Tag: mpMRI

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Residents’ podcast: Implementation of mpMRI technology for evaluation of PCa in the clinic

February 4, 2019/by Giulia Lane & Kyle Johnson

Giulia Lane M.D. is a Fellow in Neuro-urology and Pelvic Reconstruction in the Department of Urology at the University of Michigan; Kyle Johnson is a Urology Resident in the same department.

In this podcast they discuss the following BJUI Article of the Month:

Implementation of multiparametric magnetic resonance imaging technology for evaluation of patients with suspicion for prostate cancer in the clinical practice setting

Abstract

Objectives

To investigate the impact of implementing magnetic resonance imaging (MRI) and ultrasonography fusion technology on biopsy and prostate cancer (PCa) detection rates in men presenting with clinical suspicion for PCa in the clinical practice setting.

Patients and Methods

We performed a review of 1 808 consecutive men referred for elevated prostate‐specific antigen (PSA) level between 2011 and 2014. The study population was divided into two groups based on whether MRI was used as a risk stratification tool. Univariable and multivariable analyses of biopsy rates and overall and clinically significant PCa detection rates between groups were performed.

Results

The MRI and PSA‐only groups consisted of 1 020 and 788 patients, respectively. A total of 465 patients (45.6%) in the MRI group and 442 (56.1%) in the PSA‐only group underwent biopsy, corresponding to an 18.7% decrease in the proportion of patients receiving biopsy in the MRI group (P < 0.001). Overall PCa (56.8% vs 40.7%; P < 0.001) and clinically significant PCa detection (47.3% vs 31.0%; P < 0.001) was significantly higher in the MRI vs the PSA‐only group. In logistic regression analyses, the odds of overall PCa detection (odds ratio [OR] 1.74, 95% confidence interval [CI] 1.29–2.35; P < 0.001) and clinically significant PCa detection (OR 2.04, 95% CI 1.48–2.80; P < 0.001) were higher in the MRI than in the PSA‐only group after adjusting for clinically relevant PCa variables.

Conclusion

Among men presenting with clinical suspicion for PCa, addition of MRI increases detection of clinically significant cancers while reducing prostate biopsy rates when implemented in a clinical practice setting.

Read the full article

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Article of the Week: A mpMRI-based risk model to determine the risk of prostate cancer prior to biopsy

December 13, 2017/by admin Z.9

Every Week the Editor-in-Chief selects an Article of the Week from the current issue of BJUI. The abstract is reproduced below and you can click on the button to read the full article, which is freely available to all readers for at least 30 days from the time of this post.

In addition to the article itself, there is an accompanying editorial written by a prominent member of the urological community. This blog is intended to provoke comment and discussion and we invite you to use the comment tools at the bottom of each post to join the conversation.

If you only have time to read one article this week, it should be this one.

A multiparametric magnetic resonance imaging-based risk model to determine the risk of significant prostate cancer prior to biopsy

Pim J. van Leeuwen*†, Andrew Hayen‡, James E. Thompson*†‡, Daniel Moses§, Ron Shnier§, Maret Bohm†, Magdaline Abuodha†, Anne-Maree Haynes†, Francis Ting*†‡, Jelle Barentsz¶, Monique Roobol**, Justin Vass††, Krishan Rasiah††, Warick Delprado‡‡ and Phillip D. Stricker*†‡

*St. Vincent’s Prostate Cancer Centre, †Garvan Institute of Medical Research/The Kinghorn Cancer Centre, Darlinghurst, ‡School of Public Health and Community Medicine, §School of Medicine, University of New South Wales, Kensington, New South Wales, Australia, ¶Department of Radiology and Nuclear Medicine, Radboud University Medical Centre, Nijmegen, **Department of Urology, Erasmus University Medical Center, Rotterdam, the Netherlands, ††Department of Urology, Royal North Shore Private Hospital, St Leonards, and ‡‡Douglass Hanly Moir Pathology and University of Notre Dame, Darlinghurst, New South Wales, Australia

Read the full article

Abstract

Objective

To develop and externally validate a predictive model for detection of significant prostate cancer.

