Multiparametric Quantitative Brain MRI in Neurological and Hepatic Forms of Wilson's Disease

. 2020 Jun ; 51 (6) : 1829-1835. [epub] 20191111

Jazyk angličtina Země Spojené státy americké Médium print-electronic

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/pmid31710776

BACKGROUND: In Wilson's disease (WD), demyelination, rarefaction, gliosis, and iron accumulation in the deep gray matter cause opposing effects on T2 -weighted MR signal. However, the degree and interplay of these changes in chronically treated WD patients has not been quantitatively studied. PURPOSE: To compare differences in brain multiparametric mapping between controls and chronically treated WD patients with neurological (neuro-WD) and hepatic (hep-WD) forms to infer the nature of residual WD neuropathology. STUDY TYPE: Cross-sectional. POPULATION/SUBJECTS: Thirty-eight WD patients (28 neuro-WD, 10 hep-WD); 26 healthy controls. FIELD STRENGTH/SEQUENCE: 3.0T: susceptibility, T2 *, T2 , T1 relaxometry; 1.5T: T2 , T1 relaxometry. ASSESSMENT: The following 3D regions of interest (ROIs) were manually segmented: globus pallidus, putamen, caudate nucleus, and thalamus. Mean bulk magnetic susceptibility, T2 *, T2 , and T1 relaxation times were calculated for each ROI. STATISTICAL TESTS: The effect of group (neuro-WD, hep-WD, controls) and age was assessed using a generalized least squares model with different variance for each ROI and quantitative parameter. A general linear hypothesis test with Tukey adjustment was used for post-hoc between-group analysis; P < 0.05 was considered significant. RESULTS: Susceptibility values were higher in all ROIs in neuro-WD compared to controls and hep-WD (P < 0.001). In basal ganglia, lower T2 and T2 * were found in neuro-WD compared to controls (P < 0.01) and hep-WD (P < 0.05) at 3.0T. Much smaller intergroup differences for T2 in basal ganglia were observed at 1.5T compared to 3.0T. In the thalamus, increased susceptibility in neuro-WD was accompanied by increased T1 at both field strengths (P < 0.001 to both groups), and an increased T2 at 1.5T only (P < 0.001 to both groups). DATA CONCLUSION: We observed significant residual brain MRI abnormalities in neuro-WD but not in hep-WD patients on chronic anticopper treatment. Patterns of changes were suggestive of iron accumulation in the basal ganglia and demyelination in the thalamus; 3.0T was more sensitive for detection of the former and 1.5T of the latter abnormality. LEVEL OF EVIDENCE: 2 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2020;51:1829-1835.

Zobrazit více v PubMed

Członkowska A, Litwin T, Dusek P, et al. Wilson disease. Nat Rev Dis Primers 2018;4:21.

Litwin T, Gromadzka G, Czlonkowska A, Golebiowski M, Poniatowska R. The effect of gender on brain MRI pathology in Wilson's disease. Metab Brain Dis 2013;28:69-75.

Zhong W, Huang Z, Tang X. A study of brain MRI characteristics and clinical features in 76 cases of Wilson's disease. J Clin Neurosci 2019;59:167-174.

Kozic DB, Petrovic I, Svetel M, Pekmezovic T, Ragaji A, Kostic VS. Reversible lesions in the brain parenchyma in Wilson's disease confirmed by magnetic resonance imaging: Earlier administration of chelating therapy can reduce the damage to the brain. Neural Regen Res 2014;9:1912-1916.

Sinha S, Taly AB, Prashanth LK, Ravishankar S, Arunodaya GR, Vasudev MK. Sequential MRI changes in Wilson's disease with de-coppering therapy: A study of 50 patients. Br J Radiol 2007;80:744-749.

Dusek P, Litwin T, Członkowska A. Neurologic impairment in Wilson disease. Ann Transl Med 2019;7(Suppl 2):S64.

Skowronska M, Litwin T, Dziezyc K, Wierzchowska A, Czlonkowska A. Does brain degeneration in Wilson disease involve not only copper but also iron accumulation? Neurol Neurochir Pol 2013;47:542-546.

