Speech and Language Interventions for Italian People With PPA

Primary progressive aphasia (PPA) is an umbrella term used to refer to several clinical variants that manifest as an insidious deterioration of speech/language skills, usually due to frontotemporal lobar degeneration and/or Alzheimer's disease. Consensus criteria have been proposed by an international community regarding the sub-classification of PPA into three variants: (1) semantic variant PPA, characterized by impaired confrontation naming and single-word comprehension; (2) logopenic variant PPA), characterised by word-finding difficulties and sentence repetition deficits; and (3) non-fluent variant, characterised by agrammatism with or without apraxia of speech. Speech and language therapists (SLTs) play a crucial role in the diagnostic process and in setting a therapeutic path along with monitoring the evolution of the clinical picture. Despite growing evidence supporting the benefits of speech-language intervention, the frequency with which individuals with PPA are referred for speech and language services, is suboptimal likely due to skepticism regarding the value of speech and language therapy in the context of neurodegeneration, the scarcity of SLTs with expertise in the treatment of PPA, the lack of awareness regarding the role of the SLT amongst referrers, and the geographical barriers that impede access to in-person speech and language services. In Italy, patients with PPA are rarely offered treatment options due to a lack of understanding of the disorder on the part of health professionals and erroneous assumptions regarding the utility of treatment in patients facing a worsening prognosis. The primary aim of this pilot study is to develop tailored speech and language interventions for patients with different variants of PPA by addressing their linguistic and cognitive difficulties. Secondly, to explore the intervention's effect also on untreated tasks and assess the long-term maintenance of the proposed interventions by monitoring patients for up to six months. Finally, in each PPA variant, the investigators aim to investigate which variables among the sociodemographic, clinical, linguistic/cognitive, and brain MRI features at baseline predict successful clinical results, as well as which structural and functional brain changes are associated with speech and language improvements.

A total of 30 PPA patients will be recruited, with a clinical and imaging-supported diagnosis of PPA according to the current diagnostic criteria, and MMSE\>15. At the study entry (T0), all patients will undergo a clinical interview, a neurological and neuropsychological evaluation, and a speech and language assessment. All these visits will be repeated soon after the intervention (at week 5, W5), at 3 months (M3), and at 6 months (M6) post-intervention. Specifically, measures of patient's and caregivers' satisfaction and patients' functional communication abilities will be collected as primary outcomes. At baseline (T0) and after intervention (W5), all patients recruited at IRCCS San Raffaele and 40% of patients recruited at IRCCS Maugeri Clinical and Scientific Institute will also perform a brain structural and functional MRI. Thirty healthy controls, matched with PPA cases for age and sex, will be also recruited. Only at baseline (T0), all controls will undergo the same visits as the PPA patients, as well as the brain MRI scan. IRCCS Maugeri Clinical and Scientific Institute will be specifically in charge of the development of the SLT protocols, for the online administration of tailored speech and language interventions and for data analysis. IRCCS Ospedale San Raffaele Milano will be specifically in charge of brain structural and functional MRI acquisition, the definition of task-based functional MRI paradigms, and MRI analysis. This unit will also recruit and collect data on the entire sample of healthy controls. Brain structural and functional changes associated with SLT interventions using the most advanced MRI techniques will be investigated. The sociodemographic, clinical, language, speech, and MRI features obtained in patients will be processed through machine learning to develop a computation paradigm that better defines their prediction value for the intervention's efficacy.