and Alzheimer’s disease. This was done by analyzing the MRIs of patients with each of the subsets of PPA. Images which compare subtypes of aphasia as well as for finding the extent of lesions are generated by overlapping images of different participant's brains (if applicable) and isolating areas of lesions or damage using third party software such as MRIcron. MRI has also been used to study the relationship between the type of aphasia developed and the age of the person with aphasia. It was found that patients with fluent aphasia are on average older than people with non-fluent aphasia. It was also found that among patients with lesions confined to the anterior portion of the brain an unexpected portion of them presented with fluent aphasia and were remarkably older than those with non-fluent aphasia. This effect was not found when the posterior portion of the brain was studied. Associated Conditions In a study on the features associated with different disease trajectories in Alzheimer's disease (AD)-related primary progressive aphasia (PPA), it was found that metabolic patterns via PET SPM analysis can help predict progression of total loss of speech and functional autonomy in AD and PPA patients. This was done by comparing an MRI or CT image of the brain and presence of a radioactive biomarker with normal levels in patients without Alzheimer’s Disease. Apraxia is another disorder often correlated with aphasia. This is due to a subset of apraxia which affects speech. Specifically, this subset affects the movement of muscles associated with speech production, apraxia and aphasia are often correlated due to the proximity of neural substrates associated with each of the disorders. Researchers concluded that there were 2 areas of lesion overlap between patients with apraxia and aphasia, the anterior temporal lobe and the left inferior parietal lobe. Treatment and Neuroimaging Evidence for positive treatment outcomes can also be quantified using neuroimaging tools. The use of fMRI and an automatic classifier can help predict language recovery outcomes in stroke patients with 86% accuracy when coupled with age and language test scores. The stimuli tested were sentences both correct and incorrect and the subject had to press a button whenever the sentence was incorrect. The fMRI data collected focused on responses in regions of interest identified by healthy subjects. Recovery from aphasia can also be quantified using diffusion tensor imaging. The accurate fasciculus (AF) connects the right and left superior