Key result
Automatic CAC scoring on radiotherapy CTs shows high reliability versus manual scoring for CVD risk.
Why the study?
Coronary artery calcium is a strong predictor of cardiovascular disease risk, but reproducibility of automatic CAC scoring on radiotherapy planning CT scans and its association with traditional cardiovascular risk factors in breast cancer patients is unclear.
Does automatic CAC scoring on radiotherapy planning CT scans provide reproducible CVD risk categorization compared to manual scoring in breast cancer patients?
Observational (n=561)
Single-blind
No
Does automatic CAC scoring on radiotherapy planning CT scans provide reproducible CVD risk categorization compared to manual scoring in breast cancer patients?
Effect estimate: kappa 0.80 (95% CI 0.74-0.87)
Automatic CAC scoring on radiotherapy planning CT scans is a reliable method to assess CVD risk, identifying elevated risk in 24% of breast cancer patients, many of whom lack traditional risk factors.
May enable routine CVD risk assessment on radiotherapy planning CTs in breast cancer patients; leaves open prospective outcome validation.
OBJECTIVES: Coronary artery calcium (CAC) is a strong and independent predictor of cardiovascular disease (CVD) risk. This study assesses reproducibility of automatic CAC scoring on radiotherapy planning computed tomography (CT) scans of breast cancer patients, and examines its association with traditional cardiovascular risk factors. METHODS: This study included 561 breast cancer patients undergoing radiotherapy between 2013 and 2015. CAC was automatically scored with an algorithm using supervised pattern recognition, expressed as Agatston scores and categorized into five categories (0, 1-10, 11-100, 101-400, >400). Reproducibility between automatic and manual expert scoring was assessed in 79 patients with automatically determined CAC above zero and 84 randomly selected patients without automatically determined CAC. Interscan reproducibility of automatic scoring was assessed in 294 patients having received two scans (82% on the same day). Association between CAC and CVD risk factors was assessed in 36 patients with CAC scores >100, 72 randomly selected patients with scores 1-100, and 72 randomly selected patients without CAC. Reliability was assessed with linearly weighted kappa and agreement with proportional agreement. RESULTS: 134 out of 561 (24%) patients had a CAC score above zero. Reliability of CVD risk categorization between automatic and manual scoring was 0.80 (95% Confidence Interval (CI): 0.74-0.87), and slightly higher for scans with breath-hold. Agreement was 0.79 (95% CI: 0.72-0.85). Interscan reliability was 0.61 (95% CI: 0.50-0.72) with an agreement of 0.84 (95% CI: 0.80-0.89). Ten out of 36 (27.8%) patients with CAC scores above 100 did not have other cardiovascular risk factors. CONCLUSIONS: Automatic CAC scoring on radiotherapy planning CT scans is a reliable method to assess CVD risk based on Agatston scores. One in four breast cancer patients planned for radiotherapy have elevated CAC score. One in three patients with high CAC scores don't have other CVD risk factors and wouldn't have been identified as high risk.
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Gernaat et al. (2016) conducted an observational in Breast cancer (n=561). Automatic coronary artery calcium (CAC) scoring vs. Manual expert CAC scoring was evaluated on Reliability of cardiovascular disease risk categorization between automatic and manual scoring (kappa 0.80, 95% CI 0.74-0.87). Automatic coronary artery calcium scoring on radiotherapy planning CT scans demonstrated high reliability (kappa 0.80) compared to manual scoring for assessing cardiovascular disease risk categories in breast cancer patients.
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