National implementation of multi‐parametric magnetic resonance imaging for prostate cancer detection – recommendations from a <scp>UK</scp> consensus meeting

Appayya, Mrishta Brizmohun; Adshead, Jim; Ahmed, Hashim U.; Allen, Clare; Bainbridge, Alan; Barrett, Tristan; Giganti, Francesco; Graham, John D.; Haslam, Phil; Johnston, Edward; Kastner, Christof; Kirkham, Alex; Lipton, Alexandra; McNeill, Alan; Moniz, Larissa S.; Moore, Caroline M.; Nabi, Ghulam; Padhani, Anwar R.; Parker, Chris; Patel, Amit R.; Pursey, Jacqueline; Richenberg, Jonathan; Staffurth, John; Meulen, Jan van der; Walls, Darren; Punwani, Shonit

doi:10.1111/bju.14361

Cited by 117 publications

(101 citation statements)

References 66 publications

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“…DWI-derived apparent diffusion coefficient (ADC) maps can provide a quantitative measure of the degree of restricted diffusion, with a number of studies showing that these values correlate inversely to Gleason grade [7][8][9]. Whilst potentially attractive as a surrogate marker of tumour aggressiveness, absolute ADC values can vary depending on the choice and number of b values selected and thus current guidelines caution against the use of quantitative ADC measurements [10][11][12]. Another potential source of error is the reproducibility of the test itself, which may cause particular problems in the assessment of response to treatment and determining meaningful change in patients on active surveillance.…”

Section: Introductionmentioning

confidence: 99%

Repeatability of diffusion-weighted MRI of the prostate using whole lesion ADC values, skew and histogram analysis

Barrett

Lawrence

Priest

et al. 2019

European Journal of Radiology

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To investigate the repeatability of diffusion-weighted imaging parameter including ADC-derived histogram values in prostate cancer. Methods: 10 patients with prostate cancer were prospectively recruited to a retest cohort. 3 T diffusion-weighted MRI of the prostate was acquired consecutively with patient getting off the scanner between studies. Prostatectomy-histopathology defined tumour regions-of-interest were outlined on ADC maps and diffusionweighted metrics including histograms were calculated. The coefficient of reproducibility (CoR) and Bland-Altman plots were used to assess repeatability. Results: 10 th centile, 90 th centile, and median ADC showed good repeatability with mean difference ranging from-0.005 to-0.025 × 10 3 mm 2 s-1 , and CoR ranging from 0.271-0.294 × 10 3 mm 2 s-1 of scan 1 mean). Two measures of heterogeneity and simplified texture, IQR and mean local range, had only moderate repeatability. IQR had a mean difference of-0.032 × 10 3 mm 2 s-1 between scans with CoR 0.181 × 10 3 mm 2 s-1 (56% of scan 1 mean). Mean local range had a mean difference-0.008 × 10 3 mm 2 s-1 between scans (37% of scan 1 mean). Bland-Altman plots showed good repeatability for test and re-test analysis for median, percentile and mean range values. All ADC values had good reliability regardless of whether the tumour border was included in quantitative analysis. ADC histogram skew had poor repeatability, CoR 0.78 × 10 3 mm 2 s-1 (373% of scan 1 mean). Conclusion: 10 th and 90 th centile ADC demonstrated sufficient repeatability for clinical use. However, more advanced measures of heterogeneity such as histogram skew, IQR, or mean local range may be limited by their repeatability.

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Section: Introductionmentioning

confidence: 99%

Repeatability of diffusion-weighted MRI of the prostate using whole lesion ADC values, skew and histogram analysis

Barrett

Lawrence

Priest

et al. 2019

European Journal of Radiology

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“…In our study population, this would have resulted in a 20% decrease in the number of biopsies performed, and only 4% of significant cancers would have escaped diagnosis. If slightly different criteria suggested by other authors were applied to our cohort (i.e., PIRADS = 3 and PSAD < 0.15) [14,16,17], it would result in a 50% reduction in the number of biopsies but would also miss 21% of significant cancers. We speculate that the discrepancy between this finding and those reported in other papers might be explained by the performance of the mpMRI [3,18,19].…”