Patients and Methods

Development of the model was based on a prosp ctive cohort including 393 men who underwent multiparametric magnetic resonance imaging (mpMRI) before biopsy. External validity of the model was then examined retrospectively in 198 men from a separate institution whom underwent mpMRI followed by biopsy for abnormal prostate-specific antigen (PSA) level or digital rectal examination (DRE). A model was developed with age, PSA level, DRE, prostate volume, previous biopsy, and Prostate Imaging Reporting and Data System (PIRADS) score, as predictors for significant prostate cancer (Gleason 7 with >5% grade 4, ≥20% cores positive or ≥7 mm of cancer in any core). Probability was studied via logistic regression. Discriminatory performance was quantified by concordance statistics and internally validated with bootstrap resampling.

Results

In all, 393 men had complete data and 149 (37.9%) had significant prostate cancer. While the variable model had good accuracy in predicting significant prostate cancer, area under the curve (AUC) of 0.80, the advanced model (incorporating mpMRI) had a significantly higher AUC of 0.88 (P < 0.001). The model was well calibrated in internal and external validation. Decision analysis showed that use of the advanced model in practice would improve biopsy outcome predictions. Clinical application of the model would reduce 28% of biopsies, whilst missing 2.6% significant prostate cancer.

Conclusions

Individualised risk assessment of significant prostate cancer using a predictive model that incorporates mpMRI PIRADS score and clinical data allows a considerable reduction in unnecessary biopsies and reduction of the risk of over-detection of insignificant prostate cancer at the cost of a very small increase in the number of significant cancers missed.

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Editorial: Novel risk stratification nomograms for counseling patients on the need for prostate biopsy

December 13, 2017/by admin Z.9

Contemporary recommendations for prostate screening incorporate the measurement of serum PSA levels into shared decision making [1]. PSA is limited by a low specificity for prostate cancer and exposes a certain number of men to unnecessary prostate biopsies. Moreover, it has been attributed to an over-diagnosis and over treatment of this disease, especially in indolent cancer that may never affect a man’s longevity [2].

Prostate cancer risk stratification and aggressiveness is necessary in both the pre-biopsy clinical counselling, as well as the decision-making process. It is clear that such an important approach cannot be accomplished based on PSA alone. In order to enhance prostate cancer screening and detection, other clinical variables such as PSA density, prostate volume, percentage free PSA, and DRE, are routinely considered in conjunction with PSA for determining the need for prostate biopsy.

Increasing evidence supports the use of MRI in prostate cancer detection when used as a localisation tool to guide MRI-targeted biopsy techniques such as MRI-ultrasonography fusion-targeted biopsy [3-5]. Pre-biopsy MRI not only allows accurate tumour localisation, but also provides an assessment of cancer suspicion using an MRI suspicion score, and thus provides accurate prediction of the likelihood of prostate cancer on prostate biopsy [6].

In this study, van Leeuwen et al. [7] developed and externally validated a set of nomograms predicting clinically significant prostate cancer by incorporating prostate MRI. The performance characteristics of the nomograms were maximised by inclusion of MRI results. The authors determined that clinical application of the model would reduce 28% of biopsies, while missing 2.6% of clinically significant prostate cancer. Ultimately incorporating these nomograms into the clinical decision-making process could result in a considerable reduction in unnecessary biopsies and reduction in the risk of over-detection of clinically insignificant disease at the cost of a small increase in the number of significant cancers missed.

The authors should be commended for their predictive nomograms, in that they may further aid in the decision to perform biopsy in men with clinical suspicion of prostate cancer. However, the findings of this study should be interpreted with caution. In formulating nomograms, the obvious clinical goal is the creation of a tool that improves the selection of men in need of biopsy. Unless nomograms are derived from general ‘at risk’ populations, including men with low- and high-risk of prostate cancer, the tool may be limited in its prediction. As an example, if all men in the training cohort have an elevated PSA level, the predictive value of PSA in the nomogram may be reduced. In this case, the training and validation cohort are not well described, but it seems to be a referral population, and the PSA range is relatively narrow. As such, it’s applicability to all men presenting for prostate cancer may be questionable.

We also have had difficulty modelling a nomogram from our MRI-targeted biopsy dataset because the power of MRI-suspicion score in predicting cancer tends to minimise the effect of other variables such as PSA, age, and gland size. The authors did not compare their multivariable predictive models to MRI alone, and this may have been the most relevant comparison. In this study, the gland size and PSA level contribute significantly to the nomogram score, but one might question the findings. For example, a man with a Prostate Imaging Reporting and Data System (PI-RADS) score of 4 or 5, a large gland and a low PSA level, has a similar or lower risk as a man with a PSA level of 15 ng/mL, a moderate gland, and a PI-RADS score of 3. This is not consistent with our clinical experience and draws concern in the reliability of the nomogram at extremes of PSA and age. Men with PI-RADS 5 have high rates of clinically significant prostate cancer, regardless of PSA or age. This also may reflect variability in the predictive accuracy of MRI depending upon MRI interpretation.

