PET/MR in Dementia and Other Neurodegenerative Diseases
Abstract
The spectrum of neurodegenerative diseases covers the dementias, parkinsonian syndromes, Huntington disease, amyotrophic lateral sclerosis, and prion diseases. In these entities, brain MRI is often used in clinical routine to exclude other pathologies and to demonstrate specific atrophy patterns. [18F]FDG PET delivers early and sensitive readouts of neural tissue loss, and more specific PET tracers currently in use clinically target β-amyloid plaques or dopaminergic deficiency. The recent integration of PET into MR technology offers a new chance to improve early and differential diagnosis of many neurodegenerative diseases. Initial evidence in the literature is available to support this notion. New emerging PET tracers, such as tracers that bind to tau or α-synuclein aggregates, as well as MR techniques, like diffusion-tensor imaging, resting-state functional MRI, and arterial spin labeling, have the potential to broaden the diagnostic capabilities of combined PET/MRI to image dementias, Parkinson disease, and other neurodegenerative diseases. The ultimate goal is to establish combined PET/MRI as a first-line imaging technique to provide, in a one-stop-shop fashion with improved patient comfort, all biomarker information required to increase diagnostic confidence toward specific diagnoses. The technical challenge of accurate PET data attenuation correction within PET/MRI systems needs yet to be solved. Apart from the projected clinical routine applications, future research would need to answer the questions of whether combined brain PET/MRI is able to improve basic research of neurodegenerative diseases and antineurodegeneration drug testing.
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Diagnosis of neurodegenerative diseases is usually based on subjective cognitive tests in combination with neuroimaging, but the current techniques are not able to successfully diagnose these diseases in their earlier stages, when the pathology is already present but does not cause symptoms yet.
“Diagnosis of neurodegenerative diseases is usually based on subjective cognitive tests in combination with neuroimaging [131–133], but the current techniques are not able to successfully diagnose these diseases in their earlier stages, when the pathology is already present but does not cause symptoms yet.”
From Brain-Derived Neurotrophic Factor in Brain Disorders: Focus on Neuroinflammation (2019) · cites this paper as [131]
Cites
McKhann, G. M., Knopman, D. S., Chertkow, H., Hyman, B. T., Jack, C. R., Kawas, C. H., Klunk, W. E., Koroshetz, W. J., Manly, J. J., Mayeux, R., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.005 · Cited by 18,657 · see citing works
Albert, M. S., DeKosky, S. T., Dickson, D., Dubois, B., Feldman, H. H., Fox, N. C., Gamst, A., Holtzman, D. M., Jagust, W. J., Petersen, R. C., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.008 · Cited by 10,152 · cited 1× · see citing works
“This led to the stratification of 33%, 48%, and 19% of the MCI subjects as unlikely owing to AD, intermediate, and high likelihood of MCI due to AD, respectively, according to established diagnostic criteria.(19) For the remaining 41 patients with AD dementia, 59% had pathologic PET and 44%had pathologic PETþMR images.”
Albert, M., DeKosky, S. T., Dickson, D. W., Dubois, B., Feldman, H., Fox, N. C., Gamst, A. C., Holtzman, D. M., Jagust, W. J., Petersen, R. C., et al. (2013) · FOCUS The Journal of Lifelong Learning in Psychiatry · doi:10.1176/appi.focus.11.1.96 · Cited by 2,630 · see citing works
Simultaneous PET-MRI: a new approach for functional and morphological imaging
Judenhofer, M. S., Wehrl, H. F., Newport, D. F., Catana, C., Siegel, S. B., Becker, M., Thielscher, A., Kneilling, M., Lichy, M. P., Eichner, M., et al. (2008) · Nature Medicine · doi:10.1038/nm1700 · Cited by 983 · see citing works
Simultaneous MR/PET Imaging of the Human Brain: Feasibility Study
Schlemmer, H.-P., Pichler, B. J., Schmand, M. J., Burbar, Z., Michel, C. J., Ladebeck, R., Jattke, K., Townsend, D. W., Nahmias, C., Jacob, P. K., et al. (2008) · Radiology · doi:10.1148/radiol.2483071927 · Cited by 473 · see citing works
Molecular Basis of the Neurodegenerative Disorders
Martin, J. B. (1999) · New England Journal of Medicine · doi:10.1056/nejm199906243402507 · Cited by 416 · see citing works
Johnson, K. A., Minoshima, S., Bohnen, N. I., Donohoe, K. J., Foster, N. L., Herscovitch, P., Karlawish, J. H., Rowe, C. C., Carrillo, M. C., Hartley, D. M., et al. (2013) · Journal of Nuclear Medicine · doi:10.2967/jnumed.113.120618 · Cited by 329 · see citing works
