Value of the capsular enhancement sign on dynamic contrast-enhanced prostate multiparametric MRI for the detection of extracapsular extension

Imaging Assessment of Prostate Cancer Extra-prostatic Extension: From Histology to Controversies

Prostate cancer (PCa) is the most common non-skin malignancy among men and the fourth leading cause of cancer-related deaths globally. Accurate staging of PCa, particularly the assessment of extra-prostatic extension (EPE), is critical for prognosis and treatment planning. EPE, typically evaluated using magnetic resonance imaging (MRI), is associated with higher risks of positive surgical margins, biochemical recurrence, metastasis, and reduced overall survival. Despite the widespread use of MRI, there is no consensus on diagnosing EPE via imaging. There are 2 main scores assessing EPE by MRI: the European Society of Urogenital Radiology score and an MRI-based EPE grading system from an American group. While both are widely recognized, their differences can lead to varying interpretations in specific cases. This paper clarifies the anatomical considerations in diagnosing locally advanced PCa, explores EPE's impact on treatment and prognosis, and evaluates the relevance of MRI findings according to different criteria. Accurate EPE diagnosis remains challenging due to MRI limitations and inconsistencies in interpretation. Understanding these variations is crucial for optimal patient management.

Extra-prostatic extension grading system: correlation with MRI features and integration of capsular enhancement sign for "enhanced" detection of T3a lesions

PURPOSE

This study aims to confirm the diagnostic accuracy of extra-prostatic extension (EPE) grading system and to explore the predictive capabilities of the prostate MRI while considering various MRI features such as lesion location, apparent diffusion coefficient (ADC) values and capsular enhancement sign (CES).

METHODS

Our monocentric study is based on a retrospective analysis of 99 patients who underwent radical prostatectomy from January 2021 to January 2023. The observers reviewed for each lesion, including location (transitional or peripheral zone, anterior or posterior location), capsular contact length, irregular bulging of the capsule, asymmetry of the neurovascular bundle, obliteration of the recto-prostatic angle, macroscopic EPE, ADC value, and CES.

RESULTS

Among 99 patients, 31 patients had EPE. Lesions with EPE have broadercapsule contact (24 mm vs 12 mm) with contact ≥14 mm being the optimal cut-off for EPE discrimination. Among the morphological MRI criteria used to determine the EPE, the one with major sensitivity was shown to be bulging (sen 81%), while macroscopic extension had highest specificity (100%). Univariate analysis showed as significative risk factors for EPE: capsular contact ≥14 mm (P < .001), International Society of Urological Pathology score ≥3 (P = .005), CES (P < .001), bulging (P = .001), neurovascular bundle asymmetry (P < .001) and EPE score ≥2 (P < .001), and in multivariate analysis CES (P = .001) and EPE score ≥2 (P = .004) were significant. The AUC of the EPE score was 0.76, raised to 0.83 when combining it with CES (P = .11).

CONCLUSION

CES in the setting of multiparametric MRI can increase diagnostic accuracy for the prediction of extracapsular disease.

ADVANCES IN KNOWLEDGE

This study highlights the potential of contrast media in prostate cancer local staging.

Extracapsular extension of transitional zone prostate cancer miss-detected by multiparametric magnetic resonance imaging

OBJECTIVES

To demonstrate the importance of extracapsular extension (ECE) of transitional zone (TZ) prostate cancer (PCa), examine the causes of its missed detection by Mp-MRI, and develop a new predictive model by integrating multi-level clinical variables.

MATERIALS AND METHODS

This retrospective study included 304 patients who underwent laparoscopic radical prostatectomy after 12 + X needle transperineal transrectal ultrasound (TRUS)-MRI-guided targeted prostate biopsy from 2018 to 2021 in our center was performed.

RESULTS

In this study, the incidence rates of ECE were similar in patients with MRI lesions in the peripheral zone (PZ) and TZ (P = 0.66). However, the missed detection rate was higher in patients with TZ lesions than in those with PZ lesions (P < 0.05). These missed detections result in a higher positive surgical margin rate (P < 0.05). In patients with TZ lesions, detected MP-MRI ECE may have grey areas: the longest diameters of the MRI lesions were 16.5-23.5 mm; MRI lesion volumes were 0.63-2.51 ml; MRI lesion volume ratios were 2.75-8.86%; PSA were 13.85-23.05 ng/ml. LASSO regression was used to construct a clinical prediction model for predicting the risk of ECE in TZ lesions from the perspective of MRI and clinical features, including four variables: the longest diameter of MRI lesions, TZ pseudocapsule invasion, ISUP grading of biopsy pathology, and number of positive biopsy needles.

CONCLUSIONS

Patients with MRI lesions in the TZ have the same incidence of ECE as those with lesions in the PZ, but a higher missed detection rate.

Beyond diagnosis: is there a role for radiomics in prostate cancer management?

The role of imaging in pretreatment staging and management of prostate cancer (PCa) is constantly evolving. In the last decade, there has been an ever-growing interest in radiomics as an image analysis approach able to extract objective quantitative features that are missed by human eye. However, most of PCa radiomics studies have been focused on cancer detection and characterisation. With this narrative review we aimed to provide a synopsis of the recently proposed potential applications of radiomics for PCa with a management-based approach, focusing on primary treatments with curative intent and active surveillance as well as highlighting on recurrent disease after primary treatment. Current evidence is encouraging, with radiomics and artificial intelligence appearing as feasible tools to aid physicians in planning PCa management. However, the lack of external independent datasets for validation and prospectively designed studies casts a shadow on the reliability and generalisability of radiomics models, delaying their translation into clinical practice.Key points• Artificial intelligence solutions have been proposed to streamline prostate cancer radiotherapy planning.• Radiomics models could improve risk assessment for radical prostatectomy patient selection.• Delta-radiomics appears promising for the management of patients under active surveillance.• Radiomics might outperform current nomograms for prostate cancer recurrence risk assessment.• Reproducibility of results, methodological and ethical issues must still be faced before clinical implementation.