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Objectives: Triple-negative (ER-/PR-/HER2-) breast carcinomas (TNBC) are aggressive tumours with underexplored imaging features. This study investigates whether their vascular characteristics as assessed by dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast-enhanced (DSC) MRI are distinct from the prognostically more favourable ER+/PR+/HER2- cancers.Methods: Patients with primary breast cancer underwent MRI before neoadjuvant chemotherapy and were identified as ER-/PR-/HER2- or ER+/PR+/HER2- from core biopsy specimens. MRI parameters reflecting tissue perfusion, permeability, and extracellular leakage space were measured. Values for inflow transfer constant (K(trans)), outflow rate constant (k(ep)), leakage space (v(e)), area under the gadolinium curve (IAUGC(60) ), relative blood volume (rBV) and flow (rBF), and Mean Transit Time (MTT) were compared across receptor status and with known prognostic variables.Results: Thirty seven patients were assessable in total (16 ER-/PR-/HER2-, 21 ER+/PR+/HER2-). Lower v(e) (p = 0.001), shorter MTT (p = 0.007) and higher k(ep) values (p = 0.044) were observed in TNBC. v(e) was lower across all T stages, node-negative (p = 0.004) and low-grade TNBC (p = 0.037). v(e) was the best predictor of triple negativity (ROC AUC 0.80).Conclusions: TNBC possess characteristic features on imaging, with lower extracellular space (higher cell density) and higher contrast agent wash-out rate (higher vascular permeability) suggesting a distinctive phenotype detectable by MRI. [ABSTRACT FROM AUTHOR]

The purpose was to determine the reproducibility of apparent diffusion coefficient (ADC) measurements in a two-centre phase I clinical trial; and to track ADC changes in response to the sequential administration of the vascular disrupting agent, combretastatin A4 phosphate (CA4P), and the anti-angiogenic drug, bevacizumab. Sixteen patients with solid tumours received CA4P and bevacizumab treatment. Echo-planar diffusion-weighted MRI was performed using six b values (b = 0-750 s/mm(2)) before (x2), and at 3 and 72 h after a first dose of CA4P. Bevacizumab was given 4 h after a second dose of CA4P, and imaging performed 3 h post CA4P and 72 h after bevacizumab treatment. The coefficient of repeatability (r) of ADC total (all b values), ADC high (b = 100-750) and ADC low (b = 0-100) was calculated by Bland-Altman analysis. The ADC total and ADC high showed good measurement reproducibility (r% = 13.3, 14.1). There was poor reproducibility of the perfusion-sensitive ADC low (r% = 62.5). Significant increases in the median ADC total and ADC high occurred at 3 h after the second dose of CA4P (p < 0.05). ADC measurements were highly reproducible in a two-centre clinical trial setting and appear promising for evaluating the effects of drugs that target tumour vasculature. [ABSTRACT FROM AUTHOR]

Hepatic metastases are arterially supplied, resulting in an elevated hepatic perfusion index (HPI). The purpose of this study was to use dynamic contrast-enhanced (DCE) MR imaging to quantify the HPI of metastases and the liver before and after treatment with a novel antiangiogenic drug. Ten patients with known metastatic liver disease underwent DCE-MR studies. HPIs of metastases and whole liver were derived using regions of interest (ROIs) and calculated on a pixel-by-pixel basis from quantified changes in gadopentetate dimeglumine (Gd-DTPA) concentration. The HPI measurement error prior to treatment was derived by the Bland-Altman analysis. The median HPI before and after treatment with antiangiogenic drug BIBF 1120 were compared using the Wilcoxon signed rank test. Prior to treatment, the median HPI of metastases, 0.75 +/- 0.14, was significantly higher than that of the whole liver, 0.66 +/- 0.16 (p < 0.01). Bland-Altman reproducibility coefficients of the median HPI from metastases and whole liver were 13.0 and 5.1% respectively. The median HPI of metastases decreased significantly at 28 days after treatment with BIBF 1120 (p < 0.05). This pilot study demonstrates that HPI determined using quantified Gd-DTPA concentration is reproducible and may be useful for monitoring antiangiogenic treatment response of hepatic metastases. [ABSTRACT FROM AUTHOR]

Angiogenesis is a key factor in the growth and dissemination of colorectal cancer, with significant implications for its clinical management. Previous trials have provided proof-of-principle that inhibition of angiogenesis has the potential to enhance the effectiveness of treatment for this disease. Characterisation of the angiogenic status of the tumour on an individual patient basis could allow for a more targeted approach to treatment. In vivo imaging techniques that assess tumour microvessel function have the potential to improve the management of treatment for patients with colorectal cancer. This review focuses on MRI and CT assessment of colorectal cancer angiogenesis. We discuss the effects that these two techniques have had in the assessment of this disease, including tumour staging and therapeutic assessment. Their comparability with other imaging techniques, in particular ultrasound, and their limitations are also addressed. [ABSTRACT FROM AUTHOR]

Background and Objectives: We assessed the agreement between prostate-specific antigen (PSA) and imaging responses using whole-body magnetic resonance imaging (wbMRI). Our aim was to explore the potential prognostic value of PSA and wbMRI responses in metastatic hormone-naïve prostate cancer (mHNPC) and castration-resistant PC (mCRPC)., Methods: wbMRI was prospectively performed in 37 patients with mHNPC and 51 with mCRPC before and after 6-12 mo of androgen deprivation therapy and an androgen receptor pathway inhibitor (ARPI). Imaging responses were defined according to the Metastasis Reporting and Data System for PC (MET-RADS-P) criteria. A PSA response was defined as PSA ≤0.2 ng/ml in mHNPC and a ≥50% decrease from the pretreatment level in mCRPC. Agreement between PSA and wbMRI responses was assessed using Cohen's κ. The association between time to subsequent treatment and overall survival (OS) was analyzed using Cox regression analysis., Key Findings and Limitations: Agreement between PSA and wbMRI responses was fair in mHNPC (κ = 0.30) but none to slight in mCRPC (κ = 0.15). In mHNPC, patients with a PSA or wbMRI response were less likely to receive subsequent treatments; wbMRI progression was associated with a significantly higher risk of death (hazard ratio 8.59; p = 0.002). In mCRPC, two-thirds of patients with a PSA response showed progression on wbMRI; neither PSA nor wbMRI progression changed the likelihood of starting a subsequent treatment or the risk of death., Conclusions and Clinical Implications: In mHNPC, wbMRI progression was associated with a higher risk of needing subsequent treatment and shorter OS., Patient Summary: We evaluated the agreement between routine PSA (prostate-specific antigen) test results and whole-body MRI (magnetic resonance imaging) scans for assessing the response of metastatic prostate cancer to treatment. There was disagreement between the PSA and MRI results, mainly for patients with cancer that was resistant to hormone-based treatment. Combining PSA with whole-body MRI might provide a more accurate picture of the response of advanced prostate cancer to treatment., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

MRI has gained prominence in the diagnostic workup of prostate cancer (PCa) patients, with the Prostate Imaging Reporting and Data System (PI-RADS) being widely used for cancer detection. Beyond PI-RADS, other MRI-based scoring tools have emerged to address broader aspects within the PCa domain. However, the multitude of available MRI-based grading systems has led to inconsistencies in their application within clinical workflows. The Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) assesses the likelihood of clinically significant radiological changes of PCa during active surveillance, and the Prostate Imaging for Local Recurrence Reporting (PI-RR) scoring system evaluates the risk of local recurrence after whole-gland therapies with curative intent. Underlying any system is the requirement to assess image quality using the Prostate Imaging Quality Scoring System (PI-QUAL). This article offers practicing radiologists a comprehensive overview of currently available scoring systems with clinical evidence supporting their use for managing PCa patients to enhance consistency in interpretation and facilitate effective communication with referring clinicians. KEY POINTS: Assessing image quality is essential for all prostate MRI interpretations and the PI-QUAL score represents  the standardized tool for this purpose. Current urological clinical guidelines for prostate cancer diagnosis and localization recommend adhering to the PI-RADS recommendations. The PRECISE and PI-RR scoring systems can be used for assessing radiological changes of prostate cancer during active surveillance and the likelihood of local recurrence after radical treatments respectively., (© 2024. The Author(s).)

Multiparametric MRI is the optimal primary investigation when prostate cancer is suspected, and its ability to rule in and rule out clinically significant disease relies on high-quality anatomical and functional images. Avenues for achieving consistent high-quality acquisitions include meticulous patient preparation, scanner setup, optimised pulse sequences, personnel training, and artificial intelligence systems. The impact of these interventions on the final images needs to be quantified. The prostate imaging quality (PI-QUAL) scoring system was the first standardised quantification method that demonstrated the potential for clinical benefit by relating image quality to cancer detection ability by MRI. We present the updated version of PI-QUAL (PI-QUAL v2) which applies to prostate MRI performed with or without intravenous contrast medium using a simplified 3-point scale focused on critical technical and qualitative image parameters. CLINICAL RELEVANCE STATEMENT: High image quality is crucial for prostate MRI, and the updated version of the PI-QUAL score (PI-QUAL v2) aims to address the limitations of version 1. It is now applicable to both multiparametric MRI and MRI without intravenous contrast medium. KEY POINTS: High-quality images are essential for prostate cancer diagnosis and management using MRI. PI-QUAL v2 simplifies image assessment and expands its applicability to prostate MRI without contrast medium. PI-QUAL v2 focuses on critical technical and qualitative image parameters and emphasises T2-WI and DWI., (© 2024. The Author(s).)

Background and Objective: Intensification of targeted biopsy (TBx) around a magnetic resonance imaging (MRI)-visible lesion with regional biopsy (RBx) could obviate the need for systematic biopsy (SBx). We aimed to compare the detection yields of clinically significant prostate cancer (csPCa)-defined as International Society of Urological Pathology (ISUP) grade group ≥2-between TBx + RBx and the reference standard (TBx + SBx)., Methods: RBx was defined as perilesional or ipsilateral biopsy. A literature search was conducted up to September 2023 using PubMed, Embase, and Web of Science databases. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines were followed. Included studies were eligible when presenting data from SBx, TBx, and TBx + RBx cores and their detection yields. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) criteria were used to assess the risk of bias of the included studies., Key Findings and Limitations: Twenty-one studies were included for a meta-analysis. The overall detection yield of csPCa was not statistically different between TBx + SBX and TBx + RBx (46.1% vs 44.2%; odds ratio [OR] 1.07, 95% confidence interval [CI] 0.99-1.16, p = 0.07); similar findings were found also for ISUP grade group ≥3 prostate cancer (PCa; OR 1.06, 95% CI 0.92-1.22, p = 0.43) and in different subgroup analyses. TBx + SBx was associated with higher cancer detection of ISUP grade group 1 PCa (OR 1.16, 95% CI 1.04-1.30, p = 0.008). The main limitations include the retrospective nature of most of the selected studies, heterogeneity of RBx definition, and template., Conclusions and Clinical Implications: Our study supports the use of the TBx + RBx template in the early detection pathway for the detection of csPCa. SBx can be omitted when targeting lesions visible on MRI., Patient Summary: A prostate biopsy strategy consisting of taking biopsy in and around an magnetic resonance imaging-visible lesion reduces the risk of detecting indolent prostate cancers without affecting the detection of aggressive tumours., (Copyright © 2024 European Association of Urology. Published by Elsevier B.V. All rights reserved.)

