Metabolic imaging across scales reveals distinct prostate cancer phenotypes.

Hyperpolarised magnetic resonance imaging (HP-13C-MRI) has shown promise as a clinical tool for detecting and characterising prostate cancer. Here we use a range of spatially resolved histological techniques to identify the biological mechanisms underpinning differential [1-13C]lactate labelling between benign and malignant prostate, as well as in tumours containing cribriform and non-cribriform Gleason pattern 4 disease. Here we show that elevated hyperpolarised [1-13C]lactate signal in prostate cancer compared to the benign prostate is primarily driven by increased tumour epithelial cell density and vascularity, rather than differences in epithelial lactate concentration between tumour and normal. We also demonstrate that some tumours of the cribriform subtype may lack [1-13C]lactate labelling, which is explained by lower epithelial lactate dehydrogenase expression, higher mitochondrial pyruvate carrier density, and increased lipid abundance compared to lactate-rich non-cribriform lesions. These findings highlight the potential of combining spatial metabolic imaging tools across scales to identify clinically significant metabolic phenotypes in prostate cancer.

Optimising the use of the prostate- specific antigen blood test in asymptomatic men for early prostate cancer detection in primary care: report from a UK clinical consensus.

BACKGROUND: Screening is not recommended for prostate cancer in the UK. Asymptomatic men aged ≥50 years can request a prostate-specific antigen (PSA) test following counselling on potential harms and benefits. There are areas of clinical uncertainty among GPs, resulting in the content and quality of counselling varying. AIM: To produce a consensus that can influence guidelines for UK primary care on the optimal use of the PSA test in asymptomatic men for early prostate cancer detection. DESIGN AND SETTING: Prostate Cancer UK facilitated a RAND/UCLA consensus. METHOD: Statements covering five topics were developed with a subgroup of experts. A panel of 15 experts in prostate cancer scored (round one) statements on a scale of one (strongly disagree) to nine (strongly agree). Panellists met to discuss statements before rescoring (round two). A lived experience panel of seven men scored a subset of statements with outcomes fed into the main panel. RESULTS: Of the initial 94 statements reviewed by the expert panel, a final 48/85 (56%) achieved consensus. In the absence of screening, there was consensus on proactive approaches to initiate discussions about the PSA test with men who were at higher-than-average risk. CONCLUSION: Improvements in the prostate cancer diagnostic pathway may have reduced some of the harms associated with PSA testing; however, several areas of uncertainty remain in relation to screening, including optimal PSA thresholds for referral and intervals for retesting. There is consensus on proactive approaches to testing in higher-than-average risk groups. This should prompt a review of current guidelines.

Prostate cancer detection through unbiased capture of methylated cell-free DNA.

Prostate cancer screening using prostate-specific antigen (PSA) has been shown to reduce mortality but with substantial overdiagnosis, leading to unnecessary biopsies. The identification of a highly specific biomarker using liquid biopsies, represents an unmet need in the diagnostic pathway for prostate cancer. In this study, we employed a method that enriches for methylated cell-free DNA fragments coupled with a machine learning algorithm which enabled the detection of metastatic and localized cancers with AUCs of 0.96 and 0.74, respectively. The model also detected 51.8% (14/27) of localized and 88.7% (79/89) of patients with metastatic cancer in an external dataset. Furthermore, we show that the differentially methylated regions reflect epigenetic and transcriptomic changes at the tissue level. Notably, these regions are significantly enriched for biologically relevant pathways associated with the regulation of cellular proliferation and TGF-beta signaling. This demonstrates the potential of circulating tumor DNA methylation for prostate cancer detection and prognostication.

Diagnostic value of the abnormal digital rectal examination in the modern MRI-based prostate cancer diagnostic pathway.

