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Article of the week: External validation of novel magnetic resonance imaging‐based models for prostate cancer prediction

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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 this post, there is an editorial written by a prominent member of the urological community and a visual abstract created by trainee urologists. Please use the comment buttons below to join the conversation.

If you only have time to read one article this week, we recommend this one. 

External validation of novel magnetic resonance imaging‐based models for prostate cancer prediction

Lukas Püllen*, Jan P. Radtke*†, Manuel Wiesenfarth‡, Monique J. Roobol§, Jan F.M. Verbeek§, Axel Wetter, Nika Guberina, Abhishek Pandey**, Clemens Hüttenbrink**, Stephan Tschirdewahn*, Sascha Pahernik**, Boris A. Hadaschik* and Florian A. Distler**

*Department of Urology, University Hospital Essen, Nordrhein-Westfalen, †Department of Radiology, German Cancer Research Centre (DKFZ), ‡Division of Biostatistics, German Cancer Research Centre (DKFZ), Heidelberg, Germany, §Department of Urology, Erasmus University Medical Centre, Rotterdam, The Netherlands, Department of Radiology, University Hospital Essen, Nordrhein-Westfalen, and **Department of Urology, Paracelsus Medical University, Nuremberg, Nürnberg, Germany

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Abstract

Objectives

To validate, in an external cohort, three novel risk models, including the recently updated European Randomized Study of Screening for Prostate Cancer (ERSPC) risk calculator, that combine multiparametric magnetic resonance imaging (mpMRI) and clinical variables to predict clinically significant prostate cancer (PCa).

Patients and Methods

We retrospectively analysed 307 men who underwent mpMRI prior to transperineal ultrasound fusion biopsy between October 2015 and July 2018 at two German centres. mpMRI was rated by Prostate Imaging Reporting and Data System (PI‐RADS) v2.0 and clinically significant PCa was defined as International Society of Urological Pathology Gleason grade group ≥2. The prediction performance of the three models (MRI‐ERSPC‐3/4, and two risk models published by Radtke et al. and Distler et al., ModRad and ModDis) were compared using receiver‐operating characteristic (ROC) curve analyses, with area under the ROC curve (AUC), calibration curve analyses and decision curves used to assess net benefit.

Fig. 4. Biopsies saved vs prostate cancer detected/missed using different risk thresholds for clinically significant prostate cancers (PCas) for the different models for a standardized number of 1000 men for the whole cohort (A) and the two analysed subgroups (biopsy‐naïve (B) and previous negative biopsy (C)); including a graphical presentation of biopsy saving vs. missing clinically significant PCas for two different thresholds (10% and 15%) for the validated nomograms. Green shading shows the number of saved biopsies. Red shading shows the number of clinically significant PCas missed. ModDis, risk model published by Distler et al.; ModRad, risk model published by Radtke et al.; MRI‐ERSPC‐3/4, updated ERSPC risk calculator 3/4.

Results

The AUCs of the three novel models (MRI‐ERSPC‐3/4, ModRad and ModDis) were 0.82, 0.85 and 0.83, respectively. Calibration curve analyses showed the best intercept for MRI‐ERSPC‐3 and ‐4 of 0.35 and 0.76. Net benefit analyses indicated clear benefit of the MRI‐ERSPC‐3/4 risk models compared with the other two validated models. The MRI‐ERSPC‐3/4 risk models demonstrated a discrimination benefit for a risk threshold of up to 15% for clinically significant PCa as compared to the other risk models.

Conclusion

In our external validation of three novel prostate cancer risk models, which incorporate mpMRI findings, a head‐to‐head comparison indicated that the MRI‐ERSPC‐3/4 risk model in particular could help to reduce unnecessary biopsies.

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Editorial: Magnetic resonance imaging as a personalised tool to safely avoid prostate biopsy

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Identifying men at risk of developing clinically significant prostate cancer (csPCa) who are either biopsy naïve or have undergone a prior negative systematic biopsy remains a dilemma for urologists seeking to utilise clinical resources in a cost‐conscious and safe manner. Clinical and demographic factors including DRE findings, serum PSA concentrations, race/ethnicity, and family history, guide shared decision‐making to pursue an initial or repeat prostate biopsy. Despite thoughtful risk assessments, the screening tools implemented often lead to biopsies where a majority demonstrates benign pathology findings or indolent forms of PCa that would not mandate immediate, definitive intervention. Hence, various risk models (RMs) have been proposed to stratify men who have a greater likelihood of harbouring csPCa, and several now incorporate findings from multiparametric MRI (mpMRI) by assessing suspicious lesion characteristics into their algorithms. While promising, most of these models were generated using single‐institution retrospective data and lack the external validation that could make them more generalisable and widely adopted in clinical practice.

