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Insights into Imaging
Published in: Insights into Imaging 1/2019

Open Access 01-12-2019 | MR Angiography | Critical Review

Diagnostic value of alternative techniques to gadolinium-based contrast agents in MR neuroimaging—a comprehensive overview

Authors: Anna Falk Delgado, Danielle Van Westen, Markus Nilsson, Linda Knutsson, Pia C. Sundgren, Elna-Marie Larsson, Alberto Falk Delgado

Published in: Insights into Imaging | Issue 1/2019

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Abstract

Gadolinium-based contrast agents (GBCAs) increase lesion detection and improve disease characterization for many cerebral pathologies investigated with MRI. These agents, introduced in the late 1980s, are in wide use today. However, some non-ionic linear GBCAs have been associated with the development of nephrogenic systemic fibrosis in patients with kidney failure. Gadolinium deposition has also been found in deep brain structures, although it is of unclear clinical relevance. Hence, new guidelines from the International Society for Magnetic Resonance in Medicine advocate cautious use of GBCA in clinical and research practice. Some linear GBCAs were restricted from use by the European Medicines Agency (EMA) in 2017.
This review focuses on non-contrast-enhanced MRI techniques that can serve as alternatives for the use of GBCAs. Clinical studies on the diagnostic performance of non-contrast-enhanced as well as contrast-enhanced MRI methods, both well established and newly proposed, were included. Advantages and disadvantages together with the diagnostic performance of each method are detailed. Non-contrast-enhanced MRIs discussed in this review are arterial spin labeling (ASL), time of flight (TOF), phase contrast (PC), diffusion-weighted imaging (DWI), magnetic resonance spectroscopy (MRS), susceptibility weighted imaging (SWI), and amide proton transfer (APT) imaging.
Ten common diseases were identified for which studies reported comparisons of non-contrast-enhanced and contrast-enhanced MRI. These specific diseases include primary brain tumors, metastases, abscess, multiple sclerosis, and vascular conditions such as aneurysm, arteriovenous malformation, arteriovenous fistula, intracranial carotid artery occlusive disease, hemorrhagic, and ischemic stroke.
In general, non-contrast-enhanced techniques showed comparable diagnostic performance to contrast-enhanced MRI for specific diagnostic questions. However, some diagnoses still require contrast-enhanced imaging for a complete examination.
Literature
1.
Runge VM, Clanton JA, Price AC, Wehr CJ, Herzer WA, Partain CL et al (1985) The use of Gd DTPA as a perfusion agent and marker of blood-brain barrier disruption. Magn Reson Imaging. 3:43–55PubMedCrossRef
2.
3.
Wang Y, Alkasab TK, Narin O, Nazarian RM, Kaewlai R, Kay J et al (2011) Incidence of nephrogenic systemic fibrosis after adoption of restrictive gadolinium-based contrast agent guidelines. Radiology 260:105–111PubMedCrossRef
4.
Bennett CL, Qureshi ZP, Sartor AO, Norris LB, Murday A, Xirasagar S et al (2012) Gadolinium-induced nephrogenic systemic fibrosis: the rise and fall of an iatrogenic disease. Clin Kidney J 5:82–88PubMedPubMedCentralCrossRef
5.
Gulani V, Calamante F, Shellock FG, Kanal E, Reeder SB (2017) Gadolinium deposition in the brain: summary of evidence and recommendations. Lancet Neurol. 16:564–570PubMedCrossRef
6.
McDonald RJ, McDonald JS, Kallmes DF, Jentoft ME, Paolini MA, Murray DL et al (2017) Gadolinium deposition in human brain tissues after contrast-enhanced mr imaging in adult patients without intracranial abnormalities. Radiology 285:546–554PubMedCrossRef
7.
Lord ML, Chettle DR, Gräfe JL, Noseworthy MD, McNeill FE (2018) Observed deposition of gadolinium in bone using a new noninvasive in vivo biomedical device: results of a small pilot feasibility study. Radiology 287:96–103PubMedCrossRef
8.
Anzalone N, Scomazzoni F, Cirillo M, Righi C, Simionato F, Cadioli M et al (2008) Follow-up of coiled cerebral aneurysms at 3T: comparison of 3D time-of-flight MR angiography and contrast-enhanced MR angiography. AJNR Am J Neuroradiol 29:1530–1536PubMedCrossRefPubMedCentral
9.
Liang L, Korogi Y, Sugahara T, Onomichi M, Shigematsu Y, Yang D et al (2001) Evaluation of the intracranial dural sinuses with a 3D contrast-enhanced MP-RAGE sequence: prospective comparison with 2D-TOF MR venography and digital subtraction angiography. AJNR Am J Neuroradiol 22:481–492PubMedPubMedCentral
10.
Morana G, Tortora D, Staglianò S, Nozza P, Mascelli S, Severino M et al (2018) Pediatric astrocytic tumor grading: comparison between arterial spin labeling and dynamic susceptibility contrast MRI perfusion. Neuroradiology 60:437–446PubMedCrossRef
11.
