MRI/Transrectal Ultrasound Fusion-Guided Targeted Biopsy and Transrectal Ultrasound-Guided Systematic Biopsy for Diagnosis of Prostate Cancer: A Systematic Review and Meta-analysis

Normalised repeat serum prostate-specific antigen: associations with age and magnetic resonance imaging results

OBJECTIVE

To assess the value of a repeat prostate-specific antigen measurement (PSA2) before magnetic resonance imaging (MRI) in men with a raised PSA (PSA1) <10 µg/L.

METHOD

Medical records of men aged < 75 years referred in 2021 for PSA1 3.0-9.9 µg/L (< 70 years) or 5.0-9.9 µg/L (70-74 years) were reviewed. PSA2 was sampled before MRI within 60 days from PSA1. Odds ratios (ORs) were calculated with logistic regression. Chi-square and trend-test were used for categorical variables.

RESULTS

A total of 341 men were included. Median time between PSA1 and PSA2 was 28 days (interquartile range 20-35 days). PSA normalised in 16% (95% confidence interval [CI]: 13-21). Younger men were more likely to have a normal PSA2 (OR: 0.95 per year older, 95% CI: 0.92-0.99). Among men aged < 70 years, those with PSA1 < 5 µg/L were more likely to have normalised PSA2 than those with PSA1 ≥ 5 µg/L (21% vs. 10%, p = 0.01). A greater proportion of men with normalised PSA2 had a Prostate Imaging Data and Reporting System MRI score of 1-3 than men with non-normalised PSA2 (93% vs. 77%, p = 0.01).

CONCLUSIONS

A clinically significant proportion of men with a moderately raised PSA value have a normal PSA2. Younger men and men with lower PSA1 were more likely to have a normal PSA2. Few men with normalised PSA2 had suspicious MRI findings. Routine repeat PSA-testing may be motivated in men with a moderately raised PSA value to save MRI resources, particularly in younger men.

Key learning on the promise and limitations of MRI in prostate cancer screening

MRI retains its ability to reduce the harm of prostate biopsies by decreasing biopsy rates and the detection of indolent cancers in population-based screening studies aiming to find clinically significant prostate cancers. Limitations of low positive predictive values and high reader variability in diagnostic performance require optimisations in patient selection, imaging protocols, interpretation standards, diagnostic thresholds, and biopsy methods. Improvements in diagnostic accuracy could come about through emerging technologies like risk calculators and polygenic risk scores to select men for MRI. Furthermore, artificial intelligence and workflow optimisations focused on streamlining the diagnostic pathway, quality control, and assurance measures will improve MRI variability. CLINICAL RELEVANCE STATEMENT: MRI significantly reduces harm in prostate cancer screening, lowering unnecessary biopsies and minimizing the overdiagnosis of indolent cancers. MRI maintains the effective detection of high-grade cancers, thus improving the overall benefit-to-harm ratio in population-based screenings with or without using serum prostate-specific antigen (PSA) for patient selection. KEY POINTS: • The use of MRI enables the harm reduction benefits seen in individual early cancer detection to be extended to both risk-stratified and non-stratified prostate cancer screening populations. • MRI limitations include a low positive predictive value and imperfect reader variability, which require standardising interpretations, biopsy methods, and integration into a quality diagnostic pathway. • Current evidence is based on one-time point use of MRI in screening; MRI effectiveness in multiple rounds of screening is not well-documented.

Potential Clinical Applications of Dedicated Prostate Positron Emission Tomography

The diagnosis of prostate cancer (PCa) is usually based on transrectal or transperineal biopsies (from 12 to 24 samples) in most cases after the performance of a dedicated MRI and/or transrectal ultrasound. A small-dedicated PET scanner could improve spatial resolution and increase sensitivity, allowing a precise detection and location of the PCa foci, thus allowing an image-guided biopsy. In this short review, we will focus our attention on the potential application of a dedicated prostate PET scanner and on the prototype that has been already assembled for this purpose.

