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Improving digital breast tomosynthesis reading time: A pilot multi-reader, multi-case study using concurrent

Corinne Balleyguier1, Julia Arfi-Rouche1, Laurent Levy2

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European Journal of Radiology
|November 21, 2017
PubMed
Summary
This summary is machine-generated.

Computer-Aided Detection (CAD) with Digital Breast Tomosynthesis (DBT) significantly reduces radiologist reading time without compromising diagnostic performance. This study found CAD non-inferior for interpretation accuracy, enhancing efficiency in breast cancer screening.

Keywords:
Breast cancerComputer-assisted diagnosisDiagnostic imagingDigital breast tomosynthesisTime studies

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Area of Science:

  • Radiology and Medical Imaging
  • Artificial Intelligence in Healthcare
  • Breast Cancer Diagnostics

Background:

  • Digital Breast Tomosynthesis (DBT) is a key imaging modality for breast cancer detection.
  • Computer-Aided Detection (CAD) systems aim to improve the accuracy and efficiency of radiological interpretations.
  • Evaluating the combined use of CAD with DBT is crucial for optimizing breast cancer screening workflows.

Purpose of the Study:

  • To assess the impact of concurrent Computer-Aided Detection (CAD) on radiologist performance when used with Digital Breast Tomosynthesis (DBT).
  • To determine the effect of CAD on the reading time required for DBT interpretation.
  • To evaluate changes in sensitivity, specificity, and recall rates with the integration of CAD into DBT readings.

Main Methods:

  • A retrospective, crossover study design was employed, comparing DBT readings with and without CAD.
  • Six radiologists interpreted 80 DBT cases, including 23 malignant lesions, using both standard DBT and CAD-enhanced DBT.
  • Performance was evaluated using Area Under the Receiver Operating Characteristic Curve (AUC), sensitivity, specificity, recall rate, and reading time, analyzed via multi-reader, multi-case (MRMC) methods.

Main Results:

  • Concurrent CAD demonstrated non-inferiority in overall interpretation performance, with average AUCs of 0.854 without CAD and 0.850 with CAD.
  • A significant average reduction of 23.5% in reading time was observed when using CAD with DBT.
  • Per-patient sensitivity remained unchanged, while per-lesion sensitivity showed a slight improvement with CAD; specificity and recall rates were largely similar.

Conclusions:

  • The integration of Computer-Aided Detection (CAD) with Digital Breast Tomosynthesis (DBT) leads to faster interpretation times for radiologists.
  • Radiologist performance in terms of sensitivity, specificity, and overall accuracy (AUC) is maintained when using CAD concurrently with DBT.
  • CAD-enhanced DBT offers a promising approach to improve the efficiency of breast cancer screening without sacrificing diagnostic quality.