Another limitation of the study, as the authors cite, is that patients were biopsied using a transperineal mapping with a median of 30 cores. This biopsy strategy is not routinely used in most institutions, and consequently limits the generalisability of the nomograms.

Selective use of prostate biopsy among men with elevated PSA levels through further refinement of cancer risk is highly desirable. The novel risk stratification nomograms developed by van Leeuwen et al. [7] add to the tools we may use to counsel our patients on the need for prostate biopsy. Further evaluation of these nomograms on additional independent patient cohorts is warranted prior to implementation in clinical practice.

Marc A. Bjurlin* and Samir S. Taneja†

*Division of Urology, Department of Surgery, NYU Lutheran Medical Center, NYU Langone Health System, New York, NY, USA and †Division of Urologic Oncology, Department of Urology, NYU Langone Medical Center, New York, NY, US

References

1 Carter HB, Albertsen PC, Barry MJ et al. Early detection of prostate cancer: AUA Guideline. J Urol2013; 190: 419–26

2 Loeb S, Bjurlin MA, Nicholson J et al. Overdiagnosis and overtreatment of prostate cancer. Eur Urol

2014; 65: 1046–55

3 Mendhiratta N, Meng X, Rosenkrantz AB et al. Prebiopsy MRI and MRI-ultrasound fusion-targeted prostate biopsy in men with previous negative biopsies: impact on repeat biopsy strategies. Urology 2015; 86: 1192–8

4 Mendhiratta N, Rosenkrantz AB, Meng X et al. Magnetic resonance imaging-ultrasound fusion-targeted prostate biopsy in a consecutive cohort of men with no previous biopsy: reduction of over-detection through improved risk stratifi cation. J Urol 2015; 194: 1601–6

5 Meng X, Rosenkrantz AB, Mendhiratta N et al. Relationship between prebiopsy multiparametric magnetic resonance imaging (MRI), biopsy indication, and MRI-ultrasound fusion-targeted prostate biopsy outcomes. Eur Urol 2016; 69: 512–17

6 Kuru TH, Roethke MC, Rieker P et al.Histology core-specific evaluation of the European Society of Urogenital Radiology (ESUR) standardised scoring system of multiparametric magnetic resonance imaging (mpMRI) of the prostate. BJU Int2013; 112: 1080–7

7 van Leeuwen PJ, Hayan A, Thompson JE et al. A multiparametric magnetic resonance imaging-based risk model to determine the risk of significant prostate cancer prior to biopsy. BJU Int 2017; 120: 774–8

Article of the Week: 3-Tesla mpMRI and TRUS-Bx in PCa patients on AS

March 29, 2017/by admin Z.9

Every week the Editor-in-Chief selects an Article of the Week from the current issue of BJUI. The abstract is reproduced below and you can click on the button to read the full article, which is freely available to all readers for at least 30 days from the time of this post.

If you only have time to read one article this week, it should be this one.

Value of 3-Tesla multiparametric magnetic resonance imaging and targeted biopsy for improved risk stratification in patients considered for active surveillance

Rodrigo R. Pessoa*, Publio C. Viana†, Romulo L. Mattedi‡, Giuliano B. Guglielmetti*, Mauricio D. Cordeiro*, Rafael F. Coelho*, William C. Nahas* and Miguel Srougi*

Departments of *Urology, †Diagnostic and Interventional Radiology, and ‡Department of Pathology, Instituto do Cancer, Universidade de Sao Paulo Faculdade de Medicina Hospital das Clinicas, Sao Paulo, SP, Brazil

Read the full article

Abstract

Objective

To evaluate the role of multiparametric magnetic resonance imaging (mpMRI) of the prostate and transrectal ultrasonography guided biopsy (TRUS-Bx) with visual estimation in early risk stratification of patients with prostate cancer on active surveillance (AS).

