The use of positron emission tomography/magnetic resonance imaging in dementia: A literature review.
Alzheimer's disease
PET/MRI
dementia
hybrid imaging
magnetic resonance imaging
mild cognitive impairment
neuroimaging
positron emission tomography
Journal
International journal of geriatric psychiatry
ISSN: 1099-1166
Titre abrégé: Int J Geriatr Psychiatry
Pays: England
ID NLM: 8710629
Informations de publication
Date de publication:
10 2021
10 2021
Historique:
revised:
22
04
2021
received:
15
02
2021
accepted:
17
05
2021
entrez:
7
9
2021
pubmed:
8
9
2021
medline:
5
10
2021
Statut:
ppublish
Résumé
Positron emission tomography-magnetic resonance imaging (PET/MRI) is an emerging hybrid imaging system in clinical nuclear medicine. Research demonstrates a comparative utility to current unimodal and hybrid methods, including PET-computed tomography (PET/CT), in several medical subspecialities such as neuroimaging. The aim of this review is to critically evaluate the literature from 2016 to 2021 using PET/MRI for the investigation of patients with mild cognitive impairment or dementia, and discuss the evidence base for widening its application into clinical practice. A comprehensive literature search using the PubMed database was conducted to retrieve studies using PET/MRI in relation to the topics of mild cognitive impairment, dementia, or Alzheimer's disease between January 2016 and January 2021. This search strategy enabled studies on all dementia types to be included in the analysis. Studies were required to have a minimum of 10 human subjects and incorporate simultaneous PET/MRI. A total of 116 papers were retrieved, with 39 papers included in the final selection. These were broadly categorised into reviews (12), technical/methodological papers (11) and new data studies (16). For the current review, discussion focused on findings from the new data studies. PET/MRI offers additional insight into the underlying anatomical, metabolic and functional changes associated with dementia when compared with unimodal methods and PET/CT, particularly relating to brain regions including the hippocampus and default mode network. Furthermore, the improved diagnostic utility of PET/MRI, as reported by radiologists, offers improved classification of dementia patients, with important implications for clinical management.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
1501-1513Subventions
Organisme : Medical Research Council
ID : MR/M024873/1
Pays : United Kingdom
Informations de copyright
© 2021 The Authors. International Journal of Geriatric Psychiatry published by John Wiley & Sons Ltd.
Références
Muzic RF, DiFilippo FP. Positron emission tomography-magnetic resonance imaging: technical review. Semin Roentgenol. 2014;49(3):242-254.
Garlick PB, Marsden PK, Cave AC, et al. PET and NMR dual acquisition (PANDA): applications to isolated, perfused rat hearts. NMR Biomed. 1997;10:138-142.
Marsden PK, Shao Y, Cherry SR, et al. Simultaneous acquisition of PET images and NMR spectra in a high field magnet. J Nucl Med. 1997;38:161.
Shao Y, Cherry SR, Farahani K, et al. Simultaneous PET and MR imaging. Phys Med Biol. 1997;42:1965-1970.
Boss A, Stegger L, Bisdas S, et al. Feasibility of simultaneous PET/MR imaging in the head and upper neck area. Eur Radiol. 2011;21:1439-1446.
Schlemmer HP, Pichler BJ, Schmand M, et al. Simultaneous MR/PET imaging of the human brain: feasibility study. Radiology. 2008;248:1028-1035.
Hoult DI, Phil D. Sensitivity and power deposition in a high-field imaging experiment. J Magn Reson Imaging. 2000;12:46-67.
Musafargani S, Ghosh KK, Mishra S, Mahalakshmi P, Padmanabhan P, Gulyás B. PET/MRI: a frontier in era of complementary hybrid imaging. Eur J Hybrid Imaging. 2018;2(1):12.
Haigh C, Dunkerley J, Rogers M. Competitive advantage of PET/MRI. Eur J Radiol. 2014;83(1):66-89.
Hubert J, Descotes JL, Olivier P. Positron emission tomography. Prog Urol, 2003;13(5):807-812.
Liang ZP, Haacke EM. Magnetic resonance imaging. Biomedical Imaging V-Proceedings of the 5th IEEE EMBS International Summer School on Biomedical Imaging, SSBI. 2002. p. 324.
Rischpler C, Nekolla SG, Dregely I, et al. Hybrid PET/MR imaging of the heart: potential, initial experiences, and future prospects. J Nucl Med. 2013;54:402-415.
Chen K, Blebera J, Laredo JD, et al. Evaluation of musculoskeletal disorders with PET, PET/CT, and PET/MRI. PET Clin. 2008;3:451-465.
