Page 54 - GTM-2-3

Global Translational Medicine Deep learning by NMR-biochemical

of proton and 13C NMR study of glutamate metabolism secondary progressive multiple sclerosis: A magnetic
in cultured glial cells and human brain in vivo. Biochemie, resonance spectroscopic imaging study. J Neurol,
73: 93–97. 265: 1795–1802.
https://doi.org/10.1016/0300-9084(91)90080-k https://doi.org/10.1007/s00415-018-8903-y
12. Zia B, Bogia DP, 2020, Fast Fourier Transform and 22. Filippi M, Rocca MA, Rovaris M, 2002, Clinical trials and
Convolution in Medical Image Reconstruction. Available clinical practice in multiple sclerosis: Conventional and
from: https://www.intel.com/content/www/us/en/developer/ emerging magnetic resonance imaging technologies. Curr
articles/technical/fast-fourier-transform-and-convolution- Neurol Neurosci Rep, 2: 267–276.
in-medical-image-reconstruction.html [Last accessed on https://doi.org/10.1007/s11910-002-0086-2
2019 Nov 30].
23. Zuo J, Joseph GB, Li X, et al., 2012, In vivo intervertebral disc
13. Iqbal Z, Nguyen D, Thomas MA, et al., 2021, Deep learning characterization using magnetic resonance spectroscopy and
can accelerate and quantify simulated localized correlated T1ρ imaging: Association with discography and Oswestry
spectroscopy. Sci Rep, 11: 8727.
Disability Index and Short Form-36 Health Survey. Spine
14. Yang J, Lei D, Qin K, et al., 2021, Using deep learning to (Phila Pa 1976), 37: 214–221.
classify pediatric posttraumatic stress disorder at the https://doi.org/10.1097/BRS.0b013e3182294a63
individual level. BMC Psychiatry, 21: 535.
24. Tartaglia MC, Arnold DL, 2006, The role of MRS and fMRI
https://doi.org/10.1186/s12888-021-03503-9
in multiple sclerosis. Adv Neurol, 98: 185–202.
15. Balakrishnan R, Valdés Hernández MDC, Farrall AJ, 2021, 25. Miller DH, Albert PS, Barkhof F, et al., 1996, Guidelines for
Automatic segmentation of white matter hyperintensities the use of magnetic resonance techniques in monitoring the
from brain magnetic resonance images in the era of deep
learning and big data - A systematic review. Comput Med treatment of multiple sclerosis. US National MS Society Task
Imaging Graph, 88: 101867. Force. Ann Neurol, 39: 6–16.
https://doi.org/10.1002/ana.410390104
https://doi.org/10.1016/j.compmedimag.2021.101867
26. Binesh N, Yue K, Fairbanks L, et al., 2002, Reproducibility of
16. Terpstra ML, Maspero M, Sbrizzi A, et al., 2022, A localized 2D correlated MR spectroscopy. Magn Reson Med,
symmetric loss function for magnetic resonance imaging
reconstruction and image registration with deep learning. 48: 942–948.
Med Image Anal, 80: 102509. https://doi.org/10.1002/mrm.10307
https://doi.org/10.1016/j.media.2022.102509 27. Jung JA, Coakley FV, Vigneron DB, et al., 2004, Prostate
depiction at endorectal MR spectroscopic imaging:
17. Chen D, Wang Z, Guo D, 2020, Review and prospect: Deep
learning in nuclear magnetic resonance spectroscopy. Investigation of a standardized evaluation system. Radiology,
Chemistry, 26: 10391–10401. 233: 701–708.
https://doi.org/10.1148/radiol.2333030672
https://doi.org/10.1002/chem.202000246
28. Boesch SM, Wolf C, Seppi K, et al., 2007, Differentiation
18. Li X, Strasser B, Neuberger U, et al., 2022, Deep learning of SCA2 from MSA-C using proton magnetic resonance
super-resolution magnetic resonance spectroscopic imaging
of brain metabolism and mutant isocitrate dehydrogenase spectroscopic imaging. J Magn Reson Imaging, 25: 564–569.
glioma. Neurooncol Adv, 4: vdac071. https://doi.org/10.1002/jmri.20846
https://doi.org/10.1093/noajnl/vdac071 29. Kahleova H, Petersen KF, Shulman GI, et al., 2020,
Effect of a low-fat vegan diet on body weight, insulin
19. Migdadi L, Lambert J, Telfah A, et al., 2021, Automated
metabolic assignment: Semi-supervised learning in sensitivity, postprandial metabolism, and intramyocellular
metabolic analysis employing two dimensional Nuclear and hepatocellular lipid levels in overweight adults:
Magnetic Resonance (NMR). Comput Struct Biotechnol J, A randomized clinical trial. JAMA Netw Open, 3: e2025454.
19: 5047–5058. https://doi.org/10.1001/jamanetworkopen.2020.25454
20. Sarma MK, Nagarajan R, Macey PM, et al., 2014, Accelerated 30. Smits M, 2021, MRI biomarkers in neuro-oncology. Nat Rev
echo-planar J-resolved spectroscopic imaging in the human Neurol, 17: 486–500.
brain using compressed sensing: A pilot validation in https://doi.org/10.1038/s41582-021-00510-y
obstructive sleep apnea. AJNR Am J Neuroradiol, 35: S81–S89.
31. Galanaud D, Haik S, Linguraru MG, et al, 2010, Combined
https://doi.org/10.3174/ajnr.A3846
diffusion imaging and MR spectroscopy in the diagnosis
21. Marshall I, Thrippleton MJ, Bastin ME, et al., 2018, of human prion diseases. AJNR Am J Neuroradiol,
Characterisation of tissue-type metabolic content in 31: 1311–1318.

Volume 2 Issue 3 (2023) 22 https://doi.org/10.36922/gtm.337