Validation of the European Society of Urogenital Radiology scoring system for prostate cancer diagnosis on multiparametric magnetic resonance imaging in a cohort of repeat biopsy patients

Reliability of Multiparametric Magnetic Resonance Imaging in Patients with a Previous Negative Biopsy: Comparison with Biopsy-Naïve Patients in the Detection of Clinically Significant Prostate Cancer

Background: Multiparametric magnetic resonance is an established imaging utilized in the diagnostic pathway of prostate cancer. The aim of this study is to evaluate the accuracy and reliability of multiparametric magnetic resonance imaging (mpMRI) in the detection of clinically significant prostate cancer, defined as Gleason Score ≥ 4 + 3 or a maximum cancer core length 6 mm or longer, in patients with a previous negative biopsy. Methods: The study was conducted as a retrospective observational study at the University of Naples "Federico II", Italy. Overall, 389 patients who underwent systematic and target prostate biopsy between January 2019 and July 2020 were involved and were divided into two groups: Group A, which included biopsy-naïve patients; Group B, which included re-biopsy patients. All mpMRI images were obtained using three Tesla instruments and were interpreted according to PIRADS (Prostate Imaging Reporting and Data System) version 2.0. Results: 327 patients were biopsy-naïve, while 62 belonged to the re-biopsy group. Both groups were comparable in terms of age, total PSA (prostate-specific antigen), and number of cores obtained at the biopsy. 2.2%, 8.8%, 36.1%, and 83.4% of, respectively, PIRADS 2, 3, 4, and 5 biopsy-naïve patients reported a clinically significant prostate cancer compared to 0%, 14.3%, 39%, and 66.6% of re-biopsy patients (p < 0.0001-p = 0.040). No difference was reported in terms of post-biopsy complications. Conclusions: mpMRI confirms its role as a reliable diagnostic tool prior to performing prostate biopsy in patients who underwent a previous negative biopsy, reporting a comparable detection rate of clinically significant prostate cancer.

Paradigm Shift in Prostate Cancer Diagnosis: Pre-Biopsy Prostate Magnetic Resonance Imaging and Targeted Biopsy

With regard to the indolent clinical characteristics of prostate cancer (PCa), the more selective detection of clinically significant PCa (CSC) has been emphasized in its diagnosis and management. Magnetic resonance imaging (MRI) has advanced technically, and recent international cooperation has provided a standardized imaging and reporting system for prostate MRI. Accordingly, prostate MRI has recently been investigated and utilized as a triage tool before biopsy to guide tissue sampling to increase the detection rate of CSC beyond the staging tool for patients in whom PCa was already confirmed on conventional systematic biopsy. Radiologists must understand the current paradigm shift for better PCa diagnosis and management. This article reviewed the recent literature, demonstrating the diagnostic value of pre-biopsy prostate MRI with targeted biopsy and discussed unsolved issues regarding the paradigm shift in the diagnosis of PCa.

Biomechanical modelling of the pelvic system: improving the accuracy of the location of neoplasms in MRI-TRUS fusion prostate biopsy

Background

An accurate knowledge of the relocation of prostate neoplasms during biopsy is of great importance to reduce the number of false negative results. Prostate neoplasms are visible in magnetic resonance images (MRI) but it is difficult for the practitioner to locate them at the time of performing a transrectal ultrasound (TRUS) guided biopsy. In this study, we present a new methodology, based on simulation, that predicts both prostate deformation and lesion migration during the biopsy.

Methods

A three-dimensional (3-D) anatomy model of the pelvic region, based on medical images, is constructed. A finite element (FE) numerical simulation of the organs motion and deformation as a result of the pressure exerted by the TRUS probe is carried out using the Code-Aster open-source computer software. Initial positions of potential prostate lesions prior to biopsy are taken into consideration and the final location of each lesion is targeted in the FE simulation output.

Results

Our 3-D FE simulations show that the effect of the pressure exerted by the TRUS probe is twofold as the prostate experiences both a motion and a deformation of its original shape. We targeted the relocation of five small prostate lesions when the TRUS probe exerts a force of 30 N on the rectum inner wall. The distance travelled by these lesions ranged between 5.6 and 13.9 mm.

Conclusions

Our new methodology can help to predict the location of neoplasms during a prostate biopsy but further studies are needed to validate our results. Moreover, the new methodology is completely developed on open-source software, which means that its implementation would be affordable to all healthcare providers.

Usefulness of grayscale values measuring hypoechoic lesions for predicting prostate cancer: An experimental pilot study

Background

Methods

Results

Conclusions

Diagnostic accuracy of magnetic resonance imaging targeted biopsy techniques compared to transrectal ultrasound guided biopsy of the prostate: a systematic review and meta-analysis

Background

Multiparametric MRI localizes cancer in the prostate, allowing for MRI guided biopsy (MRI-GB) 43 alongside transrectal ultrasound-guided systematic biopsy (TRUS-GB). Three MRI-GB approaches exist; visual estimation (COG-TB); fusion software-assisted (FUS-TB) and MRI ‘in-bore’ biopsy (IB-TB). It is unknown whether any of these are superior.

We conducted a systematic review and meta-analysis to address three questions. First, whether MRI-GB is superior to TRUS-GB at detecting clinically significant PCa (csPCa). Second, whether MRI-GB is superior to TRUS-GB at avoiding detection of insignificant PCa. Third, whether any MRI-GB strategy is superior at detecting csPCa.

Methods

A systematic literature review from 2015 to 2019 was performed in accordance with the START recommendations. Studies reporting PCa detection rates, employing MRI-GB and TRUS-GB were included and evaluated using the QUADAS-2 checklist. 1553 studies were found, of which 43 were included in the meta-analysis.

Results

For csPCa, MRI-GB was superior in detection to TRUS-GB (0.83 vs. 0.63 [p = 0.02]). MRI-GB was superior in detection to TRUS-GB at avoiding detection of insignificant PCa. No MRI-GB technique was superior at detecting csPCa (IB-TB 0.87; COG TB 0.81; FUS-TB 0.81, [p = 0.55]). There was significant heterogeneity observed between the included studies.

Conclusions

In patients with suspected PCa on MRI, MRI-GB offers superior rates of csPCa detection and reduces detection of insignificant PCa compared to TRUS-GB. No individual MRI-GB technique was found to be better in csPCa detection. Prospective adequately powered randomized controlled trials are required.

A Deep Learning Approach to Diagnostic Classification of Prostate Cancer Using Pathology-Radiology Fusion

BACKGROUND

A definitive diagnosis of prostate cancer requires a biopsy to obtain tissue for pathologic analysis, but this is an invasive procedure and is associated with complications.

PURPOSE

To develop an artificial intelligence (AI)-based model (named AI-biopsy) for the early diagnosis of prostate cancer using magnetic resonance (MR) images labeled with histopathology information.

STUDY TYPE

Retrospective.

POPULATION

Magnetic resonance imaging (MRI) data sets from 400 patients with suspected prostate cancer and with histological data (228 acquired in-house and 172 from external publicly available databases).

FIELD STRENGTH/SEQUENCE

1.5 to 3.0 Tesla, T2-weighted image pulse sequences.

ASSESSMENT

MR images reviewed and selected by two radiologists (with 6 and 17 years of experience). The patient images were labeled with prostate biopsy including Gleason Score (6 to 10) or Grade Group (1 to 5) and reviewed by one pathologist (with 15 years of experience). Deep learning models were developed to distinguish 1) benign from cancerous tumor and 2) high-risk tumor from low-risk tumor.

