Author Correction: The evolutionary history of lethal metastatic prostate cancer.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

ssVERDICT: Self-supervised VERDICT-MRI for enhanced prostate tumor characterization.

PURPOSE: Demonstrating and assessing self-supervised machine-learning fitting of the VERDICT (vascular, extracellular and restricted diffusion for cytometry in tumors) model for prostate cancer. METHODS: We derive a self-supervised neural network for fitting VERDICT (ssVERDICT) that estimates parameter maps without training data. We compare the performance of ssVERDICT to two established baseline methods for fitting diffusion MRI models: conventional nonlinear least squares and supervised deep learning. We do this quantitatively on simulated data by comparing the Pearson's correlation coefficient, mean-squared error, bias, and variance with respect to the simulated ground truth. We also calculate in vivo parameter maps on a cohort of 20 prostate cancer patients and compare the methods' performance in discriminating benign from cancerous tissue via Wilcoxon's signed-rank test. RESULTS: In simulations, ssVERDICT outperforms the baseline methods (nonlinear least squares and supervised deep learning) in estimating all the parameters from the VERDICT prostate model in terms of Pearson's correlation coefficient, bias, and mean-squared error. In vivo, ssVERDICT shows stronger lesion conspicuity across all parameter maps, and improves discrimination between benign and cancerous tissue over the baseline methods. CONCLUSION: ssVERDICT significantly outperforms state-of-the-art methods for VERDICT model fitting and shows, for the first time, fitting of a detailed multicompartment biophysical diffusion MRI model with machine learning without the requirement of explicit training labels.

Regional Histopathology and Prostate MRI Positivity: A Secondary Analysis of the PROMIS Trial.

Background The effects of regional histopathologic changes on prostate MRI scans have not been accurately quantified in men with an elevated prostate-specific antigen (PSA) level and no previous biopsy. Purpose To assess how Gleason grade, maximum cancer core length (MCCL), inflammation, prostatic intraepithelial neoplasia (PIN), or atypical small acinar proliferation within a Barzell zone affects the odds of MRI visibility. Materials and Methods In this secondary analysis of the Prostate MRI Imaging Study (PROMIS; May 2012 to November 2015), consecutive participants who underwent multiparametric MRI followed by a combined biopsy, including 5-mm transperineal mapping (TPM), were evaluated. TPM pathologic findings were reported at the whole-prostate level and for each of 20 Barzell zones per prostate. An expert panel blinded to the pathologic findings reviewed MRI scans and declared which Barzell areas spanned Likert score 3-5 lesions. The relationship of Gleason grade and MCCL to zonal MRI outcome (visible vs nonvisible) was assessed using generalized linear mixed-effects models with random intercepts for individual participants. Inflammation, PIN, and atypical small acinar proliferation were similarly assessed in men who had negative TPM results. Results Overall, 161 men (median age, 62 years [IQR, 11 years]) were evaluated and 3179 Barzell zones were assigned MRI status. Compared with benign areas, the odds of MRI visibility were higher when a zone contained cancer with a Gleason score of 3+4 (odds ratio [OR], 3.1; 95% CI: 1.9, 4.9; P < .001) or Gleason score greater than or equal to 4+3 (OR, 8.7; 95% CI: 4.5, 17.0; P < .001). MCCL also determined visibility (OR, 1.24 per millimeter increase; 95% CI: 1.15, 1.33; P < .001), but odds were lower with each prostate volume doubling (OR, 0.7; 95% CI: 0.5, 0.9). In men who were TPM-negative, the presence of PIN increased the odds of zonal visibility (OR, 3.7; 95% CI: 1.5, 9.1; P = .004). Conclusion An incremental relationship between cancer burden and prostate MRI visibility was observed. Prostatic intraepithelial neoplasia contributed to false-positive MRI findings. ClinicalTrials.gov registration no. NCT01292291 © RSNA, 2022 Supplemental material is available for this article. See also the editorial by Harmath in this issue.

Accurate diagnosis of prostate cancer by combining Proclarix with magnetic resonance imaging.

