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Published on: December 15, 2014
Prognostic Value of MRI-Derived Apparent Diffusion Coefficient in Intermediate-Risk Prostate Cancer Treated With
Cem Onal1,2, Gurcan Erbay3, Aysenur Elmali2
1Department of Radiation Oncology, Adana Dr. Turgut Noyan Research and Treatment Center, Baskent University Faculty of Medicine, Adana, Turkiye.
Background:
Intermediate-risk prostate cancer (IR-PCa) is a heterogeneous disease with variable clinical outcomes despite established risk classification. We evaluated whether pretreatment tumor apparent diffusion coefficient (ADC) derived from multiparametric MRI was associated with long-term outcomes and provided additional prognostic information beyond established clinical risk classification in patients treated with definitive radiotherapy.
Methods And Materials:
We retrospectively analyzed 238 patients with IR-PCa treated with definitive radiotherapy. Tumor ADC values were obtained from pre-treatment diffusion-weighted MRI. Patients were stratified according to ADC levels and clinical risk subgroups, including favorable and unfavorable intermediate-risk disease. Survival analyses and Cox regression models were used to assess associations between ADC and clinical outcomes, including biochemical failure and distant metastasis.
Results:
At a median follow-up of 10.3 years, 22 patients developed biochemical failure, and 12 developed distant metastases. Lower ADC values (≤ 0.668 × 10-3 mm2/s) were associated with inferior outcomes, with a significant impact on freedom from distant metastasis (FFDM) (HR 3.94, 95% CI 1.14-13.62; p = 0.03). When ADC was combined with clinical risk classification, outcomes differed across the four resulting subgroups for both FFDM (p = 0.02) and FFBF (p = 0.02). However, the FIR-low ADC subgroup included only seven patients, and these subgroup findings should be considered exploratory.
Conclusions:
Lower tumor ADC was associated with an increased risk of distant metastasis and provided exploratory prognostic information beyond established clinical risk classification. Given the limited number of events and the data-derived cutoff, these findings require external validation before ADC can be used to guide treatment selection.
