Comparative Analysis of the Apparent Diffusion Coefficient and Diffusion Tensor Imaging in the Diagnosis of Prostate Cancer

Karakoishin, Kanat; Zholdybay, Zhamilya; Ainakulova, Akmaral; Dauytova, Yulduzkhan; Kamhen, Vitaly

doi:10.31557/APJCP.2024.25.7.2397

Comparative Analysis of the Apparent Diffusion Coefficient and Diffusion Tensor Imaging in the Diagnosis of Prostate Cancer

Document Type : Research Articles

Authors

¹ Department of Visual Diagnostics, Asfendiyarov Kazakh National Medical University, Almaty, Republic of Kazakhstan.

² Department of Radiology, Medical Center “Sunkar”, Almaty, Republic of Kazakhstan.

³ Department of Health Policy and Organization, Al-Farabi Kazakh National University, Almaty, Republic of Kazakhstan.

10.31557/APJCP.2024.25.7.2397

Abstract

Objective: The aim of this work was to demonstrate capabilities of diffusion tensor imaging as a diagnostic tool for prostate cancer in comparison with the apparent diffusion coefficient. Methods: 364 patients with suspected prostate cancer underwent multiparametric magnetic resonance imaging including diffusion tensor imaging. Results: The anatomical structure of the prostate obtained on T2-weighted imaging was compared with the apparent diffusion coefficient and diffusion tensor imaging maps. The rest of the gland (central and peripheral regions) were used as healthy areas. The apparent diffusion coefficient at diffusion-weighted imaging, fractional anisotropy and mean diffusivity at diffusion tensor imaging were evaluated in pathological zones. Cancer-suspicious areas of the prostate had high fractional anisotropy fractional anisotropy and low mean diffusivity compared to unaltered areas. Fractional anisotropy values were significantly elevated in central gland cancer, compared to normal tissue, and slightly elevated in peripheral zone cancer. Conclusion: Diffusion tensor imaging has the potential to identify prostate cancer with high accuracy and specificity. The combination of standard magnetic resonance imaging and diffusion tensor imaging can significantly improve the prognosis of the disease during active surveillance. The fractional anisotropy and mean diffusivity values can be useful in assessing the grade of malignancy and the radiolopathological correlation of the lesion.

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