人的大腦隨著年齡的增長而變化。先前的研究表示，與年齡相關的認知功能衰退與大腦內部的變化有關。Quantitative Susceptibility Mapping (QSM) 是一項用於量化組織內磁化率來源分佈的技術。本研究旨在判斷QSM技術是否能用於測量老化的大腦的變化。
本研究列入35位老年受試者。所有受試者均提供病歷，腦部MRI影像以及心理檢驗。然而，收集到的MRI資料遭受運動偽影造成品質降低。於是在重建QSM之前，將一個回朔性運動偽影校正技術應用在每一筆MRI原始資料。獲得磁化率圖後，本研究執行大腦的ROI選取以進行腦區磁化率的計算。在分析階段，探討認知表現和大腦區域磁化率之間的相關性。隨後，參考一些與本研究發現一致的先前研究。本研究的結果指出，磁化率能夠定量測量衰老的大腦的變化。

Human brain changes as one aged. Previous studies suggest that age-related cognitive decline is associated with changes in brain. Quantitative Susceptibility Mapping (QSM) is a powerful technique for quantifying the spatial distribution of susceptibility sources in tissues. Our study aims to determine whether QSM can be used to measure changes in aging brain.
In this study, 35 elder subjects were included. All subjects provided medical records, brain MRIs and neuropsychological tests. However, acquired MRI data was degraded by motion artifacts. Before QSM reconstruction, a retrospective motion correction technique was applied to each subject’s MRI raw data. After obtaining magnetic susceptibility maps, we performed brain ROIs extraction for evaluating brain regional susceptibility values. In the stage of analysis, we investigated correlations between cognitve performances and brain regional susceptibility values. Subsequently, we referred to previous studies which are consistent with our findings. Our results indicate that magnetic susceptibility mapping is capable of quantitatively measuring changes in aging brain.

1. Deistung, A., F. Schweser, and J.R. Reichenbach, Overview of quantitative susceptibility mapping. NMR Biomed, 2017. 30(4).
2. Wang, Y. and T. Liu, Quantitative susceptibility mapping (QSM): Decoding MRI data for a tissue magnetic biomarker. Magn Reson Med, 2015. 73(1): p. 82-101.
3. Chavhan, G.B., et al., Principles, techniques, and applications of T2*-based MR imaging and its special applications. Radiographics, 2009. 29(5): p. 1433-1449.
4. Mittal, S., et al., Susceptibility-weighted imaging: technical aspects and clinical applications, part 2. American Journal of neuroradiology, 2009. 30(2): p. 232-252.
5. Haacke, E.M., et al., Susceptibility-weighted imaging: technical aspects and clinical applications, part 1. American Journal of Neuroradiology, 2009. 30(1): p. 19-30.
6. Gilbert, G., et al., Quantitative comparison between a multiecho sequence and a single-echo sequence for susceptibility-weighted phase imaging. Magn Reson Imaging, 2012. 30(5): p. 722-30.
7. Liu, T., et al., A novel background field removal method for MRI using projection onto dipole fields (PDF). NMR in Biomedicine, 2011. 24(9): p. 1129-1136.
8. de Rochefort, L., et al., Quantitative MR susceptibility mapping using piece-wise constant regularized inversion of the magnetic field. Magnetic Resonance in Medicine, 2008. 60(4): p. 1003-1009.
9. de Rochefort, L., et al., Quantitative susceptibility map reconstruction from MR phase data using bayesian regularization: Validation and application to brain imaging. Magnetic Resonance in Medicine, 2010. 63(1): p. 194-206.
10. Liu, J., et al., Morphology enabled dipole inversion for quantitative susceptibility mapping using structural consistency between the magnitude image and the susceptibility map. Neuroimage, 2012. 59(3): p. 2560-8.
11. Deistung, A., et al., Structural and functional magnetic resonance imaging of the cerebellum: considerations for assessing cerebellar ataxias. The Cerebellum, 2016. 15(1): p. 21-25.
12. Ramos, P., et al., Iron levels in the human brain: a post-mortem study of anatomical region differences and age-related changes. Journal of Trace Elements in Medicine and Biology, 2014. 28(1): p. 13-17.
13. Harada, C.N., M.C.N. Love, and K.L. Triebel, Normal cognitive aging. Clinics in geriatric medicine, 2013. 29(4): p. 737-752.
14. Murman, D.L. The impact of age on cognition. in Seminars in hearing. 2015. Thieme Medical Publishers.
15. Teng, E.L., et al., The Cognitive Abilities Screening Instrument (CASI): a practical test for cross-cultural epidemiological studies of dementia. International psychogeriatrics, 1994. 6(1): p. 45-58.
