ExploreASL: An image processing pipeline for multi-center ASL perfusion MRI studies

Arterial spin labeling (ASL) has undergone significant development since its inception, with a focus on improving standardization and reproducibility of its acquisition and quantification. In a community-wide effort towards robust and reproducible clinical ASL image processing, we developed the software package ExploreASL, allowing standardized analyses across centers and scanners. The procedures used in ExploreASL capitalize on published image processing advancements and address the challenges of multi-center datasets with scanner-specific processing and artifact reduction to limit patient exclusion. ExploreASL is self-contained, written in MATLAB and based on Statistical Parameter Mapping (SPM) and runs on multiple operating systems. To facilitate collaboration and data-exchange, the toolbox follows several standards and recommendations for data structure, provenance, and best analysis practice. ExploreASL was iteratively refined and tested in the analysis of >10,000 ASL scans using different pulse-sequences in a variety of clinical populations, resulting in four processing modules: Import, Structural, ASL, and Population that perform tasks, respectively, for data curation, structural and ASL image processing and quality control, and finally preparing the results for statistical analyses on both single-subject and group level. We illustrate ExploreASL processing results from three cohorts: perinatally HIV-infected children, healthy adults, and elderly at risk for neurodegenerative disease. We show the reproducibility for each cohort when processed at different centers with different operating systems and MATLAB versions, and its effects on the quantification of gray matter cerebral blood flow. ExploreASL facilitates the standardization of image processing and quality control, allowing the pooling of cohorts which may increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice

Nuclear Imaging in Frontotemporal Dementia

Frontotemporal dementia (FTD) covers a range of heterogeneous neurodegenerative syndromes, predominantly affecting the frontal and temporal lobes (frontotemporal lobar degeneration or FTLD). Most patients present with behavioural deficits, executive dysfunction and language difficulties. FTD presents as clinically recognized subtypes with behavioural manifestation (FTD-b) and primary progressive aphasia (PPA), which can be divided into semantic dementia (SD), progressive nonfluent aphasia (PNFA) and logopenic aphasia (LPA). FTD is a common type of dementia, particularly at younger age. The underlying neuropathological process of FTLD leads to the clinical phenotype and can be characterized roughly in tauopathy (FTD-TAU) and TAR DNA-binding protein (TDP-43) pathology. Genetics is an important causal factor for FTD, and genetic heterogeneity is reflected by the identification of mutations in causative genes. Diagnostic criteria have modest sensitivity, and it may be challenging to differentiate FTD from psychiatric disorders or other types of dementia, especially AD. Advances in molecular imaging have increased the accuracy of FTD diagnosis, and nuclear imaging techniques improve the understanding of the molecular basis of FTD, which is important to develop rational therapies. Although currently no effective treatment is available for FTD, early and correct diagnosis is necessary for adequate clinical management, because of prognostic implications and for genetic counselling.</p

Neuroimaging in Frontotemporal Lobar Degeneration: Research and Clinical Utility

Frontotemporal Lobar Dementia (FTLD) is a clinically and pathologically complex disease. Advances in neuroimaging techniques have provided a specialized set of tools to investigate underlying pathophysiology and identify clinical biomarkers that aid in diagnosis, prognostication, monitoring, and identification of appropriate endpoints in clinical trials. In this chapter, we review data discussing the utility of neuroimaging biomarkers in sporadic FTLD, with an emphasis on current and future clinical applications. Among those modalities readily utilized in clinical settings, T-1 weighted structural magnetic resonance imaging (MRI) and 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) are best supported in differential diagnosis and as targets for clinical trial endpoints. However, a number of non-clinical neuroimaging modalities, including diffusion tensor imaging and resting state functional connectivity MRI, show promise as biomarkers to predict progression and as clinical trial endpoints. Other neuroimaging modalities including amyloid PET, Tau PET, and arterial spin labeling MRI are also discussed, though more work is required to establish their utility in FTLD in clinical settings