rocData

This ROC dataset was collected by Carolyn Van Dyke, MD, in an ROC study that compared the performance of two modalities
(Spin Echo MRI and cine MRI). There are 69 non-diseased and 45 diseased cases. Five radiologists interpreted all images in both modalities
using an integer 1 - 5 ratings scale, where larger ratings represented stronger confidence for presence of disease.
The *.xlsx file can be downloaded from <url>http://www.devchakraborty.com/RocData/rocData.xlsx</url>. The dataset file can then
be read into a dataset object using <a href="/link/ReadDataFile?package=RJafroc&version=0.0.1" rd-options="" data-mini-rdoc="RJafroc::ReadDataFile">ReadDataFile</a> function. The *.csv and *.lrc files can be downloaded from OR-DBM MRMC
website, currently <url>http://perception.radiology.uiowa.edu/</url>. Alternatively they can be downloaded from
<url>http://www.devchakraborty.com/RocData/rocData.csv</url> or <url>http://www.devchakraborty.com/RocData/rocData.lrc</url>. The iMRMC file
can be downloaded from <url>http://www.devchakraborty.com/RocData/rocData.imrmc</url>.

A common task in medical imaging is assessing whether a new imaging system or device is an improvement over an existing one. Observer performance methodology, such as receiver operating characteristic analysis, is widely used for this purpose. Receiver operating characteristic studies are often required for regulatory approval of new devices. The purpose of this work is to software for the analysis of data acquired using the receiver operating characteristic paradigm and its location specific extensions. It is an enhanced implementation of existing Windows software (http://www.devchakraborty.com). In this paradigm the radiologist rates each image for confidence in presence of disease. The images are typically split equally between actually non-diseased and diseased. A common figure of merit is the area under the receiver operating characteristic curve, which has the physical interpretation as the probability that a diseased image is rated higher than a non-diseased one. In receiver operating characteristic studies a number of radiologists (readers) rate images in two or more treatments, and the object of the analysis is to determine the significance of the inter-treatment difference between reader-averaged figures of merit. In the free-response paradigm the reader marks the locations of suspicious regions and rates each region for confidence in presence of disease, and credit for detection is only given if a true lesion is correctly localized. In the region of interest paradigm each image is divided into a number of regions and the reader rates each region. Each paradigm requires definition of a valid figure of merit that rewards correct decisions and penalizes incorrect ones and specialized significance testing procedures are applied. The package reads data in all currently used data formats including Excel. Significance testing uses two models in widespread use, a jackknife pseudo-value based model and an analysis of variance model with correlated errors. Included are tools for (1) calculating a variety of free-response figures of merit; (2) sample size estimation for planning a future study based on pilot data; (3) viewing empirical operating characteristics in receiver operating characteristic and free-response paradigms; (4) producing formatted report files; and (5) saving a data file in appropriate format for analysis with alternate software.

Xuetong Zhai

RJafroc

Analysis of Data Acquired Using the Receiver Operating
        Characteristic Paradigm and Its Extensions

rocData function

A dataset object consisting of a list containing 8 elements, see <a href="/link/RJafroc-package?package=RJafroc&version=0.0.1" rd-options="" data-mini-rdoc="RJafroc::RJafroc-package">RJafroc-package</a>.

format

Van Dyke, C. W., et al. "Cine MRI in the diagnosis of thoracic aortic dissection." 79th Annual Meeting of the Radiological
Society of North America, Radiological Society of North America, Chicago, Illinois. 1993.

rocData: An ROC dataset originally provided by Dr. Kevin Berbaum, U of Iowa, ca. 2002.

Description

Usage

Arguments

format

source