Role of mpMRI of the prostate in screening for prostate cancer

MicroRNA in prostate cancer: from biogenesis to applicative potential

Prostate cancer is the most common solid malignant tumor in men, characterized by high morbidity and mortality. While current screening tools, such as prostate-specific antigen (PSA) testing and digital rectal examination, are available for early detection of prostate cancer, their sensitivity and specificity are limited. Tissue puncture biopsy, although capable of offering a definitive diagnosis, has poor positive predictive rates and burdens the patient more. Therefore, more reliable molecular diagnostic tools for prostate cancer urgently need to be developed. In recent years, microRNAs (miRNAs) have attracted much attention in prostate cancer research. miRNAs are extensively engaged in biological processes such as cell proliferation, differentiation, apoptosis, migration, and invasion by modulating gene expression post-transcriptionally. Dysregulation of miRNA expression in cancer is considered a critical factor in tumorigenesis and progression. This review first briefly introduces the biogenesis of miRNAs and their functions in cancer, then focuses on tumor-promoting miRNAs and tumor-suppressor miRNAs in prostate cancer. Finally, the potential application of miRNAs as multifunctional tools for cancer diagnosis, prognostic assessment, and therapy is discussed in detail. The concluding section summarizes the major points of the review and the challenges ahead.

Multiparametric MRI for characterization of the tumour microenvironment

Our understanding of tumour biology has evolved over the past decades and cancer is now viewed as a complex ecosystem with interactions between various cellular and non-cellular components within the tumour microenvironment (TME) at multiple scales. However, morphological imaging remains the mainstay of tumour staging and assessment of response to therapy, and the characterization of the TME with non-invasive imaging has not yet entered routine clinical practice. By combining multiple MRI sequences, each providing different but complementary information about the TME, multiparametric MRI (mpMRI) enables non-invasive assessment of molecular and cellular features within the TME, including their spatial and temporal heterogeneity. With an increasing number of advanced MRI techniques bridging the gap between preclinical and clinical applications, mpMRI could ultimately guide the selection of treatment approaches, precisely tailored to each individual patient, tumour and therapeutic modality. In this Review, we describe the evolving role of mpMRI in the non-invasive characterization of the TME, outline its applications for cancer detection, staging and assessment of response to therapy, and discuss considerations and challenges for its use in future medical applications, including personalized integrated diagnostics.

A radiomics based method for prediction of prostate cancer Gleason score using enlarged region of interest

BACKGROUND

Prostate cancer (PCa) is one of the most common cancers in men worldwide, and its timely diagnosis and treatment are becoming increasingly important. MRI is in increasing use to diagnose cancer and to distinguish between non-clinically significant and clinically significant PCa, leading to more precise diagnosis and treatment. The purpose of this study is to present a radiomics-based method for determining the Gleason score (GS) for PCa using tumour heterogeneity on multiparametric MRI (mp-MRI).

METHODS

Twenty-six patients with biopsy-proven PCa were included in this study. The quantitative T2 values, apparent diffusion coefficient (ADC) and signal enhancement rates (α) were calculated using multi-echo T2 images, diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MRI (DCE-MRI), for the annotated region of interests (ROI). After texture feature analysis, ROI range expansion and feature filtering was performed. Then obtained data were put into support vector machine (SVM), K-Nearest Neighbor (KNN) and other classifiers for binary classification.

RESULTS

The highest classification accuracy was 73.96% for distinguishing between clinically significant (Gleason 3 + 4 and above) and non-significant cancers (Gleason 3 + 3) and 83.72% for distinguishing between Gleason 3 + 4 from Gleason 4 + 3 and above, which was achieved using initial ROIs drawn by the radiologists. The accuracy improved when using expanded ROIs to 80.67% using SVM and 88.42% using Bayesian classification for distinguishing between clinically significant and non-significant cancers and Gleason 3 + 4 from Gleason 4 + 3 and above, respectively.

CONCLUSIONS

Our results indicate the research significance and value of this study for determining the GS for prostate cancer using the expansion of the ROI region.

