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Prostate magnetic resonance imaging (MRI) of high diagnostic quality is a key determinant for either detection or exclusion of prostate cancer. Adequate high spatial resolution on T2-weighted imaging, good diffusion-weighted imaging and dynamic contrast-enhanced sequences of high signal-to-noise ratio are the prerequisite for a high-quality MRI study of the prostate. The Prostate Imaging Quality (PI-QUAL) score was created to assess the diagnostic quality of a scan against a set of objective criteria as per Prostate Imaging-Reporting and Data System recommendations, together with criteria obtained from the image. The PI-QUAL score is a 1-to-5 scale where a score of 1 indicates that all MR sequences (T2-weighted imaging, diffusion-weighted imaging and dynamic contrast-enhanced sequences) are below the minimum standard of diagnostic quality, a score of 3 means that the scan is of sufficient diagnostic quality, and a score of 5 implies that all three sequences are of optimal diagnostic quality. The purpose of this educational review is to provide a practical guide to assess the quality of prostate MRI using PI-QUAL and to familiarise the radiologist and all those involved in prostate MRI with this scoring system. A variety of images are also presented to demonstrate the difference between suboptimal and good prostate MR scans.

Objectives The Prostate Imaging Quality (PI-QUAL) score assesses the quality of multiparametric MRI (mpMRI). A score of 1 means all sequences are below the minimum standard of diagnostic quality, 3 implies that the scan is of sufficient diagnostic quality, and 5 means that all three sequences are of optimal diagnostic quality. We investigated the inter-reader reproducibility of the PI-QUAL score in patients enrolled in the NeuroSAFE PROOF trial. Methods We analysed the scans of 103 patients on different MR systems and vendors from 12 different hospitals. Two dedicated radiologists highly experienced in prostate mpMRI independently assessed the PI-QUAL score for each scan. Interobserver agreement was assessed using Cohen’s kappa with standard quadratic weighting (κw) and percent agreement. Results The agreement for each single PI-QUAL score was strong (κw = 0.85 and percent agreement = 84%). A similar agreement (κw = 0.82 and percent agreement = 84%) was observed when the scans were clustered into three groups (PI-QUAL 1–2 vs PI-QUAL 3 vs PI-QUAL 4–5). The agreement in terms of diagnostic quality for each single sequence was highest for T2-weighted imaging (92/103 scans; 89%), followed by dynamic contrast-enhanced sequences (91/103; 88%) and diffusion-weighted imaging (80/103; 78%). Conclusion We observed strong reproducibility in the assessment of PI-QUAL between two radiologists with high expertise in prostate mpMRI. At present, PI-QUAL offers clinicians the only available tool for evaluating and reporting the quality of prostate mpMRI in a systematic manner but further refinements of this scoring system are warranted. Key Points • Inter-reader agreement for each single Prostate Imaging Quality (PI-QUAL) score (i.e., PI-QUAL 1 to PI-QUAL 5) was strong, with weighted kappa = 0.85 (95% confidence intervals: 0.51 – 1) and percent agreement = 84%. • Interobserver agreement was strong when the scans were clustered into three groups according to the ability (or not) to rule in and to rule out clinically significant prostate cancer (i.e., PI-QUAL 1-2 vs PI-QUAL 3 vs PI-QUAL 4–5), with weighted kappa = 0.82 (95% confidence intervals: 0.68 – 0.96) and percent agreement = 84%. • T2-weighted acquisitions were the most compliant with the Prostate Imaging Reporting and Data System (PI-RADS) v. 2.0 technical recommendations and were the sequences of highest diagnostic quality for both readers in 95/103 (92%) scans, followed by dynamic contrast enhanced acquisition with 81/103 (79%) scans and lastly by diffusion-weighted imaging with 79/103 (77%) scans.