16. Sheikh, J.I. and J.A. Yesavage, Geriatric Depression Scale (GDS): recent evidence and development of a shorter version. Clinical Gerontologist: The Journal of Aging and Mental Health, 1986.
17. Liu, H.-C., et al., Assessing cognitive abilities and dementia in a predominantly illiterate population of older individuals in Kinmen. Psychological medicine, 1994. 24(3): p. 763-770.
18. Loktyushin, A., et al., Blind retrospective motion correction of MR images. Magnetic resonance in medicine, 2013. 70(6): p. 1608-1618.
19. Feng, X., et al. Image Quality Improvement by Applying Retrospective Motion Correction on Quantitative Susceptibility Mapping and R2. in 25th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM 2017). 2017.
20. Godenschweger, F., et al., Motion correction in MRI of the brain. Physics in Medicine & Biology, 2016. 61(5): p. R32.
21. Zaitsev, M., J. Maclaren, and M. Herbst, Motion artifacts in MRI: A complex problem with many partial solutions. Journal of Magnetic Resonance Imaging, 2015. 42(4): p. 887-901.
22. McGee, K.P., et al., Image metric‐based correction (autocorrection) of motion effects: analysis of image metrics. Journal of Magnetic Resonance Imaging: An Official Journal of the International Society for Magnetic Resonance in Medicine, 2000. 11(2): p. 174-181.
23. Liu, T., et al., Nonlinear formulation of the magnetic field to source relationship for robust quantitative susceptibility mapping. Magnetic Resonance in Medicine, 2013. 69(2): p. 467-476.
24. Cusack, R. and N. Papadakis, New robust 3-D phase unwrapping algorithms: application to magnetic field mapping and undistorting echoplanar images. Neuroimage, 2002. 16(3 Pt 1): p. 754-64.
25. Moon, T.K. and W.C. Stirling, Mathematical methods and algorithms for signal processing. Vol. 1. 2000: Prentice hall Upper Saddle River, NJ.
26. Liu, T., et al., Calculation of susceptibility through multiple orientation sampling (COSMOS): A method for conditioning the inverse problem from measured magnetic field map to susceptibility source image in MRI. Magnetic Resonance in Medicine, 2009. 61(1): p. 196-204.
27. Kressler, B., et al., Nonlinear regularization for per voxel estimation of magnetic susceptibility distributions from MRI field maps. IEEE transactions on medical imaging, 2009. 29(2): p. 273-281.
28. Fischl, B., et al., Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron, 2002. 33(3): p. 341-355.
29. Desikan, R.S., et al., An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage, 2006. 31(3): p. 968-980.
30. Salat, D.H., et al., Age-associated alterations in cortical gray and white matter signal intensity and gray to white matter contrast. Neuroimage, 2009. 48(1): p. 21-28.
31. Bush, G., P. Luu, and M.I. Posner, Cognitive and emotional influences in anterior cingulate cortex. Trends in cognitive sciences, 2000. 4(6): p. 215-222.
32. Kiehl, K.A., P.F. Liddle, and J.B. Hopfinger, Error processing and the rostral anterior cingulate: An event‐related fMRI study. Psychophysiology, 2000. 37(2): p. 216-223.
33. Grambaite, R., et al., Executive dysfunction in mild cognitive impairment is associated with changes in frontal and cingulate white matter tracts. Journal of Alzheimer's Disease, 2011. 27(2): p. 453-462.
34. Andersson, M., et al., Correlations between measures of executive attention and cortical thickness of left posterior middle frontal gyrus-a dichotic listening study. Behavioral and Brain Functions, 2009. 5(1): p. 1-9.
35. Fields, R.D., White matter matters. Scientific American, 2008. 298(3): p. 54-61.
36. Maddock, R.J., A.S. Garrett, and M.H. Buonocore, Remembering familiar people: the posterior cingulate cortex and autobiographical memory retrieval. Neuroscience, 2001. 104(3): p. 667-676.
37. Minoshima, S., et al., Metabolic reduction in the posterior cingulate cortex in very early Alzheimer's disease. Annals of Neurology: Official Journal of the American Neurological Association and the Child Neurology Society, 1997. 42(1): p. 85-94.
38. Fuh, J.-L. and S.-J. Wang, Caudate hemorrhage: clinical features, neuropsychological assessments and radiological findings. Clinical neurology and neurosurgery, 1995. 97(4): p. 296-299.
39. Kumral, E., D. Evyapan, and K. Balkir, Acute caudate vascular lesions. Stroke, 1999. 30(1): p. 100-108.
40. Hirono, N., et al., Hypofunction in the posterior cingulate gyrus correlates with disorientation for time and place in Alzheimer’s disease. Journal of Neurology, Neurosurgery & Psychiatry, 1998. 64(4): p. 552-554.