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High-Resolution Imaging of Extracellular pH in Mouse Liver Tumor
Jessica Gois Santana1, Sara Kurdi1, Lisa Marie Helene Peschke2,3
1Department of Biomedical Engineering, Yale University, New Haven, Connecticut, USA.
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Extracellular acidosis is a biologically important feature of the tumor microenvironment in the liver, promoting immune evasion, angiogenesis, and resistance to therapy, and representing a mechanistically important and potentially targetable axis in liver cancer. Imaging extracellular pH (pHe) at high resolution is needed to better understand the immuno-metabolic interplay, especially at the transition regions between the tumor core, tumor margin, and background liver, which is critical for any pharmacological or image-guided intervention. Yet, there is a paucity of imaging techniques capable of providing pHe mapping at high resolution. Here, we demonstrate high-resolution pHe imaging in a mouse Hepa1-6 liver tumor model using 1H Biosensor Imaging of Redundant Deviation in Shifts (BIRDS) with REduced Spherical Encoding with GAussian Weighting (RESEGAW). Eight tumor-bearing C57BL/6J mice were used to demonstrate pHe imaging with RESEGAW using the macrocyclic agent TmDOTP5- at 0.6 mm isotropic resolution on a 9.4 T scanner, which was validated using 31P-MRSI with 3-aminopropylphosphonate (3-APP). pHe imaging with 1H-BIRDS-RESEGAW consistently showed acidic tumor regions (pHe = 6.77 ± 0.14) relative to adjacent normal liver (pHe = 7.14 ± 0.07). Mean pHe values measured by 31P-MRSI with 3-APP and 1H-BIRDS-RESEGAW with TmDOTP5- show no significant differences in tumors (pHe = 6.81 ± 0.13) and normal liver (pHe = 7.14 ± 0.06). Voxelwise comparison after co-registration of 31P-MRSI with 3-APP to 1H-BIRDS-RESEGAW using Bland-Altman analysis demonstrated excellent agreement between the two methods, with minimal mean bias (-0.005 pH units) and variance of less than 0.1 pH units. These results demonstrate the feasibility and quantitative reliability of 1H-BIRDS-RESEGAW for imaging extracellular acidosis in liver tumors at submillimeter resolution, establishing a technical foundation for studying the immuno-metabolic interplay in liver cancer and its response to therapy.