OBJECTIVES: To assess of the clinical performance of Proclarix® (a novel Conformité Européenne [CE]-marked biomarker test aiding in the identification of clinically significant prostate cancer [csPCa]) alone or in combination with multiparametric magnetic resonance imaging (mpMRI) to predict csPCa (International Society of Urological Pathology Grade Group ≥2). PATIENTS AND METHODS: The study included blood samples from 721 men undergoing mpMRI followed by biopsy at University College London, London, and Vall d'Hebron University Hospital, Barcelona. Samples were tested blindly. The Proclarix-MRI model combining prostate volume, Proclarix and mpMRI results was trained using the UCL cohort (n = 159) and validated in the Vall d'Hebron cohort (n = 562). Its diagnostic performance was established in correlation to biopsy outcome and compared to available clinical parameters and risk calculators. RESULTS: Clinical performance of the Proclarix-MRI model in the validation cohort did not significantly differ from the training cohort and resulted in a sensitivity for csPCa of 90%, 90% negative predictive value and 66% positive predictive value. The Proclarix-MRI score's specificity (68%) was significantly (P < 0.001) better than the MRI-European Randomized study of Screening for Prostate Cancer risk score (51%), Proclarix (27%) or mpMRI (28%) alone. In addition, Proclarix by itself was found to be useful in the MRI Prostate Imaging-Reporting and Data System (PI-RADS) score 3 subgroup by outperforming prostate-specific antigen density in terms of specificity (25% vs 13%, P = 0.004) at 100% sensitivity. CONCLUSION: When combined with mpMRI and prostate volume, Proclarix reliably predicted csPCa and ruled out men with no or indolent cancer. A large reduction of two thirds of unneeded biopsies was achieved. Proclarix can further be used with high confidence to reliably detect csPCa in men with an indeterminate PI-RADS score 3 mpMRI. Despite these encouraging results, further validation is needed.

The architecture of clonal expansions in morphologically normal tissue from cancerous and non-cancerous prostates.

BACKGROUND: Up to 80% of cases of prostate cancer present with multifocal independent tumour lesions leading to the concept of a field effect present in the normal prostate predisposing to cancer development. In the present study we applied Whole Genome DNA Sequencing (WGS) to a group of morphologically normal tissue (n = 51), including benign prostatic hyperplasia (BPH) and non-BPH samples, from men with and men without prostate cancer. We assess whether the observed genetic changes in morphologically normal tissue are linked to the development of cancer in the prostate. RESULTS: Single nucleotide variants (P = 7.0 × 10-03, Wilcoxon rank sum test) and small insertions and deletions (indels, P = 8.7 × 10-06) were significantly higher in morphologically normal samples, including BPH, from men with prostate cancer compared to those without. The presence of subclonal expansions under selective pressure, supported by a high level of mutations, were significantly associated with samples from men with prostate cancer (P = 0.035, Fisher exact test). The clonal cell fraction of normal clones was always higher than the proportion of the prostate estimated as epithelial (P = 5.94 × 10-05, paired Wilcoxon signed rank test) which, along with analysis of primary fibroblasts prepared from BPH specimens, suggests a stromal origin. Constructed phylogenies revealed lineages associated with benign tissue that were completely distinct from adjacent tumour clones, but a common lineage between BPH and non-BPH morphologically normal tissues was often observed. Compared to tumours, normal samples have significantly less single nucleotide variants (P = 3.72 × 10-09, paired Wilcoxon signed rank test), have very few rearrangements and a complete lack of copy number alterations. CONCLUSIONS: Cells within regions of morphologically normal tissue (both BPH and non-BPH) can expand under selective pressure by mechanisms that are distinct from those occurring in adjacent cancer, but that are allied to the presence of cancer. Expansions, which are probably stromal in origin, are characterised by lack of recurrent driver mutations, by almost complete absence of structural variants/copy number alterations, and mutational processes similar to malignant tissue. Our findings have implications for treatment (focal therapy) and early detection approaches.

Avoiding Unnecessary Biopsy after Multiparametric Prostate MRI with VERDICT Analysis: The INNOVATE Study.

