Computational modeling can help understand Alzheimer’s disease

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A professor of mechanical engineering explains how computational models of Alzheimer’s spread in the brain are providing new information about the disease.
Physicians diagnose Alzheimer’s disease with tests that measure memory loss and behavioral change. But many years before these symptoms appear, the disease is changing the brain, leading to the buildup of misfolded proteins and brain shrinkage that cause cognitive decline. In this episode of Stanford Engineering’s The Future of Everything, Stanford mechanical engineer Ellen Kuhl explains how she’s using databases of brain images of both Alzheimer’s patients and healthy individuals to create computational models that show how the disease spreads through distinct parts of the brain and gradually impacts different brain functions. Kuhl and host, Stanford bioengineer Russ Altman, explore how these models have generated new insights into how Alzheimer’s affects the brain, as well as its diagnosis and its potential treatment.