by Sara Soltaninejad
Parkinson’s disease (PD) is the second important degenerative neurological disease (NDDs) next to Alzheimer’s disease that usually causes major threat to the elderly people. Parkinson’s disease is caused by the progressive loss of a particular set of nerve cells that produce dopamine, which has a critical role in transmitting the signals in the brain. Due to degeneration of these cells, the patient faces movement disorders, including muscle rigidity, tremors, and changes in speech and gait. After diagnosis, treatments can help relieve symptoms, but there is no cure. Sometimes, the doctors may suggest surgery to regulate certain regions of the brain hoping to relieve symptoms. Therefore, the research goal is to develop treatments that can slow or halt the progression of the disease before it significantly affects quality of life. As a computing science research, my plan is to facilitate early diagnosis.
The diagnosis of PD is challenging even by experienced clinical experts. Very often, there is no noticeable symptom in the early stage and only at a later stage patients display severe tremor condition (tremor dominant cases). Many clinical tests and non-licensed diagnostic techniques have been conducted, targeting accuracy, repeatability and reliability. But none of them have demonstrated the required accuracy and ease of use that can warrant them as a standard clinical practice. On the other hand, magnetic resonance imaging (MRI) has been referred as “a gold standard” mechanism for studying the brain anatomy of different developmental stage. MRI research has attracted a lot of interest with the belief that it can be used for early diagnosis of Parkinson’s disease.