Early-stage differentiation between presenile Alzheimer's disease and frontotemporal dementia using arterial spin labeling MRI

Arterial Spin Labeling MRI in Alzheimer's Disease: A Systematic Review of Cerebral Perfusion Biomarkers

BACKGROUND

Alzheimer's disease (AD) is a leading cause of dementia. Arterial spin labeling (ASL) MRI, particularly at 3 Tesla (3T), offers a noninvasive method to assess cerebral blood flow alterations, which are believed to be early indicators of AD.

PURPOSE

The purpose of this study is to evaluate the utility of 3T ASL MRI in identifying cerebral perfusion biomarkers for the diagnosis and management of AD, assess its prognostic value, and compare it to other imaging modalities, such as PET.

DATA SOURCES

A systematic literature search was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines across PubMed, Cochrane Library, and Scopus using keywords related to "ASL," "3T MRI," and "AD."

STUDY SELECTION

Studies were included if they used 3T ASL MRI to investigate CBF in AD. Reviews, preclinical studies, case reports, studies lacking 3T ASL MRI, or those focusing on other dementias or mild cognitive impairment without an AD comparison were excluded. Data extracted included study design, sample characteristics, imaging techniques, parameters measured, and outcomes. A qualitative synthesis of findings highlights CBF patterns and biomarkers associated with AD.

RESULTS

Findings demonstrated hypoperfusion in the hippocampus, precuneus, and posterior cingulate cortex, distinguishing AD from normal aging and other forms of dementia. CBF patterns are often correlated with the severity and progression of cognitive impairment. ASL MRI at 3T demonstrated diagnostic accuracy comparable to that of PET while being noninvasive and radiation free.

CONCLUSION

ASL MRI at 3T could be a valuable tool for the early diagnosis and monitoring of AD. Its noninvasive nature makes it ideal for repeated measures and longitudinal studies. Further research should focus on standardizing protocols and validating their use in larger populations.

Frontotemporal dementia. How to deal with its diagnostic complexity?

INTRODUCTION

Frontotemporal dementia (FTD) encompasses a group of heterogeneous neurodegenerative disorders. Aside from genetic cases, its diagnosis is challenging, particularly in the early stages when symptoms are ambiguous, and structural neuroimaging does not reveal characteristic patterns.

AREAS COVERED

The authors performed a comprehensive literature search through MEDLINE, Scopus, and Web of Science databases to gather evidence to aid the diagnostic process for suspected FTD patients, particularly in early phases, even in sporadic cases, ranging from established to promising tools. Blood-based biomarkers might help identify very early neuropathological stages and guide further evaluations. Subsequently, neurophysiological measures reflecting functional changes in cortical excitatory/inhibitory circuits, along with functional neuroimaging assessing brain network, connectivity, metabolism, and perfusion alterations, could detect specific changes associated to FTD even decades before symptom onset. As the neuropathological process advances, cognitive-behavioral profiles and atrophy patterns emerge, distinguishing specific FTD subtypes.

EXPERT OPINION

Emerging disease-modifying therapies require early patient enrollment. Therefore, a diagnostic paradigm shift is needed - from relying on typical cognitive and neuroimaging profiles of advanced cases to widely applicable biomarkers, primarily fluid biomarkers, and, subsequently, neurophysiological and functional neuroimaging biomarkers where appropriate. Additionally, exploring subjective complaints and behavioral changes detected by home-based technologies might be crucial for early diagnosis.

Cerebral perfusion correlates with amyloid deposition in patients with mild cognitive impairment due to Alzheimer's disease

BACKGROUND

Changes in cerebral blood flow (CBF) may contribute to the initial stages of the pathophysiological process in patients with Alzheimer's disease (AD). Hypoperfusion has been observed in several brain regions in patients with mild cognitive impairment (MCI). However, the clinical significance of CBF changes in the early stages of AD is currently unclear.

OBJECTIVES

The aim of this study was to investigate the characteristics, diagnostic value and cognitive correlation of cerebral perfusion measured with arterial spin labeling (ASL) magnetic resonance imaging (MRI) in patients with MCI due to AD.

DESIGN, SETTING AND PARTICIPANTS

A total of fifty-nine MCI patients and 49 cognitively unimpaired controls (CUCs) were recruited and underwent multimodal MRI scans, including pseudocontinuous ASL, and neurocognitive testing. MCI patients were dichotomously classified according to the presence of amyloid deposition on 11C-labelled Pittsburgh compound B (PiB) positron emission tomography (PET).

MEASUREMENTS

The differences in CBF and expression of the AD-related perfusion pattern (ADRP), established by spatial covariance analysis in our previous study, were compared between the PiB+ MCI group and the CUC group and between the PiB+ and PiB- MCI groups. The diagnostic accuracy and correlations with cognitive function scores for CBF and ADRP expression were further analyzed.

RESULTS

Hypoperfusion in the precuneus and posterior cingulate cortex (PCC) was more characteristic of patients with MCI due to AD than of those with non-AD-related MCI. The relative regional CBF value of the left precuneus best distinguished patients with MCI due to AD from CUCs and patients with MCI due to non-AD conditions. Cerebral perfusion, as indicated by either the relative regional CBF or the expression score of the ADRP, was strongly correlated with certain cognitive function scores.

CONCLUSIONS

Here, we show that changes in CBF in the precuneus/PCC are promising MRI biomarkers for the identification of an AD etiology in patients with MCI. ASL, a noninvasive and cost-effective tool, has broad application prospects in the screening and early diagnosis of AD.

Arterial Spin Labeling: Key Concepts and Progress Towards Use as a Clinical Tool

Arterial spin labeling (ASL), a non-invasive MRI technique, has emerged as a valuable tool for researchers that can measure blood flow and related parameters. This review aims to provide a qualitative overview of the technical principles and recent developments in ASL and to highlight its potential clinical applications. A growing literature demonstrates impressive ASL sensitivity to a range of neuropathologies and treatment responses. Despite its potential, challenges persist in the translation of ASL to widespread clinical use, including the lack of standardization and the limited availability of comprehensive training. As experience with ASL continues to grow, the final stage of translation will require moving beyond single site observational studies to multi-site experience and measurement of the added contribution of ASL to patient care and outcomes.

Arterial spin labelling magnetic resonance imaging and perfusion patterns in neurocognitive and other mental disorders: a systematic review

We reviewed 33 original research studies assessing brain perfusion, using consensus guidelines from a "white paper" issued by the International Society for Magnetic Resonance in Medicine Perfusion Study Group and the European Cooperation in Science and Technology Action BM1103 ("Arterial Spin Labelling Initiative in Dementia"; https://www.cost.eu/actions/BM1103/ ). The studies were published between 2011 and 2023 and included participants with subjective cognitive decline plus; neurocognitive disorders, including mild cognitive impairment (MCI), Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD), dementia with Lewy bodies (DLB) and vascular cognitive impairment (VCI); as well as schizophrenia spectrum disorders, bipolar and major depressive disorders, autism spectrum disorder, attention-deficit/hyperactivity disorder, panic disorder and alcohol use disorder. Hypoperfusion associated with cognitive impairment was the major finding across the spectrum of cognitive decline. Regional hyperperfusion also was reported in MCI, AD, frontotemporal dementia phenocopy syndrome and VCI. Hypoperfused structures found to aid in diagnosing AD included the precunei and adjacent posterior cingulate cortices. Hypoperfused structures found to better diagnose patients with FTLD were the anterior cingulate cortices and frontal regions. Hypoperfusion in patients with DLB was found to relatively spare the temporal lobes, even after correction for partial volume effects. Hyperperfusion in the temporal cortices and hypoperfusion in the prefrontal and anterior cingulate cortices were found in patients with schizophrenia, most of whom were on medication and at the chronic stage of illness. Infratentorial structures were found to be abnormally perfused in patients with bipolar or major depressive disorders. Brain perfusion abnormalities were helpful in diagnosing most neurocognitive disorders. Abnormalities reported in VCI and the remaining mental disorders were heterogeneous and not generalisable.

A systematic review of automated methods to perform white matter tract segmentation

White matter tract segmentation is a pivotal research area that leverages diffusion-weighted magnetic resonance imaging (dMRI) for the identification and mapping of individual white matter tracts and their trajectories. This study aims to provide a comprehensive systematic literature review on automated methods for white matter tract segmentation in brain dMRI scans. Articles on PubMed, ScienceDirect [NeuroImage, NeuroImage (Clinical), Medical Image Analysis], Scopus and IEEEXplore databases and Conference proceedings of Medical Imaging Computing and Computer Assisted Intervention Society (MICCAI) and International Symposium on Biomedical Imaging (ISBI), were searched in the range from January 2013 until September 2023. This systematic search and review identified 619 articles. Adhering to the specified search criteria using the query, "white matter tract segmentation OR fiber tract identification OR fiber bundle segmentation OR tractography dissection OR white matter parcellation OR tract segmentation," 59 published studies were selected. Among these, 27% employed direct voxel-based methods, 25% applied streamline-based clustering methods, 20% used streamline-based classification methods, 14% implemented atlas-based methods, and 14% utilized hybrid approaches. The paper delves into the research gaps and challenges associated with each of these categories. Additionally, this review paper illuminates the most frequently utilized public datasets for tract segmentation along with their specific characteristics. Furthermore, it presents evaluation strategies and their key attributes. The review concludes with a detailed discussion of the challenges and future directions in this field.

