Determination of an optimally sensitive and specific chemical exchange saturation transfer MRI quantification metric in relevant biological phantoms
The purpose of this study was to develop realistic phantom models of the intracellular environment of metastatic breast tumour and naïve brain, and using these models determine an analysis metric for quantification of CEST MRI data that is sensitive to only labile proton exchange rate and concentrat...
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| Published in | NMR in biomedicine Vol. 29; no. 11; pp. 1624 - 1633 |
|---|---|
| Main Authors | , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Blackwell Publishing Ltd
01.11.2016
Wiley Subscription Services, Inc John Wiley and Sons Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0952-3480 1099-1492 1099-1492 |
| DOI | 10.1002/nbm.3614 |
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| Abstract | The purpose of this study was to develop realistic phantom models of the intracellular environment of metastatic breast tumour and naïve brain, and using these models determine an analysis metric for quantification of CEST MRI data that is sensitive to only labile proton exchange rate and concentration. The ability of the optimal metric to quantify pH differences in the phantoms was also evaluated.
Novel phantom models were produced, by adding perchloric acid extracts of either metastatic mouse breast carcinoma cells or healthy mouse brain to bovine serum albumin. The phantom model was validated using 1H NMR spectroscopy, then utilized to determine the sensitivity of CEST MRI to changes in pH, labile proton concentration, T1 time and T2 time; six different CEST MRI analysis metrics (MTRasym, APT*, MTRRex, AREX and CESTR* with and without T1/T2 compensation) were compared.
The new phantom models were highly representative of the in vivo intracellular environment of both tumour and brain tissue. Of the analysis methods compared, CESTR* with T1 and T2 time compensation was optimally specific to changes in the CEST effect (i.e. minimal contamination from T1 or T2 variation). In phantoms with identical protein concentrations, pH differences between phantoms could be quantified with a mean accuracy of 0.6 pH units.
We propose that CESTR* with T1 and T2 time compensation is the optimal analysis method for these phantoms. Analysis of CEST MRI data with T1/T2 time compensated CESTR* is reproducible between phantoms, and its application in vivo may resolve the intracellular alkalosis associated with breast cancer brain metastases without the need for exogenous contrast agents.
Novel biologically relevant phantom models of the intracellular environment of metastatic breast tumour and naïve brain were produced, and used to determine an optimally sensitive and specific analysis metric for quantification of pH from CEST MRI data. Of the analysis methods compared, CESTR* with T1 and T2 time compensation was optimally specific to changes in the CEST effect (i.e. minimal contamination from T1 or T2 variation), with the ability to measure quantitative differences in pH with an accuracy of 0.6 pH units. |
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| AbstractList | The purpose of this study was to develop realistic phantom models of the intracellular environment of metastatic breast tumour and naïve brain, and using these models determine an analysis metric for quantification of CEST MRI data that is sensitive to only labile proton exchange rate and concentration. The ability of the optimal metric to quantify pH differences in the phantoms was also evaluated. Novel phantom models were produced, by adding perchloric acid extracts of either metastatic mouse breast carcinoma cells or healthy mouse brain to bovine serum albumin. The phantom model was validated using
H NMR spectroscopy, then utilized to determine the sensitivity of CEST MRI to changes in pH, labile proton concentration, T
time and T
time; six different CEST MRI analysis metrics (MTR
, APT*, MTR
, AREX and CESTR* with and without T
/T
compensation) were compared. The new phantom models were highly representative of the in vivo intracellular environment of both tumour and brain tissue. Of the analysis methods compared, CESTR* with T
and T
time compensation was optimally specific to changes in the CEST effect (i.e. minimal contamination from T
or T
variation). In phantoms with identical protein concentrations, pH differences between phantoms could be quantified with a mean accuracy of 0.6 pH units. We propose that CESTR* with T
and T
time compensation is the optimal analysis method for these phantoms. Analysis of CEST MRI data with T
