Computer modeling is increasingly used in medicine to inform diagnosis, therapy, and biomedical discovery. The emergence of this new field of computational medicine is partly driven by the tremendous growth in the amount and quality of imaging data available to inform a variety of modeling approaches. The symposium will review the role of imaging technologies in advancing computational medicine using examples from four major areas of application: cardiovascular disease, neuroscience, orthopedics, and oncology. The talks will discuss the opportunities for development of new quantitative imaging protocols, technologies, and algorithms to better support the modeling.
The lectures will present recent advances in the following areas: (i) model-based treatment planning in cardiovascular disease, in particular for catheter ablation of persistent atrial fibrillation based on Late Gd-Enhanced MRI, (ii) modeling of organ shape, its population variability and temporal evolution to inform understanding of neurodegenerative disease, (iii) applications of imaging to develop computer models in orthopedics, including joint kinematics and finite element analysis of bone, surgical implants, and bone-implant interactions, and (iv) development of imaging-based models in oncology to understand and assess response and resistance to targeted drugs.
This lectures will provide an overview of the computer models used in those major application areas. The origin of the morphological, functional, and quantitative imaging signals used in the modeling will be discussed. Recent advances in fundamental biomedical research, diagnosis, and treatment planning enabled by computer models will be presented.
1. Understand the increasing role of computer modeling in medicine
2. Understand the models used in cardiology, shape analysis (neuroscience), orthopedics, and assessment of drug and treatment response (oncology)
3. Understand the role of imaging in development and validation of computer models in medicine
IM/TH- Image Analysis (Single modality or Multi-modality): Computer-aided decision support systems (detection, diagnosis, risk prediction, staging, treatment response assessment/monitoring, prognosis prediction)