Assessment of Prostate Cancer Aggressiveness by Use of the Combination of Quantitative DWI and Dynamic Contrast-Enhanced MRI.

OBJECTIVE The objective of this study was to investigate whether the apparent diffusion coefficient (ADC) value from DWI and the forward volume transfer constant (K(trans)) value from dynamic contrast-enhanced MRI independently predict prostate cancer aggressiveness, and to determine whether the combination of both parameters performs better than either parameter alone in assessing tumor aggressiveness before treatment. MATERIALS AND METHODS This retrospective study included 158 men with histopathologically confirmed prostate cancer who underwent 3-T MRI before undergoing prostatectomy in 2011. Whole-mount step-section pathologic maps identified 195 prostate cancer foci that were 0.5 mL or larger; these foci were then volumetrically assessed to calculate the per-tumor ADC and K(trans) values. Associations between MRI and histopathologic parameters were assessed using Spearman correlation coefficients, univariate and multivariable logistic regression, and AUCs. RESULTS The median ADC and K(trans) values showed moderate correlation only for tumors for which the Gleason score (GS) was 4 + 4 or higher (ρ = 0.547; p = 0.042). The tumor ADC value was statistically significantly associated with all dichotomized GSs (p < 0.005), including a GS of 3 + 3 versus a GS of 3 + 4 or higher (AUC, 0.693; p = 0.001). The tumor K(trans) value differed statistically significantly only between tumors with a GS of 3 + 3 and those with a primary Gleason grade of 4 (p ≤ 0.015), and it made a statistically significant contribution only in differentiating tumors with a GS of 4 + 3 or higher (AUC, 0.711; p < 0.001) and those with a GS of 4 + 4 or higher (AUC, 0.788; p < 0.001) from lower-grade tumors. Combining ADC and K(trans) values improved diagnostic performance in characterizing tumors with a GS of 4 + 3 or higher and those with a GS of 4 + 4 or higher (AUC, 0.739 and 0.856, respectively; p < 0.01). CONCLUSION Although the ADC value helped to differentiate between all GSs, the K(trans) value was only a benefit in characterizing more aggressive tumors. Combining these parameters improves their performance in identifying patients with aggressive tumors who may require radical treatment.

[1]  Thomas Hambrock,et al.  Assessment of prostate cancer aggressiveness using dynamic contrast-enhanced magnetic resonance imaging at 3 T. , 2013, European urology.

[2]  Yousef Mazaheri,et al.  Prostate MRI: Evaluating Tumor Volume and Apparent Diffusion Coefficient as Surrogate Biomarkers for Predicting Tumor Gleason Score , 2014, Clinical Cancer Research.

[3]  W. I. Tseng,et al.  Washout gradient in dynamic contrast‐enhanced MRI is associated with tumor aggressiveness of prostate cancer , 2012, Journal of magnetic resonance imaging : JMRI.

[4]  M. Knopp,et al.  Estimating kinetic parameters from dynamic contrast‐enhanced t1‐weighted MRI of a diffusable tracer: Standardized quantities and symbols , 1999, Journal of magnetic resonance imaging : JMRI.

[5]  V. Seshan,et al.  Comparing ROC curves derived from regression models , 2013, Statistics in medicine.

[6]  Massimo Mischi,et al.  Angiogenesis in prostate cancer: onset, progression and imaging , 2012, BJU international.

[7]  M. Giger,et al.  Quantitative analysis of multiparametric prostate MR images: differentiation between prostate cancer and normal tissue and correlation with Gleason score--a computer-aided diagnosis development study. , 2013, Radiology.

[8]  Theodorus H van der Kwast,et al.  A critical analysis of the tumor volume threshold for clinically insignificant prostate cancer using a data set of a randomized screening trial. , 2011, The Journal of urology.

[9]  John Kurhanewicz,et al.  Transatlantic Consensus Group on active surveillance and focal therapy for prostate cancer , 2012, BJU international.

[10]  D P Dearnaley,et al.  Dynamic contrast enhanced MRI of prostate cancer: correlation with morphology and tumour stage, histological grade and PSA. , 2000, Clinical radiology.

[11]  H. G. van der Poel,et al.  Can we expand active surveillance criteria to include biopsy Gleason 3+4 prostate cancer? A multi-institutional study of 2,323 patients. , 2015, Urologic oncology.

[12]  Kevin W Eliceiri,et al.  NIH Image to ImageJ: 25 years of image analysis , 2012, Nature Methods.

[13]  P. P. Iu,et al.  ESUR prostate MR guidelines. , 2013, European radiology.

[14]  A. Rosenkrantz,et al.  Prostate Cancer: Diffusion-Weighted Imaging Versus Dynamic-Contrast Enhanced Imaging for Tumor Localization—A Meta-Analysis , 2013, Journal of computer assisted tomography.

[15]  Oguz Akin,et al.  Transition zone prostate cancer: incremental value of diffusion-weighted endorectal MR imaging in tumor detection and assessment of aggressiveness. , 2013, Radiology.

[16]  Katsuyuki Nakanishi,et al.  Clinical utility of apparent diffusion coefficient (ADC) values in patients with prostate cancer: Can ADC values contribute to assess the aggressiveness of prostate cancer? , 2011, Journal of magnetic resonance imaging : JMRI.

[17]  Jelle O. Barentsz,et al.  Prostate MRI: diffusion-weighted imaging at 1.5T correlates better with prostatectomy Gleason grades than TRUS-guided biopsies in peripheral zone tumours , 2012, European Radiology.

[18]  Jan van der Meulen,et al.  Multiparametric MR imaging for detection of clinically significant prostate cancer: a validation cohort study with transperineal template prostate mapping as the reference standard. , 2013, Radiology.

[19]  Yousef Mazaheri,et al.  Diffusion-weighted endorectal MR imaging at 3 T for prostate cancer: tumor detection and assessment of aggressiveness. , 2011, Radiology.

[20]  A. Oto,et al.  Diffusion-weighted and dynamic contrast-enhanced MRI of prostate cancer: correlation of quantitative MR parameters with Gleason score and tumor angiogenesis. , 2011, AJR. American journal of roentgenology.

[21]  J. Fütterer,et al.  ESUR prostate MR guidelines 2012 , 2012, European Radiology.

[22]  Kathleen F. Kerr,et al.  Testing for improvement in prediction model performance , 2013, Statistics in medicine.

[23]  S. Verma,et al.  Assessment of aggressiveness of prostate cancer: correlation of apparent diffusion coefficient with histologic grade after radical prostatectomy. , 2011, AJR. American journal of roentgenology.

[24]  N. Lawrentschuk,et al.  Active surveillance for low-risk prostate cancer: an update , 2011, Nature Reviews Urology.

[25]  D. Altman,et al.  Calculating correlation coefficients with repeated observations: Part 2--Correlation between subjects. , 1995, BMJ.

[26]  M. Terris,et al.  Upgrading and downgrading of prostate needle biopsy specimens: risk factors and clinical implications. , 2006, Urology.

[27]  Gary P Liney,et al.  Correlation of ADC and T2 Measurements With Cell Density in Prostate Cancer at 3.0 Tesla , 2009, Investigative radiology.

[28]  Yousef Mazaheri,et al.  Prostate cancer aggressiveness: assessment with whole-lesion histogram analysis of the apparent diffusion coefficient. , 2014, Radiology.

[29]  P. Box Relationship between apparent diffusion coefficients at 3.0-T MR imaging and Gleason grade in peripheral zone prostate cancer , 2011 .

[30]  Ralph B D'Agostino,et al.  Misuse of DeLong test to compare AUCs for nested models , 2012, Statistics in medicine.