The use of neuroimaging techniques in the early and differential diagnosis of dementia

Dementia is a leading cause of disability and death worldwide. At present there is no disease modifying treatment for any of the most common types of dementia such as Alzheimer's disease (AD), Vascular dementia, Lewy Body Dementia (LBD) and Frontotemporal dementia (FTD). Early and accurate diagnosis of dementia subtype is critical to improving clinical care and developing better treatments. Structural and molecular imaging has contributed to a better understanding of the pathophysiology of neurodegenerative dementias and is increasingly being adopted into clinical practice for early and accurate diagnosis. In this review we summarise the contribution imaging has made with particular focus on multimodal magnetic resonance imaging (MRI) and positron emission tomography imaging (PET). Structural MRI is widely used in clinical practice and can help exclude reversible causes of memory problems but has relatively low sensitivity for the early and differential diagnosis of dementia subtypes. 18F-fluorodeoxyglucose PET has high sensitivity and specificity for AD and FTD, while PET with ligands for amyloid and tau can improve the differential diagnosis of AD and non-AD dementias, including recognition at prodromal stages. Dopaminergic imaging can assist with the diagnosis of LBD. The lack of a validated tracer for α-synuclein or TAR DNA-binding protein 43 (TDP-43) imaging remain notable gaps, though work is ongoing. Emerging PET tracers such as 11C-UCB-J for synaptic imaging may be sensitive early markers but overall larger longitudinal multi-centre cross diagnostic imaging studies are needed.

Current state and guidance on arterial spin labeling perfusion MRI in clinical neuroimaging

This article focuses on clinical applications of arterial spin labeling (ASL) and is part of a wider effort from the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group to update and expand on the recommendations provided in the 2015 ASL consensus paper. Although the 2015 consensus paper provided general guidelines for clinical applications of ASL MRI, there was a lack of guidance on disease-specific parameters. Since that time, the clinical availability and clinical demand for ASL MRI has increased. This position paper provides guidance on using ASL in specific clinical scenarios, including acute ischemic stroke and steno-occlusive disease, arteriovenous malformations and fistulas, brain tumors, neurodegenerative disease, seizures/epilepsy, and pediatric neuroradiology applications, focusing on disease-specific considerations for sequence optimization and interpretation. We present several neuroradiological applications in which ASL provides unique information essential for making the diagnosis. This guidance is intended for anyone interested in using ASL in a routine clinical setting (i.e., on a single-subject basis rather than in cohort studies) building on the previous ASL consensus review.

Classifying Alzheimer's disease and frontotemporal dementia using machine learning with cross-sectional and longitudinal magnetic resonance imaging data

Alzheimer's disease (AD) and frontotemporal dementia (FTD) are common causes of dementia with partly overlapping, symptoms and brain signatures. There is a need to establish an accurate diagnosis and to obtain markers for disease tracking. We combined unsupervised and supervised machine learning to discriminate between AD and FTD using brain magnetic resonance imaging (MRI). We included baseline 3T-T1 MRI data from 339 subjects: 99 healthy controls (CTR), 153 AD and 87 FTD patients; and 2-year follow-up data from 114 subjects. We obtained subcortical gray matter volumes and cortical thickness measures using FreeSurfer. We used dimensionality reduction to obtain a single feature that was later used in a support vector machine for classification. Discrimination patterns were obtained with the contribution of each region to the single feature. Our algorithm differentiated CTR versus AD and CTR versus FTD at the cross-sectional level with 83.3% and 82.1% of accuracy. These increased up to 90.0% and 88.0% with longitudinal data. When we studied the classification between AD versus FTD we obtained an accuracy of 63.3% at the cross-sectional level and 75.0% for longitudinal data. The AD versus FTD versus CTR classification has reached an accuracy of 60.7%, and 71.3% for cross-sectional and longitudinal data respectively. Disease discrimination brain maps are in concordance with previous results obtained with classical approaches. By using a single feature, we were capable to classify CTR, AD, and FTD with good accuracy, considering the inherent overlap between diseases. Importantly, the algorithm can be used with cross-sectional and longitudinal data.

Differentiation of Alzheimer’s Disease from Frontotemporal Dementia and Mild Cognitive Impairment Based on Arterial Spin Labeling Magnetic Resonance Imaging: A Pilot Cross-Sectional Study from PUMCH Dementia Cohort

Background: Arterial spin labeling (ASL) is helpful in early diagnosis and differential diagnosis of Alzheimer’s disease (AD), with advantages including no exposure to radioactivity, no injection of a contrast agent, more accessible, and relatively less expensive. Objective: To establish the perfusion pattern of different dementia in Chinese population and evaluate the effectiveness of ASL in differentiating AD from cognitive unimpaired (CU), mild cognitive impairment (MCI), and frontotemporal dementia (FTD). Methods: Four groups of participants were enrolled, including AD, FTD, MCI, and CU based on clinical diagnosis from PUMCH dementia cohort. ASL image was collected using 3D spiral fast spin echo–based pseudo-continuous ASL pulse sequence with background suppression and a high resolution T1-weighted scan covering the whole brain. Data processing was performed using Dr. Brain Platform to get cerebral blood flow (ml/100g/min) in every region of interest cortices. Results: Participants included 66 AD, 26 FTD, 21 MCI, and 21 CU. Statistically, widespread hypoperfusion neocortices, most significantly in temporal-parietal-occipital cortices, but not hippocampus and subcortical nucleus were found in AD. Hypoperfusion in parietal lobe was most significantly associated with cognitive decline in AD. Hypoperfusion in parietal lobe was found in MCI and extended to adjacent temporal, occipital and posterior cingulate cortices in AD. Significant reduced perfusion in frontal and temporal cortices, including subcortical nucleus and anterior cingulate cortex were found in FTD. Hypoperfusion regions were relatively symmetrical in AD and left predominant especially in FTD. Conclusion: Specific patterns of ASL hypoperfusion were helpful in differentiating AD from CU, MCI, and FTD.

Multimodality imaging of neurodegenerative disorders with a focus on multiparametric magnetic resonance and molecular imaging

Neurodegenerative diseases afflict a large number of persons worldwide, with the prevalence and incidence of dementia rapidly increasing. Despite their prevalence, clinical diagnosis of dementia syndromes remains imperfect with limited specificity. Conventional structural-based imaging techniques also lack the accuracy necessary for confident diagnosis. Multiparametric magnetic resonance imaging and molecular imaging provide the promise of improving specificity and sensitivity in the diagnosis of neurodegenerative disease as well as therapeutic monitoring of monoclonal antibody therapy. This educational review will briefly focus on the epidemiology, clinical presentation, and pathologic findings of common and uncommon neurodegenerative diseases. Imaging features of each disease spanning from conventional magnetic resonance sequences to advanced multiparametric methods such as resting-state functional magnetic resonance imaging and arterial spin labeling imaging will be described in detail. Additionally, the review will explore the findings of each diagnosis on molecular imaging including single-photon emission computed tomography and positron emission tomography with a variety of clinically used and experimental radiotracers. The literature and clinical cases provided demonstrate the power of advanced magnetic resonance imaging and molecular techniques in the diagnosis of neurodegenerative diseases and areas of future and ongoing research. With the advent of combined positron emission tomography/magnetic resonance imaging scanners, hybrid protocols utilizing both techniques are an attractive option for improving the evaluation of neurodegenerative diseases.

Recent Technical Developments in ASL: A Review of the State of the Art

This review article provides an overview of a range of recent technical developments in advanced arterial spin labeling (ASL) methods that have been developed or adopted by the community since the publication of a previous ASL consensus paper by Alsop et al. It is part of a series of review/recommendation papers from the International Society for Magnetic Resonance in Medicine Perfusion Study Group. Here, we focus on advancements in readouts and trajectories, image reconstruction, noise reduction, partial volume correction, quantification of nonperfusion parameters, fMRI, fingerprinting, vessel selective ASL, angiography, deep learning, and ultrahigh field ASL. We aim to provide a high level of understanding of these new approaches and some guidance for their implementation, with the goal of facilitating the adoption of such advances by research groups and by MRI vendors. Topics outside the scope of this article that are reviewed at length in separate articles include velocity selective ASL, multiple-timepoint ASL, body ASL, and clinical ASL recommendations.

Arterial spin labeling demonstrates preserved regional cerebral blood flow in the P301L mouse model of tauopathy

There is growing evidence for the vascular contribution to cognitive impairment and dementia in Alzheimer's disease (AD) and other neurodegenerative diseases. While perfusion deficits have been observed in patients with Alzheimer's disease and tauopaties, little is known about the role of tau in vascular dysfunction. In the present study, regional cerebral blood (rCBF) was characterized in P301L mice with arterial spin labeling. No differences in rCBF in P301L mice compared to their age-matched non-transgenic littermates at mid (10-12 months of age) and advanced (19-21 months of age) disease stages. This was concomitant with preservation of cortical brain structure as assessed with structural T₂-weighted magnetic resonance imaging. These results show that hypoperfusion and neurodegeneration are not a phenotype of P301L mice. More studies are thus needed to understand the relationship of tau, neurodegeneration and vascular dysfunction and its modulators in AD and primary tauopathies.

