Clinical Translation of Tumor Acidosis Measurements with AcidoCEST MRI

Purpose We optimized acido-chemical exchange saturation transfer (acidoCEST) magnetic resonance imaging (MRI), a method that measures extracellular pH (pHe), and translated this method to the radiology clinic to evaluate tumor acidosis. Procedures A CEST-FISP MRI protocol was used to image a flank S...

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Veröffentlicht in:Molecular imaging and biology 2017-08, Vol.19 (4), p.617-625
Hauptverfasser: Jones, Kyle M., Randtke, Edward A., Yoshimaru, Eriko S., Howison, Christine M., Chalasani, Pavani, Klein, Robert R., Chambers, Setsuko K., Kuo, Phillip H., Pagel, Mark D.
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Sprache:eng
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Zusammenfassung:Purpose We optimized acido-chemical exchange saturation transfer (acidoCEST) magnetic resonance imaging (MRI), a method that measures extracellular pH (pHe), and translated this method to the radiology clinic to evaluate tumor acidosis. Procedures A CEST-FISP MRI protocol was used to image a flank SKOV3 tumor model. Bloch fitting modified to include the direct estimation of pH was developed to generate parametric maps of tumor pHe in the SKOV3 tumor model, a patient with high-grade invasive ductal carcinoma, and a patient with metastatic ovarian cancer. The acidoCEST MRI results of the patient with metastatic ovarian cancer were compared with DCE MRI and histopathology. Results The pHe maps of a flank model showed pHe measurements between 6.4 and 7.4, which matched with the expected tumor pHe range from past acidoCEST MRI studies in flank tumors. In the patient with metastatic ovarian cancer, the average pHe value of three adjacent tumors was 6.58, and the most reliable pHe measurements were obtained from the right posterior tumor, which favorably compared with DCE MRI and histopathological results. The average pHe of the kidney showed an average pHe of 6.73 units. The patient with high-grade invasive ductal carcinoma failed to accumulate sufficient agent to generate pHe measurements. Conclusions Optimized acidoCEST MRI generated pHe measurements in a flank tumor model and could be translated to the clinic to assess a patient with metastatic ovarian cancer.
ISSN:1536-1632
1860-2002
DOI:10.1007/s11307-016-1029-7