Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation or lack thereof. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this first part, we discuss dynamic susceptibility contrast and dynamic contrast‐enhanced MRI, arterial spin labeling, diffusion‐weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility‐weighted imaging, MRI‐PET, MR elastography, and MR‐based radiomics applications. Evidence Level: 3 Technical Efficacy: Stage 2

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Purpose To describe the anatomic relationship of the lingual nerve with the lateral oropharyngeal structures. Methods An anatomic dissection of the lateral oropharyngeal wall was conducted in eight sides from four fresh-frozen cadaveric heads. Small titanium clips were placed along the lingual nerve and the most anterior and medial border of the medial pterygoid muscle. Radiological reconstructions were employed for optimal visualization; the coronal view was preferred to resemble the surgical position. The distance between the lingual nerve and the medial pterygoid muscle at its upper and lower portion was measured radiologically. The trajectory angle of the lingual nerve with respect to the pterygomandibular raphe was obtained from the intersection between the vector generated between the clips connecting the upper and lower portion of the medial pterygoid muscle with the vector generated from the lingual nerve clips. Results The mean distance from the upper portion of the medial pterygoid muscle and superior lingual nerve clips was 10.16 ± 2.18 mm (mean ± standard deviation), and the lower area of the medial pterygoid muscle to the lingual nerve was separated 5.05 ± 1.49 mm. The trajectory angle of the lingual nerve concerning to the vector that describes the upper portion of the most anterior and medial border of the medial pterygoid muscle with its lower part was 43.73º ± 11.29. Conclusions The lingual nerve runs lateral to the lateral oropharyngeal wall, from superiorly–inferiorly and laterally–medially, and it is closer to it at its lower third.

A pseudocontinuous arterial spin labeling (PCASL) sequence combined with background suppression and single-shot accelerated 3D RARE stack-of-spirals was used to evaluate cerebrovascular reactivity (CVR) induced by breath-holding (BH) in ten healthy volunteers. Four different models designed using the measured change in PETCO2 induced by BH were compared, for CVR quantification. The objective of this comparison was to understand which regressor offered a better physiological model to characterize the cerebral blood flow response under BH. The BH task started with free breathing of 42 s, followed by interleaved end-expiration BHs of 21 s, for ten cycles. The total scan time was 12 min and 20 s. The accelerated readout allowed the acquisition of PCASL data with better temporal resolution than previously used, without compromising the post-labeling delay. Elevated CBF was observed in most cerebral regions under hypercapnia, which was delayed with respect to the BH challenge. Significant statistical differences in CVR were obtained between the different models in GM (p < 0.0001), with ramp models yielding higher values than boxcar models and between the two tissues, GM and WM, with higher values in GM, in all the models (p < 0.0001). The adjustment of the ramp amplitude during each BH cycle did not improve the results compared with a ramp model with a constant amplitude equal to the mean PETCO2 change during the experiment.

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