Dynamic evaluation of MRI-targeted, systematic and combined biopsy for prostate cancer diagnosis through 10 years of practice in a single institution

Learning curve for fusion magnetic resonance imaging targeted prostate biopsy and three-dimensional transrectal ultrasonography segmentation

OBJECTIVE

To report the learning curve of multiple operators for fusion magnetic resonance imaging (MRI) targeted biopsy and to determine the number of cases needed to achieve proficiency.

MATERIALS AND METHODS

All adult males who underwent fusion MRI targeted biopsy between February 2012 and July 2021 for clinically suspected prostate cancer (PCa) in a single centre were included. Fusion transrectal MRI targeted biopsy was performed under local anaesthesia using the Koelis platform. Learning curves for segmentation of transrectal ultrasonography (TRUS) images and the overall MRI targeted biopsy procedure were estimated with locally weighted scatterplot smoothing by computing each operator's timestamps for consecutive procedures. Non-risk-adjusted cumulative sum (CUSUM) methods were used to create learning curves for clinically significant (i.e., International Society of Urological Pathology grade ≥ 2) PCa detection.

RESULTS

Overall, 1721 patients underwent MRI targeted biopsy in our centre during the study period. The median (interquartile range) times for TRUS segmentation and for the MRI targeted biopsy procedure were 4.5 (3.5, 6.0) min and 13.2 (10.6, 16.9) min, respectively. Among the 14 operators with experience of more than 50 cases, a plateau was reached after 40 cases for TRUS segmentation time and 50 cases for overall MRI targeted biopsy procedure time. CUSUM analysis showed that the learning curve for clinically significant PCa detection required 25 to 45 procedures to achieve clinical proficiency. Pain scores ranged between 0 and 1 for 84% of patients, and a plateau phase was reached after 20 to 100 cases.

CONCLUSIONS

A minimum of 50 cases of MRI targeted biopsy are necessary to achieve clinical and technical proficiency and to reach reproducibility in terms of timing, clinically significant PCa detection, and pain.

Impact of Relative Volume Difference Between Magnetic Resonance Imaging and Three-dimensional Transrectal Ultrasound Segmentation on Clinically Significant Prostate Cancer Detection in Fusion Magnetic Resonance Imaging-targeted Biopsy

BACKGROUND

Segmentation of three-dimensional (3D) transrectal ultrasound (TRUS) images is known to be challenging, and the clinician often lacks a reliable and easy-to-use indicator to assess its accuracy during the fusion magnetic resonance imaging (MRI)-targeted prostate biopsy procedure.

OBJECTIVE

To assess the effect of the relative volume difference between 3D-TRUS and MRI segmentation on the outcome of a targeted biopsy.

DESIGN, SETTING, AND PARTICIPANTS

All adult males who underwent an MRI-targeted prostate biopsy for clinically suspected prostate cancer between February 2012 and July 2021 were consecutively included.

INTERVENTION

All patients underwent a fusion MRI-targeted prostate biopsy with a Koelis device.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Three-dimensional TRUS and MRI prostate volumes were calculated using 3D prostate models issued from the segmentations. The primary outcome was the relative segmentation volume difference (SVD) between transrectal ultrasound and MRI divided by the MRI volume (SVD = MRI volume - TRUS volume/MRI volume) and its correlation with clinically significant prostate cancer (eg, International Society of Urological Pathology [ISUP] ≥2) positiveness on targeted biopsy cores.

RESULTS AND LIMITATIONS

Overall, 1721 patients underwent a targeted biopsy resulting in a total of 5593 targeted cores. The median relative SVD was significantly lower in patients diagnosed with clinically significant prostate cancer than in those with ISUP 0-1: (6.7% [interquartile range {IQR} -2.7, 13.6] vs 8.0% [IQR 3.3, 16.4], p < 0.01). A multivariate regression analysis showed that a relative SVD of >10% of the MRI volume was associated with a lower detection rate of clinically significant prostate cancer (odds ratio = 0.74 [95% confidence interval: 0.55-0.98]; p = 0.038).

CONCLUSIONS

A relative SVD of >10% of the MRI segmented volume was associated with a lower detection rate of clinically significant prostate cancer on targeted biopsy cores. The relative SVD can be used as a per-procedure quality indicator of 3D-TRUS segmentation.

PATIENT SUMMARY

A discrepancy of ≥10% between segmented magnetic resonance imaging and transrectal ultrasound volume is associated with a reduced ability to detect significant prostate cancer on targeted biopsy cores.

Clinical and economic impact of the introduction of pre-biopsy MRI-based assessment on a large prostate cancer centre diagnostic population and activity: 10 years on

INTRODUCTION

Prostate mpMRI was introduced in 2011 as a secondary test and subsequently integrated into a prostate cancer (PCa) diagnostics unit representing a population of approximately 550,000 people. The following represents an audit of its step-wise introduction between 2 index years, 2009 and 2018, focusing on the activity, patient outcomes and economic benefits. PATIENTS AND METHODS: The 2 distinct years were selected for relying on a transrectal ultrasound biopsy pathway in 2009 to an mpMRI-based pathway in 2018. All referrals were retrospectively screened and compared for age, PSA levels, DRE findings, biopsy history, biopsy and mpMRI allocation data. Cost analysis was determined using local unit procedure costs.

RESULTS

Patients referred included 648 in 2009 and 714 in 2018. mpMRI seldomly informed decision to biopsy in 2009 (9.8%), while in 2018 it was performed in the pre-biopsy setting in 87.9% cases and enabled biopsy avoidance in 137 patients. In 2018, there was a 31.8% decrease in the number of biopsies in patients without previous PCa diagnosis, coupled with an increase in diagnostic rates of csPCa, from 28.6 to 49.0% (p < 0.0001) and a reduction in negative biopsy rates from 52.3 to 33.8%. mpMRI had a positive impact on the system with reduced patient morbidity and post-procedural complications. The estimated overall cost savings amount to approximately £75,000/year for PCa diagnosis and £11,000/year due to reduced complications.

CONCLUSION

Our evaluation shows the mpMRI-based pathway has improved early detection of csPCa and reduction of repeat biopsies, resulting in significant financial benefits for the local healthcare system.

Advancements in MRI-Based Radiomics and Artificial Intelligence for Prostate Cancer: A Comprehensive Review and Future Prospects

The use of multiparametric magnetic resonance imaging (mpMRI) has become a common technique used in guiding biopsy and developing treatment plans for prostate lesions. While this technique is effective, non-invasive methods such as radiomics have gained popularity for extracting imaging features to develop predictive models for clinical tasks. The aim is to minimize invasive processes for improved management of prostate cancer (PCa). This study reviews recent research progress in MRI-based radiomics for PCa, including the radiomics pipeline and potential factors affecting personalized diagnosis. The integration of artificial intelligence (AI) with medical imaging is also discussed, in line with the development trend of radiogenomics and multi-omics. The survey highlights the need for more data from multiple institutions to avoid bias and generalize the predictive model. The AI-based radiomics model is considered a promising clinical tool with good prospects for application.