Patients and Methods

Patients with low-risk, low-grade, localised prostate cancer were prospectively enrolled and submitted to a 3-T 16-channel cardiac surface coil mpMRI of the prostate and confirmatory biopsy (CBx), which included a standard biopsy (SBx) and visual estimation-guided TRUS-Bx. Cancer-suspicious regions were defined using Prostate Imaging Reporting and Data System (PI-RADS) scores. Reclassification occurred if CBx confirmed the presence of a Gleason score ≥7, greater than three positive fragments, or ≥50% involvement of any core. The performance of mpMRI for the prediction of CBx results was assessed. Univariate and multivariate logistic regressions were performed to study relationships between age, prostate-specific antigen (PSA) level, PSA density (PSAD), number of positive cores in the initial biopsy, and mpMRI grade on CBx reclassification. Our report is consistent with the Standards of Reporting for MRI-targeted Biopsy Studies (START) guidelines.

Results

In all, 105 patients were available for analysis in the study. From this cohort, 42 (40%) had PI-RADS 1, 2, or 3 lesions and 63 (60%) had only grade 4 or 5 lesions. Overall, 87 patients underwent visual estimation TRUS-Bx. Reclassification among patients with PI-RADS 1, 2, 3, 4, and 5 was 0%, 23.1%, 9.1%, 74.5%, and 100%, respectively. Overall, mpMRI sensitivity, specificity, positive predictive value, and negative predictive value for disease reclassification were 92.5%, 76%, 81%, and 90.5%, respectively. In the multivariate analysis, only PSAD and mpMRI remained significant for reclassification (P < 0.05). In the cross-tabulation, SBx would have missed 15 significant cases detected by targeted biopsy, but SBx did detect five cases of significant cancer not detected by targeted biopsy alone.

Conclusion

Multiparametric magnetic resonance imaging is a significant tool for predicting cancer severity reclassification on CBx among AS candidates. The reclassification rate on CBx is particularly high in the group of patients who have PI-RADS grades 4 or 5 lesions. Despite the usefulness of visual-guided biopsy, it still remains highly recommended to retrieve standard fragments during CBx in order to avoid missing significant tumours.

Read more articles of the week

Article of the Week: TRUS-Guided RB PCa Detection – Reasons for Targeted Biopsy Failure

July 20, 2016/2 Comments/by admin Z.9

In addition to the article itself, there is an accompanying editorial written by a prominent member of the urological community. This blog is intended to provoke comment and discussion and we invite you to use the comment tools at the bottom of each post to join the conversation.

Finally, the third post under the Article of the Week heading on the homepage will consist of additional material or media. This week we feature a video from Hannes Cash and Patrick Asbach, discussing their paper.

If you only have time to read one article this week, it should be this one.

Prostate cancer detection on transrectal ultrasonography-guided random biopsy despite negative real-time magnetic resonance imaging/ultrasonography fusion-guided targeted biopsy: reasons for targeted biopsy failure

Hannes Cash*, Karsten Gunzel*, Andreas Maxeiner*, Carsten Stephan*, Thomas Fischer†, Tahir Durmus†, Kurt Miller*, Patrick Asbach†, Matthias Haas† and Carsten Kempkensteffen*

*Department of Urology, and †Department of Radiology, Charite–University of Medicine Berlin, Berlin, Germany M. H. and C.K. contributed equally to the study.

Read the full article

Objective

To examine the value of additional transrectal ultrasonography (TRUS)-guided random biopsy (RB) in patients with negative magnetic resonance imaging (MRI)/ultrasonography (US) fusion-guided targeted biopsy (TB) and to identify possible reasons for TB failure.

Patients and Methods

We conducted a subgroup analysis of 61 men with prostate cancer (PCa) detected by 10-core RB but with a negative TB, from a cohort of 408 men with suspicious multiparametric magnetic resonance imaging (mpMRI) between January 2012 and January 2015. A consensus re-reading of mpMRI results (using Prostate Imaging Reporting and Data System [PI-RADS] versions 1 and 2) for each suspicious lesion was performed, with the image reader blinded to the biopsy results, followed by an unblinded anatomical correlation of the lesion on mpMRI to the biopsy result. The potential reasons for TB failure were estimated for each lesion. We defined clinically significant PCa according to the Epstein criteria and stratified patients into risk groups according to the European Association of Urology guidelines.

Results

Our analysis showed that RB detected significant PCa in 64% of patients (39/61) and intermediate-/high-risk PCa in 57% of patients (35/61). The initial mpMRI reading identified 90 suspicious lesions in the cohort. Blinded consensus re-reading of the mpMRI led to PI-RADS score downgrading of 45 lesions (50%) and upgrading of 13 lesions (14%); thus, negative TB could be explained by falsely high initial PI-RADS scores for 32 lesions (34%) and sampling of the target lesion by RB in the corresponding anatomical site for 36 out of 90 lesions (40%) in 35 of 61 patients (57%). Sampling of the target lesion by RB was most likely for lesions with PI-RADS scores of 4/5 and Gleason scores (GS) of ≥7. A total of 70 PCa lesions (67% with GS 6) in 44 patients (72%) were sampled from prostatic sites with no abnormalities on mpMRI.

