Across scientific disciplines, there is a rapidly growing recognition of the need for more statistically robust, transparent approaches to data visualization. Complimentary to this, many scientists have realized the need for plotting tools that accurately and transparently convey key aspects of statistical effects and raw data with minimal distortion. Previously common approaches, such as plotting conditional mean or median barplots together with error-bars have been criticized for distorting effect size, hiding underlying patterns in the raw data, and obscuring the assumptions upon which the most commonly used statistical tests are based. Here we describe a data visualization approach which overcomes these issues, providing maximal statistical information while preserving the desired 'inference at a glance' nature of barplots and other similar visualization devices. These "raincloud plots" can visualize raw data, probability density, and key summary statistics such as median, mean, and relevant confidence intervals in an appealing and flexible format with minimal redundancy. In this tutorial paper we provide basic demonstrations of the strength of raincloud plots and similar approaches, outline potential modifications for their optimal use, and provide open-source code for their streamlined implementation in R, Python and Matlab (https://github.com/RainCloudPlots/RainCloudPlots). Readers can investigate the R and Python tutorials interactively in the browser using Binder by Project Jupyter.

ObjectiveIncreasing evidence suggest that neuronal damage is an early and diffuse feature of Multiple Sclerosis (MS) pathology. Analysis of the optic pathway may help to clarify the mechanisms involved in grey matter damage in MS. Purpose of our study was to investigate the relationship between inflammation and neurodegeneration and to achieve evidence of trans-synaptic degeneration in the optic pathway in MS at clinical onset.Methods50 clinically isolated syndromes/early relapse-onset MS (CIS/eRRMS) with mean disease duration of 4.0±3.5 months, 28 MRI healthy controls (HC) and 31 OCT-HC were studied. Ten patients had optic neuritis at presentation (MSON+), 40 presented with other symptoms (MSON-). MRI examination included 3D-T1, 3D-FLAIR and 3D-DIR sequences. Global cortical thickness (gCTh), pericalcarin CTh (pCTh) and white matter volume (WMV) were analysed by means of Freesurfer on 3D-T1 scans. Optic radiation morphology (OR) and volume (ORV) were reconstructed on the base of the Jülich’s Atlas. White matter lesion volume (WMLV), OR-WMLV and percent WM damage (WMLV/WMV = WMLV% and OR-WMLV/ORV = ORWMLV%) were obtained by 3D-FLAIR image segmentation. 3D-DIR sequences were applied to identify inflammatory lesions of the optic nerve. Optic coherence tomography (OCT) protocol included the analysis of global peripapillary retinal nerve fiber layer (g-RNFL) and the 6 fundus oculi’s sectors (temporal, T-RNFL; temporal superior, TS-RNFL; nasal superior, NS-RNFL; nasal, N-RNFL; nasal inferior, NI-RNFL, temporal inferior, TI-RNFL). The retina of both eyes was analyzed. The eyes of ON+ were further divided into affected (aON+) or not (naON+).ResultsNo difference in CTh was found between CIS/eRRMS and HC, and between MSON+ and MSON-. Moreover, MSON+ and MSON- did not differ for any WM lesion load parameter. The most significant correlations between RNFL thickness and optic radiation WM pathology were found in MSON+. In these patients, the temporal RNFL inversely correlated to ipsilateral optic radiation WM lesion load (T-RNFL: r -0.7, p<0.05; TS-RNFL: r -0.7, p<0.05), while nasal RNFL inversely correlated to contralateral optic radiation WM lesion load (NI: r -0.8, p<0.01; NS-RNFL: r -0.8, p<0.01).ConclusionsOur findings suggest that in MSON+ the optic pathway is site of a diffuse pathological process that involves both directly and via trans-synaptic degeneration the RNFL.

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Purpose To date, there is no consensus on how to semi-quantitatively assess brain amyloid PET. Some approaches use late acquisition alone (e.g., ELBA, based on radiomic features), others integrate the early scan (e.g., TDr, which targets the area of maximum perfusion) and structural imaging (e.g., WMR, that compares kinetic behaviour of white and grey matter, or SI based on the kinetic characteristics of the grey matter alone). In this study SUVr, ELBA, TDr, WMR, and SI were compared. The latter — the most complete one — provided the reference measure for amyloid burden allowing to assess the efficacy and feasibility in clinical setting of the other approaches. Methods We used data from 85 patients (aged 44–87) who underwent dual time-point PET/MRI acquisitions. The correlations with SI were computed and the methods compared with the visual assessment. Assuming SUVr, ELBA, TDr, and WMR to be independent measures, we linearly combined them to obtain more robust indices. Finally, we investigated possible associations between each quantifier and age in amyloid-negative patients. Results Each quantifier exhibited excellent agreement with visual assessment and strong correlation with SI (average AUC = 0.99, ρ = 0.91). Exceptions to this were observed for subcortical regions with ELBA and WMR (ρELBA = 0.44, ρWMR = 0.70). The linear combinations showed better performances than the individual methods. Significant associations were observed between TDr, WMR, SI, and age in amyloid-negative patients (p < 0.05). Conclusion Among the other methods, TDr came closest to the reference with less implementation complexity. Moreover, this study suggests that combining independent approaches gives better results than the individual procedure, so efforts should focus on multi-classifier systems for amyloid PET. Finally, the ability of techniques integrating blood perfusion to depict age-related variations in amyloid load in amyloid-negative subjects demonstrates the goodness of the estimate.

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