PET/MRI for Neurologic Applications
Catana, C., Drzezga, A. E., Heiss, W., & Rosen, B. R. (2012) · Journal of Nuclear Medicine · doi:10.2967/jnumed.112.105346 · Cited by 292 · see citing works
In Vivo Quantitative Susceptibility Mapping (QSM) in Alzheimer's Disease
Acosta‐Cabronero, J., Williams, G. B., Cárdenas‐Blanco, A., Arnold, R. J., Lupson, V. C., & Nestor, P. J. (2013) · PLoS ONE · doi:10.1371/journal.pone.0081093 · Cited by 288 · see citing works
Riedl, V., Kurcyus, K., Strobel, C., Tahmasian, M., Grimmer, T., Förster, S., Friston, K. J., Sorg, C., & Drzezga, A. E. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.0492-14.2014 · Cited by 188 · see citing works
[ 18 F]FDG-PET is superior to [ 123 I]IBZM-SPECT for the differential diagnosis of parkinsonism
Hellwig, S., Amtage, F., Kreft, A., Buchert, R., Winz, O., Vach, W., Spehl, T. S., Rijntjes, M., Hellwig, B., Weiller, C., et al. (2012) · Neurology · doi:10.1212/wnl.0b013e31826c1b0a · Cited by 175 · see citing works
Combined Evaluation of FDG-PET and MRI Improves Detection and Differentiation of Dementia
Dukart, J., Mueller, K., Horstmann, A., Barthel, H., Möller, H. E., Villringer, A., Sabri, O., & Schroeter, M. L. (2011) · PLoS ONE · doi:10.1371/journal.pone.0018111 · Cited by 153 · see citing works
Self-citationSignificance of MRI in Diagnosis and Differential Diagnosis of Parkinson’s Disease
Mahlknecht, P., Hotter, A., Hussl, A., Esterhammer, R., Schocke, M. F. H., & Seppi, K. (2010) · Neurodegenerative Diseases · doi:10.1159/000314495 · Cited by 148 · see citing works
The potential of PET/MR for brain imaging
Heiss, W. (2008) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-008-0962-3 · Cited by 139 · see citing works
Zhang, K., Herzog, H. R., Mauler, J., Filß, C., Okell, T. W., Kops, E. R., Tellmann, L., Fischer, T., Brocke, B., Sturm, W., et al. (2014) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.2014.92 · Cited by 138 · see citing works
Dukart, J., Mueller, K., Barthel, H., Villringer, A., Sabri, O., & Schroeter, M. L. (2012) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2012.04.007 · Cited by 129 · see citing works
Self-citationClinical Applications of Hybrid PET/MRI in Neuroimaging
Garibotto, V., Heinzer-Schweizer, S., Vulliémoz, S., Guignard, R., Wissmeyer, M., Seeck, M., Lövblad, K., Zaidi, H., Ratib, O. M., & Vargas, M. I. (2012) · Clinical Nuclear Medicine · doi:10.1097/rlu.0b013e3182638ea6 · Cited by 102 · see citing works
Potential Clinical Applications of PET/MR Imaging in Neurodegenerative Diseases
Drzezga, A. E., Barthel, H., Minoshima, S., & Sabri, O. (2014) · Journal of Nuclear Medicine · doi:10.2967/jnumed.113.129254 · Cited by 81 · see citing works
Self-citationDynamic network participation of functional connectivity hubs assessed by resting-state fMRI
Schaefer, A., Margulies, D. S., Lohmann, G., Gorgolewski, K. J., Smallwood, J., Kiebel, S. J., & Villringer, A. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00195 · Cited by 70 · see citing works
Schroeter, M. L., & Neumann, J. (2011) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2011.00010 · Cited by 55 · see citing works
Self-citationHitz, S., Habekost, C., Fürst, S., Delso, G., Förster, S., Ziegler, S. I., Nekolla, S. G., Souvatzoglou, M., Beer, A. J., Grimmer, T., et al. (2014) · Journal of Nuclear Medicine · doi:10.2967/jnumed.113.126813 · Cited by 52 · see citing works
Bailey, D. L., Barthel, H., Beuthien‐Baumann, B., Beyer, T., Bisdas, S., Boellaard, R., Czernin, J. G., Drzezga, A. E., Ernemann, U., Franzius, C., et al. (2014) · Molecular Imaging and Biology · doi:10.1007/s11307-014-0725-4 · Cited by 39 · see citing works
Self-citationChoi, H., Cheon, G. J., Kim, H., Choi, S. H., Lee, J. S., Kim, Y., Kang, K. W., Chung, J.-K., Kim, E. E., & Lee, D. S. (2014) · Journal of Nuclear Medicine · doi:10.2967/jnumed.114.138636 · Cited by 26 · see citing works
Jena, A., Taneja, S., Goel, R., Renjen, P. N., & Negi, P. (2014) · European Journal of Radiology · doi:10.1016/j.ejrad.2014.04.008 · Cited by 22 · see citing works
Amyloid PET/MRI in the Differential Diagnosis of Dementia
Vercher-Conejero, J. L., Rubbert, C., Kohan, A. A., Partovi, S., & O’Donnell, J. K. (2013) · Clinical Nuclear Medicine · doi:10.1097/rlu.0b013e31829b9e5f · Cited by 16 · see citing works
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1 of the 26 references couldn’t be matched to a known paper.