Proportional Changes in Cognitive Subdomains During Normal Brain Aging

Background: Neuroscience lacks a reliable method of screening the early stages of dementia. Objective: To improve the diagnostics of age-related cognitive functions by developing insight into the proportionality of age-related changes in cognitive subdomains. Materials and Methods: We composed a battery of psychophysiological tests and collected an open-access psychophysiological outcomes of brain atrophy (POBA) dataset by testing individuals without dementia. To extend the utility of machine learning (ML) classification in cognitive studies, we proposed estimates of the disproportional changes in cognitive functions: an index of simple reaction time to decision-making time (ISD), ISD with the accuracy performance (ISDA), and an index of performance in simple and complex visual-motor reaction with account for accuracy (ISCA). Studying the distribution of the values of the indices over age allowed us to verify whether diverse cognitive functions decline equally throughout life or there is a divergence in age-related cognitive changes. Results: Unsupervised ML clustering shows that the optimal number of homogeneous age groups is four. The sample is segregated into the following age-groups: Adolescents ∈ [0, 20), Young adults ∈ [20, 40), Midlife adults ∈ [40, 60) and Older adults ≥60 year of age. For ISD, ISDA, and ISCA values, only the median of the Adolescents group is different from that of the other three age-groups sharing a similar distribution pattern (p > 0.01). After neurodevelopment and maturation, the indices preserve almost constant values with a slight trend toward functional decline. The reaction to a moving object (RMO) test results (RMO_mean) follow another tendency. The Midlife adults group's median significantly differs from the remaining three age subsamples (p < 0.01). No general trend in age-related changes of this dependent variable is observed. For all the data (ISD, ISDA, ISCA, and RMO_mean), Levene's test reveals no significant changes of the variances in age-groups (p > 0.05). Homoscedasticity also supports our assumption about a linear dependency between the observed features and age. Conclusion: In healthy brain aging, there are proportional age-related changes in the time estimates of information processing speed and inhibitory control in task switching. Future studies should test patients with dementia to determine whether the changes of the aforementioned indicators follow different patterns.

Integrated Positron Emission Tomography/Magnetic Resonance Imaging in clinical diagnosis of Alzheimer's disease

Alzheimer's disease (AD), a progressive neurodegenerative disease which seriously endangers the health of the aged, is the most common etiology of senile dementia. With the increasing progress of neuroimaging technology, more and more imaging methods have been applied to study Alzheimer's disease. The emergence of integrated PET/MRI (Positron Emission Tomography/Magnetic Resonance Imaging) is a major advance in multimodal molecular imaging with many advantages on the structure of resolution and contrast of image over computed tomography (CT), PET and MRI. PET/MRI is now used stepwise in neurodegenerative diseases, and also has broad prospect of application in the early diagnosis of AD. In this review, we emphatically introduce the imaging advances of AD including functional imaging and molecular imaging, the advantages of PET/MRI over other imaging methods and prospects of PET/MRI in AD clinical diagnosis, especially in early diagnosis, clinical assessment and prediction on AD.

Multiparametric magnetic resonance imaging and positron emission tomography findings in neurodegenerative diseases: Current status and future directions

Neurodegenerative diseases (NDDs) are characterized by progressive neuronal loss, leading to dementia and movement disorders. NDDs broadly include Alzheimer's disease, frontotemporal lobar degeneration, parkinsonian syndromes, and prion diseases. There is an ever-increasing prevalence of mild cognitive impairment and dementia, with an accompanying immense economic impact, prompting efforts aimed at early identification and effective interventions. Neuroimaging is an essential tool for the early diagnosis of NDDs in both clinical and research settings. Structural, functional, and metabolic imaging modalities, including magnetic resonance imaging (MRI) and positron emission tomography (PET), are widely available. They show encouraging results for diagnosis, monitoring, and treatment response evaluation. The current review focuses on the complementary role of various imaging modalities in relation to NDDs, the qualitative and quantitative utility of newer MRI techniques, novel radiopharmaceuticals, and integrated PET/MRI in the setting of NDDs.

Partial volume correction in arterial spin labeling perfusion MRI: A method to disentangle anatomy from physiology or an analysis step too far?

The mismatch in the spatial resolution of Arterial Spin Labeling (ASL) MRI perfusion images and the anatomy of functionally distinct tissues in the brain leads to a partial volume effect (PVE), which in turn confounds the estimation of perfusion into a specific tissue of interest such as gray or white matter. This confound occurs because the image voxels contain a mixture of tissues with disparate perfusion properties, leading to estimated perfusion values that reflect primarily the volume proportions of tissues in the voxel rather than the perfusion of any particular tissue of interest within that volume. It is already recognized that PVE influences studies of brain perfusion, and that its effect might be even more evident in studies where changes in perfusion are co-incident with alterations in brain structure, such as studies involving a comparison between an atrophic patient population vs control subjects, or studies comparing subjects over a wide range of ages. However, the application of PVE correction (PVEc) is currently limited and the employed methodologies remain inconsistent. In this article, we outline the influence of PVE in ASL measurements of perfusion, explain the main principles of PVEc, and provide a critique of the current state of the art for the use of such methods. Furthermore, we examine the current use of PVEc in perfusion studies and whether there is evidence to support its wider adoption. We conclude that there is sound theoretical motivation for the use of PVEc alongside conventional, 'uncorrected', images, and encourage such combined reporting. Methods for PVEc are now available within standard neuroimaging toolboxes, which makes our recommendation straightforward to implement. However, there is still more work to be done to establish the value of PVEc as well as the efficacy and robustness of existing PVEc methods.

Visualization of incidentally imaged pituitary gland on three-dimensional arterial spin labeling of the brain

OBJECTIVE

To evaluate the visualization of incidentally imaged normal pituitary gland on three-dimensional (3D) pseudo continuous arterial spin labeling (PCASL) perfusion imaging of the brain.

METHODS

Ninety-three patients with a normal pituitary gland who underwent 3D PCASL for suspected brain diseases were retrospectively included. Visualization of the pituitary gland on PCASL cerebral blood flow (CBF) maps was assessed independently by two observers using a three-point grading system: Grade 1, pituitary CBF ≤ CBF of the cerebral white matter (WM); Grade 2, CBF of WM < pituitary CBF ≤ CBF of the cortical gray matter (GM); and Grade 3, CBF of GM < pituitary CBF. The interobserver agreement of visual grading was determined using weighted κ statistic. The associations of visual grades with age, sex, and pituitary volume were assessed using multivariate logistic regression. Pituitary glands were divided equally into three groups (small, medium, and large) according to their volume for categorization.

RESULTS

The interobserver agreement for visual rating was excellent (weighted κ = 0.823). Of the 93 cases, Grades 1, 2, and 3 included 17 (18.3%), 41 (44.1%), and 35 cases (37.6%), respectively. Medium and large pituitary volume were significantly associated with Grade 3 visualization (p = 0.0153, OR = 4.8323; 95% CI: 1.3525, 17.2649 and p = 0.0009; OR = 9.0299; 95% CI: 2.4663, 33.0614, respectively), whereas there was no significant association for age or sex.

CONCLUSION

The normal pituitary gland is often visualized with higher CBF than cortical GM on 3D PCASL, especially in individuals with larger pituitary volume.

ADVANCES IN KNOWLEDGE

Appearance of the normal pituitary gland on 3D PCASL has been documented for the first time.

Detection of age related differences in CBF with PCASL using 2 post label delays

BACKGROUND

The brain is reliant on an abundant and uninterrupted CBF for normal neural function because it is an organ with high metabolic activity and limited ability to store energy.

PURPOSE

This study aimed to compare age-related variations in CBF measured with PCASL.

METHODS

This prospective study included healthy volunteers at the Radiology Department of Shanxi Cardiovascular Hospital between October 2018 and July 2019. The volunteers were divided into three groups (n = 30 per group): young (≤44 years), middle-aged (45-59 years) and elderly (≥60 years). CBF was measured by PCASL using 2 post label delays (PLD) (PLD = 1.5 s, 2.5 s), and compared between PLDs and groups. The relation between CBF value and age was assessed by Pearson correlation analysis.

RESULTS

For PLD = 1.5 s, CBF differed significantly between groups for all brain regions (P < 0.05), with higher values in the young group and lower values in the elderly group. For PLD = 2.5 s, the young and middle-aged groups had broadly comparable CBF values, whereas the elderly group had higher CBF values (P < 0.05) for most brain regions. For both PLDs, no brain regions showed significant differences in CBF values between males and females. The CBF of all brain regions was negatively correlated with age for PLD = 1.5 s (P < 0.05) but not PLD = 2.5 s. Compared with PLD = 1.5 s, PLD = 2.5 s yielded lower CBF values for the young group and higher CBF values for the elderly group.

CONCLUSION

3D-pCASL with dual PLDs can non-invasively evaluate age-related changes in CBF in healthy people.