In the present issue, Püllen et al. [1] evaluate three RMs that incorporate mpMRI findings using a cohort of 307 men who were biopsy naïve or had previously undergone a negative prostate biopsy. Risk of csPCa according to the MRI‐European Randomized Prostate Screening for Prostate Cancer Risk Calculators 3 and 4 (MRI‐ERSPC‐3/4) [2], Radtke’s RM (ModRAD) [3], and Distler’s RM (ModDis) [4] were compared to final pathology after TRUS‐guided perineal prostate biopsy with MRI‐fusion targeted sampling, as indicated using a Prostate Imaging‐Reporting and Data System version 2 (PI‐RADSv2) score ≥3 as the threshold.

The cohort had a median age of 67 years, median PSA concentration of 8.8 ng/mL, and there were 453 PI‐RADSv2 ≥3 lesions, which is consistent with a typical at‐risk screening population. Amongst these men, 134 (40%) harboured csPCa defined as a Gleason Grade Group ≥2. All three RMs performed similarly on receiver operating curve analyses with area under the curve for prediction nearing 0.85 for finding csPCa in both biopsy naïve and prior negative‐biopsy patients. Using a 15% risk threshold, the adapted MRI‐ERSPC‐3/4 RM would have safely avoided 30% of biopsies with 6% of csPCa diagnoses being missed, whereas the ModRad and ModDis RMs would have only avoided 17% and 6% of unnecessary biopsies, respectively, albeit with far fewer occult cases of csPCa.

The integration of mpMRI in the pre‐biopsy setting is being more widely adopted into the clinical landscape, with emerging support largely due to its value in detecting csPCa, but also the recognised high negative predictive value potentiating the safe avoidance or deferral of prostate biopsy [5]. Performing a prostate biopsy in all men with a clinical screening positive PSA and/or DRE carries a significant public health burden, and harbours recognised clinical morbidity without definitive overall survival benefit for many. Hence, integration of MRI findings, importantly the lack of highly suspicious lesions, is of interest in RM assessment to determine which patients would be benefited most from prostate biopsy while sparing some from biopsy, without compromising detection of csPCa and oncological outcomes.

For patients who forgo prostate biopsy based upon factors such as nomogram‐predicted risk of harbouring csPCa, the appropriate timing for performing repeat evaluation with biomarkers and/or MRI is not well defined. Various models have shown much higher rates of biopsy avoidance if accepting some level of missed csPCa [6]. With the awareness that some men who would theoretically avoid a biopsy based on these RMs may actually harbour csPCa, should these men undergo repeat MRI as standard or would serial PSA assessment drive biopsy detection of their csPCa with adequate lead time for definitive treatment? Prospective investigations assessing the clinical course of patients with negative MRI findings who avoid or defer biopsy are critical to determine the real‐world applicability of such RMs. The true value of these RMs and nomograms should balance their public health cost and morbidity benefit with potential oncological risk.

by Zachary A. Glaser and Soroush Rais‐Bahrami

References

  1. Püllen L, Radtke JP, Wiesenfarth M et al. External validation of novel magnetic resonance imaging‐based models for prostate cancer prediction. BJU Int 2020; 125: 407– 16
  2. Alberts AR, Roobol MJ, Verbeek JFM et al. Prediction of high‐grade prostate cancer following multiparametric magnetic resonance imaging: improving the Rotterdam European randomized study of screening for prostate cancer risk calculators. Eur Urol 2019; 75: 310– 8
  3. Radtke JP, Wiesenfarth M, Kesch C et al. Combined clinical parameters and multiparametric magnetic resonance imaging for advanced risk modeling of prostate cancer‐patient‐tailored risk stratification can reduce unnecessary biopsies. Eur Urol 2017; 72: 888– 96
  4. Distler FA, Radtke JP, Bonekamp D et al. The value of PSA density in combination with PI‐RADS for the accuracy of prostate cancer prediction. J Urol 2017; 198: 575– 82
  5. Siddiqui MM, Rais‐Bahrami S, Turkbey B et al. Comparison of MR/ultrasound fusion‐guided biopsy with ultrasound‐guided biopsy for the diagnosis of prostate cancer. JAMA 2015; 313: 390– 7
  6. Mehralivand S, Shih JH, Rais‐Bahrami S et al. A Magnetic resonance imaging‐based prediction model for prostate biopsy risk stratification. JAMA Oncol 2018; 4: 678– 85