STATISTICAL TESTS

To evaluate our models, we calculated negative predictive value, positive predictive value, specificity, sensitivity, and accuracy. We also calculated areas under the receiver operating characteristic (ROC) curves (AUCs) and Cohen's kappa.

RESULTS

Our computational method (https://github.com/ih-lab/AI-biopsy) achieved AUCs of 0.89 (95% confidence interval [CI]: [0.86-0.92]) and 0.78 (95% CI: [0.74-0.82]) to classify cancer vs. benign and high- vs. low-risk of prostate disease, respectively.

DATA CONCLUSION

AI-biopsy provided a data-driven and reproducible way to assess cancer risk from MR images and a personalized strategy to potentially reduce the number of unnecessary biopsies. AI-biopsy highlighted the regions of MR images that contained the predictive features the algorithm used for diagnosis using the class activation map method. It is a fully automatic method with a drag-and-drop web interface (https://ai-biopsy.eipm-research.org) that allows radiologists to review AI-assessed MR images in real time.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY STAGE: 2.

Electrochemical Biosensors for Detection of MicroRNA as a Cancer Biomarker: Pros and Cons

Cancer is the second most fatal disease in the world and an early diagnosis is important for a successful treatment. Thus, it is necessary to develop fast, sensitive, simple, and inexpensive analytical tools for cancer biomarker detection. MicroRNA (miRNA) is an RNA cancer biomarker where the expression level in body fluid is strongly correlated to cancer. Various biosensors involving the detection of miRNA for cancer diagnosis were developed. The present review offers a comprehensive overview of the recent developments in electrochemical biosensor for miRNA cancer marker detection from 2015 to 2020. The review focuses on the approaches to direct miRNA detection based on the electrochemical signal. It includes a RedOx-labeled probe with different designs, RedOx DNA-intercalating agents, various kinds of RedOx catalysts used to produce a signal response, and finally a free RedOx indicator. Furthermore, the advantages and drawbacks of these approaches are highlighted.

MRI/TRUS fusion vs. systematic biopsy: intra-patient comparison of diagnostic accuracy for prostate cancer using PI-RADS v2

OBJECTIVE

To evaluate the efficacy of multiparametric magnetic resonance/transrectal ultrasound fusion (MRI/TRUS fusion) biopsy versus systematic biopsy and its association with PI-RADS v2 categories in patients with suspected prostate cancer.

MATERIALS AND METHODS

122 patients undergoing both MRI/TRUS fusion and systematic biopsy, with suspicion of prostate cancer, with suspicious findings on MRI based on PI-RADS v2, were included between April 2016 and March 2017. Comparison of tumor detection rates using each technique and combined techniques was performed for all lesions as well as those that are traditionally difficult to access (i.e., anterior lesions).

RESULTS

Prostate cancer was detected in 83/122 patients (68%) with 74.6% clinically significant lesions (Gleason 3 + 4 or greater). There was a statistically significant difference in presence of clinically significant prostate cancer in PI-RADS v2 categories of 3, 4, and 5 (20%, 52% and 77%, respectively, p < 0.001). Fusion biopsy was positive in a significantly higher percentage of patients versus systematic biopsy (56% versus 48%, respectively, p < 0.05). The fusion biopsy alone was positive in 20%. Of 34 patients with anterior lesions on MRI, 44% were detected only by fusion biopsy, with a joint yield of 71%. In patients with previous negative systematic biopsies, 48.7% lesions were found by fusion biopsy with 20.5% being exclusively positive by this method. The percentage of positive cores for fusion biopsies was significantly higher than for systematic biopsies (26% vs. 12.3%, p < 0.001).

CONCLUSION

The incorporation of MRI/TRUS fusion biopsy significantly improves the detection rate of prostate cancer versus systematic biopsy, particularly for anterior lesions.

Comparison of clinically significant prostate cancer detection by MRI cognitive biopsy and in-bore MRI-targeted biopsy for naïve biopsy patients

Background

Multiparametric magnetic resonance imaging (mpMRI) targeted prostate biopsy increases the diagnostic accuracy of clinically significant prostate cancer (PCa). Currently there is no consensus on which type of MRI-targeted biopsy performs better in a given setting. In this study, we aimed to compare the detection rate of (clinically significant) PCa by MRI cognitive targeted biopsy (COG) and in-bore MRI-targeted biopsy (IB) techniques for naïve prostate biopsy patients in China.

Methods

Our study included 85 men from Beijing United Family Hospital and Clinics and 88 men from Beijing Hospital, National Center of Gerontology. All men had no history of prostate biopsy, undergoing mpMRI scan due to elevated PSA and/or abnormal DRE. The men in Beijing United Family Hospital group received COG plus systematic biopsy. The men in Beijing Hospital group only received IB.

Results

The median age in COG and IB group was 63.0 years and 70.0 years (P<0.01). The median PSA was 7.4 and 6.8 ng/mL in COG and IB group respectively (P=0.124). The detection rate of PCa was 36.5% by COG and 52.3% by IB (P=0.037). The detection rate of clinically significant PCa (Gleason score ≥7) was 23.5% and 29.5% by COG and IB (P=0.371) respectively. In COG group, combination biopsy (COG + systematic biopsy) achieved improved PCa (42.4%) and clinically significant PCa (28.2%) detection rate compared with COG alone. However, there was no difference in overall PCa and clinically significant PCa detection between combination biopsy and IB.

Conclusions

IB had a higher rate of overall PCa detection compared with COG, but the two approaches did not differ significantly in the detection of clinically significant PCa. There was no significant difference in detection rate of PCa and clinically significant PCa between the combination biopsy and IB.

Independent Evaluation of the Respective Predictive Values for High-Grade Prostate Cancer of Clinical Information and RNA Biomarkers after Upfront MRI and Image-Guided Biopsies

Upfront MRI is taking the lead in the diagnosis of clinically significant prostate cancer, while few image-guided biopsies (IGBs) fail to demonstrate clinically significant prostate cancer. The added value of innovative biomarkers is not confirmed in this context. We analysed SelectMDx-v2 (MDx-2) in a cohort of upfront MRI and image-guided biopsy patients. Participants included patients who received a trans-rectal elastic-fusion registration IGB on the basis of DRE, PSA, PCA3, and PCPT-2.0 risk evaluation. Pre-biopsy MRI DICOM archives were reviewed according to PI-RADS-v2. Post-massage first-void urine samples stored in the institutional registered bio-repository were commercially addressed to MDxHealth to obtain MDx-2 scores. Univariate and multivariate analyses were conducted with the detection on IGB of high-grade (ISUP 2 and higher) as the dependent variable. High-grade cancer was demonstrated in 32/117 (27.4%) patients (8/2010-8/2018). Age, prostate volume, biopsy history, MDx-2, and PI-RADS-v2 scores significantly related to the detection of high-grade cancer. MDx-2 scores and the clinical variables embedded into MDx-2 scores were analysed in multivariate analysis to complement PI-RADS-v2 scores. The two combinations outperformed PI-RADS-v2 alone (AUC-ROC 0.67 vs. 0.73 and 0.80, respectively, p < 0.05) and calibration curves confirmed an adequate prediction. Similar discrimination (C-statistics, p = 0.22) was observed in the prediction of high-grade cancer, thereby questioning the respective inputs and added values of biomarkers and clinical predictors in MDx-2 scores. Based on the results of this study, we can conclude that instruments of prediction developed for systematic prostate biopsies, including those that incorporate innovative biomarkers, must be reassessed and eventually confirmed in the context of upfront MRI and IGB.