Section: Discussionmentioning

confidence: 99%

Use of Prostate Specific Antigen Density Combined with Multiparametric Magnetic Resonance Imaging Improves Triage for Prostate Biopsy

et al. 2019

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Background: Multi-parametric magnetic resonance imaging (mpMRI)-directed biopsy for prostate cancer (PC) diagnosis improves the detection of clinically significant prostate cancer (CSPC) and decreases the rate of over-diagnosis of insignificant disease. The aim of this study was to investigate the value of mpMRI combined with prostate specific antigen density (PSAD) in the decision making related to the biopsy. Methods: mpMRI and mpMRI/transrectal ultrasound fusion targeted biopsies with subsequent systematic biopsies were performed in 397 patients (223 biopsy-naïve and 174 with a previous biopsy). Detection rates of (CSPC) and insignificant PC were stratified using the PIRADS score, and the number of avoidable biopsies and missed (CSPC) were plotted against PSAD values of 0.1–0.5 ng/mL². Results: PIRADS <3 and PSAD <0.2 ng/mL² were the safest criteria for not performing a biopsy. When applied to the biopsy-naïve group, 21.5% (48/223) of the biopsies could have been avoided and 3.7% (3/82) of CSPC would have been missed. In the repeat biopsy group, 12.6% (22/174) of biopsies could have been avoided and 6.9% (4/58) of (CSPC) would have been missed. Conclusions: A combination of mpMRI and PSAD might reduce the number of biopsies performed with the cost of missing <4% of CSPC.

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“…Although this PI-RADS 3 category significant prostate cancer prevalence is low in comparison to PI-RADS category 4 (range 33-39%) and 5 lesions (range 60-73%) [37], the proportion of men with significant disease is not inconsequential. As a result, in some clinical practices, the decision to biopsy PI-RADS category 3 men is influenced by a range of clinical factors including PSA kinetics, PSA density, previous biopsy results, and patient preferences [43,44]. This argues for including multivariate prediction tools for biopsy decision-making in men with intermediate PI-RADS 3 category lesions.…”

Section: Indicating Need For Biopsymentioning

confidence: 99%

“…When over-diagnosis is a concern, for example in biopsy-naïve men with PI-RADS category 3 or small category 4 prostate lesions, biopsies using MRI-targeted and focal saturation biopsy approaches may be sufficient [39]. In men with PI-RADS category 3, lesions with low clinical suspicion on risk calculator or on PSA density will likely not be biopsied at all [44]. On the other hand, men with non suspicious MRI who are deemed to be at high risk using clinical and biochemical parameters would need to be biopsied in a systematic manner, even in the absence of definable MRI targets.…”

Section: Indicating Biopsy Extent and Approachesmentioning

confidence: 99%

Personalizing prostate cancer diagnosis with multivariate risk prediction tools: how should prostate MRI be incorporated?

Schoots

Padhani

2019

World J Urol

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Risk-based patient selection for systematic biopsy in prostate cancer diagnosis has been adopted in daily clinical practice, either by clinical judgment and PSA testing, or using multivariate risk prediction tools. The use of multivariable risk prediction tools can significantly reduce unnecessary systematic biopsies, without compromising the detection of clinically significant disease. Increasingly multi-parametric magnetic resonance imaging (MRI) is performed, not only in men with a persistent suspicion of prostate cancer after prior negative systematic biopsy, but also at initial screening before the first biopsy. The combination of MRI and multivariate risk prediction tools could potentially enhance prostate cancer diagnosis using multivariate MRI incorporated risk-based models to decide on the need for prostate MRI, but also using MRI results to adjusted risk-based models, and to guide MRI-directed biopsies. In this review, we discuss the diagnostic work-up for clinically significant prostate cancer, where the combination of MRI and multivariate risk prediction tools is integrated, and how together they can contribute to personalized diagnosis.Keywords Prostate cancer · Biopsy · Magnetic resonance imaging (MRI) · Risk stratification · Multivariate risk prediction · Risk calculator · NomogramThe following relevant activities related to the submitted work: Ivo G. Schoots is a full panel member of the EAU-ESTRO-ESUR-SIOG Guidelines on Prostate Cancer, and a full panel member of the PI-RADS Steering committee. Anwar R. Padhani is Co-Chair of the PI-RADS Steering committee.Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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National implementation of multi‐parametric magnetic resonance imaging for prostate cancer detection – recommendations from a UK consensus meeting

Abstract: Our consensus statements demonstrate a set of criteria that are required for the practical dissemination of consistently high-quality prostate mpMRI as a diagnostic test before biopsy in men at risk.

Cited by 117 publications

References 66 publications

Repeatability of diffusion-weighted MRI of the prostate using whole lesion ADC values, skew and histogram analysis

Repeatability of diffusion-weighted MRI of the prostate using whole lesion ADC values, skew and histogram analysis

Use of Prostate Specific Antigen Density Combined with Multiparametric Magnetic Resonance Imaging Improves Triage for Prostate Biopsy

Personalizing prostate cancer diagnosis with multivariate risk prediction tools: how should prostate MRI be incorporated?

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