TABLE 4:
Metric | ROC Analysis AUC | Prediction Performance for Score Classification 1–3 Versus 4 and 5 |
|||
---|---|---|---|---|---|
Optimal Cutoffa | Sensitivity at Cutoff | Specificity at Cutoff | PPV at Cutoff | ||
Whole prostate | |||||
Mean ADC | 0.87 (0.82–0.92) | < 1061 (1074–950) | 0.88 (0.73–0.95) | 0.72 (0.64–0.89) | 0.83 (0.77–0.93) |
Normalized ADC | 0.82 (0.76–0.88) | < 0.65 (0.74–0.58) | 0.72 (0.62–0.96) | 0.79 (0.53–0.90) | 0.84 (0.74–0.92) |
Area | 0.65 (0.56–0.73) | ≥ 0.54 (0.20–0.90) | 0.37 (0.23–0.82) | 0.87 (0.44–0.97) | 0.81 (0.66–0.95) |
Mean ADC and area | 0.91 (0.87–0.94) | ≥ 0.72 (0.50–0.80) | 0.78 (0.68–0.91) | 0.91 (0.77–0.98) | 0.93 (0.85–0.99) |
Normalized ADC and area | 0.86 (0.81–0.90) | ≥ 0.63 (0.48–0.81) | 0.76 (0.60–0.87) | 0.82 (0.72–0.98) | 0.87 (0.80–0.98) |
Peripheral zone | |||||
Mean ADC | 0.87 (0.81–0.92) | ≤ 1045 (1074–910) | 0.87 (0.61–0.97) | 0.71 (0.61–0.96) | 0.78 (0.70–0.95) |
Normalized ADC | 0.82 (0.75–0.88) | ≤ 0.65 (0.72–0.56) | 0.77 (0.59–0.93) | 0.75 (0.59–0.94) | 0.78 (0.68–0.93) |
Area | 0.60 (0.50–0.70) | ≥ 0.70 (0.20–1.10) | 0.23 (0.13–0.81) | 0.94 (0.39–1.00) | 0.82 (0.55–1.00) |
Mean ADC and area | 0.91 (0.83–0.94) | ≥ 0.71 (0.39–0.80) | 0.69 (0.61–0.92) | 0.94 (0.73–1.00) | 0.93 (0.77–1.00) |
Normalized ADC and area | 0.84 (0.77–0.90) | ≥ 0.69 (0.40–0.77) | 0.67 (0.59–0.90) | 0.90 (0.69–0.98) | 0.89 (0.73–0.97) |
Transition zone | |||||
Mean ADC | 0.89 (0.80–0.97) | ≤ 1024 (1068–896) | 0.86 (0.57–0.98) | 0.81 (0.67–1.00) | 0.93 (0.86–1.00) |
Normalized ADC | 0.86 (0.74–0.96) | ≤ 0.64 (0.76–0.57) | 0.70 (0.56–1.00) | 0.88 (0.52–1.00) | 0.94 (0.81–1.00) |
Area | 0.66 (0.50–0.80) | ≥ 0.90 (0.30–1.20) | 0.40 (0.26–0.91) | 0.94 (0.43–1.00) | 0.94 (0.78–1.00) |
Mean ADC and area | 0.93 (0.86–0.99) | ≥ 0.77 (0.55–0.91) | 0.84 (0.68–0.98) | 0.94 (0.78–1.00) | 0.97 (0.91–1.00) |
Normalized ADC and area | 0.89 (0.80–0.97) | ≥ 0.76 (0.37–0.92) | 0.79 (0.57–1.00) | 0.81 (0.67–1.00) | 0.92 (0.86–1.00) |
Note—Values in parentheses are 95% CI. ADC = apparent diffusion coefficient. Mean ADC is measured in square micrometers per second.
With use of the optimal cutoffs, the sensitivity, specificity, and positive predictive value (PPV) shown can be achieved. Univariate cutoffs refer to actual value of the variable; bivariate cutoffs refer to risk calculated with the given logistic regression model.