 

 

Visual abstract: External validation of novel MRI-based models for prostate cancer prediction

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Article of the week: Using spatial tracking with magnetic resonance imaging/ultrasound‐guided biopsy to identify unilateral prostate cancer

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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 this post, there is an editorial written by a prominent member of the urological community and a visual abstract created by one of our artistic urologists. Please use the comment buttons below to join the conversation.

If you only have time to read one article this week, we recommend this one. 

Using spatial tracking with magnetic resonance imaging/ultrasound‐guided biopsy to identify unilateral prostate cancer

Steve R. Zhou*, Alan M. Priester†‡, Rajiv Jayadevan†, David C. Johnson§, Jason J. Yang*, Jorge Ballon*, Shyam Natarajan†‡ and Leonard S. Marks†

*David Geffen School of Medicine, University of California, †Department of Urology, University of California, ‡Department of Bioengineering, University of California, Los Angeles, CA, and §Department of Urology, University of
North Carolina, Chapel Hill, NC, USA

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Abstract

Objectives

To create reliable predictive metrics of unilateral disease using spatial tracking from a fusion device, thereby improving patient selection for hemi‐gland ablation of prostate cancer.

Patients and Methods

We identified patients who received magnetic resonance imaging (MRI)/ultrasound‐guided biopsy and radical prostatectomy at a single institution between 2011 and 2018. In addition to standard clinical features, we extracted quantitative features related to biopsy core and MRI target locations predictive of tumour unilaterality. Classification and Regression Tree (CART) analysis was used to create a decision tree (DT) for identifying cancer laterality. We evaluated concordance of model‐determined laterality with final surgical pathology.

Fig. 2. Correlation of MRI (A), spatial biopsy pathology (B), and WMP (C). Suspicious MRI lesion (green in A and B) is shown to underestimate true tumour volume (red in A and B, outlined in C). Positive ipsilateral cores (orange) confirm intermediate disease in the MRI lesion and near midline. Negative contralateral cores in blue erroneously imply unilaterality of disease. Only a subset of tracked cores is shown for clarity.

Results

A total of 173 patients were identified with biopsy coordinates and surgical pathology available. Based on CART analysis, in addition to biopsy‐ and MRI‐confirmed disease unilaterality, patients should be further screened for cancer detected within 7 mm of midline in a 40 mL prostate, which equates to the central third of any‐sized prostate by radius. The area under the curve for this DT was 0.82. Standard diagnostics and the DT correctly identified disease laterality in 73% and 80% of patients, respectively (P = 0.13). Of the patients identified as unilateral by standard diagnostics, 47% had undetected contralateral disease or were otherwise incorrectly identified. This error rate was reduced to 17% (P = 0.01) with the DT.

Conclusion

Using spatial tracking from fusion devices, a DT was more reliable for identifying laterality of prostate cancer compared to standard diagnostics. Patients with cancer detected within the central third of the prostate by radius are poor hemi‐gland ablation candidates due to the risk of midline extension of tumour.

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Visual abstract: Using spatial tracking with MRI/ultrasound‐guided biopsy to identify unilateral PCa

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Article of the week: Likert vs PI‐RADS v2: a comparison of two radiological scoring systems for detection of clinically significant PCa

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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 editorial written by a prominent member of the urological community and a video prepared by the authors; 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, we recommend this one. 

