Background and Objectives Patients with primary progressive aphasia (PPA) have gradually progressive language deficits during the initial phase of the illness. As the underlying neurodegenerative disease progresses, patients with PPA start losing independent functioning due to the development of nonlanguage cognitive or behavioral symptoms. The timeline of this progression from the mild cognitive impairment stage to the dementia stage of PPA is variable across patients. In this study, in a sample of patients with PPA, we measured the magnitude of cortical atrophy within functional networks believed to subserve diverse cognitive and affective functions. The objective of the study was to evaluate the utility of this measure as a predictor of time to subsequent progression to dementia in PPA.
Methods Patients with PPA with largely independent daily function were recruited through the Massachusetts General Hospital Frontotemporal Disorders Unit. All patients underwent an MRI scan at baseline. Cortical atrophy was then estimated relative to a group of amyloid-negative cognitively normal control participants. For each patient, we measured the time between the baseline visit and the subsequent visit at which dementia progression was documented or last observation. Simple and multivariable Cox regression models were used to examine the relationship between cortical atrophy and the likelihood of progression to dementia.
Results Forty-nine patients with PPA (mean age = 66.39 ± 8.36 years, 59.2% females) and 25 controls (mean age = 67.43 ± 4.84 years, 48% females) were included in the data analysis. Greater baseline atrophy in not only the left language network (hazard ratio = 1.47, 95% CI = 1.17–1.84) but also in the frontoparietal control (1.75, 1.25–2.44), salience (1.63, 1.25–2.13), default mode (1.55, 1.19–2.01), and ventral frontotemporal (1.41, 1.16–1.71) networks was associated with a higher risk of progression to dementia. A multivariable model identified contributions of the left frontoparietal control (1.94, 1.09–3.48) and ventral frontotemporal (1.61, 1.09–2.39) networks in predicting dementia progression, with no additional variance explained by the language network (0.75, 0.43–1.31).