Normal brain cells depend on glucose metabolism, yet they have the flexibility to switch to the usage of ketone bodies during caloric restriction. In contrast, tumor cells lack genomic and metabolic flexibility and are largely dependent on glucose. Ketogenic-diet (KD) was suggested as a therapeutic option for malignant brain cancer. This study aimed to detect metabolic brain changes in patients with malignant brain gliomas on KD using proton magnetic-resonance-spectroscopy (H-MRS). Fifty MR scans were performed longitudinally in nine patients: four patients with recurrent glioblastoma (GB) treated with KD in addition to bevacizumab; one patient with gliomatosis-cerebri treated with KD only; and four patients with recurrent GB who did not receive KD. MR scans included conventional imaging and H-MRS acquired from normal appearing-white-matter (NAWM) and lesion. High adherence to KD was obtained only in two patients, based on high urine ketones; in these two patients ketone bodies, Acetone and Acetoacetate were detected in four MR spectra-three within the NAWM and one in the lesion area -4 and 25 months following initiation of the diet. No ketone-bodies were detected in the control group. In one patient with gliomatosis-cerebri, who adhered to the diet for 3 years and showed stable disease, an increase in glutamin + glutamate and reduction in N-Acetyl-Aspartate and myo-inositol were detected during KD.H-MRS was able to detect ketone-bodies in patients with brain tumors who adhered to KD. Yet it remains unclear whether accumulation of ketone bodies is due to increased brain uptake or decreased utilization of ketone bodies within the brain.

The proposed method overcomes some inaccuracies in FA production, providing more accurate estimation of T1 values compared with standard methods, and is applicable for currently available data.

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Purpose: To improve image quality and accelerate the acquisition of 3D MR fingerprinting (MRF). Methods: Building on the multi-axis spiral-projection MRF technique, a subspace reconstruction with locally low-rank constraint and a modified spiral-projection spatiotemporal encoding scheme called tiny golden-angle shuffling were implemented for rapid whole-brain high-resolution quantitative mapping. Reconstruction parameters such as the locally low-rank regularization parameter and the subspace rank were tuned using retrospective in vivo data and simulated examinations. B 0 inhomogeneity correction using multifrequency interpolation was incorporated into the subspace reconstruction to further improve the image quality by mitigating blurring caused by off-resonance effect. Results: The proposed MRF acquisition and reconstruction framework yields high-quality 1-mm isotropic whole-brain quantitative maps in 2 min at better quality compared with 6-min acquisitions of prior approaches. The proposed method was validated to not induce bias in T 1 and T 2 mapping. High-quality whole-brain MRF data were also obtained at 0.66-mm isotropic resolution in 4 min using the proposed technique, where the increased resolution was shown to improve visualization of subtle brain structures. Conclusions: The proposed tiny golden-angle shuffling, MRF with optimized spiral-projection trajectory and subspace reconstruction enables high-resolution quantitative mapping in ultrafast acquisition time.

The proposed method yielded good discrimination between LGG with and without 1p/19q codeletion. Results from this study demonstrate the great potential of this method to aid decision-making in the clinical management of patients with LGG.

Super-resolved SPEN with SENSE (SUSPENSE) achieves the goals of multishot SPEN interleaving delivering single-shot submillimeter in-plane resolutions in scanners equipped with suitable multiple sensors. Magn Reson Med 79:796-805, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

1 Technical Efficacy Stage 4 J. Magn. Reson. Imaging 2018.

This study proposes an automatic method for identification and quantification of different tissue components: the non-enhanced infiltrative tumor, vasogenic edema and enhanced tumor areas, at the subject level, in patients with glioblastoma (GB) based on dynamic contrast enhancement (DCE) and dynamic susceptibility contrast (DSC) MRI. Nineteen MR data sets, obtained from 12 patients with GB, were included. Seven patients were scanned before and 8 weeks following bevacizumab initiation. Segmentation of the tumor area was performed based on the temporal data of DCE and DSC at the group-level using k-means algorithm, and further at the subject-level using support vector machines algorithm. The obtained components were associated to different tissues types based on their temporal characteristics, calculated perfusion and permeability values and MR-spectroscopy. The method enabled the segmentation of the tumor area into the enhancing permeable component; the non-enhancing hypoperfused component, associated with vasogenic edema; and the non-enhancing hyperperfused component, associated with infiltrative tumor. Good agreement was obtained between the group-level, unsupervised and subject-level, supervised classification results, with significant correlation (r = 0.93, p < 0.001) and average symmetric root-mean-square surface distance of 2.5 ± 5.1 mm. Longitudinal changes in the volumes of the three components were assessed alongside therapy. Tumor area segmentation using DCE and DSC can be used to differentiate between vasogenic edema and infiltrative tumors in patients with GB, which is of major clinical importance in therapy response assessment.