Likert vs PI‐RADS v2: a comparison of two radiological scoring systems for detection of clinically significant prostate cancer

Christopher C. Khoo*†, David Eldred-Evans*†, Max Peters‡, Mariana Bertoncelli Tanaka*†, Mohamed Noureldin*†, Saiful Miah*†, Taimur Shah*†, Martin J. Connor*, Deepika Reddy*, Martin Clark§, Amish Lakhani§, Andrea Rockall§, Feargus Hosking-Jervis*, Emma Cullen*, Manit Arya*†, David Hrouda†, Hasan Qazi, Mathias Winkler*†, Henry Tam§ and Hashim U. Ahmed*†

*Imperial Prostate, Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, †Imperial Urology, Charing Cross Hospital, Imperial College Healthcare NHS Trust, London, UK, ‡Department of Radiotherapy, University Medical Centre, Utrecht, The Netherlands, §Department of Radiology, Charing Cross Hospital, Imperial College Healthcare NHS Trust and Department of Urology, St. George’s Hospital, St. George’s Healthcare NHS Trust, London, UK

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Abstract

Objective

To compare the clinical validity and utility of Likert assessment and the Prostate Imaging Reporting and Data System (PI‐RADS) v2 in the detection of clinically significant and insignificant prostate cancer.

Patients and Methods

A total of 489 pre‐biopsy multiparametric magnetic resonance imaging (mpMRI) scans in consecutive patients were subject to prospective paired reporting using both Likert and PI‐RADS v2 by expert uro‐radiologists. Patients were offered biopsy for any Likert or PI‐RADS score ≥4 or a score of 3 with PSA density ≥0.12 ng/mL/mL. Utility was evaluated in terms of proportion biopsied, and proportion of clinically significant and insignificant cancer detected (both overall and on a ‘per score’ basis). In those patients biopsied, the overall accuracy of each system was assessed by calculating total and partial area under the receiver‐operating characteristic (ROC) curves. The primary threshold of significance was Gleason ≥3 + 4. Secondary thresholds of Gleason ≥4 + 3, Ahmed/UCL1 (Gleason ≥4 + 3 or maximum cancer core length [CCL] ≥6 or total CCL≥6) and Ahmed/UCL2 (Gleason ≥3 + 4 or maximum CCL ≥4 or total CCL ≥6) were also used.

Table 1: Comparison of Likert and Prostate Imaging Reporting and Data System scoring.

Results

The median (interquartile range [IQR]) age was 66 (60–72) years and the median (IQR) prostate‐specific antigen level was 7 (5–10) ng/mL. A similar proportion of men met the biopsy threshold and underwent biopsy in both groups (83.8% [Likert] vs 84.8% [PI‐RADS v2]; P = 0.704). The Likert system predicted more clinically significant cancers than PI‐RADS across all disease thresholds. Rates of insignificant cancers were comparable in each group. ROC analysis of biopsied patients showed that, although both scoring systems performed well as predictors of significant cancer, Likert scoring was superior to PI‐RADS v2, exhibiting higher total and partial areas under the ROC curve.

Conclusions

Both scoring systems demonstrated good diagnostic performance, with similar rates of decision to biopsy. Overall, Likert was superior by all definitions of clinically significant prostate cancer. It has the advantages of being flexible, intuitive and allowing inclusion of clinical data. However, its use should only be considered once radiologists have developed sufficient experience in reporting prostate mpMRI.

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Editorial: Does prostate MRI reporting system affect performance of MRI in men with a clinical suspicion of PCa?

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Magnetic Resonance Imaging (MRI) of prostate continues to transform the way prostate cancer is being diagnosed and risk stratified. Multiple prospective single (e.g. the Biparametric MRI for Detection of Prostate Cancer [BIDOC] [1] and Improved Prostate Cancer Diagnosis ‐ Combination of Magnetic Resonance Imaging and Biomarkers [IMPROD] [2]) and multi‐institution trials (e.g. PROstate MRI Imaging Study [PROMIS] [3], PRostate Evaluation for Clinically Important Disease: Sampling Using Image‐guidance Or Not? [PRECISION] [4], multi‐institutional IMPROD (Multi‐IMPROD) [5], Assessment of Prostate MRI Before Prostate Biopsies [MRI‐FIRST] [6]) have demonstrated the potential of prostate MRI to limit the number of unnecessary biopsies in men with suspected prostate cancer.

