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ORIGINAL RESEARCH article

Front. Oncol.
Sec. Cancer Imaging and Image-directed Interventions
Volume 14 - 2024 | doi: 10.3389/fonc.2024.1450388
This article is part of the Research Topic Dynamic Contrast-enhanced Imaging: Technology Progress and Clinical Application in Oncology View all 3 articles

Comparison of Tracer Kinetic Models in Differentiating Malignant from Normal Prostate Tissue Using Dynamic Contrast-Enhanced MRI

Provisionally accepted
Hongjiang Zhang Hongjiang Zhang 1Jing Yang Jing Yang 1Kunhua Wu Kunhua Wu 1Zujun Hou Zujun Hou 2Ji Du Ji Du 1Jianhua Yan Jianhua Yan 3*Ying Zhao Ying Zhao 1*
  • 1 Department of MRI, The First People’s Hospital of Yunnan Province, the Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan Province, China
  • 2 Jiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China
  • 3 Department of Nuclear Medicine, The First Affiliated Hospital of USTC, hefei, China

The final, formatted version of the article will be published soon.

    The aim of this study was to evaluate the diagnostic value of dynamic contrastenhanced magnetic resonance imaging (DCE-MRI) derived kinetic parameters with high spatiotemporal resolution in discriminating malignant from normal prostate tissues.: Fifty patients with suspicious of malignant diseases in prostate were included in this study. Regions of interest (ROI) were manually delineated by experienced radiologists. Voxel-wise kinetic parameters were produced with the following tracer kinetic models (TKMs): Tofts model, extended Tofts model (ETM), Brix's conventional two-compartment model (Brix), adiabatic tissue homogeneity model (ATH), and distributed parameter model (DP). The initial area under the signaltime curve (IAUC) with an uptake integral approach was also included. Mann-Whitney U test and receiver operating characteristic (ROC) curves were used to evaluate the capability of distinguishing tumor lesions from normal tissues. A p-value of 0.05 or less is considered statistically significant. ROI based parameters correlation analysis between DP and ETM were performed. Results:624 lesions and 269 normal tissue ROIs were obtained. Thirty parameters were derived from the six kinetic models. Except for PS from Brix, statistically significant differences between lesions and normal tissues (P<0.05) were observed in other parameters.Ve from DP, ATH and Brix and PS from ATH have AUC values less than 0.6 in the ROC analysis. MTT, Vp and PS from DP, Ktrans from ETM and Tofts, E and PS from ATH, IAUC parameters and F from Brix have AUC values larger than 0.8. Ve and Vp from DP and ETM are correlated (r> 0.65). The correlation coefficient between Ktrans from ETM and PS from DP is 0.751. Conclusion: MTT, Vp and PS from DP, Ktrans from ETM and Tofts, E and PS from ATH, F from Brix and IAUC parameters can be used to differentiate malignantlesions from normal tissues in the prostate.

    Keywords: DCE MRI, tracer kinetic modeling, prostate cancer, quantitative, Gleason Score

    Received: 17 Jun 2024; Accepted: 15 Nov 2024.

    Copyright: © 2024 Zhang, Yang, Wu, Hou, Du, Yan and Zhao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Jianhua Yan, Department of Nuclear Medicine, The First Affiliated Hospital of USTC, hefei, China
    Ying Zhao, Department of MRI, The First People’s Hospital of Yunnan Province, the Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan Province, China

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