Smith APL, Marino M, Roberts J, Crowder JM, Castle J, Lowery L et al (2017) Clearance of gadolinium from the brain with no pathologic effect after repeated administration of gadodiamide in healthy rats: an analytical and histologic study. Radiology 282:743–751PubMedCrossRef
12.
13.
14.
Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK et al (2016) The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary. Acta Neuropathol 131:803–820PubMedCrossRef
15.
Scott JN, Brasher PMA, Sevick RJ, Rewcastle NB, Forsyth PA (2002) How often are nonenhancing supratentorial gliomas malignant? A population study. Neurology 59:947–949PubMedCrossRef
16.
Stockham AL, Tievsky AL, Koyfman SA, Reddy CA, Suh JH, Vogelbaum MA et al (2012) Conventional MRI does not reliably distinguish radiation necrosis from tumor recurrence after stereotactic radiosurgery. J Neurooncol 109:149–158PubMedCrossRef
17.
Wen PY, Macdonald DR, Reardon DA, Cloughesy TF, Gregory Sorensen A, Galanis E et al (2010) Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group. J Clin Oncol 28:1963–1972PubMedCrossRef
18.
Yu H, Lou H, Zou T, Wang X, Jiang S, Huang Z et al (2017) Applying protein-based amide proton transfer MR imaging to distinguish solitary brain metastases from glioblastoma. Eur Radiol. 27:4516–4524PubMedPubMedCentralCrossRef
19.
Lev MH, Ozsunar Y, Henson JW et al (2014). Glial tumor grading and outcome prediction using dynamic spin-echo MR susceptibility mapping compared with conventional contrast-enhanced MR: confounding effect of elevated rCBV of oligodendrogliomas [corrected]. AJNR Am J Neuroradiol. 2004;25: 214–221.
20.
Zetterling M, Roodakker KR, Berntsson SG, Edqvist P-H, Latini F, Landtblom A-M et al (2016) Extension of diffuse low-grade gliomas beyond radiological borders as shown by the coregistration of histopathological and magnetic resonance imaging data. J Neurosurg. 125:1155–1166PubMedCrossRef
21.
22.
Dai W, Garcia D, de Bazelaire C, Alsop DC (2008) Continuous flow-driven inversion for arterial spin labeling using pulsed radio frequency and gradient fields. Magn Reson Med. 60:1488–1497PubMedPubMedCentralCrossRef
23.
Edelman RR, Siewert B, Adamis M, Gaa J, Laub G, Wielopolski P (1994) Signal targeting with alternating radiofrequency (STAR) sequences: application to MR angiography. Magn Reson Med. 31:233–238PubMedCrossRef
24.
Detre JA, Alsop DC, Vives LR, Maccotta L, Teener JW, Raps EC (1998) Noninvasive MRI evaluation of cerebral blood flow in cerebrovascular disease. Neurology. 50:633–641PubMedCrossRef
25.
Alsop DC, Detre JA, Golay X, Günther M, Hendrikse J, Hernandez-Garcia L et al (2015) Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: a consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magn Reson Med. 73:102–116PubMedCrossRef
26.
Blauwblomme T, Naggara O, Brunelle F, Grévent D, Puget S, Di Rocco F et al (2015) Arterial spin labeling magnetic resonance imaging: toward noninvasive diagnosis and follow-up of pediatric brain arteriovenous malformations. J Neurosurg Pediatr. 15:451–458PubMedCrossRef
27.
Wang Y-L, Chen S, Xiao H-F, Li Y, Wang Y, Liu G et al (2018) Differentiation between radiation-induced brain injury and glioma recurrence using 3D pCASL and dynamic susceptibility contrast-enhanced perfusion-weighted imaging. Radiother Oncol. 129:68–74PubMedCrossRef
28.
Deibler AR, Pollock JM, Kraft RA, Tan H, Burdette JH, Maldjian JA (2008) Arterial spin-labeling in routine clinical practice, part 3: hyperperfusion patterns. AJNR Am J Neuroradiol. 29:1428–1435PubMedPubMedCentralCrossRef
29.
Nishimura DG, Macovski A, Pauly JM, Conolly SM (1987) MR angiography by selective inversion recovery. Magn Reson Med 4:193–202.PubMedCrossRef
30.
Kemmling A, Noelte I, Gerigk L, Singer S, Groden C, Scharf J (2008) A diagnostic pitfall for intracranial aneurysms in time-of-flight MR angiography: small intracranial lipomas. AJR Am J Roentgenol. 190:W62–W67PubMedCrossRef
31.
Leach JL, Fortuna RB, Jones BV, Gaskill-Shipley MF (2006) Imaging of cerebral venous thrombosis: current techniques, spectrum of findings, and diagnostic pitfalls. Radiographics 26 Suppl 1:S19–S41 discussion S42–3PubMedCrossRef
32.
Pernicone JR, Siebert JE, Potchen EJ, Pera A, Dumoulin CL, Souza SP (1990) Three-dimensional phase-contrast MR angiography in the head and neck: preliminary report. AJR Am J Roentgenol. 155:167–176PubMedCrossRef
33.
34.