Background In men suspected of having prostate cancer (PCa), up to 50% of men with positive multiparametric MRI (mpMRI) findings (Prostate Imaging Reporting and Data System [PI-RADS] or Likert score of 3 or higher) have no clinically significant (Gleason score ≤3+3, benign) biopsy findings. Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumor (VERDICT) MRI analysis could improve the stratification of positive mpMRI findings. Purpose To evaluate VERDICT MRI, mpMRI-derived apparent diffusion coefficient (ADC), and prostate-specific antigen density (PSAD) as determinants of clinically significant PCa (csPCa). Materials and Methods Between April 2016 and December 2019, men suspected of having PCa were prospectively recruited from two centers and underwent VERDICT MRI and mpMRI at one center before undergoing targeted biopsy. Biopsied lesion ADC, lesion-derived fractional intracellular volume (FIC), and PSAD were compared between men with csPCa and those without csPCa, using nonparametric tests subdivided by Likert scores. Area under the receiver operating characteristic curve (AUC) was calculated to test diagnostic performance. Results Among 303 biopsy-naive men, 165 study participants (mean age, 65 years ± 7 [SD]) underwent targeted biopsy; of these, 73 had csPCa. Median lesion FIC was higher in men with csPCa (FIC, 0.53) than in those without csPCa (FIC, 0.18) for Likert 3 (P = .002) and Likert 4 (0.60 vs 0.28, P < .001) lesions. Median lesion ADC was lower for Likert 4 lesions with csPCa (0.86 × 10-3 mm2/sec) compared with lesions without csPCa (1.12 × 10-3 mm2/sec, P = .03), but there was no evidence of a difference for Likert 3 lesions (0.97 × 10-3 mm2/sec vs 1.20 × 10-3 mm2/sec, P = .09). PSAD also showed no difference for Likert 3 (0.17 ng/mL2 vs 0.12 ng/mL2, P = .07) or Likert 4 (0.14 ng/mL2 vs 0.12 ng/mL2, P = .47) lesions. The diagnostic performance of FIC (AUC, 0.96; 95% CI: 0.93, 1.00) was higher (P = .02) than that of ADC (AUC, 0.85; 95% CI: 0.79, 0.91) and PSAD (AUC, 0.74; 95% CI: 0.66, 0.82) for the presence of csPCa in biopsied lesions. Conclusion Lesion fractional intracellular volume enabled better classification of clinically significant prostate cancer than did apparent diffusion coefficient and prostate-specific antigen density. Clinical trial registration no. NCT02689271 © RSNA, 2022 Online supplemental material is available for this article.

Conspicuity of prostate cancer on multiparametric magnetic resonance imaging: A cross-disciplinary translational hypothesis.

Pre-biopsy multiparametric magnetic resonance imaging (mpMRI) has transformed the risk stratification and diagnostic approach for suspected prostate cancer. The majority of clinically significant prostate cancers are visible on pre-biopsy mpMRI, however, there are a subset of significant tumors that are not detected by mpMRI. The radiobiological mechanisms underpinning mpMRI-visibility and invisibility of these cancers remain uncertain. Emerging evidence suggests that mpMRI-visible tumors are enriched with molecular features associated with increased disease aggressivity and poor clinical prognosis, which is supported by short-term endpoints, such as biochemical recurrence following surgery. Furthermore, at the histopathological level, mpMRI-visible tumors appear to exhibit increased architectural and vascular density compared to mpMRI-invisible disease. It seems probable that the genomic, pathological, radiological, and clinical features of mpMRI-visible and mpMRI-invisible prostate cancers are interrelated. Here, we propose a novel cross-disciplinary theory that links genomic and molecular evidence with cellular and histopathological appearances, elucidating both the mpMRI visibility and clinical status of significant prostate cancer.

The evolutionary history of lethal metastatic prostate cancer.

Cancers emerge from an ongoing Darwinian evolutionary process, often leading to multiple competing subclones within a single primary tumour. This evolutionary process culminates in the formation of metastases, which is the cause of 90% of cancer-related deaths. However, despite its clinical importance, little is known about the principles governing the dissemination of cancer cells to distant organs. Although the hypothesis that each metastasis originates from a single tumour cell is generally supported, recent studies using mouse models of cancer demonstrated the existence of polyclonal seeding from and interclonal cooperation between multiple subclones. Here we sought definitive evidence for the existence of polyclonal seeding in human malignancy and to establish the clonal relationship among different metastases in the context of androgen-deprived metastatic prostate cancer. Using whole-genome sequencing, we characterized multiple metastases arising from prostate tumours in ten patients. Integrated analyses of subclonal architecture revealed the patterns of metastatic spread in unprecedented detail. Metastasis-to-metastasis spread was found to be common, either through de novo monoclonal seeding of daughter metastases or, in five cases, through the transfer of multiple tumour clones between metastatic sites. Lesions affecting tumour suppressor genes usually occur as single events, whereas mutations in genes involved in androgen receptor signalling commonly involve multiple, convergent events in different metastases. Our results elucidate in detail the complex patterns of metastatic spread and further our understanding of the development of resistance to androgen-deprivation therapy in prostate cancer.