Magnetic resonance imaging target fusion biopsy vs. transrectal ultrasound-guided biopsy - A comparative study of ISUP score upgrading risk in the final radical prostatectomy specimen

Objectives: The aim of this study was to com-pare the risk of International Society of Urological Pathology (ISUP) score upgrading between magnetic resonance imaging targeted fusion biopsy (MRI-TB) and tran-srectal ultrasound-guided biopsy (TRUS-B) in the final radical prostatectomy (RP) specimen pathological report.Materials and methods: This retrospective single center study included 51 patients with prostate cancer (PCa) diagnosed with MRI-TB and 83 patients diagnosed with TRUS-B between October/2019 and July/2021. We compared the rates of ISUP score upgrading between both groups after robotic-assisted radi-cal prostatectomy (RARP) and the specific transition of each ISUP score based on biopsy modality. The rate of ISUP score concordance and downgrading were also assessed. To define the intra and interobserver concordance for each ISUP score in biopsy and RP specimen for each biopsy modality, the Cohen’s Kappa coefficient was calculated. ISUP scores and biopsy modal-ity were selected for multivariate analysis and a logistic regres-sion model was built to provide independent risk factors of ISUP score upgrading.Results: The difference of the rate of upgrading between MRI-TB group and TRUS-B group was statistically significant (p = 0.007) with 42.2% of patients of TRUS-B group experiencing an upgrade in their ISUP score while only 19.6% in MRI-TB group. Concordance and downgrading rates did not statistically differ between the two groups. Strength of concordance using Cohen’s Kappa coefficient was fair in both groups but higher in MRI-TB group (TRUS-B group k = 0.230; p < 0.001; concordance: 47%vs. MRI/TB group k = 0.438; p < 0.001; concordance: 62.7%). Biopsy modality and ISUP 1 on biopsy were independent predic-tors of ISUP upgrading after RP.Conclusions: MRI-TB is highly accurate with lower risk of PCa upgrading after RP than TRUS-B. Patients with ISUP 1 on biopsy have greater susceptibility to upgrading their ISUP score.

Transrectal Ultrasound in Prostate Cancer: Current Utilization, Integration with mpMRI, HIFU and Other Emerging Applications

Transrectal ultrasound (TRUS) has been an invaluable tool in the assessment of prostate size, anatomy and aiding in prostate cancer (PCa) diagnosis for decades. Emerging techniques warrant an investigation into the efficacy of TRUS, how it compares to new techniques, and options to increase the accuracy of prostate cancer diagnosis. Currently, TRUS is used to guide both transrectal and transperineal biopsy approaches with similar cancer detection rates, but lower rates of infection have been reported with the transperineal approach, while lower rates of urinary retention are often reported with the transrectal approach. Multiparametric MRI has substantial benefits for prostate cancer diagnosis and triage such as lesion location, grading, and can be combined with TRUS to perform fusion biopsies targeting specific lesions. Micro-ultrasound generates higher resolution images that traditional ultrasound and has been shown effective at diagnosing PCa, giving it the potential to become a future standard of care. Finally, high-intensity focused ultrasound focal therapy administered via TRUS has been shown to offer safe and effective short-term oncological control for localized disease with low morbidity, and the precise nature makes it a viable option for salvage and repeat therapy.

Diffusion Restriction Comparison between Gleason 4 Fused Glands and Cribriform Glands within Patient Using Whole-Mount Prostate Pathology as Ground Truth

The presence and extent of cribriform patterned Gleason 4 (G4) glands are associated with poor prognosis following radical prostatectomy. This study used whole-mount prostate histology and multiparametric magnetic resonance imaging (MP-MRI) to evaluate diffusion differences in G4 gland morphology. Fourty-eight patients underwent MP-MRI prior to prostatectomy, of whom 22 patients had regions of both G4 cribriform glands and G4 fused glands (G4CG and G4FG, respectively). After surgery, the prostate was sliced using custom, patient-specific 3D-printed slicing jigs modeled according to the T2-weighted MR image, processed, and embedded in paraffin. Whole-mount hematoxylin and eosin-stained slides were annotated by our urologic pathologist and digitally contoured to differentiate the lumen, epithelium, and stroma. Digitized slides were co-registered to the T2-weighted MRI scan. Linear mixed models were fitted to the MP-MRI data to consider the different hierarchical structures at the patient and slide level. We found that Gleason 4 cribriform glands were more diffusion-restricted than fused glands.

Use of TDI during MRI/US fusion-guided biopsy for suspected prostate cancer

BACKGROUND

Tissue Doppler imaging (TDI) uses the Doppler principle to quantify the movement of biological tissues.

