VGC Analyzer: A Software for Statistical Analysis of Fully Crossed Multiple-Reader Multiple-Case Visual Grading Characteristics Studies

Abstract

Visual grading characteristics (VGC) analysis is a non-parametric rank-invariant method for analysis of visual grading data. In VGC analysis, image quality ratings for two different conditions are compared by producing a VGC curve, similar to how the ratings for normal and abnormal cases in receiver operating characteristic (ROC) analysis are used to create an ROC curve. The use of established ROC software for the analysis of VGC data has therefore previously been proposed. However, the ROC analysis is based on the assumption of independence between normal and abnormal cases. In VGC analysis, this independence cannot always be assumed, e.g. if the ratings are based on the same patients imaged under both conditions. A dedicated software intended for analysis of VGC studies, which takes possible dependencies between ratings into account in the statistical analysis of a VGC study, has therefore been developed. The software-VGC Analyzer-determines the area under the VGC curve and its uncertainty using non-parametric resampling techniques. This article gives an introduction to VGC Analyzer, describes the types of analyses that can be performed and instructs the user about the input and output data.

80-kVp hepatic CT to reduce contrast medium dose in azotemic patients: a feasibility study

“…Scoring was done using the ViewDEX software (15) and analyzed using the software VGC Analyzer, version 1.0.2 (16). The software obtains a VGC curve by plotting the cumulative distributions of rating data for the two protocols compared against each other.…”

“…If the 95% confidence interval (CI) of the AUC VGC does not include the value 0.5, a statistically significant difference between the two protocols can be established at the 95% level (13). Although not explicitly analyzed separately, inter-observer variations are considered in the statistical analysis by the resampling technique used to determine the confidence interval of the reported AUC (16). The analysis was performed individually for all criteria and observers and in addition for all observers combined (random-observer analysis).…”

Pulmonary artery imaging under free‐breathing using golden‐angle radial bSSFP MRI: a proof of concept

“…Analysis of the observer's scores was done using Visual Grading Characteristics (VGC) in the freely available VGC Analyzer software package . Visual Grading Characteristics is a nonparametric, rank, invariant method for statistical analysis of observer‐reported image criteria scores (ICS).…”

Visibility of Structures of Relevance for Patients With Cystic Fibrosis in Chest Tomosynthesis: Influence of Anatomical Location and Observer Experience

“…In the present study, the area under the VGC curve described differences in perceived visibility between observers or between anatomical locations for a given observer. Results were calculated using VGC Analyzer ( 32 ) , based on the trapezoid VGC curve. A random-reader analysis was employed for comparisons of visibility according to anatomical location, in order to enable a generalisation of the results to the population of observers.…”