Authors
Jessica Gois Santana, Sara Kurdi, Lisa Marie Helene Peschke, Sandeep Kumar Mishra, Fahmeed Hyder, Julius Chapiro, Daniel Coman
Published in
NMR in biomedicine. Volume 39. Issue 9. Pages e70375.
Abstract
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.
PMID:
42619234
Bibliographic data and abstract were imported from PubMed on 20 Aug 2026.
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