Objectives The PRECISE recommendations for magnetic resonance imaging (MRI) in patients on active surveillance (AS) for prostate cancer (PCa) include repeated measurement of each lesion, and attribution of a PRECISE radiological progression score for the likelihood of clinically significant change over time. We aimed to compare the PRECISE score with clinical progression in patients who are managed using an MRI-led AS protocol. Methods A total of 553 patients on AS for low- and intermediate-risk PCa (up to Gleason score 3 + 4) who had two or more MRI scans performed between December 2005 and January 2020 were included. Overall, 2161 scans were retrospectively re-reported by a dedicated radiologist to give a PI-RADS v2 score for each scan and assess the PRECISE score for each follow-up scan. Clinical progression was defined by histological progression to ≥ Gleason score 4 + 3 (Gleason Grade Group 3) and/or initiation of active treatment. Progression-free survival was assessed using Kaplan-Meier curves and log-rank test was used to assess differences between curves. Results Overall, 165/553 (30%) patients experienced the primary outcome of clinical progression (median follow-up, 74.5 months; interquartile ranges, 53–98). Of all patients, 313/553 (57%) did not show radiological progression on MRI (PRECISE 1–3), of which 296/313 (95%) had also no clinical progression. Of the remaining 240/553 patients (43%) with radiological progression on MRI (PRECISE 4–5), 146/240 (61%) experienced clinical progression ( p  < 0.0001). Patients with radiological progression on MRI (PRECISE 4-5) showed a trend to an increase in PSA density. Conclusions Patients without radiological progression on MRI (PRECISE 1-3) during AS had a very low likelihood of clinical progression and many could avoid routine re-biopsy. Key Points • Patients without radiological progression on MRI (PRECISE 1–3) during AS had a very low likelihood of clinical progression and many could avoid routine re-biopsy. • Clinical progression was almost always detectable in patients with radiological progression on MRI (PRECISE 4–5) during AS. • Patients with radiological progression on MRI (PRECISE 4–5) during AS showed a trend to an increase in PSA density.

This work presents a biophysical model of diffusion and relaxation MRI for prostate called relaxation vascular, extracellular and restricted diffusion for cytometry in tumours (rVERDICT). The model includes compartment-specific relaxation effects providing T1/T2 estimates and microstructural parameters unbiased by relaxation properties of the tissue. 44 men with suspected prostate cancer (PCa) underwent multiparametric MRI (mp-MRI) and VERDICT-MRI followed by targeted biopsy. We estimate joint diffusion and relaxation prostate tissue parameters with rVERDICT using deep neural networks for fast fitting. We tested the feasibility of rVERDICT estimates for Gleason grade discrimination and compared with classic VERDICT and the apparent diffusion coefficient (ADC) from mp-MRI. The rVERDICT intracellular volume fraction f ic discriminated between Gleason 3 + 3 and 3 + 4 ( p  = 0.003) and Gleason 3 + 4 and ≥ 4 + 3 ( p  = 0.040), outperforming classic VERDICT and the ADC from mp-MRI. To evaluate the relaxation estimates we compare against independent multi-TE acquisitions, showing that the rVERDICT T2 values are not significantly different from those estimated with the independent multi-TE acquisition ( p  > 0.05). Also, rVERDICT parameters exhibited high repeatability when rescanning five patients (R 2  = 0.79–0.98; CV = 1–7%; ICC = 92–98%). The rVERDICT model allows for accurate, fast and repeatable estimation of diffusion and relaxation properties of PCa sensitive enough to discriminate Gleason grades 3 + 3, 3 + 4 and ≥ 4 + 3.

Cancer cells differ in size from those of their host tissue and are known to change in size during the processes of cell death. A noninvasive method for monitoring cell size would be highly advantageous as a potential biomarker of malignancy and early therapeutic response. This need is particularly acute in brain tumours where biopsy is a highly invasive procedure. Here, diffusion MRI data were acquired in a GL261 glioma mouse model before and during treatment with Temozolomide. The biophysical model VERDICT (Vascular Extracellular and Restricted Diffusion for Cytometry in Tumours) was applied to the MRI data to quantify multi-compartmental parameters connected to the underlying tissue microstructure, which could potentially be useful clinical biomarkers. These parameters were compared to ADC and kurtosis diffusion models, and, measures from histology and optical projection tomography. MRI data was also acquired in patients to assess the feasibility of applying VERDICT in a range of different glioma subtypes. In the GL261 gliomas, cellular changes were detected according to the VERDICT model in advance of gross tumour volume changes as well as ADC and kurtosis models. VERDICT parameters in glioblastoma patients were most consistent with the GL261 mouse model, whilst displaying additional regions of localised tissue heterogeneity. The present VERDICT model was less appropriate for modelling more diffuse astrocytomas and oligodendrogliomas, but could be tuned to improve the representation of these tumour types. Biophysical modelling of the diffusion MRI signal permits monitoring of brain tumours without invasive intervention. VERDICT responds to microstructural changes induced by chemotherapy, is feasible within clinical scan times and could provide useful biomarkers of treatment response.

