Abstract
This study aimed to explore the diagnostic value of chest computed tomography (CT) based on adaptive statistical iterative reconstruction (ASiR) in the optimal weight range for children with community-acquired pneumonia (CAP) and find the differences between chest CT and ultrasound in the diagnosis of CAP. 106 children who were diagnosed as CAP were selected as the research objects. All objects underwent CT and ultrasound scans to measure the noise of CT images after iterative reconstruction and the contrast-to-noise ratio (CNR) of the thoracic aorta and the back muscles. The correlation between ASiR weight, noise, and CNR was analyzed and compared further. In addition, the differences in imaging manifestations of lung consolidation, abnormal pleural line, alveolar interstitial syndrome, and pleural effusion were observed under the ultrasound and CT scans of the patients. The sensitivity, specificity, positive predicted value (PV), and negative PV of the CT scan and ultrasound were analyzed further for the diagnosis of CAP in children. The results showed that ASiR weight and image noise were extremely and negatively correlated ( P < 0.001 ) and that CNR and ASiR weight were extremely and positively correlated ( P < 0.001 ). 40–60% of ASiR image noise was in the middle position, and the muscle space and subcutaneous fat in CT images were clearer when ASiR was at 40% and 60%. 60.38% of children were diagnosed as CAP. The proportions of children with lung consolidation, interstitial changes, pleural effusion, and atelectasis after ultrasound and CT examination were not greatly different ( P > 0.05 ). After ASiR, the sensitivity of CT in detecting the abnormal pleural line + B-line/consolidation feature was the highest, 93.75%. The results of ultrasound diagnosis were consistent with those of chest CT diagnosis ( P < 0.01 ). This indicated that the sensitivity, specificity, positive PV, and negative PV of ASiR-based chest CT in the diagnosis of CAP were close to those of ultrasound.
Highlights
Community-acquired pneumonia (CAP) in children is an infectious parenchymal inflammation of the lung accompanied by pathogen infection, which is infected outside of a health care facility and in the incubation period, and is developed during the average incubation period after hospitalization [1]
After the computed tomography (CT) scan was completed, the collected data was reconstructed with the adaptive statistical iterative reconstruction (ASiR) algorithm, and the obtained mediastinal window and thin-slice lung window images were transmitted to GE Healthcare AW4.4 software for analysis. e reconstructed image noise and contrast-to-noise ratio (CNR) were measured and calculated by the same experienced radiologist. e CNR could be calculated with the following equation: CNR ROIa − ROIb
It reveals that as the ASiR weight of the CT image increased, the image noise showed a continuous downward trend, which means that the ASiR weight had an extremely negative correlation with the image noise (r 0.8671, and P < 0.001)
Summary
Community-acquired pneumonia (CAP) in children is an infectious parenchymal inflammation of the lung accompanied by pathogen infection, which is infected outside of a health care facility and in the incubation period, and is developed during the average incubation period after hospitalization [1]. CAP is the main cause of death for children under 5 years of age and seriously threatens the life and health of children [2]. The CAP is mainly diagnosed clinically with the chest CT, chest X-ray, and lung ultrasound. The value of applying it to the diagnosis of CAP is still being confirmed, and the ultrasound results lack intuitive imaging performance [3]. Chest CT and chest X-ray examinations cause radiation and have a certain impact on the health of children
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