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Proceedings Paper

Breast density in Saudi Arabia: intra and inter reader variability in screening mammograms assessed visually using BI-RADS and visual analogue scales
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Paper Abstract

Breast density is an important risk factor for breast cancer and has a substantial effect on the sensitivity of mammography screening. This study aimed to evaluate intra and inter reader variability of visual breast density assessment in Saudi Arabia, using the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) breast density categories (5th edition) and Visual Analogue Scales (VAS). A random sample of 102 screening mammograms from the Saudi National Breast Cancer Screening Programme (SNBCSP) was assessed twice by two breast screening consultant radiologists for intra reader variability. Inter reader variability was assessed using screening mammograms from 1132 women. Each mammogram was assessed by two readers from a pool of 11 radiologists. Inter reader variability for two mammography technologists using a sample of 75 mammograms is also reported. Intra reader variability showed radiologist A had excellent agreement for VAS [Intraclass Correlation Coefficient (ICC) = 0.95] and BI-RADS [weighted kappa (κ) = 0.88], radiologist B had lower but still excellent agreement for VAS [ICC= 0.88] and substantial agreement for BI-RADS [κ = 0.71]. Inter reader variability between radiologists showed overall moderate agreement for BI-RADS [κ =0.61] while VAS had excellent agreement [ICC=0.89]. Results of inter reader agreement between two mammography technologists was fair using BI-RADS [κ= 0.35] and moderate using VAS [ICC=0.41]. In conclusion, agreement in breast density assessment by radiologists in the Saudi breast screening programme is acceptable. Mammography technologists showed lower agreement for both methods. Training is essential to increase reader agreement, double reading is also important in such population based breast cancer screening programmes.

Paper Details

Date Published: 16 March 2020
PDF: 8 pages
Proc. SPIE 11316, Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment, 113160H (16 March 2020); doi: 10.1117/12.2548758
Show Author Affiliations
Areej S. Aloufi, Univ. of Manchester (United Kingdom)
King Saud Univ. (Saudi Arabia)
Abdulrahman AlNaeem, King Fahad Medical City (Saudi Arabia)
Abeer Almousa, King Fahad Medical City (Saudi Arabia)
Khaled Alzimami, Univ. of Manchester (United Kingdom)
Abdulrahman Alfuraih, Univ. of Manchester (United Kingdom)
Bader Alshahrani, King Khalid Univ. Hospital (Saudi Arabia)
Mohammed Zayed, King Khalid Univ. Hospital (Saudi Arabia)
Taghrid AlMashouq, King Fahad Medical City (Saudi Arabia)
Saud Alnasser, King Khalid Univ. Hospital (Saudi Arabia)
Khera Aldossari, King Khalid Univ. Hospital (Saudi Arabia)
Mona Alomrani, King Khalid Univ. Hospital (Saudi Arabia)
Iman Alzahrani, King Fahad Medical City (Saudi Arabia)
Elaine F. Harkness, Univ. of Manchester (United Kingdom)
Susan Astley, Univ. of Manchester (United Kingdom)


Published in SPIE Proceedings Vol. 11316:
Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment
Frank W. Samuelson; Sian Taylor-Phillips, Editor(s)

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