Hagmann P, Jonasson L, Deffieux T, Meuli R, Thiran J-P, Wedeen VJ (2006) Fibertract segmentation in position orientation space from high angular resolution diffusion MRI. Neuroimage. 32:665–675PubMedCrossRef
35.
Liu C, Bammer R, Acar B, Moseley ME (2004) Characterizing non-Gaussian diffusion by using generalized diffusion tensors. Magn Reson Med. 51:924–937PubMedCrossRef
36.
37.
Kim DY, Kim HS, Goh MJ, Choi CG, Kim SJ (2014) Utility of intravoxel incoherent motion MR imaging for distinguishing recurrent metastatic tumor from treatment effect following gamma knife radiosurgery: initial experience. AJNR Am J Neuroradiol 35:2082–2090PubMedCrossRefPubMedCentral
38.
Le Bihan D, Breton E, Lallemand D, Aubin ML, Vignaud J, Laval-Jeantet M (1988) Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology. 168:497–505PubMedCrossRef
39.
Heit JJ, Wintermark M, Martin BW, Zhu G, Marks MP, Zaharchuk G et al (2018) Reduced intravoxel incoherent motion microvascular perfusion predicts delayed cerebral ischemia and vasospasm after aneurysm rupture. Stroke. 49:741–745PubMedCrossRef
40.
41.
Yamashita K, Hiwatashi A, Togao O, Kikuchi K, Kitamura Y, Mizoguchi M et al (2016) Diagnostic utility of intravoxel incoherent motion MR imaging in differentiating primary central nervous system lymphoma from glioblastoma multiforme. J Magn Reson Imaging. 44:1256–1261PubMedCrossRef
42.
Le Bihan D, Breton E, Lallemand D, Grenier P, Cabanis E, Laval-Jeantet M (1986) MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology. 161:401–407PubMedCrossRef
43.
Roberts TPL, Rowley HA (2003) Diffusion weighted magnetic resonance imaging in stroke. Eur J Radiol. 45:185–194PubMedCrossRef
44.
45.
Bottomley PA, Hart HR, Edelstein WA, Schenck JF, Smith LS, Leue WM et al (1983) NMR imaging/spectroscopy system to study both anatomy and metabolism. Lancet. 2:273–274PubMedCrossRef
46.
Burtscher IM, Holtås S (2001) Proton MR spectroscopy in clinical routine. J Magn Reson Imaging. 13:560–567PubMedCrossRef
47.
48.
Schneider JF (2016) MR spectroscopy in children: protocols and pitfalls in non-tumorous brain pathology. Pediatr Radiol. 46:963–982PubMedCrossRef
49.
Reichenbach JR, Essig M, Haacke EM, Lee BC, Przetak C, Kaiser WA et al (1998) High-resolution venography of the brain using magnetic resonance imaging. MAGMA. 6:62–69PubMedCrossRef
50.
51.
Soman S, Holdsworth SJ, Barnes PD, Rosenberg J, Andre JB, Bammer R et al (2013) Improved T2* imaging without increase in scan time: SWI processing of 2D gradient echo. AJNR Am J Neuroradiol. 34:2092–2097PubMedCrossRefPubMedCentral
52.
53.
Zhou J, Payen J-F, Wilson DA, Traystman RJ, van Zijl PCM (2003) Using the amide proton signals of intracellular proteins and peptides to detect pH effects in MRI. Nat Med. 9:1085–1090PubMedCrossRef
54.
Ward KM, Aletras AH, Balaban RS (2000) A new class of contrast agents for mri based on proton chemical exchange dependent saturation transfer (CEST). J Magn Reson. 143:79–87PubMedCrossRef
55.
Zhou J, Heo HY, Knutsson L, van Zijl PCM, Jiang S (2019) APT-weighted MRI: Techniques, current neuro applications, and challenging issues. J Magn Reson Imaging. 50:347-364PubMedCrossRef
56.
Kamimura K, Nakajo M, Yoneyama T, Takumi K, Kumagae Y, Fukukura Y et al (2019) Amide proton transfer imaging of tumors: theory, clinical applications, pitfalls, and future directions. Jpn J Radiol. 37:109–116PubMedCrossRef
57.
Thomalla G, Simonsen CZ, Boutitie F, Andersen G, Berthezene Y, Cheng B et al (2018) MRI-guided thrombolysis for stroke with unknown time of onset. N Engl J Med. 379:611–622PubMedCrossRef
58.
Luo G, Mo D, Tong X, Liebeskind DS, Song L, Ma N et al (2018) Factors associated with 90-day outcomes of patients with acute posterior circulation stroke treated by mechanical thrombectomy. World Neurosurg. 109:e318–e328PubMedCrossRef
59.
Bivard A, Krishnamurthy V, Stanwell P, Levi C, Spratt NJ, Davis S et al (2014) Arterial spin labeling versus bolus-tracking perfusion in hyperacute stroke. Stroke. 45:127–133PubMedCrossRef
60.
Yu S, Ma SJ, Liebeskind DS, Yu D, Li N, Qiao XJ et al (2018) ASPECTS-based reperfusion status on arterial spin labeling is associated with clinical outcome in acute ischemic stroke patients. J Cereb Blood Flow Metab. 38:382–392PubMedCrossRef
61.