Background and Objective: Biparametric magnetic resonance imaging (bpMRI), excluding dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), is a potential replacement for multiparametric MRI (mpMRI) in diagnosing clinically significant prostate cancer (csPCa). An extensive international multireader multicase observer study was conducted to assess the noninferiority of bpMRI to mpMRI in csPCa diagnosis., Methods: An observer study was conducted with 400 mpMRI examinations from four European centers, excluding examinations with prior prostate treatment or csPCa (Gleason grade [GG] ≥2) findings. Readers assessed bpMRI and mpMRI sequentially, assigning lesion-specific Prostate Imaging Reporting and Data System (PI-RADS) scores (3-5) and a patient-level suspicion score (0-100). The noninferiority of patient-level bpMRI versus mpMRI csPCa diagnosis was evaluated using the area under the receiver operating curve (AUROC) alongside the sensitivity and specificity at PI-RADS ≥3 with a 5% margin. The secondary outcomes included insignificant prostate cancer (GG1) diagnosis, diagnostic evaluations at alternative risk thresholds, decision curve analyses (DCAs), and subgroup analyses considering reader expertise. Histopathology and ≥3 yr of follow-up were used for the reference standard., Key Findings and Limitations: Sixty-two readers (45 centers and 20 countries) participated. The prevalence of csPCa was 33% (133/400); bpMRI and mpMRI showed similar AUROC values of 0.853 (95% confidence interval [CI], 0.819-0.887) and 0.859 (95% CI, 0.826-0.893), respectively, with a noninferior difference of -0.6% (95% CI, -1.2% to 0.1%, p < 0.001). At PI-RADS ≥3, bpMRI and mpMRI had sensitivities of 88.6% (95% CI, 84.8-92.3%) and 89.4% (95% CI, 85.8-93.1%), respectively, with a noninferior difference of -0.9% (95% CI, -1.7% to 0.0%, p < 0.001), and specificities of 58.6% (95% CI, 52.3-63.1%) and 57.7% (95% CI, 52.3-63.1%), respectively, with a noninferior difference of 0.9% (95% CI, 0.0-1.8%, p < 0.001). At alternative risk thresholds, mpMRI increased sensitivity at the expense of reduced specificity. DCA demonstrated the highest net benefit for an mpMRI pathway in cancer-averse scenarios, whereas a bpMRI pathway showed greater benefit for biopsy-averse scenarios. A subgroup analysis indicated limited additional benefit of DCE MRI for nonexperts. Limitations included that biopsies were conducted based on mpMRI imaging, and reading was performed in a sequential order., Conclusions and Clinical Implications: It has been found that bpMRI is noninferior to mpMRI in csPCa diagnosis at AUROC, along with the sensitivity and specificity at PI-RADS ≥3, showing its value in individuals without prior csPCa findings and prostate treatment. Additional randomized prospective studies are required to investigate the generalizability of outcomes., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background and Objective: Innovations have improved outcomes in advanced prostate cancer (PC). Nonetheless, we continue to lack high-level evidence on a variety of topics that greatly impact daily practice. The 2024 Advanced Prostate Cancer Consensus Conference (APCCC) surveyed experts on key questions in clinical management in order to supplement evidence-based guidelines. Here we present voting results for questions from APCCC 2024., Methods: Before the conference, a panel of 120 international PC experts used a modified Delphi process to develop 183 multiple-choice consensus questions on eight different topics. Before the conference, these questions were administered via a web-based survey to the voting panel members ("panellists")., Key Findings and Limitations: Consensus was a priori defined as ≥75% agreement, with strong consensus defined as ≥90% agreement. The voting results show varying degrees of consensus, as discussed in this article and detailed in the Supplementary material. These findings do not include a formal literature review or meta-analysis., Conclusions and Clinical Implications: The voting results can help physicians and patients navigate controversial areas of clinical management for which high-level evidence is scant or conflicting. The findings can also help funders and policymakers in prioritising areas for future research. Diagnostic and treatment decisions should always be individualised on the basis of patient and cancer characteristics, and should incorporate current and emerging clinical evidence, guidelines, and logistic and economic factors. Enrolment in clinical trials is always strongly encouraged. Importantly, APCCC 2024 once again identified important gaps (areas of nonconsensus) that merit evaluation in specifically designed trials., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Objectives: To develop and test zone-specific prostate-specific antigen density (sPSAD) combined with PI-RADS to guide prostate biopsy decision strategies (BDS)., Methods: This retrospective study included consecutive patients, who underwent prostate MRI and biopsy (01/2012-10/2018). The whole gland and transition zone (TZ) were segmented at MRI using a retrained deep learning system (DLS; nnU-Net) to calculate PSAD and sPSAD, respectively. Additionally, sPSAD and PI-RADS were combined in a BDS, and diagnostic performances to detect Grade Group ≥ 2 (GG ≥ 2) prostate cancer were compared. Patient-based cancer detection using sPSAD was assessed by bootstrapping with 1000 repetitions and reported as area under the curve (AUC). Clinical utility of the BDS was tested in the hold-out test set using decision curve analysis. Statistics included nonparametric DeLong test for AUCs and Fisher-Yates test for remaining performance metrics., Results: A total of 1604 patients aged 67 (interquartile range, 61-73) with 48% GG ≥ 2 prevalence (774/1604) were evaluated. By employing DLS-based prostate and TZ volumes (DICE coefficients of 0.89 (95% confidence interval, 0.80-0.97) and 0.84 (0.70-0.99)), GG ≥ 2 detection using PSAD was inferior to sPSAD (AUC, 0.71 (0.68-0.74)/0.73 (0.70-0.76); p < 0.001). Combining PI-RADS with sPSAD, GG ≥ 2 detection specificity doubled from 18% (10-20%) to 43% (30-44%; p < 0.001) with similar sensitivity (93% (89-96%)/97% (94-99%); p = 0.052), when biopsies were taken in PI-RADS 4-5 and 3 only if sPSAD was ≥ 0.42 ng/mL/cc as compared to all PI-RADS 3-5 cases. Additionally, using the sPSAD-based BDS, false positives were reduced by 25% (123 (104-142)/165 (146-185); p < 0.001)., Conclusion: Using sPSAD to guide biopsy decisions in PI-RADS 3 lesions can reduce false positives at MRI while maintaining high sensitivity for GG ≥ 2 cancers., Clinical Relevance Statement: Transition zone-specific prostate-specific antigen density can improve the accuracy of prostate cancer detection compared to MRI assessments alone, by lowering false-positive cases without significantly missing men with ISUP GG ≥ 2 cancers., Key Points: • Prostate biopsy decision strategies using PI-RADS at MRI are limited by a substantial proportion of false positives, not yielding grade group ≥ 2 prostate cancer. • PI-RADS combined with transition zone (TZ)-specific prostate-specific antigen density (PSAD) decreased the number of unproductive biopsies by 25% compared to PI-RADS only. • TZ-specific PSAD also improved the specificity of MRI-directed biopsies by 9% compared to the whole gland PSAD, while showing identical sensitivity., (© 2024. The Author(s).)

MRI retains its ability to reduce the harm of prostate biopsies by decreasing biopsy rates and the detection of indolent cancers in population-based screening studies aiming to find clinically significant prostate cancers. Limitations of low positive predictive values and high reader variability in diagnostic performance require optimisations in patient selection, imaging protocols, interpretation standards, diagnostic thresholds, and biopsy methods. Improvements in diagnostic accuracy could come about through emerging technologies like risk calculators and polygenic risk scores to select men for MRI. Furthermore, artificial intelligence and workflow optimisations focused on streamlining the diagnostic pathway, quality control, and assurance measures will improve MRI variability. CLINICAL RELEVANCE STATEMENT: MRI significantly reduces harm in prostate cancer screening, lowering unnecessary biopsies and minimizing the overdiagnosis of indolent cancers. MRI maintains the effective detection of high-grade cancers, thus improving the overall benefit-to-harm ratio in population-based screenings with or without using serum prostate-specific antigen (PSA) for patient selection. KEY POINTS: • The use of MRI enables the harm reduction benefits seen in individual early cancer detection to be extended to both risk-stratified and non-stratified prostate cancer screening populations. • MRI limitations include a low positive predictive value and imperfect reader variability, which require standardising interpretations, biopsy methods, and integration into a quality diagnostic pathway. • Current evidence is based on one-time point use of MRI in screening; MRI effectiveness in multiple rounds of screening is not well-documented., (© 2024. The Author(s), under exclusive licence to European Society of Radiology.)

Background and Objective: The Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) recommendations standardise the reporting of prostate magnetic resonance imaging (MRI) in patients on active surveillance (AS) for prostate cancer. An international consensus group recently updated these recommendations and identified the areas of uncertainty., Methods: A panel of 38 experts used the formal RAND/UCLA Appropriateness Method consensus methodology. Panellists scored 193 statements using a 1-9 agreement scale, where 9 means full agreement. A summary of agreement, uncertainty, or disagreement (derived from the group median score) and consensus (determined using the Interpercentile Range Adjusted for Symmetry method) was calculated for each statement and presented for discussion before individual rescoring., Key Findings and Limitations: Participants agreed that MRI scans must meet a minimum image quality standard (median 9) or be given a score of 'X' for insufficient quality. The current scan should be compared with both baseline and previous scans (median 9), with the PRECISE score being the maximum from any lesion (median 8). PRECISE 3 (stable MRI) was subdivided into 3-V (visible) and 3-NonV (nonvisible) disease (median 9). Prostate Imaging Reporting and Data System/Likert ≥3 lesions should be measured on T2-weighted imaging, using other sequences to aid in the identification (median 8), and whenever possible, reported pictorially (diagrams, screenshots, or contours; median 9). There was no consensus on how to measure tumour size. More research is needed to determine a significant size increase (median 9). PRECISE 5 was clarified as progression to stage ≥T3a (median 9)., Conclusions and Clinical Implications: The updated PRECISE recommendations reflect expert consensus opinion on minimal standards and reporting criteria for prostate MRI in AS., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Objectives: To compare the image quality of deep learning accelerated whole-body (WB) with conventional diffusion sequences., Methods: Fifty consecutive patients with bone marrow cancer underwent WB-MRI. Two experts compared axial b900 s/mm 2 and the corresponding maximum intensity projections (MIP) of deep resolve boost (DRB) accelerated diffusion-weighted imaging (DWI) sequences (time of acquisition: 6:42 min) against conventional sequences (time of acquisition: 14 min). Readers assessed paired images for noise, artefacts, signal fat suppression, and lesion conspicuity using Likert scales, also expressing their overall subjective preference. Signal-to-noise and contrast-to-noise ratios (SNR and CNR) and the apparent diffusion coefficient (ADC) values of normal tissues and cancer lesions were statistically compared., Results: Overall, radiologists preferred either axial DRB b900 and/or corresponding MIP images in almost 80% of the patients, particularly in patients with a high body-mass index (BMI > 25 kg/m 2 ). In qualitative assessments, axial DRB images were preferred (preferred/strongly preferred) in 56-100% of cases, whereas DRB MIP images were favoured in 52-96% of cases. DRB-SNR/CNR was higher in all normal tissues (p < 0.05). For cancer lesions, the DRB-SNR was higher (p < 0.001), but the CNR was not different. DRB-ADC values were significantly higher for the brain and psoas muscles, but not for cancer lesions (mean difference: + 53 µm 2 /s). Inter-class correlation coefficient analysis showed good to excellent agreement (95% CI 0.75-0.93)., Conclusion: DRB sequences produce higher-quality axial DWI, resulting in improved MIPs and significantly reduced acquisition times. However, differences in the ADC values of normal tissues need to be considered., Clinical Relevance Statement: Deep learning accelerated diffusion sequences produce high-quality axial images and MIP at reduced acquisition times. This advancement could enable the increased adoption of Whole Body-MRI for the evaluation of patients with bone marrow cancer., Key Points: Deep learning reconstruction enables a more than 50% reduction in acquisition time for WB diffusion sequences. DRB images were preferred by radiologists in almost 80% of cases due to fewer artefacts, improved background signal suppression, higher signal-to-noise ratio, and increased lesion conspicuity in patients with higher body mass index. Cancer lesion diffusivity from DRB images was not different from conventional sequences., Competing Interests: Compliance with ethical standards Guarantor The scientific guarantor of this publication is Prof. Anwar R. Padhani. Conflict of interest Andrea Ponsiglione holds the position of Junior Deputy Editor at European Radiology,  but he did not participate in the selection nor review processes. Thomas Benkert serves as Product Manager for MR Neuro Applications at Siemens Healthineers and has been involved in providing technical consultation. He had no access to patient data and was not involved in any process of the study methodology and analysis. Statistics and biometry One of the authors (A.M.P.) has significant statistical expertise. Informed consent As per the clinical routine, written informed consent from all patients for WB-MRI examination as they were clinically indicated. Ethical approval This was a prospective evaluation of a pre-commercial product as a new clinical technology introduction and so was approved by the local ethics committee as a service quality improvement audit activity. Methodology ProspectivePerformed at one institution, (© 2024. The Author(s), under exclusive licence to European Society of Radiology.)