PEOPLE: PatiEnt prOstate samPLes for rEsearch, a tissue collection pathway utilizing magnetic resonance imaging data to target tumor and benign tissue in fresh radical prostatectomy specimens.

BACKGROUND: Over 1 million men are diagnosed with prostate cancer each year worldwide, with a wide range of research programs requiring access to patient tissue samples for development of improved diagnoses and treatments. A random sampling of prostate tissue is sufficient for certain research studies; however, there is growing research need to target areas of the aggressive tumor as fresh tissue. Here we set out to develop a new pathway "PEOPLE: PatiEnt prOstate samPLes for rEsearch" to collect high-quality fresh tissue for research use, using magnetic resonance imaging (MRI) to target areas of tumor and benign tissue. METHODS: Prostate tissue was sampled following robotic radical prostatectomy, using MRI data to target areas of benign and tumor tissue. Initially, 25 cases were sampled using MRI information from clinical notes. A further 59 cases were sampled using an optimized method that included specific MRI measurements of tumor location along with additional exclusion criteria. All cases were reviewed in batches with detailed clinical and histopathological data recorded. For one subset of samples, DNA was extracted and underwent quality control. Ex vivo culture was carried out using the gelatin sponge method for an additional subset. RESULTS: Tumor was successfully fully or partially targeted in 64% of the initial cohort and 70% of the optimized cohort. DNA of high quality and concentration was isolated from 39 tumor samples, and ex vivo culture was successfully carried out in three cases with tissue morphology, proliferation, and apoptosis remaining comparable before and after 72 hours culture. CONCLUSION: Here we report initial data from the PEOPLE pathway; using a method for targeting areas of tumor within prostate samples using MRI. This method operates alongside the standard clinical pathway and minimizes additional input from surgical, radiological, and pathological teams, while preserving surgical margins and diagnostic tissue.

Immunohistochemical biomarker validation in highly selective needle biopsy microarrays derived from mpMRI-characterized prostates.

INTRODUCTION: Diagnosing prostate cancer routinely involves tissue biopsy and increasingly image guided biopsy using multiparametric MRI (mpMRI). Excess tissue after diagnosis can be used for research to improve the diagnostic pathway and the vertical assembly of prostate needle biopsy cores into tissue microarrays (TMAs) allows the parallel immunohistochemical (IHC) validation of cancer biomarkers in routine diagnostic specimens. However, tissue within a biopsy core is often heterogeneous and cancer is not uniformly present, resulting in needle biopsy TMAs that suffer from highly variable cancer detection rates that complicate parallel biomarker validation. MATERIALS AND METHODS: The prostate cores with the highest tumor burden (in terms of Gleason score and/or maximum cancer core length) were obtained from 249 patients in the PICTURE trial who underwent transperineal template prostate mapping (TPM) biopsy at 5 mm intervals preceded by mpMRI. From each core, 2 mm segments containing tumor or benign tissue (as assessed on H&E pathology) were selected, excised and embedded vertically into a new TMA block. TMA sections were then IHC-stained for the routinely used prostate cancer biomarkers PSA, PSMA, AMACR, p63, and MSMB and assessed using the h-score method. H-scores in patient matched malignant and benign tissue were correlated with the Gleason grade of the original core and the MRI Likert score for the sampled prostate area. RESULTS: A total of 2240 TMA cores were stained and IHC h-scores were assigned to 1790. There was a statistically significant difference in h-scores between patient matched malignant and adjacent benign tissue that is independent of Likert score. There was no association between the h-scores and Gleason grade or Likert score within each of the benign or malignant groups. CONCLUSION: The construction of highly selective TMAs from prostate needle biopsy cores is possible. IHC data obtained through this method are highly reliable and can be correlated with imaging. IHC expression patterns for PSA, PSMA, AMACR, p63, and MSMB are distinct in malignant and adjacent benign tissue but did not correlate with mpMRI Likert score.

Asporin is a stromally expressed marker associated with prostate cancer progression.

