Preoperative multiparametric magnetic resonance imaging based risk stratification system for predicting biochemical recurrence after radical prostatectomy

Multiparametric magnetic resonance imaging (mpMRI) is used as a current marker in preoperative staging and surgical decision-making, but current evidence on predicting post-surgical oncological outcomes based on preoperative mpMRI findings is limited. In this study We aimed to develop a risk classif...

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Veröffentlicht in:Surgical oncology 2024-12, Vol.57, p.102150, Article 102150
Hauptverfasser: Akpinar, Cagri, Kuru Oz, Digdem, Oktar, Alkan, Ozsoy, Furkan, Ozden, Eriz, Haliloglu, Nuray, Ibis, Muhammed Arif, Suer, Evren, Baltaci, Sumer
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Sprache:eng
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Zusammenfassung:Multiparametric magnetic resonance imaging (mpMRI) is used as a current marker in preoperative staging and surgical decision-making, but current evidence on predicting post-surgical oncological outcomes based on preoperative mpMRI findings is limited. In this study We aimed to develop a risk classification based on mpMRI and mpMRI-derived biopsy findings to predict early biochemical recurrence (BCR) after radical prostatectomy. Between January 2017 and January 2023, the data of 289 patients who underwent mpMRI, transrectal ultrasound-guided cognitive and fusion targeted biopsies, and subsequent radical prostatectomy (RP) with or without pelvic lymph node dissection in a single center were retrospectively re-evaluated. BCR was defined as a prostate specific-antigen (PSA) ≥ 0.2 ng/mL at least twice after RP. Multivariate logistic regression models tested the predictors of BCR. The regression tree analysis stratified patients into risk groups based on preoperative mpMRI characteristics. Receiver operating characteristic (ROC)-derived area under the curve (AUC) estimates were used to test the accuracy of the regression tree–derived risk stratification tool. BCR was detected in 47 patients (16.2 %) at a median follow-up of 24 months. In mpMRI based multivariate analyses, the maximum diameter of the index lesion (HR 1.081, 95%Cl 1.015–1.151, p = 0.015) the presence of PI-RADS 5 lesions (HR 2.604, 95%Cl 1.043–6.493, p = 0.04), ≥iT3a stage (HR 2.403, 95%Cl 1.013–5.714, p = 0.046) and ISUP grade ≥4 on biopsy (HR 2.440, 95%Cl 1.123–5.301, p = 0.024) were independent predictors of BCR. In regression tree analysis, patients were stratified into three risk groups: maximum diameter of index lesion, biopsy ISUP grade, and clinical stage on mpMRI. The regression tree–derived risk stratification model had moderate-good accuracy in predicting early BCR (AUC 77 %) Straightforward mpMRI and mpMRI-derived biopsy-based risk stratification for BCR prediction provide an additional clinical predictive model to the currently available pathological risk tools. •Our homogen cohort was interpreted by two readers with extensive experience in mpMRI.•mpMRI readings and targeted-biopsies were performed by two same radiologists.•mpMRI-based findings are promising, with a predictive value of up to 78 %.•mpMRI may provide a clinical predictive model prior to radical prostatectomy.•mpMRI may aid in improving BCR-free survival and prognostication after surgery.
ISSN:0960-7404
1879-3320
1879-3320
DOI:10.1016/j.suronc.2024.102150