Quantification of cerebral perfusion using dynamic quantitative susceptibility mapping

Magnetic Resonance Imaging

Spincemaille

Liu

et al. 2017

Self Cite

234

199

Quantitative susceptibility mapping (QSM) has enabled MRI of tissue magnetic susceptibility to advance from simple qualitative detection of hypointense blooming artifacts to precise quantitative measurement of spatial biodistributions. QSM technology may be regarded to be sufficiently developed and validated to warrant wide dissemination for clinical applications of imaging isotropic susceptibility, which is dominated by metals in tissue, including iron and calcium. These biometals are highly regulated as vital participants in normal cellular biochemistry, and their dysregulations are manifested in a variety of pathologic processes. Therefore, QSM can be used to assess important tissue functions and disease. To facilitate QSM clinical translation, this review aims to organize pertinent information for implementing a robust automated QSM technique in routine MRI practice and to summarize available knowledge on diseases for which QSM can be used to improve patient care. In brief, QSM can be generated with postprocessing whenever gradient echo MRI is performed. QSM can be useful for diseases that involve neurodegeneration, inflammation, hemorrhage, abnormal oxygen consumption, substantial alterations in highly paramagnetic cellular iron, bone mineralization, or pathologic calcification; and for all disorders in which MRI diagnosis or surveillance requires contrast agent injection. Clinicians may consider integrating QSM into their routine imaging practices by including gradient echo sequences in all relevant MRI protocols.

Section: Clinical Applications Enabled By Qsm Biometal Imagingmentioning

confidence: 99%

Clinical quantitative susceptibility mapping (QSM): Biometal imaging and its emerging roles in patient care

Magnetic Resonance Imaging

Spincemaille

Liu

et al. 2017

Self Cite

234

199

“…As has been shown, the R2* and susceptibility contrast in the white matter and grey matter are mainly contributed by the myelin and iron respectively, which are important biomarker for studying the brain’s development and neurological disorders. They have been applied in a variety of studies including ageing678, functional study9, perfusion10, Parkinson disease11, Alzheimer disease12, calcification13, multiple sclerosis1415, etc.…”

mentioning

confidence: 99%

Stability of R2* and quantitative susceptibility mapping of the brain tissue in a large scale multi-center study

Xie

Zhai

et al. 2017

Sci Rep

Multi-center studies are advantageous for enrolling participants of varying pathological and demographical conditions, and especially in neurological studies. Hence stability of the obtained quantitative R2* and susceptibility in multicenter studies is a key issue for their widespread applications. In this work, the stabilities of simultaneously obtained R2* and susceptibility are investigated and compared across 10 sites that are equipped with the same scanner and receiver coil, the same post-processing process was used to achieve consistent experiment setup. Two healthy adult volunteers (one male and female) participated in this study. High intraclass correlation coefficient was obtained for both susceptibility (0.94) and R2* (0.96). The coefficients of variance for all measurements obtained were smaller than 0.1, the largest variations of measurements in all the chosen ROIs fall within ±20% from the median value. Higher level of stability was obtained in R2* as compared to susceptibility at 1 mm resolution (P < 0.05) and at 1.5 mm (P < 0.01).

“…Based on its intrinsic characters, QSMs have found its power in differentiating diamagnetic calcification from paramagnetic materials [7, 39], quantifying the deoxyhemoglobin concentration [9, 12], depicting the deep brain structure [40], quantifying contrast agent concentration [41], characterizing white matter fiber tracks, and so forth [1–4, 42]. The potential clinical usefulness of QSM also has been shown in multiple sclerosis [6, 43], lupus erythematosus [44], Alzheimer's disease [45], Parkinson's disease [46], multifocal leukoencephalopathy [47], cerebral perfusion [41], hemorrhage [9, 48], function MRI [12, 42] in brain, and some applications in aorta, breast, extremity, kidney, and so forth [1–4, 42, 49].…”

Section: Discussionmentioning

confidence: 99%

“…The potential clinical usefulness of QSM also has been shown in multiple sclerosis [6, 43], lupus erythematosus [44], Alzheimer's disease [45], Parkinson's disease [46], multifocal leukoencephalopathy [47], cerebral perfusion [41], hemorrhage [9, 48], function MRI [12, 42] in brain, and some applications in aorta, breast, extremity, kidney, and so forth [1–4, 42, 49]. Improving accuracy of QSM will profit these approaches.…”

Section: Discussionmentioning

confidence: 99%

Structure Prior Effects in Bayesian Approaches of Quantitative Susceptibility Mapping

Chen

BioMed Research International

et al. 2016

Self Cite

Quantitative susceptibility mapping (QSM) has shown its potential for anatomical and functional MRI, as it can quantify, for in vivo tissues, magnetic biomarkers and contrast agents which have differential susceptibilities to the surroundings substances. For reconstructing the QSM with a single orientation, various methods have been proposed to identify a unique solution for the susceptibility map. Bayesian QSM approach is the major type which uses various regularization terms, such as a piece-wise constant, a smooth, a sparse, or a morphological prior. Six QSM algorithms with or without structure prior are systematically discussed to address the structure prior effects. The methods are evaluated using simulations, phantom experiments with the given susceptibility, and human brain data. The accuracy and image quality of QSM were increased when using structure prior in the simulation and phantom compared to same regularization term without it, respectively. The image quality of QSM method using the structure prior is better comparing, respectively, to the method without it by either sharpening the image or reducing streaking artifacts in vivo. The structure priors improve the performance of the various QSMs using regularized minimization including L1, L2, and TV norm.