Cerebrovascular reactivity measurements using simultaneous 15O-water PET and ASL MRI: Impacts of arterial transit time, labeling efficiency, and hematocrit

Cerebrovascular reactivity (CVR) reflects the capacity of the brain to meet changing physiological demands and can predict the risk of cerebrovascular diseases. CVR can be obtained by measuring the change in cerebral blood flow (CBF) during a brain stress test where CBF is altered by a vasodilator such as acetazolamide. Although the gold standard to quantify CBF is PET imaging, the procedure is invasive and inaccessible to most patients. Arterial spin labeling (ASL) is a non-invasive and quantitative MRI method to measure CBF, and a consensus guideline has been published for the clinical application of ASL. Despite single post labeling delay (PLD) pseudo-continuous ASL (PCASL) being the recommended ASL technique for CBF quantification, it is sensitive to variations to the arterial transit time (ATT) and labeling efficiency induced by the vasodilator in CVR studies. Multi-PLD ASL controls for the changes in ATT, and velocity selective ASL is in theory insensitive to both ATT and labeling efficiency. Here we investigate CVR using simultaneous ¹⁵O-water PET and ASL MRI data from 19 healthy subjects. CVR and CBF measured by the ASL techniques were compared using PET as the reference technique. The impacts of blood T1 and labeling efficiency on ASL were assessed using individual measurements of hematocrit and flow velocity data of the carotid and vertebral arteries measured using phase-contrast MRI. We found that multi-PLD PCASL is the ASL technique most consistent with PET for CVR quantification (group mean CVR of the whole brain = 42 ± 19% and 40 ± 18% respectively). Single-PLD ASL underestimated the CVR of the whole brain significantly by 15 ± 10% compared with PET (p<0.01, paired t-test). Changes in ATT pre- and post-acetazolamide was the principal factor affecting ASL-based CVR quantification. Variations in labeling efficiency and blood T1 had negligible effects.

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, T1-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 nonclinical 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.

A Tensor-Based Framework for rs-fMRI Classification and Functional Connectivity Construction

Recently, machine learning methods have gained lots of attention from researchers seeking to analyze brain images such as Resting-State Functional Magnetic Resonance Imaging (rs-fMRI) to obtain a deeper understanding of the brain and such related diseases, for example, Alzheimer's disease. Finding the common patterns caused by a brain disorder through analysis of the functional connectivity (FC) network along with discriminating brain diseases from normal controls have long been the two principal goals in studying rs-fMRI data. The majority of FC extraction methods calculate the FC matrix for each subject and then use simple techniques to combine them and obtain a general FC matrix. In addition, the state-of-the-art classification techniques for finding subjects with brain disorders also rely on calculating an FC for each subject, vectorizing, and feeding them to the classifier. Considering these problems and based on multi-dimensional nature of the data, we have come up with a novel tensor framework in which a general FC matrix is obtained without the need to construct an FC matrix for each sample. This framework also allows us to reduce the dimensionality and create a novel discriminant function that rather than using FCs works directly with each sample, avoids vectorization in any step, and uses the test data in the training process without forcing any prior knowledge of its label into the classifier. Extensive experiments using the ADNI dataset demonstrate that our proposed framework effectively boosts the fMRI classification performance and reveals novel connectivity patterns in Alzheimer's disease at its early stages.

Consistent Cerebral Blood Flow Covariance Networks across Healthy Individuals and Their Similarity with Resting State Networks and Vascular Territories

Cerebral blood flow (CBF) represents the local blood supply to the brain, and it can be considered a proxy for neuronal activation. Independent component analysis (ICA) can be applied to CBF maps to derive patterns of spatial covariance across subjects. In the present study, we aimed to assess the consistency of the independent components derived from CBF maps (CBF-ICs) across a cohort of 92 healthy individuals. Moreover, we evaluated the spatial similarity of CBF-ICs with respect to resting state networks (RSNs) and vascular territories (VTs). The data were acquired on a 1.5 T scanner using arterial spin labeling (ASL) and resting state functional magnetic resonance imaging. Similarity was assessed considering the entire ASL dataset. Consistency was evaluated by splitting the dataset into subsamples according to three different criteria: (1) random split of age and sex-matched subjects, (2) elderly vs. young, and (3) males vs. females. After standard preprocessing, ICA was performed. Both consistency and similarity were assessed by visually comparing the CBF-ICs. Then, the degree of spatial overlap was quantified with Dice Similarity Coefficient (DSC). Frontal, left, and right occipital, cerebellar, and thalamic CBF-ICs were consistently identified among the subsamples, independently of age and sex, with fair to moderate overlap (0.2 < DSC ≤ 0.6). These regions are functional hubs, and their involvement in many neurodegenerative pathologies has been observed. As slight to moderate overlap (0.2< DSC < 0.5) was observed between CBF-ICs and some RSNs and VTs, CBF-ICs may mirror a combination of both functional and vascular brain properties.

Tau reduction in aged mice does not impact Microangiopathy

Microangiopathy, including proliferation of small diameter capillaries, increasing vessel tortuosity, and increased capillary blockage by leukocytes, was previously observed in the aged rTg4510 mouse model. Similar gene expression changes related to angiogenesis were observed in both rTg4510 and Alzheimer's disease (AD). It is uncertain if tau is directly responsible for these vascular changes by interacting directly with microvessels, and/or if it contributes indirectly via neurodegeneration and concurrent neuronal loss and inflammation. To better understand the nature of tau-related microangiopathy in human AD and in tau mice, we isolated capillaries and observed that bioactive soluble tau protein could be readily detected in association with vasculature. To examine whether this soluble tau is directly responsible for the microangiopathic changes, we made use of the tetracycline-repressible gene expression cassette in the rTg4510 mouse model and measured vascular pathology following tau reduction. These data suggest that reduction of tau is insufficient to alter established microvascular complications including morphological alterations, enhanced expression of inflammatory genes involved in leukocyte adherence, and blood brain barrier compromise. These data imply that 1) soluble bioactive tau surprisingly accumulates at the blood brain barrier in human brain and in mouse models, and 2) the morphological and molecular phenotype of microvascular disturbance does not resolve with reduction of whole brain soluble tau. Additional consideration of vascular-directed therapies and strategies that target tau in the vascular space may be required to restore normal function in neurodegenerative disease.

DSC Brain Perfusion Using Advanced Deconvolution Models in the Diagnostic Work-up of Dementia and Mild Cognitive Impairment: A Semiquantitative Comparison with HMPAO-SPECT-Brain Perfusion

BACKGROUND

SPECT (single-photon emission-computed tomography) is used for the detection of hypoperfusion in cognitive impairment and dementia but is not widely available and related to radiation dose exposure. We compared the performance of DSC (dynamic susceptibility contrast) perfusion using semi- and fully adaptive deconvolution models to HMPAO-SPECT (99mTc-hexamethylpropyleneamine oxime-SPECT).

MATERIAL AND METHODS

Twenty-seven patients with dementia of different subtypes including frontotemporal dementia (FTD) and mild cognitive impairment (MCI) received a multimodal diagnostic work-up including DSC perfusion at a clinical 3T high-field scanner and HMPAO-SPECT. Nineteen healthy control individuals received DSC perfusion. For calculation of the hemodynamic parameter maps, oscillation-index standard truncated singular value decomposition (oSVD, semi-adaptive) as well as Bayesian parameter estimation (BAY, fully adaptive) were performed.

RESULTS

Patients showed decreased cortical perfusion in the left frontal lobe compared to controls (relative cerebral blood volume corrected, rBVc: 0.37 vs 0.27, p = 0.048, adjusted for age and sex). Performance of rBVc (corrected for T1 effects) was highest compared to SPECT for detection of frontal hypoperfusion (sensitivity 83%, specificity 80% for oSVD and BAY, area under curve (AUC) = 0.833 respectively, p < 0.05) in FTD and MCI. For nonleakage-corrected rBV and for rBF (relative cerebral blood flow), sensitivity of frontal hypoperfusion was above 80% for oSVD and for BAY (rBV: sensitivity 83%, specificity 75%, AUC = 0.908 for oSVD and 0.917 for BAY, p < 0.05 respectively; rBF: sensitivity 83%, specificity 65%, AUC = 0.825, p < 0.05 for oSVD).

CONCLUSION

Advanced deconvolution DSC can reliably detect pathological perfusion alterations in FTD and MCI. Hence, this widely accessible technique has the potential to improve the diagnosis of dementia and MCI as part of an interdisciplinary multimodal imaging work-up. Advances in knowledge: Advanced DSC perfusion has a high potential in the work-up of suspected dementia and correlates with SPECT brain perfusion results in dementia and MCI.

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.

Conflict monitoring on an emotional Stroop task. Comparison of healthy older adults and patients with major neurocognitive disorders due to probable AD

INTRODUCTION

The conflict monitoring system exerts an influence on centers responsible for cognitive control, causing them to intervene more strongly in processing when conflict occurs. These mechanisms are usually investigated through specific tasks where there is an inherent interference elicited by the congruency or incongruency between the stimuli and responses, such as the Stroop task. In studies of emotional conflict, one hypothesis related to the dorsal anterior cingulate cortex (ACC) is that it serves, in part, to signal the appearance of conflicts, thus triggering compensatory adjustments. This study aims to verify whether the conflict monitoring hypothesis is confirmed in a group with Alzheimer's disease and, therefore, whether they exhibit a reduction in their reaction times.

