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: 3Technical Efficacy: Stage 2

Preoperative clinical 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. 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 second part, we review magnetic resonance spectroscopy (MRS), chemical exchange saturation transfer (CEST), susceptibility‐weighted imaging (SWI), MRI‐PET, MR elastography (MRE), and MR‐based radiomics applications. The first part of this review addresses dynamic susceptibility contrast (DSC) and dynamic contrast‐enhanced (DCE) MRI, arterial spin labeling (ASL), diffusion‐weighted MRI, vessel imaging, and magnetic resonance fingerprinting (MRF).Evidence Level: 3.Technical Efficacy: Stage 2.

Hemodynamic measurements such as cerebral blood flow (CBF) and cerebrovascular reactivity (CVR) can provide useful information for the diagnosis and characterization of brain tumors. Previous work showed that arterial spin labeling (ASL) in combination with vasoactive stimulation enabled simultaneous non‐invasive evaluation of both parameters, however this approach had not been previously tested in tumors. The aim of this work was to investigate the application of this technique, using a pseudo‐continuous ASL (PCASL) sequence combined with breath‐holding at 3 T, to measure CBF and CVR in high‐grade gliomas and metastatic lesions, and to explore differences across tumoral‐peritumoral regions and tumor types. To that end, 27 patients with brain tumor were studied. Baseline CBF and CVR were measured in tumor, edema, and gray matter (GM) volumes‐of‐interest (VOIs). Peritumoral ipsilateral ring‐shaped VOIs were also generated and mirrored to the contralateral hemisphere. Differences in baseline CBF and CVR were evaluated between contralateral and ipsilateral GM, contralateral and ipsilateral peritumoral rings, and among VOIs and tumor types. CBF in the tumor was higher in grade 4 gliomas than metastases. In grade 4 gliomas, edema had lower CBF than the tumor and contralateral GM. CVR values were different between grade 3 and grade 4 gliomas, and between grade 4 and metastases. CVR values in the tumor were lower compared to the contralateral GM. Differences in CVR between contralateral and ipsilateral‐ring VOIs were also found in grade 4 gliomas, presumably suggesting tumor infiltration within the peritumoral tissue. A cut‐off value for CVR of 27.9%‐signal‐change is suggested to differentiate between grade 3 and grade 4 gliomas (specificity = 83.3%, sensitivity = 70.6%). In conclusion, CBF and CVR mapping with ASL offered insights into the perilesional environment that could help to detect infiltrative disease, particularly in grade 4 gliomas. CVR emerged as a potential biomarker to differentiate between grade 3 and grade 4 gliomas.

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.

Background: Pulmonary artery enlargement (PAE) detected using chest computed tomography (CT) is associated with poor outcomes in chronic obstructive pulmonary disease (COPD). It is unknown whether nocturnal hypoxemia occurring in smokers, with or without COPD, obstructive sleep apnoea (OSA) or their overlap, may be associated with PAE assessed by chest CT. Methods: We analysed data from two prospective cohort studies that enrolled 284 smokers in lung cancer screening programs and completing baseline home sleep studies and chest CT scans. Main pulmonary artery diameter (PAD) and the ratio of the PAD to that of the aorta (PA:Ao ratio) were measured. PAE was defined as a PAD ≥ 29 mm in men and ≥27 mm in women or as a PA:Ao ratio > 0.9. We evaluated the association of PAE with baseline characteristics using multivariate logistic models. Results: PAE prevalence was 27% as defined by PAD measurements and 11.6% by the PA:Ao ratio. A body mass index ≥ 30 kg/m² (OR 2.01; 95%CI 1.06–3.78), lower % predicted of forced expiratory volume in one second (FEV₁) (OR 1.03; 95%CI 1.02–1.05) and higher % of sleep time with O₂ saturation < 90% (T90) (OR 1.02; 95%CI 1.00–1.03), were associated with PAE as determined by PAD. However, only T90 remained significantly associated with PAE as defined by the PA:Ao ratio (OR 1.02; 95%CI 1.01–1.03). In the subset group without OSA, only T90 remains associated with PAE, whether defined by PAD measurement (OR 1.02; 95%CI 1.01–1.03) or PA:Ao ratio (OR 1.04; 95%CI 1.01–1.07). Conclusions: In smokers with or without COPD, nocturnal hypoxemia was associated with PAE independently of OSA coexistence.