Development of a nomogram combining clinical staging with 18F-FDG PET/CT image features in non-small-cell lung cancer stage I–III
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Our goal was to develop a nomogram by exploiting intratumour heterogeneity on CT and PET images from routine 18F-FDG PET/CT acquisitions to identify patients with the poorest prognosis.
This retrospective study included 116 patients with NSCLC stage I, II or III and with staging 18F-FDG PET/CT imaging. Primary tumour volumes were delineated using the FLAB algorithm and 3D Slicer™ on PET and CT images, respectively. PET and CT heterogeneities were quantified using texture analysis. The reproducibility of the CT features was assessed on a separate test–retest dataset. The stratification power of the PET/CT features was evaluated using the Kaplan-Meier method and the log-rank test. The best standard metric (functional volume) was combined with the least redundant and most prognostic PET/CT heterogeneity features to build the nomogram.
PET entropy and CT zone percentage had the highest complementary values with clinical stage and functional volume. The nomogram improved stratification amongst patients with stage II and III disease, allowing identification of patients with the poorest prognosis (clinical stage III, large tumour volume, high PET heterogeneity and low CT heterogeneity).
Intratumour heterogeneity quantified using textural features on both CT and PET images from routine staging 18F-FDG PET/CT acquisitions can be used to create a nomogram with higher stratification power than staging alone.
KeywordsPET/CT Textural features Heterogeneity Prognosis NSCLC
Compliance with ethical standards
This work received a French Government support granted to the CominLabs excellence laboratory and managed by the National Research Agency in the “Investing for the Future” program under reference ANR-10-LABX-07-01, and support from the city of Brest.
Conflicts of interest
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the principles of the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. For this retrospective study formal consent is not required.
- 5.Hatt M, Majdoub M, Vallières M, Tixier F, Le Rest CC, Groheux D, et al. 18F-FDG PET uptake characterization through texture analysis: investigating the complementary nature of heterogeneity and functional tumor volume in a multi-cancer site patient cohort. J Nucl Med. 2015;56:38–44.CrossRefPubMedGoogle Scholar
- 7.Pyka T, Bundschuh RA, Andratschke N, Mayer B, Specht HM, Papp L, et al. Textural features in pre-treatment [F18]-FDG-PET/CT are correlated with risk of local recurrence and disease-specific survival in early stage NSCLC patients receiving primary stereotactic radiation therapy. Radiat Oncol. 2015;10:100.CrossRefPubMedPubMedCentralGoogle Scholar
- 19.Arens AI, Troost EG, Hoeben BA, Grootjans W, Lee JA, Grégoire V, et al. Semiautomatic methods for segmentation of the proliferative tumour volume on sequential FLT PET/CT images in head and neck carcinomas and their relation to clinical outcome. Eur J Nucl Med Mol Imaging. 2014;41:915–24.CrossRefPubMedGoogle Scholar
- 26.Dancey CP, Reidy J. Statistics without maths for psychology. 5th ed. Harlow: Prentice Hall; 2011.Google Scholar
- 28.Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Statist Soc B. 1995;57:289–300.Google Scholar