Magnetic Resonance Imaging–based T-staging to Predict Biochemical Recurrence after Radical Prostatectomy: A Step Towards the iTNM Classification

Baboudjian, Michael; Gondran-Tellier, Bastien; Touzani, Alae; Martini, Alberto; Diamand, Romain; Roche, Jean-Baptiste; Lacetera, Vito; Beauval, Jean-Baptiste; Roumeguère, Thierry; Simone, Guiseppe; Benamran, Daniel; Fourcade, Alexandre; Fiard, G.; Bergh, Roderick C.N. van den; Peltier, Alexandre; Ploussard, Guillaume

doi:10.1016/j.euo.2022.09.005

Cited by 8 publications

(3 citation statements)

References 23 publications

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“…Therefore, it is possible that when using mpMRI for local staging, the rate of patients harbouring T2c or higher diseases would increase, potentially reducing the impact of PSA and GGG in predicting NOC disease, especially concerning ECE. However, a magnetic resonance imaging-based T-staging will be applied, as recently proposed [ 18 ], and DRE remains the standard for risk stratification in guideline recommendations, clinical trials, and patient counselling. Future studies are needed to understand if a change in TNM classification would affect our current results.…”

Section: Discussionmentioning

confidence: 99%

The association of the type and number of D’Amico high-risk criteria with rates of pathologically non-organ-confined prostate cancer

2023

Cent European J Urol

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Introduction The aim of this study was to assess the association between the type and number of D’Amico high-risk criteria (DHRCs) with rates of pathologically non-organ-confined (NOC) prostate cancer in patients treated with radical prostatectomy (RP) and pelvic lymphadenectomy (PLND). Material and methods In the Surveillance, Epidemiology, and End Results database (2004–2016), we identified 12961 RP and PLDN patients with at least one DHRC. We relied on descriptive statistics and multivariable logistic regression models. Results Of 12 961 patients, 6135 (47%) exclusively harboured biopsy Gleason score (GS) 8–10, 3526 (27%) had clinical stage ≥T2c, and 1234 (9.5%) had prostate-specific antigen (PSA) >20 ng/mL. Only 1886 (15%) harboured any combination of 2 DHRCs. Finally, all 3 DHRCs were present in 180 (1.4%) patients. NOC rates increased from 32% for clinical T stage ≥T2c to 49% for either GS 8–10 only or PSA >20 ng/mL only and to 66–68% for any combination of 2 DHRCs, and to 84% for respectively all 3 DHRCs, which resulted in a multivariable logistic regression OR of 1.00, 2.01 (95% CI 1.85–2.19; p <0.001), 4.16 (95% CI 3.69–4.68; p <0.001), and 10.83 (95% CI 7.35–16.52; p <0.001), respectively. Conclusions Our study indicates a stimulus-response effect according to the type and number of DHRCs. Hence, a formal risk-stratification within high-risk prostate cancer patients should be considered in clinical decision-making.

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Section: Discussionmentioning

confidence: 99%

The association of the type and number of D’Amico high-risk criteria with rates of pathologically non-organ-confined prostate cancer

2023

Cent European J Urol

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“…mpMRI-based biopsy strategies have been shown to improve the detection of clinically significant disease while reducing the detection of clinically insignificant disease [1][2][3][4] . Furthermore, the characteristics of dominant intraprostatic lesions (DILs) on mpMRI, including PI-RADS scores 5 , radiologic T-stage 6,7 , and lesion size [8][9][10][11] , have been shown to be prognostic. Recently, a nomogram based on clinical and radiologic parameters was found to be highly prognostic for early biochemical recurrence after radical prostatectomy 12 .…”

Section: Introductionmentioning

confidence: 99%

Association Between Artificial Intelligence-Derived Tumor Volume and Oncologic Outcomes for Localized Prostate Cancer Treated with Radiation Therapy

Yang

Lee

Tsui³

et al. 2023

Preprint

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Background: Although clinical features of multi-parametric magnetic resonance imaging (mpMRI) have been associated with biochemical recurrence in localized prostate cancer, such features are subject to inter-observer variability. Objective: To evaluate whether the volume of the dominant intraprostatic lesion (DIL), as provided by a deep learning segmentation algorithm, could provide prognostic information for patients treated with definitive radiation therapy (RT). Design, Setting, and Participants: Retrospective study of 438 patients with localized prostate cancer who underwent an endorectal coil, high B-value, 3-Tesla mpMRI and were treated with RT between 2010 and 2017. Intervention: RT. Outcome Measurements and Statistical Analysis: Biochemical recurrence and metastasis risk, assessed with a cause-specific Cox regression and time-dependent receiver operating characteristic analysis. Results and Limitations: The artificial intelligence (AI) model identified DILs with an area under the receiver operating characteristic curve (AUROC) of 0.827 at the patient level. For the 233 patients with available PI-RADS scores, with a median follow-up of 5.6 years, AI-defined DIL volume was significantly associated with biochemical failure (adjusted hazard ratio 1.54, 95% confidence interval 1.09-2.17, p=0.014) after adjustment for PI-RADS score. Among all 438 patients with a median follow-up of 6.9 years, the AUROC for predicting 7-year biochemical failure for AI volume (0.790) was similar to that for an expanded National Comprehensive Cancer Network (NCCN+) category (p=0.17). The AUROC for predicting 7-year metastasis for AI volume trended towards being higher compared to NCCN+ categories (0.854 vs 0.769, p=0.06). Conclusions: A deep learning algorithm could identify the DIL with good performance. AI-defined DIL volume may be able to provide prognostic information independent of the NCCN+ risk group or other radiologic factors for patients with localized prostate cancer treated with RT.

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“…These parameters include the clinical T stage, PSA level, and tumor’s Gleason grade group [ 3 ]. Several studies already revealed that the combination of clinical parameters and parameters extracted from pre-biopsy mpMRI may improve the performance of risk stratification for distant metastasis and biochemical recurrence (BCR) [ 8 – 15 ]. Mazzone et al developed a novel classification integrating clinical and MRI parameters to assess the risk for disease recurrence.…”

Section: Introductionmentioning

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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Magnetic Resonance Imaging–based T-staging to Predict Biochemical Recurrence after Radical Prostatectomy: A Step Towards the iTNM Classification

Cited by 8 publications

References 23 publications

The association of the type and number of D’Amico high-risk criteria with rates of pathologically non-organ-confined prostate cancer

The association of the type and number of D’Amico high-risk criteria with rates of pathologically non-organ-confined prostate cancer

Association Between Artificial Intelligence-Derived Tumor Volume and Oncologic Outcomes for Localized Prostate Cancer Treated with Radiation Therapy

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

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