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 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 using1H NMR spectroscopy, then utilized to determine the sensitivity of CEST MRI to changes in pH, labile proton concentration, T1time and T2time; six different CEST MRI analysis metrics (MTRasym, APT*, MTRRex, AREX and CESTR* with and without T1/T2compensation) 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 T1and T2time compensation was optimally specific to changes in the CEST effect (i.e. minimal contamination from T1or T2variation). 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 T1and T2time compensation is the optimal analysis method for these phantoms. Analysis of CEST MRI data with T1/T2time 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.
Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, OX3 7LE, UK.
Kevin J
KJ
Ray
Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, OX3 7LE, UK.
James R
JR
Larkin
Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia.
Yee K
YK
Tee
Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, OX3 7LE, UK.
Alexandre A
AA
Khrapitchev
Physical and Theoretical Chemistry, University of Oxford, Oxford, OX1 3QZ, UK.
Gogulan
G
Karunanithy
Physical and Theoretical Chemistry, University of Oxford, Oxford, OX1 3QZ, UK.
Michael
M
Barber
Physical and Theoretical Chemistry, University of Oxford, Oxford, OX1 3QZ, UK.
Andrew J
AJ
Baldwin
Institute for Biomedical Engineering, University of Oxford, Oxford, OX3 7LE, UK.
Michael A
MA
Chappell
Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, OX3 7LE, UK. nicola.sibson@oncology.ox.ac.uk.
Nicola R
NR
Sibson
D000465:Algorithms; D000818:Animals; D004867:Equipment Design; D006863:Hydrogen-Ion Concentration; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000295:instrumentation* / Q000379:methods; D051379:Mice; D057054:Molecular Imaging / Q000295:instrumentation* / Q000379:methods; D009374:Neoplasms, Experimental / Q000737:chemistry* / Q000000981:diagnostic imaging / Q000473:pathology; D019047:Phantoms, Imaging; D066244:Proton Magnetic Resonance Spectroscopy / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted
CEST; MRI; brain; metastases; pH
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