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Lung adenocarcinoma: development of nomograms based on PET/CT images for prediction of epidermal growth factor receptor mutation status and subtypes.
Huang, Lele; Cao, Yuntai; Zhou, Fei; Li, Jicheng; Ren, Jialiang; Zhang, Guojin; Luo, Yongjun; Liu, Jiangyan; He, Jiangping; Zhou, Junlin.
Affiliation
  • Huang L; Department of Radiology.
  • Cao Y; Department of Nuclear Medicine, Lanzhou University Second Hospital.
  • Zhou F; Second Clinical School, Lanzhou University.
  • Li J; Key Laboratory of Medical Imaging of Gansu Province.
  • Ren J; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou.
  • Zhang G; Department of Radiology, Affiliated Hospital of Qinghai University, Xining.
  • Luo Y; School of information Science and Engineering, Gansu University of Chinese Medicine.
  • Liu J; Department of Nuclear Medicine, Lanzhou University Second Hospital.
  • He J; School of Public Health, Lanzhou University, Lanzhou.
  • Zhou J; Department of Pharmaceuticals Diagnosis, GE Healthcare, Beijing.
Nucl Med Commun ; 43(3): 310-322, 2022 Mar 01.
Article de En | MEDLINE | ID: mdl-34954763
ABSTRACT

OBJECTIVE:

To develop nomograms that combine clinical characteristics, computed tomographic (CT) features and 18F-fluorodeoxyglucose PET (18F-FDG PET) metabolic parameters for individual prediction of epidermal growth factor receptor (EGFR) mutation status and exon 19 deletion mutation and exon 21 point mutation (21 L858R) subtypes in lung adenocarcinoma.

METHODS:

In total 124 lung adenocarcinoma patients who underwent EGFR mutation testing and whole-body 18F-FDG PET/CT were enrolled. Each patient's clinical characteristics (age, sex, smoking history, etc.), CT features (size, location, margins, etc.) and four metabolic parameters (SUVmax, SUVmean, MTV and TLG) were recorded and analyzed. Logistic regression analyses were performed to screen for significant predictors of EGFR mutation status and subtypes, and these predictors were presented as easy-to-use nomograms.

RESULTS:

According to the results of multiple regression analysis, three nomograms for individualized prediction of EGFR mutation status and subtypes were constructed. The area under curve values of three nomograms were 0.852 (95% CI, 0.783-0.920), 0.857 (95% CI, 0.778-0.937) and 0.893 (95% CI, 0.819-0.968) of EGFR mutation vs. wild-type, 19 deletion mutation vs. wild-type and 21 L858R vs. wild-type, respectively. Only calcification showed significant differences between the EGFR 19 deletion and 21 L858R mutations.

CONCLUSION:

EGFR 21 L858R mutation was more likely to be nonsolid texture with air bronchograms and pleural retraction on CT images. And they were more likely to be associated with lower FDG metabolic activity compared with those wild-types. The sex difference was mainly caused by the 19 deletion mutation, and calcification was more frequent in them.
Sujet(s)

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Tomographie par émission de positons couplée à la tomodensitométrie Type d'étude: Prognostic_studies / Risk_factors_studies Langue: En Journal: Nucl Med Commun Année: 2022 Type de document: Article

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Tomographie par émission de positons couplée à la tomodensitométrie Type d'étude: Prognostic_studies / Risk_factors_studies Langue: En Journal: Nucl Med Commun Année: 2022 Type de document: Article
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