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Contains fulltext : 253046.pdf (Publisher’s version ) (Open Access)

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported.The initial STOMP and ORIOLE trial reports suggested that metastasis-directed therapy (MDT) in oligometastatic castration-sensitive prostate cancer (omCSPC) was associated with improved treatment outcomes. Here, we present long-term outcomes of MDT in omCSPC by pooling STOMP and ORIOLE and assess the ability of a high-risk mutational signature to risk stratify outcomes after MDT. The primary end point was progression-free survival (PFS) calculated using the Kaplan-Meier method. High-risk mutations were defined as pathogenic somatic mutations within ATM, BRCA1/2, Rb1, or TP53. The median follow-up for the whole group was 52.5 months. Median PFS was prolonged with MDT compared with observation (pooled hazard ratio [HR], 0.44; 95% CI, 0.29 to 0.66; P value < .001), with the largest benefit of MDT in patients with a high-risk mutation (HR high-risk, 0.05; HR no high-risk, 0.42; P value for interaction: .12). Within the MDT cohort, the PFS was 13.4 months in those without a high-risk mutation, compared with 7.5 months in those with a high-risk mutation (HR, 0.53; 95% CI, 0.25 to 1.11; P = .09). Long-term outcomes from the only two randomized trials in omCSPC suggest a sustained clinical benefit to MDT over observation. A high-risk mutational signature may help risk stratify treatment outcomes after MDT.

Item does not contain fulltext, BACKGROUND: Imaging techniques are used to identify local recurrence of prostate cancer (PCa) for salvage therapy and to exclude metastases that should be addressed with systemic therapy. For magnetic resonance imaging (MRI), a reduction in the variability of acquisition, interpretation, and reporting is required to detect local PCa recurrence in men with biochemical relapse after local treatment with curative intent. OBJECTIVE: To propose a standardised method for image acquisition and assessment of PCa local recurrence using MRI after radiation therapy (RP) and radical prostatectomy (RT). EVIDENCE ACQUISITION: Prostate Imaging for Recurrence Reporting (PI-RR) was formulated using the existing literature. An international panel of experts conducted a nonsystematic review of the literature. The PI-RR system was created via consensus through a combination of face-to-face and online discussions. EVIDENCE SYNTHESIS: Similar to with PI-RADS, based on the best available evidence and expert opinion, the minimum acceptable MRI parameters for detection of recurrence after radiation therapy and radical prostatectomy are set. Also, a simplified and standardised terminology and content of the reports that use five assessment categories to summarise the suspicion of local recurrence (PI-RR) are designed. PI-RR scores of 1 and 2 are assigned to lesions with a very low and low likelihood of recurrence, respectively. PI-RR 3 is assigned if the presence of recurrence is uncertain. PI-RR 4 and 5 are assigned for a high and very high likelihood of recurrence, respectively. PI-RR is intended to be used in routine clinical practice and to facilitate data collection and outcome monitoring for research. CONCLUSIONS: This paper provides a structured reporting system (PI-RR) for MRI evaluation of local recurrence of PCa after RT and RP. PATIENT SUMMARY: A new method called PI-RR was developed to promote standardisation and reduce variations in the acquisition, interpretation, and reporting

Contains fulltext : 245173.pdf (Publisher’s version ) (Open Access), Artificial intelligence developments are essential to the successful deployment of community-wide, MRI-driven prostate cancer diagnosis. AI systems should ensure that the main benefits of biopsy avoidance are delivered while maintaining consistent high specificities, at a range of disease prevalences. Since all current artificial intelligence / computer-aided detection systems for prostate cancer detection are experimental, multiple developmental efforts are still needed to bring the vision to fruition. Initial work needs to focus on developing systems as diagnostic supporting aids so their results can be integrated into the radiologists' workflow including gland and target outlining tasks for fusion biopsies. Developing AI systems as clinical decision-making tools will require greater efforts. The latter encompass larger multicentric, multivendor datasets where the different needs of patients stratified by diagnostic settings, disease prevalence, patient preference, and clinical setting are considered. AI-based, robust, standard operating procedures will increase the confidence of patients and payers, thus enabling the wider adoption of the MRI-directed approach for prostate cancer diagnosis. KEY POINTS: * AI systems need to ensure that the benefits of biopsy avoidance are delivered with consistent high specificities, at a range of disease prevalence. * Initial work has focused on developing systems as diagnostic supporting aids for outlining tasks, so they can be integrated into the radiologists' workflow to support MRI-directed biopsies. * Decision support tools require a larger body of work including multicentric, multivendor studies where the clinical needs, disease prevalence, patient preferences, and clinical setting are additionally defined.