Park M-G, Yoon CH, Baik SK, Park K-P (2015) Susceptibility vessel sign for intra-arterial thrombus in acute posterior cerebral artery infarction. J Stroke Cerebrovasc Dis. 24:1229–1234PubMedCrossRef
62.
Radbruch A, Mucke J, Schweser F, Deistung A, Ringleb PA, Ziener CH et al (2013) Comparison of susceptibility weighted imaging and TOF-angiography for the detection of Thrombi in acute stroke. PLoS One. 8:e63459PubMedPubMedCentralCrossRef
63.
64.
Hodel J, Leclerc X, Kalsoum E, Zuber M, Tamazyan R, Benadjaoud MA et al (2017) Intracranial arteriovenous shunting: detection with arterial spin-labeling and susceptibility-weighted imaging combined. AJNR Am J Neuroradiol. 38:71–76PubMedCrossRefPubMedCentral
65.
Jensen-Kondering U, Lindner T, van Osch MJP, Rohr A, Jansen O, Helle M (2015) Superselective pseudo-continuous arterial spin labeling angiography. Eur J Radiol. 84:1758–1767PubMedCrossRef
66.
Sunwoo L, Sohn C-H, Lee JY, Yi KS, Yun TJ, Choi SH et al (2015) Evaluation of the degree of arteriovenous shunting in intracranial arteriovenous malformations using pseudo-continuous arterial spin labeling magnetic resonance imaging. Neuroradiology. 57:775–782PubMedCrossRef
67.
Kodera T, Arai Y, Arishima H, Higashino Y, Isozaki M, Tsunetoshi K et al (2017) Evaluation of obliteration of arteriovenous malformations after stereotactic radiosurgery with arterial spin labeling MR imaging. Br J Neurosurg. 31:641–647PubMedCrossRef
68.
Nabavizadeh SA, Edgar JC, Vossough A (2014) Utility of susceptibility-weighted imaging and arterial spin perfusion imaging in pediatric brain arteriovenous shunting. Neuroradiology. 56:877–884PubMedCrossRef
69.
Iryo Y, Hirai T, Kai Y, Nakamura M, Shigematsu Y, Kitajima M et al (2014) Intracranial dural arteriovenous fistulas: evaluation with 3-T four-dimensional MR angiography using arterial spin labeling. Radiology. 271:193–199PubMedCrossRef
70.
71.
Amukotuwa SA, Heit JJ, Marks MP, Fischbein N, Bammer R (2016) Detection of cortical venous drainage and determination of the Borden type of dural arteriovenous fistula by means of 3D pseudocontinuous arterial spin-labeling MRI. AJR Am J Roentgenol. 207:163–169PubMedCrossRef
72.
Edjlali M, Roca P, Rabrait C, Trystram D, Rodriguez-Régent C, Johnson KM et al (2014) MR selective flow-tracking cartography: a postprocessing procedure applied to four-dimensional flow MR imaging for complete characterization of cranial dural arteriovenous fistulas. Radiology. 270:261–268PubMedCrossRef
73.
Clark Z, Johnson KM, Wu Y, Edjlali M, Mistretta C, Wieben O et al (2016) Accelerated time-resolved contrast-enhanced magnetic resonance angiography of dural arteriovenous fistulas using highly constrained reconstruction of sparse cerebrovascular data sets. Invest Radiol. 51:365–371PubMedPubMedCentralCrossRef
74.
Hiratsuka Y, Miki H, Kiriyama I, Kikuchi K, Takahashi S, Matsubara I et al (2008) Diagnosis of unruptured intracranial aneurysms: 3T MR angiography versus 64-channel multi-detector row CT angiography. Magn Reson Med Sci. 7:169–178PubMedCrossRef
75.
Hirai T, Korogi Y, Arimura H, Katsuragawa S, Kitajima M, Yamura M et al (2005) Intracranial aneurysms at MR angiography: effect of computer-aided diagnosis on radiologists’ detection performance. Radiology. 237:605–610PubMedCrossRef
76.
Chng SM, Petersen ET, Zimine I, Sitoh Y-Y, Lim CCT, Golay X (2008) Territorial arterial spin labeling in the assessment of collateral circulation: comparison with digital subtraction angiography. Stroke. 39:3248–3254PubMedCrossRef
77.
Iryo Y, Hirai T, Nakamura M, Inoue Y, Watanabe M, Ando Y et al (2015) Collateral circulation via the circle of Willis in patients with carotid artery steno-occlusive disease: evaluation on 3-T 4D MRA using arterial spin labelling. Clin Radiol. 70:960–965PubMedCrossRef
78.
Ito K, Sasaki M, Kobayashi M, Ogasawara K, Nishihara T, Takahashi T et al (2014) Noninvasive evaluation of collateral blood flow through circle of willis in cervical carotid stenosis using selective magnetic resonance angiography. J Stroke Cerebrovasc Dis. 23:1019–1023PubMedCrossRef
79.
