Novel Clinical Algorithm for Prenatal Monitoring of Congenital Lung Malformations

Abstract

IntroductionCongenital lung malformations (CLMs) are readily identified early in pregnancy with a variable natural history. Monitoring for lesion size and mediastinal shift (MS) is recommended following diagnosis. The purpose of this study is to propose a risk-stratified clinical algorithm for prenatal monitoring of CLM. MethodsAfter ethical approval, all fetuses with CLMs evaluated at our fetal center from January 2015 to June 2022 were retrospectively reviewed. Patient demographics, imaging characteristics, and fetal interventions were collected. Lesions were stratified by congenital lung malformation volume ratio (CVR) and the presence of MS. Descriptive statistics and receiver operating characteristic curves were employed in the analysis. ResultsWe analyzed 111 patients with a mean of 23.4 wk gestational age, a median CVR of 0.5 (interquartile range, 0.3-1.2), and MS in 76 of 111(68%) patients on initial evaluation. Among low-risk patients (CVR ≤1.1), 96% remained low-risk on final evaluation. No patients transitioned from low to high risk during the growth period. Patients with CVR >1.1 often had persistent MS (P < 0.001). Hydrops (5/111, 5%) and fetal intervention (4/111, 4%) only occurred in patients with CVR >1.1 (P < 0.001, P = 0.002) and MS (P = 0.144, P = 0.214). On receiver operating characteristic curve analysis, initial CVR >1.1 had 100% sensitivity and negative predictive value for hydrops and fetal intervention. ConclusionsCLMs with initial CVR ≤1.1 are low risk for hydrops and fetal intervention. We propose a risk-stratified algorithm for the monitoring of CLM during the growth period based on CVR. While our experience suggests that patients with CLM and MS are at higher risk, the current subjective assessment of MS is not adequately predictive. Incorporating an MS grading system may further refine risk stratification in the management of CLM.