Adaptive denoising for chemical exchange saturation transfer MR imaging.
CEST
MRI
amide
denoising
principal component analysis
rNOE
singular value decomposition
Journal
NMR in biomedicine
ISSN: 1099-1492
Titre abrégé: NMR Biomed
Pays: England
ID NLM: 8915233
Informations de publication
Date de publication:
11 2019
11 2019
Historique:
received:
20
03
2019
revised:
03
06
2019
accepted:
04
06
2019
pubmed:
31
7
2019
medline:
25
6
2020
entrez:
31
7
2019
Statut:
ppublish
Résumé
High image signal-to-noise ratio (SNR) is required to reliably detect the inherently small chemical exchange saturation transfer (CEST) effects in vivo. In this study, it was demonstrated that identifying spectral redundancies of CEST data by principal component analysis (PCA) in combination with an appropriate data-driven extraction of relevant information can be used for an effective and robust denoising of CEST spectra. The relationship between the number of relevant principal components and SNR was studied on fitted in vivo Z-spectra with artificially introduced noise. Three different data-driven criteria to automatically determine the optimal number of necessary components were investigated. In addition, these criteria facilitate straightforward assessment of data quality that could provide guidance for CEST MR protocols in terms of SNR. Insights were applied to achieve a robust denoising of highly sampled low power Z-spectra of the human brain at 3 and 7 T. The median criterion provided the best estimation for the optimal number of components consistently for all three investigated artificial noise levels. Application of the denoising technique to in vivo data revealed a considerable increase in image quality for the amide and rNOE contrast with a considerable SNR gain. At 7 T the denoising capability was quantified to be comparable or even superior to an averaging of six measurements. The proposed denoising algorithm enables an efficient and robust denoising of CEST data by combining PCA with appropriate data-driven truncation criteria. With this generally applicable technique at hand, small CEST effects can be reliably detected without the need for repeated measurements.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e4133Commentaires et corrections
Type : ErratumIn
Informations de copyright
© 2019 John Wiley & Sons, Ltd.
Références
Forsen S, Hoffman RA. Study of moderately rapid chemical exchange reactions by means of nuclear magnetic double resonance. J Chem Phys. 1963;39:2892-2901.
Ward K, Aletras A, Balaban R. A new class of contrast agents for MRI based on proton chemical exchange dependent saturation transfer (CEST). J Magn Reson. 2000;143:79-87.
Zhou J, Payen J-F, Wilson DA, Traystman RJ, van Zijl PCM. Using the amide proton signals of intracellular proteins and peptides to detect pH effects in MRI. Nat Med. 2003;9:1085-1090.
Jones CK, Huang A, Xu J, et al. Nuclear Overhauser enhancement (NOE) imaging in the human brain at 7T. Neuroimage. 2013;77:114-124.
Zaiss M, Windschuh J, Paech D, et al. Relaxation-compensated CEST-MRI of the human brain at 7T: unbiased insight into NOE and amide signal changes in human glioblastoma. Neuroimage. 2015;112:180-188.
Zaiss M, Windschuh J, Goerke S, et al. Downfield-NOE-suppressed amide-CEST-MRI at 7 tesla provides a unique contrast in human glioblastoma. Magn Reson Med. 2017;77:196-208.
Zaiss M, Kunz P, Goerke S, Radbruch A, Bachert P. MR imaging of protein folding in vitro employing nuclear-Overhauser-mediated saturation transfer. NMR Biomed. 2013;26:1815-1822.
Goerke S, Zaiss M, Kunz P, et al. Signature of protein unfolding in chemical exchange saturation transfer imaging. NMR Biomed. 2015;28:906-913.
Goerke S, Milde KS, Bukowiecki R, et al. Aggregation-induced changes in the chemical exchange saturation transfer (CEST) signals of proteins. NMR Biomed. 2017;30:e3665.
Kogan F, Haris M, Singh A, et al. Method for high-resolution imaging of creatine in vivo using chemical exchange saturation transfer. Magn Reson Med. 2014;71:164-172.
Rerich E, Zaiss M, Korzowski A, Ladd ME, Bachert P. Relaxation-compensated CEST-MRI at 7 T for mapping of creatine content and pH - preliminary application in human muscle tissue in vivo. NMR Biomed. 2015;28:1402-1412.
Cai K, Haris M, Singh A, et al. Magnetic resonance imaging of glutamate. Nat Med. 2012;18:302-306.
