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Automated mammographic density measurement using Quantra™: comparison with the Royal Australian and New Zealand College of Radiology synoptic scale.

Inez YeoJudith AkwoErnest U Ekpo
Published in: Journal of medical imaging (Bellingham, Wash.) (2020)
Purpose: This technology evaluation study assesses the limits of agreement between the mammographic density (MD) measurement of Quantra™ from different breasts and mammographic views and its agreement with the Royal Australian and New Zealand College of Radiologists (RANZCR) synoptic scale. Approach: MD of 800 women was assessed by Quantra™ and seven radiologists using the RANZCR synoptic scale. Bland-Altman analysis was used to assess the limits of agreement between Quantra™ MD measures from both breasts and mammographic views. The agreement between Quantra™ and the RANZCR synoptic scale was assessed using weighted kappa ( K w ). The receiver operating characteristics area under the curve (AUC) was used to assess the performance of Quantra™ in reproducing RANZCR MD ratings. Results: There was no significant bias in the mean MD of Quantra™ from both breasts: left versus right craniocaudal (CC) views ( B = - 0.14 ; p = 0.36 ) and right versus left mediolateral oblique (MLO) ( B = - 0.021 ; p = 0.18 ). However, MD measures from the same breast but different views showed significant bias: right CC versus right MLO ( B = 0.064 ; p < 0.0001 ) and left CC versus left MLO ( B = 0.56 ; p < 0.0001 ). Quantra™ demonstrated substantial agreement with the RANZCR synoptic scale on four- and two-category scales ( K w = 0.62 ; 0.59 to 0.66 and 0.76; 0.72 to 0.81, respectively). Quantra™ better reproduced the RANZCR synoptic scale on a two-category scale ( AUC = 0.88 ; 0.84 to 0.91) than a four-category scale ( AUC = 0.62 ; 0.58 to 0.67 to 0.78; 0.74 to 0.82). Conclusions: Quantra™ reproduces MD classification using the RANZCR synoptic scale on a two-category scale and should help in identification of women with dense breasts who may need adjunctive imaging for early detection of breast cancer.
Keyphrases
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  • magnetic resonance
  • magnetic resonance imaging
  • deep learning
  • high throughput
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  • breast cancer risk
  • photodynamic therapy
  • nuclear factor