BACKGROUND: Prostate cancer shows considerable heterogeneity in disease progression and we propose that markers expressed in tumour stroma may be reliable predictors of aggressive tumour subtypes. METHODS: We have used Kaplan-Meier, univariate and multivariate analysis to correlate the expression of Asporin (ASPN) mRNA and protein with prostate cancer progression in independent cohorts. We used immunohistochemistry and H scoring to document stromal localisation of ASPN in a tissue microarray and mouse prostate cancer model, and correlated expression with reactive stroma, defined using Masson Trichrome staining. We used cell cultures of primary prostate cancer fibroblasts treated with serum-free conditioned media from prostate cancer cell lines to examine regulation of ASPN mRNA in tumour stromal cells. RESULTS: We observed increased expression of ASPN mRNA in a data set derived from benign vs tumour microdissected tissue, and a correlation with biochemical recurrence using Kaplan-Meier and Cox proportional hazard analysis. ASPN protein localised to tumour stroma and elevated expression of ASPN was correlated with decreased time to biochemical recurrence, in a cohort of 326 patients with a median follow up of 9.6 years. Univariate and multivariate analysis demonstrated that ASPN was correlated with progression, as were Gleason score, and clinical stage. Additionally, ASPN expression correlated with the presence of reactive stroma, suggesting that it may be a stromal marker expressed in response to the presence of tumour cells and particularly with aggressive tumour subtypes. We observed expression of ASPN in the stroma of tumours induced by p53 inhibition in a mouse model of prostate cancer, and correlation with neuroendocrine marker expression. Finally, we demonstrated that ASPN transcript expression in normal and cancer fibroblasts was regulated by conditioned media derived from the PC3, but not LNCaP, prostate cancer cell lines. CONCLUSIONS: Our results suggest that ASPN is a stromally expressed biomarker that correlates with disease progression, and is observed in reactive stroma. ASPN expression in stroma may be part of a stromal response to aggressive tumour subtypes.

Method for sampling tissue for research which preserves pathological data in radical prostatectomy.

BACKGROUND: The diagnosis and treatment of prostate cancer is a challenging global healthcare issue requiring significant molecular research. Such research frequently utilizes fresh frozen human tissue which needs to be obtained in a manner acceptable to the pathologist which does not compromise tumor diagnosis or staging. METHODS: Radical prostatectomy specimens were handled in a standardized method before being sliced fresh. Leaving the margins intact, multiple cylindrical cores were removed using a large skin punch and the sites were marked on a prostate map. The cylindrical cores were placed onto individual, pre-numbered foil squares and snap frozen in liquid nitrogen. Prostate maps were aligned with formalin-fixed paraffin embedded hematoxylin and eosin stained sections of the sampled slice to select tumor regions. Frozen tumor tissue cylinders were processed taking one section for hematoxylin and eosin staining, 6 µm × 50 µm sections for molecular studies and a further section for hematoxylin and eosin staining. This was performed for the length of the cylinder. RESULTS: A total of 150 prostates have been removed and sliced using this technique. Pathological assessment remained uncompromised. Using the sequential hematoxylin and eosin stained frozen sections, cellularity could be monitored closely in tissues processed for research. The yield of RNA and DNA extracted was high (tumor mean 2.4 µg (RNA) and 12.7 ng per 300 µm tissue) and of high quality (mean tumor RIN 5.9). CONCLUSIONS: This novel, rapid sampling and processing method provides high quality tissue for research without compromising pathology.

Joint estimation of relaxation and diffusion tissue parameters for prostate cancer with relaxation-VERDICT MRI.

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 fic 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 (R2 = 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.

Use of artificial intelligence in the detection of primary prostate cancer in multiparametric MRI with its clinical outcomes: a protocol for a systematic review and meta-analysis.

INTRODUCTION: Multiparametric MRI (mpMRI) has transformed the prostate cancer diagnostic pathway, allowing for improved risk stratification and more targeted subsequent management. However, concerns exist over the interobserver variability of images and the applicability of this model long term, especially considering the current shortage of radiologists and the growing ageing population. Artificial intelligence (AI) is being integrated into clinical practice to support diagnostic and therapeutic imaging analysis to overcome these concerns. The following report details a protocol for a systematic review and meta-analysis investigating the accuracy of AI in predicting primary prostate cancer on mpMRI. METHODS AND ANALYSIS: A systematic search will be performed using PubMed, MEDLINE, Embase and Cochrane databases. All relevant articles published between January 2016 and February 2023 will be eligible for inclusion. To be included, articles must use AI to study MRI prostate images to detect prostate cancer. All included articles will be in full-text, reporting original data and written in English. The protocol follows the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols 2015 checklist. The QUADAS-2 score will assess the quality and risk of bias across selected studies. ETHICS AND DISSEMINATION: Ethical approval will not be required for this systematic review. Findings will be disseminated through peer-reviewed publications and presentations at both national and international conferences. PROSPERO REGISTRATION NUMBER: CRD42021293745.

