Effect of inhaled oxygen level on dynamic glucose-enhanced MRI in mouse brain.

PURPOSE: To investigate the effect of inhaled oxygen level on dynamic glucose enhanced (DGE) MRI in mouse brain tissue and CSF at 3 T. METHODS: DGE data of brain tissue and CSF from mice under normoxia or hyperoxia were acquired in independent and interleaved experiments using on-resonance variable delay multi-pulse (onVDMP) MRI. A bolus of 0.15 mL filtered 50% D-glucose was injected through the tail vein over 1 min during DGE acquisition. MRS was acquired before and after DGE experiments to confirm the presence of D-glucose. RESULTS: A significantly higher DGE effect under normoxia than under hyperoxia was observed in brain tissue (p = 0.0001 and p = 0.0002 for independent and interleaved experiments, respectively), but not in CSF (p > 0.3). This difference is attributed to the increased baseline MR tissue signal under hyperoxia induced by a shortened T1 and an increased BOLD effect. When switching from hyperoxia to normoxia without glucose injection, a signal change of ˜3.0% was found in brain tissue and a signal change of ˜1.5% was found in CSF. CONCLUSIONS: DGE signal was significantly lower under hyperoxia than that under normoxia in brain tissue, but not in CSF. The reason is that DGE effect size of brain tissue is affected by the baseline signal, which could be influenced by T1 change and BOLD effect. Therefore, DGE experiments in which the oxygenation level is changed from baseline need to be interpreted carefully.

Deep-learning-based super-resolution for accelerating chemical exchange saturation transfer MRI.

Chemical exchange saturation transfer (CEST) MRI is a molecular imaging tool that provides physiological information about tissues, making it an invaluable tool for disease diagnosis and guided treatment. Its clinical application requires the acquisition of high-resolution images capable of accurately identifying subtle regional changes in vivo, while simultaneously maintaining a high level of spectral resolution. However, the acquisition of such high-resolution images is time consuming, presenting a challenge for practical implementation in clinical settings. Among several techniques that have been explored to reduce the acquisition time in MRI, deep-learning-based super-resolution (DLSR) is a promising approach to address this problem due to its adaptability to any acquisition sequence and hardware. However, its translation to CEST MRI has been hindered by the lack of the large CEST datasets required for network development. Thus, we aim to develop a DLSR method, named DLSR-CEST, to reduce the acquisition time for CEST MRI by reconstructing high-resolution images from fast low-resolution acquisitions. This is achieved by first pretraining the DLSR-CEST on human brain T1w and T2w images to initialize the weights of the network and then training the network on very small human and mouse brain CEST datasets to fine-tune the weights. Using the trained DLSR-CEST network, the reconstructed CEST source images exhibited improved spatial resolution in both peak signal-to-noise ratio and structural similarity index measure metrics at all downsampling factors (2-8). Moreover, amide CEST and relayed nuclear Overhauser effect maps extrapolated from the DLSR-CEST source images exhibited high spatial resolution and low normalized root mean square error, indicating a negligible loss in Z-spectrum information. Therefore, our DLSR-CEST demonstrated a robust reconstruction of high-resolution CEST source images from fast low-resolution acquisitions, thereby improving the spatial resolution and preserving most Z-spectrum information.

Preclinical Application of CEST MRI to Detect Early and Regional Tumor Response to Local Brain Tumor Treatment.

Treating glioblastoma and monitoring treatment response non-invasively remain challenging. Here, we developed a robust approach using a drug-loaded liposomal hydrogel that is mechanically compatible with the brain, and, simultaneously, we successfully monitored early tumor response using Chemical Exchange Saturation Transfer (CEST) MRI. This CEST-detectable liposomal hydrogel was optimized based on a sustainable drug release and a soft hydrogel for the brain tumor, which is unfavorable for tumor cell proliferation. After injecting the hydrogel next to the tumor, three distinctive CEST contrasts enabled the monitoring of tumor response and drug release longitudinally at 3T. As a result, a continuous tumor volume decrease was observed in the treatment group along with a significant decrease in CEST contrasts relating to the tumor response at 3.5 ppm (Amide Proton Transfer; APT) and at -3.5 ppm (relayed Nuclear Overhauser Effect; rNOE) when compared to the control group (p < 0.05). Interestingly, the molecular change at 3.5 ppm on day 3 (p < 0.05) was found to be prior to the significant decrease in tumor volume on day 5. An APT signal also showed a strong correlation with the number of proliferating cells in the tumors. This demonstrated that APT detected a distinctive decrease in mobile proteins and peptides in tumors before the change in tumor morphology. Moreover, the APT signal showed a regional response to the treatment, associated with proliferating and apoptotic cells, which allowed an in-depth evaluation and prediction of the tumor treatment response. This newly developed liposomal hydrogel allows image-guided brain tumor treatment to address clinical needs using CEST MRI.

