Objectives To assess the influence of age and sex on 10 cerebrospinal fluid (CSF) flow dynamics parameters measured with an MR phase contrast (PC) sequence within the cerebral aqueduct at the level of the intercollicular sulcus. Materials and Methods 128 healthy subjects (66 female subjects with a mean age of 52.9 years and 62 male subjects with a mean age of 51.8 years) with a normal Evans index, normal medial temporal atrophy (MTA) score, and without known disorders of the CSF circulation were included in the study. A PC MR sequence on a 3T MR scanner was used. Ten different flow parameters were analyzed using postprocessing software. Ordinal and linear regression models were calculated. Results The parameters stroke volume (sex: p < 0.001, age: p = 0.003), forward flow volume (sex: p < 0.001, age: p = 0.002), backward flow volume (sex: p < 0.001, age: p = 0.018), absolute stroke volume (sex: p < 0.001, age: p = 0.005), mean flux (sex: p < 0.001, age: p = 0.001), peak velocity (sex: p = 0.009, age: p = 0.0016), and peak pressure gradient (sex: p = 0.029, age: p = 0.028) are significantly influenced by sex and age. The parameters regurgitant fraction, stroke distance, and mean velocity are not significantly influenced by sex and age. Conclusion CSF flow dynamics parameters measured in the cerebral aqueduct are partly age and sex dependent. For establishment of reliable reference values for clinical use in future studies, the impact of sex and age should be considered and incorporated.

Various techniques have been proposed which aim at scan time reduction and/or at improved image quality by increasing the spatial resolution. Compressed sensing (CS) takes advantage of the fact that MR images are usually sparse in some transform domains and recovers this sparse representation from undersampled data. CS may be combined with parallel imaging such as sensitivity encoding (SENSE), hereafter referred to as Compressed SENSE, to further accelerate image acquisition since both techniques rely on different ancillary information. In practice, Compressed SENSE may reduce scan times of two-dimensional (2D) and three-dimensional (3D) scans by up to 50% depending on the sequence acquired and it works on 1.5-T or 3-T scanners. Compressed SENSE may be applied to 2D and 3D sequences in various anatomies and image contrasts. Image artefacts (i.e. motion, metal and flow artefacts, susceptibility artefacts) frequently appear on magnetic resonance images. The Compressed SENSE technique may cause special artefacts, which might influence image assessment if they go undetected by imaging readers. Our institution has been using Compressed SENSE for over half a year, both in a neuroradiological setting and for musculoskeletal examinations. So far, three special image artefacts—called the wax-layer artefact, the streaky-linear artefact and the starry-sky artefact—have been encountered and we aim to review these main artefacts appearing in sequences acquired with Compressed SENSE.Teaching Points • Compressed SENSE combines compressed sensing and SENSE technique. • Compressed SENSE permits scan time reduction and increases spatial image resolution. • Images acquired with Compressed SENSE may present with special artefacts. • Knowledge of artefacts is necessary for reliable image assessment.

Objectives Acceleration of MR sequences beyond current parallel imaging techniques is possible with the Compressed SENSE technique that has recently become available for 1.5 and 3 Tesla scanners, for nearly all image contrasts and for 2D and 3D sequences. The impact of this technique on examination timing parameters and MR protocols in a clinical setting was investigated in this retrospective study. Material and methods A numerical analysis of the examination timing parameters (scan time, exam time, procedure time, interscan delay time, changeover time, nonscan time) based on the MR protocols of 6 different body regions (brain, knee, lumbar spine, breast, shoulder) using MR log files was performed and the total number of examinations acquired from January to April both in 2017 and 2018 on a 1.5 T MR scanner was registered. Percentages, box plots and unpaired two-sided t tests were obtained for statistical evaluation. Results All examination timing parameters of the six anatomical regions analysed were significantly shortened after implementation of Compressed SENSE. On average, scan times were accelerated by 20.2% (p<0.0001) while procedure times were shortened by 16% (p<0.0001). Considering all anatomical regions and all MR protocols, 27% more examinations were performed over the same 4 month period in 2018 compared to 2017. Conclusion Compressed SENSE allows for a significant acceleration of MR examinations and a considerable increase in the total number of MR examinations is possible.

