A simple scoring system for breast MRI interpretation: does it compensate for reader experience?

Purpose: To investigate the impact of a scoring system (Tree) on inter-reader agreement and diagnostic performance in breast MRI reading.Materials and Methods: This IRB-approved, single-centre study included 100 patients with 121 consecutive histopathologically verified lesions (52 malignant, 68 ben...

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Publicado en:European Radiology Vol. 26; no. 8; pp. 2529 - 2538
Autores principales: Marino, Maria, Clauser, Paola, Woitek, Ramona, Wengert, Georg, Kapetas, Panagiotis, Bernathova, Maria, Pinker-Domenig, Katja, Helbich, Thomas, Preidler, Klaus, Baltzer, Pascal, Marino, Maria Adele, Wengert, Georg J, Helbich, Thomas H, Baltzer, Pascal A T
Formato: diagnostic images research tables/charts Journal Article
Publicado: Springer Nature Aug2016
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Springer Nature
      place: New York, New York
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        atl: A simple scoring system for breast MRI interpretation: does it compensate for reader experience?
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          Marino, Maria
          Clauser, Paola
          Woitek, Ramona
          Wengert, Georg
          Kapetas, Panagiotis
          Bernathova, Maria
          Pinker-Domenig, Katja
          Helbich, Thomas
          Preidler, Klaus
          Baltzer, Pascal
          Marino, Maria Adele
          Wengert, Georg J
          Helbich, Thomas H
          Baltzer, Pascal A T
        affil: Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Vienna General Hospital, Floor 7F Waehringer Guertel 18-20 1090 Vienna Austria
      sug:
        subj:
          Magnetic Resonance Imaging Methods
          Breast
          Breast Neoplasms Diagnosis
          Retrospective Design
          Aged, 80 and Over
          Adult
          Probability
          Middle Age
          Aged
          ROC Curve
          Female
          Barthel Index
          Human
          Aged, 80 & over
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Aged: 65+ years
          Female
      ab: Purpose: To investigate the impact of a scoring system (Tree) on inter-reader agreement and diagnostic performance in breast MRI reading.Materials and Methods: This IRB-approved, single-centre study included 100 patients with 121 consecutive histopathologically verified lesions (52 malignant, 68 benign). Four breast radiologists with different levels of MRI experience and blinded to histopathology retrospectively evaluated all examinations. Readers independently applied two methods to classify breast lesions: BI-RADS and Tree. BI-RADS provides a reporting lexicon that is empirically translated into likelihoods of malignancy; Tree is a scoring system that results in a diagnostic category. Readings were compared by ROC analysis and kappa statistics.Results: Inter-reader agreement was substantial to almost perfect (kappa: 0.643-0.896) for Tree and moderate (kappa: 0.455-0.657) for BI-RADS. Diagnostic performance using Tree (AUC: 0.889-0.943) was similar to BI-RADS (AUC: 0.872-0.953). Less experienced radiologists achieved AUC: improvements up to 4.7 % using Tree (P-values: 0.042-0.698); an expert's performance did not change (P = 0.526). The least experienced reader improved in specificity using Tree (16 %, P = 0.001). No further sensitivity and specificity differences were found (P > 0.1).Conclusion: The Tree scoring system improves inter-reader agreement and achieves a diagnostic performance similar to that of BI-RADS. Less experienced radiologists, in particular, benefit from Tree.Key Points: • The Tree scoring system shows high diagnostic accuracy in mass and non-mass lesions. • The Tree scoring system reduces inter-reader variability related to reader experience. • The Tree scoring system improves diagnostic accuracy in non-expert readers.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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