Multiparametric statistical quantification of pH heterogeneity by 1 H MRS and MRSI of extracellular pH markers: Proof of principle

: Acid production and transport in numerous biological tissues and medical conditions are active areas of research. Heterogeneity of pH within a given homogeneous-appearing tissue volume has been reported, but none of the conventional methods currently available for measuring tissue pH provides quantitative parameters describing the frequency of occurrence of pH values within such a volume. We have previously presented a multiparametric noninvasive in vivo approach, providing at least 10 different statistical descriptors of pH heterogeneity based on a novel type of line shape analysis developed for pH-sensitive 31 P MRS resonances. However, this method suffers from lack of sensitivity, thus making rapid and spatially resolved measurements difficult. We present here the proof of principle of a new, more sensitive approach to statistical characterization of extracellular pH heterogeneity based on 1 H MRS, with the potential of being combined with spatial resolution. We experimentally study a range of test solutions of a reporter molecule that has previously been shown to possess a 1 H MRS resonance whose chemical shift varies with pH, including when injected intravenously into experimental animals (imidazole ethoxycarbonylpropionic acid, [IEPA]). Statistical pH heterogeneity descriptors are determined for phantoms mimicking tissue pH heterogeneity. To this end, the pH-sensitive 1 H MRS resonance is transformed into a pH curve. Subsequently, the digital points of this pH profile are used to build a histogram using dedicated algorithms. The following descriptors are computed from this histogram: weighted mean pH and median pH, pH standard deviation, pH range, pH mode(s), pH kurtosis, pH skewness and pH entropy. Our new method is also validated by analyzing previously published in vivo MRSI spectra. The proof of principle provided in this work should form the basis of further in vivo studies in physiology and medicine, eg in cancer research, but also in other fields such as kidney and muscle research.