphology/Architecture 182 6.2.1 High–Resolution Endoscopy (HRE) 182 6.2.2 Confocal Microscopy (CM) 183 6.2.3 Chromoendoscopy (CE) 183 6.2.4 Narrow–Band Imaging (NBI) 183 6.2.5 Optical Coherence Tomography (OCT) 184 6.2.6 Novel Imaging Techniques: Summary 185 6.3 Molecular Endospectroscopic Techniques: Probing Native Molecular Signals 185 6.3.1 Autofluorescence Imaging (AFI) 186 6.3.2 Fluorescence Lifetime Imaging (FLIM) 186 6.3.3 Elastic Scattering Spectroscopy (ESS) 187 6.3.4 Raman Spectroscopy (RS) 188 6.3.4.1 Introduction to Diagnostic Raman Spectroscopy Techniques 188 6.3.4.2 In Vivo Raman Endospectroscopy 192 6.3.4.3 Colon 197 6.3.4.4 Bladder 198 6.3.4.5 Further Developments in In Vivo Endoscopic Raman and Associated Applications 199 6.3.4.6 Raman Summary 199 6.4 Endoscopic Imaging with Contrast Agents 200 6.4.1 Imaging Exogenous Fluorophores 200 6.4.1.1 Specific Labeling of Biomarkers 200 6.4.2 Surface–Enhanced Raman Scattering (SERS) Endoscopy 200 6.5 Nonlinear Endoscopic Raman Techniques under Development 202 6.6 Multimodal Endoscopic Detection and Diagnosis 203 6.7 Conclusions 204 References 206 7 Image Processing—Chemometric Approaches to Analyze Optical Molecular Images 215 Thomas Bocklitz, Michael Schmitt, and Jürgen Popp 7.1 Introduction 215 7.2 Introduction to Statistics 216 7.2.1 Univariate Statistics–Univariate Data 217 7.2.1.1 Poisson Distribution 217 7.2.1.2 Gaussian Distribution 218 7.2.2 Multivariate Statistics–Hyperspectral Data 219 7.3 Pretreatment 221 7.3.1 Raman Spectroscopy 221 7.3.2 IR Spectroscopy 222 7.3.3 Nonlinear Raman spectroscopy 223 7.3.4 Images 223 7.4 Image Analysis 224 7.4.1 Filtration Methods 224 7.4.2 Property Calculation 227 7.4.3 Segmentation Approaches 227 7.4.4 Object Recognition 228 7.5 Analysis Methods 229 7.5.1 Optimization Problems and Optimization Methods 229 7.5.1.1 Gradient Decent 230 7.5.1.2 Genetic Algorithm 231 7.5.1.3 Simulated Annealing 231 7.5.2 Classification Models 231 7.5.2.1 Linear Discriminant Analysis 233 7.5.2.2 Support Vector Machine 233 7.5.2.3 Artificial Neural Networks 235 7.5.2.4 Combining Classifiers 236 7.5.3 Multivariate Calibration Methods 237 7.5.4 Evaluation Procedures 238 7.5.4.1 Cross Validation 239 7.5.4.2 Jacknife, Bootstrap, and Holdout Validation 240 7.5.5 Factor Methods 240 7.5.5.1 Principal Component Analysis (PCA) 241 7.5.5.2 Independent Component Analysis (ICA) 242 7.5.5.3 Non–negative matrix factorization (NMF) 242 7.5.6 Cluster Algorithms 242 7.5.6.1 k–Means Cluster Analysis (k–CA) 242 7.5.6.2 c–Means Cluster Analysis 243 7.5.6.3 Hierarchical Cluster Analysis 243 7.5.6.4 Vertex Component Analysis (VCA) and N–FINDR 244 7.6 Summary 246 References 247 8 Summary and Conclusions 249 Christian Matthäus, Michael Schmitt, and Jürgen Popp Index 253

Jürgen Popp is Professor at the Friedrich–Schiller–University Jena where he is Director of the Institute of Physical Chemistry. He is also Director of the Institute of Physical High Technology (IPHT) Jena. In the German Main Research Topic ′Biophotonik′ (National Network financed by the BMBF) he serves as the speaker.