Uchino H, Ito M, Fujima N, Kazumata K, Yamazaki K, Nakayama N et al (2015) A novel application of four-dimensional magnetic resonance angiography using an arterial spin labeling technique for noninvasive diagnosis of moyamoya disease. Clin Neurol Neurosurg. 137:105–111PubMedCrossRef
80.
Sugino T, Mikami T, Miyata K, Suzuki K, Houkin K, Mikuni N (2013) Arterial spin-labeling magnetic resonance imaging after revascularization of moyamoya disease. J Stroke Cerebrovasc Dis. 22:811–816PubMedCrossRef
81.
Noguchi T, Kawashima M, Nishihara M, Egashira Y, Azama S, Irie H (2015) Noninvasive method for mapping CVR in moyamoya disease using ASL-MRI. Eur J Radiol. 84:1137–1143PubMedCrossRef
82.
Lee S, Yun TJ, Yoo R-E, Yoon B-W, Kang KM, Choi SH et al (2018) Monitoring cerebral perfusion changes after revascularization in patients with moyamoya disease by using arterial spin-labeling MR imaging. Radiology. 170509
83.
Expert Panel on Neurologic Imaging, Salmela MB, Mortazavi S, Jagadeesan BD, Broderick DF, Burns J et al (2017) ACR appropriateness criteria cerebrovascular disease. J Am Coll Radiol. 14:S34–S61CrossRef
84.
Ferro JM, Bousser M-G, Canhão P, Coutinho JM, Crassard I, Dentali F et al (2017) European Stroke Organization guideline for the diagnosis and treatment of cerebral venous thrombosis - endorsed by the European Academy of Neurology. Eur J Neurol. 24:1203–1213PubMedCrossRef
85.
Niu P-P, Yu Y, Guo Z-N, Jin H, Liu Y, Zhou H-W et al (2016) Diagnosis of non-acute cerebral venous thrombosis with 3D T1-weighted black blood sequence at 3T. J Neurol Sci. 367:46–50PubMedCrossRef
86.
Renard D, Le Bars E, Arquizan C, Gaillard N, de Champfleur NM, Mourand I (2017) Time-of-flight MR angiography in cerebral venous sinus thrombosis. Acta Neurol Belg 117:837–840PubMedCrossRef
87.
Ozturk K, Soylu E, Parlak M (2018) Dural venous sinus thrombosis: The combination of noncontrast CT, MRI and PC-MR venography to enhance accuracy. Neuroradiol J. 1971400918781969
88.
Tubridy N, Molyneux PD, Moseley IF, Miller DH (1999) The sensitivity of thin-slice fast spin echo, fast FLAIR and gadolinium-enhanced T1-weighted MRI sequences in detecting new lesion activity in multiple sclerosis. J Neurol 246:1181–1185PubMedCrossRef
89.
Thompson AJ, Banwell BL, Barkhof F, Carroll WM, Coetzee T, Comi G et al (2018) Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol 17:162–173PubMedCrossRef
90.
Geraldes R, Ciccarelli O, Barkhof F, De Stefano N, Enzinger C, Filippi M et al (2018) The current role of MRI in differentiating multiple sclerosis from its imaging mimics. Nat Rev Neurol 14:213PubMedCrossRef
91.
Traboulsee A, Simon JH, Stone L, Fisher E, Jones DE, Malhotra A et al (2016) Revised recommendations of the consortium of MS centers task force for a standardized mri protocol and clinical guidelines for the diagnosis and follow-up of multiple sclerosis. AJNR Am J Neuroradiol 37:394–401PubMedCrossRefPubMedCentral
92.
Held U, Heigenhauser L, Shang C, Kappos L, Polman C, Sylvia Lawry Centre for MS Research (2005) Predictors of relapse rate in MS clinical trials. Neurology. 65:1769–1773PubMedCrossRef
93.
Daumer M, Neuhaus A, Morrissey S, Hintzen R, Ebers GC (2009) MRI as an outcome in multiple sclerosis clinical trials. Neurology. 72:705–711PubMedCrossRef
94.
Shinohara RT, Goldsmith J, Mateen FJ, Crainiceanu C, Reich DS (2012) Predicting breakdown of the blood-brain barrier in multiple sclerosis without contrast agents. AJNR Am J Neuroradiol. 33:1586–1590PubMedPubMedCentralCrossRef
95.
Barkhof F, Held U, Simon JH, Daumer M, Fazekas F, Filippi M et al (2005) Predicting gadolinium enhancement status in MS patients eligible for randomized clinical trials. Neurology. 65:1447–1454PubMedCrossRef
96.
Gupta A, Al-Dasuqi K, Xia F, Askin G, Zhao Y, Delgado D et al (2017) The use of noncontrast quantitative MRI to detect gadolinium-enhancing multiple sclerosis brain lesions: a systematic review and meta-analysis. AJNR Am J Neuroradiol. 38:1317–1322PubMedPubMedCentralCrossRef
97.
Michoux N, Guillet A, Rommel D, Mazzamuto G, Sindic C, Duprez T (2015) Texture analysis of T2-weighted MR images to assess acute inflammation in brain MS lesions. PLoS One. 10:e0145497PubMedPubMedCentralCrossRef
98.
