Factor analysis of responses to thermal, electrical, and mechanical painful stimuli supports the importance of multi-modal pain assessment

During the last decade, a multi-modal approach has been established in human experimental pain research for assessing pain thresholds and responses to various experimental pain modalities. Studies have concluded that differences in responses to pain stimuli are mainly related to variation between individuals rather than variation in response to different stimulus modalities. In a factor analysis of 272 consecutive volunteers (137 men and 135 women) who underwent tests with different experimental pain modalities, it was determined whether responses to different pain modalities represent distinct individual uncorrelated dimensions of pain perception. Volunteers underwent single painful electrical stimulation, repeated painful electrical stimulation (temporal summation), test for reflex receptive field, pressure pain stimulation, heat pain stimulation, cold pain stimulation, and a cold pressor test (ice water test). Five distinct factors were found representing responses to 5 distinct experimental pain modalities: pressure, heat, cold, electrical stimulation, and reflex-receptive fields. Each of the factors explained approximately 8% to 35% of the observed variance, and the 5 factors cumulatively explained 94% of the variance. The correlation between the 5 factors was near null (median ρ=0.00, range -0.03 to 0.05), with 95% confidence intervals for pairwise correlations between 2 factors excluding any relevant correlation. Results were almost similar for analyses stratified according to gender and age. Responses to different experimental pain modalities represent different specific dimensions and should be assessed in combination in future pharmacological and clinical studies to represent the complexity of nociception and pain experience.

Multimodal viral communication: a social semiotic analysis of the popular Spanish "Ola ke ase" meme

Multimodality – the interdependence of semiotic resources in text – is an existential element of today’s media. The term multimodality attends systematically to the social interpretation of a wide range of communicational forms used in meaning making. A primary focus of social- semiotic multimodal analysis is on mapping how modal resources are used by people in a given social context. In November 2012 the “Ola ke ase” catchphrase, which is a play on “Hola ¿qué hace?”, appeared for the first time in Spain and immediately has been adopted as a Twitter hashtag and an image macro series. Its viral spread on social networks has been tremendous, being a trending topic in various Spanish-speaking countries. The objective of analysis is how language and image work together in the “Ola ke ase” meme. The interplay between text and image in one of the original memes and some of its variations is quantitatively analysed applying a social-semiotic approach. Results demonstrate how the “Ola ke ase” meme functions through its multimodal character and the non-standard orthography. The spread of uncountable variations of the meme shows the social process that goes on in the meaning making of the semiotic elements.

Multi-modal glioblastoma segmentation: man versus machine

BACKGROUND AND PURPOSE Reproducible segmentation of brain tumors on magnetic resonance images is an important clinical need. This study was designed to evaluate the reliability of a novel fully automated segmentation tool for brain tumor image analysis in comparison to manually defined tumor segmentations. METHODS We prospectively evaluated preoperative MR Images from 25 glioblastoma patients. Two independent expert raters performed manual segmentations. Automatic segmentations were performed using the Brain Tumor Image Analysis software (BraTumIA). In order to study the different tumor compartments, the complete tumor volume TV (enhancing part plus non-enhancing part plus necrotic core of the tumor), the TV+ (TV plus edema) and the contrast enhancing tumor volume CETV were identified. We quantified the overlap between manual and automated segmentation by calculation of diameter measurements as well as the Dice coefficients, the positive predictive values, sensitivity, relative volume error and absolute volume error. RESULTS Comparison of automated versus manual extraction of 2-dimensional diameter measurements showed no significant difference (p = 0.29). Comparison of automated versus manual segmentation of volumetric segmentations showed significant differences for TV+ and TV (p<0.05) but no significant differences for CETV (p>0.05) with regard to the Dice overlap coefficients. Spearman's rank correlation coefficients (ρ) of TV+, TV and CETV showed highly significant correlations between automatic and manual segmentations. Tumor localization did not influence the accuracy of segmentation. CONCLUSIONS In summary, we demonstrated that BraTumIA supports radiologists and clinicians by providing accurate measures of cross-sectional diameter-based tumor extensions. The automated volume measurements were comparable to manual tumor delineation for CETV tumor volumes, and outperformed inter-rater variability for overlap and sensitivity.