%0 Journal Article
%A Wang, Xianfeng
%A Hielscher, Thomas
%A Radtke, Jan Philipp
%A Görtz, Magdalena
%A Schütz, Viktoria
%A Kuder, Tristan Anselm
%A Gnirs, Regula
%A Schwab, Constantin
%A Stenzinger, Albrecht
%A Hohenfellner, Markus
%A Schlemmer, Heinz-Peter
%A Bonekamp, David
%T Comparison of single-scanner single-protocol quantitative ADC measurements to ADC ratios to detect clinically significant prostate cancer.
%J European journal of radiology
%V 136
%@ 0720-048X
%C Amsterdam [u.a.]
%I Elsevier Science
%M DKFZ-2021-00174
%P 109538
%D 2021
%Z #EA:E010#LA:E010#
%X Mean ADC has high predictive value for the presence of clinically significant prostate cancer (sPC). Measurement variability is introduced by different scanners, protocols, intra-and inter-patient variation. Internal calibration by ADC ratios can address such fluctuations however can potentially lower the biological value of quantitative ADC determination by being sensitive to deviations in reference tissue signal.To better understand the predictive value of quantitative ADC measurements in comparison to internal reference ratios when measured in a single scanner, single protocol setup.284 consecutive patients who underwent 3 T MRI on a single scanner followed by MRI-transrectal ultrasound fusion biopsy were included. A board-certified radiologist retrospectively reviewed all MRIs blinded to clinical information and placed regions of interest (ROI) on all focal lesions and the following reference regions: normal-appearing peripheral zone (PZNL) and transition zone (TZNL), the urinary bladder (BLA), and right and left internal obturator muscle (RIOM, LIOM). ROI-based mean ADC and ADC ratios to the reference regions were compared regarding their ability to predict the aggressiveness of prostate cancer. Spearman's rank correlation coefficient was used to estimate the correlation between ADC parameters, Gleason score (GS) and ADC ratios. The primary endpoint was presence of sPC, defined as a GS ≥ 3 + 4. Univariable and multivariable logistic regression models were constructed to predict sPC. Receiver operating characteristics curves (ROC) were used for visualization; DeLong test was used to evaluate the differences of the area under the curve (AUC). Bias-corrected AUC values and corresponding 95 
%K Apparent diffusion coefficient (Other)
%K Gleason score (Other)
%K Multiparametric MRI (Other)
%K Prostate cancer (Other)
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:33482592
%R 10.1016/j.ejrad.2021.109538
%U https://inrepo02.dkfz.de/record/167183