OBJECTIVE

To investigate the contribution of TDI parameters derived during magnetic resonance imaging and ultrasound (MRI/US) fusion-guided biopsy for prostate cancer (PCa) discrimination.

METHODS

From March 2016 to Dec. 2018, 75 men with suspected PCa prospectively underwent fusion-guided prostate biopsy. TDI overlaid on predefined target lesion were compared to the confirmed contralateral tumor-free area of the prostate gland (using Image J). Diagnostic value of TDI parameters was assessed using histopathology as standard of reference.

RESULTS

Thirty-seven patients were diagnosed with PCa (49.3%), among them 27 with clinically significant PCa (Gleason score >  3 + 3 = 6 (ISUP 1). The LES/REF ratio was lower in confirmed PCa patients compared to patients without PCa (0.42, IQR, 0.22-0.59 vs. 0.52, IQR, 0.40-0.72, p = 0.017). TDI parameters allowed differentiation of low-risk from high-to-intermediate-risk PCa (ISUP 2 versus ISUP 3) based on lower pixel counts within the target ROI (1340, IQR 596-2430 vs. 2687, IQR 2453-3216, p = 0.004), lower pixel percentage (16.4 IQR 11.4-29.5 vs. 27.3, IQR 22.1-39.5; p = 0.005), and lower LES/REF ratios (0.29, IQR 0.19-0.51 vs. 0.52, IQR 0.47-0.74, p = 0.001).

CONCLUSION

TDI of prostate lesions prelocated by MRI discriminates between cancerous and noncancerous lesions and further seems to enable characterization of PCa aggressiveness. This widely available US technique may improve confidence in target lesion localization for tissue sampling.

Magnetic Resonance Imaging Radiomics-Based Machine Learning Prediction of Clinically Significant Prostate Cancer in Equivocal PI-RADS 3 Lesions

BACKGROUND

While Prostate Imaging Reporting and Data System (PI-RADS) 4 and 5 lesions typically warrant prostate biopsy and PI-RADS 1 and 2 lesions may be safely observed, PI-RADS 3 lesions are equivocal.

PURPOSE

To construct and cross-validate a machine learning model based on radiomics features from T₂ -weighted imaging (T₂ WI) of PI-RADS 3 lesions to identify clinically significant prostate cancer (csPCa), that is, pathological Grade Group ≥ 2.

STUDY TYPE

Single-center retrospective study.

POPULATION

A total of 240 patients were included (training cohort, n = 188, age range 43-82 years; test cohort, n = 52, age range 41-79 years). Eligibility criteria were 1) magnetic resonance imaging (MRI)-targeted biopsy between 2015 and 2020; 2) PI-RADS 3 index lesion identified on multiparametric MRI; (3) biopsy performed within 1 year of MRI. The percentages of csPCa lesions were 10.6% and 15.4% in the training and test cohorts, respectively.

FIELD STRENGTH/SEQUENCE

A 3 T; T₂ WI turbo-spin echo, diffusion-weighted spin-echo echo planar imaging, dynamic contrast-enhanced MRI with time-resolved T1-weighted imaging.

ASSESSMENT

Multislice volumes-of-interest (VOIs) were drawn in the PI-RADS 3 index lesions on T₂ WI. A total of 107 radiomics features (first-order histogram and second-order texture) were extracted from the segmented lesions.

STATISTICAL TESTS

A random forest classifier using the radiomics features as input was trained and validated for prediction of csPCa. The performance of the machine learning classifier, prostate specific antigen (PSA) density, and prostate volume for csPCa prediction was evaluated using receiver operating characteristic (ROC) analysis.

RESULTS

The trained random forest classifier constructed from the T₂ WI radiomics features good and statistically significant area-under-the-curves (AUCs) of 0.76 (P = 0.022) for prediction of csPCa in the test set. Prostate volume and PSA density showed moderate and nonsignificant performance (AUC 0.62, P = 0.275 and 0.61, P = 0.348, respectively) for csPCa prediction in the test set.

CONCLUSION

The machine learning classifier based on T₂ WI radiomic features demonstrated good performance for prediction of csPCa in PI-RADS 3 lesions.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: 2.

