Determination of an optimally sensitive and specific chemical exchange saturation transfer MRI quantification metric in relevant biological phantoms

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, 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.

Tumor pH and Protein Concentration Contribute to the Signal of Amide Proton Transfer Magnetic Resonance Imaging

“…Correction for water T 1 and T 2 effects was implemented by allowing BayCEST to fit water T 1 and T 2 from the data, with prior values set based on the average T 1 and T 2 time within the whole rat brain or whole tumour for mice, yielding an APTR* value that is sensitive only to amide proton concentration and exchange rate (which is itself proportional to 10 pH ). A previous study (30) has shown that APTR* quantified using this analysis approach is specific to changes in protein concentration and pH in biologically relevant phantoms. The exchange rate and concentration estimated by BayCEST were used to generate an idealised two-pool Z-spectrum, and APTR* calculated using equation 1.…”

“…The APT effect from the measured CEST MRI data was quantified using the APTR* metric as described previously (25,28–30). Briefly, data were fit to the Bloch-McConell equations using BayCEST in the FMRIB Software Library (FSL; https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/baycest) assuming a 3-pool exchange model comprising water, amide protons at 3.5 ppm, and a combined NOE+MT pool at -2.41 ppm.…”

APT Weighted MRI as an Effective Imaging Protocol to Predict Clinical Outcome After Acute Ischemic Stroke

“…In study conducted by Sun et al APTW signal was significantly decrease in the ischemic region as the T1 was significantly increased compared with the contralateral normal area. In fact, more precise methods, including model-based approach ( 37 ), inverse metric approach ( 34 ) and T 1 / T 2 time compensated CESTR ( 38 ) have been used, which makes APT imaging more sensitive. Second, the sample size was relatively small and further investigations that involve a larger sample size are required.…”

Does the magnetization transfer effect bias chemical exchange saturation transfer effects? Quantifying chemical exchange saturation transfer in the presence of magnetization transfer

“…Previous studies have either quantified the MT effect using a qMT model, and then applied the qMT parameter estimates into a CEST analysis, or simply included the MT effect as an additional pool in a multi‐pool Lorentzian‐lineshape analysis, preventing comparison of these results with existing qMT literature. To the authors’ knowledge, only one quantitative analysis method, derived from the Bloch‐McConnell equations, has been developed that quantitatively estimates both the MT and CEST parameters simultaneously . Unfortunately, this methodology has not yet been used to explicitly measure the MT effect, instead modeling it as a combined term with nuclear Overhauser effect‐relayed exchange (NOE) .…”