Objective: Currently the National Institute for Health and Care Excellence (NICE) recommends an abnormal digital rectal examination (DRE) as a standalone referral criterion for suspected prostate cancer. Unlike referrals for a raised prostate-specific antigen (PSA) which are triaged directly to magnetic resonance imaging (MRI), an abnormal DRE requires re-examination in a secondary clinic first. Here, we investigated the ongoing value of the abnormal DRE as a referral criterion. Methods: This study is a retrospective review of patients referred to secondary care for suspected prostate cancer based on an abnormal DRE over a 15-month period at a single UK hospital (n = 158). Age, PSA, primary and repeat DRE findings and eventual diagnosis were collated. Results: A concurrent raised PSA was present in 65/158 (41%). Concordance between primary and secondary care DRE was only 72/158 (46%). The overall and significant cancer detection rate was 26/158 (16%) and 22/158 (14%), respectively. Among men with a concurrent raised PSA, 19/65 (29%) had significant cancer found, whereas with an abnormal primary care DRE and normal PSA (n = 93), only 3/93 (3%) had a significant cancer. Mandating a PSA before referral for an abnormal DRE would have redirected 65/158 (41%) of men to MRI first, negating the need for a repeat DRE (p < 0.0001). This finding was recapitulated in a second prospective validation cohort (n = 30) with 9/30 (30%) redirected to MRI first. Conclusions: This is one of the first studies to investigate the value of the DRE in contemporary practice. We propose that PSA is used to triage men with an abnormal DRE to MRI without needing a repeat DRE. If the PSA is normal, the diagnostic yield is low but may still warrant a repeat DRE to assess the need for further investigations. Additional multicentre studies are required to further validate our findings. Level of evidence: 4.

Adaption and National Validation of a Tool for Predicting Mortality from Other Causes Among Men with Nonmetastatic Prostate Cancer.

BACKGROUND: An electronic health record-based tool could improve accuracy and eliminate bias in provider estimation of the risk of death from other causes among men with nonmetastatic cancer. OBJECTIVE: To recalibrate and validate the Veterans Aging Cohort Study Charlson Comorbidity Index (VACS-CCI) to predict non-prostate cancer mortality (non-PCM) and to compare it with a tool predicting prostate cancer mortality (PCM). DESIGN, SETTING, AND PARTICIPANTS: An observational cohort of men with biopsy-confirmed nonmetastatic prostate cancer, enrolled from 2001 to 2018 in the national US Veterans Health Administration (VA), was divided by the year of diagnosis into the development (2001-2006 and 2008-2018) and validation (2007) sets. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Mortality (all cause, non-PCM, and PCM) was evaluated. Accuracy was assessed using calibration curves and C statistic in the development, validation, and combined sets; overall; and by age (<65 and 65+ yr), race (White and Black), Hispanic ethnicity, and treatment groups. RESULTS AND LIMITATIONS: Among 107 370 individuals, we observed 24 977 deaths (86% non-PCM). The median age was 65 yr, 4947 were Black, and 5010 were Hispanic. Compared with CCI and age alone (C statistic 0.67, 95% confidence interval [CI] 0.67-0.68), VACS-CCI demonstrated improved validated discrimination (C statistic 0.75, 95% CI 0.74-0.75 for non-PCM). The prostate cancer mortality tool also discriminated well in validation (C statistic 0.81, 95% CI 0.78-0.83). Both were well calibrated overall and within subgroups. Owing to missing data, 18 009/125 379 (14%) were excluded, and VACS-CCI should be validated outside the VA prior to outside application. CONCLUSIONS: VACS-CCI is ready for implementation within the VA. Electronic health record-assisted calculation is feasible, improves accuracy over age and CCI alone, and could mitigate inaccuracy and bias in provider estimation. PATIENT SUMMARY: Veterans Aging Cohort Study Charlson Comorbidity Index is ready for application within the Veterans Health Administration. Electronic health record-assisted calculation is feasible, improves accuracy over age and Charlson Comorbidity Index alone, and might help mitigate inaccuracy and bias in provider estimation of the risk of non-prostate cancer mortality.

Imaging tumor lactate is feasible for identifying intermediate-risk prostate cancer patients with postsurgical biochemical recurrence.