Cited by
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Brain-Derived Neurotrophic Factor in Brain Disorders: Focus on Neuroinflammation
Lima Giacobbo, B., Doorduin, J., Klein, H. C., Dierckx, R. A. J. O., Bromberg, E., & de Vries, E. F. J. (2019) · Molecular Neurobiology · doi:10.1007/s12035-018-1283-6 · Cited by 750 · see citing works
Test–retest measurements of dopamine D1-type receptors using simultaneous PET/MRI imaging
Kaller, S., Rullmann, M., Patt, M., Becker, G.-A., Luthardt, J., Girbardt, J., Meyer, P. M., Werner, P., Barthel, H., Bresch, A., et al. (2017) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-017-3645-0 · Cited by 152 · see citing works
Self-citationTalwar, P., Kushwaha, S. S., Chaturvedi, M., & Mahajan, V. (2021) · Clinical Neuroradiology · doi:10.1007/s00062-021-01057-7 · Cited by 134 · see citing works
Deep learning-based PET image denoising and reconstruction: a review
Hashimoto, F., Onishi, Y., Ote, K., Tashima, H., Reader, A. J., & Yamaya, T. (2024) · Radiological Physics and Technology · doi:10.1007/s12194-024-00780-3 · Cited by 103 · see citing works
MR/PET Imaging of the Cardiovascular System
Robson, P. M., Dey, D., Newby, D. E., Berman, D. S., Li, D., Fayad, Z. A., & Dweck, M. R. (2017) · JACC. Cardiovascular imaging · doi:10.1016/j.jcmg.2017.07.008 · Cited by 96 · see citing works
Initial experience with a SiPM-based PET/CT scanner: influence of acquisition time on image quality
Sonni, I., Baratto, L., Park, S., Hatami, N., Srinivas, S., Davidzon, G., Gambhir, S. S., & Iagaru, A. (2018) · EJNMMI Physics · doi:10.1186/s40658-018-0207-x · Cited by 74 · see citing works
Broski, S. M., Goenka, A. H., Kemp, B. J., & Johnson, G. B. (2018) · American Journal of Roentgenology · doi:10.2214/ajr.18.20001 · Cited by 74 · see citing works
PET/MR Imaging: New Frontier in Alzheimer's Disease and Other Dementias
Zhang, X. Y., Yang, Z. L., Lu, G., Yang, G. F., & Zhang, L. J. (2017) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2017.00343 · Cited by 70 · see citing works
FDG PET/CT in cancer: comparison of actual use with literature-based recommendations
on behalf of the PET/CT Task Force of the Region of Southern Denmark, Petersen, H., Holdgaard, P. C., Madsen, P. H., Knudsen, L. M., Gad, D., Gravergaard, A. E., Rohde, M., Godballe, C., Engelmann, B. E., et al. (2015) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-015-3217-0 · Cited by 63 · see citing works
Khalili‐Mahani, N., Rombouts, S. A. R. B., van Osch, M. J. P., Duff, E. P., Carbonell, F., Nickerson, L. D. H., Becerra, L. R., Dahan, A., Evans, A. C., Soucy, J., et al. (2017) · Human Brain Mapping · doi:10.1002/hbm.23516 · Cited by 61 · see citing works
Bailey, D. L., Pichler, B. J., Gückel, B., Antoch, G., Barthel, H., Bhujwalla, Z. M., Biskup, S., Biswal, S., Bitzer, M., Boellaard, R., et al. (2017) · Molecular Imaging and Biology · doi:10.1007/s11307-017-1123-5 · Cited by 58 · see citing works
Self-citationHu, X., Sun, X., Hu, F., Liu, F., Ruan, W., Wu, T., An, R. F., & Lan, X. (2021) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-021-05325-z · Cited by 56 · see citing works
Sharma, V., Singh, T. G., Kaur, A., Mannan, A., & Dhiman, S. (2022) · Neurochemical Research · doi:10.1007/s11064-022-03755-1 · Cited by 55 · see citing works
Application of Deep Learning for Prediction of Alzheimer’s Disease in PET/MR Imaging
Zhao, Y., Guo, Q., Zhang, Y., Zheng, J., Yang, Y., Du, X., Feng, H., & Zhang, S. (2023) · Bioengineering · doi:10.3390/bioengineering10101120 · Cited by 48 · see citing works
Generalization of deep learning models for ultra-low-count amyloid PET/MRI using transfer learning
Chen, K. T., Schürer, M., Ouyang, J., Koran, M. E. I., Davidzon, G., Mormino, E. C., Tiepolt, S., Hoffmann, K., Sabri, O., Zaharchuk, G., et al. (2020) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-020-04897-6 · Cited by 48 · see citing works
Self-citationSpatial adaptive and transformer fusion network (STFNet) for low‐count PET blind denoising with MRI
Zhang, L., Xiao, Z., Zhou, C., Yuan, J., He, Q., Yang, Y., Liu, X., Liang, D., Zheng, H., Fan, W., et al. (2021) · Medical Physics · doi:10.1002/mp.15368 · Cited by 45 · see citing works
Current radiotracers to image neurodegenerative diseases