Multiparametric MRI (mpMRI) of the prostate aids risk stratification of patients with elevated PSA levels. Although most clinically significant prostate cancers are detected by mpMRI, insignificant cancers are less evident. Thus, multiple international prostate cancer guidelines now endorse routine use of prostate MRI as a secondary screening test before prostate biopsy. Nonetheless, management of patients with negative mpMRI results (defined as PI-RADS category 1 or 2) remains unclear. This AJR Expert Panel Narrative Review summarizes the available literature on patients with an elevated screening PSA level and a negative prostate mpMRI result and provides guidance for these patients' management. Systematic biopsy should not be routinely performed after a negative mpMRI examination in patients at average risk but should be considered in patients at high risk. In patients who undergo PSA screening rather than systematic biopsy after negative mpMRI, clear triggers should be established for when to perform a repeat MRI examination. Patients with a negative MRI result followed by negative biopsy should follow their health care practitioners' preferred guidelines concerning subsequent PSA screening for the patient's risk level. Insufficient high-level data exist to support routine use of adjunctive serum or urine biomarkers, artificial intelligence, or PSMA PET to determine the need for prostate biopsy after a negative mpMRI examination.

Background: Artificial intelligence (AI) systems can potentially aid the diagnostic pathway of prostate cancer by alleviating the increasing workload, preventing overdiagnosis, and reducing the dependence on experienced radiologists. We aimed to investigate the performance of AI systems at detecting clinically significant prostate cancer on MRI in comparison with radiologists using the Prostate Imaging-Reporting and Data System version 2.1 (PI-RADS 2.1) and the standard of care in multidisciplinary routine practice at scale., Methods: In this international, paired, non-inferiority, confirmatory study, we trained and externally validated an AI system (developed within an international consortium) for detecting Gleason grade group 2 or greater cancers using a retrospective cohort of 10 207 MRI examinations from 9129 patients. Of these examinations, 9207 cases from three centres (11 sites) based in the Netherlands were used for training and tuning, and 1000 cases from four centres (12 sites) based in the Netherlands and Norway were used for testing. In parallel, we facilitated a multireader, multicase observer study with 62 radiologists (45 centres in 20 countries; median 7 [IQR 5-10] years of experience in reading prostate MRI) using PI-RADS (2.1) on 400 paired MRI examinations from the testing cohort. Primary endpoints were the sensitivity, specificity, and the area under the receiver operating characteristic curve (AUROC) of the AI system in comparison with that of all readers using PI-RADS (2.1) and in comparison with that of the historical radiology readings made during multidisciplinary routine practice (ie, the standard of care with the aid of patient history and peer consultation). Histopathology and at least 3 years (median 5 [IQR 4-6] years) of follow-up were used to establish the reference standard. The statistical analysis plan was prespecified with a primary hypothesis of non-inferiority (considering a margin of 0·05) and a secondary hypothesis of superiority towards the AI system, if non-inferiority was confirmed. This study was registered at ClinicalTrials.gov, NCT05489341., Findings: Of the 10 207 examinations included from Jan 1, 2012, through Dec 31, 2021, 2440 cases had histologically confirmed Gleason grade group 2 or greater prostate cancer. In the subset of 400 testing cases in which the AI system was compared with the radiologists participating in the reader study, the AI system showed a statistically superior and non-inferior AUROC of 0·91 (95% CI 0·87-0·94; p<0·0001), in comparison to the pool of 62 radiologists with an AUROC of 0·86 (0·83-0·89), with a lower boundary of the two-sided 95% Wald CI for the difference in AUROC of 0·02. At the mean PI-RADS 3 or greater operating point of all readers, the AI system detected 6·8% more cases with Gleason grade group 2 or greater cancers at the same specificity (57·7%, 95% CI 51·6-63·3), or 50·4% fewer false-positive results and 20·0% fewer cases with Gleason grade group 1 cancers at the same sensitivity (89·4%, 95% CI 85·3-92·9). In all 1000 testing cases where the AI system was compared with the radiology readings made during multidisciplinary practice, non-inferiority was not confirmed, as the AI system showed lower specificity (68·9% [95% CI 65·3-72·4] vs 69·0% [65·5-72·5]) at the same sensitivity (96·1%, 94·0-98·2) as the PI-RADS 3 or greater operating point. The lower boundary of the two-sided 95% Wald CI for the difference in specificity (-0·04) was greater than the non-inferiority margin (-0·05) and a p value below the significance threshold was reached (p<0·001)., Interpretation: An AI system was superior to radiologists using PI-RADS (2.1), on average, at detecting clinically significant prostate cancer and comparable to the standard of care. Such a system shows the potential to be a supportive tool within a primary diagnostic setting, with several associated benefits for patients and radiologists. Prospective validation is needed to test clinical applicability of this system., Funding: Health~Holland and EU Horizon 2020., Competing Interests: Declaration of interests NAO provides statistical consultation to Siemens Healthineers, Takeda, and Qure, and serves as a committee member of the Eastern Cooperative Oncology Group–American College of Radiology Imaging Network, the Tomosynthesis Mammographic Imaging Screening Trial, and the National Cancer Institute's Clinical Imaging Steering Committee (Bethesda, MD, USA). AB has been a consultant and advisor for Astellas and Bayer; board membership, officer, and trustee for Glactone Pharma, and LIDDS Pharma; has received lecture honoraria for Accord, Astellas, AstraZeneca, Bayer, Ipsen, Janssen, and Merck; has participated in trials run by Astellas, Ferring, and Janssen; and holds stock in Glactone Pharma, LIDDS Pharma, Noviga, and WntResearch. BvG holds stocks in and is a founder of Thirona. JKC has received research funding from GE Healthcare and Genentech and is the co-inventor of software that has been licensed to Siloam Vision. JKC has equity ownership in Siloam Vision. GS has been an advisory board member of Exact Imaging and Angiogenesis and has received lecture honorarium from Hitachi. OR has received funding for travel expenses from Philips Medical Systems. ARP has received research funding from Siemens Healthineers, holds stocks in Lucida Medical, and has received lecture honoraria for Siemens Healthineers and Bayer. HH has received research funding from Siemens Healthineers and Canon Medical Systems. GV has been a clinical advisory board member of AGFA Healthcare. VK has received lecture honoraria on prostate cancer diagnosis from the European Association of Urology and Singapore Urology Association and has received research funding from Prostate Cancer UK and the John Black Charitable Foundation. DB has received lecture honorarium from Bayer Vital and holds stocks in NVIDIA, Microsoft, and MSCI-World ETF. RvdB has been an advisory board member for Janssen; has received lecture honoraria from Amgen, Astellas, Ipsen, Janssen, and MSD; has received research support from Astellas and Janssen; and has participated in trials run by Janssen. All other authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)

BACKGROUND. PI-RADS incorporates rules by which ancillary sequence findings upgrade a dominant score to a higher final category. Evidence on the upgrading rules' impact on diagnostic pathways remains scarce. OBJECTIVE. The purpose of this article was to evaluate the clinical net benefit of the PI-RADS upgrading rules in MRI-directed diagnostic pathways. METHODS. This study was a retrospective analysis of a prospectively maintained clinical registry. The study included patients without known prostate cancer who underwent prostate MRI followed by prostate biopsy from January 2016 to May 2020. Clinically significant prostate cancer (csPCa) was defined as International Society of Urological Pathology (ISUP) grade group 2 and higher. csPCa detection was compared between dominant (i.e., no upgrade rule applied) and upgraded lesions. Decision-curve analysis was used to compare the net benefit, considering the trade-off of csPCa detection and biopsy avoidance, of MRI-directed pathways in scenarios considering and disregarding PI-RADS upgrading rules. These included a biopsy-all pathway, MRI-focused pathway (no biopsy for PI-RADS ≤ 2), and risk-based pathway (use of PSA density ≥ 0.15 ng/mL 2 to select patients with PI-RADS ≤ 3 for biopsy). RESULTS. The sample comprised 716 patients (mean age, 64.9 years; 93 with a PI-RADS ≤ 2 examination, 623 with total of 780 PI-RADS ≥ 3 lesions). Frequencies of csPCa were not significantly different between dominant and upgraded PI-RADS 3 transition zone lesions (20% vs 19%, respectively), dominant and upgraded PI-RADS 4 transition zone lesions (33% vs 26%), and dominant and upgraded PI-RADS 4 peripheral zone lesions (58% vs 45%) ( p > .05). In the biopsy-all, per-guideline MRI-focused, MRI-focused disregarding upgrading rules, per-guideline risk-based, and risk-based disregarding upgrading rules pathways, csPCa frequency was 53%, 52%, 51%, 52%, and 48% and biopsy avoidance was 0%, 13%, 16%, 19%, and 25%, respectively. Disregarding upgrading rules yielded 5.5 and 1.9 biopsies avoided per missed csPCa for MRI-focused and risk-based pathways, respectively. At probability thresholds for biopsy selection of 7.5-30.0%, net benefit was highest for the per-guideline risk-based pathway. CONCLUSION. Disregarding PI-RADS upgrading rules reduced net clinical bene fit of the risk-based MRI-directed diagnostic pathway when considering trade-offs between csPCa detection and biopsy avoidance. CLINICAL IMPACT. This study supports the application of PI-RADS upgrading rules to optimize biopsy selection, particularly in risk-based pathways.