Conclusion

In cases of TB failure, RB still detected a high rate of significant PCa. The main reason for a negative TB was a TB error, compensated for by positive sampling of the target lesion by the additional RB, and the second reason for TB failure was a falsely high initial PI-RADS score. The challenges that arise for both MRI diagnostics and prostate lesion sampling are evident in our data and support the integration of RB into the TB workflow.

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Editorial: MRI-Fusion Biopsy – Behind the Scenes

July 20, 2016/by Lars Budaus

MRI information of the prostate is increasingly used for improving the diagnostic yield of prostate biopsies [1]. However, increasing complexity of a procedure makes it prone to errors at multiple technical and human levels. Incorporating MRI information and ultrasonography (US) images for MRI-fusion biopsies is a technically challenging task. It involves various steps such as the acquisition and fusion of MRI and US images, the needle guidance during biopsy, and the diligence of the pathological evaluation of biopsy specimens. These different steps and interfaces between different medical professions influence the diagnostic performance of MRI-fusion biopsies.

For example, in daily clinical practice, MRIs from different institutions still harbour a great variance of sequences and reporting, despite the European Society of Urogenital Urology (ESUR) recently introducing acquisition and imaging protocols and a new and advanced version of the Prostate Imaging Reporting and Data System (PIRADS) version 2.0 [2]. The usefulness of such reporting schemes is evidenced by a moderate-to-good interobserver agreement between uro-radiologists for tumour lesion interpretation and corresponding κ values ranging from 0.55 to 0.80 [3]. Important pitfalls of image interpretation are benign lesions such as prostatitis, BPH and fibrosis, which might score similarly to prostate cancer lesions. This problem is further aggravated by a high proportion of patients that receive their first multiparametric MRI (mpMRI) of the prostate in the repeat-biopsy setting with a high burden of post-biopsy artefacts (haemorrhage, capsular irregularity) and lower overall cancer detection rate. Also, during MRI-fusion biopsy patient movement, prostate deformation by the US probe, and mismatch of image planes can lead to a biopsy error exceeding 4 mm. Moreover, targeting error might be aggravated by MRI underestimation of the tumour volume compared with final pathology [4]. After various authors reported the advantages and accuracy of MRI/US-fusion biopsy approaches, Cash et al. [5] address potential reasons for targeted biopsy failure to detect prostate cancer compared with random biopsy. Within their analyses the authors address potential limitations and technical considerations. Based on different technical biopsy strategies (with the patient placed within the MRI scanner (‘in-bore’) vs outside) and different technical approaches, these considerations are very important.

In contrast to cognitive fusion, most MRI/US platforms allow needle tracking by archiving the needle orientation, either by an electromagnetic, image-based or stepper-based mechanism [1]. However, lesion targeting by needle guidance is highly dependent on the dimensions of the primary lesion, numbers of relevant lesions, localisation, and overall prostate volume, making MRI-US fusion and cognitive fusion more error prone (i.e. aiming off the mark with the needle) than in-bore biopsies. Moreover, different technical fusion approaches provide different degrees of manual/automated adjustment tools, with for example either rigid or elastic image transformation to facilitate MRI/US image alignment.

Finally, due to the recent introduction of these techniques the influence of learning curve and experience of the uro-radiologist must be considered [6].

In their analyses, Cash et al. [5] found that 34% of negative targeted biopsies could be explained by initially too high estimated PIRADS scores that were downgraded at re-reading. Interestingly, the remaining lesions were without an mpMRI correlate but within this group 92.9% showed a primary Gleason 3 pattern in biopsy pathology, suggesting a high degree of invisibility on mpMRI. Subanalyses did not show an association of targeted biopsy failures in the ventral location. Therefore, the study by Cash et al. [5] is an important precursor for further analyses to address other underlying reasons for targeted biopsy failure. Moreover, it reveals the need for a tight collaboration of radiologists, urologists, and pathologists as interdisciplinary partners involved in MRI-fusion biopsy. Consequently, the optimal diagnostic performance of MRI-fusion biopsies can only be achieved through standardised MRI performance, reading and reporting of MRI findings, as well as final correlation of MRI findings with histopathological work up.

