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01-09-2015 | Magnetic Resonance

Zone-specific logistic regression models improve classification of prostate cancer on multi-parametric MRI

Authors: Nikolaos Dikaios, Jokha Alkalbani, Mohamed Abd-Alazeez, Harbir Singh Sidhu, Alex Kirkham, Hashim U. Ahmed, Mark Emberton, Alex Freeman, Steve Halligan, Stuart Taylor, David Atkinson, Shonit Punwani

Published in: European Radiology | Issue 9/2015

Abstract

Objectives

To assess the interchangeability of zone-specific (peripheral-zone (PZ) and transition-zone (TZ)) multiparametric-MRI (mp-MRI) logistic-regression (LR) models for classification of prostate cancer.

Methods

Two hundred and thirty-one patients (70 TZ training-cohort; 76 PZ training-cohort; 85 TZ temporal validation-cohort) underwent mp-MRI and transperineal-template-prostate-mapping biopsy. PZ and TZ uni/multi-variate mp-MRI LR-models for classification of significant cancer (any cancer-core-length (CCL) with Gleason > 3 + 3 or any grade with CCL ≥ 4 mm) were derived from the respective cohorts and validated within the same zone by leave-one-out analysis. Inter-zonal performance was tested by applying TZ models to the PZ training-cohort and vice-versa. Classification performance of TZ models for TZ cancer was further assessed in the TZ validation-cohort. ROC area-under-curve (ROC-AUC) analysis was used to compare models.

Results

The univariate parameters with the best classification performance were the normalised T2 signal (T2nSI) within the TZ (ROC-AUC = 0.77) and normalized early contrast-enhanced T1 signal (DCE-nSI) within the PZ (ROC-AUC = 0.79). Performance was not significantly improved by bi-variate/tri-variate modelling. PZ models that contained DCE-nSI performed poorly in classification of TZ cancer. The TZ model based solely on maximum-enhancement poorly classified PZ cancer.

Conclusion

LR-models dependent on DCE-MRI parameters alone are not interchangable between prostatic zones; however, models based exclusively on T2 and/or ADC are more robust for inter-zonal application.

Key points

• The ADC and T2-nSI of benign/cancer PZ are higher than benign/cancer TZ.

• DCE parameters are significantly different between benign PZ and TZ, but not between cancerous PZ and TZ.

• Diagnostic models containing contrast enhancement parameters have reduced performance when applied across zones.

Prostate cancer: diagnosis and treatment. NICE clinical guideline 175 Issued: January 2014 guidance.nice.org.uk/cg175

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Title: Zone-specific logistic regression models improve classification of prostate cancer on multi-parametric MRI
Authors: Nikolaos Dikaios
Jokha Alkalbani
Mohamed Abd-Alazeez
Harbir Singh Sidhu
Alex Kirkham
Hashim U. Ahmed
Mark Emberton
Alex Freeman
Steve Halligan
Stuart Taylor
David Atkinson
Shonit Punwani
Publication date: 01-09-2015
Publisher: Springer Berlin Heidelberg
Published in: European Radiology / Issue 9/2015
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-015-3636-0

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Zone-specific logistic regression models improve classification of prostate cancer on multi-parametric MRI

Abstract

Objectives

Methods

Results

Conclusion

Key points

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Objectives

Methods

Results

Conclusion

Key points

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