Background and Objective: Magnetic resonance imaging (MRI) can detect recurrences after focal therapy for prostate cancer but there is no robust guidance regarding its use. Our objective was to produce consensus recommendations on MRI acquisition, interpretation, and reporting after focal therapy., Methods: A systematic review was performed in July 2022 to develop consensus statements. A two-round consensus exercise was then performed, with a consensus meeting in January 2023, during which 329 statements were scored by 23 panellists from Europe and North America spanning urology, radiology, and pathology with experience across eight focal therapy modalities. Using RAND Corporation/University of California-Los Angeles methodology, the Transatlantic Recommendations for Prostate Gland Evaluation with MRI after Focal Therapy (TARGET) were based on consensus for statements scored with agreement or disagreement., Key Findings and Limitations: In total, 73 studies were included in the review. All 20 studies (100%) reporting suspicious imaging features cited focal contrast enhancement as suspicious for cancer recurrence. Of 31 studies reporting MRI assessment criteria, the Prostate Imaging-Reporting and Data System (PI-RADS) score was the scheme used most often (20 studies; 65%), followed by a 5-point Likert score (six studies; 19%). For the consensus exercise, consensus for statements scored with agreement or disagreement increased from 227 of 295 statements (76.9%) in round one to 270 of 329 statements (82.1%) in round two. Key recommendations include performing routine MRI at 12 mo using a multiparametric protocol compliant with PI-RADS version 2.1 standards. PI-RADS category scores for assessing recurrence within the ablation zone should be avoided. An alternative 5-point scoring system is presented that includes a major dynamic contrast enhancement (DCE) sequence and joint minor diffusion-weighted imaging and T2-weighted sequences. For the DCE sequence, focal nodular strong early enhancement was the most suspicious imaging finding. A structured minimum reporting data set and minimum reporting standards for studies detailing MRI data after focal therapy are presented., Conclusions and Clinical Implications: The TARGET consensus recommendations may improve MRI acquisition, interpretation, and reporting after focal therapy for prostate cancer and provide minimum standards for study reporting., Patient Summary: Magnetic resonance imaging (MRI) scans can detect recurrent of prostate cancer after focal treatments, but there is a lack of guidance on MRI use for this purpose. We report new expert recommendations that may improve practice., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background and Objective: Accurate magnetic resonance imaging (MRI) reporting is essential for transperineal prostate biopsy (TPB) planning. Although approved computer-aided diagnosis (CAD) tools may assist urologists in this task, evidence of improved clinically significant prostate cancer (csPCa) detection is lacking. Therefore, we aimed to document the diagnostic utility of using Prostate Imaging Reporting and Data System (PI-RADS) and CAD for biopsy planning compared with PI-RADS alone., Methods: A total of 262 consecutive men scheduled for TPB at our referral centre were analysed. Reported PI-RADS lesions and an US Food and Drug Administration-cleared CAD tool were used for TPB planning. PI-RADS and CAD lesions were targeted on TPB, while four (interquartile range: 2-5) systematic biopsies were taken. The outcomes were the (1) proportion of csPCa (grade group ≥2) and (2) number of targeted lesions and false-positive rate. Performance was tested using free-response receiver operating characteristic curves and the exact Fisher-Yates test., Key Findings and Limitations: Overall, csPCa was detected in 56% (146/262) of men, with sensitivity of 92% and 97% (p = 0.007) for PI-RADS- and CAD-directed TPB, respectively. In 4% (10/262), csPCa was detected solely by CAD-directed biopsies; in 8% (22/262), additional csPCa lesions were detected. However, the number of targeted lesions increased by 54% (518 vs 336) and the false-positive rate doubled (0.66 vs 1.39; p = 0.009). Limitations include biopsies only for men at clinical/radiological suspicion and no multidisciplinary review of MRI before biopsy., Conclusions and Clinical Implications: The tested CAD tool for TPB planning improves csPCa detection at the cost of an increased number of lesions sampled and false positives. This may enable more personalised biopsy planning depending on urological and patient preferences., Patient Summary: The computer-aided diagnosis tool tested for transperineal prostate biopsy planning improves the detection of clinically significant prostate cancer at the cost of an increased number of lesions sampled and false positives. This may enable more personalised biopsy planning depending on urological and patient preferences., (Copyright © 2024 European Association of Urology. Published by Elsevier B.V. All rights reserved.)

Radiation therapy is fundamental in the treatment of cancer. Imaging has always played a central role in radiation oncology. Integrating imaging technology into irradiation devices has increased the precision and accuracy of dose delivery and decreased the toxic effects of the treatment. Although CT has become the standard imaging modality in radiation therapy, the development of recently introduced next-generation imaging techniques has improved diagnostic and therapeutic decision making in radiation oncology. Functional and molecular imaging techniques, as well as other advanced imaging modalities such as SPECT, yield information about the anatomic and biologic characteristics of tumors for the radiation therapy workflow. In clinical practice, they can be useful for characterizing tumor phenotypes, delineating volumes, planning treatment, determining patients' prognoses, predicting toxic effects, assessing responses to therapy, and detecting tumor relapse. Next-generation imaging can enable personalization of radiation therapy based on a greater understanding of tumor biologic factors. It can be used to map tumor characteristics, such as metabolic pathways, vascularity, cellular proliferation, and hypoxia, that are known to define tumor phenotype. It can also be used to consider tumor heterogeneity by highlighting areas at risk for radiation resistance for focused biologic dose escalation, which can impact the radiation planning process and patient outcomes. The authors review the possible contributions of next-generation imaging to the treatment of patients undergoing radiation therapy. In addition, the possible roles of radio(geno)mics in radiation therapy, the limitations of these techniques, and hurdles in introducing them into clinical practice are discussed. © RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

Context: The clinical introduction of next-generation imaging methods and molecular biomarkers ("radiogenomics") has revolutionized the field of prostate cancer (PCa). While the clinical validity of these tests has thoroughly been vetted, their clinical utility remains a matter of investigation., Objective: To systematically review the evidence to date on the impact of positron emission tomography (PET) imaging and tissue-based prognostic biomarkers, including Decipher, Prolaris, and Oncotype Dx, on the risk stratification, treatment choice, and oncological outcomes of men with newly diagnosed PCa or those with biochemical failure (BCF)., Evidence Acquisition: We performed a quantitative systematic review of the literature using the MEDLINE, EMBASE, and Web of Science databases (2010-2022) following the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement guidelines. The validated Quality Assessment of Diagnostic Accuracy Studies 2 scoring system was used to assess the risk of bias., Evidence Synthesis: A total of 148 studies (130 on PET and 18 on biomarkers) were included. In the primary PCa setting, prostate-specific membrane antigen (PSMA) PET imaging was not useful in improving T staging, moderately useful in improving N staging, but consistently useful in improving M staging in patients with National Comprehensive Cancer Network (NCCN) unfavorable intermediate- to very-high-risk PCa. Its use led to a management change in 20-30% of patients. However, the effect of these treatment changes on survival outcomes was not clear. Similarly, biomarkers in the pretherapy primary PCa setting increased and decreased the risk, respectively, in 7-30% and 32-36% of NCCN low-risk and 31-65% and 4-15% of NCCN favorable intermediate-risk patients being considered for active surveillance. A change in management was noted in up to 65% of patients, with the change being in line with the molecular risk-based reclassification, but again, the impact of these changes on survival outcomes remained unclear. Notably, in the postsurgical primary PCa setting, biomarker-guided adjuvant radiation therapy (RT) was associated with improved oncological control: Δ↓ 2-yr BCF by 22% (level 2b). In the BCF setting, the data were more mature. PSMA PET was consistently useful in improving disease localization-Δ↑ detection for T, N, and M staging was 13-32%, 19-58%, and 9-29%, respectively. Between 29% and 73% of patients had a change in management. Most importantly, these management changes were associated with improved survival outcomes in three trials: Δ↑ 4-yr disease-free survival by 24.3%, Δ↑ 6-mo metastasis-free survival (MFS) by 46.7%, and Δ↑ androgen deprivation therapy-free survival by 8 mo in patients who received PET-concordant RT (level 1b-2b). Biomarker testing in these patients also appeared to be helpful in risk stratifying and guiding the use of early salvage RT (sRT) and concomitant hormonal therapy. Patients with high-genomic-risk scores benefitted from treatment intensification: Δ↑ 8-yr MFS by 20% with the use of early sRT and Δ↑ 12-yr MFS by 11.2% with the use of hormonal therapy alongside early sRT, while low-genomic-risk score patients did equally well with initial conservative management (level 3)., Conclusions: Both PSMA PET imaging and tumor molecular profiling provide actionable information in the management of men with primary PCa and those with BCF. Emerging data suggest that radiogenomics-guided treatments translate into direct survival benefits for patients, however, additional prospective data are awaited., Patient Summary: In this review, we evaluated the utility of prostate-specific membrane antigen positron emission tomography and tumor molecular profiling in guiding the care of men with prostate cancer (PCa). We found that these tests augmented risk stratification, altered management, and improved cancer control in men with a new diagnosis of PCa or for those experiencing a relapse., (Copyright © 2023 European Association of Urology. All rights reserved.)

Objective: To compare biopsy recommendation rates and accuracy of the Prostate Imaging-Reporting and Data System, version 2 (PI-RADSv2) with the Likert scale for detection of clinically significant and insignificant prostate cancer in men screened within the Imperial Prostate 1 Prostate Cancer Screening Trial Using Imaging (IP1-PROSTAGRAM)., Patients and Methods: Men aged 50-69 years were screened with Prostagram MRI. Scans were prospectively reported using both PI-RADSv2 (excluding dynamic contrast-enhanced sequence score) and 5-point Likert scores by expert uro-radiologists. Systematic and targeted transperineal biopsy was recommended if the scan was scored ≥ 3, based on either reporting system. The proportion of patients recommended for biopsy and detection rates for Grade Groups (GGs) 1 and ≥ 2 were compared. Receiver operating characteristic (ROC) analysis was performed to compare performance., Results: A total of 406 men underwent Prostagram MRI. The median (interquartile range) age and prostate-specific antigen level were 57 (53-61) years and 0.91 (0.56-1.74) ng/mL, respectively. At MRI score ≥ 3, more patients were recommended for biopsy based on Likert criteria (94/406; 23%, 95% confidence interval [CI] 19.2%-27.6%) compared to PI-RADSv2 (72/406; 18%, 95% CI 14.2%-21.9%; P = 0.03). For MRI scores ≥ 4, PI-RADSv2 and Likert scales led to 43/406 (11%, 95% CI 7.9%-14.1%) and 35/406 (9%, 95% CI 6.2%-11.9%) men recommended for biopsy (P = 0.40). For GG ≥ 2 detection, PIRADSv2 and Likert detected 22% (95% CI 11.4%-30.8%, 14/72) and 16% (95% CI 9.5%-25.3%, 15/94), respectively (P = 0.56). For GG1 cancers detection these were 11% (95% CI 4.3%-19.6%, seven of 72) vs 11% (95% CI 4.7%-17.8%, nine of 94; P = 1.00). The accuracy of PI-RADSv2 and Likert scale was similar (area under the ROC curve 0.64 vs 0.65, P = 0.95)., Conclusions: In reporting non-contrast-enhanced Prostagram MRI in a screening population, the PI-RADSv2 and Likert scoring systems were equally accurate; however, Likert scale use led to more men undergoing biopsy without a subsequent increase in significant cancer detection rates. To improve reporting of Prostagram MRI, either the PI-RADSv2 or a modified Likert scale or a standalone scoring system should be developed., (© 2023 The Authors. BJU International published by John Wiley & Sons Ltd on behalf of BJU International.)

Background: Radium-223 is a bone-seeking, ɑ-emitting radionuclide used to treat men with bone metastases from castration-resistant prostate cancer. Sclerotic bone lesions cannot be evaluated using Response Evaluation Criteria in Solid Tumors. Therefore, imaging response biomarkers are needed., Methods: We conducted a phase 2 randomized trial to assess disease response to radium-223. Men with metastatic castration-resistant prostate cancer and bone metastases were randomly allocated to 55 or 88 kBq/kg radium-223 every 4 weeks for 6 cycles. Whole-body diffusion-weighted magnetic resonance imaging (DWI) was performed at baseline, at cycles 2 and 4, and after treatment. The primary endpoint was defined as a 30% increase in global median apparent diffusion coefficient., Results: Disease response on DWI was seen in 14 of 36 evaluable patients (39%; 95% confidence interval = 23% to 56%), with marked interpatient and intrapatient heterogeneity of response. There was an association between prostate-specific antigen response and MRI response (odds ratio = 18.5, 95% confidence interval = 1.32 to 258, P = .013). Mean administered activity of radium-223 per cycle was not associated with global MRI response (P = .216) but was associated with DWI response using a 5-target-lesion evaluation (P = .007). In 26 of 36 (72%) patients, new bone metastases, not present at baseline, were seen on DWI scans during radium-223 treatment., Conclusions: DWI is useful for assessment of disease response in bone. Response to radium-223 is heterogeneous, both between patients and between different metastases in the same patient. New bone metastases appear during radium-223 treatment.The REASURE trial is registered under ISRCTN17805587., (© The Author(s) 2023. Published by Oxford University Press.)