Read the full article

Lars Budaus and Sami-Ramzi Leyh-Bannurah

Martini-Clinic University Hospital Hamburg-Eppendorf, Hamburg, Germany

References

1 Logan JK, Rais-Bahrami S, Turkbey B et al. Current status of magnetic resonance imaging (MRI) and ultrasonography fusion software platforms for guidance of prostate biopsies. BJU Int 2014;114:641–52

2 American College of Radiology. Prostate Imaging Reporting and Data System (PI-RADS), version 2.0. 2015. Available at: https://www.acr.org/ Quality-Safety/Resources/PIRADS/. Accessed November 2015

3 Schimmoller L, Quentin M, Arsov C et al. Inter-reader agreement of the ESUR score for prostate MRI using in-bore MRI-guided biopsies as the reference standard. Eur Radiol 2013;23:3185–90

4 Rud E, Klotz D, Rennesund K et al. Detection of the index tumour and tumour volume in prostate cancer using T2-weighted and diffusion-weighted magnetic resonance imaging (MRI) alone. BJU Int 2014;114: E32–42

5 Cash H, Gunzel K, Maxeiner A et al. Prostate cancer detection on transrectal ultrasonography-guided random biopsy despite negative real- time magnetic resonance imaging/ultrasonography fusion-guided targeted biopsy: reasons for targeted biopsy failure. BJU Int 2016; 118: 35–43

6 Gaziev G, Wadhwa K, Barrett T et al. Deﬁning the learning curve for multiparametric magnetic resonance imaging (MRI) of the prostate using MRI-transrectal ultrasonography (TRUS) fusion-guided transperineal prostate biopsies as a validation tool. BJU Int 2016; 117: 80–6

Video: TRUS-Guided RB Prostate Cancer Detection – Reasons for Targeted Biopsy Failure

July 20, 2016/1 Comment/by admin Z.9

Prostate cancer detection on transrectal ultrasonography-guided random biopsy despite negative real-time magnetic resonance imaging/ultrasonography fusion-guided targeted biopsy: reasons for targeted biopsy failure

Hannes Cash*, Karsten Gunzel*, Andreas Maxeiner*, Carsten Stephan*, Thomas Fischer†, Tahir Durmus†, Kurt Miller*, Patrick Asbach†, Matthias Haas† and Carsten Kempkensteffen*

*Department of Urology, and †Department of Radiology, Charite–University of Medicine Berlin, Berlin, Germany M. H. and C.K. contributed equally to the study.

Read the full article

Objective

Patients and Methods

Results

Conclusion

Read more articles of the week

The PROMIS of MRI

June 24, 2016/1 Comment/by Hashim Ahmed

The prostate cancer pathway is controversial and views are often polarized. For a researcher, this is the perfect melting pot for innovation and practice-changing studies. It is clear that we need to reduce the harms of treatment, not only by treating very few low-risk cancers but also by innovations in surgery. It is pleasing to see Grasso et al. [1] systematic review of surgical innovation that may potentially lead to improvements in urinary incontinence after radical prostatectomy. This was a diligently conducted systematic review and points to the need for a randomized trial, which the authors tell us is currently being conducted.

The era of multiparametric MRI (mpMRI) for prostate cancer diagnosis is upon us. Few of us will live through such a wholesale change in the entire pathway for diagnosis and treatment of a cancer, and a common one at that. Whilst a few of us have been using mpMRI prior to first biopsy, there can be no doubting that we now have level 1b evidence to support the adoption of mpMRI prior to a first prostate biopsy as the standard care. The NIHR-HTA/MRC-CTU/UCL PROstate MR Imaging Study (or PROMIS) has been long awaited, and its initial results were presented at ASCO last month [2]. mpMRI performed better than expectations in a multicentre setting across 11 NHS trusts and just over a dozen radiologists. Sensitivity was 93% (95% CI 88–96) and the negative predictive value was 89% (95% CI 83–94). Although the focus, quite rightly, has been on mpMRI, equally significant has been the discovery of how bad a test TRUS-guided biopsy really was, with a sensitivity for clinically significant prostate cancer of only 48% (95% CI 42–55).

