Receiver-operating characteristic analysis

Christensen, S., et al.. Comparison of 10 perfusion MRI parameters in 97 sub-6-hour stroke patients using voxel-based receiver operating characteristics analysis. Stroke, 2009. 40(6) p. 2055-61. 

Ward J, Naik KS, Guthrie JA, Wilson D, Robinson PJ (1999) Hepatic lesion detection comparison of MR imaging after the administration of superparamagnetic iron oxide with dual-phase CT by using alternative-free response receiver operating characteristic analysis. Radiology 210 459-466... 

Greiner M (2000). Principles and practical application of the receiver-operating characteristic analysis for diagnostic tests. Preventive Veterinary Medicine, 45 23-41. 

M. L. Meistrell and K. A. Spackman, Proceedings of the 13 th Annual Symposium on Computer Applications in Medical Care, Washington, DC, 1989, pp. 295-301. Evaluation of Neural Network Performance by Receiver Operating Characteristic Analysis Examples from the Biotechnology Domain. 

This type of signal detection analysis was advanced during World War II for the monitoring of radar images where it was necessary for radar receiver operators to make judgments on whether a blip was due to enemy or friendly objects, or just noise. Consequently the analysis is known as Receiver Operator Characteristics or ROC. 

Constructing a receiver operating characteristic (ROC) curve, which is a quantitative analysis, it showed that a rapamycin blood concentration of >8 ng/mL was the proper cutoff to define high blood concentration of the drug, and that it was in agreement with the mean rapamycin blood concentration in patients having no restenosis (7.9 ng/mL). 

The recognition accuracy estimation described above faces one very important problem what is the best choice for the threshold value 0 To solve this problem, statistical decision theory is used. ° The basis for this is an analysis of the so-called the Received Operating Characteristic (ROC) curve. By tradition, ROC is plotted as a function of true positive rate TPj TP + FN) (or sensitivity) versus false positive rate FPj TN+FP) (or 1-Specificity) for all possible threshold values 0. Figure 6.5 presents an example of such a ROC curve for the results obtained with our computer program PASS in predicting antineoplastic activity. 

Wintermark M, Flanders AE, Velthuis B, Meuh R, van Leeuwen M, Goldsher D, Pineda C, Serena J, van der Schaaf I, Waaijer A, Anderson J, Nesbit G, Gabriely L Medina V, Quiles A, Pohlman S, Quist M, Schnyder P, Bogousslavsky J, Dillon WP, Pedraza S (2006) Perfusion-CT assessment of infarct core and penumbra. Receiver operating characteristic curve analysis in 130 patients suspected of acute hemispheric stroke. Stroke 37 979-985. 

Shultz EK. Multivariate receiver-operating characteristic curve analysis Prostate cancer screening as an example. Clin Chem 1995 41 1248-55. 

The aim of BPS-MS approach presented here can be summarized by comparing the simulated receiver operator characteristic (ROC) curves shown in Figure 1. Each additional dimension of analysis (a distinct pulse shape, that yields distinct mass spectrum) enlarges the area under the curve and therefore the confidence of the measurement. 

The Receiver Operator Characteristic curve (ROC curve) is a graphical plot of the sensitivity Sn versus false positive rate FPR for a binary classifier system as its discrimination threshold is varied. The ROC curve can also be represented equivalently by plotting the fraction of true positives (TP) versus the fraction of false positives (FP) (Figure C3). ROC analysis provides tools to select possibly optimal classification models. 

Stokes RF and Rossman MD (1991) Blood cell proliferation response to beryllium analysis by receiver-operating characteristics. J Occup Med 33 23-28. 

Despite these potential issnes with absolnte thresholds, they have been applied with good resnlts in some centers - most notably for core CBV assessment [33,188-190]. Receiver operating characteristic cnrve analysis in 130 patients snspected of acnte ischemic stroke suggested that relative MTT with an optimal threshold of 145% was the CTP parameter most accurately characterizing salvageable penumbra, and absolute CBV the parameter most accurately characterizing infarct core at admission, again with an optimal threshold of 2.0 mL/100 g [187]. 

Wintermark, M., et al., Perfusion-CT assessment of infarct core and penumbra receiver operating characteristic curve analysis in 130 patients suspected of acute hemispheric stroke. Stroke, 2006. 37(4) p. 979-85. 

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