VanDyke {MRMCbinary} | R Documentation |
Multi-reader multi-case dataset
Description
Example data from a study comparing the relative performance of cinematic presentation of magnetic resonance imaging (CINE MRI) to single spin-echo magnetic resonance imaging (SE MRI) for the detection of thoracic aortic dissection (Van Dyke et al., 1993).
Usage
VanDyke
Format
A data frame with 1140 rows and 7 variables:
- reader
Reader identifier for the five radiologists
- treatment
Treatment identifier for the two imaging modalities
- case
Case identifiers for 114 cases
- case2
Case identifier (cases nested within readers)
- case3
Case identifier (cases nested within treatments)
- truth
-
Indicator for thoracic aortic dissection (i.e., true disease status): 1 = performed (i.e., patients with aortic dissection imaged with both SE MRI and CINE MRI) or 0 = not performed (i.e., patients without dissection imaged with both SE MRI and CINE MRI)
- rating
-
Five-point ratings given to case images by the radiologists (i.e., diagnostic test result): 1 = definitely no aortic dissection, 2 = probably no aortic dissection, 3 = unsure about aortic dissection, 4 = probably aortic dissection, or 5 = definitely aortic dissection
Details
This example compares the relative performance of SE MRI with the CINE MRI in detecting thoracic aortic dissection.
There are 45 patients with an aortic dissection and 69 patients without a dissection imaged with both SE MRI and CINE MRI.
One can directly use this data from MRMCaov
package. See Source.
Source
This data are available at https://perception.lab.uiowa.edu and https://github.com/brian-j-smith/MRMCaov/tree/master/data.
References
Van Dyke, C. W., White, R. D., Obuchowski, N. A., Geisinger, M. A., Lorig, R. J., & Meziane, M. A. (1993). Cine MRI in the diagnosis of thoracic aortic dissection. 79th RSNA Meetings. Chicago, IL, 28.
Examples
## Load example data
data(VanDyke)
## Return the first parts of an object
head(VanDyke)
## Extract unique modalities
unique(VanDyke$treatment)
## Extract Unique readers
unique(VanDyke$reader)
## Create binary test results (Y_ijk)
VanDyke$Y <- as.numeric(VanDyke$rating >= 3)