Prostate Cancer Screening with PSA: Ten Years' Experience of Population Based Early Prostate Cancer Detection Programme in Lithuania

The aim of this study is to report key performance estimates from the ten years of a population-based prostate cancer screening programme in Lithuania. Retrospective analysis of screening activities recorded in 2006–2015 among men aged 50–74 years was performed. We estimated screening coverage, cancer detection rate, compliance to biopsy, and positive predictive values in each screening round inside and outside the target population. In the first 10 years of screening, 16,061 prostate cancer cases were registered within the screening programme, 10,202 were observed among screened men but reported outside the screening programme, and 1455 prostate cancers were observed in a screening-naïve population. Screening cover reached up to 45.5% of the target population in the recent rounds. The proportion of prostate specific antigen (PSA) test-positive men decreased from 16.9% in 2006 to 10.7% in 2014–2015. Up to 40.0% of PSA test-positive men received a biopsy, of whom 42.0% were positive for prostate cancer. The cancer detection rate was 10.4−15.0% among PSA test-positives and 1.4–1.9% among screened individuals. Screening participants were more likely to be diagnosed with organ-confined disease as compared to non-participants. Despite the unorganized screening practices being employed and low coverage per screening round, 70% of the target population were screened at least once in the first 10 years of screening.

Prostate Cancer Screening Recommendations for General and Specific Populations in the Western Nations

There is a chaotic scenario that exists in the field of prostate cancer (PCa) screening. To balance goals, such as decreasing mortality, avoiding unnecessary procedures, and decreasing the cost of medical care, the pendulum seems to have swung to the side of more restricted screening. The decrease in PCa screening has led to a slowly creeping decline in the favourable outcomes that existed among patients with PCa. If a potential patient or a family member is trying to get clear guidance about PCa screening by searching the internet, they will end up confused by several recommendations from many organisations. It is even more challenging to obtain any clarity about PCa screening for special populations, such as those with a family history of PCa, those of African descent/African Americans, and the elderly. The advent of genomic medicine and precision medicine is an opportunity to identify those at a very high risk of developing aggressive PCa, so that PCa screening can be more actively undertaken among them. In this paper, the authors review the current recommendations by different entities and summarise emerging molecular markers that may help bring clarity to PCa screening. The authors predict that concrete, consensual guidelines will emerge in less than one decade. Meanwhile, this article suggests intermediary steps that will help save lives from PCa mortality, especially for under-represented populations. This paper is a catalyst to stimulate further discussion and serves as a guide to noncancer-specialists for the near future as precision medicine progresses to better understand risk–benefit and cost–benefit ratios in PCa screening.

Update of the Standard Operating Procedure on the Use of Multiparametric Magnetic Resonance Imaging for the Diagnosis, Staging and Management of Prostate Cancer

PURPOSE

We update the prior standard operating procedure for magnetic resonance imaging of the prostate, and summarize the available data about the technique and clinical use for the diagnosis and management of prostate cancer. This update includes practical recommendations on the use of magnetic resonance imaging for screening, diagnosis, staging, treatment and surveillance of prostate cancer.

MATERIALS AND METHODS

A panel of clinicians from the American Urological Association and Society of Abdominal Radiology with expertise in the diagnosis and management of prostate cancer evaluated the current published literature on the use and technique of magnetic resonance imaging for this disease. When adequate studies were available for analysis, recommendations were made on the basis of data and when adequate studies were not available, recommendations were made on the basis of expert consensus.

RESULTS

Prostate magnetic resonance imaging should be performed according to technical specifications and standards, and interpreted according to standard reporting. Data support its use in men with a previous negative biopsy and ongoing concerns about increased risk of prostate cancer. Sufficient data now exist to support the recommendation of magnetic resonance imaging before prostate biopsy in all men who have no history of biopsy. Currently, the evidence is insufficient to recommend magnetic resonance imaging for screening, staging or surveillance of prostate cancer.

CONCLUSIONS

Use of prostate magnetic resonance imaging in the risk stratification, diagnosis and treatment pathway of men with prostate cancer is expanding. When quality prostate imaging is obtained, current evidence now supports its use in men at risk of harboring prostate cancer and who have not undergone a previous biopsy, as well as in men with an increasing prostate specific antigen following an initial negative standard prostate biopsy procedure.