Schmidt H, Brendle C, Schrami C, et al. Correlation of simultaneously acquired diffusion-weighted imaging and 2-deoxy-[18F]fluoro-2-D-glucose positron emission tomography of pulmonary lesions in a dedicated whole-body magnetic resonance/positron emission tomography system. Invest Radiol. 2013;48:247-255.
Shamim SA, Torigian DA, Kumar R. PET, PET/CT, and PET/MRI assessment of breast cancer. PET Clin. 2008; 3:381-393.
Wetter A, Lipponer C, Nensa F, et al. Simultaneous 18F choline positron emission tomography/magnetic resonance imaging of the prostate: initial results. Invest Radiol. 2013;48:256-262.
Punwani S, Taylor SA, Saad ZZ, et al. Diffusion-weighted MRI of lymphoma: prognostic utility and implications for PET/MRI? Eur J Nucl Med Mol Imaging. 2013;40:373-385.
Pavese N, Simpson BS, Metta V, et al. [18F]FDOPA uptake in the raphe nuclei complex reflects serotonin transporter availability. A combined [18F]FDOPA and [11C]DASB PET study in Parkinson's disease. Neuroimage. 2012;59:1080-1084.
Pavese N, Metta V, Bose SK, et al. Fatigue in Parkinson's disease is linked to striatal and limbic serotonergic dysfunction. Brain, 2010;133:3434-3443.
Kim E, Howes OD, Kapur S. Molecular imaging as a guide for the treatment of central nervous system disorders. Dialogues Clin Neurosci. 2013;15:315-328.
Rocchi L, Niccolini F, Politis M, et al. Recent imaging advances in neurology. J Neurol. 2015;262:2182-2194.
Heiss WD. Ischemic penumbra: evidence from functional imaging in man. J Cereb Blood Flow Metab. 2000;20:1276-1293.
Sorensen AG. Magnetic resonance as a cancer imaging biomarker. J Clin Oncol. 2006;24:3274-3281.
Banaszek A, Bladowska J, Pokryszko-Dragan A, et al. Evaluation of the degradation of the selected projectile, commissural and association white matter tracts within normal appearing white matter in patients with multiple sclerosis using diffusion tensor MR imaging-a preliminary study. Pol J Radiol, 2015;80:457-463.
Gracien RM, Reitz SC, Hof SM, et al. Changes and variability of proton density and T1 relaxation times in early multiple sclerosis: MRI markers of neuronal damage in the cerebral cortex. Eur Radiol, 2015;26(8):2578-2586.
Rudko DA, Solovey I, Gati JS, et al. Multiple sclerosis: improved identification of disease-relevant changes in gray and white matter by using susceptibility-based MR imaging. Radiology. 2014;272:851-864.
Hojjati M, Badve C, Garg V, et al. Role of FDG-PET/MRI, FDG-PET/CT, and dynamic susceptibility contrast perfusion MRI in differentiating radiation necrosis from tumor recurrence in glioblastomas. J Neuroimaging. 2018;28(1):118-125.
Afshar-Oromieh A, Wolf MB, Kratochwil C, et al. Comparison of 68Ga-DOTATOC-PET/CT and PET/MRI hybrid systems in patients with cranial meningioma: initial results. Neuro Oncol. 2015;17(2):312-319.
Thorwarth D, Henke G, Müller AC, et al. Simultaneous 68Ga-DOTATOC-PET/MRI for IMRT treatment planning for meningioma: first experience. Int J Radiat Oncol Biol Phys. 2011;81(1):277-283.
Paldino MJ, Yang E, Jones JY, et al. Comparison of the diagnostic accuracy of PET/MRI to PET/CT-acquired FDG brain exams for seizure focus detection: a prospective study. Pediatr Radiol. 2017;47:1500-1507.
Buckner RL, Andrews-Hanna JR, Schacter DL. The brain's default network: anatomy, function, and relevance to disease. Ann N Y Acad Sci. 2008;1124:1-38
Greicius MD, Srivastava G, Reiss AL, Menon V. Default-mode network activity distinguishes Alzheimer's disease from healthy aging: evidence from functional MRI. Proc Natl Acad Sci U S A. 2004;101:4637-4642.
Shivamurthy VKN, Tahari AK, Marcus C, Subramaniam RM. Brain FDG PET and the diagnosis of dementia. Am J Roentgenol. 2015;204:W76-W85.
