磁共振頻譜(MRS)是一種收取腦中代謝物資訊的技術，它是以非侵入式的方式透過收取氫原子核的訊號，利用不同的化學鍵結會影響氫原子核的旋進頻率，進一步利用這樣的資訊觀測腦中代謝物情形。通常是利用單點式頻譜(SVS)技術，藉由使用者在感興趣區域定義一長方體(稱其為VOI)，再掃描收取此長方體區域內的MRS資料。近年來，也發現有越來越多的研究是結合了MRS及fMRI兩項技術，來測量在大腦活化區域或者是大腦靜息態區域的代謝物資訊。因此，能在標準腦空間中定義VOI是相當重要的功能，可以藉此將VOI定義在fMRI的活化區域上或者是特定的大腦結構上，再將VOI轉換到受試者空間上供MRS掃描用。如此代謝物訊息可以與fMRI的結果連結，也可以減少不同操作者間造成的定位差異。
在這個研究中，我們開發了一套自動化單點式磁共振頻譜定位技術的圖形介面工具：ALLVOI。在MRS掃描前先在標準腦上定義好VOI參數值，然後再經由自動對位演算法計算出在受試者空間上VOI的參數值，包括大小、位置和旋轉。這套自動對位工具提供了一個客觀的定位方法，工具中程式及圖形使用者介面的設計，提供使用者能有一個簡單且方便的方式來定義VOI。

Magnetic resonance spectroscopy (MRS) data were usually acquired with single voxel spectroscopy techniques (SVS), which is used to access metabolites concentrations from a predefined volume of interest (VOI). Currently, MRS has been linked to fMRI studies to access metabolic information in activated brain regions or in resting brain areas. Therefore, it’s important to define the VOI on standard space (template) and transform the predefined VOI from standard space to subject space for each MRS scan. In this way, VOI can be determined from the template based on a cluster in fMRI results or a known brain structure instead of determining VOI subject-by-subject by operator’s experience. Metabolic information can be directly linked to fMRI results and operator bias on the localization of VOI can be minimized.
In this study, an automatic tool is developed for this purpose. We developed a toolbox: automatic localization of VOI (ALLVOI). It is to guide the definition of VOI on template before MRS scan then automatically calculate parameters of VOI such as voxel position, voxel size, orientation, and rotation in subject space. Moreover, the toolbox based on user-defined VOI on the MNI template is a more objective processing, and it is simple and convenient on operation so that users can easily perform the task of VOI definition.

