Improving short-term prediction from MCI to AD by applying searchlight analysis

Alzheimer's disease (AD) is the most common cause of dementia. Nowadays, 44 million people worldwide suffer from this neurodegenerative disease. Fortunately, the use of new technologies can help doctors in diagnosing this disease in an increasingly early stage, which is vital to prevent its advance. In this work we have developed a new automatic method to predict if patients suffering from mild cognitive impairment (MCI) will develop AD within one year or, conversely, its impairment will remain stable. This technique is based on the so-called Searchlight, a widely known approach in fMRI but which has not been previously used with structural images. Besides analyzing the intensity of the voxels in each of the subregions defined by the Searchlight, data from two neuro-psychological tests were used during the classification process, achieving an accuracy of 84%.