Suppiah S, Didier MA, Vinjamuri, S. The who, when, why, and how of PET amyloid imaging in management of Alzheimer's disease-review of literature and interesting images. Diagnostics, 2019;9(2):65.
Catana C, Drzezga A, Heiss W, Rosen B. PET/MRI for neurological applications. J Nucl Med. 2012; 53(12):1916-1925.
Dementias Platform UK. https://www.dementiasplatform.uk/for-researchers/dementia-research-resources/dementia-research-resources). Accessed January 19, 2021.
Franceschi AM, Clifton MA, Naser-Tavakolian K, et al. FDG PET/MRI for visual detection of crossed cerebellar diaschisis in patients with dementia. AJR Am J Roentgenol 2021;216(1):165-171.
Tiepolt, S, Rullmann, M, Jochimsen, TH, et al. Quantitative susceptibility mapping in β-amyloid PET-stratified patients with dementia and healthy controls-a hybrid PET/MRI study. Eur J Radiol. 2020;131:109243.
Kang KM, Sohn CH, Byun MS, et al. Prediction of amyloid positivity in mild cognitive impairment using fully automated brain segmentation software. Neuropsychiatr Dis Treat. 2020;16:1745-1754.
Carlson ML, DiGiacomo PS, Fan AP, et al. Simultaneous FDG-PET/MRI detects hippocampal subfield metabolic differences in AD/MCI. Sci Rep. 2020;10(1):12064.
Okazawa H, Ikawa M, Jung M, et al. Multimodal analysis using [11C]PiB-PET/MRI for functional evaluation of patients with Alzheimer's disease. EJNMMI Res. 2020;10(1):30.
Dong JW, Jelescu IO, Ades-Aron B, et al. Diffusion MRI biomarkers of white matter microstructure vary nonmonotonically with increasing cerebral amyloid deposition. Neurobiol Aging. 2020;89:118-128.
Mukku SSR, Sivakumar PT, Nagaraj C, Mangalore S, Harbishettar V, Varghese M. Clinical utility of 18F-FDG-PET/MRI brain in dementia: preliminary experience from a geriatric clinic in South India. Asian J Psychiatr. 2019;44:99-105.
Kaltoft NS, Marner L, Larsen VA, Hasselbalch SG, Law I, Henriksen OM. Hybrid FDG PET/MRI vs. FDG PET and CT in patients with suspected dementia-a comparison of diagnostic yield and propagated influence on clinical diagnosis and patient management. PLoS ONE, 2019;14(5):e0216409.
Riederer I, Bohn KP, Preibisch C, et al. Alzheimer disease and mild cognitive impairment: integrated pulsed arterial spin-labeling MRI and 18F-FDG PET. Radiology. 2018;288(1):198-206.
Marchitelli R, Aiello M, Cachia A, et al. Simultaneous resting-state FDG-PET/fMRI in Alzheimer disease: relationship between glucose metabolism and intrinsic activity. Neuroimage. 2018;176:246-258.
Göttler J, Preibisch C, Riederer I, et al. Reduced blood oxygenation level dependent connectivity is related to hypoperfusion in Alzheimer's disease. J Cereb Blood Flow Metab. 2019;39(7):1314-1325.
Schütz L, Lobsien D, Fritzsch D, et al. Feasibility and acceptance of simultaneous amyloid PET/MRI. Eur J Nucl Med Mol Imaging. 2016;43(12):2236-2243.
Tahmasian M, Shao J, Meng C, et al. Based on the network degeneration hypothesis: separating individual patients with different neurodegenerative syndromes in a preliminary hybrid PET/MR study. J Nucl Med. 2016;57(3):410-415.
Ding C, Han Y, Jiang J. Exploring the relevance between brain glucose metabolism and functional connectivity in Chinese cognitive dysfunctions' subjects using integrated resting-state PET/MRI images. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC); May 20-24, 2020; Montreal.
Yan S, Zheng C, Cui B, et al. Multiparametric imaging hippocampal neurodegeneration and functional connectivity with simultaneous PET/MRI in Alzheimer's disease. Eur J Nucl Med Mol Imaging. 2020;47(10):2440-2452.
Scherr M, Utz L, Tahmasian M, et al. Effective connectivity in the default mode network is distinctively disrupted in Alzheimer's disease-a simultaneous resting-state FDG-PET/fMRI study. Hum Brain Mapp. 2019:1-10.
Braak H, Braak E. Neuropathological staging of Alzheimer-related changes. Acta Neuropathol. 1991;82:239-259.