Tiepolt, S., Patt, M., Aghakhanyan, G., Meyer, P., Hesse, S., Barthel, H., & Sabri, O. (2019) · EJNMMI Radiopharmacy and Chemistry · doi:10.1186/s41181-019-0070-7 · Cited by 41 · see citing works
Self-citationTeuho, J., Torrado-Carvajal, Á., Herzog, H. R., Anazodo, U., Klén, R., Iida, H., & Teräs, M. (2020) · Frontiers in Physics · doi:10.3389/fphy.2019.00243 · Cited by 40 · see citing works
Bonvento, G., Valette, J., Flament, J., Mochel, F., & Brouillet, E. (2017) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x17697989 · Cited by 36 · see citing works
Workflow in Simultaneous PET/MRI
Barbosa, F. D. G., von Schulthess, G. K., & Veit‐Haibach, P. (2015) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2015.03.007 · Cited by 35 · see citing works
PET/MRI of central nervous system: current status and future perspective
Yang, Z. L., & Zhang, L. J. (2016) · European Radiology · doi:10.1007/s00330-015-4202-5 · Cited by 35 · see citing works
The role of magnetic resonance imaging in the diagnosis of Parkinson's disease: a review
Al‐Radaideh, A., & Rababah, E. M. (2016) · Clinical Imaging · doi:10.1016/j.clinimag.2016.05.006 · Cited by 35 · see citing works
Lew, C. O., Zhou, L., Mazurowski, M. A., Doraiswamy, P. M., Petrella, J. R., & Initiative, A. D. N. (2023) · Radiology · doi:10.1148/radiol.222441 · Cited by 34 · see citing works
Protein and Gene Delivery Systems for Neurodegenerative Disorders: Where Do We Stand Today?
Siafaka, P. I., Okur, M. E., Dilsiz, P., Çağlar, E. Ş., Özgenç, E., Gündoğdu, E., Köprülü, R. E. P., Karantas, I. D., & Okur, N. Ü. (2022) · Pharmaceutics · doi:10.3390/pharmaceutics14112425 · Cited by 34 · see citing works
Ladefoged, C. N., Andersen, F. L., Kjær, A., Højgaard, L., & Law, I. G. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00453 · Cited by 31 · see citing works
Performance Study of a Radio-Frequency Field-Penetrable PET Insert for Simultaneous PET/MRI
Chang, C., Lee, B. J., Grant, A. M., Groll, A. N., & Levin, C. S. (2018) · IEEE Transactions on Radiation and Plasma Medical Sciences · doi:10.1109/trpms.2018.2852686 · Cited by 30 · see citing works
Clinical PET/MR Imaging in Dementia and Neuro-Oncology
Henriksen, O. M., Marner, L., & Law, I. G. (2016) · PET Clinics · doi:10.1016/j.cpet.2016.05.003 · Cited by 30 · see citing works
The Advents of Hybrid Imaging Modalities: A New Era in Neuroimaging Applications
Padmanabhan, P., Nedumaran, A. M., Mishra, S., Pandarinathan, G., Archunan, G., & Gulyás, B. Z. (2017) · Advanced Biosystems · doi:10.1002/adbi.201700019 · Cited by 29 · see citing works
The Additional Value of PET in the Assessment of Cerebral Small Vessel Disease
Heiss, W. (2018) · Journal of Nuclear Medicine · doi:10.2967/jnumed.118.214270 · Cited by 29 · see citing works
Florek, L., Tiepolt, S., Schroeter, M. L., Berrouschot, J., Saur, D., Hesse, S., Jochimsen, T. H., Luthardt, J., Sattler, B., Patt, M., et al. (2018) · Journal of Alzheimer s Disease · doi:10.3233/jad-180522 · Cited by 28 · see citing works
Self-citationOkazawa, H., Ikawa, M., Jung, M., Maruyama, R., Tsujikawa, T., Mori, T., Rahman, M. G. M., Makino, A., Kiyono, Y., & Kosaka, H. (2020) · EJNMMI Research · doi:10.1186/s13550-020-00619-z · Cited by 28 · see citing works
Kumari, R., Nigam, A., & Pushkar, S. (2022) · Neural Computing and Applications · doi:10.1007/s00521-022-07076-w · Cited by 26 · see citing works
Lee, J., Renslo, J., Wong, K., Clifford, T. G., Beutler, B. D., Kim, P. E., & Gholamrezanezhad, A. (2024) · Diagnostics · doi:10.3390/diagnostics14060585 · Cited by 25 · see citing works
Develop a diagnostic tool for dementia using machine learning and non-imaging features
Wang, H., Sheng, L. Q., Xu, S., Jin, Y., Jin, X., Qiao, S., Chen, Q., Xing, W., Zhao, Z., Yan, J., et al. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.945274 · Cited by 25 · see citing works
Yu, B., Ozdemir, S., Dong, Y., Shao, W., Pan, T., Shi, K., & Gong, K. (2025) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-025-07122-4 · Cited by 24 · see citing works
Ostapchenko, V. G., Snir, J. A., Suchý, M., Fan, J., Cobb, M. R., Chronik, B. A., Kovacs, M. S., Prado, V. F., Hudson, R. H. E., Pasternak, S., et al. (2019) · Contrast Media & Molecular Imaging · doi:10.1155/2019/6403274 · Cited by 24 · see citing works