While radical prostatectomy remains the mainstay of prostate cancer (PCa) treatment, 20 to 40% of patients develop postsurgical biochemical recurrence (BCR). A particularly challenging clinical cohort includes patients with intermediate-risk disease whose risk stratification would benefit from advanced approaches that complement standard-of-care diagnostic tools. Here, we show that imaging tumor lactate using hyperpolarized 13C MRI and spatial metabolomics identifies BCR-positive patients in two prospective intermediate-risk surgical cohorts. Supported by spatially resolved tissue analysis of established glycolytic biomarkers, this study provides the rationale for multicenter trials of tumor metabolic imaging as an auxiliary tool to support PCa treatment decision-making.

Re-evaluating the diagnostic efficacy of PSA as a referral test to detect clinically significant prostate cancer in contemporary MRI-based image-guided biopsy pathways.

Introduction: Modern image-guided biopsy pathways at diagnostic centres have greatly refined the investigations of men referred with suspected prostate cancer. However, the referral criteria from primary care are still based on historical prostate-specific antigen (PSA) cut-offs and age-referenced thresholds. Here, we tested whether better contemporary pathways and biopsy methods had improved the predictive utility value of PSA referral thresholds. Methods: PSA referral thresholds, age-referenced ranges and PSA density (PSAd) were assessed for positive predictive value (PPV) in detection of clinically significant prostate cancer (csPCa - histological ⩾ Grade Group 2). Data were analysed from men referred to three diagnostics centres who used multi-parametric magnetic resonance imaging (mpMRI)-guided prostate biopsies for disease characterisation. Findings were validated in a separate multicentre cohort. Results: Data from 2767 men were included in this study. The median age, PSA and PSAd were 66.4 years, 7.3 ng/mL and 0.1 ng/mL2, respectively. Biopsy detected csPCa was found in 38.7%. The overall area under the curve (AUC) for PSA was 0.68 which is similar to historical performance. A PSA threshold of ⩾ 3 ng/mL had a PPV of 40.3%, but this was age dependent (PPV: 24.8%, 32.7% and 56.8% in men 50-59 years, 60-69 years and ⩾ 70 years, respectively). Different PSA cut-offs and age-reference ranges failed to demonstrate better performance. PSAd demonstrated improved AUC (0.78 vs 0.68, p < 0.0001) and improved PPV compared to PSA. A PSAd of ⩾ 0.10 had a PPV of 48.2% and similar negative predictive value (NPV) to PSA ⩾ 3 ng/mL and out-performed PSA age-reference ranges. This improved performance was recapitulated in a separate multi-centre cohort (n = 541). Conclusion: The introduction of MRI-based image-guided biopsy pathways does not appear to have altered PSA diagnostic test characteristics to positively detect csPCa. We find no added value to PSA age-referenced ranges, while PSAd offers better PPV and the potential for a single clinically useful threshold (⩾0.10) for all age groups. Level of evidence: IV.

Prospective Implementation and Early Outcomes of a Risk-stratified Prostate Cancer Active Surveillance Follow-up Protocol.

