Quantitative CT imaging analysis to predict pathology features in patients with a congenital pulmonary airway malformation

Sergei M Hermelijn; Maarten J Mackenbach; Cathy van Horik; Pierluigi Ciet; Janina L Wolf; Jan H von der Thüsen; René M H Wijnen; Harm A W M Tiddens; J Marco Schnater

doi:10.1016/j.jpedsurg.2021.10.008

Quantitative CT imaging analysis to predict pathology features in patients with a congenital pulmonary airway malformation

J Pediatr Surg. 2022 Aug;57(8):1567-1572. doi: 10.1016/j.jpedsurg.2021.10.008. Epub 2021 Oct 14.

Authors

Sergei M Hermelijn¹, Maarten J Mackenbach², Cathy van Horik¹, Pierluigi Ciet³, Janina L Wolf⁴, Jan H von der Thüsen⁴, René M H Wijnen¹, Harm A W M Tiddens³, J Marco Schnater⁵

Affiliations

¹ Department of Pediatric Surgery, Erasmus Medical Center, Sophia Children's Hospital, Molewaterplein 40. 3015 GD Rotterdam, Mailing address: Postbus 2060, Rotterdam 3000 CB, the Netherlands.
² Department of Pediatric Metabolic Diseases, Erasmus Medical Center, Sophia Children's Hospital, Rotterdam, the Netherlands.
³ Department of Pediatric Pulmonology, Erasmus Medical Center, Sophia Children's Hospital, Rotterdam, the Netherlands; Department of Radiology, Erasmus University Medical Center, Rotterdam, the Netherlands.
⁴ Department of Pathology, Erasmus University Medical Center, Rotterdam, the Netherlands.
⁵ Department of Pediatric Surgery, Erasmus Medical Center, Sophia Children's Hospital, Molewaterplein 40. 3015 GD Rotterdam, Mailing address: Postbus 2060, Rotterdam 3000 CB, the Netherlands. Electronic address: j.schnater@erasmusmc.nl.

PMID: 34809963
DOI: 10.1016/j.jpedsurg.2021.10.008

Abstract

Background: Risk for infection and potential malignant degeneration are the most common arguments for resecting asymptomatic Congenital Pulmonary Airway Malformations (CPAM). We aimed to investigate if CT- imaging characteristics can be used to predict histopathological features, by using an objective quantitative CT scoring method.

Methods: Archival CPAM tissue samples were histologically re-assessed and patients who had a pre-operative volumetric CT-scan were included. Lung disease was quantified using the newly-developed congenital lung abnormality quantification(CLAQ) scoring method and obtained percentages were used to predict histopathological signs of inflammation and presence of mucinous proliferation (MP). Because MP is presumed a precursor for mucinous adenocarcinoma in situ (AIS) this method was also used to compare CT-scans of patients with AIS to those with only CPAM.

Results: Thirty-three CPAM patients were included of which 13(39%) had histological signs of inflammation and 8(24%) had a MP. Patients with inflammation had a significantly smaller lesion (14% vs 38%) while those with MP had more extensive disease (54%vs17%). Patients with AIS had a significantly smaller lesion compared to CPAM patients (5%vs29%). Significant predictors for inflammation were smaller lesion size and percentage hypodensity within lesions while a larger lesion size and percentage parenchymal hyperdensity (solid lung tissue components) were predictors for MP as well as AIS.

Conclusions: Smaller CPAM lesions may be more susceptible to inflammation while larger lesions may be associated with the presence of MP. Parenchymal hyperdensity is found as a predictor for MP as well as AIS and should therefore elicit more extensive gross sampling.

Level of evidence: Level III.

Keywords: Computed tomography; Congenital cystic adenomatoid malformation; Congenital pulmonary airway malformation; Mucinous adenocarcinoma; Pathology.

MeSH terms

Cystic Adenomatoid Malformation of Lung, Congenital* / surgery
Humans
Inflammation
Lung / diagnostic imaging
Respiratory System Abnormalities* / diagnostic imaging
Tomography, X-Ray Computed