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Prediction of epidermal growth factor receptor mutation status by textural features in stage IV lung adenocarcinoma

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Summary

Background

The purpose of this study was to assess the correlation between textural features from 18fluorodeoxyglucose positron emission tomography (18F-FDG-PET) or computed tomography (CT) and EGFR mutation status in patients with stage IV adenocarcinoma lung cancer.

Methods

In all, 71 patients who were diagnosed with stage IV adenocarcinoma lung cancer between April 2014 and August 2018 were included in this study. 18F-FDG-PET/CT scanning and EGFR mutation tests were performed before targeted molecular therapy. Textural features were extracted from manually segmented volumes of tumors, and highly dependent features were excluded. Multivariate logistic regression analysis was used to establish predictive models for detection of EGFR mutations. Receiver operating characteristic (ROC) curves were applied to evaluate areas under the curves (AUCs) of each model.

Results

Of the 71 patients, 39 (54.9%) were EGFR mutation and 32 (45.1%) showed wild-type. EGFR mutation status was significantly associated with female sex (P = 0.026). In multivariate analysis, three PET (co-occurrence contrast, intensity-size-zone low-intensity large-zone emphasis, and texture spectrum max spectrum) and two CT quantitative features (intensity-size-zone high-intensity zone emphasis and normalized co-occurrence second angular moment) were independent predictors of EGFR mutation status. The predictive model generated from combined clinical and textural features showed a better predictive value than the model from textural features alone (AUC 0.897 vs 0.864).

Conclusions

Textural features combined with clinical features could establish a model for improving the predicting power of EGFR mutation status in patients with stage IV adenocarcinoma lung cancer.

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Fig. 1
Fig. 2

Data availability

All datasets for this study are available.

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Acknowledgements

The manuscript was approved by all authors for publication. This work was financially supported by the National Natural Science Foundation of China (No. 81572970) and National Key R&D Program of China (2017YFC0107502).

Author information

Authors and Affiliations

  1. Department of Radiation Oncology, Shengli Oilfield Central Hospital, Dongying, Shandong, China

    Changbin Wang

  2. Department of Radiation Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China

    Ran Zhang

  3. Tongji University, Shanghai, China

    Ran Zhang

  4. Department of Nuclear Medicine, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China

    Xiaorong Sun

  5. Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, No. 440 Jiyan Road, Jinan, Shandong, China

    Ligang Xing

Authors
  1. Changbin Wang
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  2. Ran Zhang
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  3. Xiaorong Sun
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  4. Ligang Xing
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Contributions

CW and RZ performed the study and drafted the manuscript; XS, LX and CW designed the study and LX helped to draft the manuscript; CW and RZ helped acquire the clinical data and images; XS offered assistance for data analysis; LX evaluated data on radiation therapy. All authors read and approved the final manuscript and had full control of the data submitted for publication.

Corresponding author

Correspondence to Ligang Xing.

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Conflict of interest

C. Wang, R. Zhang, X. Sun and L. Xing declare that they have no competing interests.

Ethical standards

Due to this retrospective study, informed consent was waived. This study was authorized by the ethics committee in Shandong Cancer Hospital Affiliated to Shandong First Medical University. The database of our study had removed the patients’ identifying information.

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Wang, C., Zhang, R., Sun, X. et al. Prediction of epidermal growth factor receptor mutation status by textural features in stage IV lung adenocarcinoma. memo (2024). https://doi.org/10.1007/s12254-024-00961-1

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  • DOI: https://doi.org/10.1007/s12254-024-00961-1

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