共 43 条
Automatic Coronary Artery Calcium Scoring on Radiotherapy Planning CT Scans of Breast Cancer Patients: Reproducibility and Association with Traditional Cardiovascular Risk Factors
被引:35
|作者:
Gernaat, Sofie A. M.
[1
]
Isgum, Ivana
[2
]
de Vos, Bob D.
[2
]
Takx, Richard A. P.
[3
]
Young-Afat, Danny A.
[1
]
Rijnberg, Noor
[4
]
Grobbee, Diederick E.
[1
]
van der Graaf, Yolanda
[1
]
de Jong, Pim A.
[3
]
Leiner, Tim
[3
]
van den Bongard, Desiree H. J.
[5
]
Pignol, Jean-Philippe
[6
]
Verkooijen, Helena M.
[7
]
机构:
[1] Univ Med Ctr Utrecht, Dept Epidemiol, Julius Ctr, Utrecht, Netherlands
[2] Univ Med Ctr Utrecht, Image Sci Inst, Utrecht, Netherlands
[3] Univ Med Ctr Utrecht, Dept Radiol, Utrecht, Netherlands
[4] Acad Med Ctr, Devis Internal Med, Amsterdam, Netherlands
[5] Univ Med Ctr Utrecht, Dept Radiat Oncol, Utrecht, Netherlands
[6] Erasmus MC, Dept Radiat Oncol, Rotterdam, Netherlands
[7] Univ Med Ctr Utrecht, Imaging Div, Utrecht, Netherlands
来源:
PLOS ONE
|
2016年
/
11卷
/
12期
关键词:
ALL-CAUSE MORTALITY;
HEART-DISEASE;
VALVE CALCIFICATIONS;
PROGNOSTIC VALUE;
EVENTS;
PROGRESSION;
PREDICTION;
AGREEMENT;
MDCT;
D O I:
10.1371/journal.pone.0167925
中图分类号:
O [数理科学和化学];
P [天文学、地球科学];
Q [生物科学];
N [自然科学总论];
学科分类号:
07 ;
0710 ;
09 ;
摘要:
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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