Frisoni GB, Fox NC, Jack CR Jr., Scheltens P, Thompson PM. The clinical use of structural MRI in Alzheimer disease. Nat Rev Neurol. 2010;6:67.
West MJ, Coleman PD, Flood DG, Troncoso JC. Differences in the pattern of hippocampal neuronal loss in normal ageing and Alzheimer's disease. Lancet. 1994;344:769-772.
Csernansky JG, Wang L, Swank J, et al. Preclinical detection of Alzheimer's disease: hippocampal shape and volume predict dementia onset in the elderly. Neuroimage. 2005;25:783-792.
Mosconi L, Santi SD, Li J, et al. Hippocampal hypometabolism predicts cognitive decline from normal aging. Neurobiol Aging. 2008;29:676-692.
Monti S, Cavaliere C, Covello M, Nicolai E, Salvatore M, Aiello M. An evaluation of the benefits of simultaneous acquisition on PET/MR co-registration in head/neck imaging. J Healthc Eng. 2017;2017:2634389.
Staff RT, Murray AD, Ahearn TS, Mustafa N, Fox HC, Whalley LJ. Childhood socioeconomic status and adult brain size: childhood socioeconomic status influences adult hippocampal size. Ann Neurol. 2012;71(5):653-660.
Jack CR, Wiste HJ, Vemuri P, et al. Brain beta-amyloid measures and magnetic resonance imaging atrophy both predict time-to-progression from mild cognitive impairment to Alzheimer's disease. Brain. 2010;133(11):3336-3348.
Wang L, Zang Y, He Y, et al. Changes in hippocampal connectivity in the early stages of Alzheimer's disease: evidence from resting state fMRI. Neuroimage 2006;31:496-504.
Choi EJ, Son YD, Noh Y, Lee H, Kim YB, Park KH. Glucose hypometabolism in hippocampal subdivisions in Alzheimer's disease: a pilot study using high-resolution 18F-FDG PET and 7.0-T MRI. J Clin Neurol 2018;14(2):158-164.
Yassa MA, Stark SM, Bakker A, Albert MS, Gallagher M, Stark CE. High-resolution structural and functional MRI of hippocampal CA3 and dentate gyrus in patients with amnestic mild cognitive impairment. Neuroimage. 2010;51:1242-1252.
Bakker A, Krauss GL, Albert MS, et al. Reduction of hippocampal hyperactivity improves cognition in amnestic mild cognitive impairment. Neuron. 2012;74:467-474.
Badhwar A, Tam A, Dansereau C, Orban P, Hoffstaedter F, Bellec P. Resting-state network dysfunction in Alzheimer's disease: a systematic review and meta-analysis. Alzheimers Dement. 2017;8:73-85.
Klaassens BL, van Gerven JMA, van der Grond J, de Vos F, Moller C, Rombouts S. Diminished posterior precuneus connectivity with the default mode network differentiates normal aging from Alzheimer's disease. Front Aging Neurosci. 2017;9:97.
Minoshima S, Giordani B, Berent S, Frey KA, Foster NL, Kuhl DE. Metabolic reduction in the posterior cingulate cortex in very early Alzheimer's disease. Ann Neurol. 1997;42(1):85-94.
Mergenthaler P, Lindauer U, Dienel GA, Meisel A. Sugar for the brain: the role of glucose in physiological and pathological brain function. Trends Neurosci 2013;36(10):587-597.
Fox PT, Raichle ME, Mintun MA, Dence C. Nonoxidative glucose consumption during focal physiologic neural activity. Cell Biol 1986;102:2076.
Huang S, Zhou F, Jiang J, et al. Regional impairment of intrinsic functional connectivity strength in patients with chronic primary insomnia. Neuropsychiatr Dis Treat. 2017;13:1449-1462.
Brun A, Englund E. A white matter disorder in dementia of the Alzheimer type: a pathoanatomical study. Ann Neurol. 1986;19:253-262.
Brown JA, Deng J, Neuhaus J, et al. Patient-tailored, connectivity-based forecasts of spreading brain atrophy, Neuron. 2019;104(5):856-868.
Agosta F, Pievani M, Sala S, et al. White matter damage in Alzheimer disease and its relationship to gray matter atrophy. Radiology. 2011;258:853-863.
Shepherd TM, Nayak GK. Clinical use of integrated positron emission tomography-magnetic resonance imaging for dementia patients. Top Magn Reson Imaging. 2019;28(6):299-310.
Suarez J, Tartaglia MC, Vitali P, et al. Characterizing radiology reports in patients with frontotemporal dementia. Neurology. 2009;73:1073-1074.