METHOD

A group of healthy older adults (HOA) and a group with Major Neurocognitive Disorders due to probable AD were evaluated to test the conflict monitoring hypothesis with an emotional Stroop task.

RESULTS

A significant interaction was obtained on the word and faces blocks. In the HOA group, a reduction in reaction times was observed, whereas in the AD groups, no reduction in reaction times was obtained.

CONCLUSIONS

Whereas in HOA the conflict monitoring hypothesis is confirmed, in the Major Neurocognitive Disorders due to probable AD group there is no reduction in their reaction times on the high conflict resolution trials (incongruent trials that follow incongruent trials) due to their difficulty in making compensatory adjustments to cognitive control that help them to reduce conflict and improve their success rate.

Cerebral perfusion changes in presymptomatic genetic frontotemporal dementia: a GENFI study

Genetic forms of frontotemporal dementia are most commonly due to mutations in three genes, C9orf72, GRN or MAPT, with presymptomatic carriers from families representing those at risk. While cerebral blood flow shows differences between frontotemporal dementia and other forms of dementia, there is limited evidence of its utility in presymptomatic stages of frontotemporal dementia. This study aimed to delineate the cerebral blood flow signature of presymptomatic, genetic frontotemporal dementia using a voxel-based approach. In the multicentre GENetic Frontotemporal dementia Initiative (GENFI) study, we investigated cross-sectional differences in arterial spin labelling MRI-based cerebral blood flow between presymptomatic C9orf72, GRN or MAPT mutation carriers (n = 107) and non-carriers (n = 113), using general linear mixed-effects models and voxel-based analyses. Cerebral blood flow within regions of interest derived from this model was then explored to identify differences between individual gene carrier groups and to estimate a timeframe for the expression of these differences. The voxel-based analysis revealed a significant inverse association between cerebral blood flow and the expected age of symptom onset in carriers, but not non-carriers. Regions included the bilateral insulae/orbitofrontal cortices, anterior cingulate/paracingulate gyri, and inferior parietal cortices, as well as the left middle temporal gyrus. For all bilateral regions, associations were greater on the right side. After correction for partial volume effects in a region of interest analysis, the results were found to be largely driven by the C9orf72 genetic subgroup. These cerebral blood flow differences first appeared approximately 12.5 years before the expected symptom onset determined on an individual basis. Cerebral blood flow was lower in presymptomatic mutation carriers closer to and beyond their expected age of symptom onset in key frontotemporal dementia signature regions. These results suggest that arterial spin labelling MRI may be a promising non-invasive imaging biomarker for the presymptomatic stages of genetic frontotemporal dementia.

Single-slice Alzheimer's disease classification and disease regional analysis with Supervised Switching Autoencoders

BACKGROUND

Alzheimer's disease (AD) is a difficult to diagnose pathology of the brain that progressively impairs cognitive functions. Computer-assisted diagnosis of AD based on image analysis is an emerging tool to support AD diagnosis. In this article, we explore the application of Supervised Switching Autoencoders (SSAs) to perform AD classification using only one structural Magnetic Resonance Imaging (sMRI) slice. SSAs are revised supervised autoencoder architectures, combining unsupervised representation and supervised classification as one unified model. In this work, we study the capabilities of SSAs to capture complex visual neurodegeneration patterns, and fuse disease semantics simultaneously. We also examine how regions associated to disease state can be discovered by SSAs following a local patch-based approach.

METHODS

Patch-based SSAs models are trained on individual patches extracted from a single 2D slice, independently for Axial, Coronal, and Sagittal anatomical planes of the brain at selected informative locations, exploring different patch sizes and network parameterizations. Then, models perform binary class prediction - healthy (CDR = 0) or AD-demented (CDR > 0) - on test data at patch level. The final subject classification is performed employing a majority rule from the ensemble of patch predictions. In addition, relevant regions are identified, by computing accuracy densities from patch-level predictions, and analyzed, supported by Atlas-based regional definitions.

RESULTS

Our experiments employing a single 2D T1-w sMRI slice per subject show that SSAs perform similarly to previous proposals that rely on full volumetric information and feature-engineered representations. SSAs classification accuracy on slices extracted along the Axial, Coronal, and Sagittal anatomical planes from a balanced cohort of 40 independent test subjects was 87.5%, 90.0%, and 90.0%, respectively. A top sensitivity of 95.0% on both Coronal and Sagittal planes was also obtained.

CONCLUSIONS

SSAs provided well-ranked accuracy performance among previous classification proposals, including feature-engineered and feature learning based methods, using only one scan slice per subject, instead of the whole 3D volume, as it is conventionally done. In addition, regions identified as relevant by SSAs' were, in most part, coherent or partially coherent in regard to relevant regions reported on previous works. These regions were also associated with findings from medical knowledge, which gives value to our methodology as a potential analytical aid for disease understanding.

The Use of Biomarkers and Genetic Screening to Diagnose Frontotemporal Dementia: Evidence and Clinical Implications

Within the wide range of neurodegenerative brain diseases, the differential diagnosis of frontotemporal dementia (FTD) frequently poses a challenge. Often, signs and symptoms are not characteristic of the disease and may instead reflect atypical presentations. Consequently, the use of disease biomarkers is of importance to correctly identify the patients. Here, we describe how neuropsychological characteristics, neuroimaging and neurochemical biomarkers and screening for causal gene mutations can be used to differentiate FTD from other neurodegenerative diseases as well as to distinguish between FTD subtypes. Summarizing current evidence, we propose a stepwise approach in the diagnostic evaluation. Clinical consensus criteria that take into account a full neuropsychological examination have relatively good accuracy (sensitivity [se] 75–95%, specificity [sp] 82–95%) to diagnose FTD, although misdiagnosis (mostly AD) is common. Structural brain MRI (se 70–94%, sp 89–99%) and FDG PET (se 47–90%, sp 68–98%) or SPECT (se 36–100%, sp 41–100%) brain scans greatly increase diagnostic accuracy, showing greater involvement of frontal and anterior temporal lobes, with sparing of hippocampi and medial temporal lobes. If these results are inconclusive, we suggest detecting amyloid and tau cerebrospinal fluid (CSF) biomarkers that can indicate the presence of AD with good accuracy (se 74–100%, sp 82–97%). The use of P-tau₁₈₁ and the Aβ_1–42/Aβ_1–40 ratio significantly increases the accuracy of correctly identifying FTD vs. AD. Alternatively, an amyloid brain PET scan can be performed to differentiate FTD from AD. When autosomal dominant inheritance is suspected, or in early onset dementia, mutation screening of causal genes is indicated and may also be offered to at-risk family members. We have summarized genotype–phenotype correlations for several genes that are known to cause familial frontotemporal lobar degeneration, which is the neuropathological substrate of FTD. The genes most commonly associated with this disease (C9orf72, MAPT, GRN, TBK1) are discussed, as well as some less frequent ones (CHMP2B, VCP). Several other techniques, such as diffusion tensor imaging, tau PET imaging and measuring serum neurofilament levels, show promise for future implementation as diagnostic biomarkers.

A Systematic Review and Implementation of IoT-Based Pervasive Sensor-Enabled Tracking System for Dementia Patients

In today's world, 46.8 million people suffer from brain related diseases. Dementia is most prevalent of all. In general scenario, a dementia patient lacks proper guidance in searching out the way to return back at his/her home. Thus, increasing the risk of getting damaged at individual-health level. Therefore, it is important to track their movement in more sophisticated manner as possible. With emergence of wearables, GPS sensors and Internet of Things (IoT), such devices have become available in public domain. Smartphone apps support caregiver to locate the dementia patients in real-time. RF, GSM, 3G, Wi-Fi and 4G technology fill the communication gap between patient and caregiver to bring them closer. In this paper, we incorporated 7 most popular wearables for investigation to seek appropriateness for dementia tracking in recent times in systematic manners. We performed an in-depth review of these wearables as per the cost, technology wise and application wise characteristics. A case novel study i.e. IoT-based Force Sensor Resistance enabled System-FSRIoT, has been proposed and implemented to validate the effectiveness of IoT in the domain of smarter dementia patient tracking in wearable form factor. The results show promising aspect of a whole new notion to leverage efficient assistive physio-medical healthcare to the dementia patients and the affected family members to reduce life risks and achieve a better social life.

Three-dimensional pseudocontinuous arterial spin labeling and susceptibility-weighted imaging associated with clinical progression in amnestic mild cognitive impairment and Alzheimer's disease

BACKGROUND

This study aimed to evaluate the value of 3-dimensional pseudocontinuous arterial spin labeling (3D-pcASL) and susceptibility-weighted imaging (SWI) for the early disease-sensitive markers of conversion from amnestic MCI (aMCI) to Alzheimer disease (AD) in this process.

METHODS

Forty patients with aMCI and AD respectively were recruited in the study, and 40 healthy subjects were taken as controls. Data were recorded using 3T MR scanner. We assessed the cerebral blood flow (CBF) in 11 different regions of interest, and counted number of microhemorrhages (MB) in 3 regions of brain lobes, bilateral basal ganglia/thalamus, and brain stem/cerebellum, and then investigated correlations between Montreal Cognitive Assessment (MoCA) scores, CBF, and susceptibility-weighted imaging (SWI) features in these 3 groups.

