Quantitative parameters in dynamic contrast-enhanced magnetic resonance imaging for the detection and characterization of prostate cancer

Cheng Wei, Bowen Jin, Magdalena Szewczyk-Bieda, Stephen Gandy, Stephen Lang, Yilong Zhang, Zhihong Huang, Ghulam Nabi (Lead / Corresponding author)

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    27 Citations (Scopus)
    204 Downloads (Pure)


    Objectives: to assess the diagnostic accuracy of quantitative parameters of DCE-MRI in multi-parametric MRI (mpMRI) in comparison to the histopathology (including Gleason grade) of prostate cancer.

    Patients and methods: 150 men with suspected prostate cancer (abnormal digital rectum examination and or elevated prostate-specific antigen) received pre-biopsy 3T mpMRI and were recruited into peer-reviewed, protocol-based prospective study. The DCE-MRI quantitative parameters (Ktrans (influx transfer constant) and kep (efflux rate constant)) of the cancerous and normal areas were recorded using four different kinetic models employing Olea Sphere (Olea Medical, La Ciotat, France). The correlation between these parameters and the histopathology of the lesions (biopsy and in a sub-cohort 41 radical prostatectomy specimen) was assessed.

    Results: The quantitative parameters showed a significant difference between non-cancerous (benign) and cancerous lesions (Gleason score≥3+3) in the prostate gland. The cut-off values for prostate cancer differentiation were: Ktrans (0.205 min-1) and kep (0.665 min-1) in the extended Tofts model (ET) and Ktrans(0.205 min-1 and kep (0.63 min-1) in the Lawrence and Lee delay (LD) models respectively. The mean Ktrans value also showed a difference between low-grade cancer (Gleason score=3+3) and high-grade cancer (Gleason score ≥ 3+4). With the addition of DCE-MRI quantitative parameters, the sensitivity of the PIRAD scoring system was increased from 56.6% to 92.1% (Ktrans_ET), 93.1% (kep_ET), 91.0%, (Ktrans_LD) and 89.4% (kep_LD).

    Conclusion: Quantitative DCE-MRI parameters improved the diagnostic performance of conventional MRI in distinguishing normal and prostate cancers, including characterization of grade of cancers. The ET and LD models in post-image processing analysis provided better cut-off values for prostate cancer differentiation than the other quantitative DCE-MRI parameters.
    Original languageEnglish
    Pages (from-to)15997-16007
    Number of pages11
    Issue number22
    Publication statusPublished - 23 Mar 2018


    • Dynamic contrast-enhanced magnetic resonance imaging
    • Kinetic models
    • Multi-parametric magnetic resonance imaging
    • Prostate cancer

    ASJC Scopus subject areas

    • Oncology


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