Poster + Paper
3 April 2023 Diagnostic performance characteristics of Chinese radiologists in breast cancer detection with FFDM versus DBT images
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Conference Poster
Abstract
Introduction: Breast cancer is the most common cancer among women in China and early detection is key to reducing mortality. This study aimed to understand diagnostic performances of Chinese radiologists between FFDM (full-field digital mammography) and DBT (digital breast tomosynthesis) images in terms of lesion features and reader characteristics.
Methods: 32 Chinese radiologists read two mammogram test sets to identify cancer cases and to detect lesions. The first set was of FFDM images (60 cases, 21 cancers) and the second was of DBT images (35 cases, 15 cancers). The accuracy in cancer case detection and lesion detection of radiologists in each test set were analysed. Comparison of diagnostic performances of radiologists with different working experiences were also undertaken. Results were compared using the Wilcoxon Sign Rank and Mann-Whitney U tests.
Results: Chinese radiologists recorded higher diagnostic accuracy with FFDM than DBT for detecting certain lesion types (calcifications, architectural distortion, mixed types) and lesions ≤ 10 mm. There was no significant difference in the accuracy for cancer case detection between FFDM and DBT. Radiologists who had more than eight years working experience, read more than 60 cases per week or had no DBT training had significantly higher lesion accuracy with FFDM than DBT.
Conclusion: Chinese radiologists had higher lesion accuracy with FFDM in certain lesion types and sizes than DBT. This may be related to the lack of appropriate DBT training for radiologists in China.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jia Lin Chua, Qin Xiao, Tong Li, Yajia Gu, Melissa L. Robinson, Kriscia Tapia, Sarah Lewis, and Phuong D. Trieu "Diagnostic performance characteristics of Chinese radiologists in breast cancer detection with FFDM versus DBT images", Proc. SPIE 12467, Medical Imaging 2023: Image Perception, Observer Performance, and Technology Assessment, 1246715 (3 April 2023); https://doi.org/10.1117/12.2654277
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KEYWORDS
Digital breast tomosynthesis

Cancer

Cancer detection

Breast cancer

Education and training

Breast

Mammography

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