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

Anazodo, Udunna; Finger, Elizabeth; Kwan, Benjamin Y. M.; Pavlosky, William; Warrington, James; Günther, Matthias; Prato, Frank S.; Thiessen, Jonathan D.; Lawrence, Keith St.

doi:10.1016/j.nicl.2017.10.033

Cited by 46 publications

(48 citation statements)

References 59 publications

(99 reference statements)

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“…bvFTD behavioral variant frontotemporal dementia, SD semantic dementia, PNFA progressive non-fluent aphasia, 3R three repeat, 4R four repeat, CBD corticobasal degeneration, PSP progressive supranuclear palsy, AGD argyrophilic grain disease, TDP TAR DNA binding protein, FTDP frontotemporal degeneration and Parkinsonism, FUS fused in sarcoma, UPS ubiquitin-proteasome system, DLDH dementia lacking distinctive histology brain perfusion images, and was verified for diagnosing FTD [45]. However, the accuracy for discriminant diagnosis of FTD patients from healthy subjects using ASL was reported to be inferior to that with FDG-PET [46], and ALS may not be widely available for use in clinical examination.…”

Section: Bvftdmentioning

confidence: 99%

Diagnostic imaging of dementia with Lewy bodies, frontotemporal lobar degeneration, and normal pressure hydrocephalus

Ishii

2019

Jpn J Radiol

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Neuroimaging can provide important biomarkers and is very useful for supporting dementia diagnosis. This review summarizes the neuroimaging findings of dementia with Lewy bodies (DLB), frontotemporal lobar degeneration (FTLD), and normal pressure hydrocephalus (NPH). In DLB, medial temporal atrophy is milder than that of Alzheimer's disease. 2-fluoro-2-deoxy-d-glucose-positron emission tomography and brain perfusion single-photon emission computed tomography demonstrate hypometabolism and hypoperfusion in the occipital lobe, in addition to decreased metabolism and perfusion in the parietotemporal, posterior cingulate, precuneus, and frontal association cortices. The cingulate island sign, which shows relatively spared middle-to-posterior cingulate cortex metabolism compared with precuneus hypometabolism, is proposed to detect DLB in 2-fluoro-2-deoxy-d-glucose-positron emission tomography imaging. Reduced uptake in dopamine transporter imaging and reduced myocardial uptake in iodine-123 metaiodobenzylguanidine cardiac scintigraphy are indicative biomarkers for DLB diagnosis. Characteristic findings of FTLD include dominant frontotemporal atrophy, hypometabolism, and hypoperfusion. Most idiopathic NPH cases demonstrate disproportionally enlarged subarachnoid space hydrocephalus findings, including dilated ventricular systems, enlarged Sylvian fissures, tight sulci in the midline, and a high convexity.

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Section: Bvftdmentioning

confidence: 99%

Diagnostic imaging of dementia with Lewy bodies, frontotemporal lobar degeneration, and normal pressure hydrocephalus

Ishii

2019

Jpn J Radiol

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“…Compared to FDG PET, ASL has the advantage of not requiring any injection of radiotracers or exogenous contrast agents, making its acquisition more acceptable (20). ASL studies have found evidence of hypoperfusion patterns that mirror those seen with FDG PET in Alzheimer's disease and fronto-temporal dementia (19,21,22). Conversely, patterns of ASL-derived hypoperfusion have not yet been confirmed as a valuable biomarker for the risk of developing cognitive impairment in PD.…”

