Dados do Trabalho
Título
The value of PET-CT in patients with pulmonary fibrosis
Introdução
ABSTRACT
Introduction and objective: to assess whether PET-CT can contribute to the differentiation between pulmonary fibrosis patterns and, consequently, assist non-invasively in the diagnosis of idiopathic pulmonary fibrosis.
Casuística e Métodos
Material and methods: retrospective single center study, including 42 PET-CT exams of oncologic patients that also had a clinical diagnosis of pulmonary fibrosis, with a tomographic pattern of usual interstitial pneumonia (UIP) or non-specific interstitial pneumonia (NSIP). The exams were assessed in a qualitative way regarding the presence or absence of F-FDG pulmonary uptake, and in a semi-quantitative way determining the SUV (Standardized Uptake Value) in the fibrous lung area.
Resultados
Results and discussion: NSIP was observed in 31 exams (73.8%) and UIP in 11 (26.19%). There was a higher uptake of F-FDG in fibrous lung areas regarding healthy lung areas, both for NSIP and for UIP, indicating that fibrous tissue has avidity for glucose. Qualitative and semi-quantitative analyzes showed a significant statistical difference (p <0.001) in pulmonary uptake between patients with NSIP and UIP, with higher uptake in most patients with NSIP.
Conclusões
Conclusions: SUV analysis in PET-CT exams can contribute to the differentiation between UIP and NSIP patterns, with direct measurement of maximum SUV (SUVmax ) of fibrous area being the best performance parameter. This result contributes to the clinical practice, since the overlapping of imaging characteristics can make this clinical task challenging, leading to the need for invasive procedures, such as a surgical lung biopsy.
Palavras Chave
Key-words: Pulmonary fibrosis. Usual interstitial pneumonia. Non-specific interstitial pneumonia. PET-CT.
Área
Alunos de Medicina / Ligas radiológicas (trabalhos de extensão acadêmica)
Instituições
UFCSPA - Rio Grande do Sul - Brasil
Autores
DANIARA ASSIS, Yana Pallaoro, Bruno Hochhegger, Carlos Nin, Luana Posser, Roseana Chaves, Dalton Guimarães, Bruno Takara, Ana Carolina Silva