Objective: To comprehensively review the literature on the integration of MRI as a diagnostic tool in prostate cancer screening and offer practical recommendations for optimising its use., Methods: Existing research studies, clinical guidelines and expert opinions were reviewed to support the optimisation standards for MRI use in screening. Consolidated screening principles were used to make appropriate recommendations regarding the integration of MRI into the diagnostic pathway., Results: To strike a balance between the potential benefits of early detection on mortality and minimising the harm of over-diagnosing indolent cancers, it is necessary to have a clear understanding of the context of MRI use. The key to optimisation is patient selections and MRI-targeted biopsies. For men at higher-than-average risk, it is essential to use screening-specific MRI protocols and establish accuracy levels and interpretation criteria. Optimisation of readings by the automation of data acquisition, image quality monitoring, post-processing, radiologist certification and deep-learning computer-aided software is needed. The optimal utilisation of MRI involves its integration into a multistep diagnostic pathway, supported by a quality-assured and cost-effective infrastructure that ensures community-wide access to imaging., Conclusion: MRI in the prostate cancer screening pathway can bring substantial diagnostic benefits. By carefully considering its advantages, limitations and safety concerns and integrating it into a multistep diagnostic pathway, clinicians can improve outcomes while minimising harm to screening participants., Clinical Relevance Statement: The manuscript discusses the role of MRI in prostate cancer screening, highlighting its potential to improve accuracy and reduce overdiagnosis. It emphasises the importance of optimising protocols and integrating MRI into a multistep diagnostic pathway for successfully delivering screening benefits., Key Points: • Population screening for prostate cancer is a new indication for prostate MRI that allows the detection of high-risk cancers while reducing the need for biopsies and associated harm. • To optimise prostate cancer screening using MRI, it is essential to redefine MRI protocols; establish accuracy levels, reliability and interpretation criteria; and optimise reading (including post-processing, image quality, radiologist certification, and deep-learning computer-aided software). • The optimal utilisation of MRI for prostate cancer screening would involve its integration into a multistep diagnostic pathway, supported by a quality-assured and cost-effective infrastructure that ensures community-wide access to imaging., (© 2023. The Author(s), under exclusive licence to European Society of Radiology.)

Background: The IP1-PROSTAGRAM study showed that a short, non-contrast MRI detected more significant cancers with similar rates of biopsy compared to PSA. Herein, we compare the expected and perceived burden of PSA, MRI and ultrasound as screening tests., Methods: IP1-PROSTAGRAM was a prospective, population-based, paired screening study of 408 men conducted at seven UK primary care practices and two imaging centres. The screening tests were serum PSA, non-contrast MRI and ultrasound. If any test was screen-positive, a prostate biopsy was performed. Participants completed an Expected Burden Questionnaire (EBQ) and Perceived Burden Questionnaire (PBQ) before and after each screening test., Results: The overall level of burden for MRI and PSA was minimal. Few men reported high levels of anxiety, burden, embarrassment or pain following either MRI or PSA. Participants indicated an overall preference for MRI after completing all screening tests. Of 408 participants, 194 (47.5%) had no preference, 106 (26.0%) preferred MRI and 79 (19.4%) preferred PSA. This indicates that prior to screening, participants preferred MRI compared to PSA (+6.6%, 95% CI 4.4-8.4, p = 0.02) and after completing screening, the preference for MRI was higher (+21.1%, 95% CI 14.9-27.1, p < 0.001). The proportion of participants who strongly agreed with repeating the test was 50.5% for ultrasound, 65% for MRI and 68% for PSA. A larger proportion of participants found ultrasound anxiety-inducing, burdensome, embarrassing and painful compared to both MRI and PSA., Conclusions: Prostagram MRI and PSA are both acceptable as screening tests among men aged 50-69 years. Both tests were associated with minimal amounts of anxiety, burden, embarrassment and pain. The majority of participants preferred MRI over PSA and ultrasound., Registration: This study was registered on clinicaltrials.gov at https://clinicaltrials.gov/ct2/show/NCT03702439 ., (© 2023. The Author(s).)