In this issue of the BJUI, Khoo et al. [7] retrospectively analysed reports from a multicentre prostate cancer pathway registry, Rapid Assessment and Prostate Imaging for Diagnosis (RAPID). Men with a clinical suspicion of prostate cancer were enrolled based on various clinical criteria such as: age, performance status, and PSA level. All men had a pre‐biopsy MRI, including dynamic contrast‐enhanced MRI, reported using a 5‐point Likert scale and Prostate Imaging Reporting and Data System version 2.0 (PI‐RADSv2.0) systems by one of four uro‐radiologists (5–9 years of experience of prostate multi‐parametric MRI). Subsequently, all Likert and PI‐RADSv2.0 scores were reviewed by a dedicated reader in a multidisciplinary team setting. Likert scores were reported with knowledge of clinical variables such as: PSA, patient age, and past medical history. Men with Likert or PI‐RADSv2.0 score ≥4 or a score of 3 with a PSA density ≥0.12 ng/mL/mL underwent transperineal targeted prostate biopsies. Additionally, some men below these thresholds deemed to be at particularly high risk of prostate cancer (usually based on presence of other risk factors such as family history, high PSA kinetics or ethnic risk) were also offered biopsy on a case‐by‐case basis. At least three targeted cores were taken from each MRI‐suspicious lesion and no systematic biopsy cores were included in this analysis.

In total, 489 men were included in the analyses, with 377 and 408 men meeting the Likert and PI‐RADSv2.0 biopsy thresholds, respectively, of whom 316 (83.8%) and 346 (84.8%) proceeded to biopsy (P = 0.704), respectively. The Likert system predicted more clinically significant prostate cancer than PI‐RADSv2.0, e.g., 58.2% (184/316) vs 53.2% (184/346) of prostate cancer (P = 0.190) with Gleason score ≥3+4. Detection rates of clinically insignificant prostate cancer were comparable. The authors concluded that the Likert system was superior to PI‐RADSv2.0.

The authors should be congratulated on their effort to improve prostate MRI as a risk‐stratification and biopsy targeting tool. However, caution should be applied when translating these results to other centres. In order to access inter‐centre variability and to allow independent external validation, research groups should provide access to their imaging and patient level data. The authors do not provide such access and do not present inter‐reader variability of Likert vs PI‐RADv2.0 for all enrolled men. Similar to other trials evaluating prostate MRI in men with a clinical suspicion of prostate cancer, true prostate cancer and significant prostate cancer prevalence in this cohort is unknown, as men did not undergo saturation biopsy or prostatectomy with whole‐mount prostatectomy sections.

Overall, this retrospective analysis by Khoo et al. [7], comparing Likert scores reported using clinical variables vs PIRADSv2.0, provides further evidence that good quality prostate MRI can be used as a risk‐stratification and biopsy targeting tool in men with a clinical suspicion of prostate cancer. Each centre needs to develop its own quality control process and continually review its own performance measures of prostate MRI and MRI‐targeted biopsy. Furthermore, in order to access inter‐centre variability in performance of prostate MRI and MRI‐targeted biopsy, free public access to imaging and patient level data should be provided.

by Ivan Jambor and Ugo Falagorio

References

  1. Boesen L, Nørgaard N, Logager V et al. Assessment of the diagnostic accuracy of biparametric magnetic resonance imaging for prostate cancer in biopsy‐naive men: the Biparametric MRI for Detection of Prostate Cancer (BIDOC) study. JAMA Netw Open 2018; 1: 1– 28
  2. Jambor I, Boström PJ, Taimen P et al. Novel biparametric MRI and targeted biopsy improves risk stratification in men with a clinical suspicion of prostate cancer (IMPROD Trial). J Magn Reson Imaging 2017; 46: 1089– 95
  3. Ahmed HU, El‐Shater Bosaily A, Brown LC et al. Diagnostic accuracy of multi‐parametric MRI and TRUS Biopsy in prostate cancer (PROMIS): a paired validating confirmatory  study. Lancet 2017; 389: 815– 22
  4. Kasivisvanathan V, Rannikko AS, Borghi M et al. MRI‐targeted or standard biopsy for prostate‐cancer diagnosis. N Engl J Med 2018; 378: 1767– 77
  5. Jambor I, Verho J, Ettala O et al. Validation of IMPROD biparametric MRI in men with clinically suspected prostate cancer: A prospective multi‐institutional trial. PLoS Med 2019; 16: e1002813.
  6. Rouvière O, Puech P, Renard‐Penna R et al. Use of prostate systematic and targeted biopsy on the basis of multiparametric MRI in biopsy‐naive patients (MRI‐FIRST): a prospective, multicentre, paired diagnostic study. Lancet Oncol 2019; 20: 100– 9
  7. Khoo CC, Eldred‐Evans D, Peters M et al. Likert vs PI‐RADS v2: a comparison of two radiological scoring systems for detection of clinically significant prostate cancer. BJU Int 2019; 125:49-55.

