Preoperative multiparametric MRI of the prostate for the prediction of lymph node metastases in prostate cancer patients treated with extended pelvic lymph node dissection
To assess the role of preoperative multiparametric MRI (mpMRI) of the prostate in the prediction of nodal metastases in patients treated with radical prostatectomy (RP) and extended pelvic lymph node dissection (ePLND).
We retrospectively analyzed 101 patients who underwent both preoperative mpMRI of the prostate and RP with ePLND at our institution. For each patient, complete preoperative clinical data and tumour characteristics at mpMRI were recorded. Final histopathologic stage was considered the standard of reference. Univariate and multivariate logistic regression analyses were performed.
Nodal metastases were found in 23/101 (22.8%) patients. At univariate analyses, all clinical and radiological parameters were significantly associated to nodal invasion (all p<0.03); tumour volume at MRI (mrV), tumour ADC and tumour T-stage at MRI (mrT) were the most accurate predictors (AUC = 0.93, 0.86 and 0.84, respectively). A multivariate model including PSA levels, primary Gleason grade, mrT and mrV showed high predictive accuracy (AUC = 0.956). Observed prevalence of nodal metastases was very low among tumours with mrT2 stage and mrV<1cc (1.8%).
Preoperative mpMRI of the prostate can predict nodal metastases in prostate cancer patients, potentially allowing a better selection of candidates to ePLND.
• Multiparametric-MRI of the prostate can predict nodal metastases in prostate cancer
• Tumour volume and stage at MRI are the most accurate predictors
• Prevalence of nodal metastases is low for T2-stage and <1cc tumours
• Preoperative mpMRI may allow a better selection of candidates to lymphadenectomy
KeywordsMagnetic resonance imaging Prostate cancer Tumour volume Lymph nodes Lymph node dissection
Extended Pelvic Lymph Node Dissection
Lymph Node Staging
T-stage at MRI
Tumour Volume at MRI
Compliance with ethical standards
The scientific guarantor of this publication is Francesco De Cobelli, M.D.
Conflict of interest
The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.
Statistics and biometry
Alessandro Ambrosi Ph.D. kindly provided statistical advice for this manuscript, and is one of the authors.
Written informed consent was obtained from all subjects (patients) in this study.
Institutional Review Board approval was obtained.
• performed at one institution
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