Background: Active surveillance (AS) is a major management option for men with early prostate cancer. Current guidelines however advocate identical AS follow-up for all without considering different disease trajectories. We previously proposed a pragmatic three-tier STRATified CANcer Surveillance (STRATCANS) follow-up strategy based on different progression risks from clinic-pathological and imaging features. Objective: To report early outcomes from the implementation of the STRATCANS protocol in our centre. Design setting and participants: Men on AS were enrolled into a prospective stratified follow-up programme. Intervention: Three tiers of increasing follow-up intensity based on National Institute for Health and Care Excellence (NICE): Cambridge Prognostic Group (CPG) 1 or 2, prostate-specific antigen density, and magnetic resonance imaging (MRI) Likert score at entry. Outcome measurements and statistical analysis: Rates of progression to CPG ≥3, any pathological progression, AS attrition, and patient choice for treatment were assessed. Differences in progression were compared with chi-square statistics. Results and limitations: Data from 156 men (median age 67.3 yr) were analysed. Of these, 38.4% had CPG2 disease and 27.5% had grade group 2 disease at diagnosis. The median time on AS was 4 yr (interquartile range 3.2-4.9) and 1.5 yr on STRATCANS. Overall, 135/156 (86.5%) men remained on AS or converted to watchful waiting and 6/156 (3.8%) stopped AS by choice by the end of the evaluation period. Of the 156 patients, 66 (42.3%) were allocated to STRATCANS 1 (least intense follow-up), 61 (39.1%) to STRATCANS 2, and 29 (18.6%) to STRATCANS 3 (highest intensity). By increasing STRATCANS tier, progression rates to CPG ≥3 and any progression events were 0% and 4.6%, 3.4% and 8.6%, and 7.4% and 22.2%, respectively (p = 0.019). Modelling resource usage suggested potential reductions in appointments by 22% and MRI by 42% compared with current NICE guideline recommendations (first 12 months of AS). The study is limited by short follow-up, a relatively small cohort, and being single centre. Conclusions: A simple risk-tiered AS strategy is possible with early outcomes supporting stratified follow-up intensity. STRATCANS implementation could de-escalate follow-up in men at a low risk of progression while husbanding resources for those who need closer follow-up. Patient summary: We report a practical way to personalise follow-up for men on active surveillance for early prostate cancer. Our method may allow reductions in the follow-up burden for men at a low risk of disease change while maintaining vigilance for those at a higher risk.

Time series radiomics for the prediction of prostate cancer progression in patients on active surveillance.

Serial MRI is an essential assessment tool in prostate cancer (PCa) patients enrolled on active surveillance (AS). However, it has only moderate sensitivity for predicting histopathological tumour progression at follow-up, which is in part due to the subjective nature of its clinical reporting and variation among centres and readers. In this study, we used a long short-term memory (LSTM) recurrent neural network (RNN) to develop a time series radiomics (TSR) predictive model that analysed longitudinal changes in tumour-derived radiomic features across 297 scans from 76 AS patients, 28 with histopathological PCa progression and 48 with stable disease. Using leave-one-out cross-validation (LOOCV), we found that an LSTM-based model combining TSR and serial PSA density (AUC 0.86 [95% CI: 0.78-0.94]) significantly outperformed a model combining conventional delta-radiomics and delta-PSA density (0.75 [0.64-0.87]; p = 0.048) and achieved comparable performance to expert-performed serial MRI analysis using the Prostate Cancer Radiologic Estimation of Change in Sequential Evaluation (PRECISE) scoring system (0.84 [0.76-0.93]; p = 0.710). The proposed TSR framework, therefore, offers a feasible quantitative tool for standardising serial MRI assessment in PCa AS. It also presents a novel methodological approach to serial image analysis that can be used to support clinical decision-making in multiple scenarios, from continuous disease monitoring to treatment response evaluation. KEY POINTS: •LSTM RNN can be used to predict the outcome of PCa AS using time series changes in tumour-derived radiomic features and PSA density. •Using all available TSR features and serial PSA density yields a significantly better predictive performance compared to using just two time points within the delta-radiomics framework. •The concept of TSR can be applied to other clinical scenarios involving serial imaging, setting out a new field in AI-driven radiology research.

Evaluation of transabdominal and transperineal ultrasound-derived prostate specific antigen (PSA) density and clinical utility compared to MRI prostate volumes: A feasibility study.