/T
time compensated CESTR* is reproducible between phantoms, and its application in vivo may resolve the intracellular alkalosis associated with breast cancer brain metastases without the need for exogenous contrast agents. The purpose of this study was to develop realistic phantom models of the intracellular environment of metastatic breast tumour and naïve brain, and using these models determine an analysis metric for quantification of CEST MRI data that is sensitive to only labile proton exchange rate and concentration. The ability of the optimal metric to quantify pH differences in the phantoms was also evaluated. Novel phantom models were produced, by adding perchloric acid extracts of either metastatic mouse breast carcinoma cells or healthy mouse brain to bovine serum albumin. The phantom model was validated using 1H NMR spectroscopy, then utilized to determine the sensitivity of CEST MRI to changes in pH, labile proton concentration, T 1 time and T 2 time; six different CEST MRI analysis metrics (MTRasym, APT*, MTRRex, AREX and CESTR* with and without T 1/T 2 compensation) were compared. The new phantom models were highly representative of the in vivo intracellular environment of both tumour and brain tissue. Of the analysis methods compared, CESTR* with T 1 and T 2 time compensation was optimally specific to changes in the CEST effect (i.e. minimal contamination from T 1 or T 2 variation). In phantoms with identical protein concentrations, pH differences between phantoms could be quantified with a mean accuracy of 0.6 pH units. We propose that CESTR* with T 1 and T 2 time compensation is the optimal analysis method for these phantoms. Analysis of CEST MRI data with T 1/T 2 time compensated CESTR* is reproducible between phantoms, and its application in vivo may resolve the intracellular alkalosis associated with breast cancer brain metastases without the need for exogenous contrast agents. The purpose of this study was to develop realistic phantom models of the intracellular environment of metastatic breast tumour and naïve brain, and using these models determine an analysis metric for quantification of CEST MRI data that is sensitive to only labile proton exchange rate and concentration. The ability of the optimal metric to quantify pH differences in the phantoms was also evaluated. Novel phantom models were produced, by adding perchloric acid extracts of either metastatic mouse breast carcinoma cells or healthy mouse brain to bovine serum albumin. The phantom model was validated using 1H NMR spectroscopy, then utilized to determine the sensitivity of CEST MRI to changes in pH, labile proton concentration, T1 time and T2 time; six different CEST MRI analysis metrics (MTRasym, APT*, MTRRex, AREX and CESTR* with and without T1/T2 compensation) were compared. The new phantom models were highly representative of the in vivo intracellular environment of both tumour and brain tissue. Of the analysis methods compared, CESTR* with T1 and T2 time compensation was optimally specific to changes in the CEST effect (i.e. minimal contamination from T1 or T2 variation). In phantoms with identical protein concentrations, pH differences between phantoms could be quantified with a mean accuracy of 0.6 pH units. We propose that CESTR* with T1 and T2 time compensation is the optimal analysis method for these phantoms. Analysis of CEST MRI data with T1/T2 time compensated CESTR* is reproducible between phantoms, and its application in vivo may resolve the intracellular alkalosis associated with breast cancer brain metastases without the need for exogenous contrast agents. The purpose of this study was to develop realistic phantom models of the intracellular environment of metastatic breast tumour and naïve brain, and using these models determine an analysis metric for quantification of CEST MRI data that is sensitive to only labile proton exchange rate and concentration. The ability of the optimal metric to quantify pH differences in the phantoms was also evaluated. Novel phantom models were produced, by adding perchloric acid extracts of either metastatic mouse breast carcinoma cells or healthy mouse brain to bovine serum albumin. The phantom model was validated using 1 H NMR spectroscopy, then utilized to determine the sensitivity of CEST MRI to changes in pH, labile proton concentration, T1 time and T2 time; six different CEST MRI analysis metrics (MTRasym , APT*, MTRRex , AREX and CESTR* with and without T1 /T2 compensation) were compared. The new phantom models were highly representative of the in vivo intracellular