These findings answer several criticisms of mpMRI. First, that it is not as accurate as retrospective data suggest. It is, provided you do not expect it to find every millimetre of significant disease. Second, it is not reproducible outside of expert centres. It is, provided you quality assure every scanner, optimize the sequences iteratively, quality control scans and have robust training for radiologists. Third, it cannot be carried out on 1.5-Tesla scanners. It can; all the PROMIS scans were 1.5 Tesla without an endorectal coil. Fourth, it misses lots of clinically significant prostate cancers. It does not, but this depends on your definition of clinical significance. In this respect, the study by Cash et al. [3] is pertinent. They evaluated the rates of subsequent cancer found on ‘negative’ mpMRIs and, using the very conservative Epstein definition, found a high rate of missed ‘significant’ cancers. The rate of Gleason 7 disease missed was lower and some missed cancers were attributable to interobserver variability in mpMRI reporting. All centres should evaluate their own data to determine where their own negative predictive value sits and then strive to improve upon this through a constant iterative dialogue between urology and radiology. PROMIS shows that mpMRI has very high performance characteristics that should be possible across the board.

There is considerable work still to be done. Cost-effectiveness analyses are under way; with these data, NICE will need to consider their clinical recommendations, having laboured the point that they wished to await PROMIS. The challenge of dissemination and maintenance of quality standards is not to be underestimated. Work on determining what is out there, who is capable of performing such scans and reporting them, whether there is enough capacity in the NHS and whether all centres are capable of carrying out targeted biopsies are all legitimate health policy issues.

Similar to mammography standards laid down centrally, we will need to insist on: independent (not self-) accreditation; independent scan and report audits, with outliers (too many negatives, too many positives, too many equivocals) reviewed to determine whether further standardization training is required; rates of clinically significant and insignificant cancers detected on subsequent biopsy; rates of repeat biopsies; and rates of unnecessary radical therapy on low risk cases. We should all look within our centres to ensure we can meet these expectations.

Hashim U. Ahmed, BJUI Consulting Editor – Imaging Division of Surgery and Interventional Sciences, UCL, and
Department of Urology, UCL Hospital NHS Foundation Trust, London, UK

References

1. Grasso AAC, Mistretta FA, Sandri M et al. Posterior musculofascial reconstruction after radical prostatectomy: an updated systematic review and a meta-analysis. BJU Int 2016; 118: 20–34 Wiley Online Library

2. Ahmed HU. The PROMIS study: a paired-cohort, blinded confirmatory study evaluating the accuracy of multi-parametric MRI and TRUS biopsy in men with an elevated PSA. J Clin Oncol 2016; 34: (suppl; abstr 5000)

3. Cash H, Günzel K, Maxeiner A et al. Prostate cancer detection on transrectal ultrasonography-guided random biopsy despite negative real-time magnetic resonance imaging/ ultrasonography fusion-guided targeted biopsy: reasons for targeted biopsy failure. BJU Int 2016; 118: 35–43 Wiley Online Library

Article of the week: Getting to the core of the matter with PIRADS scoring

December 27, 2013/by admin Z.9

Every week the Editor-in-Chief selects the Article of the Week from the current issue of BJUI. The abstract is reproduced below and you can click on the button to read the full article, which is freely available to all readers for at least 30 days from the time of this post.

In addition to the article itself, there is an accompanying editorial written by prominent members of the urological community. This blog is intended to provoke comment and discussion and we invite you to use the comment tools at the bottom of each post to join the conversation.

If you only have time to read one article this week, it should be this one.

Histology core-specific evaluation of the European Society of Urogenital Radiology (ESUR) standardised scoring system of multiparametric magnetic resonance imaging (mpMRI) of the prostate

Timur H. Kuru*^†, Matthias C. Roethke^†, Philip Rieker*, Wilfried Roth^‡, Michael Fenchel^†, Markus Hohenfellner*, Heinz-Peter Schlemmer^† and Boris A. Hadaschik*

*Department of Urology, University Hospital Heidelberg, ^†Department of Radiology, German Cancer Research Center (DKFZ), and ^‡Institute of Pathology, University of Heidelberg, Heidelberg, Germany

Read the full article

Link to Video: MRI-Navigated Stereotactic Prostate Biopsy

OBJECTIVES

• To evaluate the Prostate Imaging Reporting and Data System (PIRADS) in multiparametric magnetic resonance imaging (mpMRI) based on single cores and single-core histology.

• To calculate positive (PPV) and negative predictive values (NPV) of different modalities of mpMRI.