Accuracy of multiparametric magnetic resonance imaging for diagnosing prostate Cancer: a systematic review and meta-analysis

BACKGROUND

The application of multiparametric magnetic resonance imaging (mpMRI) for diagnosis of prostate cancer has been recommended by the European Association of Urology (EAU), National Comprehensive Cancer Network (NCCN), and European Society of Urogenital Radiology (ESUR) guidelines. The purpose of this study is to systematically review the literature on assessing the accuracy of mpMRI in patients with suspicion of prostate cancer.

METHOD

We searched Embase, Pubmed and Cochrane online databases from January 12,000 to October 272,018 to extract articles exploring the possibilities that the pre-biopsy mpMRI can enhance the diagnosis accuracy of prostate cancer. The numbers of true- and false-negative results and true- and false-positive ones were extracted to calculate the corresponding sensitivity and specificity of mpMRI. Study quality was assessed using QUADAS-2 tool. Random effects meta-analysis and a hierarchical summary receiver operating characteristic (HSROC) plot were performed for further study.

RESULTS

After searching, we acquired 3741 articles for reference, of which 29 studies with 8503 participants were eligible for inclusion. MpMRI maintained impressive diagnostic value, the area under the HSROC curve was 0.87 (95%CI,0.84-0.90). The sensitivity and specificity for mpMRI were 0.87 [95%CI, 0.81-0.91] and 0.68 [95%CI,0.56-0.79] respectively. The positive likelihood ratio was 2.73 [95%CI 1.90-3.90]; negative likelihood ratio was 0.19 [95% CI 0.14,-0.27]. The risk of publication bias was negligible with P = 0.96.

CONCLUSION

Results of the meta-analysis suggest that mpMRI is a sensitive tool to diagnose prostate cancer. However, because of the high heterogeneity existing among the included studies, further studies are needed to apply the results of this meta-analysis in clinic.

The primacy of multiparametric MRI in men with suspected prostate cancer

Background

Multiparametric MRI (mpMRI) became recognised in investigating those with suspected prostate cancer between 2010 and 2012; in the USA, the preventative task force moratorium on PSA screening was a strong catalyst. In a few short years, it has been adopted into daily urological and oncological practice. The pace of clinical uptake, born along by countless papers proclaiming high accuracy in detecting clinically significant prostate cancer, has sparked much debate about the timing of mpMRI within the traditional biopsy-driven clinical pathways. There are strongly held opposing views on using mpMRI as a triage test regarding the need for biopsy and/or guiding the biopsy pattern.

Objective

To review the evidence base and present a position paper on the role of mpMRI in the diagnosis and management of prostate cancer.

Methods

A subgroup of experts from the ESUR Prostate MRI Working Group conducted literature review and face to face and electronic exchanges to draw up a position statement.

Results

This paper considers diagnostic strategies for clinically significant prostate cancer; current national and international guidance; the impact of pre-biopsy mpMRI in detection of clinically significant and clinically insignificant neoplasms; the impact of pre-biopsy mpMRI on biopsy strategies and targeting; the notion of mpMRI within a wider risk evaluation on a patient by patient basis; the problems that beset mpMRI including inter-observer variability.

Conclusions

The paper concludes with a set of suggestions for using mpMRI to influence who to biopsy and who not to biopsy at diagnosis.

Key Points

• Adopt mpMRI as the first, and primary, investigation in the workup of men with suspected prostate cancer.

• PI-RADS assessment categories 1 and 2 have a high negative predictive value in excluding significant disease, and systematic biopsy may be postponed, especially in men with low-risk of disease following additional risk stratification.

• PI-RADS assessment category lesions 4 and 5 should be targeted; PI-RADS assessment category lesion 3 may be biopsied as a target, as part of systematic biopsies or may be observed depending on risk stratification.

Electronic supplementary material

The online version of this article (10.1007/s00330-019-06166-z) contains supplementary material, which is available to authorized users.

PI-RADS v2 and ADC values: is there room for improvement?

PURPOSE

To determine the diagnostic accuracy of ADC values in combination with PI-RADS v2 for the diagnosis of clinically significant prostate cancer (CS-PCa) compared to PI-RADS v2 alone.

MATERIALS AND METHODS

This retrospective study included 155 men whom underwent 3-Tesla prostate MRI and subsequent MR/US fusion biopsies at a single non-academic center from 11/2014 to 3/2016. All scans were performed with a surface coil and included T2, diffusion-weighted, and dynamic contrast-enhanced sequences. Suspicious findings were classified using Prostate Imaging Reporting and Data System (PI-RADS) v2 and targeted using MR/US fusion biopsies. Mixed-effect logistic regression analyses were used to determine the ability of PIRADS v2 alone and combined with ADC values to predict CS-PCa. As ADC categories are more practical in clinical situations than numeric values, an additional model with ADC categories of ≤ 800 and > 800 was performed.

RESULTS

A total of 243 suspicious lesions were included, 69 of which were CS-PCa, 34 were Gleason score 3+3 PCa, and 140 were negative. The overall PIRADS v2 score, ADC values, and ADC categories are independent statistically significant predictors of CS-PCa (p < 0.001). However, the area under the ROC of PIRADS v2 alone and PIRADS v2 with ADC categories are significantly different in both peripheral and transition zone lesions (p = 0.026 and p = 0.03, respectively) Further analysis of the ROC curves also shows that the main benefit of utilizing ADC values or categories is better discrimination of PI-RADS v2 4 lesions.

CONCLUSION

ADC values and categories help to diagnose CS-PCa when lesions are assigned a PI-RADS v2 score of 4.

Distribution of Prostate Imaging Reporting and Data System score and diagnostic accuracy of magnetic resonance imaging-targeted biopsy: comparison of an Asian and European cohort

Background

This study aimed to compare the distribution of Prostate Imaging Reporting and Data System (PI-RADS) score and the diagnostic accuracy of magnetic resonance imaging (MRI)-targeted biopsy and systematic biopsy between a Chinese and a Dutch cohort.

Materials and methods

Our study includes 316 men from Shanghai Changhai Hospital, China, and 266 men from the Erasmus University Medical Center, Rotterdam, the Netherlands. All men had a suspicion for prostate cancer (PCa) and were offered an multiparametric MRI (mpMRI) scan.

Results

The distribution of the PI-RADS score was different between the two cohorts (P = 0.008). In the Chinese cohort of PI-RADS ≥3, the detection rate for high-grade PCa (Gleason ≥7) was 37.3% by systematic biopsy and 35.5% by MRI-targeted biopsy. The sensitivity of systematic biopsy was 0.80 for PCa and 0.75 for high-grade PCa. MRI-targeted biopsy achieved slightly higher sensitivity for PCa (0.82) and high-grade PCa (0.76). In the Dutch cohort of PI-RADS ≥3, the high-grade PCa detection rate was 44.4% and 54.5% for systematic biopsy and MRI-targeted biopsy. The sensitivity of systematic biopsy was 0.93 for PCa and 0.81 for high-grade PCa. By MRI-targeted biopsy, the sensitivity was 0.85 for PCa and 0.97 for high-grade PCa.

Conclusions

The distribution of the PI-RADS score was different with more PI-RADS 4/5 in the Chinese cohort. Applying a PI-RADS ≥3 cutoff resulted in a favorable overall sensitivity. MRI-targeted biopsy showed a higher sensitivity in the detection of high-grade PCa than systematic biopsy. The sensitivity of MRI-targeted biopsy and systematic biopsy for both PCa and high-grade PCa in the Dutch cohort was superior to those in the Chinese cohort.

