Multiparametric MRI and MRI/TRUS Fusion Guided Biopsy for the Diagnosis of Prostate Cancer

Can a nomogram predict apical prostate cancer pathology upgrade from fusion biopsy to final pathology? A multicenter study

BACKGROUND

This study evaluates the efficacy of a nomogram for predicting the pathology upgrade of apical prostate cancer (PCa).

METHODS

A total of 754 eligible patients were diagnosed with apical PCa through combined systematic and magnetic resonance imaging (MRI)-targeted prostate biopsy followed by radical prostatectomy (RP) were retrospectively identified from two hospitals (training: 754, internal validation: 182, internal-external validation: 148). A nomogram for the identification of apical tumors in high-risk pathology upgrades through comparing the results of biopsy and RP was established incorporating statistically significant risk factors based on univariable and multivariable logistic regression. The nomogram's performance was assessed via the receiver operating characteristic (ROC) curve, calibration plots, and decision curve analysis (DCA).

RESULTS

Univariable and multivariable analysis identified age, targeted biopsy, number of targeted cores, TNM stage, and the prostate imaging-reporting and data system score as significant predictors of apical tumor pathological progression. Our nomogram, based on these variables, demonstrated ROC curves for pathology upgrade with values of 0.883 (95% CI, 0.847-0.929), 0.865 (95% CI, 0.790-0.945), and 0.840 (95% CI, 0.742-0.904) for the training, internal validation and internal-external validation cohorts respectively. Calibration curves showed good consistency between the predicted and actual outcomes. The validation groups also showed great generalizability with the calibration curves. DCA results also demonstrated excellent performance for our nomogram with positive benefit across a threshold probability range of 0-0.9 for the training and internal validation group, and 0-0.6 for the internal-external validation group.

CONCLUSION

The nomogram, integrating clinical, radiological, and pathological data, effectively predicts the risk of pathology upgrade in apical PCa tumors. It holds significant potential to guide clinicians in optimizing the surgical management of these patients.

Number of cores needed to diagnose prostate cancer during MRI targeted biopsy decreases after the learning curve

INTRODUCTION

We hypothesized that the number of cores needed to detect prostate cancer would decrease with increasing MRI-targeted biopsy (TBx) experience.

METHODS

All patients undergoing TBx at our institution from May 2017 to August 2019 were enrolled in a prospectively maintained database. Five biopsy cores were obtained from each lesion ≥3 on PI-RADS v2.0 followed by a systematic 12-core biopsy. To assess learning curve, the study population was divided into quartiles by sequential biopsies. Clinically significant prostate cancer (csPC) was defined as Gleason Grade Group 2 or higher.

RESULTS

377 patients underwent prostate biopsy (533 lesions); 233 lesions (44%) were positive for prostate cancer and 173 lesions (32%) were csPC. There was a significant decline in the number of cores required for diagnosing any cancer (P < 0.001) and csPC (P < 0.05) after the first quartile. There was no difference when stratifying by PI-RADS score or lesion volume. Within the first quartile, limiting the biopsy to 3 cores would miss 16.2% of csPC, decreasing to 6.6% after approximately 100 patients.

CONCLUSION

MRI TBx is associated with a learning curve of approximately 100 cases. Four or 5 cores should be considered during the initial experience, but thereafter, 3 cores per lesion is sufficient to detect csPC.

Software-assisted US/MRI fusion-targeted biopsy for prostate cancer

BACKGROUND

Prostate cancer is the first cancer diagnosis in men. European Association of Urology  (EAU) Guidelines for Prostate Cancer underline the importance of screening, performed through PSA testing on all men with more than 50 years of age and before on men with risk factors. The diagnosis is still histopathologic, and it is done on the basis of the findings on biopsy samples.

MATERIALS AND METHODS

Fusion biopsy is a relatively new technique that allows the operator to perform the biopsies in office instead of the MRI gantry, without losing the detection capability of MRI. The  T2-wighted images obtained during a previous mpMRI are merged with the real-time ones of the TRUS.

RESULTS

Fusion biopsy in comparison with the systematic standard biopsy has a better detection rate of clinically significant cancers and of any cancers.

CONCLUSION

EAU 2020 guidelines still do offer a list of indications of when the biopsy should be performed, but it still appeared to be overperformed. The aim of our study is to underline how, in accordance with the recent literature result,  fusion biopsy has showed a better detection rate of any cancer and clinically significant disease with a reduced numbers of samplings, and no substantial difference between the multiple software.

Brief Overview of Prostate Cancer Statistics, Grading, Diagnosis and Treatment Strategies

This chapter provides a brief overview of prostate cancer statistics, grading, diagnosis and treatment strategies that are discussed in more detail in the subsequent chapters of this book and the companion book titled "Clinical Molecular and Diagnostic Imaging of Prostate Cancer and Treatment Strategies". It also points to websites that provide additional useful information for patients affected by prostate cancer and for students and teachers to obtain practical and updated information on research, new diagnostic modalities and new therapies including new updated clinical trials. Three sections are focused on overview of prostate cancer statistics; overview of detection, diagnosis, stages and grading of prostate cancer; and treatment possibilities and options.