Sgard, B., Khalifé, M., Bouchut, A., Fernandez, B., Soret, M., Giron, A., Zaslavsky, C., Delso, G., Habert, M., & Kas, A. (2019) · European Radiology · doi:10.1007/s00330-019-06514-z · Cited by 23 · see citing works
Hybrid PET/MR Imaging in Neurology: Present Applications and Prospects for the Future
Heiss, W. (2016) · Journal of Nuclear Medicine · doi:10.2967/jnumed.116.175208 · Cited by 23 · see citing works
Kaltoft, N. S., Marner, L., Larsen, V. A., Hasselbalch, S. G., Law, I. G., & Henriksen, O. M. (2019) · PLoS ONE · doi:10.1371/journal.pone.0216409 · Cited by 21 · see citing works
Posterior Cingulate Cortex Hypometabolism in Non-Amnestic Variants of Alzheimer’s Disease
Bergeron, D., Beauregard, J., Jean-Guimond, Soucy, J., Verret, L., Poulin, S. P., Matías‐Guiu, J. A., Cabrera‐Martín, M. N., Bouchard, R. W., & Laforce, R. J. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200567 · Cited by 20 · see citing works
Multi-technique hybrid imaging in PET/CT and PET/MR: what does the future hold?
Barbosa, F. D. G., Delso, G., ter Voert, E. E. G. W., Huellner, M. W., Herrmann, K., & Veit‐Haibach, P. (2016) · Clinical Radiology · doi:10.1016/j.crad.2016.03.013 · Cited by 20 · see citing works
Porous Materials for Early Diagnosis of Neurodegenerative Diseases
Arghavani, P., Daneshgar, H., Sojdeh, S., Edrisi, M., Moosavi‐Movahedi, A. A., & Rabiee, N. (2025) · Advanced Healthcare Materials · doi:10.1002/adhm.202404685 · Cited by 19 · see citing works
Hybrid PET-MRI Applications in Movement Disorders
Tondo, G., Esposito, M., Dervenoulas, G., Wilson, H., Politis, M., & Pagano, G. (2018) · International review of neurobiology · doi:10.1016/bs.irn.2018.10.003 · Cited by 18 · see citing works
Clinical Value of Hybrid PET/MR Imaging
Kas, A., Rozenblum, L., & Pyatigorskaya, N. (2023) · Magnetic Resonance Imaging Clinics of North America · doi:10.1016/j.mric.2023.06.004 · Cited by 17 · see citing works
Measurement Challenges in Research With Individuals With Cognitive Impairment
Kolanowski, A. M., Gilmore‐Bykovskyi, A. L., Hill, N. L., Massimo, L. M., & Mogle, J. A. (2019) · Research in Gerontological Nursing · doi:10.3928/19404921-20181212-06 · Cited by 17 · see citing works
Clinical and Instrumental Characterization of Patients With Late-Onset Epilepsy
DiFrancesco, J. C., Labate, A., Romoli, M., Chipi, E., Salvadori, N., Galimberti, C. A., Perani, D., Ferrarese, C., & Costa, C. (2022) · Frontiers in Neurology · doi:10.3389/fneur.2022.851897 · Cited by 17 · see citing works
Rigid-body motion correction in hybrid PET/MRI using spherical navigator echoes
Johnson, P. M., Taylor, R., Whelan, T. J., Thiessen, J. D., Anazodo, U., & Drangova, M. (2019) · Physics in Medicine and Biology · doi:10.1088/1361-6560/ab10b2 · Cited by 16 · see citing works
Ito, H., Kubo, H., Takahashi, K., Nishijima, K., Ukon, N., Nemoto, A., Sugawara, S., Yamakuni, R., Ibaraki, M., & Ishii, S. (2021) · Annals of Nuclear Medicine · doi:10.1007/s12149-021-01578-8 · Cited by 15 · see citing works
In vivo whole brain, cellular and molecular imaging in nonhuman primate models of neuropathology
Huang, L., Merson, T. D., & Bourne, J. A. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.04.009 · Cited by 15 · see citing works
FDG PET/MR Imaging in Major Neurocognitive Disorders
Mainta, I., Perani, D., Delattre, B. M. A., Assal, F., Haller, S., Vargas, M. I., Zekry, D., Frisoni, G. B., Zaidi, H., Ratib, O. M., et al. (2016) · Current Alzheimer Research · doi:10.2174/1567205013666160620115130 · Cited by 14 · see citing works
Design and initial results of an RF-penetrable TOF PET insert dedicated for brain PET/MRI
Chang, C., Lee, B. J., Sacco, I., Watkins, R. D., Dong, Q., & Levin, C. S. (2017) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2017.8533057 · Cited by 13 · see citing works
van Waalwijk van Doorn, L. J. C., Gispert, J. D., Kuiperij, H. B., Claassen, J. A. H. R., Arighi, A., Baldeiras, I., Blennow, K., Bozzali, M., Castelo-Branco, M., Cavedo, E., et al. (2017) · Journal of Alzheimer’s Disease · doi:10.3233/jad-160668 · Cited by 13 · see citing works
Øen, S. K., Keil, T. M., Berntsen, E. M., Aanerud, J., Schwarzlmüller, T., Ladefoged, C. N., Karlberg, A. M., & Eikenes, L. (2019) · EJNMMI Research · doi:10.1186/s13550-019-0553-2 · Cited by 12 · see citing works
A Role of PET/MR Imaging in Dementia?
