Prostate Cancer: Diffusion-weighted MR Imaging for Detection and Assessment of Aggressiveness-Comparison between Conventional and Kurtosis Models.

Purpose To compare standard diffusion-weighted (DW) imaging and diffusion kurtosis (DK) imaging for prostate cancer (PC) detection and characterization in a large patient cohort, with attention to the potential added value of DK imaging. Materials and Methods This retrospective institutional review board-approved study received a waiver of informed consent. Two hundred eighty-five patients with PC underwent 3.0-T phased-array coil prostate magnetic resonance (MR) imaging, including a DK imaging sequence (b values 0, 500, 1000, 1500, and 2000 sec/mm2) before prostatectomy. Maps of apparent diffusion coefficient (ADC) and diffusional kurtosis (K) were derived by using maximal b values of 1000 and 2000 sec/mm2, respectively. Mean ADC and K were obtained from volumes of interest (VOIs) placed on each patient's dominant tumor and benign prostate tissue. Metrics were compared between benign and malignant tissue, between Gleason score (GS) ≤ 3 + 3 and GS ≥ 3 + 4 tumors, and between GS ≤ 3 + 4 and GS ≥ 4 + 3 tumors by using paired t tests, analysis of variance, receiver operating characteristic (ROC) analysis, and exact tests. Results ADC and K showed significant differences for benign versus tumor tissues, GS ≤ 3 + 3 versus GS ≥ 3 + 4 tumors, and GS ≤ 3 + 4 versus GS ≥ 4 + 3 tumors (P < .001 for all). ADC and K were highly correlated (r = -0.82; P < .001). Area under the ROC curve was significantly higher (P = .002) for ADC (0.921) than for K (0.902) for benign versus malignant tissue but was similar for GS ≤ 3 + 3 versus GS ≥ 3 + 4 tumors (0.715-0.744) and GS ≤ 3 + 4 versus GS ≥ 4 + 3 tumors (0.694-0.720) (P > .15). ADC and K were concordant for these various outcomes in 80.0%-88.6% of patients; among patients with discordant results, ADC showed better performance than K for GS ≤ 3 + 4 versus GS ≥ 4 + 3 tumors (P = .016) and was similar to K for other outcomes (P > .136). Conclusion ADC and K were highly correlated, had similar diagnostic performance, and were concordant for the various outcomes in the large majority of cases. These observations did not show a clear added value of DK imaging compared with standard DW imaging for clinical PC evaluation. © RSNA, 2017 Online supplemental material is available for this article.

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

[2]  Thomas Hambrock,et al.  Relationship between apparent diffusion coefficients at 3.0-T MR imaging and Gleason grade in peripheral zone prostate cancer. , 2011, Radiology.

[3]  Yu-Dong Zhang,et al.  Histogram analysis of diffusion kurtosis magnetic resonance imaging in differentiation of pathologic Gleason grade of prostate cancer. , 2015, Urologic oncology.

[4]  Justin M Ream,et al.  Prostate Cancer: Utility of Whole-Lesion Apparent Diffusion Coefficient Metrics for Prediction of Biochemical Recurrence After Radical Prostatectomy. , 2015, AJR. American journal of roentgenology.

[5]  He Wang,et al.  Non-Gaussian water diffusion kurtosis imaging of prostate cancer. , 2014, Magnetic resonance imaging.

[6]  Baris Turkbey,et al.  Is apparent diffusion coefficient associated with clinical risk scores for prostate cancers that are visible on 3-T MR images? , 2011, Radiology.

[7]  G. Johnson,et al.  Prostate cancer: feasibility and preliminary experience of a diffusional kurtosis model for detection and assessment of aggressiveness of peripheral zone cancer. , 2012, Radiology.

[8]  Alessandro Giuliani,et al.  multiparametric MRI of the prostate : Does intravoxel incoherent otion diffusion imaging have a role in the detection and tratification of prostate cancer in the peripheral zone ? , 2016 .

[9]  Koichi Oshio,et al.  Diffusion‐weighted imaging of prostate cancer using a statistical model based on the gamma distribution , 2015, Journal of magnetic resonance imaging : JMRI.

[10]  A. Rosenkrantz,et al.  Transition zone prostate cancer: revisiting the role of multiparametric MRI at 3 T. , 2015, AJR. American journal of roentgenology.

[11]  Thomas Hambrock,et al.  Multiparametric Magnetic Resonance Imaging for Discriminating Low-Grade From High-Grade Prostate Cancer , 2015, Investigative radiology.

[12]  H. Shinmoto,et al.  Diffusion kurtosis imaging study of prostate cancer: Preliminary findings , 2014, Journal of magnetic resonance imaging : JMRI.

[13]  K. Sugimura,et al.  Do apparent diffusion coefficient (ADC) values obtained using high b-values with a 3-T MRI correlate better than a transrectal ultrasound (TRUS)-guided biopsy with true Gleason scores obtained from radical prostatectomy specimens for patients with prostate cancer? , 2013, European journal of radiology.

[14]  P. Albers,et al.  Comparison of different mathematical models of diffusion-weighted prostate MR imaging. , 2012, Magnetic resonance imaging.

[15]  Fang-Ming Deng,et al.  Relationship Between Prebiopsy Multiparametric Magnetic Resonance Imaging (MRI), Biopsy Indication, and MRI-ultrasound Fusion-targeted Prostate Biopsy Outcomes. , 2016, European urology.

[16]  D. Bihan.  Apparent Diffusion Coefficient and Beyond: What Diffusion MR Imaging Can Tell Us about Tissue Structure , 2013 .

[17]  Katsuyoshi Ito,et al.  Diffusion‐weighted MRI and its role in prostate cancer , 2014, NMR in biomedicine.

[18]  J. Babb,et al.  Assessment of prostate cancer aggressiveness using apparent diffusion coefficient values: impact of patient race and age , 2017, Abdominal Radiology.

[19]  B. Ardekani,et al.  Estimation of tensors and tensor‐derived measures in diffusional kurtosis imaging , 2011, Magnetic resonance in medicine.

[20]  L. Egevad,et al.  The 2005 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma , 2005, The American journal of surgical pathology.

[21]  Beom Jin Park,et al.  Detectability of low and intermediate or high risk prostate cancer with combined T2-weighted and diffusion-weighted MRI , 2012, European Radiology.

[22]  J. Cho,et al.  Preoperative Evaluation of Prostate Cancer Aggressiveness: Using ADC and ADC Ratio in Determining Gleason Score. , 2016, AJR. American journal of roentgenology.

[23]  D. Margolis,et al.  MR spectroscopic imaging and diffusion‐weighted imaging of prostate cancer with Gleason scores , 2012, Journal of magnetic resonance imaging : JMRI.

[24]  Jussi Toivonen,et al.  Mathematical models for diffusion‐weighted imaging of prostate cancer using b values up to 2000 s/mm2: Correlation with Gleason score and repeatability of region of interest analysis , 2015, Magnetic resonance in medicine.

[25]  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.

[26]  T. Sone,et al.  High b Value (2,000 s/mm2) Diffusion-Weighted Magnetic Resonance Imaging in Prostate Cancer at 3 Tesla: Comparison with 1,000 s/mm2 for Tumor Conspicuity and Discrimination of Aggressiveness , 2014, PloS one.

[27]  B. Stieltjes,et al.  Evaluation of Diffusion Kurtosis Imaging Versus Standard Diffusion Imaging for Detection and Grading of Peripheral Zone Prostate Cancer , 2015, Investigative radiology.