Ms. Reham Altokhais Profile

Reham Altokhais

at Univ of Manchester

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Publications (2)

Proceedings Article | 29 March 2024 Presentation + Paper

Contrast enhanced mammography (CEM): is experience necessary? an inter and intra-reader agreement study for lesion classification and breast density

Reham Altokhais, Riham Eiada, Nuha Khoumais, Leena Zeitouni, Deema Abunayyan, Abdulrahman Alfuraih, Bandar Alghamdi, Reem Alghamdi, Elaine Harkness, Susan Astley

Proceedings Volume 12929, 129290K (2024) https://doi.org/10.1117/12.3005562

KEYWORDS: Breast density, Mammography, Magnetic resonance imaging, Radiology, Neodymium, Breast, Breast imaging, Correlation coefficients, Breast cancer, Visualization

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The aim of this study is to measure reader agreement for i) lesion classification and ii) breast density in Contrast Enhanced Mammography (CEM). Methods: Two experienced and two inexperienced CEM readers reported 60 examinations. Kappa was used to assess inter-reader agreement between experienced and inexperienced readers for lesion classification (benign/malignant) and breast density (dense/non-dense). Weighted kappa was used to assess agreement for BI-RADS categories (1-5) and BI-RADS density (A-D). Intraclass correlation coefficient (ICC) measured agreement for breast density using Visual Analog scale (VAS). Intra-reader agreement for one experienced and one inexperienced reader was measured after a three month interval. Results: Agreement between experienced readers was substantial (κ=0.66) for benign/malignant, and moderate (κ=0.57) for BI-RADS categories. Agreement for inexperienced readers was moderate for benign/malignant and BI-RADS categories (κ=0.52, κ=0.47 respectively). Breast density (dense/non-dense) agreement was almost perfect for experienced readers (κ=0.83) and substantial for BI-RADS (κ=0.70). Inexperienced reader agreement was moderate for dense/non-dense (κ=0.50) and BI-RADS (κ=0.49). ICC for VAS was moderate for experienced (ICC=0.60) and good (ICC=0.84) for inexperienced readers. Intra-reader agreement for benign/malignant classification was almost perfect for both experienced and inexperienced readers respectively (κ=0.83, κ=0.91). Conclusion: Experienced readers showed substantial agreement for lesion classification and almost perfect agreement for breast density. While inexperienced reader agreement was moderate for both lesion classification and breast density, their agreement for VAS was higher than experienced readers, suggesting that CEM may have a short learning curve and that radiologists could potentially be trained for CEM interpretation, which would help its implementation in other clinical practices in Saudi Arabia.

Proceedings Article | 4 April 2022 Presentation + Paper

Breast density distribution among the Saudi screening population and correlation between radiologist visual assessment and two automated methods

Areej Aloufi, Abdulrahman AlNaeem, Abeer Almousa, Mehreen Malik, Amani Hashem, Fatina Altahan, Mahmoud Elsharkawi, Manal ElMahdy, Reham Altokhais, Sara Alsultan, Rasha Sahloul, Khalid Alzimami, Steven Squires, Elaine Harkness, Susan Astley

Proceedings Volume 12035, 120350L (2022) https://doi.org/10.1117/12.2611894

KEYWORDS: Breast, Visualization, Mammography, Breast cancer, Tissues, Cancer, Imaging systems, Breast imaging, Statistical analysis, Reliability

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