Dupont, P. J. (2021) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2021.01.003 · Cited by 11 · see citing works
Mannheim, J. G., Cheng, J.-C. K., Vafai, N. M., Shahinfard, E., English, C., McKenzie, J., Zhang, J., Barlow, L. R., & Sossi, V. (2021) · EJNMMI Physics · doi:10.1186/s40658-020-00349-0 · Cited by 11 · see citing works
Dose Reduction in Brain [18F]FDG PET/MRI: Give It Half a Chance
Soret, M., Piekarski, E., Yeni, N., Giron, A., Maisonobe, J.-A., Khalifé, M., Zaslavsky, C., Bertaux, M., Habert, M., & Kas, A. (2019) · Molecular Imaging and Biology · doi:10.1007/s11307-019-01398-3 · Cited by 11 · see citing works
Takeuchi, W., Suzuki, A., Shiga, T., Kubo, N., Morimoto, Y., Ueno, Y., Kobashi, K., Umegaki, K., & Tamaki, N. (2016) · EJNMMI Physics · doi:10.1186/s40658-016-0147-2 · Cited by 10 · see citing works
PET/MRI: A luxury or a necessity?
Carreras-Delgado, J. L., Pérez-Dueñas, V., Riola-Parada, C., & García‐Cañamaque, L. (2016) · Revista Española de Medicina Nuclear e Imagen Molecular (English Edition) · doi:10.1016/j.remnie.2016.07.002 · Cited by 10 · see citing works
Queiroz, M. A., Barbosa, F. D. G., Buchpiguel, C. A., & Cerri, G. G. (2018) · Revista da Associação Médica Brasileira · doi:10.1590/1806-9282.64.01.71 · Cited by 10 · see citing works
Leung, I. H. K., & Strudwick, M. W. (2024) · EJNMMI Reports · doi:10.1186/s41824-024-00194-9 · Cited by 9 · see citing works
Magnetic Resonance Fingerprinting: Implications and Opportunities for PET/MR
Ropella‐Panagis, K., Seiberlich, N., & Gulani, V. (2019) · IEEE Transactions on Radiation and Plasma Medical Sciences · doi:10.1109/trpms.2019.2897425 · Cited by 9 · see citing works
Apostolova, I. I., Lange, C., Roberts, A., Igel, H. J., Maeurer, A., Liese, S., Estrella, M., Prasad, V., Stechl, E., Lämmler, G., et al. (2016) · Journal of Alzheimer s Disease · doi:10.3233/jad-160797 · Cited by 9 · see citing works
Synergy in Neuroimaging: PET-CT and MRI Fusion for Enhanced Characterization of Brain Pathology
Radder, N., Sonar, S., Nanivadekar, A., & Radder, S. (2024) · Cureus · doi:10.7759/cureus.74353 · Cited by 8 · see citing works
Thientunyakit, T., Muangpaisan, W., & Minoshima, S. (2025) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2025.04.007 · Cited by 8 · see citing works
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Pozzoli, S. M., Carlo, V. D., & Madonna, D. (2018) · Springer eBooks · doi:10.1007/978-3-319-91557-9_10 · Cited by 8 · see citing works
Bisdas, S., la Fougère, C. J., & Ernemann, U. (2015) · Clinical Neuroradiology · doi:10.1007/s00062-015-0427-6 · Cited by 7 · see citing works
Seyedin, S. N., Bassalow, R., Mawlawi, O. R., Turner, L. M., Patel, R. R., Mazin, S. R., Oderinde, O. M., Voronenko, Y., Wages, C. A., Olcott, P. D., et al. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.921473 · Cited by 7 · see citing works
Neuroimaging in Alzheimer's disease: preclinical challenges toward clinical efficacy
Dustin, D. J., Hall, B. M., Annapragada, A., & Pautler, R. G. (2016) · Translational research · doi:10.1016/j.trsl.2016.03.005 · Cited by 7 · see citing works
Molecular Imaging with PET in the Assessment of Vascular Dementia and Cerebrovascular Disease
Patil, S., Patel, D., Kata, R., Teichner, E. M., Subtirelu, R. C., Ayubcha, C., Werner, T. J., & Alavi, A. A. (2024) · PET Clinics · doi:10.1016/j.cpet.2024.09.001 · Cited by 6 · see citing works
Yu, B., Ozdemir, S., Dong, Y., Shao, W., Shi, K., & Gong, K. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72104-5_52 · Cited by 6 · see citing works
