Share:
Share this content in WeChat
X
Review
Research progress of PET/MR imaging of carotid atherosclerotic plaque
FANG Ting  MENG Nan  BAI Yan  WEI Wei  HUANG Zhun  FENG Pengyang  WANG Meiyun 

Cite this article as: Fang T, Meng N, Bai Y, et al. Research progress of PET/MR imaging of carotid atherosclerotic plaque[J]. Chin J Magn Reson Imaging, 2021, 12(7): 105-109. DOI:10.12015/issn.1674-8034.2021.07.025.


[Abstract] Carotid atherosclerosis is recognized worldwide as an important factor leading to ischemic stroke and transient ischemic attack. In the past, many clinical trials used to measure the degree of carotid artery stenosis as a means of risk stratification. With the advancement of vascular imaging technology, it is now possible to stratify the risk of cerebrovascular accidents in patients not only according to the degree of carotid artery stenosis, but also according to the fragility of plaque rupture. People realize that the stability and vulnerability of the plaque are more important than the degree of stenosis. Because atherosclerotic diseases are driven by dynamic biological processes (inflammation is a key component), imaging plaque biology and plaque structure may provide important insights. Carotid PET/MR imaging is non-invasive. It can not only identify high-risk plaques, but also measure and detect plaque burden and activity. This review reviews the role of different tracers for state-of-the-art PET/MR imaging of atherosclerotic plaques, including the principles of this imaging method, current limitations, and future applications.
[Keywords] positron emission tomography/magnetic resonance imaging;stroke;carotid atherosclerosis;atherosclerotic plaque;positron emission tomography tracer

FANG Ting1   MENG Nan1   BAI Yan2   WEI Wei2   HUANG Zhun3   FENG Pengyang3   WANG Meiyun1, 2*  

1 Department of Medical Imaging, Zhengzhou University People's Hospital, Zhengzhou 450003, China

2 Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou 450003, China

3 Department of Medical Imaging,, Henan University People's Hospital, Zhengzhou 450003, China

Wang MY, E-mail: mywang@ha.edu.cn

Conflicts of interest   None.

ACKNOWLEDGMENTS This article is supported by the National Key R&D Program Project (No. 2017YFE0103600).
Received  2021-03-16
Accepted  2021-05-06
DOI: 10.12015/issn.1674-8034.2021.07.025
Cite this article as: Fang T, Meng N, Bai Y, et al. Research progress of PET/MR imaging of carotid atherosclerotic plaque[J]. Chin J Magn Reson Imaging, 2021, 12(7): 105-109. DOI:10.12015/issn.1674-8034.2021.07.025.