PATIENTS AND METHODS

• We performed MRI-targeted transrectal ultrasound-guided perineal prostate biopsies on 50 patients (mean age 66 years, mean PSA level of 9.9 ng/mL) with suspicion of prostate cancer. The biopsy trajectories of every core taken were documented in three dimensions (3D) in a 3D-prostate model.

• Every core was evaluated separately for prostate cancer and the performed biopsy trajectories were projected on mpMRI images.

• PIRADS scores of 1177 cores were then assessed by a histology ‘blinded’ uro-radiologist in T2-weighted (T2W), dynamic contrast-enhanced (DCE), diffusion-weighted imaging (DWI) and magnetic resonance spectroscopy (MRS).

RESULTS

• The PIRADS score was significantly higher in cores positive for cancer than in negative cores.

• There was a significant correlation between the PIRADS score and histopathology for every modality.

• Receiver operating characteristic (ROC) analysis showed excellent specificity for T2W (90% peripheral zone/97% transition zone) and DWI (98%/97%) images regardless of the prostate region observed. These numbers decreased for DCE (80%/93%) and MRS (76%/83%).

• All modalities had NPVs of 99%, if a PIRADS score threshold of 2 (for T2W, DCE, and MRS) or 3 (for DWI) was used. However, PPVs were low.

CONCLUSIONS

• Our results show that PIRADS scoring is feasible for clinical routine and allows standardised reporting.

• PIRADS can be used as a decision-support system for targeting of suspicious lesions.

• mpMRI has a high NPV for prostate cancer and, thus, might be a valuable tool in the initial diagnostic evaluation.

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Editorial: Too many men still undergo needless prostate biopsy

December 27, 2013/by Uday Patel

Multiple studies have shown that only one in three or four men with a raised PSA level prove to have prostate cancer and many men suffer potentially life-threatening complications from transrectal prostate biopsy. There is an urgent need for better risk stratification of men with elevated PSA levels. Any such test should have a high negative predicative value (NPV; small number of significant cancers missed) but also a high positive predictive value (PPV; i.e. the yield would be high and there would be very few false positives) to diminish the number of unnecessary biopsies. Multiparametric MRI (mpMRI) of the prostate, especially with a stronger 3 T magnet, has been advocated for this purpose. The parameters refer to the separate MRI sequences used, typically at least three. Sequences can not only study the anatomy of the gland (standard T2-weighted MRI), but there is also a measure of the tissue cellularity (diffusion-weighted MRI), vascularity (dynamic contrast-enhanced MRI) or biochemistry (magnetic resonance spectroscopy). Initial data have shown promise but the changes seen on these various sequences can be subtle and interpretation is subjective. Naturally observer experience plays a large part but a standardised scoring system, the so called Prostate Imaging Reporting and Data System (PIRADS) system, has been proposed to improve reporting performance [1]. Each parameter is scored on a scale of 1–5 according to the likelihood of cancer. Scoring systems are always a compromise between the NPV and PPV, and so far there is no agreement where the threshold for each parameter should be set. In the original document, the authors proposed that a score of 4 or 5 signifies a high likelihood or almost certainty of cancer, whilst scores of 1 or 2 denote a high likelihood of benign tissue. A score of 3 is evens. The paper by Kuru et al. [2] shows a high NPV only when the threshold was set at the low level of 2 for each parameter. Predictably, at this threshold the PPV was extremely low, and therefore many men would still undergo unnecessary biopsy. Another similar paper advocated a mean threshold of 3, but even then the PPV was 38% with a NPV of 95% [3]. Both these papers are retrospective studies, in particular the MRI readings were done retrospectively. Nevertheless, the low PPV is disappointing. The results of prospective studies with multiple readers are keenly awaited and I hope that that these will find a higher PPV for mpMRI, and we can to move to an era when fewer men undergo needless prostate biopsy.

Uday Patel
St George’s Hospital, London, UK

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References

Barentsz JO, Richenberg J, Clements R et al. ESUR prostate MR guidelines 2012. Eur Radiol 2012; 22: 746–757
Kuru T, Roethke M, Rieker P et al. Histology core-specific evaluation of the European Society of Urogenital Radiology (ESUR) standardised scoring system of multiparametric magnetic resonance imaging (mpMRI) of the prostate. BJU Int 2013; 112:1080–1087
Portalez D, Mozer P, Cornud F et al. Validation of the European Society of Urogenital Radiology scoring system for prostate cancer diagnosis on multiparametric magnetic resonance imaging in a cohort of repeat biopsy patients. Eur Urol 2012; 62: 986–996