Contains fulltext : 225849.pdf (Publisher’s version ) (Open Access), OBJECTIVES: This study aims to define consensus-based criteria for acquiring and reporting prostate MRI and establishing prerequisites for image quality. METHODS: A total of 44 leading urologists and urogenital radiologists who are experts in prostate cancer imaging from the European Society of Urogenital Radiology (ESUR) and EAU Section of Urologic Imaging (ESUI) participated in a Delphi consensus process. Panellists completed two rounds of questionnaires with 55 items under three headings: image quality assessment, interpretation and reporting, and radiologists' experience plus training centres. Of 55 questions, 31 were rated for agreement on a 9-point scale, and 24 were multiple-choice or open. For agreement items, there was consensus agreement with an agreement >/= 70% (score 7-9) and disagreement of /= 50% of votes. RESULTS: Twenty-four out of 31 of agreement items and 11/16 of other questions reached consensus. Agreement statements were (1) reporting of image quality should be performed and implemented into clinical practice; (2) for interpretation performance, radiologists should use self-performance tests with histopathology feedback, compare their interpretation with expert-reading and use external performance assessments; and (3) radiologists must attend theoretical and hands-on courses before interpreting prostate MRI. Limitations are that the results are expert opinions and not based on systematic reviews or meta-analyses. There was no consensus on outcomes statements of prostate MRI assessment as quality marker. CONCLUSIONS: An ESUR and ESUI expert panel showed high agreement (74%) on issues improving prostate MRI quality. Checking and reporting of image quality are mandatory. Prostate radiologists should attend theoretical and hands-on courses, followed by supervised education, and must perform regular performance assessments. KEY POINTS: * Multi-parametric MRI in the

Contains fulltext : 225861.pdf (Publisher’s version ) (Closed access)

Contains fulltext : 225907.pdf (Publisher’s version ) (Closed access)

Contains fulltext : 220776.pdf (Publisher’s version ) (Closed access), CONTEXT: There is a lack of comprehensive data regarding the factors that influence the diagnostic accuracy of multiparametric magnetic resonance imaging (mpMRI) to detect and localize clinically significant prostate cancer (csPCa). OBJECTIVE: To systematically review the current literature assessing the factors influencing the variability of mpMRI performance in csPCa diagnosis. EVIDENCE ACQUISITION: A computerized bibliographic search of Medline/PubMed database was performed for all studies assessing magnetic field strength, use of an endorectal coil, assessment system used by radiologists and inter-reader variability, experience of radiologists and urologists, use of a contrast agent, and use of computer-aided diagnosis (CAD) tools in relation to mpMRI diagnostic accuracy. EVIDENCE SYNTHESIS: A total of 77 articles were included. Both radiologists' reading experience and urologists'/radiologists' biopsy experience were the main factors that influenced diagnostic accuracy. Therefore, it is mandatory to indicate the experience of the interpreting radiologists and biopsy-performing urologists to support the reliability of the findings. The most recent Prostate Imaging Reporting and Data System (PI-RADS) guidelines are recommended for use as the main assessment system for csPCa, given the simplified and standardized approach as well as its particular added value for less experienced radiologists. Biparametric MRI had similar accuracy to mpMRI; however, biparametric MRI performed better with experienced readers. The limited data available suggest that the combination of CAD and radiologist readings may influence diagnostic accuracy positively. CONCLUSIONS: Multiple factors affect the accuracy of mpMRI and MRI-targeted biopsy to detect and localize csPCa. The high heterogeneity across the studies underlines the need to define the experience of radiologists and urologists, implement quality control, and adhere to the most recent PI-RADS assessment guidelines. Further re

