Pooling MRMC forced-choice data

Brandon D. Gallas; Gene A. Pennello

doi:10.1117/12.709628

30 March 2007 Pooling MRMC forced-choice data

Brandon D. Gallas, Gene A. Pennello

Proceedings Volume 6515, Medical Imaging 2007: Image Perception, Observer Performance, and Technology Assessment; 651506 (2007) https://doi.org/10.1117/12.709628
Event: Medical Imaging, 2007, San Diego, CA, United States

Abstract

There are at least two sources of variance when estimating the performance of an imaging device: the doctors (readers) and the patients (cases). These sources of variability generate variances and covariances in the observer study data that can be addressed with multi-reader, multi-case (MRMC) variance analysis. Frequently, a fully-crossed study design is used to collect the data; every reader reads every case. For imaging devices used during in vivo procedures, however, a fully-crossed design is infeasible. Instead, each patient is diagnosed by only one doctor, a doctor-patient study design. Here we investigate percent correct (PC) under this doctor-patient study design. From a probabilistic foundation, we present the bias and variance of two statistics: pooled PC and reader-averaged PC. We also present variance estimates of these statistics and compare them to naive estimates. Finally, we run simulations to assess the statistics and the variance estimates. The two PC statistics have the same means but different variances. The variances depend on how patients are distributed among the readers and the amount of reader variability. Regarding the variance estimates, the MRMC estimates are unbiased, whereas the naive estimates bracket the true variance and can be extremely biased.

Citation Download Citation

Brandon D. Gallas and Gene A. Pennello "Pooling MRMC forced-choice data", Proc. SPIE 6515, Medical Imaging 2007: Image Perception, Observer Performance, and Technology Assessment, 651506 (30 March 2007); https://doi.org/10.1117/12.709628

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KEYWORDS

Error analysis

Monte Carlo methods

Statistical analysis

Binary data

Computer simulations

Imaging devices

In vivo imaging

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