environment of both tumour and brain tissue. Of the analysis methods compared, CESTR* with T1 and T2 time compensation was optimally specific to changes in the CEST effect (i.e. minimal contamination from T1 or T2 variation). In phantoms with identical protein concentrations, pH differences between phantoms could be quantified with a mean accuracy of 0.6 pH units. We propose that CESTR* with T1 and T2 time compensation is the optimal analysis method for these phantoms. Analysis of CEST MRI data with T1 /T2 time compensated CESTR* is reproducible between phantoms, and its application in vivo may resolve the intracellular alkalosis associated with breast cancer brain metastases without the need for exogenous contrast agents.The purpose of this study was to develop realistic phantom models of the intracellular environment of metastatic breast tumour and naïve brain, and using these models determine an analysis metric for quantification of CEST MRI data that is sensitive to only labile proton exchange rate and concentration. The ability of the optimal metric to quantify pH differences in the phantoms was also evaluated. Novel phantom models were produced, by adding perchloric acid extracts of either metastatic mouse breast carcinoma cells or healthy mouse brain to bovine serum albumin. The phantom model was validated using 1 H NMR spectroscopy, then utilized to determine the sensitivity of CEST MRI to changes in pH, labile proton concentration, T1 time and T2 time; six different CEST MRI analysis metrics (MTRasym , APT*, MTRRex , AREX and CESTR* with and without T1 /T2 compensation) were compared. The new phantom models were highly representative of the in vivo intracellular environment of both tumour and brain tissue. Of the analysis methods compared, CESTR* with T1 and T2 time compensation was optimally specific to changes in the CEST effect (i.e. minimal contamination from T1 or T2 variation). In phantoms with identical protein concentrations, pH differences between phantoms could be quantified with a mean accuracy of 0.6 pH units. We propose that CESTR* with T1 and T2 time compensation is the optimal analysis method for these phantoms. Analysis of CEST MRI data with T1 /T2 time compensated CESTR* is reproducible between phantoms, and its application in vivo may resolve the intracellular alkalosis associated with breast cancer brain metastases without the need for exogenous contrast agents. The purpose of this study was to develop realistic phantom models of the intracellular environment of metastatic breast tumour and naive brain, and using these models determine an analysis metric for quantification of CEST MRI data that is sensitive to only labile proton exchange rate and concentration. The ability of the optimal metric to quantify pH differences in the phantoms was also evaluated. Novel phantom models were produced, by adding perchloric acid extracts of either metastatic mouse breast carcinoma cells or healthy mouse brain to bovine serum albumin. The phantom model was validated using super(1)H NMR spectroscopy, then utilized to determine the sensitivity of CEST MRI to changes in pH, labile proton concentration, T sub(1) time and T sub(2) time; six different CEST MRI analysis metrics (MTR sub(asym), APT*, MTR sub(Rex), AREX and CESTR* with and without T sub(1)/T sub(2) compensation) were compared. The new phantom models were highly representative of the in vivo intracellular environment of both tumour and brain tissue. Of the analysis methods compared, CESTR* with T sub(1) and T sub(2) time compensation was optimally specific to changes in the CEST effect (i.e. minimal contamination from T sub(1) or T sub(2) variation). In phantoms with identical protein concentrations, pH differences between phantoms could be quantified with a mean accuracy of 0.6 pH units. We propose that CESTR* with T sub(1) and T sub(2) time compensation is the optimal analysis method for these phantoms. Analysis of CEST MRI data with T sub(1)/T sub(2) time compensated CESTR* is reproducible between phantoms, and its application in vivo may resolve the intracellular alkalosis associated with breast cancer brain metastases without the need for exogenous contrast agents. Novel biologically relevant phantom models of the intracellular environment of metastatic breast tumour and naive brain were produced, and used to determine an optimally sensitive and specific analysis metric for quantification of pH from CEST MRI data. Of the analysis methods compared, CESTR* with T sub(1) and T sub(2) time compensation was optimally specific to changes in the CEST effect (i.e. minimal