RECONCILE (ClinicalTrials.gov:NCT04340245) will identify molecular and radiomic markers associated with clinical progression and radiological progression events in a cohort of localised, newly diagnosed Gleason 3 + 4 tumours. Molecular markers will be correlated against standard of care MRI-targeted histology and oncological outcomes. RECONCILE is an ethics approved (20/LO/0366) single centre, prospective, longitudinal, observational cohort study of recently diagnosed (within 12 months), organ-confined Gleason 3 + 4 cancers (MCCL ≤10mm) currently under active surveillance. 60 treatment-naïve participants with a concordant MRI lesion (Likert score 4 or 5) and PSA ≤ 15 ng/ml will be recruited. Blood, urine and targeted prostate tissue cores will be subject to next generation sequencing at baseline and one year in all participants. Semen will be collected from a specified sub-population. Baseline and interval MR images will be extracted from standard of care prostate MRI ahead of radiomic analysis. Data extracted from radiological and biological samples will be used to derive the association of molecular change and radiological progression, the primary outcome of the study. To compensate for spatial intratumoral heterogeneity and inherent sampling bias, a molecular index will be derived for each participant using the molecular profile of tumour tissue at both baseline (MolBL) and one year (MolFU). We will extract a ΔMolBL:MolFU score for each participant. Molecular progression will be defined as a MolBL:MolFU score >95% CI of the combined ΔMolBL scores. Radiological progression is defined as a PRECISE score of 4 or 5. The study is powered to detect an association with a statistical power of 80%. Recruitment began in July 2020 (n = 62). To date, 37 participants have donated tissue for analysis. We have designed and implemented a prospective, longitudinal study to evaluate the underlying molecular landscape of intermediate risk, MR-visible prostate tumours. Recruitment is ongoing.

IntroductionProstate MRI is a well-established tool for the diagnostic work-up for men with suspected prostate cancer (PCa). Current recommendations advocate the use of multiparametric MRI (mpMRI), which is composed of three sequences: T2-weighted sequence (T2W), diffusion-weighted sequence (DWI) and dynamic contrast-enhanced sequence (DCE). Prior studies suggest that a biparametric MRI (bpMRI) approach, omitting the DCE sequences, may not compromise clinically significant cancer detection, though there are limitations to these studies, and it is not known how this may affect treatment eligibility. A bpMRI approach will reduce scanning time, may be more cost-effective and, at a population level, will allow more men to gain access to an MRI than an mpMRI approach.MethodsProstate Imaging Using MRI±Contrast Enhancement (PRIME) is a prospective, international, multicentre, within-patient diagnostic yield trial assessing whether bpMRI is non-inferior to mpMRI in the diagnosis of clinically significant PCa. Patients will undergo the full mpMRI scan. Radiologists will be blinded to the DCE and will initially report the MRI using only the bpMRI (T2W and DWI) sequences. They will then be unblinded to the DCE sequence and will then re-report the MRI using the mpMRI sequences (T2W, DWI and DCE). Men with suspicious lesions on either bpMRI or mpMRI will undergo prostate biopsy. The main inclusion criteria are men with suspected PCa, with a serum PSA of ≤20 ng/mL and without prior prostate biopsy. The primary outcome is the proportion of men with clinically significant PCa detected (Gleason score ≥3+4 or Gleason grade group ≥2). A sample size of at least 500 patients is required. Key secondary outcomes include the proportion of clinically insignificant PCa detected and treatment decision.Ethics and disseminationEthical approval was obtained from the National Research Ethics Committee West Midlands, Nottingham (21/WM/0091). Results of this trial will be disseminated through peer-reviewed publications. Participants and relevant patient support groups will be informed about the results of the trial.Trial registration numberNCT04571840.