PURPOSE: To investigate the accuracy of surface-based ultrasound-derived PSA-density (US-PSAD) versus gold-standard MRI-PSAD as a risk-stratification tool. METHODS: Single-centre prospective study of patients undergoing MRI for suspected prostate cancer (PCa). Four combinations of US-volumes were calculated using transperineal (TP) and transabdominal (TA) views, with triplanar measurements to calculate volume and US-PSAD. Intra-class correlation coefficient (ICC) was used to compare US and MRI volumes. Categorical comparison of MRI-PSAD and US-PSAD was performed at PSAD cut-offs <0.15, 0.15-0.20, and >0.20 ng/mL2 to assess agreement with MRI-PSAD risk-stratification decisions. RESULTS: 64 men were investigated, mean age 69 years and PSA 7.0 ng/mL. 36/64 had biopsy-confirmed prostate cancer (18 Gleason 3+3, 18 Gleason ≥3+4). Mean MRI-derived gland volume was 60 mL, compared to 56 mL for TA-US, and 65 mL TP-US. ICC demonstrated good agreement for all US volumes with MRI, with highest agreement for transabdominal US, followed by combined TA/TP volumes. Risk-stratification decisions to biopsy showed concordant agreement between triplanar MRI-PSAD and ultrasound-PSAD in 86-91% and 92-95% at PSAD thresholds of >0.15 ng/mL2 and >0.12 ng/mL2, respectively. Decision to biopsy at threshold >0.12 ng/mL2, demonstrated sensitivity ranges of 81-100%, specificity 85-100%, PPV 86-100% and NPV 83-100%. Transabdominal US provided optimal sensitivity of 100% for this clinical decision, with specificity 85%, and transperineal US provided optimal specificity of 100%, with sensitivity 87%. CONCLUSION: Transperineal-US and combined TA-TP US-derived PSA density values compare well with standard MRI-derived values and could be used to provide accurate PSAD at presentation and inform the need for further investigations.

Developing machine learning algorithms for dynamic estimation of progression during active surveillance for prostate cancer.

Active Surveillance (AS) for prostate cancer is a management option that continually monitors early disease and considers intervention if progression occurs. A robust method to incorporate "live" updates of progression risk during follow-up has hitherto been lacking. To address this, we developed a deep learning-based individualised longitudinal survival model using Dynamic-DeepHit-Lite (DDHL) that learns data-driven distribution of time-to-event outcomes. Further refining outputs, we used a reinforcement learning approach (Actor-Critic) for temporal predictive clustering (AC-TPC) to discover groups with similar time-to-event outcomes to support clinical utility. We applied these methods to data from 585 men on AS with longitudinal and comprehensive follow-up (median 4.4 years). Time-dependent C-indices and Brier scores were calculated and compared to Cox regression and landmarking methods. Both Cox and DDHL models including only baseline variables showed comparable C-indices but the DDHL model performance improved with additional follow-up data. With 3 years of data collection and 3 years follow-up the DDHL model had a C-index of 0.79 (±0.11) compared to 0.70 (±0.15) for landmarking Cox and 0.67 (±0.09) for baseline Cox only. Model calibration was good across all models tested. The AC-TPC method further discovered 4 distinct outcome-related temporal clusters with distinct progression trajectories. Those in the lowest risk cluster had negligible progression risk while those in the highest cluster had a 50% risk of progression by 5 years. In summary, we report a novel machine learning approach to inform personalised follow-up during active surveillance which improves predictive power with increasing data input over time.

Urinary symptoms and prostate cancer-the misconception that may be preventing earlier presentation and better survival outcomes.

BACKGROUND: Prostate cancer is an epidemic of the modern age, and despite efforts to improve awareness, it remains the case that mortality has hardly altered over the decades, driven largely by late presentation. There is a strong public perception that male urinary symptoms is one of the key indicators of prostate cancer, and this continues to be part of messaging from national guidelines and media health campaigns. This narrative, however, is not based on evidence and may be seriously hampering efforts to encourage early presentation. DISCUSSION: Anatomically, prostate cancer most often arises in the peripheral zone, while urinary symptoms result from compression of the urethra by prostatic enlargement more centrally. Biopsy studies show that mean prostate volume is actually lower in men found to have (early) prostate cancer compared to those with benign biopsies. This inverse relationship between prostate size and the probability of cancer is so strong that PSA density (PSA corrected for prostate volume) is known to be significantly more accurate in predicting a positive biopsy than PSA alone. Thus, this disconnect between scientific evidence and the current perception is very striking. There is also evidence that using symptoms for investigating possible cancer may lead to higher proportions of men presenting with locally advanced or metastatic disease compared to PSA testing or screening programmes. Concerns about overwhelming health care services if men are encouraged to get tested without symptoms may also be overstated, with recent newer approaches to reduce over-investigation and treatment. In this article, we explore the link between urinary symptoms and prostate cancer and propose that public and professional messaging needs to change. CONCLUSION: If rates of earlier diagnosis are to improve, we call for strong clear messaging that prostate cancer is a silent disease especially in the curable stages and men should come forward for testing regardless of whether or not they have symptoms. This should be done in parallel with other ongoing efforts to raise awareness including targeting men at highest risk due to racial ancestry or family history. While the current resurgence in interest and debate about prostate cancer screening is timely, change of this message by guideline bodies, charities and the media can be a first simple step to improving earlier presentation and hence cures rates.