Accuracy of elastic fusion biopsy in daily practice: Results of a multicenter study of 2115 patients

OBJECTIVES

To assess the accuracy of Koelis fusion biopsy for the detection of prostate cancer and clinically significant prostate cancer in the everyday practice.

METHODS

We retrospectively enrolled 2115 patients from 15 institutions in four European countries undergoing transrectal Koelis fusion biopsy from 2010 to 2017. A variable number of target (usually 2-4) and random cores (usually 10-14) were carried out, depending on the clinical case and institution habits. The overall and clinically significant prostate cancer detection rates were assessed, evaluating the diagnostic role of additional random biopsies. The cancer detection rate was correlated to multiparametric magnetic resonance imaging features and clinical variables.

RESULTS

The mean number of targeted and random cores taken were 3.9 (standard deviation 2.1) and 10.5 (standard deviation 5.0), respectively. The cancer detection rate of Koelis biopsies was 58% for all cancers and 43% for clinically significant prostate cancer. The performance of additional, random cores improved the cancer detection rate of 13% for all cancers (P < 0.001) and 9% for clinically significant prostate cancer (P < 0.001). Prostate cancer was detected in 31%, 66% and 89% of patients with lesions scored as Prostate Imaging Reporting and Data System 3, 4 and 5, respectively. Clinical stage and Prostate Imaging Reporting and Data System score were predictors of prostate cancer detection in multivariate analyses. Prostate-specific antigen was associated with prostate cancer detection only for clinically significant prostate cancer.

CONCLUSIONS

Koelis fusion biopsy offers a good cancer detection rate, which is increased in patients with a high Prostate Imaging Reporting and Data System score and clinical stage. The performance of additional, random cores seems unavoidable for correct sampling. In our experience, the Prostate Imaging Reporting and Data System score and clinical stage are predictors of prostate cancer and clinically significant prostate cancer detection; prostate-specific antigen is associated only with clinically significant prostate cancer detection, and a higher number of biopsy cores are not associated with a higher cancer detection rate.

The emerging role of imaging in prostate cancer secondary screening: multiparametric magnetic resonance imaging and the incipient incorporation of molecular imaging

An increasingly robust body of evidence indicates that multiparametric MRI (mpMRI) prior to prostate biopsy can improve the detection of clinically significant prostate cancer while avoiding unnecessary biopsies. As a result, the use of mpMRI and biopsy platforms that allow for the real-time fusion of mpMRI and transrectal ultrasound images is now routinely used in clinical practice. On the horizon, molecular imaging offers the promise of improved sensitivity relative to mpMRI and early data would suggest that the combination of mpMRI and positron emission tomography using radiotracers targeting prostate-specific membrane antigen provide a more accurate assessment than either modality alone. In this review, we examine the current role of imaging to aid in the initial diagnosis of prostate cancer.

Prostate DCE-MRI with <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msubsup><mml:mi>B</mml:mi> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo></mml:msubsup> </mml:mrow> </mml:math> correction using an approximated analytical approach

PURPOSE

To develop and evaluate a practical <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msubsup><mml:mi>B</mml:mi> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo></mml:msubsup> </mml:mrow> </mml:math> correction method for prostate dynamic contrast-enhanced (DCE) MRI analysis.

THEORY

We proposed a simple analytical <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msubsup><mml:mi>B</mml:mi> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo></mml:msubsup> </mml:mrow> </mml:math> correction method using a Taylor series approximation to the steady-state spoiled gradient echo signal equation. This approach only requires <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msubsup><mml:mi>B</mml:mi> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo></mml:msubsup> </mml:mrow> </mml:math> maps and uncorrected pharmacokinetic (PK) parameters as input to estimate the corrected PK parameters.

METHODS

The proposed method was evaluated using a prostate digital reference object (DRO), and 82 in vivo prostate DCE-MRI cases. The approximated analytical correction was compared with the ground truth PK parameters in simulation, and compared with the reference numerical correction in in vivo experiments, using percentage error as the metric.

RESULTS

The prostate DRO results showed that our approximated analytical approach provided residual error less than 0.4% for both K^trans and v_e , compared to the ground truth. This noise-free residual error was smaller than the noise-induced error using the reference numerical correction, which had a minimum error of 2.1+4.3% with baseline signal-to-noise ratio of 234.5. For the 82 in vivo cases, K^trans and v_e percentage error compared to the reference numerical correction method had a mean of 0.1% (95% central range of [0.0%, 0.2%]) across the prostate volume.

CONCLUSION

The approximated analytical <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msubsup><mml:mi>B</mml:mi> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo></mml:msubsup> </mml:mrow> </mml:math> correction method provides comparable results with less than 0.2% error within 95% central range, compared to reference numerical <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msubsup><mml:mi>B</mml:mi> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo></mml:msubsup> </mml:mrow> </mml:math> correction. The proposed method is a practical solution for <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msubsup><mml:mi>B</mml:mi> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo></mml:msubsup> </mml:mrow> </mml:math> correction in prostate DCE-MRI because of its simple implementation.

Prostate cancer: in-bore magnetic resonance guided biopsies at active surveillance inclusion improve selection of patients for active treatment

Background Active surveillance (AS) of low-risk prostate cancer (PCa) is an accepted alternative to active treatment. However, the conventional diagnostic trans-rectal ultrasound guided biopsies (TRUS-bx) underestimate PCa aggressiveness in almost half of the cases, when compared with the surgical specimen. Purpose To investigate if additional multi-parametric magnetic resonance imaging (mpMRI) of the prostate and MRI-guided in-bore biopsies (MRGB) at AS inclusion would improve selection of patients for active treatment. Material and Methods All patients enrolled in AS programs at two Danish centers, from October 2014 to January 2016, were offered an mpMRI 8-12 weeks after the initial diagnostic TRUS-bx. Candidates had low-risk disease (PSA < 10 ng/mL, <cT2b, Gleason score [GS] < 7). Prostate lesions were scored on the five-point PIRADS scale (version 1 and 2). MRGB were performed on PIRADS 4 or 5 lesions. Significant cancer was defined as GS > 6 or GS 6 (3 + 3) lesions with ≥ 6 mm maximal cancer core length (MCCL). Results A total of 78 patients were included and in 21 patients a total of 22 PIRADS-score 4 or 5 lesions were detected. MRGB pathology revealed that 17 (81%) of these and 22% of the entire AS population harbored significant cancers at AS inclusion. In eight (38%) cases, the GS was upgraded. Also, nine patients (43%) had GS 6 (3 + 3) foci with MCCL ≥ 6 mm. Conclusion In an AS cohort based on TRUS and TRUS-bx diagnostic strategies, supplemental mpMRI and in-bore MRGB were able to efficiently reclassify a substantial number of patients as candidates for immediate active treatment.

New approach of ultra-focal brachytherapy for low- and intermediate-risk prostate cancer with custom-linked I-125 seeds: A feasibility study of optimal dose coverage

PURPOSE

To present the feasibility study of optimal dose coverage in ultra-focal brachytherapy (UFB) with multiparametric MRI for low- and intermediate-risk prostate cancer.

