Radiomics Approach to Prediction of Occult Mediastinal Lymph Node Metastasis of Lung Adenocarcinoma.
AJR Am J Roentgenol
; 211(1): 109-113, 2018 Jul.
Article
em En
| MEDLINE
| ID: mdl-29667885
ABSTRACT
OBJECTIVE:
The purpose of this study was to evaluate the prognostic impact of radiomic features from CT scans in predicting occult mediastinal lymph node (LN) metastasis of lung adenocarcinoma. MATERIALS ANDMETHODS:
A total of 492 patients with lung adenocarcinoma who underwent preoperative unenhanced chest CT were enrolled in the study. A total of 300 radiomics features quantifying tumor intensity, texture, and wavelet were extracted from the segmented entire-tumor volume of interest of the primary tumor. A radiomics signature was generated by use of the relief-based feature method and the support vector machine classification method. A ROC regression curve was drawn for the predictive performance of radiomics features. Multivariate logistic regression models based on clinicopathologic and radiomics features were compared for discriminating mediastinal LN metastasis.RESULTS:
Clinical variables (sex, tumor diameter, tumor location) and predominant subtype were risk factors for pathologic mediastinal LN metastasis. The accuracy of radiomics signature for predicting mediastinal LN metastasis was 91.1% in ROC analysis (AUC, 0.972; sensitivity, 94.8%; specificity, 92%). Radiomics signature (Akaike information criterion [AIC] value, 80.9%) showed model fit superior to that of the clinicohistopathologic model (AIC value, 61.1%) for predicting mediastinal LN metastasis.CONCLUSION:
The radiomics signature of a primary tumor based on CT scans can be used for quantitative and noninvasive prediction of occult mediastinal LN metastasis of lung adenocarcinoma.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Diagnostic_studies
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Etiology_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article