 

Video: Likert vs PI-RADS v2

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Likert vs PI‐RADS v2: a comparison of two radiological scoring systems for detection of clinically significant prostate cancer

Read the full article

Abstract

Objective

To compare the clinical validity and utility of Likert assessment and the Prostate Imaging Reporting and Data System (PI‐RADS) v2 in the detection of clinically significant and insignificant prostate cancer.

Patients and Methods

A total of 489 pre‐biopsy multiparametric magnetic resonance imaging (mpMRI) scans in consecutive patients were subject to prospective paired reporting using both Likert and PI‐RADS v2 by expert uro‐radiologists. Patients were offered biopsy for any Likert or PI‐RADS score ≥4 or a score of 3 with PSA density ≥0.12 ng/mL/mL. Utility was evaluated in terms of proportion biopsied, and proportion of clinically significant and insignificant cancer detected (both overall and on a ‘per score’ basis). In those patients biopsied, the overall accuracy of each system was assessed by calculating total and partial area under the receiver‐operating characteristic (ROC) curves. The primary threshold of significance was Gleason ≥3 + 4. Secondary thresholds of Gleason ≥4 + 3, Ahmed/UCL1 (Gleason ≥4 + 3 or maximum cancer core length [CCL] ≥6 or total CCL≥6) and Ahmed/UCL2 (Gleason ≥3 + 4 or maximum CCL ≥4 or total CCL ≥6) were also used.

Results

The median (interquartile range [IQR]) age was 66 (60–72) years and the median (IQR) prostate‐specific antigen level was 7 (5–10) ng/mL. A similar proportion of men met the biopsy threshold and underwent biopsy in both groups (83.8% [Likert] vs 84.8% [PI‐RADS v2]; P = 0.704). The Likert system predicted more clinically significant cancers than PI‐RADS across all disease thresholds. Rates of insignificant cancers were comparable in each group. ROC analysis of biopsied patients showed that, although both scoring systems performed well as predictors of significant cancer, Likert scoring was superior to PI‐RADS v2, exhibiting higher total and partial areas under the ROC curve.

Conclusions

Both scoring systems demonstrated good diagnostic performance, with similar rates of decision to biopsy. Overall, Likert was superior by all definitions of clinically significant prostate cancer. It has the advantages of being flexible, intuitive and allowing inclusion of clinical data. However, its use should only be considered once radiologists have developed sufficient experience in reporting prostate mpMRI.

 

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Article of the week: mpMRI and follow‐up to avoid prostate biopsy in 4259 men

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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 editorial written by a prominent member of the urological community and a video prepared by the authors. These are 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.

Multiparametric magnetic resonance imaging and follow‐up to avoid prostate biopsy in 4259 men

Wulphert Venderink*, Annemarijke van Luijtelaar*, Marloes van der Leest*, Jelle O. Barentsz*, Sjoerd F.M. Jenniskens*, Michiel J.P. Sedelaar†,Christina Hulsbergen-van de Kaa‡, Christiaan G. Overduin* and Jurgen J. Fütterer*

*Department of Radiology and Nuclear Medicine, †Department of Urology, and ‡Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands

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Abstract

Objective

To determine the proportion of men avoiding biopsy because of negative multiparametric magnetic resonance imaging (mpMRI) findings in a prostate MRI expert centre, and to assess the number of clinically significant prostate cancers (csPCa) detected during follow‐up.

Patients and method

Retrospective study of 4259 consecutive men having mpMRI of the prostate between January 2012 and December 2017, with either a history of previous negative transrectal ultrasonography‐guided biopsy or biopsy naïve. Patients underwent mpMRI in a referral centre. Lesions were classified according to Prostate Imaging Reporting And Data System (PI‐RADS) versions 1 and 2. Negative mpMRI was defined as an index lesion PI‐RADS ≤2. Follow‐up until 13 October 2018 was collected by searching the Dutch Pathology Registry (PALGA). Gleason score ≥3 + 4 was considered csPCa. Kaplan–Meier analysis and univariable logistic regression models were used in the cohort of patients with negative mpMRI and follow‐up.