METHODS AND MATERIALS

UFB provisional dose plans for small target volumes (<7 cc) were calculated on a prostate training phantom to optimize the seeds number and strength. Clinical UFB consisted in a contour-based nonrigid registration (MRI/Ultrasound) to implant a fiducial marker at the location of the tumor focus. Dosimetry was performed with iodine-125 seeds and a prescribed dose of 160 Gy. On CT scans acquired at 1 month, dose coverage of 152 Gy to the ultra-focal gross tumor volume was evaluated. Registrations between magnetic resonance and CT scans were assessed on the first 8 patients with three software solutions: VariSeed, 3D Slicer, and Mirada, and quantitative evaluations of the registrations were performed. Impact of these registrations on the initial dose matrix was performed.

RESULTS

Mean differences between simulated dose plans and extrapolated Bard nomogram for UFB volumes were 36.3% (26-56) for the total activity, 18.3% (10-30) for seed strength, and 22.5% (16-38) for number of seeds. Registration method implemented in Mirada performed significantly better than VariSeed and 3D Slicer (p = 0.0117 and p = 0.0357, respectively). For dose plan evaluation between Mirada and VariSeed, D₁₀₀% (Gy) for ultra-focal gross tumor volume had a mean difference of 28.06 Gy, mean values being still above the objective of 152 Gy. D₉₀% for the prostate had a mean difference of 1.17 Gy. For urethra and rectum, dose limits were far below the recommendations.

CONCLUSIONS

This UFB study confirmed the possibility to treat with optimal dose coverage target volumes smaller than 7 cc.

Multiparametric MRI in men with clinical suspicion of prostate cancer undergoing repeat biopsy: a prospective comparison with clinical findings and histopathology

Background Multiparametric magnetic resonance imaging (mpMRI) can improve detection of clinically significant prostate cancer (csPCa). Purpose To compare mpMRI score subgroups to systematic transrectal ultrasound-guided biopsies (TRUS_bx) and prostate-specific antigen (PSA)-based findings for detection of csPCa in men undergoing repeat biopsies. Material and Methods MpMRI was performed prior to re-biopsy in 289 prospectively enrolled patients. All underwent repeat TRUS_bx followed by targeted biopsies (MRI_TB) of any mpMRI-identified lesion. MpMRI suspicion grade, PSA level, and density (PSAd) were compared with biopsy results and further matched to the radical prostatectomy (RP) specimen if available. Results PCa was detected in 128/289 (44%) patients with median age, PSA, and prior negative TRUS_bx of 64 (interquartile range [IQR] = 59-67), 12.0 ng/mL (IQR = 8.3-19.1), and 2 (IQR = 1-3), respectively. TRUS_bx detected PCa in 108/289 (37%) patients, of which 49 (45%) had insignificant cancer. MRI_TB was performed in 271/289 (94%) patients and detected PCa in 96 (35%) with 78 (81%) having csPCa. MpMRI scores showed a high association between suspicion level and biopsy results on both lesion and patient level ( P < 0.001). MpMRI was better than PSA and PSAd ( P < 0.001) to identify patients with missed csPCa. In total, 64/128 (50%) patients underwent RP; 60/64 had csPCa. MpMRI was significantly better in predicting csPCa on RP compared with TRUS_bx ( P = 0.019) as MRI_TB and TRUS_bx correctly identified 47/60 (78%) and 35/60 (58%) patients, respectively. Conclusion MpMRI improves detection of missed csPCa and suspicion scores correlate well with biopsy and RP results on both patient and lesion level.

Tunable clustering of magnetic nanoparticles in microgels: enhanced magnetic relaxivity by modulation of network architecture

In the present work we used microgels as colloidal containers for the loading of hydrophobic magnetic nanoparticles using the solvent exchange method. We varied systematically two parameters: (i) the crosslinking degree of microgels (1-4.5 mol% crosslinker) and (ii) loading of hydrophobic magnetite nanoparticles (d = 7 nm) in microgels (2-10 wt%). The experimental data show that the interplay between these two parameters provides efficient control over the clustering of magnetic nanoparticles in the microgel structure. Transverse magnetization relaxation measurements indicate that the formation of nanoparticle clusters in microgels induces non-linear enhancement of the relaxivity with the increase of nanoparticle loading in microgels. The results suggest that the modulation of the microgel network architecture can be efficiently applied to trigger self-assembly processes inside microgels and design hybrid colloids with unusual morphologies and properties.

The combination of targeted and systematic prostate biopsies is the best protocol for the detection of clinically significant prostate cancer

OBJECTIVE

Compared with standard systematic transrectal ultrasound (TRUS)-guided biopsies (SBx), targeted biopsies (TBx) using magnetic resonance imaging (MRI)/TRUS fusion could increase the detection of clinically significant prostate cancer (PCa-s) and reduce non-significant PCa (PCa-ns). This study aimed to compare the performance of the two approaches.

MATERIALS AND METHODS

A prospective, single-center study was conducted on all consecutive patients with PCa suspicion who underwent prebiopsy multiparametric MRI (mpMRI) using the Prostate Imaging Reporting and Data System (PI-RADS). All patients underwent mpMRI/TRUS fusion TBx (two to four cores/target) using UroStation™ (Koelis, Grenoble, France) and SBx (10-12 cores) during the same session. PCa-s was defined as a maximal positive core length ≥4 mm or Gleason score ≥7.

RESULTS

The study included 191 patients (at least one suspicious lesion: PI-RADS ≥3). PCa was detected in 55.5% (106/191) of the cases. The overall PCa detection rate and the PCa-s detection rate were not significantly higher in TBx alone versus SBx (44.5% vs 46.1%, p = .7, and 38.2% vs 33.5%, p = .2, respectively). Combined TBx and SBx diagnosed significantly more PCa-s than SBx alone (45% vs 33.5%, p = .02). PCa-s was detected only by TBx in 12% of cases (23/191) and only by SBx in 7.3% (14/191). Gleason score was upgraded by TBx in 16.8% (32/191) and by SBx in 13.6% (26/191) of patients (p = .4).

CONCLUSIONS

The combination of TBx and SBx achieved the best results for the detection and prognosis of PCa-s. The use of SBx alone would have missed the detection of PCa-s in 12% of patients.

IDEAL 2a Phase II Study of Ultrafocal Brachytherapy for Low- and Intermediate-risk Prostate Cancer

PURPOSE

Focal therapy of prostate cancer requires precise positioning of therapeutic agents within well-characterized index tumors (ITs). We assessed the feasibility of low-dose-rate ultrafocal brachytherapy.

METHODS AND MATERIALS

The present study was an institutional review board-approved European Clinical Trials Database-registered phase II protocol. Patients referred (October 2013 to August 2016) for active surveillance (prostate-specific antigen <10 ng/mL, cT1c-cT2a, Gleason score on referring biopsy specimens ≤6 (3+3), ≤3 positive biopsy cores, ≤50% of cancer) were preselected. Inclusion was confirmed when complementary image-guided biopsy findings informed a single Prostate Imaging Reporting and Data System (PI-RADS) ≥3, Gleason score ≤7a (3+4) lesion. A ultrasound-visible ancillary marker was positioned within the IT using a magnetic resonance imaging (MRI)/3-dimensional transrectal ultrasound (TRUS) elastic fusion-guided system (Koelis). Ultrafocal transperineal delivery of ¹²⁵I seeds used classic 2-dimensional TRUS (Bard-FlexFocus) and dose optimization (Variseed Treatment Planning System). Following Simon's optimal design, 17 patients were required to assess the feasibility of delivering ≥95% of the prescribed dose (160 Gy) to the IT (primary objective). Adverse events (Common Terminology Criteria for Adverse Events) and quality of life (5-item International Index of Erectile Function, International Prostate Symptom Score) were recorded. One-year control biopsy specimens were obtained from the IT and untreated segments.

