Literature DB >> 26207600

Magnetic resonance susceptibility weighted imaging in neurosurgery: current applications and future perspectives.

Antonio Di Ieva1, Timothy Lam1, Paula Alcaide-Leon2, Aditya Bharatha2, Walter Montanera2, Michael D Cusimano1.   

Abstract

Susceptibility weighted imaging (SWI) is a relatively new imaging technique. Its high sensitivity to hemorrhagic components and ability to depict microvasculature by means of susceptibility effects within the veins allow for the accurate detection, grading, and monitoring of brain tumors. This imaging modality can also detect changes in blood flow to monitor stroke recovery and reveal specific subtypes of vascular malformations. In addition, small punctate lesions can be demonstrated with SWI, suggesting diffuse axonal injury, and the location of these lesions can help predict neurological outcome in patients. This imaging technique is also beneficial for applications in functional neurosurgery given its ability to clearly depict and differentiate deep midbrain nuclei and close submillimeter veins, both of which are necessary for presurgical planning of deep brain stimulation. By exploiting the magnetic susceptibilities of substances within the body, such as deoxyhemoglobin, calcium, and iron, SWI can clearly visualize the vasculature and hemorrhagic components even without the use of contrast agents. The high sensitivity of SWI relative to other imaging techniques in showing tumor vasculature and microhemorrhages suggests that it is an effective imaging modality that provides additional information not shown using conventional MRI. Despite SWI's clinical advantages, its implementation in MRI protocols is still far from consistent in clinical usage. To develop a deeper appreciation for SWI, the authors here review the clinical applications in 4 major fields of neurosurgery: neurooncology, vascular neurosurgery, neurotraumatology, and functional neurosurgery. Finally, they address the limitations of and future perspectives on SWI in neurosurgery.

Entities:  

Keywords:  AVM = arteriovenous malformation; CCM = cerebral cavernous malformation; CMB = cerebral microbleed; CVS = cortical vessel sign; DAI = diffuse axonal injury; DBS = deep brain stimulation; DWI = diffusion-weighted imaging; GBM = glioblastoma multiforme; GCS = Glasgow Coma Scale; GPe = external globus pallidus; GPi = internal GP; GRE = gradient-recalled echo; ITSS = intratumoral susceptibility signal; MRA = MR angiography; MRI; MS = multiple sclerosis; PD = proton density; PQ = percentagewise quantification; PWI = perfusion-weighted imaging; SN = substantia nigra; STN = subthalamic nucleus; SWI; SWI = susceptibility weighted imaging; TBI = traumatic brain injury; VM = vascular malformation; brain tumors; diagnostic and operative techniques; functional neurosurgery; mIP = minimum intensity projection; neuroradiology; neurotrauma; susceptibility weighted imaging; vascular neurosurgery

Mesh:

Year:  2015        PMID: 26207600     DOI: 10.3171/2015.1.JNS142349

Source DB:  PubMed          Journal:  J Neurosurg        ISSN: 0022-3085            Impact factor:   5.115


  12 in total

Review 1.  [Principles and applications of susceptibility weighted imaging].

Authors:  F T Kurz; M Freitag; H-P Schlemmer; M Bendszus; C H Ziener
Journal:  Radiologe       Date:  2016-02       Impact factor: 0.635

Review 2.  Contributions to magnetic susceptibility of brain tissue.

Authors:  Jeff H Duyn; John Schenck
Journal:  NMR Biomed       Date:  2016-05-30       Impact factor: 4.044

3.  Evaluation of vertebral body fractures using susceptibility-weighted magnetic resonance imaging.

Authors:  Sarah M Böker; Lisa C Adams; Yvonne Y Bender; Moritz Wagner; Torsten Diekhoff; Eva Fallenberg; Bernd Hamm; Marcus R Makowski
Journal:  Eur Radiol       Date:  2017-12-19       Impact factor: 5.315

4.  Acceleration of Brain Susceptibility-Weighted Imaging with Compressed Sensitivity Encoding: A Prospective Multicenter Study.

Authors:  J Ding; Y Duan; M Wang; Y Yuan; Z Zhuo; L Gan; Q Song; B Gao; L Yang; H Liu; Y Hou; F Zheng; R Chen; J Wang; L Lin; B Zhang; G Zhang; Y Liu
Journal:  AJNR Am J Neuroradiol       Date:  2022-03-03       Impact factor: 3.825

5.  Foundations of Multiparametric Brain Tumour Imaging Characterisation Using Machine Learning.

Authors:  Anne Jian; Kevin Jang; Carlo Russo; Sidong Liu; Antonio Di Ieva
Journal:  Acta Neurochir Suppl       Date:  2022

Review 6.  Brain Vascular Imaging Techniques.

Authors:  Bàrbara Laviña
Journal:  Int J Mol Sci       Date:  2016-12-30       Impact factor: 5.923

Review 7.  Advanced MRI for Pediatric Brain Tumors with Emphasis on Clinical Benefits.

Authors:  Hyun Woo Goo; Young-Shin Ra
Journal:  Korean J Radiol       Date:  2017-01-05       Impact factor: 3.500

8.  Iron deposition in substantia nigra: abnormal iron metabolism, neuroinflammatory mechanism and clinical relevance.

Authors:  Zhuo Liu; Hui-Cong Shen; Teng-Hong Lian; Lei Mao; Shou-Xian Tang; Li Sun; Xi-Yan Huang; Peng Guo; Chen-Jie Cao; Shu-Yang Yu; Li-Jun Zuo; Xiao-Min Wang; Sheng-Di Chen; Piu Chan; Wei Zhang
Journal:  Sci Rep       Date:  2017-11-02       Impact factor: 4.379

9.  Demyelination and remyelination detected in an alternative cuprizone mouse model of multiple sclerosis with 7.0 T multiparameter magnetic resonance imaging.

Authors:  Shuang Ding; Yu Guo; Xiaoya Chen; Silin Du; Yongliang Han; Zichun Yan; Qiyuan Zhu; Yongmei Li
Journal:  Sci Rep       Date:  2021-05-26       Impact factor: 4.379

Review 10.  Current approaches and advances in the imaging of stroke.

Authors:  Pragati Kakkar; Tarun Kakkar; Tufail Patankar; Sikha Saha
Journal:  Dis Model Mech       Date:  2021-12-07       Impact factor: 5.758

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