1
Libby P, Buring JE, Badimon L, et al. Atherosclerosis[J]. Nat Rev Dis Primers, 2019, 55(1): 56. DOI: 10.1038/s41572-019-0106-z.
2
Freilinger TM, Schindler A, Schmidt C, et al. Prevalence of nonstenosing, complicated atherosclerotic plaques in cryptogenic stroke[J]. JACC Cardiovasc Imaging, 2012, 55(4): 397-405. DOI: 10.1016/j.jcmg.2012.01.012.
3
Zamani M, Skagen K, Scott H, et al. Advanced ultrasound methods in assessment of carotid plaque instability: a prospective multimodal study[J]. BMC Neurol, 2020, 2020(1): 39. DOI: 10.1186/s12883-020-1620-z.
4
Kundel V, Trivieri MG, Karakatsanis NA, et al. Assessment of atherosclerotic plaque activity in patients with sleep apnea using hybrid positron emission tomography/magnetic resonance imaging (PET/MRI): a feasibility study[J]. Sleep Breath, 2018, 2222(4): 1125-35. DOI: 10.1007/s11325-018-1646-2.
5
Adawi M, Firas S, Blum A. Rheumatoid Arthritis and Atherosclerosis[J]. Isr Med Assoc J, 2019, 2121(7): 460-263.
6
Low H, Hoang A, Pushkarsky T, et al. HIV disease, metabolic dysfunction and atherosclerosis: A three year prospective study[J]. PLoS One, 2019, 1414(4): e0215620. DOI: 10.1371/journal.pone.0215620.
7
Carlucci PM, Purmalek MM, Dey AK, et al. Neutrophil subsets and their gene signature associate with vascular inflammation and coronary atherosclerosis in lupus[J]. JCI Insight, 2018, 33(8): e99276. DOI: 10.1172/jci.insight.99276.
8
Ali A, Tawakol A. FDG PET/CT Imaging of Carotid Atherosclerosis[J]. Neuroimaging Clin North Am, 2016, 2626(1): 45-54. DOI: 10.1016/j.nic.2015.09.004.
9
Evans NR, Tarkin JM, Le EP, et al. Integrated cardiovascular assessment of atherosclerosis using PET/MRI[J]. Br J Radiol, 2020, 9393(1113): 20190921. DOI: 10.1259/bjr.20190921.
10
Libby P, Ridker PM, Maseri A. Inflammation and atherosclerosis[J]. Circulation, 2002, 105105(9): 1135-1143. DOI: 10.1161/hc0902.104353.
11
Porambo ME, DeMarco JK. MR imaging of vulnerable carotid plaque[J]. Cardiovasc Diagn Ther, 2020, 1010(4): 1019-31. DOI: 10.21037/cdt.2020.03.12.
12
Redgrave JN, Lovett JK, Gallagher PJ, et al. Histological assessment of 526 symptomatic carotid plaques in relation to the nature and timing of ischemic symptoms: the Oxford plaque study[J]. Circulation, 2006, 113113(19): 2320-2328. DOI: 10.1161/CIRCULATIONAHA.105.589044.
13
Tomaniak M, Katagiri Y, Modolo R, et al. Vulnerable plaques and patients: state-of-the-art[J]. Eur Heart J, 2020, 4141(31): 2997-3004. DOI: 10.1093/eurheartj/ehaa227.
14
Liem MI, Kennedy F, Bonati LH, et al. Investigations of carotid stenosis to identify vulnerable atherosclerotic plaque and determine individual stroke risk[J]. Circ J, 2017, 8181(9): 1246-1253. DOI: 10.1253/circj.CJ-16-1284.
15
Schindler A, Schinner R, Altaf N, et al. Prediction of stroke risk by detection of hemorrhage in carotid plaques: Meta-analysis of individual patient data[J]. JACC Cardiovasc Imaging, 2020, 1313(2Pt 1): 395-406. DOI: 10.1016/j.jcmg.2019.03.028.
16
Makris GC, Teng Z, Patterson AJ, et al. Advances in MRI for the evaluation of carotid atherosclerosis[J]. Br J Radiol, 2015, 8888(1052): 20140282. DOI: 10.1259/bjr.20140282.
17
Morita S, Masukawa A, Suzuki K, et al. Unenhanced MR angiography: techniques and clinical applications in patients with chronic kidney disease[J]. Radiographics, 2011, 3131(2): E13-33. DOI: 10.1148/rg.312105075.
18
Saam T, Hatsukami TS, Takaya N, et al. The vulnerable, or high-risk, atherosclerotic plaque: noninvasive MR imaging for characterization and assessment[J]. Radiology, 2007, 244244(1): 64-77. DOI: 10.1148/radiol.2441051769.
19
Watanabe Y, Nagayama M. MR plaque imaging of the carotid artery[J]. Neuroradiology, 2010, 5252(4): 253-74. DOI: 10.1007/s00234-010-0663-z.
