Multiparametric magnetic resonance imaging of the prostate with computer-aided detection: experienced observer performance study

Valentina Giannini, Simone Mazzetti, Enrico Armando, Silvia Carabalona, Filippo Russo, Alessandro Giacobbe, Giovanni Muto, Daniele Regge

Research output: Contribution to journalArticlepeer-review

Abstract

Objectives: To compare the performance of experienced readers in detecting prostate cancer (PCa) using likelihood maps generated by a CAD system with that of unassisted interpretation of multiparametric magnetic resonance imaging (mp-MRI). Methods: Three experienced radiologists reviewed mp-MRI prostate cases twice. First, readers observed CAD marks on a likelihood map and classified as positive those suspicious for cancer. After 6 weeks, radiologists interpreted mp-MRI examinations unassisted, using their favourite protocol. Sensitivity, specificity, reading time and interobserver variability were compared for the two reading paradigms. Results: The dataset comprised 89 subjects of whom 35 with at least one significant PCa. Sensitivity was 80.9% (95% CI 72.1–88.0%) and 87.6% (95% CI 79.8–93.2; p = 0.105) for unassisted and CAD paradigm respectively. Sensitivity was higher with CAD for lesions with GS > 6 (91.3% vs 81.2%; p = 0.046) or diameter ≥10 mm (95.0% vs 80.0%; p = 0.006). Specificity was not affected by CAD. The average reading time with CAD was significantly lower (220 s vs 60 s; p < 0.001). Conclusions: Experienced readers using likelihood maps generated by a CAD scheme can detect more patients with ≥10 mm PCa lesions than unassisted MRI interpretation; overall reporting time is shorter. To gain more insight into CAD–human interaction, different reading paradigms should be investigated. Key points: • With CAD, sensitivity increases in patients with prostate tumours ≥10 mm and/or GS > 6. • CAD significantly reduces reporting time of multiparametric MRI. • When using CAD, a marginal increase of inter-reader agreement was observed.

Original languageEnglish
Pages (from-to)4200-4208
Number of pages9
JournalEuropean Radiology
Volume27
Issue number10
DOIs
Publication statusPublished - Oct 1 2017

Keywords

  • Computer-aided detection
  • Diagnostic performance
  • Magnetic resonance imaging
  • Observer study
  • Prostate cancer

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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