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Can Apparent Diffusion Coefficient Values Assist PI-RADS Version 2 DWI Scoring? A Correlation Study Using the PI-RADSv2 and International Society of Urological Pathology Systems

  1. Author:
    Gaur, Sonia
    Harmon, Stephanie
    Rosenblum, Lauren
    Greer, Matthew D
    Mehralivand, Sherif
    Coskun, Mehmet
    Merino, Maria J
    Wood, Bradford J
    Shih, Joanna H
    Pinto, Peter A
    Choyke, Peter L
    Turkbey, Baris
  2. Author Address

    1 Molecular Imaging Program, National Cancer Institute, National Institutes of Health, 10 Center Dr, Rm B3B85, Bethesda, MD 20814., 2 Clinical Research Directorate, Clinical Monitoring Research Program, Leidos Biomedical Research, National Cancer Institute, Frederick, MD., 3 Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD., 4 Izmir Katip 199;elebi University, Atat 252;rk Training and Research Hospital, Izmir, Turkey., 5 Center for Interventional Oncology, Clinical Center, National Institutes of Health, Bethesda, MD., 6 Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Rockville, MD.,
    1. Year: 2018
    2. Date: Jul
    3. Epub Date: 2018 05 07
  1. Journal: AJR. American Journal of Roentgenology
    1. 211
    2. 1
    3. Pages: W33-W41
  2. Type of Article: Article
  3. ISSN: 0361-803X
  1. Abstract:

    The purposes of this study were to assess correlation of apparent diffusion coefficient (ADC) and normalized ADC (ratio of tumor to nontumor tissue) with the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) and updated International Society of Urological Pathology (ISUP) categories and to determine how to optimally use ADC metrics for objective assistance in categorizing lesions within PI-RADSv2 guidelines. In this retrospective study, 100 patients (median age, 62 years; range, 44-75 years; prostate-specific antigen level, 7.18 ng/mL; range, 1.70-84.56 ng/mL) underwent 3-T multiparametric MRI of the prostate with an endorectal coil. Mean ADC was extracted from ROIs based on subsequent prostatectomy specimens. Histopathologic analysis revealed 172 lesions (113 peripheral, 59 transition zone). Two radiologists blinded to histopathologic outcome assigned PI-RADSv2 categories. Kendall tau was used to correlate ADC metrics with PI-RADSv2 and ISUP categories. ROC curves were used to assess the utility of ADC metrics in differentiating each reader's PI-RADSv2 DWI category 4 or 5 assessment in the whole prostate and by zone. ADC metrics negatively correlated with ISUP category in the whole prostate (ADC, t = -0.21, p = 0.0002; normalized ADC, t = -0.21, p = 0.0001). Moderate negative correlation was found in expert PI-RADSv2 DWI categories (ADC, t = -0.34; normalized ADC, t = -0.31; each p < 0.0001) maintained across zones. In the whole prostate, AUCs of ADC and normalized ADC were 87% and 82% for predicting expert PI-RADSv2 DWI category 4 or 5. A derived optimal cutoff ADC less than 1061 and normalized ADC less than 0.65 achieved positive predictive values of 83% and 84% for correct classification of PI-RADSv2 DWI category 4 or 5 by an expert reader. Consistent relations and predictive values were found by an independent novice reader. ADC and normalized ADC inversely correlate with PI-RADSv2 and ISUP categories and can serve as quantitative metrics to assist with assigning PI-RADSv2 DWI category 4 or 5.

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External Sources

  1. DOI: 10.2214/AJR.17.18702
  2. PMID: 29733695
  3. WOS: 000439842000004

Library Notes

  1. Fiscal Year: FY2017-2018
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