Vector Prostate Biopsy: A Novel Magnetic Resonance Imaging/Ultrasound Image Fusion Transperineal Biopsy Technique Using Electromagnetic Needle Tracking Under Local Anaesthesia

Bimodal imaging: Detection rate of clinically significant prostate cancer is higher in MRI lesions visible to transrectal ultrasound

BACKGROUND

To explore the detection rates of clinically significant prostate cancer (csPCa; ISUP ≥2) in patients with a single MRI lesion that is visible or invisible on transrectal ultrasound (TRUS) during biopsy.

METHODS

Retrospective analyses of patients who underwent targeted and systematic biopsy of the prostate for one MRI-visible lesion (PI-RADS score ≥ 3) between 2017 and 2022. TRUS-visibility, PI-RADS score, and clinical parameters were recorded prospectively. Univariable and multivariable logistic regression models were used to identify predictors of csPCa.

RESULTS

277 consecutive patients with one MRI-visible lesion were identified. A correlating lesion on TRUS was present in 147/277 (53%). The median age, PSA level, and prostate volume were 68.0 years (IQR: 62.0-73.0), 7.3 ng/ml (IQR: 5.4-10.8) and 45.0 cc (IQR: 32.0-68.0), respectively. Baseline parameters were not significantly different between the two groups. CsPCa was detected in 59/130 (45%) without and in 102/147 (69%) patients with a corresponding TRUS lesion. In multivariable logistic regression analysis predicting csPCa, TRUS-visibility (OR: 2.13, CI: 1.14-4.03, p = 0.02) and PI-RADS score (PI-RADS 4: OR: 7.28, CI: 3.33-17.19; PI-RADS 5: OR: 13.39, CI: 5.27-36.83, p < 0.001) achieved independent predictor status.

CONCLUSIONS

Bimodal-visible lesions more often harbored csPCa and were easier to target. TRUS-visibility of MRI lesions is an independent predictor of csPCa. Therefore, education in both modalities is essential. Despite MRI, the ultrasound should still be diligently examined.

[Perineal prostate biopsy]

The prostate biopsy is an essential tool for diagnosing prostate cancer (PCa). While transrectal biopsy (TR-Bx) continues to be considered the gold standard in Germany, the European Association of Urology (EAU) guidelines increasingly recommend transperineal biopsy (TP-Bx) due to lower infection rates and higher tumor detection rates. This article provides an overview of the history and development of the perineal biopsy, compares TR-Bx and TP-Bx and discusses the need for antibiotic prophylaxis before TP-Bx. Current studies have shown that TP-Bx can be performed without antibiotic prophylaxis and new techniques such as robotic-assisted and vector biopsy show very precise results. The establishment of TP-Bx is being promoted by extrabudgetary funding and technological advancements, with the choice of biopsy method remaining an individual decision jointly made in dialogue with the patient.

The learning curve and experience of a novel multi-modal image fusion targeted transperineal prostate biopsy technique using electromagnetic needle tracking under local anesthesia

Background

Prostate cancer is the most common malignant tumor of male genitourinary system, and the gold standard for its diagnosis is prostate biopsy. Focusing on the methods and skills of prostate biopsy, we explored the learning curve and experience of a novel magnetic resonance imaging and transrectal ultrasound (mpMRI-TRUS) image fusion transperineal biopsy (TPB) technique using electromagnetic needle tracking under local anesthesia.

Methods

The clinical and pathological data of 92 patients who underwent targeted TPB from January 2023 to July 2023 in our center were prospectively collected. The cumulative sum (CUSUM) analysis method and the best fitting curve were used to analyze the learning curve of this novel technique, and the clinical characteristics, perioperative data and tumor positive rate of prostate biopsy of patients at different stages of the learning curve were compared.

Results

With the increase of the number of surgical cases, the overall operative time showed a downward trend. The best fitting curve of CUSUM reached its peak at the twelfth case, which is the minimum cumulative number of surgical cases needed to cross the learning curve of the operation. Taking this as the boundary, the learning curve is divided into two stages: learning improvement stage (group A, 12 cases) and proficiency stage (group B, 80 cases). The surgical time and visual analog scale score during prostate biopsy in group A were significantly higher than those in group B. The visual numerical scale score during prostate biopsy in group A was significantly lower than that in group B. There was no statistically significant difference between group A and group B in the detection rate of csPCa and the incidence of perioperative complications.

Conclusion

The novel targeted TPB technique is divided into learning improvement stage and proficiency stage, and 12 cases may be the least cumulative number.