Haris M, Nath K, Cai K, et al. Imaging of glutamate neurotransmitter alterations in Alzheimer's disease. NMR Biomed. 2013;26:386-391.
Aime S, Calabi L, Biondi L, et al. Iopamidol: exploring the potential use of a well-established x-ray contrast agent for MRI. Magn Reson Med. 2005;53:830-834.
Longo DL, Busato A, Lanzardo S, Antico F, Aime S. Imaging the pH evolution of an acute kidney injury model by means of iopamidol, a MRI-CEST pH-responsive contrast agent. Magn Reson Med. 2013;70:859-864.
Jones KM, Randtke EA, Howison CM, et al. Measuring extracellular pH in a lung fibrosis model with acidoCEST MRI. Mol Imaging Biol. 2015;17:177-184.
Chan KWY, McMahon MT, Kato Y, et al. Natural D-glucose as a biodegradable MRI contrast agent for detecting cancer. Magn Reson Med. 2012;68:1764-1773.
Walker-Samuel S, Ramasawmy R, Torrealdea F, et al. In vivo imaging of glucose uptake and metabolism in tumors. Nat Med. 2013;19:1067-1072.
Xu X, Yadav NN, Knutsson L, et al. Dynamic glucose-enhanced (DGE) MRI: translation to human scanning and first results in glioma patients. Tomography. 2015;1:105-114.
Schuenke P, Koehler C, Korzowski A, et al. Adiabatically prepared spin-lock approach for T1ρ-based dynamic glucose enhanced MRI at ultrahigh fields. Magn Reson Med. 2017;78:215-225.
Nasrallah FA, Pagès G, Kuchel PW, Golay X, Chuang K-H. Imaging brain deoxyglucose uptake and metabolism by glucoCEST MRI. J Cereb Blood Flow Metab. 2013;33:1270-1278.
Rivlin M, Tsarfaty I, Navon G. Functional molecular imaging of tumors by chemical exchange saturation transfer MRI of 3-O-methyl-D-glucose. Magn Reson Med. 2014;72:1375-1380.
Zaiss M, Schuppert M, Deshmane A, et al. Chemical exchange saturation transfer MRI contrast in the human brain at 9.4 T. Neuroimage. 2018;179:144-155.
Cai K, Singh A, Poptani H, et al. CEST signal at 2 ppm (CEST@2ppm) from Z-spectral fitting correlates with creatine distribution in brain tumor. NMR Biomed. 2014;28:1-8.
Paech D, Burth S, Windschuh J, et al. Nuclear Overhauser enhancement imaging of glioblastoma at 7 tesla: region specific correlation with apparent diffusion coefficient and histology. PLoS ONE. 2015;10:1-16.
Paech D, Windschuh J, Oberhollenzer J, et al. Assessing the predictability of IDH mutation and MGMT methylation status in glioma patients using relaxation-compensated multipool CEST MRI at 7.0 T. Neuro Oncol. 2018;20:1661-1671.
Jiang S, Zou T, Eberhart CG, et al. Predicting IDH mutation status in grade-II gliomas using amide proton transfer-weighted (APTw) MRI. Magn Reson Med. 2017;78:1100-1109.
Jiang S, Rui Q, Wang Y, et al. Discriminating MGMT promoter methylation status in patients with glioblastoma employing amide proton transfer-weighted MRI metrics. Eur Radiol. 2018;28:2115-2123.
Meissner J-E, Korozowski A, Regnery S, et al. Early response assessment of glioma patients to definitive chemoradiotherapy using chemical exchange saturation transfer imaging at 7 T. J Magn Reson Imaging. 2019. https://doi:10.1002/jmri.26702
Regnery S, Adeberg S, Dreher C, et al. Chemical exchange saturation transfer MRI serves as predictor of early progression in glioblastoma patients. Oncotarget. 2018;9:28772-28783.
Desmond KL, Mehrabian H, Chavez S, et al. Chemical exchange saturation transfer for predicting response to stereotactic radiosurgery in human brain metastasis. Magn Reson Med. 2017;78:1110-1120.
Mehrabian H, Myrehaug S, Soliman H, Sahgal A, Stanisz GJ. Evaluation of glioblastoma response to therapy with chemical exchange saturation transfer. Int J Radiat Oncol. 2018;101:713-723.
