RESUMO
INTRODUCTION: Image noise can negatively affect the overall quality of coronary computed tomography angiography (CCTA). OBJECTIVES: The purpose of this study was to evaluate the relationship between image noise and fat volumes in the chest wall. We also aimed to compare these with other patient-specific predictors of image noise, such as body weight (BW) and body mass index (BMI). METHODS: We undertook a cross-sectional, single-center study. A tube voltage of 100â¯kV was used for patients with BW <85â¯kg and 120â¯kV for BW ≥85â¯kg. The image noise in the aortic root, single-slice fat volume (SFV) at the level of the left main coronary artery and the total fat volume of the chest (TFV) were analyzed. RESULTS: A total of 132 consecutive patients were enrolled (mean age⯱â¯standard deviation, 51⯱â¯11â¯years; 64% male). The mean image noise was 30.5⯱â¯11 Hounsfield units (HU). We found that patients with image noise >30â¯HU had significantly higher SFV (75⯱â¯33 vs. 51⯱â¯24, pâ¯<â¯0.0001) and TFV (2206⯱â¯927 vs. 1815⯱â¯737, pâ¯<â¯0.01) compared with patients having noise ≤30â¯HU, whereas BW and BMI showed no significant difference (78⯱â¯13 vs. 81⯱â¯14, pâ¯<â¯0.34) and (28.7⯱â¯4.7 vs. 26.8⯱â¯3.8, pâ¯<â¯0.19), respectively. Linear regression analysis showed that image noise has better correlation with SFV (Râ¯=â¯0.399; pâ¯<â¯0.0001); and TFV (Râ¯=â¯0, pâ¯<â¯0.009) than BMI (Râ¯=â¯0.154, pâ¯<â¯0.039) and BW (Râ¯=â¯-0.102, pâ¯=â¯0.12). CONCLUSIONS: Fat volume measurements of the chest wall can predict CCTA image noise better than other patient-specific predictors, such as BW and BMI.