RESULTS

Of the 44 preselected patients, 27 did not meet the inclusion criteria. Of the 17 ultrafocal brachytherapy-treated patients, 16 met the primary objective (per protocol success). The prescription dose was delivered to 14.5% ± 6.4% of the prostate volume, resulting in negligible urethral and rectal irradiation and toxicity. No recurrence was evidenced on the 1-year follow-up MRI studies or IT biopsy specimens. Seven nonclinically significant cancers and one Gleason score 7a (3+4) cancer (salvage prostatectomy) were observed in the untreated parenchyma.

CONCLUSIONS

Recent technology has allowed for selective and effective brachytherapy of small MRI targets.

Are concurrent systematic cores needed at the time of targeted biopsy in patients with prior negative prostate biopsies?

INTRODUCTION AND OBJECTIVES

MRI-guided targeted biopsies are advised in patients who have undergone an initial series of negative systematic biopsies, in whom prostate cancer (PCa) suspicion remains elevated. The aim of the study was to evaluate whether, in men with prior negative prostate biopsies, systematic cores are also warranted at the time of an MRI-targeted repeat biopsy.

MATERIAL AND METHODS

We enrolled patients with prior negative biopsy undergoing real time MRI/TRUS fusion guided prostate biopsy at our institute between 2014 and 2016. Patients with at least one index lesion on multiparametric MRI were included. All eligible patients underwent both systematic random biopsies (12-14 cores) and targeted biopsies (2-4 cores).

RESULTS

The study included 74 men with a median age of 65 years, PSA level of 9.27ng/mL, and prostatic volume of 45ml. The overall PCa detection rate and the clinically significant cancer detection rate were 56.7% and 39.2%, respectively. Targeted cores demonstrated similar clinically significant PCa detection rate compared to systematic cores (33.8% vs. 28.4%, P=0.38) with significantly less tissue sampling. Indeed, a combination approach was significantly superior to a targeted-only in overall PCa detection (+16.7% overall detection rate, P=0.007). Although differences in clinically significant PCa detection were statistically non-significant (P=0.13), a combination approach did allow detecting 7 extra clinically significant PCas (+13.8%).

CONCLUSIONS

In patients with elevated PSA and prior negative biopsies, concurrent systematic sampling may be needed at the time of targeted biopsy in order to maximize PCa detection rate. Larger studies are needed to validate our findings.

LEVEL OF EVIDENCE

4.

Evaluating the performance of PI-RADS v2 in the non-academic setting

PURPOSE

To evaluate the utility of PI-RADS v2 to diagnose clinically significant prostate cancer (CS-PCa) with magnetic resonance ultrasound (MR/US) fusion-guided prostate biopsies in the non-academic setting.

MATERIALS/METHODS

Retrospective analysis of men whom underwent prostate multiparametric MRI and subsequent MR/US fusion biopsies at a single non-academic center from 11/2014 to 3/2016. Prostate MRIs were performed on a 3-Tesla scanner with a surface body coil. The Prostate Imaging Reporting and Data System (PI-RADS) v2 scoring algorithm was utilized and MR/US fusion biopsies were performed in selected cases. Mixed effect logistic regression analyses and receiver-operating characteristic (ROC) curves were performed on PI-RADS v2 alone and combined with PSA density (PSAD) to predict CS-PCa.

RESULTS

170 patients underwent prostate MRI with 282 PI-RADS lesions. MR/US fusion diagnosed 71 CS-PCa, 33 Gleason score 3+3, and 168 negative. PI-RADS v2 score is a statistically significant predictor of CS-PCa (P < 0.001). For each one-point increase in the overall PI-RADS v2 score, the odds of having CS-PCa increases by 4.2 (95% CI 2.2-8.3). The area under the ROC curve for PI-RADS v2 is 0.69 (95% CI 0.63-0.76) and for PI-RADS v2 + PSAD is 0.76 (95% CI 0.69-0.82), statistically higher than PI-RADS v2 alone (P < 0.001). The rate of CS-PCa was about twice higher in men with high PSAD (≥0.15) compared to men with low PSAD (<0.15) when a PI-RADS 4 or 5 lesion was detected (P = 0.005).

CONCLUSION

PI-RADS v2 is a strong predictor of CS-PCa in the non-academic setting and can be further strengthened when utilized with PSA density.

Validation of Prostate Imaging-Reporting and Data System Version 2: A Retrospective Analysis

PURPOSE

Use of magnetic resonance imaging (MRI)/transrectal ultrasound fusion biopsies to determine the accuracy of multiparametric MRI (mpMRI), using Prostate Imaging-Reporting and Data System version 2 (PI-RADSv2), for detecting clinically significant prostate cancer in the overall gland and specifically the peripheral zone (PZ) and transitional zone (TZ).

METHODS

A retrospective analysis of patients who underwent fusion biopsy identified 137 men with 231 prostate lesions was approved by the Institutional Review Board. Subjects initially classified under PI-RADSv1 criteria were regraded using PI-RADSv2 by a radiologist blinded to PI-RADSv1 score and biopsy results. Spearman correlation, chi-squared, and logistic regression analysis were performed.

RESULTS

There was positive correlation between PI-RADSv2 and Gleason scores (P < 0.001). In the PZ, mpMRI demonstrated 100% sensitivity, 100% negative predictive value, and 35.9% positive predictive value, compared to 100%, 100%, and 27.1%, respectively, for TZ lesions. When predicting clinically significant prostate cancer, the PI-RADSv2 area under the curve for TZ lesions was 0.844 (95% CI: 0.753-0.935, P < 0.001) and 0.769 (95% CI: 0.684-0.854, P < 0.001) for PZ lesions. Combining PI-RADSv2 with additional risk factors (body mass index, prostate-specific antigen density, digital rectal examination) improved the area under curve.

CONCLUSIONS

PI-RADSv2 achieves excellent sensitivity and negative predictive value for both PZ and TZ lesions.

Assessment of free-hand transperineal targeted prostate biopsy using multiparametric magnetic resonance imaging-transrectal ultrasound fusion in Chinese men with prior negative biopsy and elevated prostate-specific antigen

BACKGROUND

To evaluate the role of free-hand transperineal targeted prostate biopsy using multiparametric magnetic resonance imaging-transrectal ultrasound (mpMRI-TRUS) fusion in Chinese men with repeated biopsy.

METHODS

A total of 101 consecutive patients suspicious of prostate cancer (PCa) at the mpMRI scan and with prior negative biopsy and elevated PSA values were prospectively recruited at two urological centers. Suspicious areas on mpMRI were defined and graded using PI-RADS score. Targeted biopsies (TB) were performed for each suspicious lesion and followed a 12-core systematic biopsy (SB). Results of biopsy pathology and whole-gland pathology at prostatectomy were analyzed and compared between TB and SB. The risk for biopsy positivity was assessed by univariate and multivariate logistic regression analysis.

RESULTS

Fusion biopsy revealed PCa in 41 of 101 men (40.6%) and 25 (24.8%) were clinically significant. There was exact agreement between TB and SB in 74 (73.3%) men. TB diagnosed 36% more significant cancer than SB (22 vs 13 cases, P = 0.012). When TB were combined with SB, an additional 14 cases (34.1%) of mostly significant PCa (71.4%) were diagnosed (P = 0.036). TB had greater sensitivity and accuracy for significant cancer than SB in 26 men with whole-gland pathology after prostatectomy. PI-RADS score on mpMRI was the most powerful predictor of PCa and significant cancer.