Sossi, V. (2018) · International review of neurobiology · doi:10.1016/bs.irn.2018.07.034 · Cited by 6 · see citing works
Cognitive impact of exposure to airborne particles captured by brain imaging
Azmoun, S., Diaz, Y. F., Tang, C. Y., Horton, M. K., Clouston, S., Luft, B. J., Bromet, E. J., Gandy, S., Placidi, D., Ambrosi, C., et al. (2022) · Advances in neurotoxicology · doi:10.1016/bs.ant.2022.05.002 · Cited by 6 · see citing works
Hashimoto, F., & Ote, K. (2024) · Physics in Medicine and Biology · doi:10.1088/1361-6560/ad40f6 · Cited by 6 · see citing works
Sekine, T., Buck, A., Delso, G., Kemp, B. J., ter Voert, E. E. G. W., Huellner, M. W., Veit‐Haibach, P., Kaushik, S. S., Wiesinger, F., Warnock, G., et al. (2020) · PLoS ONE · doi:10.1371/journal.pone.0233886 · Cited by 6 · see citing works
Vitrio, B., Destefani, V. C., & Destêfani, A. C. (2024) · Brazilian Journal of Implantology and Health Sciences · doi:10.36557/2674-8169.2024v6n8p3962-3983 · Cited by 5 · see citing works
Imaging in Neurodegeneration: Movement Disorders
Sossi, V., Cheng, J.-C. K., & Klyuzhin, I. S. (2018) · IEEE Transactions on Radiation and Plasma Medical Sciences · doi:10.1109/trpms.2018.2871760 · Cited by 5 · see citing works
Beuthien‐Baumann, B. (2018) · Der Radiologe · doi:10.1007/s00117-018-0355-y · Cited by 5 · see citing works
PET/RM: ¿un lujo o una necesidad?
Carreras-Delgado, J. L., Pérez-Dueñas, V., Riola-Parada, C., & García‐Cañamaque, L. (2016) · Revista Española de Medicina Nuclear e Imagen Molecular · doi:10.1016/j.remn.2016.05.007 · Cited by 5 · see citing works
von Schulthess, G. K., & Veit‐Haibach, P. (2015) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2014.12.006 · Cited by 5 · see citing works
Dondi, F., Latronico, N., Bellini, P., Lucchini, S., Camoni, L., Cossandi, M., Viganò, G. L., Santo, G., & Bertagna, F. (2025) · Diagnostics · doi:10.3390/diagnostics15111406 · Cited by 4 · see citing works
Comparative Study of Relevant Methods for MRI/X Brain Image Registration
Abderrahim, M., Baâzaoui, A., & Barhoumi, W. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-51517-1_30 · Cited by 4 · see citing works
Hori, A., Ai, T., Isshiki, M., Motoi, Y., Yano, K., Tabe, Y., Hattori, N., & Miida, T. (2021) · Geriatrics · doi:10.3390/geriatrics6010014 · Cited by 4 · see citing works
Guide à la lecture et interprétation de l’imagerie PET des plaques amyloïdes
Denis, A., Dietemann, S., Noirot, C., Andryszak, P., Trombella, S., Frisoni, G. B., Mainta, I., & Garibotto, V. (2017) · Médecine Nucléaire · doi:10.1016/j.mednuc.2017.06.008 · Cited by 3 · see citing works
Imaging biomarkers in Alzheimer's disease
Sudre, C. H., Cardoso, M. J., Marc Modat, A., & Sebastien Ourselin, A. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-816176-0.00020-x · Cited by 3 · see citing works
Aptamer Detection of Neurodegenerative Disease Biomarkers
Xi, H., & Zhang, Y. (2021) · Neuromethods · doi:10.1007/978-1-0716-1712-0_15 · Cited by 3 · see citing works
Sousa, J. M., Appel, L., Engström, M., Papadimitriou, S., Nyholm, D., Ahlström, H. K., & Lubberink, M. (2022) · Physica Medica · doi:10.1016/j.ejmp.2022.03.012 · Cited by 3 · see citing works
Sousa, J. M., Appel, L., Engström, M., Nyholm, D., Ahlström, H. K., & Lubberink, M. (2023) · Physica Medica · doi:10.1016/j.ejmp.2023.103185 · Cited by 2 · see citing works
Salvador-Ribés, C., Pons, C. S., García, M. J. S., Fechter, T., Olivas, C., Torres-Espallardo, I., Pérez‐Calatayud, J., Baltas, D., Mix, M. D., Martí‐Bonmatí, L., et al. (2025) · EJNMMI Physics · doi:10.1186/s40658-025-00741-8 · Cited by 1 · see citing works