contamination from T sub(1) or T sub(2) variation), with the ability to measure quantitative differences in pH with an accuracy of 0.6 pH units. The purpose of this study was to develop realistic phantom models of the intracellular environment of metastatic breast tumour and naïve brain, and using these models determine an analysis metric for quantification of CEST MRI data that is sensitive to only labile proton exchange rate and concentration. The ability of the optimal metric to quantify pH differences in the phantoms was also evaluated. Novel phantom models were produced, by adding perchloric acid extracts of either metastatic mouse breast carcinoma cells or healthy mouse brain to bovine serum albumin. The phantom model was validated using 1H NMR spectroscopy, then utilized to determine the sensitivity of CEST MRI to changes in pH, labile proton concentration, T1 time and T2 time; six different CEST MRI analysis metrics (MTRasym, APT*, MTRRex, AREX and CESTR* with and without T1/T2 compensation) were compared. The new phantom models were highly representative of the in vivo intracellular environment of both tumour and brain tissue. Of the analysis methods compared, CESTR* with T1 and T2 time compensation was optimally specific to changes in the CEST effect (i.e. minimal contamination from T1 or T2 variation). In phantoms with identical protein concentrations, pH differences between phantoms could be quantified with a mean accuracy of 0.6 pH units. We propose that CESTR* with T1 and T2 time compensation is the optimal analysis method for these phantoms. Analysis of CEST MRI data with T1/T2 time compensated CESTR* is reproducible between phantoms, and its application in vivo may resolve the intracellular alkalosis associated with breast cancer brain metastases without the need for exogenous contrast agents. Novel biologically relevant phantom models of the intracellular environment of metastatic breast tumour and naïve brain were produced, and used to determine an optimally sensitive and specific analysis metric for quantification of pH from CEST MRI data. Of the analysis methods compared, CESTR* with T1 and T2 time compensation was optimally specific to changes in the CEST effect (i.e. minimal contamination from T1 or T2 variation), with the ability to measure quantitative differences in pH with an accuracy of 0.6 pH units. The purpose of this study was to develop realistic phantom models of the intracellular environment of metastatic breast tumour and naïve brain, and using these models determine an analysis metric for quantification of CEST MRI data that is sensitive to only labile proton exchange rate and concentration. The ability of the optimal metric to quantify pH differences in the phantoms was also evaluated. Novel phantom models were produced, by adding perchloric acid extracts of either metastatic mouse breast carcinoma cells or healthy mouse brain to bovine serum albumin. The phantom model was validated using 1 H NMR spectroscopy, then utilized to determine the sensitivity of CEST MRI to changes in pH, labile proton concentration, T 1 time and T 2 time; six different CEST MRI analysis metrics (MTR asym , APT*, MTR Rex , AREX and CESTR* with and without T 1 / T 2 compensation) were compared. The new phantom models were highly representative of the in vivo intracellular environment of both tumour and brain tissue. Of the analysis methods compared, CESTR* with T 1 and T 2 time compensation was optimally specific to changes in the CEST effect (i.e. minimal contamination from T 1 or T 2 variation). In phantoms with identical protein concentrations, pH differences between phantoms could be quantified with a mean accuracy of 0.6 pH units. We propose that CESTR* with T 1 and T 2 time compensation is the optimal analysis method for these phantoms. Analysis of CEST MRI data with T 1 / T 2 time compensated CESTR* is reproducible between phantoms, and its application in vivo may resolve the intracellular alkalosis associated with breast cancer brain metastases without the need for exogenous contrast agents. |
| Author | Ray, Kevin J. Larkin, James R. Baldwin, Andrew J. Khrapitchev, Alexandre A. Sibson, Nicola R. Barber, Michael Karunanithy, Gogulan Chappell, Michael A. Tee, Yee K. |
| AuthorAffiliation | 1 Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology University of Oxford Oxford OX3 7LE UK 2 Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science Universiti Tunku Abdul Rahman Malaysia 3 Physical and Theoretical Chemistry University of Oxford Oxford OX1 3QZ UK 4 Institute for Biomedical Engineering University of Oxford Oxford OX3 7LE UK |
