StayCurrentMD · quantitative ct imaging analysis to predict Pathology features in patients with a Congenital Pulmonary Airway Malformation
Article1 min read·Published Oct 2021Older

quantitative ct imaging analysis to predict Pathology features in patients with a Congenital Pulmonary Airway Malformation

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Article · Oct 2021 · 1 min read

In brief

In brief

Study of 33 CPAM patients demonstrates quantitative CT imaging can predict histopathological features: smaller lesions correlate with inflammation risk while larger lesions with parenchymal hyperdensity predict mucinous proliferation and potential malignant transformation to adenocarcinoma in situ.

Written by the GCMD Library team from the article.

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%vs38%) 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.

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