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Diagnostic accuracy of imaging compared to histology in congenital lung malformations

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López-Díaz M, Antón-Pacheco JL, Gallego-Herrero C, Enguita-Vals A, Cano-Novillo I, Morante-Valverde R, Galindo-Izquierdo A. Diagnostic accuracy of imaging compared to histology in congenital lung malformations. An Pediatr (Engl Ed). 2023 Nov;99(5):304-311. doi: 10.1016/j.anpede.2023.10.002. Epub 2023 Oct 20. PMID: 37867012.

Abstract

Introduction The aim of this study was to evaluate the accuracy of imaging tests (prenatal ultrasound [US] and postnatal computed tomography [CT]) in comparison to histology for diagnosis of congenital lung malformations (CLMs). Material and methods Retrospective study of patients with a prenatal diagnosis of CLM whose postnatal follow-up included thoracic CT scan and histological examination of the lesion. We collected data on demographic variables, gestational age at diagnosis, US findings and the history of multiple gestation. We used the kappa coefficient to determine the level of agreement between the findings of prenatal US and postnatal tests (CT and histology).We analysed paired data on the size of the lesion, its location and the presence or absence of systemic arterial vascularization. Results The sample included 56 patients with 57 lesions. The mean gestational age at diagnosis was 22.42 weeks (SD, 3.94) and 57% were male. Malformations most frequently involved the left lung and the lower lobes. The agreement between CT and histology in the detection of cystic lesions was moderate (κ = 0.55) but stronger compared to the agreement between US and histology (κ = 0.10). The agreement between CT and histology was substantial (κ = 0.66) in the detection of systemic vascularization of the lesion and stronger compared to the agreement between US and histology. Both imaging methods were highly accurate in the identification of the location of the pulmonary lesions. Conclusions postnatal CT offers a substantial concordance with histological findings, especially in the detection of systemic vascularization, and an accurate prediction of the anatomy of the lesion.

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