Objectives: To assess the ability of 3D amide proton transfer weighted (APTw) imaging based on magnetization transfer analysis to discriminate between multiple sclerosis lesions (MSL) and white matter hyperintensities of presumed vascular origin (WMH) and to compare APTw signal intensity of healthy white matter (healthy WM) with APTw signal intensity of MSL and WHM. Materials and Methods: A total of 27 patients (16 female, 11 males, mean age 39.6 years) with multiple sclerosis, 35 patients (17 females, 18 males, mean age 66.6 years) with small vessel disease (SVD) and 20 healthy young volunteers (9 females, 11 males, mean age 29 years) were included in the MSL, the WMH, and the healthy WM group. MSL and WMH were segmented on fluid attenuated inversion recovery (FLAIR) images underlaid onto APTw images. Histogram parameters (mean, median, 10th, 25th, 75th, 90th percentile) were calculated. Mean APTw signal intensity values in healthy WM were defined by "Region of interest" (ROI) measurements. Wilcoxon rank sum tests and receiver operating characteristics (ROC) curve analyses of clustered data were applied. Results: All histogram parameters except the 75 and 90th percentile were significantly different between MSL and WMH (p = 0.018-p = 0.034). MSL presented with higher median values in all parameters. The histogram parameters offered only low diagnostic performance in discriminating between MSL and WMH. The 10th percentile yielded the highest diagnostic performance with an AUC of 0.6245 (95% CI: [0.532, 0.717]). Mean APTw signal intensity values of MSL were significantly higher than mean values of healthy WM (p = 0.005). The mean values of WMH did not differ significantly from the values of healthy WM (p = 0.345). Sartoretti et al. APTw of White Matter Lesions Conclusions: We found significant differences in APTw signal intensity, based on straightforward magnetization transfer analysis, between MSL and WMH and between MSL and healthy WM. Low AUC values from ROC analyses, however, suggest that it may be challenging to determine type of lesion with APTw imaging. More advanced analysis of the APT CEST signal may be helpful for further differentiation of MSL and WMH.

Objectives: To define normal signal intensity values of amide proton transfer-weighted (APTw) magnetic resonance (MR) imaging in different brain regions. Materials and Methods: Twenty healthy subjects (9 females, mean age 29 years, range 19-37 years) underwent MR imaging at 3 Tesla. 3D APTw (RF saturation B 1,rms = 2 µT, duration 2 s, 100% duty cycle) and 2D T2-weighted turbo spin echo (TSE) images were acquired. Postprocessing (image fusion, ROI measurements of APTw intensity values in 22 different brain regions) was performed and controlled by two independent neuroradiologists. Values were measured separately for each brain hemisphere. A subject was scanned both in prone and supine position to investigate differences between hemispheres. A mixed model on a 5% significance level was used to assess the effect of gender, brain region and side on APTw intensity values. Results: Mean APTw intensity values in the hippocampus and amygdala varied between 1.13 and 1.57%, in the deep subcortical nuclei (putamen, globus pallidus, head of caudate nucleus, thalamus, red nucleus, substantia nigra) between 0.73 and 1.84%, in the frontal, occipital and parietal cortex between 0.56 and 1.03%; in the insular cortex between 1.11 and 1.15%, in the temporal cortex between 1.22 and 1.37%, in the frontal, occipital and parietal white matter between 0.32 and 0.54% and in the temporal white matter between 0.83 and 0.89%. APTw intensity values were significantly impacted both by brain region (p < 0.001) and by side (p < 0.001), whereby overall values on the left side were higher than on the right side (1.13 vs. 0.9%). Gender did not significantly impact APTw intensity values (p = 0.24). APTw intensity values between the left and the right side were partially reversed after changing the position of one subject from supine to prone. Conclusion: We determined normal baseline APTw intensity values in different anatomical localizations in healthy subjects. APTw intensity values differed both between anatomical regions and between left and right brain hemisphere.