Vijaya Kolachalama, PhD
|Title||Adjunct Assistant Professor|
|Institution||Boston University School of Medicine|
The Kolachalama Laboratory's work is focused on three areas:
1. Machine learning and computer vision for prognosis
Data analytics is poised to help deliver precision medicine, yet achieving this goal is nontrivial. Machine learning and image processing techniques along with developments in software and hardware technologies allow us to consider questions across scales. We leverage these tools for pattern recognition and understanding pathophysiological mechanisms that would pave way towards developing biomedical technologies that are of prognostic relevance.
2. Machine learning and cardiovascular simulation
Cardiovascular applications are among the most important and widely studied cases of medical simulation. Devices such as stents and balloon catheters are used millions of times each year to help manage coronary heart disease, the leading cause of global mortality. Disease progression as well as the success and failure of such devices depend on local physical and biochemical processes coupled within complex physiological environments. Designing and achieving optimal device performance requires that we understand the confluence of fluid flow, drug transport and tissue reactivity coupled within relevant, often patient-specific environments. Recognizing this need, we utilize the theory and practice the application of machine learning to study a range of physiologic factors and their variations on several outputs of interest within the cardiovascular domain.
3. Mechanisms of endovascular therapies
Computational modeling approaches quantify aspects of device-based therapies at a resolution that is not possible to achieve using bench-top investigation or in vivo models alone. The models that we developed have explained the role of physiologic factors in determining maps of spatiotemporal arterial distribution patterns for drug-eluting devices as a function of intrinsic device design, relative device position and pulsatile nature of blood flow. We have extended models simulating idealized settings of physiology to real world issues and further examine and predict arterial tissue response that varies due to procedural settings, device composition, arterial wall ultrastructure and disease, physiologic changes within complex vascular anatomies, vascular injury and the mode of drug delivery. Understanding the mechanisms of endovascular therapies and developing new technologies is one of the core research themes of our laboratory.
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