Fig. 2. Distribution of PI‐RADS scored in the entire cohort.

Results

Overall, in 53.6% (2281/4259) of patients had a lesion classified as PI‐RADS ≤2. In 320 patients with PI‐RADS 1 or 2, follow‐up mpMRI was obtained after a median (interquartile range) of 57 (41–63) months. In those patients, csPCa diagnosis‐free survival (DFS) was 99.6% after 3 years. Univariable logistic regression analysis revealed age as a predictor for csPCa during follow‐up (P < 0.05). In biopsied patients, csPCa was detected in 15.8% (19/120), 43.2% (228/528) and 74.5% (483/648) with PI‐RADS 3, 4 and 5, respectively.

Conclusion

More than half of patients having mpMRI of the prostate avoided biopsy. In those patients, csPCa DFS was 99.6% after 3 years.

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Article of the week: Biparametric vs multiparametric prostate MRI for the detection of PCa in treatment‐naïve patients

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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 editorial written by a prominent member of the urological community, and a video produced by the authors. These are 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.

Biparametric vs multiparametric prostate magnetic resonance imaging for the detection of prostate cancer in treatment-naïve patients: a diagnostic test accuracy systematic review and meta-analysis

Mostafa Alabousi*, Jean-Paul Salameh†‡, Kaela Gusenbauer§, Lucy Samoilov, Ali Jafri**, Hang Yu§ and Abdullah Alabousi††

 

*Department of Radiology, McMaster University, Hamilton, †Department of Clinical Epidemiology and Public Health, University of Ottawa, ‡The Ottawa Hospital Research Institute, Clinical Epidemiology Program, Ottawa, §Department of Medicine, McMaster University, Hamilton, Department of Medicine, Western University, London, ON, Canada, **Department of Medicine, New York Institute of Technology School of Osteopathic Medicine, Glen Head, NY, USA, and ††Department of Radiology, St Joseph’s Healthcare, McMaster University, Hamilton, ON, Canada

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Abstract

Objective

To perform a diagnostic test accuracy (DTA) systematic review and meta‐analysis comparing multiparametric (diffusion‐weighted imaging [DWI], T2‐weighted imaging [T2WI], and dynamic contrast‐enhanced [DCE] imaging) magnetic resonance imaging (mpMRI) and biparametric (DWI and T2WI) MRI (bpMRI) in detecting prostate cancer in treatment‐naïve patients.

Methods

The Medical Literature Analysis and Retrieval System Online (MEDLINE) and Excerpta Medica dataBASE (EMBASE) were searched to identify relevant studies published after 1 January 2012. Articles underwent title, abstract, and full‐text screening. Inclusion criteria consisted of patients with suspected prostate cancer, bpMRI and/or mpMRI as the index test(s), histopathology as the reference standard, and a DTA outcome measure. Methodological and DTA data were extracted. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS)‐2 tool. DTA metrics were pooled using bivariate random‐effects meta‐analysis. Subgroup analysis was conducted to assess for heterogeneity.

Results

From an initial 3502 studies, 31 studies reporting on 9480 patients (4296 with prostate cancer) met the inclusion criteria for the meta‐analysis; 25 studies reported on mpMRI (7000 patients, 2954 with prostate cancer) and 12 studies reported on bpMRI DTA (2716 patients, 1477 with prostate cancer). Pooled summary statistics demonstrated no significant difference for sensitivity (mpMRI: 86%, 95% confidence interval [CI] 81–90; bpMRI: 90%, 95% CI 83–94) or specificity (mpMRI: 73%, 95% CI 64–81; bpMRI: 70%, 95% CI 42–83). The summary receiver operating characteristic curves were comparable for mpMRI (0.87) and bpMRI (0.90).

Conclusions

No significant difference in DTA was found between mpMRI and bpMRI in diagnosing prostate cancer in treatment‐naïve patients. Study heterogeneity warrants cautious interpretation of the results. With replication of our findings in dedicated validation studies, bpMRI may serve as a faster, cheaper, gadolinium‐free alternative to mpMRI.

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