Prostate Cancer Epithelial Mesenchymal Transition by TGF-β1 exposure monitored with a Photonic Crystal Biosensor

During prostate cancer progression, cancerous epithelial cells can undergo epithelial-mesenchymal transition (EMT). EMT is a crucial mechanism for the invasion and metastasis of epithelial tumors characterized by the loss of cell-cell adhesion and increased cell mobility. It is associated with biochemical changes such as epithelial cell markers E-cadherin and occludins being down-regulated, and mesenchymal markers vimentin and N-cadherin being upregulated. These changes in protein expression, specifically in the cell membrane, may be monitored via biophysical principles, such as changes in the refractive index (RI) of the cell membrane. In our previous research, we demonstrated the feasibility of using cellular RI as a unique contrast parameter to accomplish label-free detection of prostate cancer cells. In this paper, we report the use of our Photonic-Crystal biosensor in a Total-Internal-Reflection (PC-TIR) configuration to construct a label-free biosensing system, which allows for ultra-sensitive quantification of the changes in cellular RI due to EMT. We induced prostate cancer cells to undergo EMT by exposing these cells to soluble Transforming Growth Factor Beta 1 (TGF-β1). The biophysical characteristics of the cellular RI were quantified extensively in comparison to non-induced cancer cells. Our study shows promising clinical potential in utilizing the PC-TIR biosensing system not only to detect prostate cancer cells, but also to evaluate changes in prostate cancer cells due to EMT.

The Use of Multiparametric Magnetic Resonance Imaging (mpMRI) in the Detection, Evaluation, and Surveillance of Clinically Significant Prostate Cancer (csPCa)

PURPOSE OF REVIEW

With the long-standing controversy surrounding the use of prostate-specific antigen (PSA) for the detection, evaluation, and surveillance of prostate cancer, there is a need for a minimally invasive technique to identify and risk-stratify these patients. Additionally, in an effort to reduce the number of unnecessary biopsies and identify clinically significant prostate cancer (csPCa), there has been a shift in practice towards the use of multiparametric magnetic resonance imaging (mpMRI) in conjunction with decision-making regarding prostate cancer diagnosis and management. In the current review, we summarize the data regarding the use of mpMRI in the detection, evaluation, and surveillance of csPCa.

RECENT FINDINGS

Recent prospective clinical trials have determined that a pre-biopsy mpMRI may rule out insignificant prostate cancers, thereby reducing the number of patients who require a biopsy. The anatomic information gathered from these pre-biopsy mpMRI performed during MRI fusion biopsy in csPCa increases the accuracy of pathologic staging in terms of Gleason scores. In regard to active surveillance, prospective trials suggest little to no clinical utility for mpMRI and fusion biopsy in the surveillance of prostate cancer despite conflicting findings from retrospective studies. Recent trials suggest that mpMRI can play an important role in the detection and evaluation of csPCa. The ideal role for mpMRI in active surveillance remains limited.

Prostate cancer detection from multi-institution multiparametric MRIs using deep convolutional neural networks

Multiparametric magnetic resonance imaging (mpMRI) of the prostate aids in early diagnosis of prostate cancer, but is difficult to interpret and subject to interreader variability. Our objective is to generate probability maps, overlaid on original mpMRI images to help radiologists identify where a cancer is suspected as a computer-aided diagnostic (CAD). We optimized the holistically nested edge detection (HED) deep convolutional neural network. Our dataset contains T2, apparent diffusion coefficient, and high b -value images from 186 patients across six institutions worldwide: 92 with an endorectal coil (ERC) and 94 without. Ground-truth was based on tumor segmentations manually drawn by expert radiologists based on histologic evidence of cancer. The training set consisted of 120 patients and the validation set and test set included 19 and 47, respectively. Slice-level probability maps are evaluated at the lesion level of analysis. The best model: HED using 5 × 5 convolutional kernels, batch normalization, and optimized using Adam. This CAD performed significantly better ( p < 0.001 ) in the peripheral zone ( AUC = 0.94 ± 0.01 ) than the transition zone. It outperforms a previous CAD from our group in a head-to-head comparison on the same ERC-only test cases ( AUC = 0.97 ± 0.01 ; p < 0.001 ). Our CAD establishes a state-of-the-art performance for predicting prostate cancer lesions on mpMRIs.