Assessing the impact of MRI based diagnostics on pre-treatment disease classification and prognostic model performance in men diagnosed with new prostate cancer from an unscreened population.

INTRODUCTION: Pre-treatment risk and prognostic groups are the cornerstone for deciding management in non-metastatic prostate cancer. All however, were developed in the pre-MRI era. Here we compared categorisation of cancers using either only clinical parameters or with MRI enhanced information in men referred for suspected prostate cancer from an unscreened population. PATIENT AND METHODS: Data from men referred from primary care to our diagnostic service and with both clinical (digital rectal examination [DRE] and systematic biopsies) and MRI enhanced attributes (MRI stage and combined systematic/targeted biopsies) were used for this study. Clinical vs MRI data were contrasted for clinico-pathological and risk group re-distribution using the European Association of Urology (EAU), American Urological Association (AUA) and UK National Institute for Health Care Excellence (NICE) Cambridge Prognostic Group (CPG) models. Differences were retrofitted to a population cohort with long-term prostate cancer mortality (PCM) outcomes to simulate impact on model performance. We further contrasted individualised overall survival (OS) predictions using the Predict Prostate algorithm. RESULTS: Data from 370 men were included (median age 66y). Pre-biopsy MRI stage reassignments occurred in 7.8% (versus DRE). Image-guided biopsies increased Grade Group 2 and ≥ Grade Group 3 assignments in 2.7% and 2.9% respectively. The main change in risk groups was more high-risk cancers (6.2% increase in the EAU and AUA system, 4.3% increase in CPG4 and 1.9% CPG5). When extrapolated to a historical population-based cohort (n = 10,139) the redistribution resulted in generally lower concordance indices for PCM. The 5-tier NICE-CPG system outperformed the 4-tier AUA and 3-tier EAU models (C Index 0.70 versus 0.65 and 0.64). Using an individualised prognostic model, changes in predicted OS were small (median difference 1% and 2% at 10- and 15-years' respectively). Similarly, estimated treatment survival benefit changes were minimal (1% at both 10- and 15-years' time frame). CONCLUSION: MRI guided diagnostics does change pre-treatment risk groups assignments but the overall prognostic impact appears modest in men referred from unscreened populations. Particularly, when using more granular tiers or individualised prognostic models. Existing risk and prognostic models can continue to be used to counsel men about treatment option until long term survival outcomes are available.

Rates of Positive Abdominal Computed Tomography and Bone Scan Findings Among Men with Cambridge Prognostic Group 4 or 5 prostate cancer: A Nationwide Registry Study.

