Baloescu Cristiana, Chen Alvin, Varasteh Alexander, Hall Jane, Toporek Grzegorz, Patil Shubham, McNamara Robert L, Raju Balasundar, Moore Christopher L
Department of Emergency Medicine, Yale University School of Medicine, 464 Congress Avenue, Suite 260, New Haven, Connecticut, 06519, USA.
Philips Research Americas, 222 Jacobs Street, Cambridge, MA, 02141, USA.
Ultrasound J. 2024 Sep 16;16(1):42. doi: 10.1186/s13089-024-00391-4.
Ultrasound can detect fluid in the alveolar and interstitial spaces of the lung using the presence of artifacts known as B-lines. The aim of this study was to determine whether a deep learning algorithm generated B-line severity score correlated with pulmonary congestion and disease severity based on clinical assessment (as identified by composite congestion score and Rothman index) and to evaluate changes in the score with treatment. Patients suspected of congestive heart failure underwent daily ultrasonography. Eight lung zones (right and left anterior/lateral and superior/inferior) were scanned using a tablet ultrasound system with a phased-array probe. Mixed effects modeling explored the association between average B-line score and the composite congestion score, and average B-line score and Rothman index, respectively. Covariates tested included patient and exam level data (sex, age, presence of selected comorbidities, baseline sodium and hemoglobin, creatinine, vital signs, oxygen delivery amount and delivery method, diuretic dose).
Analysis included 110 unique subjects (3379 clips). B-line severity score was significantly associated with the composite congestion score, with a coefficient of 0.7 (95% CI 0.1-1.2 p = 0.02), but was not significantly associated with the Rothman index.
Use of this technology may allow clinicians with limited ultrasound experience to determine an objective measure of B-line burden.
超声可利用被称为B线的伪像检测肺内肺泡和间质间隙中的液体。本研究的目的是确定深度学习算法生成的B线严重程度评分是否与基于临床评估（由综合充血评分和罗斯曼指数确定）的肺充血和疾病严重程度相关，并评估治疗后该评分的变化。疑似充血性心力衰竭的患者每天接受超声检查。使用配备相控阵探头的平板超声系统扫描八个肺区（右和左前/外侧以及上/下）。混合效应模型分别探讨了平均B线评分与综合充血评分以及平均B线评分与罗斯曼指数之间的关联。测试的协变量包括患者和检查层面的数据（性别、年龄、选定合并症的存在情况、基线钠和血红蛋白、肌酐、生命体征、氧输送量和输送方式、利尿剂剂量）。
分析纳入了110名独特的受试者（3379段影像）。B线严重程度评分与综合充血评分显著相关，系数为0.7（95%可信区间0.1 - 1.2，p = 0.02），但与罗斯曼指数无显著关联。
使用该技术可能使超声经验有限的临床医生能够确定B线负担的客观测量值。
