OBJECTIVE: The purpose of this article is to determine the influence of chest wall composition on image quality in cardiac CT. MATERIALS AND METHODS: A retrospective study of 100 consecutive patients referred for CT coronary artery calcium assessment was performed. Image noise (Hounsfield units) was measured by prescribing a region of interest in the descending thoracic aorta. Image noise was correlated with conventional patient biometric parameters, including body weight, body mass index (BMI), and anteroposterior and lateral thoracic diameters, and with novel patient biometric parameters, including total chest wall soft tissue, chest wall fat, and chest wall muscle and bone. The linear correlation coefficient was used to indicate the strength of the association. RESULTS: A strong correlation was noted between BMI and image noise in men (r = 0.66), but the strongest relationships were observed in larger women (BMI ≥ 25), who had more chest wall fat than muscle and very strong correlations between image noise, chest wall fat (r = 0.82), and total chest wall soft tissue (r = 0.85). CONCLUSION: Chest wall composition has a significant correlation with image noise for cardiac CT. Therefore, strategies that target radiation dose reduction should incorporate adaptation to chest wall composition. These determinations become more significant given the current obesity epidemic.
OBJECTIVE: The purpose of this article is to determine the influence of chest wall composition on image quality in cardiac CT. MATERIALS AND METHODS: A retrospective study of 100 consecutive patients referred for CT coronary artery calcium assessment was performed. Image noise (Hounsfield units) was measured by prescribing a region of interest in the descending thoracic aorta. Image noise was correlated with conventional patient biometric parameters, including body weight, body mass index (BMI), and anteroposterior and lateral thoracic diameters, and with novel patient biometric parameters, including total chest wall soft tissue, chest wall fat, and chest wall muscle and bone. The linear correlation coefficient was used to indicate the strength of the association. RESULTS: A strong correlation was noted between BMI and image noise in men (r = 0.66), but the strongest relationships were observed in larger women (BMI ≥ 25), who had more chest wall fat than muscle and very strong correlations between image noise, chest wall fat (r = 0.82), and total chest wall soft tissue (r = 0.85). CONCLUSION: Chest wall composition has a significant correlation with image noise for cardiac CT. Therefore, strategies that target radiation dose reduction should incorporate adaptation to chest wall composition. These determinations become more significant given the current obesity epidemic.
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