20
den Hartog AG, Bovens SM, Koning W, et al. Current status of clinical magnetic resonance imaging for plaque characterisation in patients with carotid artery stenosis[J]. Eur J Vasc Endovasc Surg, 2013, 4545(1): 7-21. DOI: 10.1016/j.ejvs.2012.10.022.
21
Finessi M, Bisi G, Deandreis D. Hyperglycemia and 18F-FDG PET/CT, issues and problem solving: a literature review[J]. Acta Diabetol, 2020, 5757(3): 253-262. DOI: 10.1007/s00592-019-01385-8.
22
Font MA, Fernandez A, Carvajal A, et al. Imaging of early inflammation in low-to-moderate carotid stenosis by 18-FDG-PET[J]. Front Biosci (Landmark Ed), 2009, 1414: 3352-3360. DOI: 10.2741/3457.
23
van der Vaart MG, Meerwaldt R, Slart RH, et al. Application of PET/SPECT imaging in vascular disease[J]. Eur J Vasc Endovasc Surg, 2008, 3535(5): 507-513. DOI: 10.1016/j.ejvs.2007.11.016.
24
Bueno A, March JR, Garcia P, et al. Carotid plaque inflammation assessed by (18)F-FDG PET/CT and Lp-PLA(2) is higher in symptomatic patients[J]. Angiology, 2021, 7272(3): 260-267. DOI: 10.1177/0003319720965419.
25
Johnsrud K, Skagen K, Seierstad T, et al. (18)F-FDG PET/CT for the quantification of inflammation in large carotid artery plaques[J]. J Nucl Cardiol, 2019, 2626(3): 883-893. DOI: 10.1007/s12350-017-1121-7.
26
Chaker S, Al-Dasuqi K, Baradaran H, et al. Carotid plaque positron emission tomography imaging and cerebral ischemic disease[J]. Stroke, 2019, 5050(8): 2072-2079. DOI: 10.1161/strokeaha.118.023987.
27
Rominger A, Saam T, Wolpers S, et al. 18F-FDG PET/CT identifies patients at risk for future vascular events in an otherwise asymptomatic cohort with neoplastic disease[J]. J Nucl Med, 2009, 5050(10): 1611-1620. DOI: 10.2967/jnumed.109.065151.
28
Tarkin JM, Joshi FR, Rudd JH. PET imaging of inflammation in atherosclerosis[J]. Nat Rev Cardiol, 2014, 1111(8): 443-457. DOI: 10.1038/nrcardio.2014.80.
29
Rosset A, Spadola L, Ratib O. OsiriX: an open-source software for navigating in multidimensional DICOM images[J]. J Digit Imaging, 2004, 1717(3): 205-216. DOI: 10.1007/s10278-004-1014-6.
30
Döring Y, Pawig L, Weber C, et al. The CXCL12/CXCR4 chemokine ligand/receptor axis in cardiovascular disease[J]. Front Physiol, 2014, 55: 212. DOI: 10.3389/fphys.2014.00212.
31
Bot I, ITMN Daissormont, Zernecke A, et al. CXCR4 blockade induces atherosclerosis by affecting neutrophil function[J]. J Mol Cell Cardiol, 2014, 7474: 44-52. DOI: 10.1016/j.yjmcc.2014.04.021.
32
Hutton BF, Braun M, Thurfjell L, et al. Image registration: an essential tool for nuclear medicine[J]. Eur J Nucl Med Mol Imaging, 2002, 2929(4): 559-577. DOI: 10.1007/s00259-001-0700-6.
33
Hyafil F, Pelisek J, Laitinen I, et al. Imaging the cytokine receptor CXCR4 in atherosclerotic plaques with the radiotracer (68)Ga-Pentixafor for PET[J]. J Nucl Med, 2017, 5858(3): 499-506. DOI: 10.2967/jnumed.116.179663.
34
Li X, Yu W, Wollenweber T, et al. [68Ga]Pentixafor PET/MR imaging of chemokine receptor 4 expression in the human carotid artery[J]. Eur J Nucl Med Mol Imaging, 2019, 4646(8): 1616-1625. DOI: 10.1007/s00259-019-04322-7.
35
Mechtouff L, Sigovan M, Costes N, et al. (18) F-NaF PET-MRI: an innovative tool to assess carotid artery plaque vulnerability[J]. Eur J Neurol, 2018, 2525(2): e18-e19. DOI: 10.1111/ene.13502.
36
Mechtouff L, Sigovan M, Douek P, et al. Simultaneous assessment of microcalcifications and morphological criteria of vulnerability in carotid artery plaque using hybrid (18)F-NaF PET/MRI[J]. J Nucl Cardiol, 2020, DOI: 10.1007/s12350-020-02400-0.
37