Diagnostic potential of radiological apical tumor involvement.

We commend Veerman et al. for investigating the diagnostic performance of radiological apical tumor involvement (radATI) in preoperative prostate magnetic resonance imaging (MRI) and its impact on clinical outcomes in patients with localized prostate cancer. This retrospective study evaluated the diagnostic accuracy of MRI to detect pathological ATI (pathATI) in robot-assisted radical prostatectomy specimens. They found patients with radATI more likely to develop biochemical recurrence (BCR), p = 0.003, and have apical positive surgical margins (APSM), p = 0.004. We believe that the author's acknowledgement of the relationship between tumor location and cancer risk is an important step in the classification of prostate cancer. An important question that is under addressed is, what is it about apical tumors that carry additional risk? Higher rates of PSM due to incomplete surgical excision may contribute to increased recurrence risk in the apex. If this is the case, surgical management must be tailored by a tumor location-based risk assessment. The literature suggests that a single APSM may be clinically insignificant for long-term outcomes. Conversely, the authors also recommend radATI be treated with reduced apical nerve sparing to avoid APSM. We believe that this approach may lead to overtreatment in the presence of an otherwise good prognosis. We believe the extent of APSMs upon diagnosis would be an interesting topic for further investigation. The authors may also wish to perform multivariable analysis for the effect of radATI on BCR. We believe that MRI may play a critical role in enhancing diagnosis and prognostication of prostate cancer.

Prostate MR image quality of apparent diffusion coefficient maps versus fractional intracellular volume maps from VERDICT MRI using the PI-QUAL score and a dedicated Likert scale for artefacts.

PURPOSE: This study aimed to assess the image quality of apparent diffusion coefficient (ADC) maps derived from conventional diffusion-weighted MRI and fractional intracellular volume maps (FIC) from VERDICT MRI (Vascular, Extracellular, Restricted Diffusion for Cytometry in Tumours) in patients from the INNOVATE trial. The inter-reader agreement was also assessed. METHODS: Two readers analysed both ADC and FIC maps from 57 patients enrolled in the INNOVATE prospective trial. Image quality was assessed using the Prostate Imaging Quality (PI-QUAL) score and a subjective image quality Likert score (Likert-IQ). The image quality of FIC and ADC were compared using a Wilcoxon Signed Ranks test. The inter-reader agreement was assessed with Cohen's kappa. RESULTS: There was no statistically significant difference between the PI-QUAL score for FIC datasets compared to ADC datasets for either reader (p = 0.240 and p = 0.614). Using the Likert-IQ score, FIC image quality was higher compared to ADC (p = 0.021) as assessed by reader-1 but not for reader-2 (p = 0.663). The inter-reader agreement was 'fair' for PI-QUAL scoring of datasets with FIC maps at 0.27 (95% confidence interval; 0.08-0.46) and ADC datasets at 0.39 (95% confidence interval 0.22-0.57). For Likert scoring, the inter-reader agreement was also 'fair' for FIC maps at 0.38 (95% confidence interval; 0.10-0.65) and substantial for ADC maps at 0.62 (95% confidence interval; 0.39-0.86). CONCLUSION: Image quality was comparable for FIC and ADC. The inter-reader agreement was similar when using PIQUAL for both FIC and ADC datasets but higher for ADC maps compared to FIC maps using the image quality Likert score.

Effects of photobiomodulation therapy on regulation of myogenic regulatory factor mRNA expression in vivo: A systematic review.

Non-invasive promotion of myogenic regulatory factors (MRFs), through photobiomodulation therapy (PBMT), may be a viable method of facilitating skeletal muscle regeneration post-injury, given the importance of MRF in skeletal muscle regeneration. The aim of this systematic review was to collate current evidence, identifying key themes and changes in expression of MRF in in vivo models. Web of Science, PubMed, Scopus and Cochrane databases were systematically searched and identified 1459 studies, of which 10 met the inclusion criteria. Myogenic determination factor was most consistently regulated in response to PBMT treatment, and the expression of remaining MRFs was heterogenous. All studies exhibited a high risk of bias, primarily due to lack of blinding in PBMT application and MRF analysis. Our review suggests that the current evidence base for MRF expression from PBMT is highly variable. Future research should focus on developing a robust methodology for determining the effect of laser therapy on MRF expression, as well as long-term assessment of skeletal muscle regeneration.