Emergence of "Big Data" and Its Potential and Current Limitations in Medical Imaging

Although electronic imaging was performed in the early 1950s in nuclear medicine, it was the introduction of computed tomography in 1972 that caused a revolution in medical imaging in that it marked the beginning of the inevitable transformation to digital imaging. This transformation is now more or less complete. While initially these CT images were relatively small, comprised of only about 6400 pixels per slice, the steady move toward higher spatial resolution, multislice imaging, digital radiography, and fluoroscopy rapidly increased the size of images and the amount of data required to be stored, processed, displayed, and moved about in a medical imaging department. The more recent introduction of digital pathology with submicron-sized pixels and the need for color further increases these demands. Rising work volumes in hospital, a push for cost containment, and a move toward greater precision in diagnosis and treatment of disease all work together to motivate the development of automated image analysis algorithms and techniques to improve efficiencies in in vivo imaging and pathology. This may require bringing together information from different imaging and nonimaging sources within the institution. While technological development has provided practical means for storage of the burgeoning data load and the use of multiple processors and high-speed networks has enabled more sophisticated analysis locally or in the cloud, challenges remain in terms of the ability to integrate data from different systems, the development of appropriately annotated image bases for training and testing of algorithms, and issues around privacy and ownership in obtaining access to patient-related data.

Exploration of the diagnostic value and molecular mechanism of miR‑1 in prostate cancer: A study based on meta‑analyses and bioinformatics

Prostate cancer (PCa) remains a principal issue to be addressed in male cancer-associated mortality. Therefore, the present study aimed to examine the clinical value and associated molecular mechanism of microRNA (miR)-1 in PCa. A meta-analysis was conducted to evaluate the diagnosis of miR-1 in PCa via Gene Expression Omnibus and ArrayExpress datasets, The Cancer Genome Atlas miR-1 expression data and published literature. It was identified that expression of miR-1 was significantly downregulated in PCa. Decreased miR-1 expression possessed moderate diagnostic value, with area under the curve, sensitivity, specificity and odds ratio values at 0.73, 0.77, 0.57 and 4.60, respectively. Using bioinformatics methods, it was revealed that a number of pathways, including the ‘androgen receptor signaling pathway’, ‘androgen receptor activity’, ‘transcription factor binding’ and ‘protein processing in the endoplasmic reticulum’, were important in PCa. A total of seven hub genes, including phosphoribosylaminoimidazole carboxylase and phosphoribosylaminoimidazolesuccin ocarboxamide synthase (PAICS), cadherin 1 (CDH1), SRC proto-oncogene, non-receptor tyrosine kinase, twist family bHLH transcription factor 1 (TWIST1), ZW10 interacting kinetochore protein (ZWINT), PCNA clamp associated factor (KIAA0101) and androgen receptor, among which, five (PAICS, CDH1, TWIST1, ZWINT and KIAA0101) were significantly upregulated and negatively correlated with miR-1, were identified as key miR-1 target genes in PCa. Additionally, it was investigated whether miR-1 and its hub genes were associated with clinical features, including age, tumor status, residual tumor, lymph node metastasis, pathological T stage and prostate specific antigen level. Collectively the results suggest that miR-1 may be involved in the progression of PCa, and consequently be a promising diagnostic marker. The ‘androgen receptor signaling pathway’, ‘androgen receptor activity’, ‘transcription factor binding’ and ‘protein processing in the endoplasmic reticulum’ may be crucial interactive pathways in PCa. Furthermore, PAICS, CDH1, TWIST1, ZWINT and KIAA0101 may serve as crucial miR-1 target genes in PCa.

Prostate cancer screening-when to start and how to screen?

Prostate-specific antigen (PSA) screening reduces prostate cancer (PCa) mortality; however such screening may lead to harm in terms of overdiagnosis and overtreatment. Therefore, upfront shared decision making involving a discussion about pros and cons between a physician and a patient is crucial. Total PSA remains the most commonly used screening tool and is a strong predictor of future life-threatening PCa. Currently there is no strong consensus on the age at which to start PSA screening. Most guidelines recommend PSA screening to start no later than at age 55 and involve well-informed men in good health and a life expectancy of at least 10–15 years. Some suggest to start screening in early midlife for men with familial predisposition and men of African-American descent. Others suggest starting conversations at age 45 for all men. Re-screening intervals can be risk-stratified as guided by the man’s age, general health and PSA-value; longer intervals for those at lower risk and shorter intervals for those at higher risk. Overdiagnosis and unnecessary biopsies can be reduced using reflex tests. Magnetic resonance imaging in the pre-diagnostic setting holds promise in pilot studies and large-scale prospective studies are ongoing.