| AuthorAffiliation_xml | – name: 1 Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology University of Oxford Oxford OX3 7LE UK – name: 4 Institute for Biomedical Engineering University of Oxford Oxford OX3 7LE UK – name: 2 Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science Universiti Tunku Abdul Rahman Malaysia – name: 3 Physical and Theoretical Chemistry University of Oxford Oxford OX1 3QZ UK |
| Author_xml | – sequence: 1 givenname: Kevin J. surname: Ray fullname: Ray, Kevin J. organization: Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, OX3 7LE, UK – sequence: 2 givenname: James R. surname: Larkin fullname: Larkin, James R. organization: Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, OX3 7LE, UK – sequence: 3 givenname: Yee K. surname: Tee fullname: Tee, Yee K. organization: Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia – sequence: 4 givenname: Alexandre A. surname: Khrapitchev fullname: Khrapitchev, Alexandre A. organization: Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, OX3 7LE, UK – sequence: 5 givenname: Gogulan surname: Karunanithy fullname: Karunanithy, Gogulan organization: Physical and Theoretical Chemistry, University of Oxford, Oxford, OX1 3QZ, UK – sequence: 6 givenname: Michael surname: Barber fullname: Barber, Michael organization: Physical and Theoretical Chemistry, University of Oxford, Oxford, OX1 3QZ, UK – sequence: 7 givenname: Andrew J. surname: Baldwin fullname: Baldwin, Andrew J. organization: Physical and Theoretical Chemistry, University of Oxford, Oxford, OX1 3QZ, UK – sequence: 8 givenname: Michael A. surname: Chappell fullname: Chappell, Michael A. organization: Institute for Biomedical Engineering, University of Oxford, Oxford, OX3 7LE, UK – sequence: 9 givenname: Nicola R. surname: Sibson fullname: Sibson, Nicola R. email: nicola.sibson@oncology.ox.ac.uk, nicola.sibson@oncology.ox.ac.uk organization: Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, OX3 7LE, UK |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/27686882$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1016_j_jmr_2019_106648 crossref_primary_10_3390_jimaging10070166 crossref_primary_10_3389_fneur_2018_00901 crossref_primary_10_1002_mrm_28565 crossref_primary_10_1002_nbm_4711 crossref_primary_10_1016_j_jmr_2019_01_006 crossref_primary_10_1158_0008_5472_CAN_18_2168 crossref_primary_10_1002_mrm_28212 crossref_primary_10_1016_j_nicl_2019_101833 crossref_primary_10_1002_mrm_29187 crossref_primary_10_1002_mrm_29173 crossref_primary_10_1021_acschemneuro_9b00334 |
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| Keywords | pH metastases CEST brain MRI |
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| References | Zhou J, Payen JF, Wilson DA, Traystman RJ, van Zijl PC. Using the amide proton signals of intracellular proteins and peptides to detect pH effects in MRI. Nat Med. 2003a;9:1085-1090. Dixon WT, Ren J, Lubag AJM, et al. A concentration-independent method to measure exchange rates in PARACEST agents. Magn Reson Med. 2010;63:625-632. doi: 10.1002/mrm.22242 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. doi: 10.1002/mrm.24315 Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144:646-674. doi: 10.1016/j.cell.2011.02.013 Yan K, Fu Z, Yang C, et al. Assessing amide proton transfer (APT) MRI contrast origins in 9 l gliosarcoma in the rat brain using proteomic analysis. Mol Imaging Biol. 2015;17:479-487. doi: 10.1007/s11307-015-0828-6 Zaiss M, Xu J, Goerke S, et al. Inverse Z-spectrum analysis for spillover-, MT-, and T1 -corrected steady-state pulsed CEST MRI-application to pH-weighted MRI of acute stroke. NMR Biomed. 2014;27:240-252. doi: 10.1002/nbm.3054 Zhou J, Tryggestad E, Wen Z, et al. Differentiation between glioma and radiation necrosis using molecular magnetic resonance imaging of endogenous proteins and peptides. Nat Med. 2011;17:130-134. doi: 10.1038/nm.2268 Zaiss M, Windschuh J, Paech D, et al. Relaxation-compensated CEST-MRI of the human brain at 7 T: unbiased insight into NOE and amide signal changes in human glioblastoma. Neuroimage. 2015;112:180-188. doi: 10.1016/j.neuroimage.2015.02.040 Serres S, Martin CJ, Sarmiento Soto M, et al. Structural and functional effects of metastases in rat brain determined by multimodal MRI. Integr Cancer Ther. 2014;134:885-896. doi: 10.1002/ijc.28406 Porcelli AM, Ghelli A, Zanna C, Pinton P, Rizzuto R, Rugolo M. pH difference across the outer mitochondrial membrane measured with a green fluorescent protein mutant. Biochem Biophys Res Commun. 