Jurcoane A, Wagner M, Schmidt C, Mayer C, Gracien R-M, Hirschmann M et al (2013) Within-lesion differences in quantitative MRI parameters predict contrast enhancement in multiple sclerosis. J Magn Reson Imaging. 38:1454–1461PubMedCrossRef
99.
Popescu V, Agosta F, Hulst HE, Sluimer IC, Knol DL, Sormani MP et al (2013) Brain atrophy and lesion load predict long term disability in multiple sclerosis. J Neurol Neurosurg Psychiatry. 84:1082–1091PubMedCrossRef
100.
Brex PA, Ciccarelli O, O’Riordan JI, Sailer M, Thompson AJ, Miller DH (2002) A longitudinal study of abnormalities on MRI and disability from multiple sclerosis. N Engl J Med. 346:158–164PubMedCrossRef
101.
Granberg T, Uppman M, Hashim F, Cananau C, Nordin LE, Shams S et al (2016) Clinical feasibility of synthetic MRI in multiple sclerosis: a diagnostic and volumetric validation study. AJNR Am J Neuroradiol. 37:1023–1029PubMedCrossRefPubMedCentral
102.
Berry I, Brant-Zawadzki M, Osaki L, Brasch R, Murovic J, Newton TH (1986) Gd-DTPA in clinical MR of the brain: 2. Extraaxial lesions and normal structures. AJR Am J Roentgenol. 147:1231–1235PubMedCrossRef
103.
104.
Verburg N, Hoefnagels FWA, Barkhof F, Boellaard R, Goldman S, Guo J et al (2017) Diagnostic accuracy of neuroimaging to delineate diffuse gliomas within the brain: a meta-analysis. AJNR Am J Neuroradiol. 38:1884–1891PubMedCrossRefPubMedCentral
105.
Boonzaier NR, Larkin TJ, Matys T, van der Hoorn A, Yan J-L, Price SJ (2017) Multiparametric MR imaging of diffusion and perfusion in contrast-enhancing and nonenhancing components in patients with glioblastoma. Radiology. 284:180–190PubMedCrossRef
106.
Goebell E, Paustenbach S, Vaeterlein O, Ding X-Q, Heese O, Fiehler J et al (2006) Low-grade and anaplastic gliomas: differences in architecture evaluated with diffusion-tensor MR imaging. Radiology. 239:217–222PubMedCrossRef
107.
Lu S, Ahn D, Johnson G, Law M, Zagzag D, Grossman RI (2004) Diffusion-tensor MR imaging of intracranial neoplasia and associated peritumoral edema: introduction of the tumor infiltration index. Radiology. 232:221–228PubMedCrossRef
108.
109.
Tomura N, Narita K, Takahashi S, Otani T, Sakuma I, Yasuda K et al (2007) Contrast-enhanced multi-shot echo-planar FLAIR in the depiction of metastatic tumors of the brain: comparison with contrast-enhanced spin-echo T1-weighted imaging. Acta radiol 48:1032–1037PubMedCrossRef
110.
Ahn SJ, Chung T-S, Chang J-H, Lee S-K (2014) The added value of double dose gadolinium enhanced 3D T2 fluid-attenuated inversion recovery for evaluating small brain metastases. Yonsei Med J. 55:1231–1237PubMedPubMedCentralCrossRef
111.
Chamberlain M, Junck L, Brandsma D, Soffietti R, Rudà R, Raizer J et al (2017) Leptomeningeal metastases: a RANO proposal for response criteria. Neuro Oncol 19:484–492PubMedCrossRef
112.
Rodriguez Gutierrez D, Awwad A, Meijer L, Manita M, Jaspan T, Dineen RA et al (2014) Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors. AJNR Am J Neuroradiol 35:1009–1015PubMedCrossRefPubMedCentral
113.
Fetit AE, Novak J, Peet AC, Arvanitits TN (2015) Three-dimensional textural features of conventional MRI improve diagnostic classification of childhood brain tumours. NMR Biomed. 28:1174–1184PubMedCrossRef
114.
Ko CC, Tai MH, Li CF, Chen TY, Chen JH, Shu G et al (2016) Differentiation between glioblastoma multiforme and primary cerebral lymphoma: additional benefits of quantitative diffusion-weighted MR imaging. PLoS One. 11:e0162565PubMedPubMedCentralCrossRef
115.
116.
Vallée A, Guillevin C, Wager M, Delwail V, Guillevin R, Vallée J-N (2018) Added value of spectroscopy to perfusion MRI in the differential diagnostic performance of common malignant brain tumors. AJNR Am J Neuroradiol. https://​doi.​org/​10.​3174/​ajnr.​A5725
117.
Sunwoo L, Yun TJ, You S-H, Yoo R-E, Kang KM, Choi SH et al (2016) Differentiation of glioblastoma from brain metastasis: qualitative and quantitative analysis using arterial spin labeling MR imaging. PLoS One 11:e0166662PubMedPubMedCentralCrossRef
118.