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.

Risk stratification of prostate cancer with MRI and prostate-specific antigen density-based tool for personalized decision making

OBJECTIVES

MRI is now established for initial prostate cancer diagnosis; however, there is no standardized pathway to avoid unnecessary biopsy in low-risk patients. Our study aimed to test previously proposed MRI-focussed and risk-adapted biopsy decision models on a real-world dataset.

METHODS

Single-centre retrospective study performed on 2055 biopsy naïve patients undergoing MRI. Diagnostic pathways included "biopsy all", "MRI-focussed" and two risk-based MRI-directed pathways. Risk thresholds were based on prostate-specific antigen (PSA) density as low (<0.10 ng mL-2), intermediate (0.10-0.15 ng mL-2), high (0.15-0.20 ng mL-2), or very high-risk (>0.20 ng mL-2). The outcome measures included rates of biopsy avoidance, detection of clinically significant prostate cancer (csPCa), missed csPCa, and overdiagnosis of insignificant prostate cancer (iPCa).

RESULTS

Overall cancer rate was 39.9% (819/2055), with csPCa (Grade-Group ≥2) detection of 30.3% (623/2055). In men with a negative MRI (Prostate Imaging-Reporting and Data System, PI-RADS 1-2), the risk of cancer was 1.2%, 2.6%, 9.0%, and 12.9% in the low, intermediate, high, and very high groups, respectively; for PI-RADS score 3 lesions, the rates were 10.5%, 14.3%, 25.0%, and 33.3%, respectively. MRI-guided pathway and risk-based pathway with a low threshold missed only 1.6% csPCa with a biopsy-avoidance rate of 54.4%, and the risk-based pathway with a higher threshold avoided 62.9% (1292/2055) of biopsies with 2.9% (61/2055) missed csPCa detection. Decision curve analysis found that the "risk-based low threshold" pathway has the highest net benefit for probability thresholds between 3.6% and 13.9%.

CONCLUSION

Combined MRI and PSA-density risk-based pathways can be a helpful decision-making tool enabling high csPCa detection rates with the benefit of biopsy avoidance and reduced iPCa detection.

ADVANCES IN KNOWLEDGE

This real-world dataset from a large UK-based cohort confirms that combining MRI scoring with PSA density for risk stratification enables safe biopsy avoidance and limits the over-diagnosis of insignificant cancers.

Transperineal US-MRI Fusion-Guided Biopsy for the Detection of Clinical Significant Prostate Cancer: A Systematic Review and Meta-Analysis Comparing Cognitive and Software-Assisted Technique

INTRODUCTION

We aimed to find potential differences in clinically significant prostate cancer (csPCa) detection rates between transperineal software-assisted fusion biopsy (saFB) and cognitive fusion biopsies (cFB).

METHODS

A systematic review of the literature was performed to identify comparative studies using PubMed, EMBASE, and Scopus according to the PICOS criteria. Cancer detection and complication rates were pooled using the Cochran-Mantel-Haenszel method with the random effect model and reported as odds ratios (ORs), 95% confidence intervals (CI), and p-values. A meta-analysis was performed using Review Manager (RevMan) 5.4 software by Cochrane Collaboration. The quality assessment of the included studies was performed using the Cochrane Risk of Bias tool, using RoB 2 for randomized studies and ROBINS-I for retrospective and nonrandomized ones.

RESULTS

Eight studies were included for the meta-analysis, including 1149 cases in software-based and 963 cases in cognitive fusion biopsy. The detection rates of csPCa were similar between the two groups (OR 1.01, 95% CI 0.74-1.37, p = 0.95). Study heterogeneity was low (I2 55%).

CONCLUSION

There is no actual evidence of the superiority of saFB over cFB in terms of the csPCa detection rate. Operator experience and software availability can drive the choice of one fusion technique over the other.

A Systematic Review of the Current Status of Magnetic Resonance-Ultrasound Images Fusion Software Platforms for Transperineal Prostate Biopsies

Given this new context, our objective is to recognize the suitability of the currently available software for image fusion and the reported series using the transperineal route, as well as to generate new evidence on the complementarity of the directed and systematic biopsies, which has been established through the transrectal approach.

EVIDENCE ACQUISITION

This systematic review, registered in Prospero (CRD42022375619), began with a bibliographic search that was carried out in PubMed, Cochrane, and Google Scholar databases. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) criteria and the studied eligibility based on the Participants, Intervention, Comparator, and Outcomes (PICO) strategy were followed. Warp analysis of selected studies was performed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. In addition, a Google search of all currently available fusion platforms was performed. Our Google search found 11 different commercially available robots to perform transperineal image fusion biopsies, of which 10 devices have published articles supporting their diagnostic effectiveness in transperineal prostate biopsies.