Goerke S, Breitling J, Zaiss M, et al. Dual-frequency irradiation CEST-MRI of endogenous bulk mobile proteins. NMR Biomed. 2018;31:e3920.
Deshmane A, Zaiss M, Lindig T, et al. 3D gradient echo snapshot CEST MRI with low power saturation for human studies at 3T. Magn Reson Med. 2019;81:2412-2423.
Windschuh J, Zaiss M, Meissner J-E, et al. Correction of B 1-inhomogeneities for relaxation-compensated CEST imaging at 7 T. NMR Biomed. 2015;28:529-537.
Jin T, Wang P, Zong X, Kim S-G. MR imaging of the amide-proton transfer effect and the pH-insensitive nuclear overhauser effect at 9.4 T. Magn Reson Med. 2013;69:760-770.
Zhou IY, Wang E, Cheung JS, Zhang X, Fulci G, Sun PZ. Quantitative chemical exchange saturation transfer (CEST) MRI of glioma using image downsampling expedited adaptive least-squares (IDEAL) fitting. Sci Rep. 2017;7:84.
Zaiss M, Ehses P, Scheffler K. Snapshot-CEST: optimizing spiral-centric-reordered gradient echo acquisition for fast and robust 3D CEST MRI at 9.4 T. NMR Biomed. 2018;31:e3879.
Eckart C, Young G. The approximation of one matrix by another of lower rank. Psychometrika. 1936;1:211-218.
Hotelling H. Analysis of a complex of statistical variables into principal components. J Educ Psychol. 1933;24:417-441.
Döpfert J, Witte C, Kunth M, Schröder L. Sensitivity enhancement of (hyper-)CEST image series by exploiting redundancies in the spectral domain. Contrast Media Mol Imaging. 2014;9:100-107.
Wech T, Köstler H. Robust motion correction in CEST imaging exploiting low-rank approximation of the z-spectrum. Magn Reson Med. 2018;80:1979-1988.
Balvay D, Kachenoura N, Espinoza S, et al. Signal-to-noise ratio improvement in dynamic contrast-enhanced CT and MR imaging with automated principal component analysis filtering. Radiology. 2011;258:435-445.
Veraart J, Novikov DS, Christiaens D, Ades-aron B, Sijbers J, Fieremans E. Denoising of diffusion MRI using random matrix theory. Neuroimage. 2016;142:394.
Kaiser HF. The varimax criterion for analytic rotation in factor analysis. Psychometrika. 1958;23:187-200.
Valle S, Li W, Qin SJ. Selection of the number of principal components: the variance of the reconstruction error criterion with a comparison to other methods. Ind Eng Chem Res. 1999;38:4389-4401.
Malinowski ER. Theory of error in factor analysis. Anal Chem. 1977;49:606-612.
Malinowski ER. Determination of the number of factors and the experimental error in a data matrix. Anal Chem. 1977;49:612-617.
Cattell RB. The scree test for the number of factors. Multivar Behav Res. 1966;1:245-276.
Nelson LR. Some observations on the scree test, and on coefficient alpha. J Educ Res Meas. 2005;3:1-17.
Manjón JV, Coupé P, Buades A. MRI noise estimation and denoising using non-local PCA. Med Image Anal. 2015;22:35-47.
Schuenke P, Windschuh J, Roeloffs V, Ladd ME, Bachert P, Zaiss M. Simultaneous mapping of water shift and B1 (WASABI)-application to field-inhomogeneity correction of CESTMRI data. Magn Reson Med. 2017;77:571-580.
Cox RW, Hyde JS. Software tools for analysis and visualization of fMRI data. NMR Biomed. 1997;10:171-178.
Nolden M, Zelzer S, Seitel A, et al. The medical imaging interaction toolkit: challenges and advances: 10 years of open-source development. Int J Comput Assist Radiol Surg. 2013;8:607-620.
Windschuh J, Zaiss M, Meissner J-E, et al. Correction of B1-inhomogeneities for relaxation-compensated CEST imaging at 7 T. NMR Biomed. 2015;28:529-537.
Aja-Fernández S, Tristán-Vega A, Hoge WS. Statistical noise analysis in GRAPPA using a parametrized noncentral chi approximation model. Magn Reson Med. 2011;65:1195-1206.
Foi A. Noise estimation and removal in MR imaging: the variance-stabilization approach. In: 2011 IEEE International Symposium on Biomedical Imaging: from Nano to Macro;2011:1809-1814.