Background: The use of prostate-specific antigen (PSA) testing to screen for prostate cancer has been fraught with under- and overdiagnosis. Short, noncontrast magnetic resonance imaging (MRI) might detect more grade group ≥2 cancers with similar rates of biopsy., Objective: To evaluate strategies that combined PSA and MRI to select men based in the community for a prostate biopsy., Design, Setting, and Participants: IP1-PROSTAGRAM was a prospective, population-based, paired cohort study of 408 men aged 50-69 yr conducted at seven UK primary care practice and two imaging centres (from October 10, 2018 to May 15, 2019)., Intervention: All participants underwent screening with a PSA test, MRI (T2-weighted and diffusion), and transrectal ultrasound (b-mode and elastography). If any test was screen positive, a systematic 12-core biopsy was performed. Additional image-fusion targeted biopsies were taken if the MRI or ultrasound was positive., Outcome Measurements and Statistical Analysis: We conducted an analysis, set out in the statistical plan a priori, comparing 13 different pathways including PSA-alone, MRI-alone, and a range of PSA thresholds and MRI scores. The performance of each pathway was evaluated focusing on the trade-offs between biopsy referral rates and detection of grade group ≥2 cancers. A targeted biopsy was performed only where the PROSTAGRAM MRI showed a lesion score of 3, 4, or 5., Results and Limitations: The standard PSA pathway (PSA ≥3 ng/ml + systematic biopsy) would lead to 10% of men being referred for a biopsy and a 1.0% detection rate of grade group ≥2 cancers. Pathways that relied on MRI alone set at a threshold score of 3 for a biopsy led to higher biopsy rates, but with benefit of high cancer detection rates. The pathway that combined an initial low PSA threshold (≥1.0 ng/ml) and MRI score ≥4 accurately identified a high rate of grade group ≥2 cancers (2.5%, 95% confidence interval 1.3-4.6) while recommending fewer patients for a biopsy (7.1%, 95% confidence interval 4.9-10.2). The results are pertinent to only one screening round, the impact of repeat screening rounds is not evaluated, and the required MRI capacity is currently lacking., Conclusions: Our results highlight the trade-off that exists between reducing excessive numbers of biopsies and maintaining grade group ≥2 cancer detection rates. A pathway that combines PSA ≥1 ng/ml and MRI score ≥4 maintains the detection of grade group ≥2 cancers while recommending fewer men for biopsies and would be the preferred strategy to evaluate in future studies at the first screening round., Patient Summary: The IP1-PROSTAGRAM study shows that PROSTAGRAM magnetic resonance imaging in men with a prostate-specific antigen level of ≥1.0 ng/ml could be a promising pathway to evaluate in future screening trials., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Innovations in imaging and molecular characterisation together with novel treatment options have improved outcomes in advanced prostate cancer. However, we still lack high-level evidence in many areas relevant to making management decisions in daily clinical practise. The 2022 Advanced Prostate Cancer Consensus Conference (APCCC 2022) addressed some questions in these areas to supplement guidelines that mostly are based on level 1 evidence., Objective: To present the voting results of the APCCC 2022., Design, Setting, and Participants: The experts voted on controversial questions where high-level evidence is mostly lacking: locally advanced prostate cancer; biochemical recurrence after local treatment; metastatic hormone-sensitive, non-metastatic, and metastatic castration-resistant prostate cancer; oligometastatic prostate cancer; and managing side effects of hormonal therapy. A panel of 105 international prostate cancer experts voted on the consensus questions., Outcome Measurements and Statistical Analysis: The panel voted on 198 pre-defined questions, which were developed by 117 voting and non-voting panel members prior to the conference following a modified Delphi process. A total of 116 questions on metastatic and/or castration-resistant prostate cancer are discussed in this manuscript. In 2022, the voting was done by a web-based survey because of COVID-19 restrictions., Results and Limitations: The voting reflects the expert opinion of these panellists and did not incorporate a standard literature review or formal meta-analysis. The answer options for the consensus questions received varying degrees of support from panellists, as reflected in this article and the detailed voting results are reported in the supplementary material. We report here on topics in metastatic, hormone-sensitive prostate cancer (mHSPC), non-metastatic, castration-resistant prostate cancer (nmCRPC), metastatic castration-resistant prostate cancer (mCRPC), and oligometastatic and oligoprogressive prostate cancer., Conclusions: These voting results in four specific areas from a panel of experts in advanced prostate cancer can help clinicians and patients navigate controversial areas of management for which high-level evidence is scant or conflicting and can help research funders and policy makers identify information gaps and consider what areas to explore further. However, diagnostic and treatment decisions always have to be individualised based on patient characteristics, including the extent and location of disease, prior treatment(s), co-morbidities, patient preferences, and treatment recommendations and should also incorporate current and emerging clinical evidence and logistic and economic factors. Enrolment in clinical trials is strongly encouraged. Importantly, APCCC 2022 once again identified important gaps where there is non-consensus and that merit evaluation in specifically designed trials., Patient Summary: The Advanced Prostate Cancer Consensus Conference (APCCC) provides a forum to discuss and debate current diagnostic and treatment options for patients with advanced prostate cancer. The conference aims to share the knowledge of international experts in prostate cancer with healthcare providers worldwide. At each APCCC, an expert panel votes on pre-defined questions that target the most clinically relevant areas of advanced prostate cancer treatment for which there are gaps in knowledge. The results of the voting provide a practical guide to help clinicians discuss therapeutic options with patients and their relatives as part of shared and multidisciplinary decision-making. This report focuses on the advanced setting, covering metastatic hormone-sensitive prostate cancer and both non-metastatic and metastatic castration-resistant prostate cancer., Twitter Summary: Report of the results of APCCC 2022 for the following topics: mHSPC, nmCRPC, mCRPC, and oligometastatic prostate cancer., Take-Home Message: At APCCC 2022, clinically important questions in the management of advanced prostate cancer management were identified and discussed, and experts voted on pre-defined consensus questions. The report of the results for metastatic and/or castration-resistant prostate cancer is summarised here., Competing Interests: Conflict of interest statement The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Aurelis Omlin: Advisory role (compensated, institutional): Astra Zeneca, Astellas, Bayer, Janssen, Molecular Partners, MSD, Pfizer, Roche, Sanofi Aventis. Research support (institutional): TEVA, Janssen. Travel support: Astellas, Bayer, Janssen, Sanofi Aventis. Speakers Bureau (compensated, institutional): Bayer, Astellas, Janssen. Fizazi Karim: Participation to advisory boards or talks for: Amgen, Astellas, Astrazeneca, Bayer, Clovis, Janssen, MSD, Novartis, Pfizer, Sanofi. Honoraria are provided to Gustave Roussy, my institution. Participation to advisory boards with personal honorarium for: CureVac, Orion. Bossi Alberto: Honoraria: Astellas, Ipsen, Janssen, Myovant. Consulting or advisory role: Astellas, Ipsen, Janssen, Myovant. Speakers’ bureau: Astellas, Ipsen, Elketa. Research funding: Astellas, Ipsen, Myovant. Travel, accommodations, expenses: Janssen. Tombal Bertrand: Advisor for Astellas, Amgen, Bayer, Curium, Ferring, Myovant, Janssens, MSD, Novartis (AAA), Pfizer, Sanofi. Gillessen Silke: SG received personal honoraria for participation in advisory boards for Sanofi, Orion, Roche, Amgen, MSD; other honoraria from RSI (Televisione Svizzera Italiana); invited speaker for ESMO, Swiss group for Clinical Cancer Research (SAKK), Swiss Academy of Multidisciplinary oncology (SAMO), Orikata academy research group, China Anti-Cancer Association Genitourinary Oncology Committee (CACA-GU); Speaker’s bureau for Janssen Cilag; travel grant from ProteoMEdiX; institutional honoraria for advisory boards for Bayer, Janssen Cilag, Roche, AAA International including Indipendent Data Monitoring Committee and IDMC and Steering Committee member for Amgen, Menarini Silicon Biosystems, Astellas Pharma, Tolero Pharmaceutcials, MSD, Pfizer, Telixpharma, BMS and Orion; patent royalties and other intellectual property for a research method for biomarker WO2009138392. Ian Davis: Research Funding: Company: Astellas Pharma, Recipient: Your Institution; Company: Pfizer, Recipient: Your Institution; Company: Roche/Genentech, Recipient: Your Institution; Company: MSD Oncology, Recipient: Your Institution; Company: AstraZeneca, Recipient: Your Institution; Company: Janssen Oncology, Recipient: Your Institution; Company: Eisai, Recipient: Your Institution; Company: Bayer, Recipient: Your Institution; Company: Amgen, Recipient: Your Institution; Company: Bristol-Myers Squibb, Recipient: Your Institution; Company: Movember Foundation, Recipient: Your Institution; Company: Exelixis, Recipient: Your Institution; Company: Ipsen, Recipient: Your Institution; Company: Medivation, Recipient: Your Institution; Company: Seagen, Recipient: Your Institution. Patents, Royalties, Other Intellectual Property: Please describe: International Patent Application No: PCT /US2004/032147 (NY-ESO-1) through Ludwig Institute for Cancer Research; Recipient: You. Christopher Sweeney: Receipt of grants/research supports: Astellas, Bayer, Janssen, Pfizer, Sanofi, Dendreon; Receipt of honoraria or consultation fees: Astellas, Bayer, Janssen, Pfizer, Sanofi, Lilly, Genentech. Eric J. Small: Receipt of honoraria or consultation fees: Jannsen, Johnson & Johnson; Participation in a company sponsored speaker’s bureau: Jannsen, Fortis, Teon, Ulgragenyx, Fortis, Harpoon Johann de Bono: Receipt of grants/research supports: Professor De Bono is an employee of The Institute of Cancer Research, which has received funding or other support for his research work from Astellas, Astra Zeneca, Bayer, Cellcentric, Daiichi, Genentech Roche, Genmab, GlaxoSmithKline, Harpoon, Janssen, Merck Serono, Merck Sharp & Dohme, Orion Pharma, Pfizer, Sanofi Aventis, Sierra Oncology, Taiho, Vertex Pharmaceuticals, and which has a commercial interest in abiraterone, PARP inhibition in DNA repair defective cancers and PI3K/AKT pathway inhibitors (no personal income); Receipt of honoraria or consultation fees: Professor De Bono has served on advisory boards and received fees from Amgen, Astellas, Astra Zeneca, Bayer, Bioxcel Therapeutics, Boehringer Ingelheim, Cellcentric, Daiichi, Eisai, Genentech Roche, Genmab, GlaxoSmithKline, Harpoon, Janssen, Menarini Silicon. Biosystems, Merck Serono, Merck Sharp & Dohme, Orion Pharma, Pfizer, Qiagen, Sanofi Aventis, Sierra Oncology, Taiho, Terumo, Vertex Pharmaceuticals; Participation in a company sponsored speaker’s bureau: AstraZeneca, MSD. Matthew Smith: Receipt of grants/research supports: Clinical trial funding to my institution from: Amgen, Bayer, ESSA, Janssen, ORIC, Pfizer; Receipt of honoraria or consultation fees: Amgen, Astellas, Astrazeneca, Bayer, Janssen, ORIC, Pfizer. Neal Shore: Receipt of honoraria or consultation fees: Abbvie, Amgen, Astellas, Astrazeneca, Bayer, BMS, Boston Scientific, Clovis Oncology, Cold Genesys, Dendreon, Exact Imaging, Exact Sciences, FerGene, Foundation Medicine, Genesis Care, Invitae, Janssen, MDxhealth, Merck, Myvovant, Myriad, Nymox, Pacific Edge, Pfizer, Phosphorous, Propella, Sanofi, Genzyme, Sesen Bio, Tolmar, Urogen; Partecipation in a company sponsored speaker's bureau: Astellas, Astrazeneca, Bayer, Clovis Oncology, Foundation Medicina, Janssen, Merck, Pfizer, Guardant Health. Nicholas James: Receipt of grants/research supports: • Funding for STAMPEDE trial – Coordinating PI – financial interest, Institutional. Name of commercial company: Astellas. • Funding for RADIO trial bladder cancer – Coordinating. PI – financial interest, Institutional. Name of commercial company: AstraZeneca. • Funding for STAMPEDE trial – Coordinating PI – No. financial interest, Institutional. Name of commercial company: Janssen; Receipt of honoraria or consultation fees: • Advisory Board – Advice around PARP inhibitors, Personal,<€5000. Name of commercial company: AstraZeneca dvisory Board – Prostate cancer therapies, Personal,<€5000. Name of commercial company: Clovis. Expert Testimony – Assisted with submissions. regarding licensing for abiraterone, Institutional>€100,001. Name of commercial company: Janssen. Advisory Board – Prostate cancer therapies, Personal, €5001–€10,000. Name of commercial company: Janssen. Advisory Board – Bladder cancer therapy, Personal,<€5000. Name of commercial company: Merck. Advisory Board – Prostate cancer therapies, Personal,<€5000. Name of commercial company: Novartis Expert Testimony – Providing STAMPEDE trial data to facilitate licence extensions internationally for docetaxel, Institutional,>€100,001. Name of commercial company: Sanofi. Advisory Board - Docetaxel, Personal,<€5000. Name of commercial company: Sanofi. Participation in a company sponsored speaker’s bureau: Bayer, Novartis. Nicolas MOTTET: Receipt of grants/research supports: Astellas, Sanofi Pasteur, Pierre Fabre; Receipt of honoraria or consultation fees: Astellas, Jansen, BMS, Bayer, IPSEN, Ferring, Sanofi, Steba, Astra Zeneca, Carrik, Arquer. diagnostics, GE, Takeda. Thomas ZILLI. AFFILIATION: Geneva University Hospital, Geneva, Switzerland. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports: Varian Medical Systems International AG; Debiopharm. Receipt of honoraria or consultation fees: Janssen, Astellas, Debiopharm, Ferring, Varian Medical Systems International AG. Participation in a company sponsored speaker’s bureau: Janssen, Astellas, Debiopharm. Stock shareholder: Spouse/partner: Other support (please specify): Signature: Date: Geneva 07.02.2022. Christopher Logothetis. AFFILIATION: MD Anderson Cancer Center. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports: Janssen, ORIC Pharmaceuticals, Novartis, Aragon Pharmaceuticals. Receipt of honoraria or consultation fees: Merck, Sharp & Dohme, Bayer, Amgen. Participation in a company sponsored speakers bureau: None. Stock shareholder: None. Spouse/partner: None. Other support (please specify): None. Signature: Date: February 7, 2022. William Oh. AFFILIATION: Chief Medical Officer at Sema4 and Clinical Professor of Medicine, Div. of Hematology/Medical Oncology at Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports: Receipt of honoraria or consultation fees: GSK, Janssen, Merck, Pfizer. Participation in a company sponsored speakers bureau: Stock shareholder: Spouse/partner: Other support (please specify): Signature: Date: February 7, 2022. Himisha Beltran. AFFILIATION: Dana Farber Cancer Institute. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports: Janssen, AbbVie/Stemcentrx, Eli Lilly, Millennium Pharmaceuticals, Bristol Myers Squibb. Receipt of honoraria or consultation fees: Janssen, Astellas, Astra Zeneca, Merck, Pfizer, Foundation Medicine, Blue Earth Diagnostics, Amgen, Oncorus, LOXO. Participation in a company sponsored speaker’s bureau: NONE. Stock shareholder: NONE. Spouse/partner: NONE. Other support (please specify): Signature: Date: Feb 7, 2022. Pirkko-Liisa Kellokumpu-Lehtinen. AFFILIATION: Tampere University and Tampere University Hospital, Tampere, Finland. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports: Only directly to my hospital; Lilly, Merck and Finnish Cancer Society. Receipt of honoraria or consultation fees: BMS, Merck. Participation in a company sponsored speaker’s bureau: NONE. Stock shareholder: NONE. Spouse/partner: NONE. Other support (please specify):reimbursement of expenses to attend conference; Sanofi. Signature: Date: Feb 7, 2022. Prof. Mark A. Rubin, MD. AFFILIATION: University of Bern, Department for BioMedical Research (DBMR). Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports: Janssen, Roche, Novartis. Receipt of honoraria or consultation fees: NeoGenomics Labs. Participation in a company sponsored speaker’s bureau: Stock shareholder: Spouse/partner: Other support (please specify): Signature: Date: Feb 8, 2022. Prof. Dr. Thomas Steuber. AFFILIATION: Martini-Klinik, Prostate Cancer Center, University Hospital Hamburg-Eppendorf. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports: NONE. Receipt of honoraria or consultation fees: Astellas, Amgen, Bayer, Janssen, ProteoMedix, Sanofi, Merck, Astra Zeneca. Participation in a company sponsored speaker’s bureau: Stock shareholder: Spouse/partner: Other support (please specify): Signature: Date: Feb 8, 2022. Prof. Rob Bristow. AFFILIATION: University of Manchester. I have no potential conflict of interest to report. IGNACIO DURAN. AFFILIATION: HOSPITAL UNIVERSITARIO MARQUES DE VALDECILLA. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports: Roche and Astra-Zeneca. Receipt of honoraria or consultation fees: Bristol Myers Squibb, MSD, Ipsen, Roche- Genentech, Janssen, Astellas Pharma, EUSA Pharma, Bayer, Novartis. Participation in a company sponsored speaker’s bureau: Stock shareholder: Spouse/partner: Other support (please specify): Signature: Date: February 8th 2022. FERNANDO MALUF. AFFILIATION: ONCOLOGIST. I have no potential conflict of interest to report. Signature: Date: February 8th 2022. Hiroyoshi Suzuki. AFFILIATION: Department of Urology, Toho University Sakura Medical Center. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports: Takeda, AsahiKasei, Taiho, Ono, Chugai, Sanofi, Daiichi-Sankyo, Nihon, Nippon Shinyaku. Receipt of honoraria or consultation fees: Bayer, Janssen, AstraZeneca, Astellas, Chuga-Roche, MSD. Participation in a company sponsored speaker’s bureau:Takeda, Bayer, Janssen, AstraZeneca, Astellas, Sanofi. Stock shareholder: Spouse/partner: Other support (please specify): Signature: Date: February 8th 2022. Danny M. Rabah. AFFILIATION: King Saud University and king Faisal specialist hospital and research centre. I have no potential conflict of interest to report. Signature: Date: February 8th 2022. LEVENT TÜRKERİ. AFFILIATION: ACIBADEM M.A. AYDINLAR UNIVERSITY, ISTANBUL, TURKEY. I have no potential conflict of interest to report. Signature: Date: February 8th 2022. Mark Frydenberg. AFFILIATION: ACIBADEM M.A. AYDINLAR UNIVERSITY, ISTANBUL, TURKEY. I have no potential conflict of interest to report. Signature: Date: February 8th 2022. Anders Bjartell. AFFILIATION: Dept. Of Urology, Skane University Hospital Malmö, Sweden. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports: Ferring, Bayer, Astellas. Receipt of honoraria or consultation fees: Astellas, AstraZeneca, Bayer, Janssen, Merck, Recordati, Sandoz. Participation in a company sponsored speaker’s bureau:Astellas, Bayer, IPSEN, Janssen, Recordati, Sandoz. Stock shareholder: LIDDS Pharma, Glactone Pharma, WntResearch. Spouse/partner: NONE. Other support (please specify): Signature: Date: February 9th 2022. Dingwei Ye. AFFILIATION: Fudan University Shanghai Cancer Center. I have no potential conflict of interest to report. Signature: Date: February 9th 2022. Ros Eeles. AFFILIATION: ………………………………………. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports: GU-ASCO, The Royal Marsden NHS Foundation Trust, University of Chicago, ESMO, AstraZeneca UK Limited. Receipt of honoraria or consultation fees: Honorarium as speaker. Participation in a company sponsored speaker’s bureau: Stock shareholder: Spouse/partner: Other support (please specify): January 2016. Signature: Date: February 15th 2022. Inge van Oort. AFFILIATION: Urology, Radboudumc, Nijmegen, The Netherlands. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports: Astellas, Bayer, Janssen. Receipt of honoraria or consultation fees: Astellas, Bayer, MSD-Astra Zeneca, Janssen. Participation in a company sponsored speaker’s bureau: Bayer, Astellas. Stock shareholder: Spouse/partner: Other support (please specify): Signature: Date: February 22nd 2022. Ravindran Kanesvaran. AFFILIATION: Urology, Radboudumc, Nijmegen, The Netherlands. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports: Sanofi, Eisai. Receipt of honoraria or consultation fees: MSD, BMS, AstraZeneca, Amgen, Astellas, Johnson&Johnson, Novartis, Merck, Pfizer. Participation in a company sponsored speaker’s bureau:MSD, BMS, AstraZeneca, Amgen, Astellas, Johnson&Johnson, Novartis, Merck, Pfizer. Stock shareholder: Spouse/partner: Other support (please specify): Signature: Date: February 22nd 2022. Signature: Date: February 9th 2022. Nicola Fossati. AFFILIATION: Urology, Ente Ospedaliero Cantonale (EOC), Lugano, CH. I have no potential conflict of interest to report. Signature: Date: February 1st March 2022. Hiroji Uemura. AFFILIATION: Department of Urology and Renal Transplantation, Yokohama City University Medical Center. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports: none. Receipt of honoraria or consultation fees: Bayer, Janssen, Sanofi, Takeda, Astellas, AstraZeneca, Amgen, Dai-ichi Sankyo, Pfizer, MSD, Chugai. Participation in a company sponsored speaker’s bureau:none. Stock shareholder: none. Spouse/partner: none. Other support (please specify): none. Signature: Date: March 7th 2022. Lisa Horvath. AFFILIATION: Chris O′Brien Lifehouse. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports: Astellas. Receipt of honoraria or consultation fees: Astellas, Janssen, Bayer, Imagion Biosystems. Participation in a company sponsored speaker’s bureau:Astellas, Janssen, Bayer. Stock shareholder: Imagion Biosystems. Spouse/partner: Connected Medicine Solutions (Employee, stocks). Other support (please specify): none. Signature: Date: March 9th 2022. Robert Reiter. AFFILIATION: UCLA Urology. X I have no potential conflict of interest to report. Signature: Date: March 11th 2022. Daniel Castellano. AFFILIATION: MEDICAL ONCOLOGIST HEAD GU UNIT HOSPITAL UNIVERSITARIO 12 DE OCTUBRE. MADRID-UNIVERSIDAD COMPLUTENSE. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports: JANSSEN. Receipt of honoraria or consultation fees:ASTELLAS, ROCHE, MERCK, PFIZER, NOVARTIS, MSD, BMS, IPSEN, GILEAD, JANSSEN, BAYER. Participation in a company sponsored speaker’s bureau:none. Stock shareholder: none. Spouse/partner: none. Other support (please specify): none. Signature: 28th March 2022. Sandy Srinivas. AFFILIATION: Stanford University, CA. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:. Receipt of honoraria or consultation fees:BAYER, JANSSEN, MERCK, NOVARTIS. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 31ST March 2022. Matthew Sydes. AFFILIATION: MRC Clinical Trials Unit at UCL. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:ASTELLAS, CLOVIS ONCOLOGY, JANSSEN, NOVARTIS, PFIZER, SANOFI AVENTIS. Receipt of honoraria or consultation fees:ELI LILLY, JANSSEN. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 3Oth March 2022. Ekeke, Onyanunam Ngozi. AFFILIATION: DEPARTMENT OF SURGERY, UNIVERSITY OF PORT HARCOURT TEACHING HOSPITAL, PORT HARCOUT, NIGERIA. X I have no potential conflict of interest to report. Signature: Date: March 30 h 2022. Susan Halabi, PhD. AFFILIATION: Duke University. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:ASCO TAPUR, Astellas. Receipt of honoraria or consultation fees:Sanofi, Aveo Oncology. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 3Oth March 2022. Cora N. Sternberg, MD, FACP. AFFILIATION: Eeill Cornell Medicine, New York Presbyterian. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:. Receipt of honoraria or consultation fees:Astellas Pharma, Astrazeneca, Bayer, Genzyme, Gilead, Incyte, Medscape, Janssen, Bristol Myers Squibb, Merck, Msd, Pfizer, Roche, Impact Pharma, Sanofi-Genzyme, Urotoday, Cco Clinical, Nci. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 3Oth March 2022. Hirotsugu Uemura. AFFILIATION:. Kindai University Faculty of Medicine. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:AstraZeneca, Janssen, Takeda, Astellas, Sanofi, Taiho, Ono pharm, Kissei. Receipt of honoraria or consultation fees:Bayer, Sanofi, Janssen, MSD, Ono, BMS, Pfizer. Participation in a company sponsored speaker’s bureau:Bayer, Sanofi, Janssen, MSD, Ono, BMS, Pfizer. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 31st March 2022. Orazio Caffo. AFFILIATION: Santa Chiara Hospital – Trento (Italy). Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:none. Receipt of honoraria or consultation fees:AAA, Astella, Bayer, Janssen, MSD, Pfizer. Participation in a company sponsored speaker’s bureau:Astellas, Bayer, Janssen, Ipsen, MSD. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 31st March 2022. Valérie Fonteyne. AFFILIATION:Ghent University Hospital. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:Ipsen. Receipt of honoraria or consultation fees:Ipsen, Astellas, Janssen. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 31st March 2022. Muhammad Bulbul. AFFILIATION: American University of Beirut. X I have no potential conflict of interest to report. Signature: Date: March 31st 2022. Claire Vale. AFFILIATION: MRC Clinical Trials Unit at UCL. X I have no potential conflict of interest to report. Signature: Date: March 31st 2022. MRABTI Hind. AFFILIATION: Institut National d′oncologie, Mohamed V University. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:. Receipt of honoraria or consultation fees:Astellas, Sanofi, Janssen, AstraZeneca, Ipsen, MSD, Pfizer, Amgen. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 31st March 2022. Deborah Mukherji. AFFILIATION: American University of Beirut. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:Astellas. Receipt of honoraria or consultation fees:Astellas, Janssen, MSD, Ipsen, BMS. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 31st March 2022. Sloan Kettering Cancer Center. AIQ Pharma. Epic Sciences. Janssen. Menarini Silicon Biosystems. ThermoFisher. Howard I. Scher, MD, FASCO. AFFILIATION: Memorial Sloan Kettering Cancer Center. Howard I. Scher, MD, FASCO - Disclosure Form. March 31, 2022. Honoraria. Sidney Kimmel Cancer Center, Jefferson Health. Elsevier, LTD. Arsenal Capital. Consultancy/Advisory Board. Ambry Genetics Corporation, Konica Minolta,Inc. Amgen. Bayer. Janssen Research & Development, LLC. Pfizer Inc. Sun Pharmaceuticals Industries, Inc. WCG Oncology. Research Funding to Memorial Sloan Kettering Cancer Center. AIQ Pharma. Epic Sciences. Janssen. Menarini Silicon Biosystems. ThermoFisher. Evan Y. Yu, M.D. AFFILIATION: Fred Hutchinson Cancer Center and University of Washington. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:Bayer, Blue Earth, Daiichi-Sankyo, Dendreon, Lantheus, Merck, Seagen. Receipt of honoraria or consultation fees:Abbvie, Advanced Accelerator Applications, Bayer, Clovis, Exelixis, Janssen, Merck, Sanofi. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 31st March 2022. Gedske Daugaard. AFFILIATION: Rigshospitalet, Copenhagen. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:. Receipt of honoraria or consultation fees:Bayer, Sanofi, Astellas, MSD, Bristol Myers. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 30th March 2022. Celestia S. Higano, MD, FACP. AFFILIATION: University of Columbia. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:None last 24 months. Receipt of honoraria or consultation fees:AstraZeneca, Astellas, Genentech, Merck Sharp & Dohme, Myovant, Tolmar, Vaccitech, Verity. Participation in a company sponsored speaker’s bureau:none. Stock shareholder: CTI Biopharma. Spouse/partner: none. Other support (please specify): Expert testimony, Ferring. Signature: 31st March 2022. Dr. Vedang Murthy. AFFILIATION: Radiotion Oncology. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:Varian Medical Systems. Receipt of honoraria or consultation fees:. Participation in a company sponsored speaker’s bureau: Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 1st April 2022. Gero Kramer. AFFILIATION: Department of Urology, Medical University of Vienna. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:None. Receipt of honoraria or consultation fees:Astellas, AstraZeneca, Bayer, BMS, Ipsen, Janssen, MSD, Novartis, Sanofi Genzyme, Takeda, Ferring. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 31st March 2022. Niven Mehra. AFFILIATION: Radboudumc. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:Astellas, Astrazeneca, BMS. Receipt of honoraria or consultation fees:Astellas, Astrazeneca, Bayer, Janssen. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 1st April 2022. Juan Pablo Sade. AFFILIATION: Instituto Alexnder Fleming, Buenos Aires, Argentina. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:Janssen, Astellas, AtraZeneca, MSD, BMS. Receipt of honoraria or consultation fees:Janssen, Bayer, Pfizer, Astellas. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 3rd April 2022. Dr Maria De Santis. AFFILIATION: Charité Universitätsmedizin Berlin, Department of Urology. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:. Receipt of honoraria or consultation fees:AAA, Amgen, Astellas, AstraZeneca, Basilea, Bayer, Bioclin, BMS, EISAI, Ferring, Immunomedics, Ipsen, Janssen, MSD, Merck, Novartis, Pfizer, Roche, Sandoz, Sanofi, SeaGen. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 1st April 2022. Iwona Skoneczna. AFFILIATION: Maria Sklodowska-Curie National Research Institute of Oncology, Szpital Grochowski, Warsaw, Poland. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:Astellas, Bayer, BMS, Janssen, Roche. Receipt of honoraria or consultation fees:Astellas, Bayer, Janssen. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 1st April 2022. Laurence Klotz. AFFILIATION: University of Toronto. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:miR Scientific, Exact Imaging. Receipt of honoraria or consultation fees:miR Scientific, Antev. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 30th March 2022. Yüksel Ürün. AFFILIATION: Ankara University School of Medicine. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:. Receipt of honoraria or consultation fees:Astellas, AtraZeneca, BMS, Janssen Oncology, MSD, Pfizer, Roche. Participation in a company sponsored speaker’s bureau:Astellas, Amgen, AtraZeneca, BMS, Janssen Oncology, Pfizer, Roche. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 01st April 2022. Howard R. Soule. AFFILIATION: Prostate Cancer Foundation. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:. Receipt of honoraria or consultation fees:Compugen. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 4th April 2022. Simon Chowdhury. AFFILIATION:. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:Janssen Oncology, Beigene, Clovis Oncology, Pfizer,. Receipt of honoraria or consultation fees:. Participation in a company sponsored speaker’s bureau:Janssen Oncology, AstraZeneca, Bayer, Pfizer, Sandoz. Stock shareholder:. Spouse/partner:. Other support (please specify): Janssen Oncology (Advisory board). Novartis (advisory board, consultancy). Bayer (Advisory board). Astellas (advisory board, consultancy). Athenex (advisory board). Beigene (advisory board). Clovis Oncology (Advisory board). Telix (advisory board, consultancy). Curve.Life (founder and stock). Huma (consulting fees and Stock). Remedy Bio: consulting fees, Stock. Signature: 4th April 2022. Daniel Heinrich. AFFILIATION: Innlandet Hospital, Department of Oncology and Radiotherapy, Gjøvik, Norway. X I have no potential conflict of interest to report. Signature: Date: 28th February 2022. Raya Leibowitz. AFFILIATION: Shamir Medical Center, Zerifin, Be’er Yaakov, Israel. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:none. Receipt of honoraria or consultation fees:MSD, BMS, Isotopia, Bayer, AstraZeneca, Astellas, Janssen, Pfizer. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify):. Signature: 05th April 2022. Raja Khauli. AFFILIATION: American University of Beirut Medical Ctr Clinical. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:none. Receipt of honoraria or consultation fees:. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify): honoraria: Astellas, Janssen, Algorithm SAL. Signature: 06th April 2022. Axel Merseburger. AFFILIATION: Campus Lübeck, University Hospital Schleswig-Holstein. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:none. Receipt of honoraria or consultation fees:. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify):. Lectures/Speaker/Honoraria:. Astra Zeneca, Bristol-Myers Squibb, Eisai, Ferring, Ipsen, MSD, Merck Serono, Janssen, Takeda, TEVA, Astellas, Novartis, Pfizer, Recordati and Roche. Consultant:. AstraZeneca, Astellas, Bristol-Myers Squibb, Ferring, Ipsen, Janssen, EUSAPharm, MSD, Merck Serono, Novartis, Takeda, Teva, Pfizer, Recordati and Roche. Research and clinical trials:. AstraZeneca, Astellas, Bristol-Myers Squibb, Ipsen, Janssen, EUSAPharm, MSD, Merck Serono, Novartis, Takeda, Teva, Pfizer und Roche. Signature: 06th April 2022. Carmel Pezaro. AFFILIATION: Sheffield Teaching Hospitals NHS Foundation Trust. Type of affiliation / financial interest Name of commercial company. Receipt of grants/research supports:none. Receipt of honoraria or consultation fees:Advanced Accelerator Applications, Astellas, AstraZeneca, Bayer, Janssen. Participation in a company sponsored speaker’s bureau:. Stock shareholder:. Spouse/partner:. Other support (please specify): Bayer, Ipsen (travel support). Signature: 06th April 2022. All remaining authors declare no conflict of interest., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Innovations in imaging and molecular characterisation and the evolution of new therapies have improved outcomes in advanced prostate cancer. Nonetheless, we continue to lack high-level evidence on a variety of clinical topics that greatly impact daily practice. To supplement evidence-based guidelines, the 2022 Advanced Prostate Cancer Consensus Conference (APCCC 2022) surveyed experts about key dilemmas in clinical management., Objective: To present consensus voting results for select questions from APCCC 2022., Design, Setting, and Participants: Before the conference, a panel of 117 international prostate cancer experts used a modified Delphi process to develop 198 multiple-choice consensus questions on (1) intermediate- and high-risk and locally advanced prostate cancer, (2) biochemical recurrence after local treatment, (3) side effects from hormonal therapies, (4) metastatic hormone-sensitive prostate cancer, (5) nonmetastatic castration-resistant prostate cancer, (6) metastatic castration-resistant prostate cancer, and (7) oligometastatic and oligoprogressive prostate cancer. Before the conference, these questions were administered via a web-based survey to the 105 physician panel members ("panellists") who directly engage in prostate cancer treatment decision-making. Herein, we present results for the 82 questions on topics 1-3., Outcome Measurements and Statistical Analysis: Consensus was defined as ≥75% agreement, with strong consensus defined as ≥90% agreement., Results and Limitations: The voting results reveal varying degrees of consensus, as is discussed in this article and shown in the detailed results in the Supplementary material. The findings reflect the opinions of an international panel of experts and did not incorporate a formal literature review and meta-analysis., Conclusions: These voting results by a panel of international experts in advanced prostate cancer can help physicians and patients navigate controversial areas of clinical management for which high-level evidence is scant or conflicting. The findings can also help funders and policymakers prioritise areas for future research. Diagnostic and treatment decisions should always be individualised based on patient and cancer characteristics (disease extent and location, treatment history, comorbidities, and patient preferences) and should incorporate current and emerging clinical evidence, therapeutic guidelines, and logistic and economic factors. Enrolment in clinical trials is always strongly encouraged. Importantly, APCCC 2022 once again identified important gaps (areas of nonconsensus) that merit evaluation in specifically designed trials., Patient Summary: The Advanced Prostate Cancer Consensus Conference (APCCC) provides a forum to discuss and debate current diagnostic and treatment options for patients with advanced prostate cancer. The conference aims to share the knowledge of international experts in prostate cancer with health care providers and patients worldwide. At each APCCC, a panel of physician experts vote in response to multiple-choice questions about their clinical opinions and approaches to managing advanced prostate cancer. This report presents voting results for the subset of questions pertaining to intermediate- and high-risk and locally advanced prostate cancer, biochemical relapse after definitive treatment, advanced (next-generation) imaging, and management of side effects caused by hormonal therapies. The results provide a practical guide to help clinicians and patients discuss treatment options as part of shared multidisciplinary decision-making. The findings may be especially useful when there is little or no high-level evidence to guide treatment decisions., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

