肺部超声在新生儿呼吸窘迫综合征中的诊断价值及应用OA

Lung ultrasound(LUS)is a non-ionizing radiation medical imaging technique widely used in clinical practice.The diagnostic sensitivity and specificity in neonatal respiratory distress syndrome(NRDS)have already been cofirmed by multiple studies.The scoring system based on B-line scores and the extent of pulmonary consolidation enables NRDS patients to be observed on demand to predicts the risk of adverse complications such as ventilator-associated pneumonia and bronchopulmonary dysplasia(BPD),providing important references for clinical decision-making.However,the detection of deep-seated lesions is limited by air-filled alveoli,rib shadows,and scapular obstruction,potentially leading to missed diagnoses and restricted clinical application.With the rapid advancement of artificial intelligence technology,the integration of AI-assisted diagnostic systems with LUS holds promise for overcoming the physical limitations of traditional LUS,significantly enhancing the accuracy and timeliness of NRDS diagnosis.This paper reviews the progress in lung ultrasound technology for the diagnosis of NRDS,disease severity assessment,guidance of pulmonary surfactant therapy,and prediction of adverse complications.