RESULTS

The results revealed that for AD patients, the MoCA scores and CBF values in frontal gray matter (FGM), occipital gray matter (OGM), temporal gray matter (TGM), parietal gray matter (PGM), hippocampus, anterior cingulate cortex (ACC), precuneus, posterior cingulate cortex (PCC), precuneus, basal ganglia and thalamus decreased compared with aMCI patients and control group, and significant difference was revealed among the 3 groups. While in cerebellum, statistical significance was only found between AD patients and control group. On SWI, the average numbers of hemorrhage in regions of lobes for AD patients were significantly higher than aMCI patients and control group. The same results occurred in the bilateral basal ganglia/thalamus. We further found the MoCA score was positively correlated with CBF, but negatively correlated with hypointense signal on SWI.

CONCLUSION

3D-pCASL and SWI have promising potential to be biomarkers for conversion from aMCI to AD in this process.

Detecting frontotemporal dementia syndromes using MRI biomarkers

Background

Diagnosing frontotemporal dementia may be challenging. New methods for analysis of regional brain atrophy patterns on magnetic resonance imaging (MRI) could add to the diagnostic assessment. Therefore, we aimed to develop automated imaging biomarkers for differentiating frontotemporal dementia subtypes from other diagnostic groups, and from one another.

Methods

In this retrospective multicenter cohort study, we included 1213 patients (age 67 ± 9, 48% females) from two memory clinic cohorts: 116 frontotemporal dementia, 341 Alzheimer's disease, 66 Dementia with Lewy bodies, 40 vascular dementia, 104 other dementias, 229 mild cognitive impairment, and 317 subjective cognitive decline. Three MRI atrophy biomarkers were derived from the normalized volumes of automatically segmented cortical regions: 1) the anterior vs. posterior index, 2) the asymmetry index, and 3) the temporal pole left index. We used the following performance metrics: area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. To account for the low prevalence of frontotemporal dementia we pursued a high specificity of 95%. Cross-validation was used in assessing the performance. The generalizability was assessed in an independent cohort (n = 200).

Results

The anterior vs. posterior index performed with an AUC of 83% for differentiation of frontotemporal dementia from all other diagnostic groups (Sensitivity = 59%, Specificity = 95%, positive likelihood ratio = 11.8, negative likelihood ratio = 0.4). The asymmetry index showed highest performance for separation of primary progressive aphasia and behavioral variant frontotemporal dementia (AUC = 85%, Sensitivity = 79%, Specificity = 92%, positive likelihood ratio = 9.9, negative likelihood ratio = 0.2), whereas the temporal pole left index was specific for detection of semantic variant primary progressive aphasia (AUC = 85%, Sensitivity = 82%, Specificity = 80%, positive likelihood ratio = 4.1, negative likelihood ratio = 0.2). The validation cohort provided corresponding results for the anterior vs. posterior index and temporal pole left index.

Conclusion

This study presents three quantitative MRI biomarkers, which could provide additional information to the diagnostic assessment and assist clinicians in diagnosing frontotemporal dementia.

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Quantitative MRI biomarkers (API, ASI, and TPL) for detection of FTD and its subtypes.

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API differentiated FTD from other diagnostic groups with AUC of 83%.

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ASI and TPL showed highest performance for PPA subtypes.

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A subcortical bvFTD subtype resembling AD atrophy pattern seems undetectable for MRI.

Neuroimaging and Machine Learning for Dementia Diagnosis: Recent Advancements and Future Prospects

Dementia, a chronic and progressive cognitive declination of brain function caused by disease or impairment, is becoming more prevalent due to the aging population. A major challenge in dementia is achieving accurate and timely diagnosis. In recent years, neuroimaging with computer-aided algorithms have made remarkable advances in addressing this challenge. The success of these approaches is mostly attributed to the application of machine learning techniques for neuroimaging. In this review paper, we present a comprehensive survey of automated diagnostic approaches for dementia using medical image analysis and machine learning algorithms published in the recent years. Based on the rigorous review of the existing works, we have found that, while most of the studies focused on Alzheimer's disease, recent research has demonstrated reasonable performance in the identification of other types of dementia remains a major challenge. Multimodal imaging analysis deep learning approaches have shown promising results in the diagnosis of these other types of dementia. The main contributions of this review paper are as follows. 1) Based on the detailed analysis of the existing literature, this paper discusses neuroimaging procedures for dementia diagnosis. 2) It systematically explains the most recent machine learning techniques and, in particular, deep learning approaches for early detection of dementia.

Effects of systematic partial volume errors on the estimation of gray matter cerebral blood flow with arterial spin labeling MRI

OBJECTIVE

Partial volume (PV) correction is an important step in arterial spin labeling (ASL) MRI that is used to separate perfusion from structural effects when computing the mean gray matter (GM) perfusion. There are three main methods for performing this correction: (1) GM-threshold, which includes only voxels with GM volume above a preset threshold; (2) GM-weighted, which uses voxel-wise GM contribution combined with thresholding; and (3) PVC, which applies a spatial linear regression algorithm to estimate the flow contribution of each tissue at a given voxel. In all cases, GM volume is obtained using PV maps extracted from the segmentation of the T1-weighted (T1w) image. As such, PV maps contain errors due to the difference in readout type and spatial resolution between ASL and T1w images. Here, we estimated these errors and evaluated their effect on the performance of each PV correction method in computing GM cerebral blood flow (CBF).

MATERIALS AND METHODS

Twenty-two volunteers underwent scanning using 2D echo planar imaging (EPI) and 3D spiral ASL. For each PV correction method, GM CBF was computed using PV maps simulated to contain estimated errors due to spatial resolution mismatch and geometric distortions which are caused by the mismatch in readout between ASL and T1w images. Results were analyzed to assess the effect of each error on the estimation of GM CBF from ASL data.

RESULTS

Geometric distortion had the largest effect on the 2D EPI data, whereas the 3D spiral was most affected by the resolution mismatch. The PVC method outperformed the GM-threshold even in the presence of combined errors from resolution mismatch and geometric distortions. The quantitative advantage of PVC was 16% without and 10% with the combined errors for both 2D and 3D ASL. Consistent with theoretical expectations, for error-free PV maps, the PVC method extracted the true GM CBF. In contrast, GM-weighted overestimated GM CBF by 5%, while GM-threshold underestimated it by 16%. The presence of PV map errors decreased the calculated GM CBF for all methods.

CONCLUSION

The quality of PV maps presents no argument for the preferential use of the GM-threshold method over PVC in the clinical application of ASL.

Functional MRI of brain physiology in aging and neurodegenerative diseases

Brain aging and associated neurodegeneration constitute a major societal challenge as well as one for the neuroimaging community. A full understanding of the physiological mechanisms underlying neurodegeneration still eludes medical researchers, fuelling the development of in vivo neuroimaging markers. Hence it is increasingly recognized that our understanding of neurodegenerative processes likely will depend upon the available information provided by imaging techniques. At the same time, the imaging techniques are often developed in response to the desire to observe certain physiological processes. In this context, functional MRI (fMRI), which has for decades provided information on neuronal activity, has evolved into a large family of techniques well suited for in vivo observations of brain physiology. Given the rapid technical advances in fMRI in recent years, this review aims to summarize the physiological basis of fMRI observations in healthy aging as well as in age-related neurodegeneration. This review focuses on in-vivo human brain imaging studies in this review and on disease features that can be imaged using fMRI methods. In addition to providing detailed literature summaries, this review also discusses future directions in the study of brain physiology using fMRI in the clinical setting.

Are Major Dementias Triggered by Poor Blood Flow to the Brain? Theoretical Considerations

There is growing evidence that chronic brain hypoperfusion plays a central role in the development of Alzheimer's disease (AD) long before dyscognitive symptoms or amyloid-β accumulation in the brain appear. This commentary proposes that dementia with Lewy bodies (DLB), frontotemporal dementia (FTD), and Creutzfeldt-Jakob disease (CJD) may also develop from chronic brain hypoperfusion following a similar but not identical neurometabolic breakdown as AD. The argument to support this conclusion is that chronic brain hypoperfusion, which is found at the early stages of the three dementias reviewed here, will reduce oxygen delivery and lower oxidative phosphorylation promoting a steady decline in the synthesis of the cell energy fuel adenosine triphosphate (ATP). This process is known to lead to oxidative stress. Virtually all neurodegenerative diseases, including FTD, DLB, and CJD, are characterized by oxidative stress that promotes inclusion bodies which differ in structure, location, and origin, as well as which neurological disorder they typify. Inclusion bodies have one thing in common; they are known to diminish autophagic activity, the protective intracellular degradative process that removes malformed proteins, protein aggregates, and damaged subcellular organelles that can disrupt neuronal homeostasis. Neurons are dependent on autophagy for their normal function and survival. When autophagic activity is diminished or impaired in neurons, high levels of unfolded or misfolded proteins overwhelm and downregulate the neuroprotective activity of unfolded protein response which is unable to get rid of dysfunctional organelles such as damaged mitochondria and malformed proteins at the synapse. The endpoint of this neuropathologic process results in damaged synapses, impaired neurotransmission, cognitive decline, and dementia.