European and American guidelines recommend abdominal computed tomography (CT) and bone scans for staging of high-risk prostate cancer (PC). To improve clinical risk stratification of nonmetastatic PC a new, five-tier risk classification system has been developed, the Cambridge Prognostic Groups (CPG), in which "high-risk" PC is divided into favourable CPG 4 and unfavourable CPG 5. We used the National Prostate Cancer Register of Sweden (NPCR) to define the rates of positive CT and bone scan findings among men with CPG 4 or 5 cancer. Among men with CPG 4 and prostate-specific antigen (PSA) <50 ng/ml, only 3.6% (95% confidence interval 2.9-4.5%) of the CT scans showed regional lymph-node metastasis (N1M0), while 6.2% (95% confidence interval 5.4-7.0%) of the bone scans were positive. Rates for both were higher in the subgroups with PSA 50-99 ng/ml (10% and 15%) and with CPG 5 disease. The low positivity rate questions routine use of CT for men with CPG 4 cancer and PSA <50 ng/ml, particularly considering the poor sensitivity and specificity for detection of lymph node metastasis. The positivity rate was higher for bone scans, and as current clinical practice relies on trials using bone scans for staging (eg, to define low- versus high-volume metastatic disease), continued routine use of bone scans seems justified. Patient summary: Our analysis of data from the National Prostate Cancer Register of Sweden showed that for men with favourable high-risk prostate cancer (Cambridge Prognostic Group 4), the rate of positive computed tomography (CT) scans was low. This result suggests that CT scans may not be necessary for detecting cancer spread in men with Cambridge Prognostic Group 4 prostate cancer .

Hyperpolarised 13C-MRI identifies the emergence of a glycolytic cell population within intermediate-risk human prostate cancer.

Hyperpolarised magnetic resonance imaging (HP 13C-MRI) is an emerging clinical technique to detect [1-13C]lactate production in prostate cancer (PCa) following intravenous injection of hyperpolarised [1-13C]pyruvate. Here we differentiate clinically significant PCa from indolent disease in a low/intermediate-risk population by correlating [1-13C]lactate labelling on MRI with the percentage of Gleason pattern 4 (%GP4) disease. Using immunohistochemistry and spatial transcriptomics, we show that HP 13C-MRI predominantly measures metabolism in the epithelial compartment of the tumour, rather than the stroma. MRI-derived tumour [1-13C]lactate labelling correlated with epithelial mRNA expression of the enzyme lactate dehydrogenase (LDHA and LDHB combined), and the ratio of lactate transporter expression between the epithelial and stromal compartments (epithelium-to-stroma MCT4). We observe similar changes in MCT4, LDHA, and LDHB between tumours with primary Gleason patterns 3 and 4 in an independent TCGA cohort. Therefore, HP 13C-MRI can metabolically phenotype clinically significant disease based on underlying metabolic differences in the epithelial and stromal tumour compartments.

Serial changes in tumour measurements and apparent diffusion coefficients in prostate cancer patients on active surveillance with and without histopathological progression.

OBJECTIVE: To analyse serial changes in MRI-derived tumour measurements and apparent diffusion coefficient (ADC) values in prostate cancer (PCa) patients on active surveillance (AS) with and without histopathological disease progression. METHODS: This study included AS patients with biopsy-proven PCa with a minimum of two consecutive MR examinations and at least one repeat targeted biopsy. Tumour volumes, largest axial two-dimensional (2D) surface areas, and maximum diameters were measured on T2 weighted images (T2WI). ADC values were derived from the whole lesions, 2D areas, and small-volume regions of interest (ROIs) where tumours were most conspicuous. Areas under the ROC curve (AUCs) were calculated for combinations of T2WI and ADC parameters with optimal specificity and sensitivity. RESULTS: 60 patients (30 progressors and 30 non-progressors) were included. In progressors, T2WI-derived tumour volume, 2D surface area, and maximum tumour diameter had a median increase of +99.5%,+55.3%, and +21.7% compared to +29.2%,+8.1%, and +6.9% in non-progressors (p < 0.005 for all). Follow-up whole-volume and small-volume ROIs ADC values were significantly reduced in progressors (-11.7% and -9.5%) compared to non-progressors (-6.1% and -1.6%) (p < 0.05 for both). The combined AUC of a relative increase in maximum tumour diameter by 20% and reduction in small-volume ADC by 10% was 0.67. CONCLUSION: AS patients show significant differences in tumour measurements and ADC values between those with and without histopathological disease progression. ADVANCES IN KNOWLEDGE: This paper proposes specific clinical cut-offs for T2WI-derived maximum tumour diameter (+20%) and small-volume ADC (-10%) to predict histopathological PCa progression on AS and supplement subjective serial MRI assessment.