Dusek P, Bahn E, Litwin T, et al. Brain iron accumulation in Wilson disease: A post mortem 7 Tesla MRI - Histopathological study. Neuropathol Appl Neurobiol 2016;43:514-532.

Fritzsch D, Reiss-Zimmermann M, Trampel R, Turner R, Hoffmann KT, Schafer A. Seven-Tesla magnetic resonance imaging in Wilson disease using quantitative susceptibility mapping for measurement of copper accumulation. Invest Radiol 2014;49:299-306.

Dusek P, Skoloudik D, Maskova J, et al. Brain iron accumulation in Wilson's disease: A longitudinal imaging case study during anticopper treatment using 7.0T MRI and transcranial sonography. J Magn Reson Imaging 2018;47:282-285.

Bartzokis G, Aravagiri M, Oldendorf WH, Mintz J, Marder SR. Field dependent transverse relaxation rate increase may be a specific measure of tissue iron stores. Magn Reson Med 1993;29:459-464.

Dezortova M, Herynek V, Krssak M, Kronerwetter C, Trattnig S, Hajek M. Two forms of iron as an intrinsic contrast agent in the basal ganglia of PKAN patients. Contrast Media Mol Imaging 2012;7:509-515.

Parker DL, Payne A, Todd N, Hadley JR. Phase reconstruction from multiple coil data using a virtual reference coil. Magn Reson Med 2014;72:563-569.

Acosta-Cabronero J, Cardenas-Blanco A, Betts MJ, et al. The whole-brain pattern of magnetic susceptibility perturbations in Parkinson's disease. Brain 2017;140:118-131.

Schofield MA, Zhu Y. Fast phase unwrapping algorithm for interferometric applications. Opt Lett 2003;28:1194-1196.

Li W, Wu B, Liu CL. Quantitative susceptibility mapping of human brain reflects spatial variation in tissue composition. Neuroimage 2011;55:1645-1656.

Liu T, Wiesnieff C, Lou M, et al. Nonlinear formulation of the magnetic field to source relationship for robust quantitative susceptibility mapping. Magn Reson Med 2013;69:467-476.

Herynek V, Wagnerova D, Hejlova I, Dezortova M, Hajek M. Changes in the brain during long-term follow-up after liver transplantation. J Magn Reson Imaging 2012;35:1332-1337.

Marqurdt D. An algorithm for least squares estimation of non-linear parameters. J Soc Ind Appl Math 1963;11:431-434.

R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2018. URL https://www.R-project.org/.

Langkammer C, Krebs N, Goessler W, et al. Quantitative MR imaging of brain iron: A postmortem validation study. Radiology 2010;257:455-462.

Hallgren B, Sourander P. The effect of age on the non-haemin iron in the human brain. J Neurochem 1958;3:41-51.

Vymazal J, Zak O, Bulte JW, Aisen P, Brooks RA. T1 and T2 of ferritin solutions: Effect of loading factor. Magn Reson Med 1996;36:61-65.

Gossuin Y, Muller RN, Gillis P. Relaxation induced by ferritin: A better understanding for an improved MRI iron quantification. NMR Biomed 2004;17:427-432.

Li G, Zhou X, Xu P, Pan X, Chen Y. Microstructure assessment of the thalamus in Wilson's disease using diffusion tensor imaging. Clin Radiol 2014;69:294-298.

Van Wassenaer-van Hall HN. Neuroimaging in Wilson disease. Metab Brain Dis 1997;12:1-19.

Uddin MN, Lebel RM, Wilman AH. Value of transverse relaxometry difference methods for iron in human brain. Magn Reson Imaging 2016;34:51-59.

Kozic D, Svetel M, Petrovic B, Dragasevic N, Semnic R, Kostic VS. MR imaging of the brain in patients with hepatic form of Wilson's disease. Eur J Neurol 2003;10:587-592.

Najít záznam

Citační ukazatele

Nahrávání dat...

Možnosti archivace

Nahrávání dat...