Neuroimaging findings in frontotemporal lobar degeneration spectrum of disorders

Abstract

Frontotemporal lobar degeneration (FTLD) is a clinically and pathologically heterogeneous spectrum of disorders. In the last few years, neuroimaging has contributed to the phenotypic characterisation of these patients. Complementary to the clinical and neuropsychological evaluations, structural magnetic resonance imaging (MRI) and functional techniques provide important pieces of information for the diagnosis of FTLD. They also appear to be useful in distinguishing FTLD from patients with Alzheimer’s disease (AD). Preliminary studies in pathologically proven cases suggested that distinct patterns of tissue loss could assist in predicting in vivo the pathological subtype. Recent years have also witnessed impressive advances in the development of novel imaging approaches. Diffusion tensor MRI and functional MRI have improved our understanding of the pathophysiology of the disease, and this should lead to the identification of additional useful markers of disease progression. This reviews discusses comprehensively the state-of-the-art of neuroimaging in the study of FTLD spectrum of disorders, and attempts to envisage which will be new neuroimaging biomarkers that could serve as surrogate measures of the underlying pathology. This will be central in the design of treatment trials of experimental drugs, which are likely to emerge in the near future, to target the pathological processes associated with this condition.

Introduction

Frontotemporal lobar degeneration (FTLD) represents the second most common early onset neurodegenerative dementia (Rabinovici and Miller, 2010). FTLD is a clinically and pathologically heterogeneous spectrum of disorders, which encompasses distinct clinical syndromes: the behavioural variant of frontotemporal dementia (bvFTD), and the language variant (Rabinovici and Miller, 2010). bvFTD presents with marked changes in personality and behaviour (Neary et al., 1998), and, pathologically, is associated with all the three major FTLD pathologies, characterised by abnormal cellular inclusions containing either tau, TAR DNA-binding protein 43 (TDP-43), or fused in sarcoma (FUS) protein (Mackenzie et al., 2010). In the language variant, known as primary progressive aphasia (PPA), a prominent, isolated language deficit is the dominant feature during the initial phase of the disease (Mesulam, 2001). Distinct profiles of language impairment define the three clinical phenotypes of PPA (Gorno-Tempini et al., 2011): the non-fluent/agrammatic (for convenience hereafter called as non-fluent), characterised by agrammatism in language production and effortful speech with motor speech deficits; the semantic, characterised by progressive loss of knowledge about words and objects in the context of relatively preserved fluency of speech; and the logopenic, characterised by impaired naming and repetition in the context of spared syntactic and motor speech abilities. The non-fluent variant is most commonly associated with tau pathology (Josephs et al., 2006, Knibb et al., 2006), and the semantic with a TDP-43 proteinopathy (Grossman et al., 2007b, Hodges et al., 2004, Mesulam et al., 2008). Alzheimer’s disease (AD) is the most likely underlying pathology of the more controversial logopenic variant, although FTLD with TDP-43 immunoreactive inclusions (FTLD-TDP) changes can also be found (Josephs et al., 2008, Mesulam et al., 2008).

In the last few years, neuroimaging has contributed to the phenotypic characterisation of FTLD. The most commonly used neuroimaging approaches to assess FTLD are structural magnetic resonance imaging (MRI) and functional molecular techniques, i.e., single photon-emission computed tomography (SPECT) and positron emission tomography (PET). Structural MRI showed that each clinical syndrome is associated with a specific pattern of focal atrophy and is routinely used in the diagnostic work up of FTLD. SPECT allows to study cerebral perfusion with compounds such as the [^99mTc]-hexamethylpropyleneamine oxime (HMPAO). PET, most frequently used with [^18F]-fluorodeoxyglucose (FDG), provides estimates of cerebral metabolism. Overall, functional neuroimaging techniques offer a window on brain states relative to structural imaging or even in the absence of structural brain abnormalities.

Recent years have also witnessed impressive advances in the development of novel imaging approaches, which, with varying degrees of success, had improved our ability to diagnose and understand the pathophysiology of the disease. Diffusion tensor (DT) MRI allows to measure the random diffusional motion of water molecules and, thus, provides quantitative indices of the structural and orientational features of central nervous system tissues (Pierpaoli et al., 1996). Alterations in the brain microstructure associated with FTLD have the potential to modify water diffusion characteristics, which can be reflected in increased mean diffusivity (MD) and reduced fractional anisotropy (FA) values. The PET ligand [^11C]-labelled Pittsburgh compound-B (PIB) binds specifically to fibrillar amyloid β (Aβ) (Klunk et al., 2004). The ability to image Aβ may allow distinction of FTLD from AD with a greater accuracy than that of other structural and functional imaging techniques. Given the costs, limited availability and relative invasiveness of FDG PET, functional MRI (fMRI) is likely to be an useful tool for detecting alterations in brain function that may be present very early in the course of FTLD. In particular, resting state (RS) fMRI has proved to be a new tool for mapping large-scale neural network function and dysfunction in neurodegenerative diseases (Greicius et al., 2004).

This article reviews comprehensively the state-of-the-art of neuroimaging in the study of FTLD spectrum of disorders, and envisages which will be new neuroimaging biomarkers that could improve the in vivo detection of the underlying pathology. This will be central in the design of treatment trials of new drugs targeting the pathological processes associated with FTLD, which are likely to emerge in the near future.