Objectives This study aims to define consensus-based criteria for acquiring and reporting prostate MRI and establishing prerequisites for image quality. Methods A total of 44 leading urologists and urogenital radiologists who are experts in prostate cancer imaging from the European Society of Urogenital Radiology (ESUR) and EAU Section of Urologic Imaging (ESUI) participated in a Delphi consensus process. Panellists completed two rounds of questionnaires with 55 items under three headings: image quality assessment, interpretation and reporting, and radiologists’ experience plus training centres. Of 55 questions, 31 were rated for agreement on a 9-point scale, and 24 were multiple-choice or open. For agreement items, there was consensus agreement with an agreement ≥ 70% (score 7–9) and disagreement of ≤ 15% of the panellists. For the other questions, a consensus was considered with ≥ 50% of votes. Results Twenty-four out of 31 of agreement items and 11/16 of other questions reached consensus. Agreement statements were (1) reporting of image quality should be performed and implemented into clinical practice; (2) for interpretation performance, radiologists should use self-performance tests with histopathology feedback, compare their interpretation with expert-reading and use external performance assessments; and (3) radiologists must attend theoretical and hands-on courses before interpreting prostate MRI. Limitations are that the results are expert opinions and not based on systematic reviews or meta-analyses. There was no consensus on outco

Objectives: This study aims to define consensus-based criteria for acquiring and reporting prostate MRI and establishing prerequisites for image quality. Methods: A total of 44 leading urologists and urogenital radiologists who are experts in prostate cancer imaging from the European Society of Urogenital Radiology (ESUR) and EAU Section of Urologic Imaging (ESUI) participated in a Delphi consensus process. Panellists completed two rounds of questionnaires with 55 items under three headings: image quality assessment, interpretation and reporting, and radiologists’ experience plus training centres. Of 55 questions, 31 were rated for agreement on a 9-point scale, and 24 were multiple-choice or open. For agreement items, there was consensus agreement with an agreement ≥ 70% (score 7–9) and disag

Contains fulltext : 203381.pdf (publisher's version ) (Open Access), CONTEXT: The Prostate Imaging-Reporting and Data System (PI-RADS) v2 analysis system for multiparametric magnetic resonance imaging (mpMRI) detection of prostate cancer (PCa) is based on PI-RADS v1, accumulated scientific evidence, and expert consensus opinion. OBJECTIVE: To summarize the accuracy, strengths and weaknesses of PI-RADS v2, discuss pathway implications of its use and outline opportunities for improvements and future developments. EVIDENCE ACQUISITION: For this consensus expert opinion from the PI-RADS steering committee, clinical studies, systematic reviews, and professional guidelines for mpMRI PCa detection were evaluated. We focused on the performance characteristics of PI-RADS v2, comparing data to systems based on clinicoradiologic Likert scales and non-PI-RADS v2 imaging only. Evidence selections were based on high-quality, prospective, histologically verified data, with minimal patient selection and verifications biases. EVIDENCE SYNTHESIS: It has been shown that the test performance of PI-RADS v2 in research and clinical practice retains higher accuracy over systematic transrectal ultrasound (TRUS) biopsies for PCa diagnosis. PI-RADS v2 fails to detect all cancers but does detect the majority of tumors capable of causing patient harm, which should not be missed. Test performance depends on the definition and prevalence of clinically significant disease. Good performance can be attained in practice when the quality of the diagnostic process can be assured, together with joint working of robustly trained radiologists and urologists, conducting biopsy procedures within multidisciplinary teams. CONCLUSIONS: It has been shown that the test performance of PI-RADS v2 in research and clinical practice is improved, retaining higher accuracy over systematic TRUS biopsies for PCa diagnosis. PATIENT SUMMARY: Multiparametric magnetic resonance imaging (MRI) and MRI-directed biopsies using the Prostate Imaging-Reporting and Data System improves the detection

Contains fulltext : 206232.pdf (publisher's version ) (Closed access)