1. Malhi GS, Valenzuela M, Wen W, Sachdev P. Magnetic resonance spectroscopy and its applications in psychiatry. Aust N Z J Psychiatry 2002;36(1):31-43.
2. Pouwels PJ, Frahm J. Regional metabolite concentrations in human brain as determined by quantitative localized proton MRS. Magn Reson Med 1998;39(1):53-60.
3. Zarifi M, Tzika AA. Proton MRS imaging in pediatric brain tumors. Pediatr Radiol 2016;46(7):952-962.
4. Gottschalk M, Tropres I, Lamalle L, Grand S, Le Bas JF, Segebarth C. Refined modelling of the short-T2 signal component and ensuing detection of glutamate and glutamine in short-TE, localised, (1) H MR spectra of human glioma measured at 3 T. Nmr Biomed 2016;29(7):943-951.
5. Karamchandani RR, Fletcher JJ, Pandey AS, Rajajee V. Incidence of delayed seizures, delayed cerebral ischemia and poor outcome with the use of levetiracetam versus phenytoin after aneurysmal subarachnoid hemorrhage. J Clin Neurosci 2014;21(9):1507-1513.
6. Zhong S, Wang Y, Zhao G, Xiang Q, Ling X, Liu S, Huang L, Jia Y. Similarities of biochemical abnormalities between major depressive disorder and bipolar depression: a proton magnetic resonance spectroscopy study. J Affect Disord 2014;168:380-386.
7. Lunsing RJ, Strating K, de Koning TJ, Sijens PE. Diagnostic value of MRS-quantified brain tissue lactate level in identifying children with mitochondrial disorders. Eur Radiol 2016.
8. Marro KI, Lee D, Shankland EG, Mathis CM, Hayes CE, Friedman SD, Kushmerick MJ. Quantitative in vivo magnetic resonance spectroscopy using synthetic signal injection. PLoS One 2010;5(12):e15166.
9. Heo H, Kim S, Lee HH, Cho HR, Xu WJ, Lee SH, Park CK, Park S, Choi SH, Kim H. On the Utility of Short Echo Time (TE) Single Voxel 1H-MRS in Non-Invasive Detection of 2-Hydroxyglutarate (2HG); Challenges and Potential Improvement Illustrated with Animal Models Using MRUI and LCModel. PLoS One 2016;11(1):e0147794.
10. Hsu SH, Chou MC, Ko CW, Hsu SS, Lin HS, Fu JH, Wang PC, Pan HB, Lai PH. Proton MR spectroscopy in patients with pyogenic brain abscess: MR spectroscopic imaging versus single-voxel spectroscopy. Eur J Radiol 2013;82(8):1299-1307.
11. Ricci PE, Pitt A, Keller PJ, Coons SW, Heiserman JE. Effect of voxel position on single-voxel MR spectroscopy findings. AJNR Am J Neuroradiol 2000;21(2):367-374.
12. Barker PB, Lin DDM. In vivo proton MR spectroscopy of the human brain. Prog Nucl Mag Res Sp 2006;49(2):99-128.
13. Zeki S, Watson JD, Lueck CJ, Friston KJ, Kennard C, Frackowiak RS. A direct demonstration of functional specialization in human visual cortex. J Neurosci 1991;11(3):641-649.
14. Fonov V, Evans AC, Botteron K, Almli CR, McKinstry RC, Collins DL, Brain Development Cooperative G. Unbiased average age-appropriate atlases for pediatric studies. Neuroimage 2011;54(1):313-327.
15. Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, Mazoyer B, Joliot M. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 2002;15(1):273-289.
16. Maudsley AA, Domenig C, Govind V, Darkazanli A, Studholme C, Arheart K, Bloomer C. Mapping of brain metabolite distributions by volumetric proton MR spectroscopic imaging (MRSI). Magn Reson Med 2009;61(3):548-559.
17. Ratai EM, Hancu I, Blezek DJ, Turk KW, Halpern E, Gonzalez RG. Automatic repositioning of MRSI voxels in longitudinal studies: impact on reproducibility of metabolite concentration measurements. J Magn Reson Imaging 2008;27(5):1188-1193.
18. Mon A, Durazzo TC, Meyerhoff DJ. Glutamate, GABA, and other cortical metabolite concentrations during early abstinence from alcohol and their associations with neurocognitive changes. Drug Alcohol Depend 2012;125(1-2):27-36.
19. Hartmann SL, Dawant BM, Parks MH, Schlack H, Martin PR. Image-guided MR spectroscopy volume of interest localization for longitudinal studies. Comput Med Imaging Graph 1998;22(6):453-461.
20. Gong Y. Automatic position of MR spectroscopy voxels. Taipei: National Taiwan univversity of science and technology; 2015.
21. Kapogiannis D, Reiter DA, Willette AA, Mattson MP. Posteromedial cortex glutamate and GABA predict intrinsic functional connectivity of the default mode network. Neuroimage 2013;64:112-119.
22. Wiebking C, Duncan NW, Tiret B, Hayes DJ, Marjanska M, Doyon J, Bajbouj M, Northoff G. GABA in the insula - a predictor of the neural response to interoceptive awareness. Neuroimage 2014;86:10-18.

23. Jin B, Strasburger A, Laken SJ, Kozel FA, Johnson KA, George MS, Lu X. Feature selection for fMRI-based deception detection. BMC Bioinformatics 2009;10 Suppl 9:S15.
24. Ganis G, Kosslyn SM, Stose S, Thompson WL, Yurgelun-Todd DA. Neural correlates of different types of deception: an fMRI investigation. Cereb Cortex 2003;13(8):830-836.
25. Eickhoff SB, Stephan KE, Mohlberg H, Grefkes C, Fink GR, Amunts K, Zilles K. A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data. Neuroimage 2005;25(4):1325-1335.
26. Maldjian JA, Baer AH, Kraft RA, Laurienti PJ, Burdette JH. Fully automated processing of fMRI data in SPM: from MRI scanner to PACS. Neuroinformatics 2009;7(1):57-72.
27. Uchida S. Image processing and recognition for biological images. Dev Growth Differ 2013;55(4):523-549.
28. Jiang Y, Zhu C, Peng W, Degnan AJ, Chen L, Wang X, Liu Q, Wang Y, Xiang Z, Teng Z, Saloner D, Lu J. Ex-vivo imaging and plaque type classification of intracranial atherosclerotic plaque using high resolution MRI. Atherosclerosis 2016;249:10-16.
29. Utine GE, Akpinar B, Arslan U, Kiper PO, Volkan-Salanci B, Alanay Y, Aktas D, Haliloglu G, Oguz KK, Boduroglu K, Alikasifoglu M. Neurochemical evaluation of brain function with 1H magnetic resonance spectroscopy in patients with fragile X syndrome. Am J Med Genet A 2014;164A(1):99-105.
30. Renvall V, Witzel T, Wald LL, Polimeni JR. Automatic cortical surface reconstruction of high-resolution T echo planar imaging data. Neuroimage 2016;134:338-354.
31. Traber F, Block W, Lamerichs R, Gieseke J, Schild HH. 1H metabolite relaxation times at 3.0 tesla: Measurements of T1 and T2 values in normal brain and determination of regional differences in transverse relaxation. J Magn Reson Imaging 2004;19(5):537-545.
32. Zhang Y, Han Y, Wang Y, Zhang Y, Li L, Jin E, Deng L, Watts B, Golden T, Wu N. A MRS study of metabolic alterations in the frontal white matter of major depressive disorder patients with the treatment of SSRIs. BMC Psychiatry 2015;15:99.