2005;326:799-804. doi: 10.1016/j.bbrc.2004.11.105 Harston GWJ, Tee YK, Blockley N, et al. Identifying the ischaemic penumbra using pH-weighted magnetic resonance imaging. Brain. 2015;138:36-42. doi: 10.1093/brain/awu374 Goerke S, Zaiss M, Kunz P, et al. Signature of protein unfolding in chemical exchange saturation transfer imaging. NMR Biomed. 2015;28:906-913. doi: 10.1002/nbm.3317 McVicar N, Li AX, Gonçalves DF, et al. Quantitative tissue pH measurement during cerebral ischemia using amine and amide concentration-independent detection (AACID) with MRI. J Cereb Blood Flow Metab. 2014. doi: 10.1038/jcbfm.2014.12 Tee YK, Harston GWJ, Blockley N, et al. Comparing different analysis methods for quantifying the MRI amide proton transfer (APT) effect in hyperacute stroke patients. NMR Biomed. 2014;27:1019-1029. doi: 10.1002/nbm.3147 Chappell MA, Donahue MJ, Tee YK, et al. Quantitative Bayesian model-based analysis of amide proton transfer MRI. Magn Reson Med. 2013;70:556-567. Salhotra A, Lal B, Laterra J, Sun PZ, van Zijl PCM, Zhou J. Amide proton transfer imaging of 9 L gliosarcoma and human glioblastoma xenografts. NMR Biomed. 2008;21:489-497. doi: 10.1002/nbm.1216 Bhujwalla ZM, Aboagye EO, Gillies RJ, Chacko VP, Mendola CE, Backer JM. Nm23-transfected MDA-MB-435 human breast carcinoma cells form tumors with altered phospholipid metabolism and pH: a 31P nuclear magnetic resonance study in vivo and in vitro. Magn Reson Med. 1999;41:897-903. Holm S. A simple sequentially rejective multiple test procedure. Scand J Stat. 1979;6:65-70. Desmond KL, Moosvi F, Stanisz GJ. Mapping of amide, amine, and aliphatic peaks in the CEST spectra of murine xenografts at 7 T. Magn Reson Med. 2013. doi: 10.1002/mrm.24822 Banay-Schwartz M, Kenessey A, DeGuzman T, Lajtha A, Palkovits M. Protein content of various regions of rat brain and adult and aging human brain. Age. 1992;15:51-54. doi: 10.1007/BF02435024 Delaglio F, Grzesiek S, Vuister GW, Zhu G, Pfeifer J, Bax A. NMRPipe: a multidimensional spectral processing system based on UNIX pipes. J Biomol NMR. 1995;6:277-293. Zhou J, Lal B, Wilson DA, Laterra J, van Zijl PC. Amide proton transfer (APT) contrast for imaging of brain tumors. Magn Reson Med. 2003b;50:1120-1126. Sun PZ, Wang Y, Dai Z, Xiao G, Wu R. Quantitative chemical exchange saturation transfer (qCEST) MRI-RF spillover effect corrected omega plot for simultaneous determination of labile proton fraction ratio and exchange rate. Contrast Media Mol Imaging. 2014;9:268-275. doi: 10.1002/cmmi.1569 Overly CC, Lee KD, Berthiaume E, Hollenbeck PJ. Quantitative measurement of intraorganelle pH in the endosomal-lysosomal pathway in neurons by using ratiometric imaging with pyranine. Proc Natl Acad Sci U S A. 1995;92:3156-3160. van Zijl PC, Yadav NN. Chemical exchange saturation transfer (CEST): what is in a name and what isn't? Magn Reson Med. 2011;65:927-948. Gillies RJ, Raghunand N, Garcia-Martin ML, Gatenby RA. pH imaging. A review of pH measurement methods and applications in cancers. IEEE Eng Med Biol Mag. 2004;23:57-64. Xu J, Zaiss M, Zu Z, et al. On the origins of chemical exchange saturation transfer (CEST) contrast in tumors at 9.4 T. NMR Biomed. 2014;27:406-416. doi: 10.1002/nbm.3075 Jones CK, Huang A, Xu J, et al. Nuclear Overhauser enhancement (NOE) imaging in the human brain at 7 T. Neuroimage. 2013;77:114-124. doi: 10.1016/j.neuroimage.2013.03.047 Damadian R, Zaner K, Hor D, DiMaio T. Human tumors detected by nuclear magnetic resonance. Proc Natl Acad Sci U S A. 1974;71:1471-1473. doi: 10.1073/pnas.71.4.1471 Zong X, Wang P, Kim S-G, Jin T. Sensitivity and source of amine-proton exchange and amide-proton transfer magnetic resonance imaging in cerebral ischemia. Magn Reson Med. 2014;71:118-132. doi: 10.1002/mrm.24639 2015; 17 2013; 69 1995; 92 1974; 71 2004; 23 2014; 27 2013; 70 1999; 41 1992; 15 2011; 17 2010; 63 1995; 6 2003a; 9 2014; 134 2015; 28 2013; 77 2015; 138 2003b; 50 2015; 112 2005; 326 1979; 6 2011; 65 2008; 21 2014 2013 2014; 9 2014; 71 2011; 144 e_1_2_8_28_1 e_1_2_8_29_1 e_1_2_8_24_1 e_1_2_8_25_1 e_1_2_8_27_1 e_1_2_8_3_1 Holm S (e_1_2_8_26_1) 1979; 6 e_1_2_8_2_1 e_1_2_8_5_1 e_1_2_8_4_1 e_1_2_8_7_1 e_1_2_8_6_1 e_1_2_8_9_1 e_1_2_8_8_1 e_1_2_8_20_1 e_1_2_8_21_1 e_1_2_8_22_1 e_1_2_8_23_1 e_1_2_8_17_1 e_1_2_8_18_1 e_1_2_8_19_1 e_1_2_8_13_1 e_1_2_8_14_1 e_1_2_8_15_1 e_1_2_8_16_1 e_1_2_8_10_1 e_1_2_8_31_1 e_1_2_8_11_1 e_1_2_8_12_1 e_1_2_8_30_1 |
