Optimal size threshold for PIRADSv2 category 5 upgrade and its positive predictive value: is it predictive of "very high" likelihood of clinically-significant cancer?

AIM: To identify the optimal size metric and threshold for Prostate Imaging Reporting and Data System (PIRADS) 5 upgrade, calculate its positive predictive value (PPV) for clinically-significant prostate cancer (csPCA), and determine if it is indicative of a "very high" likelihood of csPCA. MATERIALS AND METHODS: One hundred and forty-three PIRADS 4 or 5 lesions were evaluated. Lesion diameters were used to calculate lesion volume (LV). Pearson correlation between maximum lesion diameter (MLD) and LV was calculated. Area under the curve (AUC) for discriminating csPCA (Gleason grade ≥ 3 + 4) was calculated using MLD and LV. Optimal size thresholds (using Youden index) and highly predictive size thresholds were identified for the whole prostate (WP), peripheral zone (PZ), and transitional zone (TZ). RESULTS: There was high correlation between MLD and LV (r=0.77-0.81), with comparable AUCs for MLD and LV in the identification of csPCA in the WP (0.73, 0.72), PZ (0.73, 0.73), and TZ (0.79, 0.75). Optimal MLD thresholds were 1.4, 1.4, and 1.6 cm in the WP, PZ, and TZ respectively, with PPVs of 76%, 81%, and 69%, respectively. An MLD threshold of 2.7 cm would be needed in the WP to achieve a PPV approaching 90%, with sensitivity decreasing to 10%. CONCLUSIONS: There is high correlation between MLD and LV with comparable discrimination of csPCA using each. PIRADSv2's 1.5 cm MLD threshold is near the optimal threshold for PIRADS 5 upgrade but has moderate PPV. A much higher threshold would be needed to increase its PPV, with significant sacrifice in sensitivity.

Single-energy non-contrast hepatic steatosis criteria applied to virtual non-contrast images: is it still highly specific and positively predictive?

AIM: To determine the sensitivity, specificity, and predictive values of single-energy non-contrast hepatic steatosis criteria on dual-energy virtual non-contrast (VNC) images. MATERIALS AND METHODS: Forty-eight computed tomography (CT) examinations, which included single-energy non-contrast (TNC) and contrast-enhanced dual-energy CT angiography (CTA) of the abdomen, were enrolled. VNC images were reconstructed from the CTA. Region of interest (ROI) attenuations were measured in the right and left hepatic lobes, spleen, and aorta on TNC and VNC images. The right and left hepatic lobes were treated as separate samples. Steatosis was diagnosed based on TNC liver attenuation of ≤40 HU or liver attenuation index (LAI) of ≤-10 HU, which are extremely specific and predictive for moderate to severe steatosis. The sensitivity, specificity, and predictive values of VNC images for steatosis were calculated. VNC-TNC deviations were correlated with aortic enhancement and patient water equivalent diameter (PWED). RESULTS: Thirty-two liver ROIs met steatosis criteria based on TNC attenuation; VNC attenuation had sensitivity, specificity, and a positive predictive value of 66.7%, 100%, and 100%, respectively. Twenty-one liver ROIs met steatosis criteria based on TNC LAI. VNC LAI had sensitivity, specificity, and positive predictive values of 61.9%, 90.7%, and 65%, respectively. Hepatic and splenic VNC-TNC deviations did not correlate with one another (R2=0.08), aortic enhancement (R2<0.06) or PWED (R2 <0.09). CONCLUSIONS: Non-contrast hepatic attenuation criteria is extremely specific and positively predictive for moderate to severe steatosis on VNC reconstructions from the arterial phase. Hepatic attenuation performs better than LAI criteria. VNC deviations are independent of aortic enhancement and PWED.