Literature DB >> 24619210

Evaluation of iron content in human cerebral cavernous malformation using quantitative susceptibility mapping.

Huan Tan1, Tian Liu, Ying Wu, Jon Thacker, Robert Shenkar, Abdul Ghani Mikati, Changbin Shi, Conner Dykstra, Yi Wang, Pottumarthi V Prasad, Robert R Edelman, Issam A Awad.   

Abstract

OBJECTIVES: The aims of this study were to investigate and validate quantitative susceptibility mapping (QSM) for lesional iron quantification in cerebral cavernous malformations (CCMs).
MATERIALS AND METHODS: Magnetic resonance imaging studies were performed in phantoms and 16 patients on a 3-T scanner. Susceptibility weighted imaging, QSM, and R2* maps were reconstructed from in vivo data acquired with a 3-dimensional, multi-echo, and T2*-weighted gradient echo sequence. Magnetic susceptibility measurements were correlated to susceptibility weighted imaging and R2* results. In addition, iron concentrations from surgically excised CCM lesion specimens were determined using inductively coupled plasma mass spectrometry and correlated with QSM measurements.
RESULTS: The QSM images demonstrated excellent image quality for depicting CCM lesions in both sporadic and familial cases. Susceptibility measurements revealed a positive linear correlation with R2* values (R(2) = 0.99 for total, R(2) = 0.69 for mean; P < 0.01). Quantitative susceptibility mapping values of known iron-rich brain regions matched closely with those of previous studies and in interobserver consistency. A strong correlation was found between QSM and the concentration of iron phantoms (0.925; P < 0.01), as well as between QSM and mass spectroscopy estimation of iron deposition (0.999 for total iron, 0.86 for iron concentration; P < 0.01) in 18 fragments of 4 excised human CCM lesion specimens.
CONCLUSIONS: The ability of QSM to evaluate iron deposition in CCM lesions was illustrated via phantom, in vivo, and ex vivo validation studies. Quantitative susceptibility mapping may be a potential biomarker for monitoring CCM disease activity and response to treatments.

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Year:  2014        PMID: 24619210      PMCID: PMC4254705          DOI: 10.1097/RLI.0000000000000043

Source DB:  PubMed          Journal:  Invest Radiol        ISSN: 0020-9996            Impact factor:   6.016


  37 in total

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2.  High resolution magnetic susceptibility mapping of the substantia nigra in Parkinson's disease.

Authors:  Ashley K Lotfipour; Samuel Wharton; Stefan T Schwarz; V Gontu; Andreas Schäfer; Andrew M Peters; Richard W Bowtell; Dorothee P Auer; Penny A Gowland; Nin P S Bajaj
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3.  Quantitative MR imaging of brain iron: a postmortem validation study.

Authors:  Christian Langkammer; Nikolaus Krebs; Walter Goessler; Eva Scheurer; Franz Ebner; Kathrin Yen; Franz Fazekas; Stefan Ropele
Journal:  Radiology       Date:  2010-09-15       Impact factor: 11.105

4.  Morphology enabled dipole inversion (MEDI) from a single-angle acquisition: comparison with COSMOS in human brain imaging.

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Journal:  Magn Reson Med       Date:  2011-04-04       Impact factor: 4.668

5.  Cerebral cavernous malformations. Incidence and familial occurrence.

Authors:  D Rigamonti; M N Hadley; B P Drayer; P C Johnson; K Hoenig-Rigamonti; J T Knight; R F Spetzler
Journal:  N Engl J Med       Date:  1988-08-11       Impact factor: 91.245

6.  Differentiation between diamagnetic and paramagnetic cerebral lesions based on magnetic susceptibility mapping.

Authors:  Ferdinand Schweser; Andreas Deistung; Berengar W Lehr; Jürgen R Reichenbach
Journal:  Med Phys       Date:  2010-10       Impact factor: 4.071

7.  A novel mouse model of cerebral cavernous malformations based on the two-hit mutation hypothesis recapitulates the human disease.

Authors:  David A McDonald; Robert Shenkar; Changbin Shi; Rebecca A Stockton; Amy L Akers; Melanie H Kucherlapati; Raju Kucherlapati; James Brainer; Mark H Ginsberg; Issam A Awad; Douglas A Marchuk
Journal:  Hum Mol Genet       Date:  2010-10-11       Impact factor: 6.150

8.  Measuring iron in the brain using quantitative susceptibility mapping and X-ray fluorescence imaging.

Authors:  Weili Zheng; Helen Nichol; Saifeng Liu; Yu-Chung N Cheng; E Mark Haacke
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9.  Establishing a baseline phase behavior in magnetic resonance imaging to determine normal vs. abnormal iron content in the brain.

Authors:  E Mark Haacke; Muhammad Ayaz; Asadullah Khan; Elena S Manova; Bharani Krishnamurthy; Lakshman Gollapalli; Carlo Ciulla; I Kim; Floyd Petersen; Wolff Kirsch
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10.  The natural history of familial cavernous malformations: results of an ongoing study.

Authors:  J M Zabramski; T M Wascher; R F Spetzler; B Johnson; J Golfinos; B P Drayer; B Brown; D Rigamonti; G Brown
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  41 in total

1.  Simultaneous quantitative susceptibility mapping (QSM) and R2* for high iron concentration quantification with 3D ultrashort echo time sequences: An echo dependence study.

Authors:  Xing Lu; Yajun Ma; Eric Y Chang; Qun He; Adam Searleman; Annette von Drygalski; Jiang Du
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Review 2.  Cavernous angiomas: deconstructing a neurosurgical disease.

Authors:  Issam A Awad; Sean P Polster
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3.  Fidelity imposed network edit (FINE) for solving ill-posed image reconstruction.

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Review 4.  Quantitative Susceptibility Mapping: Concepts and Applications.

Authors:  J R Reichenbach; F Schweser; B Serres; A Deistung
Journal:  Clin Neuroradiol       Date:  2015-07-22       Impact factor: 3.649

5.  IBEX: an open infrastructure software platform to facilitate collaborative work in radiomics.

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6.  Automated adaptive preconditioner for quantitative susceptibility mapping.

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Journal:  Magn Reson Med       Date:  2019-08-11       Impact factor: 4.668

Review 7.  Introduction to Quantitative Susceptibility Mapping and Susceptibility Weighted Imaging.

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Journal:  Br J Radiol       Date:  2019-07-26       Impact factor: 3.039

8.  Susceptibility weighted imaging and quantitative susceptibility mapping of the cerebral vasculature using ferumoxytol.

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Journal:  J Magn Reson Imaging       Date:  2017-07-21       Impact factor: 4.813

Review 9.  Cerebrovascular disorders associated with genetic lesions.

Authors:  Philipp Karschnia; Sayoko Nishimura; Angeliki Louvi
Journal:  Cell Mol Life Sci       Date:  2018-10-16       Impact factor: 9.261

10.  Clinical Integration of Automated Processing for Brain Quantitative Susceptibility Mapping: Multi-Site Reproducibility and Single-Site Robustness.

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Journal:  J Neuroimaging       Date:  2019-08-04       Impact factor: 2.486

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