| References_xml | – reference: Dixon WT, Ren J, Lubag AJM, et al. A concentration-independent method to measure exchange rates in PARACEST agents. Magn Reson Med. 2010;63:625-632. doi: 10.1002/mrm.22242 – reference: McVicar N, Li AX, Gonçalves DF, et al. Quantitative tissue pH measurement during cerebral ischemia using amine and amide concentration-independent detection (AACID) with MRI. J Cereb Blood Flow Metab. 2014. doi: 10.1038/jcbfm.2014.12 – reference: Holm S. A simple sequentially rejective multiple test procedure. Scand J Stat. 1979;6:65-70. – reference: Sun PZ, Wang Y, Dai Z, Xiao G, Wu R. Quantitative chemical exchange saturation transfer (qCEST) MRI-RF spillover effect corrected omega plot for simultaneous determination of labile proton fraction ratio and exchange rate. Contrast Media Mol Imaging. 2014;9:268-275. doi: 10.1002/cmmi.1569 – reference: Yan K, Fu Z, Yang C, et al. Assessing amide proton transfer (APT) MRI contrast origins in 9 l gliosarcoma in the rat brain using proteomic analysis. Mol Imaging Biol. 2015;17:479-487. doi: 10.1007/s11307-015-0828-6 – reference: Salhotra A, Lal B, Laterra J, Sun PZ, van Zijl PCM, Zhou J. Amide proton transfer imaging of 9 L gliosarcoma and human glioblastoma xenografts. NMR Biomed. 2008;21:489-497. doi: 10.1002/nbm.1216 – reference: Gillies RJ, Raghunand N, Garcia-Martin ML, Gatenby RA. pH imaging. A review of pH measurement methods and applications in cancers. IEEE Eng Med Biol Mag. 2004;23:57-64. – reference: Delaglio F, Grzesiek S, Vuister GW, Zhu G, Pfeifer J, Bax A. NMRPipe: a multidimensional spectral processing system based on UNIX pipes. J Biomol NMR. 1995;6:277-293. – reference: Damadian R, Zaner K, Hor D, DiMaio T. Human tumors detected by nuclear magnetic resonance. Proc Natl Acad Sci U S A. 1974;71:1471-1473. doi: 10.1073/pnas.71.4.1471 – reference: Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144:646-674. doi: 10.1016/j.cell.2011.02.013 – reference: 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. doi: 10.1002/mrm.24315 – reference: Zaiss M, Xu J, Goerke S, et al. Inverse Z-spectrum analysis for spillover-, MT-, and T1 -corrected steady-state pulsed CEST MRI-application to pH-weighted MRI of acute stroke. NMR Biomed. 2014;27:240-252. doi: 10.1002/nbm.3054 – reference: Tee YK, Harston GWJ, Blockley N, et al. Comparing different analysis methods for quantifying the MRI amide proton transfer (APT) effect in hyperacute stroke patients. NMR Biomed. 2014;27:1019-1029. doi: 10.1002/nbm.3147 – reference: Chappell MA, Donahue MJ, Tee YK, et al. Quantitative Bayesian model-based analysis of amide proton transfer MRI. Magn Reson Med. 2013;70:556-567. – reference: Banay-Schwartz M, Kenessey A, DeGuzman T, Lajtha A, Palkovits M. Protein content of various regions of rat brain and adult and aging human brain. Age. 1992;15:51-54. doi: 10.1007/BF02435024 – reference: Xu J, Zaiss M, Zu Z, et al. On the origins of chemical exchange saturation transfer (CEST) contrast in tumors at 9.4 T. NMR Biomed. 2014;27:406-416. doi: 10.1002/nbm.3075 – reference: Porcelli AM, Ghelli A, Zanna C, Pinton P, Rizzuto R, Rugolo M. pH difference across the outer mitochondrial membrane measured with a green fluorescent protein mutant. Biochem Biophys Res Commun. 2005;326:799-804. doi: 10.1016/j.bbrc.2004.11.105 – reference: Serres S, Martin CJ, Sarmiento Soto M, et al. Structural and functional effects of metastases in rat brain determined by multimodal MRI. Integr Cancer Ther. 2014;134:885-896. doi: 10.1002/ijc.28406 – reference: Overly CC, Lee KD, Berthiaume E, Hollenbeck PJ. Quantitative measurement of intraorganelle pH in the endosomal-lysosomal pathway in neurons by using ratiometric imaging with pyranine. Proc Natl Acad Sci U S A. 1995;92:3156-3160. – reference: Zhou J, Lal B, Wilson DA, Laterra J, van Zijl PC. Amide proton transfer (APT) contrast for imaging of brain tumors. Magn Reson Med. 2003b;50:1120-1126. – reference: Zong X, Wang P, Kim S-G, Jin T. Sensitivity and source of amine-proton exchange and amide-proton transfer magnetic resonance imaging in cerebral ischemia. Magn Reson Med. 2014;71:118-132. doi: 10.1002/mrm.24639 – reference: Desmond KL, Moosvi F, Stanisz GJ. Mapping of amide, amine, and aliphatic peaks in the CEST spectra of murine xenografts at 7 T. Magn Reson Med. 2013. doi: 10.1002/mrm.24822 – reference: Harston GWJ, Tee YK, Blockley N, et al. Identifying the ischaemic penumbra using pH-weighted magnetic resonance imaging. Brain. 2015;138:36-42. doi: 10.1093/brain/awu374 – reference: Zhou J, Tryggestad E, Wen Z, et al. Differentiation between glioma and radiation necrosis using molecular magnetic resonance imaging of endogenous proteins and peptides. Nat Med. 2011;17:130-134. doi: 10.1038/nm.2268 – reference: Bhujwalla ZM, Aboagye EO, Gillies RJ, Chacko VP, Mendola CE, Backer JM. Nm23-transfected MDA-MB-435 human breast carcinoma cells form tumors with altered phospholipid metabolism and pH: a 31P nuclear magnetic resonance study in vivo and in vitro. Magn Reson Med. 1999;41:897-903. – reference: Goerke S, Zaiss M, Kunz P, et al. Signature of protein unfolding in chemical exchange saturation transfer imaging. NMR Biomed. 