CONCLUSIONS

Free-hand transperineal TB guided with MRI-TRUS fusion imaging improves detection of clinical significant PCa in Chinese men with previously negative biopsy. PI-RADS score is a reliable predictor of PCa and significant cancer.

Is contrast enhancement needed for diagnostic prostate MRI?

Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) provides clinical guidelines for multiparametric magnetic resonance imaging (mpMRI) [T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)] of prostate. However, DCE-MRI seems to show a limited contribution in prostate cancer (PCa) detection and management. In our experience, DCE-MRI, did not show significant change in diagnostic performance in addition to DWI and T2WI [biparametric MRI (bpMRI)] which represent the predominant sequences to detect suspected lesions in peripheral and transitional zone (TZ). In this article we reviewed the role of DCE-MRI also indicating the potential contribute of bpMRI approach (T2WI and DWI) and lesion volume evaluation in the diagnosis and management of suspected PCa.

[Role of prostate MRI, TRUS fusion biopsies and new markers in the diagnostic strategy of prostate cancer]

Multiparametric MRI prostate (mp-MRI) is a powerful tool to locate lesions>0.5cm³ (below this threshold tumor volume, prostate cancers are classified as "insignificant"). The detection rate of the mp-MRI for significant cancers of small volume (0.5-1cm³) with a Gleason score≥7 is>85 %. The prostate mp-MRI optimizes the management of cancers classified as low risk of progression by providing aggressive criteria for misclassified lesions, which require an active treatment and enhance the clinicopathological criteria of indolence for subclinical lesions, which can justify of surveillance. MRI-mp coupled to the 3D ultrasound image fusion, optimizes the predictive value of biopsies and improves tumor staging, particularly when benign prostatic hyperplasia (>40cm³) is associated with clinical course. New tissue markers feasible on biopsies allow to define better the risk of progression of the small volume of cancer in order to reinforce the indications of surveillance or delayed curative treatment.

Multiregional Radiogenomic Assessment of Prostate Microenvironments with Multiparametric MR Imaging and DNA Whole-Exome Sequencing of Prostate Glands with Adenocarcinoma

Purpose To assess the underlying genomic variation of prostate gland microenvironments of patients with prostate adenocarcinoma in the context of colocalized multiparametric magnetic resonance (MR) imaging and histopathologic assessment of normal and abnormal regions by using whole-exome sequencing. Materials and Methods Six patients with prostate adenocarcinoma who underwent robotic prostatectomy with whole-mount preservation of the prostate were identified, which enabled spatial mapping between preoperative multiparametric MR imaging and the gland. Four regions of interest were identified within each gland, including regions found to be normal and abnormal via histopathologic analysis. Whole-exome DNA sequencing (>50 times coverage) was performed on each of these spatially targeted regions. Radiogenomic analysis of imaging and mutation data were performed with hierarchical clustering, phylogenetic analysis, and principal component analysis. Results Radiogenomic multiparametric MR imaging and whole-exome spatial characterization in six patients with prostate adenocarcinoma (three patients, Gleason score of 3 + 4; and three patients, Gleason score of 4 + 5) was performed across 23 spatially distinct regions. Hierarchical clustering separated histopathologic analysis-proven high-grade lesions from the normal regions, and this reflected concordance between multiparametric MR imaging and resultant histopathologic analysis in all patients. Seventy-seven mutations involving 29 cancer-associated genes across the 23 spatially distinct prostate samples were identified. There was no significant difference in mutation load in cancer-associated genes between regions that were proven to be normal via histopathologic analysis (34 mutations per sample ± 19), mildly suspicious via multiparametric MR imaging (37 mutations per sample ± 21), intermediately suspicious via multiparametric MR imaging (31 mutations per sample ± 15), and high-grade cancer (33 mutations per sample ± 18) (P = .30). Principal component analysis resolved samples from different patients and further classified samples (regardless of histopathologic status) from prostate glands with Gleason score 3 + 4 versus 4 + 5 samples. Conclusion Multiregion spatial multiparametric MR imaging and whole-exome radiogenomic analysis of prostate glands with adenocarcinoma shows a continuum of mutations across regions that were found via histologic analysis to be high grade and normal. ^© RSNA, 2017 Online supplemental material is available for this article.

What Is the Negative Predictive Value of Multiparametric Magnetic Resonance Imaging in Excluding Prostate Cancer at Biopsy? A Systematic Review and Meta-analysis from the European Association of Urology Prostate Cancer Guidelines Panel

CONTEXT

It remains unclear whether patients with a suspicion of prostate cancer (PCa) and negative multiparametric magnetic resonance imaging (mpMRI) can safely obviate prostate biopsy.

OBJECTIVE

To systematically review the literature assessing the negative predictive value (NPV) of mpMRI in patients with a suspicion of PCa.

EVIDENCE ACQUISITION

The Embase, Medline, and Cochrane databases were searched up to February 2016. Studies reporting prebiopsy mpMRI results using transrectal or transperineal biopsy as a reference standard were included. We further selected for meta-analysis studies with at least 10-core biopsies as the reference standard, mpMRI comprising at least T2-weighted and diffusion-weighted imaging, positive mpMRI defined as a Prostate Imaging Reporting Data System/Likert score of ≥3/5 or ≥4/5, and results reported at patient level for the detection of overall PCa or clinically significant PCa (csPCa) defined as Gleason ≥7 cancer.

EVIDENCE SYNTHESIS

A total of 48 studies (9613 patients) were eligible for inclusion. At patient level, the median prevalence was 50.4% (interquartile range [IQR], 36.4-57.7%) for overall cancer and 32.9% (IQR, 28.1-37.2%) for csPCa. The median mpMRI NPV was 82.4% (IQR, 69.0-92.4%) for overall cancer and 88.1% (IQR, 85.7-92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, for overall cancer (r=-0.64, p<0.0001) and csPCa (r=-0.75, p=0.032). Eight studies fulfilled the inclusion criteria for meta-analysis. Seven reported results for overall PCa. When the overall PCa prevalence increased from 30% to 60%, the combined NPV estimates decreased from 88% (95% confidence interval [95% CI], 77-99%) to 67% (95% CI, 56-79%) for a cut-off score of 3/5. Only one study selected for meta-analysis reported results for Gleason ≥7 cancers, with a positive biopsy rate of 29.3%. The corresponding NPV for a cut-off score of ≥3/5 was 87.9%.

CONCLUSIONS

The NPV of mpMRI varied greatly depending on study design, cancer prevalence, and definitions of positive mpMRI and csPCa. As cancer prevalence was highly variable among series, risk stratification of patients should be the initial step before considering prebiopsy mpMRI and defining those in whom biopsy may be omitted when the mpMRI is negative.

PATIENT SUMMARY

This systematic review examined if multiparametric magnetic resonance imaging (MRI) scan can be used to reliably predict the absence of prostate cancer in patients suspected of having prostate cancer, thereby avoiding a prostate biopsy. The results suggest that whilst it is a promising tool, it is not accurate enough to replace prostate biopsy in such patients, mainly because its accuracy is variable and influenced by the prostate cancer risk. However, its performance can be enhanced if there were more accurate ways of determining the risk of having prostate cancer. When such tools are available, it should be possible to use an MRI scan to avoid biopsy in patients at a low risk of prostate cancer.

Negative Multiparametric Magnetic Resonance Imaging of the Prostate Predicts Absence of Clinically Significant Prostate Cancer on 12-Core Template Prostate Biopsy

OBJECTIVE

To determine the negative predictive value of multiparametric magnetic resonance imaging (mpMRI), we evaluated the frequency of prostate cancer detection by 12-core template mapping biopsy in men whose mpMRI showed no suspicious regions.