Cocker MS, Spence JD, Hammond R, et al. [(18)F]-NaF PET/CT identifies active calcification in carotid plaque[J]. JACC Cardiovasc Imaging, 2017, 1010(4): 486-488. DOI: 10.1016/j.jcmg.2016.03.005.
38
Dalm VA, van Hagen PM, van Koetsveld PM, et al. Expression of somatostatin, cortistatin, and somatostatin receptors in human monocytes, macrophages, and dendritic cells[J]. Am J Physiol Endocrinol Metabol, 2003, 285285(2): E344-353. DOI: 10.1152/ajpendo.00048.2003.
39
Li X, Bauer W, Kreissl MC, et al. Specific somatostatin receptor Ⅱ expression in arterial plaque: (68)Ga-DOTATATE autoradiographic, immunohistochemical and flow cytometric studies in apoE-deficient mice[J]. Atherosclerosis, 2013, 230230(1): 33-39. DOI: 10.1016/j.atherosclerosis.2013.06.018.
40
Tarkin JM, Joshi FR, Evans NR, et al. Detection of atherosclerotic inflammation by (68)Ga-DOTATATE PET Compared to [(18)F]FDG PET imaging[J]. J Am Coll Cardiol, 2017, 6969(14): 1774-1791. DOI: 10.1016/j.jacc.2017.01.060.
41
Wan MYS, Endozo R, Michopoulou S, et al. PET/CT imaging of unstable carotid plaque with (68)Ga-labeled somatostatin receptor ligand[J]. J Nucl Med, 2017, 5858(5): 774-780. DOI: 10.2967/jnumed.116.181438.
42
Bucerius J, Barthel H, Tiepolt S, et al. Feasibility of in vivo (18)F-florbetaben PET/MR imaging of human carotid amyloid-beta[J]. Eur J Nucl Med Mol Imaging, 2017, 4444(7): 1119-1128. DOI: 10.1007/s00259-017-3651-2.
43
Aizaz M, Moonen RPM, van der Pol JAJ, et al. PET/MRI of atherosclerosis[J]. Cardiovasc Diagn Ther, 2020, 1010(4): 1120-1139. DOI: 10.21037/cdt.2020.02.09.
44
Su T, Wang YB, Han D, et al. Multimodality imaging of angiogenesis in a rabbit atherosclerotic model by GEBP11 peptide targeted nanoparticles[J]. Theranostics, 2017, 77(19): 4791-4804. DOI: 10.7150/thno.20767.
45
Majmudar MD, Yoo J, Keliher EJ, et al. Polymeric nanoparticle PET/MR imaging allows macrophage detection in atherosclerotic plaques[J]. Circ Res, 2013, 112112(5): 755-761. DOI: 10.1161/CIRCRESAHA.111.300576.
46
Nie X, Laforest R, Elvington A, et al. PET/MRI of hypoxic atherosclerosis using 64Cu-ATSM in a Rabbit Model[J]. J Nucl Med, 2016, 5757(12): 2006-2011. DOI: 10.2967/jnumed.116.172544.
47
Blomberg BA, Thomassen A, Takx RA, et al. Delayed (1)(8)F-fluorodeoxyglucose PET/CT imaging improves quantitation of atherosclerotic plaque inflammation: results from the CAMONA study[J]. J Nucl Cardiol, 2014, 2121(3): 588-597. DOI: 10.1007/s12350-014-9884-6.
48
Boellaard R, Quick HH. Current image acquisition options in PET/MR[J]. Semin Nucl Med, 2015, 4545(3): 192-200. DOI: 10.1053/j.semnuclmed.2014.12.001.
49
Keereman V, Holen RV, Mollet P, et al. The effect of errors in segmented attenuation maps on PET quantification[J]. Med Phys, 2011, 3838(11): 6010-6019. DOI: 10.1118/1.3651640.
50
Rausch I, Beitzke D, Li X, et al. Accuracy of PET quantification in [(68)Ga]Ga-pentixafor PET/MR imaging of carotid plaques[J]. J Nucl Cardiol, 2020, DOI: 10.1007/s12350-020-02257-3.
51
Baradaran H, Gupta A. Carotid vessel wall imaging on CTA[J]. AJNR Am J Neuroradiol, 2020, 4141(3): 380-386. DOI: 10.3174/ajnr.A6403.
52
Høilund-Carlsen PF, Moghbel MC, Gerke O, et al. Evolving role of PET in detecting and characterizing atherosclerosis[J]. PET Clin, 2019, 1414(2): 197-209. DOI: 10.1016/j.cpet.2018.12.001.
53
Arnold JA, Modaresi KB, Thomas N, et al. Carotid plaque characterization by duplex scanning: observer error may undermine current clinical trials[J]. Stroke, 1999, 3030(1): 61-65. DOI: 10.1161/01.str.30.1.61.

PREV Research progress of DTI quantification in myelopathy
NEXT Progress in evaluation of left ventricular diastolic function by cardiac magnetic resonance
  



Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn