Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting - 1st Edition - ISBN: 9780128110188, 9780128110195

Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting

1st Edition

Editors: Simone Balocco Maria Zuluaga Guillaume Zahnd Su-Lin Lee Stefanie Demirci
eBook ISBN: 9780128110195
Hardcover ISBN: 9780128110188
Imprint: Academic Press
Published Date: 5th December 2016
Page Count: 478
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Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting presents imaging, treatment, and computed assisted technological techniques for diagnostic and intraoperative vascular imaging and stenting. These techniques offer increasingly useful information on vascular anatomy and function, and are poised to have a dramatic impact on the diagnosis, analysis, modeling, and treatment of vascular diseases.

After setting out the technical and clinical challenges of vascular imaging and stenting, the book gives a concise overview of the basics before presenting state-of-the-art methods for solving these challenges.

Readers will learn about the main challenges in endovascular procedures, along with new applications of intravascular imaging and the latest advances in computer assisted stenting.

Key Features

  • Brings together scientific researchers, medical experts, and industry partners working in different anatomical regions
  • Presents an introduction to the clinical workflow and current challenges in endovascular Interventions
  • Provides a review of the state-of-the-art methodologies in endovascular imaging and their applications
  • Poses outstanding questions and discusses future research


Biomedical engineers, medical imaging researchers, cardiologists, clinicians

Table of Contents

  • About the Editors
  • Preface
  • Section I: Clinical Introduction
    • Chapter 1: Intravascular Imaging to Assess Coronary Atherosclerosis and Percutaneous Coronary Interventions
      • Abstract
      • 1 Intravascular Imaging Development
      • 2 Safety of Intravascular Imaging
      • 3 Intravascular Imaging Versus Coronary Angiography
      • 4 Intravascular Imaging Assessment of Plaque Progression/Regression
      • 5 Intravascular Imaging Assessment of Lesions to Be Revascularized, or Not
      • 6 Intravascular Imaging Assessment of Percutaneous Interventions
      • 7 Future Developments and Final Word
    • Chapter 2: Atherosclerotic Plaque Progression and OCT/IVUS Assessment
      • Abstract
      • 1 Aims and Introduction
      • 2 Description of Atherosclerosis Lesions in Children, Adults, and Elderly Population
      • 3 Atherosclerosis Histologist Classification
      • 4 Phases of Progression of Atherosclerosis Disease
      • 5 OCT
      • 6 IVUS
      • 7 Vulnerable Plaques
      • 8 Summary
    • Chapter 3: AAA Treatment Strategy Change Over Time
      • Abstract
      • Chapter Points
      • 1 Introduction
      • 2 Pathogenesis
      • 3 Open Surgical Repair
      • 4 Endovascular Aneurysm Repair
      • 5 Preoperative Planning
      • 6 Imaging for Planning the Intraoperative Procedure and Postoperative Follow-Up
    • Chapter 4: Overview of Different Medical Imaging Techniques for the Identification of Coronary Atherosclerotic Plaques
      • Abstract
      • 1 Introduction
      • 2 Clinical Overview
      • 3 Imaging Techniques
      • 4 Discussion
  • Section II: Vascular and Intravascular Analysis of Plaque
    • Chapter 5: Implications of the Kinematic Activity of the Atherosclerotic Plaque: Analysis Using a Comprehensive Framework for B-Mode Ultrasound of the Carotid Artery
      • Abstract
      • Acknowledgments
      • 1 Introduction
      • 2 Study Population and Ultrasound Image Data
      • 3 A Comprehensive Framework for Quantifying the Arterial Wall Motion
      • 4 Bilateral Asymmetry in Kinematic Features of Atherosclerotic Arteries
      • 5 Risk Stratification Driven by the Kinematic Activity of the Arterial Wall
      • 6 Data Mining of Association-Based Phenotypic Networks
      • 7 Conclusion
    • Chapter 6: Right Generalized Cylinder Model for Vascular Segmentation
      • Abstract
      • Chapter Points
      • 1 Motivation
      • 2 Direct Model
      • 3 Parameters Inversion
      • 4 Model-Guided Image Segmentation
      • 5 Conclusions
    • Chapter 7: Domain Adapted Model for In Vivo Intravascular Ultrasound Tissue Characterization
      • Abstract
      • Acknowledgments
      • 1 Introduction
      • 2 State of the Art
      • 3 Mathematical Modeling of Ultrasonic Backscattering and Signal Propagation Physics in Heterogeneous Tissues
      • 4 Domain Adaptation for In Vivo TC
      • 5 Experiments and Discussion
      • 6 Conclusions
    • Chapter 8: Intracoronary Optical Coherence Tomography
      • Abstract
      • 1 Introduction
      • 2 Coronary Imaging
      • 3 OCT Clinical Research
      • 4 OCT Image Processing
      • 5 Future Outlook
  • Section III: Vascular Biomechanics and Modeling
    • Chapter 9: Vascular Hemodynamics with Computational Modeling and Experimental Studies
      • Abstract
      • Acknowledgments
      • 1 Vascular Hemodynamics and Atherosclerosis
      • 2 Vessel Geometry
      • 3 Computational (CFD) Modeling
      • 4 Experimental Studies
      • 5 Data Postprocessing, Co-Registration, and Comparison
      • 6 Accuracy and Reliability
      • 7 Current Developments
    • Chapter 10: Arterial Flow Impact on Aneurysmal Hemodynamics
      • Abstract
      • Acknowledgments
      • 1 Introduction
      • 2 Modeling Aneurysm Hemodynamics
      • 3 Contributions of this Chapter
      • 4 Part 1: Peak-Systolic and Maximum Hemodynamic Condition
      • 5 Part 2: Characteristic Curves of Intra-Aneurysmal Hemodynamics
      • 6 Conclusions
    • Chapter 11: Toward a Mechanical Mapping of the Arterial Tree: Challenges and Potential Solutions
      • Abstract
      • Acknowledgments
      • 1 Overview and Objectives
      • 2 Arterial Pathophysiology, Mechanics, and Stiffness Assessment
      • 3 Method: Imaging-Based Biomarker (ImBioMark)
      • 4 ImBioMark: Applications on Carotid, Brachial, and Aorta Arteries
      • 5 Discussion
      • 6 Conclusion
  • Section IV: Computer-Assisted Stenting
    • Chapter 12: Computerized Navigation Support for Endovascular Procedures
      • Abstract
      • Chapter points
      • 1 Introduction
      • 2 Simulation for Training
      • 3 Interventional Navigation Support
    • Chapter 13: Interventional Quantification of Cerebral Blood Flow
      • Abstract
      • Chapter points
      • 1 Introduction to the Clinical Value of Blood Flow Quantification
      • 2 Blood Flow Assessment Using Angiographic X-Ray Imaging
    • Chapter 14: Virtual Stenting for Intracranial Aneurysms: A Risk-Free, Patient-Specific Treatment Planning Support for Neuroradiologists and Neurosurgeons
      • Abstract
      • Acknowledgments
      • Chapter points
      • 1 Intracranial Aneurysms
      • 2 Existing Approaches—From Precise to Pragmatic
      • 3 Validation—The Curse of Computational Predictions
      • 4 Selected Applications—How Numerical Models Can Assist
      • 5 Future Directions—Chances and Limitations
    • Chapter 15: Preoperative Planning of Endovascular Procedures in Aortic Aneurysms
      • Abstract
      • 1 Introduction
      • 2 Overview of Endograft Sizing for Aortic Aneurysms
      • 3 Vascular Segmentation
      • 4 Vascular Analysis
      • 5 Quantitative Image Analysis
      • 6 Visualization and Workflow
      • 7 Endograft Sizing Software
      • 8 Conclusions and Future Perspectives
  • Index


