In the tumor microenvironment, the combination of compromised oxygen supply and high demand results in formation of regions of acute and chronic hypoxia, which promotes metastasis, proliferation, resistance to chemo and radiotherapy and poor prognosis. Targeted, non-invasive in vivo imaging of hypoxia has the potential to determine regions with poor oxygenation in the target and differentiate between normoxic vs hypoxic tissues. MRI provides a powerful platform for generating quantitative maps of hypoxia with the use of a novel pO<sub>2</sub> measuring technique PISTOL (Proton imaging of siloxanes to map tissue oxygenation levels) which could impact the therapeutic choices. In the present study, PISTOL was used to determine the changes in oxygenation of tumor in pre-clinical models of NSCLC (H1975) and epidermoid carcinoma (A431) in response to tirapzamine (TPZ), a hypoxia activated chemotherapeutic. The tumor volume measurements indicate that tirapazamine was more effective in slowing the tumor growth in H1975 as compared to A431 tumors, even though lower baseline pO<sub>2 </sub>was observed in A431 as compared to H1975 tumors. These results indicate that other factors such as tumor perfusion (essential for delivering TPZ) and relative expression of nitroreductases (essential for activating TPZ) may play an important role in conjunction with pO<sub>2</sub>.
Imaging lactate metabolism <i>in vivo </i>may improve cancer targeting and therapeutics due to its key role in the development, maintenance, and metastasis of cancer. The long acquisition times associated with magnetic resonance spectroscopic imaging (MRSI), which is a useful technique for assessing metabolic concentrations, are a deterrent to its routine clinical use. The objective of this study was to combine spectral editing and prospective compressed sensing (CS) acquisitions to enable precise and high-speed imaging of the lactate resonance. A MRSI pulse sequence with two key modifications was developed: (1) spectral editing components for selective detection of lactate, and (2) a variable density sampling mask for pseudo-random under-sampling of the k-space ‘on the fly’. The developed sequence was tested on phantoms and<i> in vivo </i>in rodent models of cancer. Datasets corresponding to the 1X (fully-sampled), 2X, 3X, 4X, 5X, and 10X accelerations were acquired. The under-sampled datasets were reconstructed using a custom-built algorithm in Matlab<sup>TM</sup>, and the fidelity of the CS reconstructions was assessed in terms of the peak amplitudes, SNR, and total acquisition time. The accelerated reconstructions demonstrate a reduction in the scan time by up to 90% <i>in vitro </i>and up to 80% <i>in vivo</i>, with negligible loss of information when compared with the fully-sampled dataset. The proposed unique combination of spectral editing and CS facilitated rapid mapping of the spatial distribution of lactate at high temporal resolution. This technique could potentially be translated to the clinic for the routine assessment of lactate changes in solid tumors.