Monitoring cerebral blood flow change through use of arterial spin labelling in acute ischaemic stroke patients after intra-arterial thrombectomy

OBJECTIVES

To evaluate the ability of arterial spin labelling perfusion-weighted imaging (ASL-PWI) to identify reperfusion status and to predict the early neurological outcome of acute ischaemic stroke patients after intra-arterial (IA) thrombectomy.

METHODS

A total of 51 acute ischaemic stroke patients who underwent IA thrombectomy were retrospectively reviewed. Asymmetrical index before and after IA thrombectomy (AICBF_pre and AICBF_post) and volume ratio of the reperfused territory to the baseline perfusion abnormality (reperfusion volume ratio) were calculated on ASL-PWI. A paired t-test was used to compare AICBF_pre and AICBF_post. Pearson correlation and multiple linear regression were performed to evaluate correlations between the imaging parameters and NIHSS scores.

RESULTS

Mean AICBF_post was significantly higher than mean AICBF_pre (0.923±0.352 vs. 0.312±0.191, p<0.001). AICBF_pre had a significant correlation with NIHSS_pre (pr=-0.430, p=.004). ∆AICBF had significant correlations with NIHSS_{24 h}, NIHSS_{5-7 days} and ∆NIHSS_{5-7 days} (r=-0.356, p=0.028; r=-0.597, p<0.001; r=-0.346, p=0.033, respectively). ∆AICBF, reperfusion volume ratio and baseline infarct volume were significant independent predictors for NIHSS_{5-7 days}.

CONCLUSIONS

ASL-PWI has the potential to serve as a non-invasive imaging tool to monitor the reperfusion status and predict the early neurological outcome of acute ischaemic stroke patients after IA thrombectomy.

KEY POINTS

• CBF change on ASL-PWI after IA thrombectomy correlated with NIHSS scores. • ASL-PWI can non-invasively monitor reperfusion in AIS patients after IA thrombectomy. • ASL-PWI may predict early outcome of AIS patients after IA thrombectomy.

Photon vs. proton radiochemotherapy: Effects on brain tissue volume and perfusion

BACKGROUND AND PURPOSE

To compare the structural and hemodynamic changes of healthy brain tissue in the cerebral hemisphere contralateral to the tumor following photon and proton radiochemotherapy.

MATERIALS AND METHODS

Sixty-seven patients (54.9 ±14.0 years) diagnosed with glioblastoma undergoing adjuvant photon (n = 47) or proton (n = 19) radiochemotherapy with temozolomide after tumor resection underwent T1-weighted and arterial spin labeling MRI. Changes in volume and perfusion before and 3 to 6 months after were compared between therapies.

RESULTS

A decrease in gray matter (GM) (-2.2%, P<0.001) and white matter (WM) (-1.2%, P<0.001) volume was observed in photon-therapy patients compared to the pre-radiotherapy baseline. In contrast, for the proton-therapy group, no significant differences in GM (0.3%, P = 0.64) or WM (-0.4%, P = 0.58) volume were observed. GM volume decreased with 0.9% per 10 Gy dose increase (P<0.001) and differed between the radiation modalities (P<0.001). Perfusion decreased in photon-therapy patients (-10.1%, P = 0.002), whereas the decrease in proton-therapy patients, while comparable in magnitude, did not reach statistical significance (-9.1%, P = 0.12). There was no correlation between perfusion decrease and either dose (P = 0.64) or radiation modality (P = 0.94).

CONCLUSIONS

Our results show that the tissue volume decrease depends on radiation dose delivered to the healthy hemisphere and differs between treatment modalities. In contrast, the decrease in perfusion was comparable for both irradiation modalities. We conclude that proton therapy may reduce brain-volume loss when compared to photon therapy.

Comparison of arterial spin labeling registration strategies in the multi-center GENetic frontotemporal dementia initiative (GENFI)

PURPOSE

To compare registration strategies to align arterial spin labeling (ASL) with 3D T1-weighted (T1w) images, with the goal of reducing the between-subject variability of cerebral blood flow (CBF) images.

MATERIALS AND METHODS

Multi-center 3T ASL data were collected at eight sites with four different sequences in the multi-center GENetic Frontotemporal dementia Initiative (GENFI) study. In a total of 48 healthy controls, we compared the following image registration options: (I) which images to use for registration (perfusion-weighted images [PWI] to the segmented gray matter (GM) probability map (pGM) (CBF-pGM) or M0 to T1w (M0-T1w); (II) which transformation to use (rigid-body or non-rigid); and (III) whether to mask or not (no masking, M0-based FMRIB software library Brain Extraction Tool [BET] masking). In addition to visual comparison, we quantified image similarity using the Pearson correlation coefficient (CC), and used the Mann-Whitney U rank sum test.

RESULTS

CBF-pGM outperformed M0-T1w (CC improvement 47.2% ± 22.0%; P < 0.001), and the non-rigid transformation outperformed rigid-body (20.6% ± 5.3%; P < 0.001). Masking only improved the M0-T1w rigid-body registration (14.5% ± 15.5%; P = 0.007).

CONCLUSION

The choice of image registration strategy impacts ASL group analyses. The non-rigid transformation is promising but requires validation. CBF-pGM rigid-body registration without masking can be used as a default strategy. In patients with expansive perfusion deficits, M0-T1w may outperform CBF-pGM in sequences with high effective spatial resolution. BET-masking only improves M0-T1w registration when the M0 image has sufficient contrast.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:131-140.

Using simultaneous PET/MRI to compare the accuracy of diagnosing frontotemporal dementia by arterial spin labelling MRI and FDG-PET

Purpose

The clinical utility of FDG-PET in diagnosing frontotemporal dementia (FTD) has been well demonstrated over the past decades. On the contrary, the diagnostic value of arterial spin labelling (ASL) MRI - a relatively new technique - in clinical diagnosis of FTD has yet to be confirmed. Using simultaneous PET/MRI, we evaluated the diagnostic performance of ASL in identifying pathological abnormalities in FTD (FTD) to determine whether ASL can provide similar diagnostic value as FDG-PET.

Methods

ASL and FDG-PET images were compared in 10 patients with FTD and 10 healthy older adults. Qualitative and quantitative measures of diagnostic equivalency were used to determine the diagnostic utility of ASL compared to FDG-PET. Sensitivity, specificity, and inter-rater reliability were calculated for each modality from scores of subjective visual ratings and from analysis of regional mean values in thirteen a priori regions of interest (ROI). To determine the extent of concordance between modalities in each patient, individual statistical maps generated from comparison of each patient to controls were compared between modalities using the Jaccard similarity index (JI).

Results

Visual assessments revealed lower sensitivity, specificity and inter-rater reliability for ASL (66.67%/62.12%/0.2) compared to FDG-PET (88.43%/90.91%/0.61). Across all regions, ASL performed lower than FDG-PET in discriminating patients from controls (areas under the receiver operating curve: ASL = 0.75 and FDG-PET = 0.87). In all patients, ASL identified patterns of reduced perfusion consistent with FTD, but areas of hypometabolism exceeded hypoperfused areas (group-mean JI = 0.30 ± 0.22).

Conclusion

This pilot study demonstrated that ASL can detect similar spatial patterns of abnormalities in individual FTD patients compared to FDG-PET, but its sensitivity and specificity for discriminant diagnosis of a patient from healthy individuals remained unmatched to FDG-PET. Further studies at the individual level are required to confirm the clinical role of ASL in FTD management.

Aberrant pattern of regional cerebral blood flow in Alzheimer's disease: a voxel-wise meta-analysis of arterial spin labeling MR imaging studies

Many studies have applied arterial spin labeling (ASL) to characterize cerebral perfusion patterns of Alzheimer's disease (AD). However, findings across studies are not conclusive. A quantitatively voxel-wise meta-analysis to pool the resting-state ASL studies that measure regional cerebral blood flow (rCBF) alterations in AD was conducted to identify the most consistent and replicable perfusion pattern using seed-based d mapping. The meta-analysis, including 17 ASL studies encompassing 327 AD patients and 357 healthy controls, demonstrated that decreased rCBF in AD patients relative to healthy controls were consistently identified in the bilateral posterior cingulate cortices (PCC)/precuneus, bilateral inferior parietal lobules (IPLs), and left dorsolateral prefrontal cortex. The meta-regression analysis showed that more severe cognitive impairment in the AD samples correlated with greater decreases of rCBF in the bilateral PCC and left IPL. This study characterizes an aberrant ASL-rCBF perfusion pattern of AD involving the posterior default mode network and executive network, which are implicated in its pathophysiology and hold promise for developing imaging biomarkers.

Head-to-Head Visual Comparison between Brain Perfusion SPECT and Arterial Spin-Labeling MRI with Different Postlabeling Delays in Alzheimer Disease

BACKGROUND AND PURPOSE

Arterial spin-labeling MR imaging has been recently developed as a noninvasive technique with magnetically labeled arterial blood water as an endogenous contrast medium for the evaluation of CBF. Our aim was to compare arterial spin-labeling MR imaging and SPECT in the visual assessment of CBF in patients with Alzheimer disease.