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About the Editor

Simone Balocco

Dr. Simone Balocco is Associate Professor of the University of Barcelona, Departement of Mathematics and Informatics, and is senior researcher at the Computer Vision Center, Bellaterra. He obtained a PhD degree in Acoustics at the laboratory Creatis, Lyon and in Electronic and Telecommunication in MSD Lab, University of Florence (Italy). He performed a post-doc at the laboratory CISTIB, at the University Pompeu Fabra. Dr. Balocco main research interest are pattern recognition and computer vision methods for the computer-aided detection of clinical pathologies. In particular his research focuses on Ultrasound and Magnetic Imaging applications and vascular modelling.

Affiliations and Expertise

Associate professor, University of Barcelona, Spain

Maria Zuluaga

In 2011, Maria A. Zuluaga obtained her PhD degree from Université Claude Bernard Lyon I investigating automatic methods for the diagnosis of coronary artery disease. After a year as a postdoctoral fellow at the European Synchrotron Radiation Facility (Grenoble, France), she joined University College London, in March 2012, as a Research Associate to work on cardiovascular image analysis and computer-aided diagnosis of cardiovascular pathologies. Since August 2014, she is part of the Image-guided fetal surgery project (GIFT-Surg) project as a senior research associate.

Affiliations and Expertise

Research Associate, University College London, UK

Guillaume Zahnd

Guillaume Zahnd received his engineering degree from the National Institutes of Applied Science (INSA-Lyon, France) in 2007, and obtained his PhD from CREATIS laboratory, University of Lyon (France) in 2012. In 2013, he joined the Biomedical Imaging Group Rotterdam, Erasmus MC (Netherlands) as a PostDoc researcher. From 2016, he is a research fellow in the Imaging-based Computational Biomedicine laboratory at Nara Institute of Science and Technology (Japan). His work focuses on image processing methodologies towards cardiovascular risk assessment. His field of interest includes vascular imaging, image-based biomarkers, ultrasound, intracoronary optical coherence tomography, motion tracking, contour segmentation and machine learning.

Affiliations and Expertise

Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus MC, Rotterdam, The Netherlands

Su-Lin Lee

Su-Lin Lee received the MEng. degree in information systems engineering and Ph.D. degree from Imperial College London, London, U.K., in 2002 and 2006, respectively, for her work on statistical shape modelling and biomechanical modelling. She is currently a Lecturer at The Hamlyn Centre for Robotic Surgery and the Department of Computing, Imperial College London. Her current research focuses on machine learning and shape modelling with application to guidance in cardiovascular interventions. Of particular interest to her are improved navigation and decision support for safer and more efficient robotic-assisted minimally invasive cardiovascular procedures.

Affiliations and Expertise

Lecturer, Hamlyn Centre for Robotic Surgery, Ipmerial College London, UK

Stefanie Demirci

Stefanie Demirci is a Postdoctoral Researcher and Research Manager at Technical University of Munich (TUM), Germany. She received her Ph.D. degree from the same institution in 2011 for her work on novel approaches to computer assisted endovascular procedures. After being a Postodctoral Fellow at the SINTEF Medical Technology lab in Trondheim, Norway, she returned back to TUM where she is currently teaching Interventional Imaging and Image Processing and managing the Computer Aided medical Procedures (CAMP) lab. Her current research focuses on multi-modal imaging and image processing, machine learning and biomedical gamification with particular interest in crowd sourcing for biomedical ground truth creation.

Affiliations and Expertise

Postdoctoral Researcher and Research Manager at Technical University of Munich (TUM), Germany