Literature DB >> 32447116

Radiographic patterns of symptomatic radiation pneumonitis in lung cancer patients: Imaging predictors for clinical severity and outcome.

Richard Thomas1, Yu-Hui Chen2, Hiroto Hatabu3, Raymond H Mak4, Mizuki Nishino5.   

Abstract

OBJECTIVE: Investigate the spectrum of radiographic patterns of radiation pneumonitis (RP) in lung cancer patients and identify imaging markers for high-grade RP and RP-related death.
METHODS: Eighty-two patients with lung cancer treated with conventional chest radiotherapy who had symptomatic RP were identified from the radiation oncology database. The imaging features of RP were studied for association with high-grade RP (Grade ≥3) and RP-related death (Grade 5).
RESULTS: RP was Grade 2 in 60 (73%), Grade 3 in 15 (18%), and Grade 5 in 7 patients (9%). Lower performance status (p = 0.04), squamous cell histology (p = 0.03), and FEV1 ≤ 2 (p = 0.009) were associated with high-grade pneumonitis. Older age (p = 0.03) and squamous cell histology (p = 0.03) were associated with RP-related death. The CT findings included ground-glass and reticular opacities in all patients, with traction bronchiectasis in 77 (94%) and consolidation in 74 (90%). The most common radiographic pattern of RP was cryptogenic organizing pneumonia (COP) pattern (n = 54), followed by acute interstitial pneumonia (AIP)/acute respiratory distress syndrome (ARDS) pattern (n = 10). Higher extent of lung involvement, diffuse distribution, and AIP/ARDS pattern were associated with high-grade pneumonitis and RP-related death. AIP/ARDS pattern was a significant factor for high-grade pneumonitis (OR:12.62, p = 0.01) in multivariable analyses adjusting for clinical variables.
CONCLUSION: COP pattern was the most common radiographic pattern for symptomatic RP in lung cancer patients. AIP/ARDS pattern was significantly associated with high-grade RP and RP-related deaths, and was an independent marker for high-grade RP. The recognition of the radiographic patterns of RP can help to effectively contribute to patient management.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Computed tomography; Imaging; Lung cancer; Pneumonitis; Radiation

Mesh:

Year:  2020        PMID: 32447116      PMCID: PMC7316126          DOI: 10.1016/j.lungcan.2020.03.023

Source DB:  PubMed          Journal:  Lung Cancer        ISSN: 0169-5002            Impact factor:   5.705


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