QSMART: Quantitative susceptibility mapping artifact reduction technique

被引:13
|
作者
Yaghmaie, Negin [1 ,2 ]
Syeda, Warda T. [3 ,4 ]
Wu, Chengchuan [1 ,2 ]
Zhang, Yicheng [1 ,2 ]
Zhang, Tracy D. [5 ]
Burrows, Emma L. [5 ]
Brodtmann, Amy [5 ]
Moffat, Bradford A. [1 ,4 ]
Wright, David K. [6 ]
Glarin, Rebecca [1 ,7 ]
Kolbe, Scott [4 ,6 ,8 ]
Johnston, Leigh A. [1 ,2 ,4 ]
机构
[1] Univ Melbourne, Melbourne Brain Ctr Imaging Unit, Melbourne, Vic, Australia
[2] Univ Melbourne, Dept Biomed Engn, Melbourne, Vic, Australia
[3] Univ Melbourne, Melbourne Neuropsychiat Ctr, Melbourne, Vic, Australia
[4] Univ Melbourne, Dept Med & Radiol, Melbourne, Vic, Australia
[5] Florey Inst Neurosci & Mental Hlth, Parkville, Vic, Australia
[6] Monash Univ, Dept Neurosci, Cent Clin Sch, Clayton, Vic, Australia
[7] Royal Melbourne Hosp, Dept Radiol, Parkville, Vic, Australia
[8] Alfred Hosp, Dept Radiol, Melbourne, Vic, Australia
关键词
Quantitative Susceptibility Mapping; Streaking artifacts; Artifact suppression; Spatially dependent filtering; Two-stage parallel inversion; PHASE UNWRAPPING ALGORITHM; MAGNETIC-SUSCEPTIBILITY; FIELD; IMAGE; DISTRIBUTIONS; IRON;
D O I
10.1016/j.neuroimage.2020.117701
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Purpose: Quantitative susceptibility mapping (QSM) is a novel MR technique that allows mapping of tissue susceptibility values from MR phase images. QSM is an ill-conditioned inverse problem, and although several methods have been proposed in the field, in the presence of a wide range of susceptibility sources, streaking artifacts appear around high susceptibility regions and contaminate the whole QSM map. QSMART is a post processing pipeline that uses two-stage parallel inversion to reduce the streaking artifacts and remove banding artifact at the cortical surface and around the vasculature. Method: Tissue and vein susceptibility values were separately estimated by generating a mask of vasculature driven from the magnitude data using a Frangi filter. Spatially dependent filtering was used for the background field removal step and the two susceptibility estimates were combined in the final QSM map. QSMART was compared to RESHARP/iLSQR and V-SHARP/iLSQR inversion in a numerical phantom, 7T in vivo single and multiple-orientation scans, 9.4T ex vivo mouse data, and 4.7T in vivo rat brain with induced focal ischemia. Results: Spatially dependent filtering showed better suppression of phase artifacts near cortex compared to RESHARP and V-SHARP, while preserving voxels located within regions of interest without brain edge erosion. QSMART showed successful reduction of streaking artifacts as well as improved contrast between different brain tissues compared to the QSM maps obtained by RESHARP/iLSQR and V-SHARP/iLSQR. Conclusion: QSMART can reduce QSM artifacts to enable more robust estimation of susceptibility values in vivo and ex vivo .
引用
收藏
页数:11
相关论文
共 50 条
  • [1] QSMxT: Robust masking and artifact reduction for quantitative susceptibility mapping
    Stewart, Ashley Wilton
    Robinson, Simon Daniel
    O'Brien, Kieran
    Jin, Jin
    Widhalm, Georg
    Hangel, Gilbert
    Walls, Angela
    Goodwin, Jonathan
    Eckstein, Korbinian
    Tourell, Monique
    Morgan, Catherine
    Narayanan, Aswin
    Barth, Markus
    Bollmann, Steffen
    MAGNETIC RESONANCE IN MEDICINE, 2022, 87 (03) : 1289 - 1300
  • [2] Streaking artifact reduction for quantitative susceptibility mapping of sources with large dynamic range
    Wei, Hongjiang
    Dibb, Russell
    Zhou, Yan
    Sun, Yawen
    Xu, Jianrong
    Wang, Nian
    Liu, Chunlei
    NMR IN BIOMEDICINE, 2015, 28 (10) : 1294 - 1303
  • [3] Mask-Adapted Background Field Removal for Artifact Reduction in Quantitative Susceptibility Mapping of the Prostate
    Straub, Sina
    Emmerich, Julian
    Schlemmer, Heinz-Peter
    Maier-Hein, Klaus H.
    Ladd, Mark E.
    Roethke, Matthias C.
    Bonekamp, David
    Laun, Frederik B.
    TOMOGRAPHY, 2017, 3 (02) : 96 - 100
  • [4] SHARQnet - Sophisticated harmonic artifact reduction in quantitative susceptibility mapping using a deep convolutional neural network
    Bollmann, Steffen
    Kristensen, Matilde Holm
    Larsen, Morten Skaarup
    Olsen, Mathias Vassard
    Pedersen, Mads Jozwiak
    Ostergaard, Lasse Riis
    O'Brien, Kieran
    Langkammer, Christian
    FazIollahi, Amir
    Barth, Markus
    ZEITSCHRIFT FUR MEDIZINISCHE PHYSIK, 2019, 29 (02): : 139 - 149
  • [5] A Method of Reduction of Artifacts of Quantitative Susceptibility Mapping
    Palamodov, V.
    SIAM JOURNAL ON IMAGING SCIENCES, 2016, 9 (01): : 481 - 489
  • [6] Background field removal technique based on non-regularized variable kernels sophisticated harmonic artifact reduction for phase data for quantitative susceptibility mapping
    Kan, Hirohito
    Arai, Nobuyuki
    Takizawa, Masahiro
    Omori, Kazuyoshi
    Kasai, Harumasa
    Kunitomo, Hiroshi
    Hirose, Yasujiro
    Shibamoto, Yuta
    MAGNETIC RESONANCE IMAGING, 2018, 52 : 94 - 101
  • [7] Technical Note: Optimization of quantitative susceptibility mapping by streaking artifact detection
    Wu, Ming-Long
    Wang, Chun-Kun
    Lin, Po-Yu
    Chao, Tzu-Cheng
    MEDICAL PHYSICS, 2020, 47 (11) : 5715 - 5722
  • [8] Single-scan quantitative T2* methods with susceptibility artifact reduction
    Franconi, Florence
    Mowat, Pierre
    Lemaire, Laurent
    Richomme, Pascal
    Le Jeune, Jean-Jacques
    NMR IN BIOMEDICINE, 2006, 19 (05) : 527 - 534
  • [9] SUSCEPTIBILITY ARTIFACT REDUCTION IN FAT-SUPPRESSION
    MAO, JT
    GAO, JH
    YAN, H
    MAGNETIC RESONANCE IN MEDICINE, 1995, 33 (04) : 582 - 587
  • [10] A DIGITAL TECHNIQUE FOR STIMULUS ARTIFACT REDUCTION
    BLOGG, T
    REID, WD
    ELECTROENCEPHALOGRAPHY AND CLINICAL NEUROPHYSIOLOGY, 1990, 76 (06): : 557 - 561