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Publication Detail
Zone-specific logistic regression models improve classification of prostate cancer on multi-parametric MRI
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Article
  • Authors:
    Dikaios N, Alkalbani J, Abd-Alazeez M, Sidhu H, Kirkham A, Ahmed H, Emberton M, Freeman A, Halligan S, Taylor S, Atkinson D, Punwani S
  • Publisher:
    Springer Verlag
  • Publication date:
    14/02/2015
  • Journal:
    European Radiology
  • Status:
    Published
  • Print ISSN:
    1432-1084
  • Keywords:
    Magnetic Resonance Imaging, Prostatic Neoplasms, Diagnosis, Computer Assisted, Logistic Models
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 transperinealtemplate- prostate-mapping biopsy. PZ and TZ uni/multivariate 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 contrastenhanced 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.
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