This research project focuses on understanding and addressing Normal Pressure Hydrocephalus (NPH), a neurological condition affecting older adults characterized by abnormal fluid buildup in the brain, leading to symptoms like walking problems and memory loss. The exact cause is unknown, and diagnosis can be challenging, often mistaken for the effects of aging or other neurological disorders. NPH remains an underdiagnosed and undertreated condition despite the availability of shunts to correct the gait dysfunction that results from this disorder. The main goals are to estimate the prevalence of NPH in aging populations, improve diagnostic methods using advanced imaging and deep learning, and train models for early detection and outcome prediction of shunt surgery. By analyzing MRI data, cognitive performance, and mobility measures in individuals aged 50 or older, the study aims to enhance our understanding of NPH and improve diagnostic accuracy. The use of cutting-edge technologies, including deep learning models, adds innovation to the project.
The expected value of the research is substantial. Beyond contributing to academic knowledge of prevalence, the project seeks to advance the diagnosis and management of NPH, offering potential benefits to individuals affected by the condition. The comprehensive approach, coupled with deep learning models, has the potential to enhance diagnostic accuracy, enabling early detection and better patient outcomes. Overall, the research aligns with public interest by addressing a neglected but reversible neurological condition that predominantly affects older adults, with the potential to positively impact clinical practice and healthcare systems.