Badve C, Yu A, Dastmalchian S, Rogers M, Ma D, Jiang Y et al (2017) MR fingerprinting of adult brain tumors: initial experience. AJNR Am J Neuroradiol. 38:492–499PubMedCrossRefPubMedCentral
119.
Tan Y, Wang X-C, Zhang H, Wang J, Qin J-B, Wu X-F et al (2015) Differentiation of high-grade-astrocytomas from solitary-brain-metastases: comparing diffusion kurtosis imaging and diffusion tensor imaging. Eur J Radiol 84:2618–2624PubMedCrossRef
120.
Neska-Matuszewska M, Bladowska J, Sąsiadek M, Zimny A (2018) Differentiation of glioblastoma multiforme, metastases and primary central nervous system lymphomas using multiparametric perfusion and diffusion MR imaging of a tumor core and a peritumoral zone-Searching for a practical approach. PLoS One. 13:e0191341PubMedPubMedCentralCrossRef
121.
Sakata A, Fushimi Y, Okada T, Arakawa Y, Kunieda T, Minamiguchi S et al (2017) Diagnostic performance between contrast enhancement, proton MR spectroscopy, and amide proton transfer imaging in patients with brain tumors. J Magn Reson Imaging. 46:732–739PubMedCrossRef
122.
Usinskiene J, Ulyte A, Bjørnerud A, Venius J, Katsaros VK, Rynkeviciene R et al (2016) Optimal differentiation of high- and low-grade glioma and metastasis: a meta-analysis of perfusion, diffusion, and spectroscopy metrics. Neuroradiology. 58:339–350PubMedCrossRef
123.
Park JE, Kim HS, Park KJ, Choi CG, Kim SJ (2015) Histogram analysis of amide proton transfer imaging to identify contrast-enhancing low-grade brain tumor that mimics high-grade tumor: increased accuracy of MR perfusion. Radiology. 277:151–161PubMedCrossRef
124.
Falk Delgado A, Nilsson M, van Westen D, Falk Delgado A (2018) Glioma grade discrimination with MR diffusion kurtosis imaging: a meta-analysis of diagnostic accuracy. Radiology. 287:119–127PubMedCrossRef
125.
Hu Y-C, Yan L-F, Wu L, Du P, Chen B-Y, Wang L et al (2014) Intravoxel incoherent motion diffusion-weighted MR imaging of gliomas: efficacy in preoperative grading. Sci Rep. 4:7208PubMedPubMedCentralCrossRef
126.
Lin NU, Lee EQ, Aoyama H, Barani IJ, Barboriak DP, Baumert BG et al (2015) Response assessment criteria for brain metastases: proposal from the RANO group. Lancet Oncol. 16:e270–e278PubMedCrossRef
127.
Park JE, Kim HS, Park KJ, Kim SJ, Kim JH, Smith SA (2016) Pre- and posttreatment glioma: comparison of amide proton transfer imaging with MR spectroscopy for biomarkers of tumor proliferation. Radiology. 278:514–523PubMedCrossRef
128.
Park KJ, Kim HS, Park JE, Shim WH, Kim SJ, Smith SA (2016) Added value of amide proton transfer imaging to conventional and perfusion MR imaging for evaluating the treatment response of newly diagnosed glioblastoma. Eur Radiol. 26:4390–4403PubMedCrossRef
129.
Wang S, Martinez-Lage M, Sakai Y, Chawla S, Kim SG, Alonso-Basanta M et al (2016) Differentiating tumor progression from pseudoprogression in patients with glioblastomas using diffusion tensor imaging and dynamic susceptibility contrast MRI. AJNR Am J Neuroradiol. 37:28–36PubMedCrossRefPubMedCentral
130.
Fink JR, Carr RB, Matsusue E, Iyer RS, Rockhill JK, Haynor DR et al (2012) Comparison of 3 Tesla proton MR spectroscopy, MR perfusion and MR diffusion for distinguishing glioma recurrence from posttreatment effects. J Magn Reson Imaging. 35:56–63PubMedCrossRef
131.
Lescher S, Jurcoane A, Veit A, Bähr O, Deichmann R, Hattingen E (2015) Quantitative T1 and T2 mapping in recurrent glioblastomas under bevacizumab: earlier detection of tumor progression compared to conventional MRI. Neuroradiology. 57:11–20PubMedCrossRef
132.
Tiwari P, Prasanna P, Wolansky L, Pinho M, Cohen M, Nayate AP et al (2016) Computer-extracted texture features to distinguish cerebral radionecrosis from recurrent brain tumors on multiparametric MRI: a feasibility study. AJNR Am J Neuroradiol. 37:2231–2236PubMedPubMedCentralCrossRef
133.
Weybright P, Maly P, Gomez-Hassan D, Blaesing C, Sundgren PC (2004) MR spectroscopy in the evaluation of recurrent contrast-enhancing lesions in the posterior fossa after tumor treatment. Neuroradiology. 46:541–549PubMedCrossRef
134.
