By Ashim Datta, Vineet Rakesh
Equipped round challenge fixing, this e-book lightly introduces the reader to computational simulation of biomedical delivery procedures, bridging basic concept with real-world functions. utilizing this e-book the reader will achieve an entire origin to the topic, beginning with challenge simplification, enforcing it in software program, via to reading the implications, validation, and optimization. Ten case stories, concentrating on rising parts resembling thermal treatment and drug supply, with effortless to keep on with step by step directions, offer ready-to-use templates for extra purposes. answer technique utilizing the generally used software COMSOL Multiphysics is defined intimately; beneficial biomedical estate facts and correlations are incorporated; and historical past idea details is given on the finish of the e-book for simple reference. a mix of brief and prolonged routines make this e-book an entire path package deal for undergraduate and starting graduate scholars in biomedical and biochemical engineering curricula, in addition to a self-study advisor.
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Extra resources for An Introduction to Modeling of Transport Processes: Applications to Biomedical Systems
4) When accurate property data are not available for a particular material, which is often the case, how do we get useful information from the simulation? These topics are addressed in greater detail in Chapter 9. It is a good idea to review relevant sections of Chapter 9 at this problem formulation stage. 2 Simplification is generally needed Like other steps in problem formulation, finding properties also requires simplification. For example, most biomaterials are non-homogeneous. A specific example can be that thermal conductivity of a muscle tissue is different along the fiber and perpendicular to the fiber.
One can consider, for example: (1) are we likely to find the property data needed for the exact material that we need? If not, is there another material that would be similar and for which data are likely to be more readily available? In the case of a complex material, what simplification of the material can we get away with? (2) Can we estimate the property using empirical predictive equations? (3) How accurate must the data be? (4) When accurate property data are not available for a particular material, which is often the case, how do we get useful information from the simulation?
Thermal therapy is any treatment or technique that elevates or decreases cell/tissue temperature for some length of time with an ultimate therapeutic goal. Thermal therapy can include hyperthermia, tissue coagulation and ablation as well as ultrasonic, laser, radiofrequency and microwave heating to destroy tissue, plus cryosurgery, burn therapy, bone growth stimulation, wound healing and thermally mediated gene therapy. Clinical applications include deep heating for various musculoskeletal diseases (rheumatoid arthritis, osteoarthritis, fibrositis and myositis), deep heating for many neuromuscular disorders (muscular dystrophy, progressive muscular atrophy), treatment of various eye disorders (iritis, postoperative uveitis), dental problems (swelling and trismus following extractions, toothache), elevating body temperature following hypothermia surgery and cancer therapy using hyperthermia (40–50 ◦ C).
An Introduction to Modeling of Transport Processes: Applications to Biomedical Systems by Ashim Datta, Vineet Rakesh