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Predicting recurrence of non-small cell lung cancer based on mean computed tomography value

BACKGROUND: The aim of this study was to assess the ability of using mean computed tomography (mCT) values to predict non-small cell lung cancer (NSCLC) tumor recurrence. METHODS: A retrospective study was conducted on 494 patients with stage IA NSCLC. Receiver operating characteristics analysis was...

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Detalles Bibliográficos
Autores principales: Tamura, Masaya, Matsumoto, Isao, Tanaka, Yusuke, Saito, Daisuke, Yoshida, Shuhei, Takata, Munehisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8117299/
https://www.ncbi.nlm.nih.gov/pubmed/33980268
http://dx.doi.org/10.1186/s13019-021-01476-0
Descripción
Sumario:BACKGROUND: The aim of this study was to assess the ability of using mean computed tomography (mCT) values to predict non-small cell lung cancer (NSCLC) tumor recurrence. METHODS: A retrospective study was conducted on 494 patients with stage IA NSCLC. Receiver operating characteristics analysis was used to assess the ability to use mCT value, C/T ratio, tumor size, and SUV to predict tumor recurrence. Multiple logistic regression analyses were performed to determine the independent variables for the prediction of tumor recurrence. RESULTS: The m-CT values were − 213.7 ± 10.2 Hounsfield Units (HU) for the recurrence group and − 594.1 ± 11.6 HU for the non-recurrence group (p < 0.0001). Recurrence occurred in 45 patients (9.1%). The tumor recurrence group was strongly associated with a high CT attenuation value, high C/T ratio, large solid tumor size, and SUV. The diagnostic value of mCT value was more accurate than the C/T ratio, excluding the pure ground-glass opacity and pure solid (0 < C/T ratio < 100) groups. The SUV and mCT are independent predictive factors of tumor recurrence. CONCLUSIONS: The evaluation of mCT values was useful for predicting recurrence after the limited resection of small-sized NSCLC, and may potentially contribute to the selection of suitable treatment strategies.