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Dementia is a term for the impaired ability to remember, think, or make decisions that interferes with doing everyday activities. Alzheimer's disease is the most common type of dementia. Though dementia mostly affects older adults, it is not a part of normal aging. This study aims to assess the role of volumetric MRI in evaluation of different types of dementia.
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Neurocognitive disorders (dementia) are prevalent clinical problems. With the increase in average life expectancy, its prevalence is rising at an alarming rate. In 2005, an estimated 24 million people around the world suffered from dementia, and that number is expected to double every 20 years. By 2040, it is predicted that over 81 million people worldwide will suffer from dementia. Most experts agree that treatment will be most beneficial if applied early, before significant, potentially irreversible neurodegeneration and functional impairment has occurred.
Clinical symptoms of most subtypes of dementia arise from progressive neuron and synapse loss, with the resulting tissue atrophy. Brain magnetic resonance imaging (MRI) is regularly used in diagnosing dementia as it visualises the structural changes caused by neurodegeneration. It is key in defining subtle differences between healthy and pathological cerebral volume loss and between dementia subtypes.
Visual assessment of brain atrophy patterns is commonly supported through the use of visual rating scales. However, these scales have a subjective element and their application relies heavily on the prior experience of the radiologist using them. And they have poor sensitivity to subtle or prodromal changes and have ceiling and/or floor effects.
Application of quantitative volumetric reporting tools, which automatically quantify an individual patient's regional brain volumes and compare them to healthy populations, can potentially help in interpretation of the severity and distribution of brain atrophy and contextualize their findings by referencing normative brain volumes in healthy populations. This will improve the accuracy of radiological diagnosis of different subtypes of dementia
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Mohamed Abdeltawab, MD; Ahmed Abdel-Razzak, McS
Data sourced from clinicaltrials.gov
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