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Verification of modified receiver-operating characteristic software using simulated rating data.

Junji Shiraishi1, Daisuke Fukuoka2, Reimi Iha3

  • 1Faculty of Life Sciences, Kumamoto University, 4-24-1 Kuhonji, Kumamoto, 862-0976, Japan. j2s@kumamoto-u.ac.jp.

Radiological Physics and Technology
|September 24, 2018
PubMed
Summary
This summary is machine-generated.

New receiver-operating characteristic (ROC) curve-fitting software was developed to overcome compatibility issues with older systems. This new software demonstrates high correlation and agreement with existing tools for analyzing diagnostic accuracy using simulated data.

Keywords:
Binormal distributionComputer softwareMulti-reader multi-caseObserver studyReceiver-operating characteristic analysis (ROC)Simulation data

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Area of Science:

  • Medical Imaging Analysis
  • Statistical Software Development
  • Diagnostic Accuracy Assessment

Background:

  • ROCKIT and DBM-MRMC are established software packages for receiver-operating characteristic (ROC) curve analysis and multi-reader multi-case (MRMC) studies.
  • Existing ROC software is not compatible with modern operating systems like Windows 7 and later.
  • There is a need for updated software that maintains the analytical capabilities of established tools.

Purpose of the Study:

  • To develop and verify new software for ROC curve fitting and MRMC analysis with updated compatibility.
  • To compare the performance of the new software against existing tools using simulated diagnostic accuracy data.
  • To ensure the modified software provides reliable analysis of diagnostic performance metrics.

Main Methods:

  • Developed new software based on ROCKIT and DBM-MRMC algorithms, with minor modifications for modern operating systems.
  • Generated simulated rating data using a binormal model with specified target AUCs and parameter 'b'.
  • Varied simulation parameters including case sample size, positive-to-negative ratio, parameter 'b', and preset AUC to test software performance under different conditions.

Main Results:

  • The new software's estimated AUCs showed a high correlation (R > 0.98) with those from existing software.
  • Statistical test results from the new and existing software demonstrated high agreement (≥85%).
  • The simulation confirmed the modified software's ability to accurately assess diagnostic accuracies across various data complexities.

Conclusions:

  • The newly developed software is a viable, compatible alternative to older ROC analysis tools.
  • The modified software maintains the analytical rigor and reliability of established packages like ROCKIT and DBM-MRMC.
  • This advancement ensures continued robust analysis of diagnostic accuracy in medical research.