Matlab release 2012b

Self-reported itch in response to histamine iontophoresis was assessed using the same 0–10 NRS as described under Expected Itch. During iontophoresis, participants continuously rated itch using a vertical bar slide depicting the NRS. Scores were sampled at a 10-Hz rate using E-Prime 2.0 (42 ). Directly following iontophoresis, mean itch was verbally assessed by asking participants how much itch (on a 0–10 scale) they experienced in general during the test. From 1 to 4 min after iontophoresis, participants were asked to rate self-reported itch every 30 s on the bar slide as a follow-up period. The primary study outcome was the area under the curve (AUC) of itch during the 2.5 min of iontophoresis. Secondary outcomes were maximum itch reported during the 2.5 min of iontophoresis, verbally assessed mean itch, and AUC itch during the 4-min follow-up. AUC of itch and maximum itch during iontophoresis were computed using MATLAB Release 2012b (The MathWorks, Inc., Natick, MA, USA).

While type difference and border distance are inherently ordinal measures, projection directions can also be considered as ordinal values, by arranging them in the order of (‘ascending’, ‘lateral’, ‘descending’). To assess relations between these ordinal variables, we computed Spearman’s rank-correlation coefficient ρ. We also computed Spearman’s ρ to assess relations between relative projection frequencies and the respective anatomical variables.
To test two groups of ordinal measures for equality of their medians, we computed Wilcoxon rank sum test statistics (W). To test for equality of more than two groups of ordinal measures, we computed Kruskal–Wallis test statistics (H). We calculated Jonckheere–Terpstra test statistics (JT) to assess trends across multiple groups of ordinal measures. JT was computed using IBM SPSS Statistics Version 19 (IBM Corporation, Armonk, NY, USA). All tests were pre-assigned a two-tailed significance level α = 0.05. If not indicated otherwise, all analyses were performed using MATLAB Release 2012B (The MathWorks, Inc., Natick, MA, USA).

All data processing, except the QSM (which was obtained by the free tool described in [34 (link)]), was performed using an in-house developed library for Matlab (MATLAB^® Release 2012b, The MathWorks, Inc., Natick, MA, USA), partly described in previous works [16 (link), 35 –37 (link)], on a commercial workstation (Intel^® Core^™ i7-3820 CPU @ 3.6 GHz; RAM 16 GB) equipped with 2 GPU boards (NVIDIA GeForce^® GTX 690). The demonstrative application of qMRI for vein segmentation, and Oxygen Extraction Fraction (OEF) and MTVF mapping was respectively provided by the MAVEN algorithm [20 ] and the in-house implementations of the methods described in [27 (link), 38 (link)].