Imaging plays a fundamental role in all aspects of the cancer management pathway. However, conventional imaging techniques are largely reliant on morphological and size descriptors that have well‐known limitations, particularly when considering targeted‐therapy response monitoring. Thus, new imaging methods have been developed to characterise cancer and are now routinely implemented, such as diffusion‐weighted imaging, dynamic contrast enhancement, positron emission technology (PET) and magnetic resonance spectroscopy. However, despite the improvement these techniques have enabled, limitations still remain. Novel imaging methods are now emerging, intent on further interrogating cancers. These techniques are at different stages of maturity along the biomarker pathway and aim to further evaluate the cancer microstructure (vascular, extracellular and restricted diffusion for cytometry in tumours) magnetic resonance imaging (MRI), luminal water fraction imaging] as well as the metabolic alterations associated with cancers (novel PET tracers, hyperpolarised MRI). Finally, the use of machine learning has shown powerful potential applications. By using prostate cancer as an exemplar, this Review aims to showcase these potentially potent imaging techniques and what stage we are at in their application to conventional clinical practice. Imaging plays a fundamental role in all aspects of cancer management. However, conventional imaging methods are largely reliant on morphological descriptors that have well‐established limitations. Although functional techniques have partially mitigated these shortcomings, they are still imperfect. Recently, potentially potent novel imaging techniques assessing cancer microstructure, metabolism and the use of machine learning have entered the pipeline to conventional application.

ObjectivesWe aimed to determine the interobserver reproducibility of the Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) criteria for magnetic resonance imaging in patients on active surveillance (AS) for prostate cancer (PCa) at two different academic centres.MethodsThe PRECISE criteria score the likelihood of clinically significant change over time. The system is a 1-to-5 scale, where 1 or 2 implies regression of a previously visible lesion, 3 denotes stability and 4 or 5 indicates radiological progression. A retrospective analysis of 80 patients (40 from each centre) on AS with a biopsy-confirmed low- or intermediate-risk PCa (i.e. ≤ Gleason 3 + 4 and prostate-specific antigen ≤ 20 ng/ml) and ≥ 2 prostate MR scans was performed. Two blinded radiologists reported all scans independently and scored the likelihood of radiological change (PRECISE score) from the second scan onwards. Cohen’s κ coefficients and percent agreement were computed.ResultsAgreement was substantial both at a per-patient and a per-scan level (κ = 0.71 and 0.61; percent agreement = 79% and 81%, respectively) for each PRECISE score. The agreement was superior (κ = 0.83 and 0.67; percent agreement = 90% and 91%, respectively) when the PRECISE scores were grouped according to the absence/presence of radiological progression (PRECISE 1–3 vs 4–5). Higher inter-reader agreement was observed for the scans performed at University College London (UCL) (κ = 0.81 vs 0.55 on a per-patient level and κ = 0.70 vs 0.48 on a per-scan level, respectively). The discrepancies between institutions were less evident for percent agreement (80% vs 78% and 86% vs 75%, respectively).ConclusionsExpert radiologists achieved substantial reproducibility for the PRECISE scoring system, especially when data were pooled together according to the absence/presence of radiological progression (PRECISE 1–3 vs 4–5).Key Points• Inter-reader agreement between two experienced prostate radiologists using the PRECISE criteria was substantial.• The agreement was higher when the PRECISE scores were grouped according to the absence/presence of radiological progression (i.e. PRECISE 1–3 vs PRECISE 4 and 5).• Higher inter-reader agreement was observed for the scans performed at UCL, but the discrepancies between institutions were less evident for percent agreement.

ObjectivesNational guidelines recommend prostate multiparametric (mp) MRI in men with suspected prostate cancer before biopsy. In this study, we explore prostate mpMRI protocols across 14 London hospitals and determine whether standardisation improves diagnostic quality.MethodsAn MRI physicist facilitated mpMRI set-up across several regional hospitals, working together with experienced uroradiologists who judged diagnostic quality. Radiologists from the 14 hospitals participated in the assessment and optimisation of prostate mpMRI image quality, assessed according to both PiRADSv2 recommendations and on the ability to “rule in” and/or “rule out” prostate cancer. Image quality and sequence parameters of representative mpMRI scans were evaluated across 23 MR scanners. Optimisation visits were performed to improve image quality, and 2 radiologists scored the image quality pre- and post-optimisation.Results20/23 mpMRI protocols, consisting of 111 sequences, were optimised by modifying their sequence parameters. Pre-optimisation, only 15% of T2W images were non-diagnostic, whereas 40% of ADC maps, 50% of high b-value DWI and 41% of DCE-MRI were considered non-diagnostic. Post-optimisation, the scores were increased with 80% of ADC maps, 74% of high b-value DWI and 88% of DCE-MRI to be partially or fully diagnostic. T2W sequences were not optimised, due to their higher baseline quality scores.ConclusionsTargeted intervention at a regional level can improve the diagnostic quality of prostate mpMRI protocols, with implications for improving prostate cancer detection rates and targeted biopsies.