Contains fulltext : 209078.pdf (publisher's version ) (Closed access), The Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) was developed with a consensus-based process using a combination of published data, and expert observations and opinions. In the short time since its release, numerous studies have validated the value of PI-RADS v2 but, as expected, have also identified a number of ambiguities and limitations, some of which have been documented in the literature with potential solutions offered. To address these issues, the PI-RADS Steering Committee, again using a consensus-based process, has recommended several modifications to PI-RADS v2, maintaining the framework of assigning scores to individual sequences and using these scores to derive an overall assessment category. This updated version, described in this article, is termed PI-RADS v2.1. It is anticipated that the adoption of these PI-RADS v2.1 modifications will improve inter-reader variability and simplify PI-RADS assessment of prostate magnetic resonance imaging even further. Research on the value and limitations on all components of PI-RADS v2.1 is strongly encouraged.

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.

Contains fulltext : 177907.pdf (publisher's version ) (Closed access)

Item does not contain fulltext, CONTEXT: Detection of clinically significant prostate cancer (PCa) is a major challenge. It has been shown that multiparametric magnetic resonance imaging (mpMRI) facilitates localisation of PCa and can help in targeting prostate biopsy. OBJECTIVE: To systematically review the literature to determine the diagnostic accuracy of mpMRI in the detection of clinically significant PCa. EVIDENCE ACQUISITION: The Pubmed, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL) databases were searched from January 1, 2000 to September 30, 2014, using the search criteria "prostate OR Pca OR PSA OR prostatic OR prostate cancer" AND "MR OR NMR OR NMRI OR MRI OR magnetic resonance OR ADC OR DWI OR DCE OR diffusion weighted OR dynamic contrast OR multiparametric OR MRSI OR MR spectroscopy". Two reviewers independently assessed 1729 records. Two independent reviewers assessed the methodologic quality using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) 2 tool. EVIDENCE SYNTHESIS: Twelve articles were eventually selected. Patients had a median age of 62-65 yr (range 39-83 yr), a median prostate-specific antigen (PSA) level of 5.1-13.4 ng/ml (range 1.2-228 ng/ml), and Gleason score of 6-10. Various definitions of clinical significance were used, mainly based on maximum cancer core length and grade at biopsy, number of positive cores, and PSA. Detection of clinically significant PCa using mpMRI ranged from 44% to 87% in biopsy-naive males and men with prior negative biopsies using prostate biopsy or definitive pathology of a radical prostatectomy specimen as the reference standard. The negative predictive value for exclusion of significant disease ranged from 63% to 98%. CONCLUSIONS: mpMRI is able to detect significant PCa in biopsy-naive males and men with prior negative biopsies. The negative predictive value of mpMRI is important to the clinician because mpMRI could be used to rule out significant disease. This may result in fewer or no systematic or

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Item does not contain fulltext, OBJECTIVES: A prospective multicenter validation of the ability of 1H magnetic resonance spectroscopic imaging (MRSI) to distinguish cancer from noncancer tissues throughout the prostate with histopathology of the resected organ as the standard of reference. MATERIALS AND METHODS: Institutional review board approval was obtained for all centers and all participating patients and volunteers provided written informed consent. Ninety-nine patients and 10 age-matched volunteers from 8 participating centers underwent magnetic resonance imaging and 3-dimensional MRSI with an endorectal coil at 1.5 T. Selected MRSI voxels were assigned to the peripheral zone (PZ), the central gland (CG), the periurethral area, and cancer tissue. Signal ratios of choline + creatine to citrate (CC/C) in spectra of these voxels were automatically calculated. Receiver operating characteristic curves were constructed to assess the accuracy by which this ratio can discriminate cancer from noncancer tissue. RESULTS: A total of 70% of voxels in noncancer tissue and 90% of voxels in cancer tissue passed the quality check of the automatically fitted spectra. The median CC/C was significantly different between any noncancer and cancer tissue (P < 0.0001), but not between the different contributing centers. CC/C increased with cancer focus size (P =0.0008) and certainty of voxel mapping to histopathologic cancer site (P 0.0001). The area under the receiver operating characteristic curve for discriminating voxels of cancer tissue from noncancer tissue was 0.88 (confidence interval: 0.84-0.92) in the PZ and 0.76 (confidence interval: 0.71- 0.81) in the CG.