Molecular Imaging of Brain Tumors and Drug Delivery Using CEST MRI: Promises and Challenges.

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) detects molecules in their natural forms in a sensitive and non-invasive manner. This makes it a robust approach to assess brain tumors and related molecular alterations using endogenous molecules, such as proteins/peptides, and drugs approved for clinical use. In this review, we will discuss the promises of CEST MRI in the identification of tumors, tumor grading, detecting molecular alterations related to isocitrate dehydrogenase (IDH) and O-6-methylguanine-DNA methyltransferase (MGMT), assessment of treatment effects, and using multiple contrasts of CEST to develop theranostic approaches for cancer treatments. Promising applications include (i) using the CEST contrast of amide protons of proteins/peptides to detect brain tumors, such as glioblastoma multiforme (GBM) and low-grade gliomas; (ii) using multiple CEST contrasts for tumor stratification, and (iii) evaluation of the efficacy of drug delivery without the need of metallic or radioactive labels. These promising applications have raised enthusiasm, however, the use of CEST MRI is not trivial. CEST contrast depends on the pulse sequences, saturation parameters, methods used to analyze the CEST spectrum (i.e., Z-spectrum), and, importantly, how to interpret changes in CEST contrast and related molecular alterations in the brain. Emerging pulse sequence designs and data analysis approaches, including those assisted with deep learning, have enhanced the capability of CEST MRI in detecting molecules in brain tumors. CEST has become a specific marker for tumor grading and has the potential for prognosis and theranostics in brain tumors. With increasing understanding of the technical aspects and associated molecular alterations detected by CEST MRI, this young field is expected to have wide clinical applications in the near future.

Monitor Tumor pHe and Response Longitudinally during Treatment Using CEST MRI-Detectable Alginate Microbeads.

Imaging pHe of the tumor microenvironment has paramount importance for characterizing aggressive, invasive tumors, as well as therapeutic responses. Here, a robust approach to image pH changes in the tumor microenvironment longitudinally and during sodium bicarbonate treatment was reported. The pH-sensing microbeads were designed and prepared based on materials approved for clinical use, i.e., alginate microbead-containing computed tomography (CT) contrast-agent (iopamidol)-loaded liposomes (Iop-lipobeads). This Iop-lipobead prepared using a customized microfluidic device generated a CEST contrast of 10.6% at 4.2 ppm at pH 7.0, which was stable for 20 days in vitro. The CEST contrast decreased by 11.8% when the pH decreased from 7.0 to 6.5 in vitro. Optimized Iop-lipobeads next to tumors showed a significant increase of 19.7 ± 6.1% (p < 0.01) in CEST contrast at 4.2 ppm during the first 3 days of treatment and decreased to 15.2 ± 4.8% when treatment stopped. Notably, percentage changes in Iop-lipobeads were higher than that of amide CEST (11.7% and 9.1%) in tumors during and after treatment. These findings demonstrated that the Iop-lipobead could provide an independent and sensitive assessment of the pHe changes for a noninvasive and longitudinal monitoring of the treatment effects using multiple CEST contrast.

Imaging Self-Healing Hydrogels and Chemotherapeutics Using CEST MRI at 3 T.

Imaging hydrogel-based local drug delivery to the brain after tumor resection has implications for refining treatments, especially for brain tumors with poor prognosis and high recurrence rate. Here, we developed a series of self-healing chitosan-dextran (CD)-based hydrogels for drug delivery to the brain. These hydrogels are injectable, self-healing, mechanically compatible, and detectable by chemical exchange saturation transfer magnetic resonance imaging (CEST MRI). CD hydrogels have an inherent CEST contrast at 1.1 ppm, which decreases as the stiffness increases. We further examined the rheological properties and CEST contrast of various chemotherapeutic-loaded CD hydrogels, including gemcitabine (Gem), doxorubicin, and procarbazine. Among these formulations, Gem presented the best compatibility with the rheological (G': 215.3 ± 4.5 Pa) and CEST properties of CD hydrogels. More importantly, the Gem-loaded CD hydrogel generated another CEST readout at 2.2 ppm (11.6 ± 0.1%) for monitoring Gem. This enabled independent and simultaneous imaging of the drug and hydrogel integrity using a clinically relevant 3 T MRI scanner. In addition, the Gem-loaded CD hydrogel exhibited a longitudinal antitumor efficacy of Gem over a week in vitro. Furthermore, the CD hydrogel could be visualized by CEST after brain injection with a contrast of 7.38 ± 2.31%. These natural labels on both the chemotherapeutics and hydrogels demonstrate unique image-guided local drug delivery for brain applications.