2015;28:906-913. doi: 10.1002/nbm.3317 – reference: Jones CK, Huang A, Xu J, et al. Nuclear Overhauser enhancement (NOE) imaging in the human brain at 7 T. Neuroimage. 2013;77:114-124. doi: 10.1016/j.neuroimage.2013.03.047 – reference: Zhou J, Payen JF, Wilson DA, Traystman RJ, van Zijl PC. Using the amide proton signals of intracellular proteins and peptides to detect pH effects in MRI. Nat Med. 2003a;9:1085-1090. – reference: van Zijl PC, Yadav NN. Chemical exchange saturation transfer (CEST): what is in a name and what isn't? Magn Reson Med. 2011;65:927-948. – reference: Zaiss M, Windschuh J, Paech D, et al. Relaxation-compensated CEST-MRI of the human brain at 7 T: unbiased insight into NOE and amide signal changes in human glioblastoma. 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A review of pH measurement methods and applications in cancers publication-title: IEEE Eng Med Biol Mag – volume: 27 start-page: 406 year: 2014 end-page: 416 article-title: On the origins of chemical exchange saturation transfer (CEST) contrast in tumors at 9.4 T publication-title: NMR Biomed – volume: 134 start-page: 885 year: 2014 end-page: 896 article-title: Structural and functional effects of metastases in rat brain determined by multimodal MRI publication-title: Integr Cancer Ther – volume: 28 start-page: 906 year: 2015 end-page: 913 article-title: Signature of protein unfolding in chemical exchange saturation transfer imaging publication-title: NMR Biomed – volume: 27 start-page: 240 year: 2014 end-page: 252 article-title: Inverse Z‐spectrum analysis for spillover‐, MT‐, and T1 ‐corrected steady‐state pulsed CEST MRI—application to pH‐weighted MRI of acute stroke publication-title: NMR Biomed – volume: 71 start-page: 1471 year: 1974 end-page: 1473 article-title: Human tumors detected by nuclear magnetic resonance publication-title: Proc Natl Acad Sci U S A – ident: e_1_2_8_21_1 doi: 10.1002/(SICI)1522-2594(199905)41:5<897::AID-MRM7>3.0.CO;2-T – ident: e_1_2_8_31_1 doi: 10.1073/pnas.92.8.3156 – ident: e_1_2_8_29_1 doi: 10.1002/mrm.24639 – ident: e_1_2_8_10_1 doi: 10.1109/MEMB.2004.1360409 – ident: e_1_2_8_14_1 doi: 10.1002/mrm.24474 – ident: e_1_2_8_9_1 doi: 10.1016/j.cell.2011.02.013 – ident: e_1_2_8_13_1 doi: 10.1002/nbm.3075 – volume: 6 start-page: 65 year: 1979 ident: e_1_2_8_26_1 article-title: A simple sequentially rejective multiple test procedure publication-title: Scand J Stat – ident: e_1_2_8_5_1 doi: 10.1016/j.neuroimage.2015.02.040 – ident: e_1_2_8_2_1 doi: 10.1038/nm907 – ident: e_1_2_8_17_1 doi: 10.1002/nbm.3054 – ident: e_1_2_8_4_1 doi: 10.1002/nbm.3147 – ident: e_1_2_8_30_1 doi: 10.1016/j.bbrc.2004.11.105 – ident: e_1_2_8_23_1 doi: 10.1007/BF02435024 – ident: e_1_2_8_19_1 doi: 10.1016/j.neuroimage.2013.03.047 – ident: e_1_2_8_3_1 doi: 10.1002/mrm.22761 – ident: e_1_2_8_18_1 doi: 10.1002/mrm.24822 – ident: e_1_2_8_16_1 doi: 10.1002/mrm.22242 – ident: e_1_2_8_27_1 doi: 10.1073/pnas.71.4.1471 – ident: e_1_2_8_6_1 doi: 10.1038/nm.2268 – ident: e_1_2_8_8_1 doi: 10.1093/brain/awu374 – ident: e_1_2_8_7_1 doi: 10.1002/nbm.3317 – ident: e_1_2_8_20_1 doi: 10.1002/ijc.28406 – ident: e_1_2_8_11_1 doi: 10.1002/mrm.10651 – ident: e_1_2_8_24_1 doi: 10.1007/BF00197809 – ident: e_1_2_8_25_1 doi: 10.1002/mrm.24315 – ident: e_1_2_8_12_1 doi: 10.1002/nbm.1216 – ident: e_1_2_8_28_1 doi: 10.1007/s11307-015-0828-6 – ident: e_1_2_8_15_1 doi: 10.1002/cmmi.1569 – ident: e_1_2_8_22_1 doi: 10.1038/jcbfm.2014.12 |
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| SubjectTerms | Algorithms Animals brain CEST Equipment Design Hydrogen-Ion Concentration Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Magnetic Resonance Imaging - instrumentation Magnetic Resonance Imaging - methods metastases Mice Molecular Imaging - instrumentation Molecular Imaging - methods MRI Neoplasms, Experimental - chemistry Neoplasms, Experimental - diagnostic imaging Neoplasms, Experimental - pathology Phantoms, Imaging Proton Magnetic Resonance Spectroscopy - methods Reproducibility of Results Sensitivity and Specificity Signal Processing, Computer-Assisted |
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| Title | Determination of an optimally sensitive and specific chemical exchange saturation transfer MRI quantification metric in relevant biological phantoms |
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