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Additional file 1: Figure S1. Kinetics of the γH2AX foci in excess in fibroblasts after a single helical head CT scan (a), or a double-helical head CT scan (b) at the indicated post-irradiation times (t0 = non-irradiated). Data result from those shown in Fig. 2 with background subtraction in order to show γH2AX foci in excess effectively due to CT exposure. Error bars indicate SEM. Figure S2. Kinetics of pATM foci in excess in fibroblasts (a) after a single helical head CT scan, (b) or a double-helical head CT scan at the indicated post-irradiation times (t0 = non irradiated). Data result from those shown in Fig. 3 with background subtraction in order to show γH2AX foci in excess effectively due to CT exposure. Error bars indicate SEM. Figure S3. Kinetics of γH2AX foci in excess in astrocytes (a) after a single helical head CT scan, or (b) a double-helical head CT scan at the indicated post-irradiation times (t0 = non-irradiated). Data result from those shown in Fig. 4 with background subtraction in order to show γH2AX foci in excess effectively due to CT exposure. Error bars indicate SEM. Figure S4. Kinetics of the pATM foci in in excess astrocytes (a) after a single helical head CT scan, or (b) a double-helical head CT scan at the indicated post-irradiation times (t0 = non-irradiated). Data result from those shown in Fig. 5 with background subtraction in order to show γH2AX foci in excess effectively due to CT exposure. Error bars indicate SEM. Figure S5. Distribution of the number of γH2AX foci per cell over the 300 nuclei scored for the 200CLB and 85MA cell lines at 1h after a single-helical head CT exposure. Table S1. Statistical results and p-values

Additional file 1. Electronic Supplementary Material.

Purposes Signal-to-noise ratio (SNR) is a prominent metric to assess scanners performances. SNR measurement in MRI is challenging because of the difficulty to quantify noise level from images. A gold-standard consist in pixel-by-pixel variance calculation on several images (>100) scanned in identical conditions. This method is accurate but cannot be practically implemented because of time constraints. Another gold-standard consists in scanning images without radiofrequency excitation hence collecting noise-only. This latter is also unpractical because it requires a specific and generally not-granted access to the hardware. Consequently, there is a need for designing alternative methods for accurate and precise noise quantification. This work aims to introduce a new noise level quantification method for SNR measurement. Methods Our method (Noisefilt) quantifies noise level by combining these operations: (1) subtraction of two images subsequently scanned in identical conditions, (2) Low-pass filtering to extract and suppress low-frequency remaining information, (3) (Noisefilt = standard deviation of pixels. Using a dataset of 30 exams of a head phantom scanned on a 3T MR unit with an 8-channel phased-array brain coil, we compared our method with three others from the literature: noise level quantified using one image-background region-of-interest (ROI) (Noisebgd), several background ROIs (Noisebgd+), and from the subtraction of two images (Noisediff) [6]. By means of Bland–Altman analysis, we assessed the agreement between all these methods and the noise-only standard method (NoisenoRF). We also assessed their correlation with NoisenoRF (Pearson’s correlation coefficient r, p Results Bland–Altman analysis showed that Noisefilt agrees more with the standard than the three other methods. Correlation of our Noisefilt method with the gold-standard (rfilt =0.80, p Conclusion We demonstrated that our method produces accurate measurement, is simple to implement, and is usable for instance for quality control (QC) purposes. This new metric is being tested with additional scans in QC monitoring of different MR scanners. Download : Download high-res image (87KB) Download : Download full-size image Download : Download high-res image (159KB) Download : Download full-size image

Purpose Since August 2016, France has transposed the 2013/35/EU directive on the minimum health and safety requirements regarding professional exposure to the risks related to electromagnetic fields (EMF).Magnetic Resonance Imaging (MRI), which uses different EMFs for image production, falls within the scope of this regulation. As MR Safety Experts (MRSE) to over 20 clinical sites, we have developed a practical scheme to implement the regulation. In this work, we wish to present the implementation scheme and practical examples of its application. Methods The directive imposes to assess the EMF-related professional exposure risks by means of health and sensory Exposure Limit Values (ELVs) and Action Levels (ALs).Clinical MRI requires the use of a static magnetic field (0Hz), circularly polarized radiofrequency fields (42, 64, 128,300 MHz), and low-frequency switched gradient fields (0.5 kHz Results As a result, a detailed risk assessment report is issued to the sites with a clear exhibit of cases in which ELVs or ALs are exceeded.The report also details the prevention actions that need to be implemented and the required safety teaching program. Conclusions The directors and managers of these clinical MRI sites are responsible for the implementation of the health and safety requirements in the frame of the 2013/35/EU directive.They need to rely on trained MR physicists and MRSE.Our implementation scheme is an excellent solution to numerous clinical sites where none of their staff is trained in MR physics or on safety requirements.