Fast and sensitive dynamic oxygen-enhanced MRI with a cycling gas challenge and independent component analysis.

Abstract

There is a critical need for non-invasive imaging biomarkers of tumor oxygenation to assist in patient stratification and development of hypoxia targeting therapies. Using a cycling gas challenge and independent component analysis (ICA), we sought to improve the sensitivity and speed of existing oxygen enhanced MRI (OE-MRI) techniques to detect changes in oxygenation with dynamically acquired T1 W signal intensity images (dOE-MRI). Mice were implanted with SCCVII, HCT-116, BT-474, or SKOV3 tumors in the dorsal subcutaneous region and imaged at 7T. T1 W images were acquired during a respiratory challenge with alternating 2-minute periods of air and 100% oxygen for three cycles. Data were analyzed with ICA and oxygenation maps were generated and compared to corresponding histology sections stained for hypoxia (pimonidazole) and blood vessels (CD31). Cycling air-oxygen-air gas challenges were well tolerated and ICA permitted extraction of the oxygen-enhancing component in all imaged tumors from four different models. Comparison with synthetic response functions showed that dOE-MRI does not require any a-priori knowledge of the physiological response. The fraction of O2 -negative dOE-MRI voxels that correlate inversely with the ICA gas-cycling component correspond well with the histological hypoxic fraction in SCCVII tumors (r=0.91, p=0.0016) but did not correlate in HCT-116 tumors (r=0.13, p=0.81). Using ICA and adding a cycling gas challenge extends the sensitivity of OE-MRI and allows the oxygenation status of tumors to be assessed in as little as six minutes. These findings support further development of OE-MRI as a biomarker of tumor oxygenation.