Pre-operative magnetic resonance imaging can predict prostate cancer with risk for positive surgical margins

Quentin, Michael; Schimmöller, Lars; Ullrich, T.; Valentin, Birte; Demetrescu, D.; Al-Monajjed, Rouvier; Mally, David; Espósito, Irene; Albers, Peter; Antoch, Gerald; Arsov, Christian

doi:10.1007/s00261-022-03543-z

Cited by 13 publications

(21 citation statements)

References 23 publications

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“…Yao et al demonstrated that preoperative MRI finding was a significant predictor of PSM especially at the prostatic apex 53 . Quentin et al found that the tumor distance to the MU ≤ 3.5 mm was the strongest MRI predictor for PSM at the apical urethra, with showing the highest accuracy of 95% 16 .…”

Section: Discussionmentioning

confidence: 99%

Multiparametric Magnetic Resonance Imaging-based Prostate Specific Antigen Density and PI-RADSv2 score help identify Apical Prostate Cancer

Huang¹,

Rui²,

Feng³

et al. 2023

J. Cancer

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Objective: To investigate the potential roles of preoperative multiparametric magnetic resonance imaging (mpMRI) in identifying aggressive apical prostate cancer (APCa), thereby helping to facilitate patient counseling and surgical planning. Patients and Methods: We performed a retrospective analysis of 662 patients who underwent radical prostatectomy (RP) between January 2010 to October 2019. All patients underwent a preoperative biopsy and mpMRI of the prostate. APCa was defined as any malignant lesions in the prostatic apex. Clinical, pathological and mpMRI variables were retrieved. Univariate, multivariate, and receiver operating characteristic (ROC) analyses were performed. Results: A total of 214 (32.3%) patients had APCa. Patients presenting APCa were more likely to harbor adverse clinicopathological features (all p < 0.05). On univariable analysis, serum prostate-specific antigen (PSA) ( p < 0.001), mpMRI-based PSA density (PSAD) ( p < 0.001), Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) score ( p < 0.001), number of positive cores ( p < 0.001), percentage of positive cores ( p < 0.001), max core involvement ( p < 0.001) and biopsy GG ( p = 0.001) were significant predictors of APCa. On multivariable analysis, mpMRI-based PSAD ≥ 0.27 ng/ml/cm 3 (odds ratio [OR]: 2.251, p = 0.003), PI-RADSv2 score > 4 (OR: 1.611, p = 0.023) and percentage of positive cores (OR: 2.333, p = 0.041) were independently predictive of APCa during RP. The AUC values of mpMRI-based PSAD and PI-RADSv2 score were 0.646 (95% Confidence Intervals [CI]: 0.608-0.682) and 0.612 (95% CI: 0.568-0.656), respectively. Conclusion: Preoperative mpMRI-based PSAD and PI-RADSv2 score help identify the presence of APCa and may be useful for surgical decision-making during RP.

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Section: Discussionmentioning

confidence: 99%

Multiparametric Magnetic Resonance Imaging-based Prostate Specific Antigen Density and PI-RADSv2 score help identify Apical Prostate Cancer

Huang¹,

Rui²,

Feng³

et al. 2023

J. Cancer

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“…Moreover, MRI has the ability to predict extracapsular extension and cT stage and is a valid predictor in PC staging [ 25 , 26 ]. For non-metastatic disease in the high-risk group, surgical treatment remains the first option and adjuvant treatment (e.g., radiation therapy or androgen deprivation) might be necessary in some cases, based on the results of RPE histopathology.…”

Section: Discussionmentioning

confidence: 99%

MRI characteristics and oncological follow-up of patients with ISUP grade group 4 or 5 prostate cancer