Multiparametric MRI of the prostate is now recommended as the initial diagnostic test for men presenting with suspected prostate cancer, with a negative MRI enabling safe avoidance of biopsy and a positive result enabling MRI-directed sampling of lesions. The diagnostic pathway consists of several steps, from initial patient presentation and preparation to performing and interpreting MRI, communicating the imaging findings, outlining the prostate and intra-prostatic target lesions, performing the biopsy and assessing the cores. Each component of this pathway requires experienced clinicians, optimized equipment, good inter-disciplinary communication between specialists, and standardized workflows in order to achieve the expected outcomes. Assessment of quality and mitigation measures are essential for the success of the MRI-directed prostate cancer diagnostic pathway. Quality assurance processes including Prostate Imaging-Reporting and Data System, template biopsy, and pathology guidelines help to minimize variation and ensure optimization of the diagnostic pathway. Quality control systems including the Prostate Imaging Quality scoring system, patient-level outcomes (such as Prostate Imaging-Reporting and Data System MRI score assignment and cancer detection rates), multidisciplinary meeting review and audits might also be used to provide consistency of outcomes and ensure that all the benefits of the MRI-directed pathway are achieved., (© 2022. Springer Nature Limited.)

Background and Objectives: Prostate cancer screening studies has previously not been able to reflect a diverse group of participants. We evaluated a range of recruitment strategies and their ability to recruit from the Black population and areas of deprivation., Methods: IP1-PROSTAGRAM was a prospective, population-based, paired screening study of 408 participants conducted at seven UK primary care practices and two imaging centres. All participants underwent screening with a prostate specific antigen (PSA) test, magnetic resonance imaging (MRI), and transrectal ultrasound. A number of recruitment strategies were embedded including direct mail, media campaigns, and a targeted recruitment strategy to increase participation among harder-to-reach groups., Results: A total of 1,316 expressions of interest were received (20th September 2018 to 15th May 2019). The direct mail strategy generated 317 expressions of interest from 1707 invitation letters. Overall 387 expressions of interest were received following the targeted strategy and 612 from media campaigns. The recruitment target was met 19 months ahead of the schedule. Of the 411 participants, ethnicity was White (38.0%), Black (32.4%), Asian (23.0%), and Other/Mixed (4.4%) ethnic groups. This higher recruitment of Black men was driven by the targeted recruitment strategy. A comparison of recruitment methods showed marked differences between ethnicities recruited (P < 0.001). The proportion of Black participants recruited by direct mail (8%) was similar to the prevalence of Black local population (9%) whereas, targeted recruitment was 88% (115) and media recruitment 1.7% (1). The Index of Multiple Deprivation (IMD) distribution was similar to the local population with marginal higher recruitment from more deprived areas; proportion increasing from 26% to 40% from least to most deprived IMD quintiles (Quintiles 4/5 vs. 1/2). Direct mail recruited a close-to-normal distribution for deprivation with targeted recruitment trending towards recruiting from most deprived areas., Conclusion: Direct mail and targeted strategies designed to engage a diverse population can achieve a representative uptake from Black participants and those from a lower socioeconomic group., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Background Prostate cancer local recurrence location and extent must be determined in an accurate and timely manner. Because of the lack of a standardized MRI approach after whole-gland treatment, a panel of international experts recently proposed the Prostate Imaging for Recurrence Reporting (PI-RR) assessment score. Purpose To determine the diagnostic accuracy of PI-RR for detecting local recurrence in patients with biochemical recurrence (BCR) after radiation therapy (RT) or radical prostatectomy (RP) and to evaluate the interreader variability of PI-RR scoring. Materials and Methods This retrospective observational study included patients who underwent multiparametric MRI between September 2016 and May 2021 for BCR after RT or RP. MRI scans were analyzed, and a PI-RR score was assigned independently by four radiologists. The reference standard was defined using histopathologic findings, follow-up imaging, or clinical response to treatment. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated to assess PI-RR performance for each reader. The intraclass correlation coefficient was used to determine interreader agreement. Results A total of 100 men were included: 48 patients after RT (median age, 76 years [IQR, 70-82 years]) and 52 patients after RP (median age, 70 years [IQR, 66-74 years]). After RT, with PI-RR of 3 or greater as a cutoff (assigned when recurrence is uncertain), diagnostic performance ranges were 71%-81% sensitivity, 74%-93% specificity, 71%-89% PPV, 79%-86% NPV, and 77%-88% accuracy across the four readers. After RP, with PI-RR of 3 or greater as a cutoff, performance ranges were 59%-83% sensitivity, 87%-100% specificity, 88%-100% PPV, 66%-80% NPV, and 75%-85% accuracy. The intraclass correlation coefficient was 0.87 across the four readers for both the RT and RP groups. Conclusion MRI scoring with the Prostate Imaging for Recurrence Reporting assessment provides structured, reproducible, and accurate evaluation of local recurrence after definitive therapy for prostate cancer. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Haider in this issue. An earlier incorrect version appeared online. This article was corrected on May 11, 2022.