This technology is suggested for use in Alzheimer's Disease, a disease in which current testing strategies are imprecise, especially in indeterminate or asymptomatic cases.
It is estimated that nearly 44 million people worldwide have Alzheimer's Disease or related dementia and that the disease remains undiagnosed in 3 out of 4 people.
A battery of tests with variable sensitivity including cognitive, neuropsychological, imaging and laboratory tests are required in combination to make a diagnosis of AD or a less severe but related condition, such as Mild Cognitive Impairment (MCI).
Even so, it is only with pathological assessment at death that AD diagnosis is definitive. This highlights the challenges and need for a more precise test that can better detect the presence of Alzheimer's Disease in a patient.
This technology screens simple brain MRI images of those with or without symptoms and precisely detects Mild Cognitive Impairment or Alzheimer's Disease in a given patient based on computational assessment of entire brain features.
- Detecting AD or MCI early, and accurately. This provides the best possible chance to apply early therapeutic interventions to halt disease progression
- Aid in better diagnosis and selection of patients for pharmacological studies during clinical trials, which may aid clinical trial success.
Professor Eric Aboagye is a professor at Imperial College and leads the NIHR Biomedical Research Centre Imaging Theme. He was recipient of the 2009 Sir Mackenzie Davidson Medal and was elected as a Fellow of the Academy of Medical Sciences in 2010 for outstanding contributions to the advancement of medical science. He has also acted as an advisor to GE-Healthcare, GSK, Roche and Novartis.