RESULTS

A total of 30 articles were selected and the characteristics and results of the biopsies of 11,313 patients were analyzed. The pooled mean age was 66.5 years (63-69). The mean pooled PSA level was 7.8 ng/mL (5.7-10.8). The mean pooled prostate volume was 45.4 cc. (34-56). The mean pooled PSA density was 0.17 (0.12-0.27). The overall cancer detection rate for all prostate cancers was 61.4%, while for csPCa it was 47.8%. PCa detection rate was more effective than that demonstrated in the systematic transrectal biopsy. However, the detection of csPCa in the systematic biopsy was only 9.5% in the reported series. To standardize our review, we grouped prostate cancer screening results according to the population studied and the software used. When the same populations were compared between elastic and rigid software, we found that rigid biopsies had a higher csPCa detection rate than biopsies with elastic fusion systems.

CONCLUSION

Platforms performing prostate biopsy using transperineal image fusion have better detection rates of csPCa than systematic transrectal biopsies. Rigid fusion systems have a better csPCa detection rate than elastic ones. We found no diagnostic differences between the different types of robotic systems currently available. The complementarity of systematic biopsy has also been demonstrated in transperineal imaging fusion biopsies.

Generative Adversarial Networks Can Create High Quality Artificial Prostate Cancer Magnetic Resonance Images

The recent integration of open-source data with machine learning models, especially in the medical field, has opened new doors to studying disease progression and/or regression. However, the ability to use medical data for machine learning approaches is limited by the specificity of data for a particular medical condition. In this context, the most recent technologies, like generative adversarial networks (GANs), are being looked upon as a potential way to generate high-quality synthetic data that preserve the clinical variability of a condition. However, despite some success, GAN model usage remains largely minimal when depicting the heterogeneity of a disease such as prostate cancer. Previous studies from our group members have focused on automating the quantitative multi-parametric magnetic resonance imaging (mpMRI) using habitat risk scoring (HRS) maps on the prostate cancer patients in the BLaStM trial. In the current study, we aimed to use the images from the BLaStM trial and other sources to train the GAN models, generate synthetic images, and validate their quality. In this context, we used T2-weighted prostate MRI images as training data for Single Natural Image GANs (SinGANs) to make a generative model. A deep learning semantic segmentation pipeline trained the model to segment the prostate boundary on 2D MRI slices. Synthetic images with a high-level segmentation boundary of the prostate were filtered and used in the quality control assessment by participating scientists with varying degrees of experience (more than ten years, one year, or no experience) to work with MRI images. Results showed that the most experienced participating group correctly identified conventional vs. synthetic images with 67% accuracy, the group with one year of experience correctly identified the images with 58% accuracy, and the group with no prior experience reached 50% accuracy. Nearly half (47%) of the synthetic images were mistakenly evaluated as conventional. Interestingly, in a blinded quality assessment, a board-certified radiologist did not significantly differentiate between conventional and synthetic images in the context of the mean quality of synthetic and conventional images. Furthermore, to validate the usability of the generated synthetic images from prostate cancer MRIs, we subjected these to anomaly detection along with the original images. Importantly, the success rate of anomaly detection for quality control-approved synthetic data in phase one corresponded to that of the conventional images. In sum, this study shows promise that high-quality synthetic images from MRIs can be generated using GANs. Such an AI model may contribute significantly to various clinical applications which involve supervised machine-learning approaches.

A Non-Conventional Review on Multi-Modality-Based Medical Image Fusion

Today, medical images play a crucial role in obtaining relevant medical information for clinical purposes. However, the quality of medical images must be analyzed and improved. Various factors affect the quality of medical images at the time of medical image reconstruction. To obtain the most clinically relevant information, multi-modality-based image fusion is beneficial. Nevertheless, numerous multi-modality-based image fusion techniques are present in the literature. Each method has its assumptions, merits, and barriers. This paper critically analyses some sizable non-conventional work within multi-modality-based image fusion. Often, researchers seek help in apprehending multi-modality-based image fusion and choosing an appropriate multi-modality-based image fusion approach; this is unique to their cause. Hence, this paper briefly introduces multi-modality-based image fusion and non-conventional methods of multi-modality-based image fusion. This paper also signifies the merits and downsides of multi-modality-based image fusion.