Section: Introductionmentioning

confidence: 99%

Parietal Perfusion Alterations in Parkinson's Disease Patients Without Dementia

et al. 2020

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Fronto-parietal regions are involved in cognitive processes that are commonly affected in Parkinson's disease (PD). The aims of this study were to investigate cerebral blood flow (CBF) and gray matter (GM) volume within the regions belonging to the fronto-parietal circuit in people with PD (pwPD) without dementia, and to assess their association with cognitive performance. Twenty-seven pwPD without dementia (mean [SD] age = 67.4 [8.1] years, 20 males, mean [SD] Montreal Cognitive Assessment, MoCA score = 24.2 [2.9], median [IQR] Hoehn and Yahr scale = 1.5 [1-2]) and twenty-six age-and sex-matched healthy controls (HC) were scanned with arterial spin labeling (ASL) and T1-weighted magnetic resonance imaging (MRI) sequences to investigate CBF and GM volume, respectively. The cognitive performance of the enrolled pwPD was assessed with MoCA, Trail Making Test (TMT, part A, B, B-A), phonemic fluency and semantic fluency tests. The scores were adjusted for age and education. After standard preprocessing, CBF differences between pwPD and HC were tested with a voxel-wise approach. Voxel-based morphometry was used to compare pwPD and HC in terms of GM volume. Both voxel-wise comparisons between pwPD and HC were restricted to regions of the fronto-parietal circuit. The following additional voxel-wise analyses were performed within regions showing either perfusion or GM volume alterations: (1) correlation with neuropsychological test scores; (2) subgroup comparison after median split on each neuropsychological test score. Family-wise error-corrected (FWE) p-values lower than 0.05 were considered significant. Significant hypoperfusion was identified in the left inferior parietal lobule (IPL, p peak = 0.037) and in the bilateral superior parietal lobule (SPL, left hemisphere: p peak = 0.037; right hemisphere: p peak = 0.049) of pwPD when compared to HC. No significant GM atrophy was observed. Local hypoperfusion did not correlate with any neuropsychological test scores. However, significantly lower CBF was observed in the left SPL and IPL of the pwPD subgroup who performed poorer on TMT part A in comparison with the pwPD subgroup that performed better. Perfusion alterations may occur in parietal regions of pwPD without dementia, and may be associated with lower visuomotor skills. Parietal CBF may be considered as a suitable early biomarker for longitudinal studies investigating cognitive decline in PD.

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“…The performance comparison between FDG-PET and arterial spin labeling (ASL) MRI diagnostic value in identifying the pathological abnormalities of frontotemporal dementia (FTD) is studied in [54]. Twenty subjects are considered to determine the qualitative and quantitative diagnostic utility of ASL and FDG-PET for analyzing the ROI and subjective visual ratings.…”

Section: B Pet Modalitiesmentioning

confidence: 99%

“…It is predicted that multi-modal molecular imaging can seizure the corresponding information of a patient in a single scan such as the recent development PET/MRI or SPECT/MRI or PET/CT or SPECT/CT which has the advantages including spatial and temporal resolution, functional anatomical basis, targeting disease biomarkers with high accuracy in brain research. Temporal and spatial registration of simultaneous PET/MRI is assessed in [105], where Arterial Spin Labeling (ASL) is shown to be an alternative of FDG-PET for clinical diagnosis of bvFTD. So based on the recent advancement of medical image modalities along with their analysis technologies in dementia diagnosis, the performance of automatic dementia diagnosis is noticeably improving.…”

Section: Major Challenges and Future Prospectsmentioning

confidence: 99%

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

Ahmed

Zhang

Feng

et al. 2019

IEEE Rev. Biomed. Eng.

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Dementia, a chronic and progressive cognitive declination of brain function due to disease or impairment, is becoming more prevalent due to the aging population. A major challenge in dementia is achieving the accurate and timely diagnosis. In recent years, neuroimaging with computer-aided algorithms have made remarkable advances in addressing this challenge. Much of the success of these approaches can be attributed to the application of machine learning and deep 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 previous five years (2013-2018). Based on the rigorous review of the existing works, we have found that while most of the studies focused on Alzheimer's disease have demonstrated reasonable performance, the identification of other types of dementia remains a major challenge. Hybrid imaging analysis through deep learning approaches may hold promises for early diagnosis of these other types of dementia, and warrant further investigation in the future. The main contributions of this review paper are as follows: 1. Based on the detailed analysis of the existing literature, this paper discusses the most recent neuroimaging procedures for dementia diagnosis, and 2. It systematically explains the machine learning techniques and, in particular, deep learning approaches for early detection of dementia.

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

Cited by 46 publications

References 59 publications

Diagnostic imaging of dementia with Lewy bodies, frontotemporal lobar degeneration, and normal pressure hydrocephalus

Diagnostic imaging of dementia with Lewy bodies, frontotemporal lobar degeneration, and normal pressure hydrocephalus

Parietal Perfusion Alterations in Parkinson's Disease Patients Without Dementia

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

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