Compressed sensing (CS) can accelerate magnetic resonance spectroscopic imaging (MRSI), facilitating its widespread clinical integration. The objective of this study was to assess the effect of different undersampling strategy on CS-MRSI reconstruction quality. Phantom data were acquired on a Philips 3 T Ingenia scanner. Four types of undersampling masks, corresponding to each strategy, namely, low resolution, variable density, iterative design, and <i>a priori </i>were simulated in Matlab and retrospectively applied to the test 1X MRSI data to generate undersampled datasets corresponding to the 2X – 5X, and 7X accelerations for each type of mask. Reconstruction parameters were kept the same in each case(all masks and accelerations) to ensure that any resulting differences can be attributed to the type of mask being employed. The reconstructed datasets from each mask were statistically compared with the reference 1X, and assessed using metrics like the root mean square error and metabolite ratios. Simulation results indicate that both the <i>a priori </i>and variable density undersampling masks maintain high fidelity with the 1X up to five-fold acceleration. The low resolution mask based reconstructions showed statistically significant differences from the 1X with the reconstruction failing at 3X, while the iterative design reconstructions maintained fidelity with the 1X till 4X acceleration. In summary, a pilot study was conducted to identify an optimal sampling mask in CS-MRSI. Simulation results demonstrate that the <i>a priori </i>and variable density masks can provide statistically similar results to the fully sampled reference. Future work would involve implementing these two masks prospectively on a clinical scanner.
Tissue oximetry studies using magnetic resonance imaging are increasingly contributing to advances in the imaging and treatment of cancer. The non-invasive measurement of tissue oxygenation (pO<sub>2</sub>) may facilitate a better understanding of the pathophysiology and prognosis of diseases, particularly in the assessment of the extensive hypoxic regions associated with cancerous lesions. The availability of tumor hypoxia maps could help quantify and predict tumor response to intervention and therapy. The PISTOL (<strong>P</strong>roton <strong>I</strong>maging of <strong>S</strong>iloxanes to map <strong>T</strong>issue <strong>O</strong>xygenation <strong>L</strong>evels) oximetry technique maps the T<sub>1</sub> of administered hexamethyldisiloxane (HMDSO), an <sup>1</sup>H NMR pO<sub>2</sub> reporter molecule in about 3 ½ min. This allows us to subsequently monitor static and dynamic changes in the tissue pO<sub>2</sub> (in response to intervention) at various locations due to the linear relationship between 1/T<sub>1</sub> and pO<sub>2</sub>. In this work, an HMDSO-selective Look-Locker imaging sequence with EPI readout has been developed to enable faster PISTOL acquisitions. The new sequence incorporates the fast Look-Locker measurement method to enable T<sub>1</sub>, and hence, pO<sub>2</sub> mapping of HMDSO in under one minute. To demonstrate the application of this pulse sequence <i>in vivo</i>, 50 μL of neat HMDSO was administered to the thigh muscle of a healthy rat (Fischer F344, n=4). Dynamic changes in the mean pO<sub>2</sub> of the thigh muscle were measured using both PISTOL and the developed LL oximetry sequence in response to oxygen challenge and compared. Results demonstrate the efficacy of the new sequence in rapidly mapping the pO<sub>2 </sub>changes, leading to advances in fast quantitative <sup>1</sup>H MR oximetry.
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.
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>.