Recent advances and future perspectives in the therapeutics of prostate cancer

Prostate cancer (PC) is one of the most common cancers in males and the fifth leading reason of death. Age, ethnicity, family history, and genetic defects are major factors that determine the aggressiveness and lethality of PC. The African population is at the highest risk of developing high-grade PC. It can be challenging to distinguish between low-risk and high-risk patients due to the slow progression of PC. Prostate-specific antigen (PSA) is a revolutionary discovery for the identification of PC. However, it has led to an increase in over diagnosis and over treatment of PC in the past few decades. Even if modifications are made to the standard PSA testing, the specificity has not been found to be significant. Our understanding of PC genetics and proteomics has improved due to advances in different fields. New serum, urine, and tissue biomarkers, such as PC antigen 3 (PCA3), have led to various new diagnostic tests, such as the prostate health index, 4K score, and PCA3. These tests significantly reduce the number of unnecessary and repeat biopsies performed. Chemotherapy, radiotherapy, and prostatectomy are standard treatment options. However, newer novel hormone therapy drugs with a better response have been identified. Androgen deprivation and hormonal therapy are evolving as new and better options for managing hormone-sensitive and castration-resistant PC. This review aimed to highlight and discuss epidemiology, various risk factors, and developments in PC diagnosis and treatment regimens.

Fusion-targeted biopsy significantly improves prostate cancer detection in biopsy-naïve men

OBJECTIVE

The precise diagnosis of prostate cancer (PC) is crucial to avoid underdiagnosis, overdiagnosis, and overtreatment. We aimed to compare clinically significant PC (csPC) detection between MRI/ultrasound fusion-targeted prostate (TBx) compared to systematic biopsy (SBx) in biopsy-naïve Japanese men.

METHODS

We included patients with suspect PC due to elevated PSA level or abnormal digital rectal examination, or both. csPC was defined as International Society Urological Pathology (ISUP) grade group ≥2 (csPC-A) and ISUP grade group ≥3 (csPC-B).

RESULTS

This study included 143 patients. Overall PC detection was 66.4% for SBx and 67.8% for MRI-TBx. MRI-TBx presented a significantly higher rate of csPC detection (csPC-A 67.1% vs. 58.7%, p = 0.04, and csPC-B 49.6% vs. 39.9%, p < 0.001) and significantly lower detection of non-csPC-A (0.6% vs. 6.7%). Importantly, MRI-TBx missed 4.9% (7/143) of csPC-A and only 0.7% (1/143) of csPC-B. On the other hand, SBx alone missed 13.3% (19/143) of csPC-A and 4.2% (6/143) of csPC-B.

CONCLUSION

MRI-TBx significantly outperformed 12-cores SBx for csPC detection and decreased non-csPC detection in biopsy-naive men. Performing MRI-TBx without SBx would have missed some csPC, supporting that MRI-TBx synergizes with SBx to increase csPC detection.

Adverse Pathology after Radical Prostatectomy of Patients Eligible for Active Surveillance-A Summary 7 Years after Introducing mpMRI-Guided Biopsy in a Real-World Setting

OBJECTIVE

Over the last decade, active surveillance (AS) of low-risk prostate cancer has been increasing. The mpMRI fusion-guided biopsy of the prostate (FBx) is considered to be the gold standard in preoperative risk stratification. However, the role of FBx remains unclear in terms of risk stratification of low-risk prostate cancer outside high-volume centers. The aim of this study was to evaluate adverse pathology after radical prostatectomy (RP) in a real-world setting, focusing on patients diagnosed with Gleason score (GS) 6 prostate cancer (PCa) and eligible for AS by FBx.

SUBJECTS AND METHODS

Between March 2015 and March 2022, 1297 patients underwent FBx at the Department of Urology, Ludwig-Maximilians-University of Munich, Germany. MpMRI for FBx was performed by 111 different radiology centers. FBx was performed by 14 urologists from our department with different levels of experience. In total, 997/1297 (77%) patients were diagnosed with prostate cancer; 492/997 (49%) of these patients decided to undergo RP in our clinic and were retrospectively included. Univariate and multivariable logistic regression analyses were performed to evaluate clinical and histopathological parameters associated with adverse pathology comparing FBx and RP specimens. To compare FBx and systematic randomized biopsies performed in our clinic before introducing FBx (SBx, n = 2309), we performed a propensity score matching on a 1:1 ratio, adjusting for age, number of positive biopsy cores, and initial PSA (iPSA).