Binary Classification of Alzheimer's Disease Using Siamese Neural Network for Early Stage Diagnosis
Tekin, R., & Onur, T. Ö. (2025) · Celal Bayar Üniversitesi Fen Bilimleri Dergisi · doi:10.18466/cbayarfbe.1529546 · Cited by 1 · see citing works
Precise MRI-histology coregistration of paraffin-embedded tissue with blockface imaging
Wang, Y., Ho, W. H. D., Huszár, I. N., DiGiacomo, P. S., Taghavi, H. M., Tao, L., Choi, M., Nguyen, N. T., Leventis, S., Camarillo, D. B., et al. (2025) · Imaging Neuroscience · doi:10.1162/imag.a.106 · Cited by 1 · see citing works
Yao, J., Ma, J., Li, P., Liao, X., Zan, J., Hu, L., & Li, G. (2026) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2026.1727812 · Cited by 1 · see citing works
Neuroimaging in Cerebral Small Vessel Disease
Heiss, W. (2018) · Journal of Neurology and Neuromedicine · doi:10.29245/2572.942x/2018/1.1171 · Cited by 1 · see citing works
Rovera, C., & Pigoni, A. (2018) · Springer eBooks · doi:10.1007/978-3-319-91557-9_3 · Cited by 1 · see citing works
Calabria, F. F., Cimini, A., Bagnato, A., Gullà, D., Cascini, G. L., Urbano, N., & Schillaci, O. (2019) · Springer eBooks · doi:10.1007/978-3-030-27779-6_1 · Cited by 1 · see citing works
PET/MR: Basics and New Developments
Khalil, M. M. (2016) · Springer eBooks · doi:10.1007/978-3-319-40070-9_9 · Cited by 1 · see citing works
Amyotrophic Lateral Sclerosis (ALS)
(2016) · Elsevier eBooks · doi:10.1016/b978-0-323-44781-2.50200-x · Cited by 1 · see citing works
Positron Emission Tomography/Magnetic Resonanse Imaging Applications in Neurologic Imaging
Akdemir, Ü. Ö., Karabacak, N. İ., & Atay, L. Ö. (2017) · Nuclear Medicine Seminars · doi:10.4274/nts.005 · Cited by 1 · see citing works
Amyotrophic Lateral Sclerosis (ALS)
(2016) · Elsevier eBooks · doi:10.1016/b978-0-323-37754-6.50289-x · Cited by 1 · see citing works
Sathekge, M. M., & Bouchelouche, K. (2021) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2021.01.004 · Cited by 1 · see citing works
Recent Developments in Combined PET/MRI
Flavell, R. R., Wilson, D. M., & Behr, S. C. (2016) · Current Radiology Reports · doi:10.1007/s40134-016-0149-9
- Authors
- Barthel, H., Schroeter, M. L., Hoffmann, K.-T., & Sabri, O.
- Affiliations
- University Hospital Leipzig (DE)
- Max Planck Institute for Human Cognitive and Brain Sciences (DE)
- Leipzig University (DE)
- Corresponding author
- Barthel, Henryk
- Venue
- Seminars in Nuclear Medicine
- Publisher
- Elsevier BV
- Published
- 2015-05
- Volume
- 45
- Issue
- 3
- Pages
- 224-233
- ISSN
- 0001-2998 (ISSN-L)
- OpenAlex
- W1987273610
- Cited by
- 123
- References
- 26
- Citations by year
- 2026: 3 · 2025: 9 · 2024: 10 · 2023: 6 · 2022: 10 · 2021: 12 · 2020: 7 · 2019: 12 · 2018: 16 · 2017: 13 · 2016: 20 · 2015: 5
- FWCI
- 14.60
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Seminars in Nuclear Medicine (publishedVersion)
- PubMed (publishedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- PET/MRI, neurodegenerative diseases, dementia, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, prion disease, FDG-PET, amyloid PET tracers, tau PET tracers, diffusion tensor imaging, resting-state fMRI, arterial spin labeling, PET attenuation correction, neurodegeneration biomarkers, differential diagnosis
- MeSH terms
- Dementia, Humans, Magnetic Resonance Imaging, Parkinsonian Disorders, Positron-Emission Tomography, Multimodal Imaging
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