Kimura T, Sako K, Tanaka K, Gotoh T, Yoshida H, Aburano T et al (2004) Evaluation of the response of metastatic brain tumors to stereotactic radiosurgery by proton magnetic resonance spectroscopy, 201TlCl single-photon emission computerized tomography, and gadolinium-enhanced magnetic resonance imaging. J Neurosurg 100:835–841PubMedCrossRef
135.
Zeng Q-S, Li C-F, Zhang K, Liu H, Kang X-S, Zhen J-H (2007) Multivoxel 3D proton MR spectroscopy in the distinction of recurrent glioma from radiation injury. J Neurooncol. 84:63–69PubMedCrossRef
136.
Schlemmer HP, Bachert P, Herfarth KK, Zuna I, Debus J, van Kaick G (2001) Proton MR spectroscopic evaluation of suspicious brain lesions after stereotactic radiotherapy. AJNR Am J Neuroradiol. 22:1316–1324PubMedPubMedCentral
137.
Calmon R, Puget S, Varlet P, Dangouloff-Ros V, Blauwblomme T, Beccaria K et al (2018) Cerebral blood flow changes after radiation therapy identifies pseudoprogression in diffuse intrinsic pontine gliomas. Neuro Oncol. 20:994–1002PubMedCrossRef
138.
Suh CH, Kim HS, Jung SC, Choi CG, Kim SJ (2018) Multiparametric MRI as a potential surrogate endpoint for decision-making in early treatment response following concurrent chemoradiotherapy in patients with newly diagnosed glioblastoma: a systematic review and meta-analysis. Eur Radiol 28:2628–2638. https://​doi.​org/​10.​1007/​s00330-017-5262-5 PubMedCrossRef
139.
Nadal Desbarats L, Herlidou S, de Marco G, Gondry-Jouet C, Le Gars D, Deramond H et al (2003) Differential MRI diagnosis between brain abscesses and necrotic or cystic brain tumors using the apparent diffusion coefficient and normalized diffusion-weighted images. Magn Reson Imaging. 21:645–650PubMedCrossRef
140.
Fertikh D, Krejza J, Cunqueiro A, Danish S, Alokaili R, Melhem ER (2007) Discrimination of capsular stage brain abscesses from necrotic or cystic neoplasms using diffusion-weighted magnetic resonance imaging. J Neurosurg 106:76–81PubMedCrossRef
141.
Splendiani A, Puglielli E, De Amicis R, Necozione S, Masciocchi C, Gallucci M (2005) Contrast-enhanced FLAIR in the early diagnosis of infectious meningitis. Neuroradiology. 47:591–598PubMedCrossRef
142.
Fukuoka H, Hirai T, Okuda T, Shigematsu Y, Sasao A, Kimura E et al (2010) Comparison of the added value of contrast-enhanced 3D fluid-attenuated inversion recovery and magnetization-prepared rapid acquisition of gradient echo sequences in relation to conventional postcontrast T1-weighted images for the evaluation of leptomeningeal diseases at 3T. AJNR Am J Neuroradiol. 31:868–873PubMedCrossRefPubMedCentral
143.
Hong JT, Son BC, Sung JH, Kim IS, Yang SH, Lee SW et al (2008) Significance of diffusion-weighted imaging and apparent diffusion coefficient maps for the evaluation of pyogenic ventriculitis. Clin Neurol Neurosurg. 110:137–144PubMedCrossRef
144.
Miki Y, Isoda H, Togashi K (2009) Guideline to use gadolinium-based contrast agents at Kyoto University Hospital. J Magn Reson Imaging30:1364–1365.PubMedCrossRef
145.
Schieda N, Blaichman JI, Costa AF et al (2018) Gadolinium-based contrast agents in kidney disease: a comprehensive review and clinical practice guideline issued by the Canadian Association of Radiologists. Can J Kidney Health Dis 5:2054358118778573.CrossRef
146.
Costa AF, van der Pol CB, Maralani PJ, McInnes MDF, Shewchuk JR, Verma R et al (2018) Gadolinium deposition in the brain: a systematic review of existing guidelines and policy statement issued by the Canadian Association of Radiologists. Can Assoc Radiol J. 69:373–382PubMedCrossRef
147.
148.
149.
Hopewell S, Clarke M, Stewart L, Tierney J (2007) Time to publication for results of clinical trials. Cochrane Database Syst Rev 18;(2):MR000011.
150.
Ray JG, Vermeulen MJ, Bharatha A, Montanera WJ, Park AL (2016) Association between MRI exposure during pregnancy and fetal and childhood outcomes. JAMA. 316:952–961PubMedCrossRef
Metadata
Title
Diagnostic value of alternative techniques to gadolinium-based contrast agents in MR neuroimaging—a comprehensive overview
Authors
Anna Falk Delgado
Danielle Van Westen
Markus Nilsson
Linda Knutsson
Pia C. Sundgren
Elna-Marie Larsson
Alberto Falk Delgado
Publication date
01-12-2019
Publisher
Springer Berlin Heidelberg
Published in
Insights into Imaging / Issue 1/2019
Electronic ISSN: 1869-4101
DOI
https://doi.org/10.1186/s13244-019-0771-1

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