Boschheidgen,

Schimmöller,

Kastl

et al. 2023

Abdom Radiol

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Objectives To analyze multiparametric MRI (mpMRI) characteristics of patients with International Society of Urological Pathology (ISUP) grade group (GG) 4 or 5 prostate cancer (PC) and to correlate MRI parameters with the occurrence of biochemical recurrence (BCR) after radical prostatectomy (RPE). Methods In this single-center cohort study consecutive patients with mpMRI and ISUP GG 4 or 5 PC were retrospectively analyzed. Clinical, MR-guided biopsy, and diagnostic mpMRI parameter were assessed. A subcohort of patients with RPE and follow-up was analyzed separately. A univariate and multivariate analyses were performed to determine parameters that are associated to patients with BCR after RPE. Results 145 patients (mean age 70y, median PSA 10.9 ng/ml) were analyzed. 99% had a PI-RADS classification of 4 or 5, 48% revealed MRI T3 stage, and median diameter of the MRI index lesion (IL) was 15 mm. IL showed a median ADC value of 668 ×10−6 mm2/s and exhibited contrast enhancement in 94% of the cases. For patients with follow-up after RPE (n = 82; mean follow-up time 68 ± 27 m), MRI parameters were significantly different for contact length of the IL to the pseudocapsule (LCC), MRI T3 stage, and IL localization (p < 0.05). Higher PSAD and MRI T3 stage were independent parameters for the risk of BCR when incorporating clinical, biopsy, and MRI parameters. Conclusion ISUP GG 4 or 5 PC has distinctive characteristics on mpMRI and were detected on MRI in all cases. In addition, higher PSAD and MRI T3 stage were significant predictors for BCR after RPE.

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“…A retrospective study of 179 patients with in-house robotic assisted LRP, M. Quentin et al. found that length of capsular tumor contact was the best MRI predictor for PSMs at the capsule and distance to the membranous urethra for tumors with PSMs at the apical urethra ( 32 ). Irini Youssef et al.…”

Section: Discussionmentioning

confidence: 99%

Multiparametric MRI-based nomograms in predicting positive surgical margins of prostate cancer after laparoscopic radical prostatectomy

et al. 2022

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BackgroundPositive surgical margins (PSMs) are an independent risk factor of biochemical recurrence in patients with prostate cancer (PCa) after laparoscopic radical prostatectomy; however, limited MRI-based predictive tools are available. This study aimed to develop a novel nomogram combining clinical and multiparametric MRI (mpMRI) parameters to reduce PSMs by improving surgical planning.MethodsOne hundred and three patients with PCa (55 patients with negative surgical margins [NSMs] and 48 patients with PSMs) were included in this retrospective study. The following parameters were obtained using GE Functool post-processing software: diffusion-weighted imaging (DWI); intravoxel incoherent motion model (IVIM); and diffusion kurtosis imaging (DKI). Patients were divided into different training sets and testing sets for different targets according to a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) regression algorithm was used to analyze the data set to select the optimal MRI predictors. Preoperatively clinical parameters used to build a clinical nomogram (C-nomogram). Multivariable logistic regression analysis was used to build an MRI nomogram (M-nomogram) by introducing the MRI parameters. Based on the MRI and clinical parameters, build an MRI combined with clinical parameters nomogram (MC-nomogram). Comparisons with the M-nomogram and MC-nomogram were based on discrimination, calibration, and decision curve analysis (DCA). A 3-fold cross-validation method was used to assess the stability of the nomogram.ResultsThere was no statistical difference in AUC between the C-nomogram (sensitivity=64%, specificity=65% and AUC=0.683), the M-nomogram (sensitivity=57%, specificity=88% and AUC=0.735) and the MC-nomogram (sensitivity= 64%, specificity=82% and AUC=0.756). The calibration curves of the three nomograms used to predict the risk of PSMs in patients with PCa showed good agreement. The net benefit of the MC-nomogram was higher than the others (range, 0.2-0.7).ConclusionsThe mpMRI-based nomogram can predict PSMs in PCa patients. Although its AUC (0.735) is not statistically different from that of the clinical-based nomogram AUC (0.683). However, mpMRI-based nomogram has higher specificity (88% VS. 63%), model stability, and clinical benefit than clinical-based nomogram. And the predictive ability of mpMRI plus clinical parameters for PSMs is further improved.

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Pre-operative magnetic resonance imaging can predict prostate cancer with risk for positive surgical margins

Cited by 13 publications

References 23 publications

Multiparametric Magnetic Resonance Imaging-based Prostate Specific Antigen Density and PI-RADSv2 score help identify Apical Prostate Cancer

Multiparametric Magnetic Resonance Imaging-based Prostate Specific Antigen Density and PI-RADSv2 score help identify Apical Prostate Cancer

MRI characteristics and oncological follow-up of patients with ISUP grade group 4 or 5 prostate cancer

Multiparametric MRI-based nomograms in predicting positive surgical margins of prostate cancer after laparoscopic radical prostatectomy

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