METHODS

Six hundred seventy patients underwent mpMRI followed by transrectal ultrasound (TRUS)-guided systematic prostate biopsy from December 2012 to June 2016. Of this cohort, 100 patients had a negative mpMRI. mpMRI imaging sequences included T2-weighted and diffusion-weighted imaging, and dynamic contrast enhancement sequences.

RESULTS

The mean age, prostate-specific antigen, and prostate volume of the 100 men included were 64.3 years, 7.2 ng/mL, and 71 mL, respectively. Overall cancer detection was 27% (27 of 100). Prostate cancer was detected in 26.3% (10 of 38) of patients who were biopsy-naïve, 12.1% (4 of 33) of patients who had a prior negative biopsy, and in 44.8% (13 of 29) of patients previously on active surveillance; Gleason grade ≥7 was detected in 3% of patients overall (3 of 100). The negative predictive value of a negative mpMRI was 73% for all prostate cancer and 97% for Gleason ≥7 prostate cancer.

CONCLUSION

There is an approximately 3% chance of detecting clinically significant prostate cancer with systematic TRUS-guided biopsy in patients with no suspicious findings on mpMRI. This information should help guide recommendations to patients about undergoing systematic TRUS-guided biopsy when mpMRI is negative.

Comparison of the Prostate Imaging Reporting and Data System (PI-RADS) Version 1 and 2 in a Cohort of 245 Patients with Histopathological Reference and Long-Term Follow-Up

Objective:

To compare the performance of PI-RADSv2 with PI-RADSv1 in patients with elevated PSA before biopsy.

Methods:

245 patients with elevated PSA underwent mpMRI before biopsy between May 2011 and December 2014 at 3.0 Tesla without endorectal coil. Patients underwent transrectal ultrasound-guided systematic 12-core biopsy followed by radical prostatectomy (N = 68), radiation therapy (N = 91) or clinical follow-up for at least two years (N = 86). All exams were scored on a per-patient basis according to PI-RADSv1 and PI-RADSv2. ClinsigPC was defined as Gleason score ≥7 (including 3+4 with prominent but not predominant Gleason 4 component), and/or tumour volume of ≥0.5cc, and/or tumour stage ≥T3a.

Results:

In 144 patients (58.8%) a ClinsigPC was found within two years after mpMRI. The PI-RADSv1 and PI-RADSv2 overall assessment scores were significantly higher (P < 0.001) in patients with ClinsigPC as compared to patients without ClinsigPC. ROC analysis showed an area under the curve of 0.82 (CI 0.76–0.87) for PI-RADSv1 and 0.79 (CI 0.73–0.85) for PI-RADSv2 (P: NS). A threshold score of 3 exhibited sensitivities of 88.2% and 79.2% (P = 0.001) and specificities of 64.4% and 67.3% (P: NS) with PI-RADSv1 and PI-RADSv2, respectively.

Conclusions:

The mpMRI scoring systems PI-RADSv1 and PI-RADSv2 yield similar accuracy to detect ClinsigPC in patients with elevated PSA, although clinicians should be aware that when an overall assessment score of 3 is used as a threshold for a positive mpMRI, PI-RADSv2 has lower sensitivity than PI-RADSv1. Nevertheless, PI-RADSv2 is preferable over PI-RADSv1 because it has the advantage of providing well-defined instructions on how to determine the overall assessment category.

Dynamic contrast-enhanced imaging has limited added value over T2-weighted imaging and diffusion-weighted imaging when using PI-RADSv2 for diagnosis of clinically significant prostate cancer in patients with elevated PSA

AIM

To determine the added value of dynamic contrast-enhanced imaging (DCE) over T2-weighted imaging (T2-WI) and diffusion-weighted imaging (DWI) for detection of clinically significant prostate cancer (csPC) in patients with elevated prostate-specific antigen (PSA).

METHODS AND MATERIALS

Two hundred and forty-five patients with elevated PSA underwent multiparametric (mp) magnetic resonance imaging (MRI) of the prostate before biopsy. mpMRI was performed using a 3 T MRI system without an endorectal coil. Patients underwent transrectal ultrasound-guided systematic 12 core biopsy followed by radical prostatectomy (n=68), radiation therapy (n=91), or clinical follow-up for at least 2 years (n=86). csPC was defined as Gleason score ≥3+4 and/or tumour volume of ≥0.5 ml, and/or tumour stage ≥T3a. The MRI findings were scored according to the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) and an alternative overall assessment category (PI-RADSv2Alt) based on only T2-WI and DWI.

RESULTS

In 144 patients (58.8%), csPC was found within 2 years after MRI. With scoring according to the PI-RADSv2 guidelines, DCE was not needed for determination of the overall assessment category in 80.8% (198/245) of patients. Receiver operating characteristic (ROC) analysis showed an area under the curve of 0.79 (95% confidence interval [CI]: 0.74-0.85) for PI-RADSv2 and 0.79 (95% CI: 0.73-0.85) for PI-RADSv2Alt.

CONCLUSION

The added value of DCE over T2-WI and DWI is limited when using PI-RADSv2 for diagnosis of csPC in patients with elevated PSA before biopsy. An alternative overall assessment score using only T2-WI and DWI yielded similar performance to PI-RADSv2.

Standardized Reporting of Prostate MRI: Comparison of the Prostate Imaging Reporting and Data System (PI-RADS) Version 1 and Version 2

Introduction

Objective of our study was to determine the agreement between version 1 (v1) and v2 of the Prostate Imaging Reporting and Data System (PI-RADS) for evaluation of multiparametric prostate MRI (mpMRI) and to compare their diagnostic accuracy, their inter-observer agreement and practicability.

Material and Methods

mpMRI including T2-weighted imaging, diffusion-weighted imaging (DWI) and dynamic contrast-enhanced imaging (DCE) of 54 consecutive patients, who subsequently underwent MRI-guided in-bore biopsy were re-analyzed according to PI-RADS v1 and v2 by two independent readers. Diagnostic accuracy for detection of prostate cancer (PCa) was assessed using ROC-curve analysis. Agreement between PI-RADS versions and observers was calculated and the time needed for scoring was determined.

Results

MRI-guided biopsy revealed PCa in 31 patients. Diagnostic accuracy for detection of PCa was equivalent with both PI-RADS versions for reader 1 with sensitivities and specificities of 84%/91% (AUC = 0.91 95%CI[0.8–1]) for PI-RADS v1 and 100%/74% (AUC = 0.92 95% CI[0.8–1]) for PI-RADS v2. Reader 2 achieved similar diagnostic accuracy with sensitivity and specificity of 74%/91% (AUC = 0.88 95%CI[0.8–1]) for PI-RADS v1 and 81%/91% (AUC = 0.91 95%CI[0.8–1]) for PI-RADS v2. Agreement between scores determined with different PI-RADS versions was good (reader 1: κ = 0.62, reader 2: κ = 0.64). Inter-observer agreement was moderate with PI-RADS v2 (κ = 0.56) and fair with v1 (κ = 0.39). The time required for building the PI-RADS score was significantly lower with PI-RADS v2 compared to v1 (24.7±2.3 s vs. 41.9±2.6 s, p<0.001).

Conclusion

Agreement between PI-RADS versions was high and both versions revealed high diagnostic accuracy for detection of PCa. Due to better inter-observer agreement for malignant lesions and less time demand, the new PI-RADS version could be more practicable for clinical routine.