How to Improve TRUS-Guided Target Biopsy following Prostate MRI

Raman spectroscopy system for real-time diagnosis of clinically significant prostate cancer tissue

Prostate cancer (PCa) is a significant healthcare problem worldwide. Current diagnosis and treatment methods are limited by a lack of precise in vivo tissue analysis methods. Real-time cancer identification and grading could dramatically improve current protocols. Here, we report the testing of a thin optical probe using Raman spectroscopy (RS) and classification methods to detect and grade PCa accurately in real-time. We present the first clinical trial on fresh ex vivo biopsy cores from an 84 patient cohort. Findings from 2395 spectra measured on 599 biopsy cores show high accuracy for diagnosing and grading PCa. We can detect clinically significant PCa from benign and clinically insignificant PCa with 90% sensitivity and 80.2% specificity. We also demonstrate the ability to differentiate cancer grades with 90% sensitivity and specificity ≥82.8%. This work demonstrates the utility of RS for real-time PCa detection and grading during routine transrectal biopsy appointments.

Developing a predictive model for clinically significant prostate cancer by combining age, PSA density, and mpMRI

PURPOSE

The study aimed to construct a predictive model for clinically significant prostate cancer (csPCa) and investigate its clinical efficacy to reduce unnecessary prostate biopsies.

METHODS

A total of 847 patients from institute 1 were included in cohort 1 for model development. Cohort 2 included a total of 208 patients from institute 2 for external validation of the model. The data obtained were used for retrospective analysis. The results of magnetic resonance imaging were obtained using Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1). Univariate and multivariate analyses were performed to determine significant predictors of csPCa. The diagnostic performances were compared using the receiver operating characteristic (ROC) curve and decision curve analyses.

RESULTS

Age, prostate-specific antigen density (PSAD), and PI-RADS v2.1 scores were used as predictors of the model. In the development cohort, the areas under the ROC curve (AUC) for csPCa about age, PSAD, PI-RADS v2.1 scores, and the model were 0.675, 0.823, 0.875, and 0.938, respectively. In the external validation cohort, the AUC values predicted by the four were 0.619, 0.811, 0.863, and 0.914, respectively. Decision curve analysis revealed that the clear net benefit of the model was higher than PI-RADS v2.1 scores and PSAD. The model significantly reduced unnecessary prostate biopsies within the risk threshold of > 10%.

CONCLUSIONS

In both internal and external validation, the model constructed by combining age, PSAD, and PI-RADS v2.1 scores exhibited excellent clinical efficacy and can be utilized to reduce unnecessary prostate biopsies.

TRUS-Guided Target Biopsy for a PI-RADS 3–5 Index Lesion to Reduce Gleason Score Underestimation: A Propensity Score Matching Analysis

Background

Magnetic resonance imaging (MRI) and transrectal ultrasound (TRUS)-guided cognitive or image fusion biopsy is performed to target a prostate imaging reporting and data system (PI-RADS) 3–5 lesion. Biopsy Gleason score (GS) is frequently underestimated compared to prostatectomy GS. However, it is still unclear about how many cores on target are necessary to reduce undergrading and if additional cores around the target may improve grade prediction on surgical specimen.

Purpose

To determine the number of target cores and targeting strategy to reduce GS underestimation.

Materials and Methods

Between May 2017 and April 2020, a total of 385 patients undergoing target cognitive or image fusion biopsy of PI-RADS 3–5 index lesions and radical prostatectomies (RP) were 2:1 matched with propensity score using multiple variables and divided into the 1–4 core (n = 242) and 5–6 core (n = 143) groups, which were obtained with multiple logistic regression with restricted cubic spline curve. Target cores of 1–3 and 4–6 were sampled from central and peripheral areas, respectively. Pathologic outcomes and target cores were retrospectively assessed to analyze the GS difference or changes between biopsy and RP with Wilcoxon signed-rank test.

Results

The median of target cores was 3 and 6 in the 1–4 core and 5–6 core groups, respectively (p < 0.001). Restricted cubic spline curve showed that GS upgrade was significantly reduced from the 5th core and there was no difference between 5th and 6th cores. Among the matched patients, 35.4% (136/385; 95% confidence interval, 0.305–0.403) had a GS upgrade after RP. The GS upgrades in the 1–4 core and 5–6 core groups were observed in 40.6% (98/242, 0.343–0.470) and 26.6% (38/143, 0.195–0.346), respectively (p = 0.023). Although there was no statistical difference between the matched groups in terms of RP GS (p = 0.092), the 5–6 core group had significantly higher biopsy GS (p = 0.006) and lower GS change from biopsy to RP (p = 0.027).

Conclusion

Five or more target cores sampling from both periphery and center of an index tumor contribute to reduce GS upgrade.