Dataset Information

Blinded Visual Scoring of Images Using the Freely-available Software Blinder.

ABSTRACT: In nearly all subfields of biomedical sciences, there are phenotypes that are currently classified by expert visual scoring. In research applications, these classifications require the experimenter to be blinded to the treatment group in order to avoid unintentional bias in scoring. Currently, many labs either use laborious and tedious methods to manually blind the images, require multiple experimenters to gather and score the data blindly or fail to properly blind the data altogether. In this protocol, we present a simple, freely available software that we created that allows the experimenter to blindly score images. In our protocol, the user loads unblinded images and defines a scoring system. The software then shows the user the images in a random order, allowing the user to select a score from their defined scoring system for each image. Furthermore, the software has an optional "quality control" mechanism where the user will be shown some images multiple times to test the robustness of the visual scoring. Finally, the software summarizes the results in an exportable file that includes unblinded summary data for each group and a full list of images with their scores. In this protocol, we briefly present directions for using the software, potential applications, and caveats/limitations to this approach.

SUBMITTER: Cothren SD

PROVIDER: S-EPMC6370323 | biostudies-other | 2018 Dec

REPOSITORIES: biostudies-other

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Blinded Visual Scoring of Images Using the Freely-available Software Blinder.

Cothren Steven D SD Meyer Joel N JN Hartman Jessica H JH

Bio-protocol 20181201 23

In nearly all subfields of biomedical sciences, there are phenotypes that are currently classified by expert visual scoring. In research applications, these classifications require the experimenter to be blinded to the treatment group in order to avoid unintentional bias in scoring. Currently, many labs either use laborious and tedious methods to manually blind the images, require multiple experimenters to gather and score the data blindly or fail to properly blind the data altogether. In this p ...[more]

PMID: 30761327

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Project description:BackgroundAnalysis of ciliary function for assessment of patients suspected of primary ciliary dyskinesia (PCD) and for research studies of respiratory and ependymal cilia requires assessment of both ciliary beat pattern and beat frequency. While direct measurement of beat frequency from high-speed video recordings is the most accurate and reproducible technique it is extremely time consuming. The aim of this study was to develop a freely available automated method of ciliary beat frequency analysis from digital video (AVI) files that runs on open-source software (ImageJ) coupled to Microsoft Excel, and to validate this by comparison to the direct measuring high-speed video recordings of respiratory and ependymal cilia. These models allowed comparison to cilia beating between 3 and 52 Hz.MethodsDigital video files of motile ciliated ependymal (frequency range 34 to 52 Hz) and respiratory epithelial cells (frequency 3 to 18 Hz) were captured using a high-speed digital video recorder. To cover the range above between 18 and 37 Hz the frequency of ependymal cilia were slowed by the addition of the pneumococcal toxin pneumolysin. Measurements made directly by timing a given number of individual ciliary beat cycles were compared with those obtained using the automated ciliaFA system.ResultsThe overall mean difference (± SD) between the ciliaFA and direct measurement high-speed digital imaging methods was -0.05 ± 1.25 Hz, the correlation coefficient was shown to be 0.991 and the Bland-Altman limits of agreement were from -1.99 to 1.49 Hz for respiratory and from -2.55 to 3.25 Hz for ependymal cilia.ConclusionsA plugin for ImageJ was developed that extracts pixel intensities and performs fast Fourier transformation (FFT) using Microsoft Excel. The ciliaFA software allowed automated, high throughput measurement of respiratory and ependymal ciliary beat frequency (range 3 to 52 Hz) and avoids operator error due to selection bias. We have included free access to the ciliaFA plugin and installation instructions in Additional file 1 accompanying this manuscript that other researchers may use.

Dataset Information

Blinded Visual Scoring of Images Using the Freely-available Software Blinder.

Publications

Blinded Visual Scoring of Images Using the Freely-available Software Blinder.

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