MATERIALS AND METHODS

In 33 patients with Alzheimer disease or mild cognitive impairment due to Alzheimer disease, CBF images were obtained by using both arterial spin-labeling-MR imaging with a postlabeling delay of 1.5 seconds and 2.5 seconds (PLD_1.5 and PLD_2.5, respectively) and brain perfusion SPECT. Twenty-two brain regions were visually assessed, and the diagnostic confidence of Alzheimer disease was recorded.

RESULTS

Among all arterial spin-labeling images, 84.9% of PLD_1.5 and 9% of PLD_2.5 images showed the typical pattern of advanced Alzheimer disease (ie, decreased CBF in the bilateral parietal, temporal, and frontal lobes). PLD_1.5, PLD_2.5, and SPECT imaging resulted in obviously different visual assessments. PLD_1.5 showed a broad decrease in CBF, which could have been due to an early perfusion. In contrast, PLD_2.5 did not appear to be influenced by an early perfusion but showed fewer pathologic findings than SPECT.

CONCLUSIONS

The distinctions observed by us should be carefully considered in the visual assessments of Alzheimer disease. Further studies are required to define the patterns of change in arterial spin-labeling-MR imaging associated with Alzheimer disease.

Imaging and fluid biomarkers in frontotemporal dementia

Frontotemporal dementia (FTD), the second most common type of presenile dementia, is a heterogeneous neurodegenerative disease characterized by progressive behavioural and/or language problems, and includes a range of clinical, genetic and pathological subtypes. The diagnostic process is hampered by this heterogeneity, and correct diagnosis is becoming increasingly important to enable future clinical trials of disease-modifying treatments. Reliable biomarkers will enable us to better discriminate between FTD and other forms of dementia and to predict disease progression in the clinical setting. Given that different underlying pathologies probably require specific pharmacological interventions, robust biomarkers are essential for the selection of patients with specific FTD subtypes. This Review emphasizes the increasing availability and potential applications of structural and functional imaging biomarkers, and cerebrospinal fluid and blood fluid biomarkers in sporadic and genetic FTD. The relevance of new MRI modalities - such as voxel-based morphometry, diffusion tensor imaging and arterial spin labelling - in the early stages of FTD is discussed, together with the ability of these modalities to classify FTD subtypes. We highlight promising new fluid biomarkers for staging and monitoring of FTD, and underline the importance of large, multicentre studies of individuals with presymptomatic FTD. Harmonization in the collection and analysis of data across different centres is crucial for the implementation of new biomarkers in clinical practice, and will become a great challenge in the next few years.

Advances in neuroimaging in frontotemporal dementia

Frontotemporal dementia (FTD) is a clinically and neuroanatomically heterogeneous neurodegenerative disorder with multiple underlying genetic and pathological causes. Whilst initial neuroimaging studies highlighted the presence of frontal and temporal lobe atrophy or hypometabolism as the unifying feature in patients with FTD, more detailed studies have revealed diverse patterns across individuals, with variable frontal or temporal predominance, differing degrees of asymmetry, and the involvement of other cortical areas including the insula and cingulate, as well as subcortical structures such as the basal ganglia and thalamus. Recent advances in novel imaging modalities including diffusion tensor imaging, resting-state functional magnetic resonance imaging and molecular positron emission tomography imaging allow the possibility of investigating alterations in structural and functional connectivity and the visualisation of pathological protein deposition. This review will cover the major imaging modalities currently used in research and clinical practice, focusing on the key insights they have provided into FTD, including the onset and evolution of pathological changes and also importantly their utility as biomarkers for disease detection and staging, differential diagnosis and measurement of disease progression. Validating neuroimaging biomarkers that are able to accomplish these tasks will be crucial for the ultimate goal of powering upcoming clinical trials by correctly stratifying patient enrolment and providing sensitive markers for evaluating the effects and efficacy of disease-modifying therapies. This review describes the key insights provided by research into the major neuroimaging modalities currently used in research and clinical practice, including what they tell us about the onset and evolution of FTD and how they may be used as biomarkers for disease detection and staging, differential diagnosis and measurement of disease progression. This article is part of the Frontotemporal Dementia special issue.

The value of whole-brain CT perfusion imaging and CT angiography using a 320-slice CT scanner in the diagnosis of MCI and AD patients

OBJECTIVES

To validate the value of whole-brain computed tomography perfusion (CTP) and CT angiography (CTA) in the diagnosis of mild cognitive impairment (MCI) and Alzheimer's disease (AD).

METHODS

Whole-brain CTP and four-dimensional CT angiography (4D-CTA) images were acquired in 30 MCI, 35 mild AD patients, 35 moderate AD patients, 30 severe AD patients and 50 normal controls (NC). Cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), time to peak (TTP), and correlation between CTP and 4D-CTA were analysed.

RESULTS

Elevated CBF in the left frontal and temporal cortex was found in MCI compared with the NC group. However, TTP was increased in the left hippocampus in mild AD patients compared with NC. In moderate and severe AD patients, hypoperfusion was found in multiple brain areas compared with NC. Finally, we found that the extent of arterial stenosis was negatively correlated with CBF in partial cerebral cortex and hippocampus, and positively correlated with TTP in these areas of AD and MCI patients.

CONCLUSIONS

Our findings suggest that whole-brain CTP and 4D-CTA could serve as a diagnostic modality in distinguishing MCI and AD, and predicting conversion from MCI based on TTP of left hippocampus.

KEY POINTS

• Whole-brain perfusion using the full 160-mm width of 320 detector rows • Provide clinical experience of 320-row CT in cerebrovascular disorders of Alzheimer's disease • Initial combined 4D CTA-CTP data analysed perfusion and correlated with CT angiography • Whole-brain CTP and 4D-CTA have high value for monitoring MCI to AD progression • TTP in the left hippocampus may predict the transition from MCI to AD.

Voxel-wise correlations between cognition and cerebral blood flow using arterial spin-labeled perfusion MRI in patients with Alzheimer's disease: a cross-sectional study

Background

To analyze voxel-wise correlation between cerebral blood flow (CBF) measured using ASL-MRI and cognition in patients with Alzheimer’s disease (AD).

Methods

Forty-one patients diagnosed with AD or mild cognitive impairment due to AD were recruited for this study. CBF images were obtained using ASL-MRI (n = 41) with a post-labeling delay (PLD) of 1.5 and 2.5 s (PLD_1.5 and PLD_2.5, respectively) using a 3 T scanner, in addition to brain perfusion SPECT with N-isopropyl-4-[I-123]iodoamphetamine (n = 28). Voxel-based analyses were performed for ASL-MRI and SPECT using Mini-Mental State Examination (MMSE) scores as covariates. Differences in CBF between PLD_1.5 and PLD_2.5 were assessed using a paired t-test with SPM12.

Results

Significant positive correlations were observed between MMSE scores and CBF at PLD_1.5 in the right posterior cingulate cortex (PCC), and both temporo-parietal association cortexes. At PLD_2.5, significant positive correlations were determined for MMSE scores and CBF in the superior parietal lobule and the right temporo-parietal association cortex. SPECT showed significant positive correlations in the PCC and both temporo-parietal association cortexes (right-side dominant). PLD_1.5 showed significantly higher CBF than PLD_2.5 in the proximal areas of vascular territories of the anterior, middle, and posterior cerebral arteries.

Conclusions

Significant positive correlations in CBF, measured with both ASL-MRI and SPECT, with cognition were found in the PCC and temporo-parietal association cortexes. PLD_1.5 and PLD_2.5 showed similar correlations with cognition, although the CBF images had significant differences.

Arterial spin labeling-based Z-maps have high specificity and positive predictive value for neurodegenerative dementia compared to FDG-PET

Objective

Cerebral perfusion analysis based on arterial spin labeling (ASL) MRI has been proposed as an alternative to FDG-PET in patients with neurodegenerative disease. Z-maps show normal distribution values relating an image to a database of controls. They are routinely used for FDG-PET to demonstrate disease-specific patterns of hypometabolism at the individual level. This study aimed to compare the performance of Z-maps based on ASL to FDG-PET.

Methods

Data were combined from two separate sites, each cohort consisting of patients with Alzheimer’s disease (n = 18 + 7), frontotemporal dementia (n = 12 + 8) and controls (n = 9 + 29). Subjects underwent pseudocontinuous ASL and FDG-PET. Z-maps were created for each subject and modality. Four experienced physicians visually assessed the 166 Z-maps in random order, blinded to modality and diagnosis.

Results

Discrimination of patients versus controls using ASL-based Z-maps yielded high specificity (84%) and positive predictive value (80%), but significantly lower sensitivity compared to FDG-PET-based Z-maps (53% vs. 96%, p < 0.001). Among true-positive cases, correct diagnoses were made in 76% (ASL) and 84% (FDG-PET) (p = 0.168).

Conclusion

ASL-based Z-maps can be used for visual assessment of neurodegenerative dementia with high specificity and positive predictive value, but with inferior sensitivity compared to FDG-PET.

Key points

• ASL-based Z-maps yielded high specificity and positive predictive value in neurodegenerative dementia.

• ASL-based Z-maps had significantly lower sensitivity compared to FDG-PET-based Z-maps.

• FDG-PET might be reserved for ASL-negative cases where clinical suspicion persists.

• Findings were similar at two study sites.