Purpose To investigate whether tumor volume derived from apparent diffusion coefficient (ADC) maps (VolumeADC) and tumor mean ADC value (ADCmean) are independent predictors of prostate tumor Gleason score (GS). Materials and Methods Tumor volume and GS were recorded from whole-mount histopathology for 131 men (median age, 60) who underwent endorectal diffusion-weighted magnetic resonance imaging for local staging of prostate cancer before prostatectomy. VolumeADC and ADCmean were derived from ADC maps and correlated with histopathologic tumor volume and GS. Uni- and multivariate analyses were performed to evaluate prediction of tumor aggressiveness. Areas under receiver-operating-characteristics curves (AUCs) were calculated to evaluate the performance of VolumeADC and ADCmean in discriminating tumors of GS 6 and GS ≥7. Results Histopathology identified 116 tumor foci >0.5 mL. VolumeADC correlated significantly with histopathologic tumor volume (ρ=0.683). The correlation increased with increasing GS (ρ=0.453 for GS 6 tumors; ρ=0.643 for GS 7 tumors; ρ=0.980 for GS≥8 tumors). Both VolumeADC (ρ=0.286) and ADCmean (ρ=-0.309) correlated with GS. At univariate analysis, both VolumeADC (p=0.0325) and ADCmean (p=0.0033) could differentiate GS=6 from GS≥7 tumor foci. However, at multivariate analysis, only ADCmean (p=0.0156) was a significant predictor of tumor aggressiveness (i.e., GS 6 vs. GS ≥7). For differentiating GS 6 from GS≤7 tumors, AUCs were 0.644 and 0.704 for VolumeADC and ADCmean, respectively, and 0.749 for both parameters combined. Conclusion In patients with prostate cancer, ADCmean is an independent predictor of tumor aggressiveness, but VolumeADC is not. The latter parameter adds little to the ADCmean in predicting tumor Gleason score.
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 August 2014.
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