RESULTS

A total of 492 patients undergoing FBx or SBx was matched. In total, 55% of patients diagnosed with GS 6 by FBx were upgraded to clinically significant PCa (defined as GS ≥ 7a) after RP, compared to 52% of patients diagnosed by SBx (p = 0.76). A time delay between FBx and RP was identified as the only correlate associated with upgrading. A total of 5.9% of all FBx patients and 6.1% of all SBx patients would have been eligible for AS (p > 0.99) but decided to undergo RP. The positive predictive value of AS eligibility (diagnosis of low-risk PCa after biopsy and after RP) was 17% for FBx and 6.7% for SBx (p = 0.39).

CONCLUSIONS

In this study, we show, in a real-world setting, that introducing FBx did not lead to significant change in ratio of adverse pathology for low-risk PCa patients after RP compared to SBx.

Artificial Intelligence for Clinical Diagnosis and Treatment of Prostate Cancer

As medical science and technology progress towards the era of "big data", a multi-dimensional dataset pertaining to medical diagnosis and treatment is becoming accessible for mathematical modelling. However, these datasets are frequently inconsistent, noisy, and often characterized by a significant degree of redundancy. Thus, extensive data processing is widely advised to clean the dataset before feeding it into the mathematical model. In this context, Artificial intelligence (AI) techniques, including machine learning (ML) and deep learning (DL) algorithms based on artificial neural networks (ANNs) and their types, are being used to produce a precise and cross-sectional illustration of clinical data. For prostate cancer patients, datasets derived from the prostate-specific antigen (PSA), MRI-guided biopsies, genetic biomarkers, and the Gleason grading are primarily used for diagnosis, risk stratification, and patient monitoring. However, recording diagnoses and further stratifying risks based on such diagnostic data frequently involves much subjectivity. Thus, implementing an AI algorithm on a PC's diagnostic data can reduce the subjectivity of the process and assist in decision making. In addition, AI is used to cut down the processing time and help with early detection, which provides a superior outcome in critical cases of prostate cancer. Furthermore, this also facilitates offering the service at a lower cost by reducing the amount of human labor. Herein, the prime objective of this review is to provide a deep analysis encompassing the existing AI algorithms that are being deployed in the field of prostate cancer (PC) for diagnosis and treatment. Based on the available literature, AI-powered technology has the potential for extensive growth and penetration in PC diagnosis and treatment to ease and expedite the existing medical process.

The combined value of mpUS and mpMRI-TRUS fusion for the diagnosis of clinically significant prostate cancer

Objective

To evaluate the combined efficacy of multiparametric ultrasonography (mpUS) and multiparametric magnetic resonance imaging/transrectal ultrasound (mpMRI-TRUS) fusion for detecting clinically significant prostate cancer (csPCa).

Methods

From November 2019 to September 2021, biopsy-naïve patients underwent mpMRI-TRUS fusion imaging combined with mpUS-guided targeted biopsies (TB) and systematic biopsies (SB). To further evaluate the additional diagnostic value of mpUS, the imaging features of 202 focus obtained from fusion imaging were assessed. The diagnostic accuracies of mpMRI-TRUS fusion imaging and the combination of mpMRI-TRUS fusion imaging with mpUS for csPCa were comparatively evaluated.

Results

A total of 202 prostate lesions (160 patients) were included in the final analysis, of which 105 were csPCa, 16 were ciPCa, and 81 were noncancerous. The median patient age was 69 (65–73) years and the median tPSA was 22.07 (11.22–62.80) ng/mL. For csPCa, the detection rate of TB was higher than that of SB (50.0% vs. 45.5%, p < 0.05). The imaging characteristics of mpUS in the PCa and non-PCa groups were significantly different (p < 0.001). When compared with mpMRI-TRUS fusion imaging, the positive predictive value, false positive rate, and area under the curve (AUC) of csPCa diagnosis by mpMRI-TRUS fusion imaging combined with mpUS increased by 11.30%, decreased by 19.58%, and increased from 0.719 to 0.770 (p < 0.05), respectively.

Conclusion

TB can improve the detection rate of csPCa and hence can be effectively used in the diagnosis and risk assessment of csPCa. The mpUS-enriched valuable diagnostic information for mpMRI-TRUS fusion imaging and their combination showed a higher diagnostic value for csPCa, which can guide subsequent clinical treatment.