Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Dec;125(3):385-391.
doi: 10.1016/j.radonc.2017.10.023. Epub 2017 Nov 6.

Post-radiochemotherapy PET radiomics in head and neck cancer - The influence of radiomics implementation on the reproducibility of local control tumor models

Affiliations
Free article

Post-radiochemotherapy PET radiomics in head and neck cancer - The influence of radiomics implementation on the reproducibility of local control tumor models

Marta Bogowicz et al. Radiother Oncol. 2017 Dec.
Free article

Abstract

Purpose: This study investigated an association of post-radiochemotherapy (RCT) PET radiomics with local tumor control in head and neck squamous cell carcinoma (HNSCC) and evaluated the models against two radiomics software implementations.

Materials and methods: 649 features, available in two radiomics implementations and based on the same definitions, were extracted from HNSCC primary tumor region in 18F-FDG PET scans 3 months post definitive RCT (training cohort n = 128, validation cohort n = 50) and compared using the intraclass correlation coefficient (ICC). Local recurrence models were trained, separately for both implementations, using principal component analysis (PCA) and the least absolute shrinkage and selection operator. The reproducibility of the concordance indexes (CI) in univariable Cox regression for features preselected in PCA and the final multivariable models was investigated using respective features from the other implementation.

Results: Only 80 PET radiomic features yielded ICC > 0.8 in the comparison between the implementations. The change of implementation caused high variability of CI in the univariable analysis. However, both final multivariable models performed equally well in the training and validation cohorts (CI > 0.7) independent of radiomics implementation.

Conclusion: The two post-RCT PET radiomic models, based on two different software implementations, were prognostic for local tumor control in HNSCC. However, 88% of the features was not reproducible between the implementations.

Keywords: Local tumor control modeling; Post-radiochemotherapy 18F-FDG PET; Radiomics; Reproducibility; Software implementation.

PubMed Disclaimer

Similar articles

Cited by

  • A Systematic Review of PET Textural Analysis and Radiomics in Cancer.
    Piñeiro-Fiel M, Moscoso A, Pubul V, Ruibal Á, Silva-Rodríguez J, Aguiar P. Piñeiro-Fiel M, et al. Diagnostics (Basel). 2021 Feb 23;11(2):380. doi: 10.3390/diagnostics11020380. Diagnostics (Basel). 2021. PMID: 33672285 Free PMC article. Review.
  • Radiomics for radiation oncologists: are we ready to go?
    Vaugier L, Ferrer L, Mengue L, Jouglar E. Vaugier L, et al. BJR Open. 2020 Mar 25;2(1):20190046. doi: 10.1259/bjro.20190046. eCollection 2020. BJR Open. 2020. PMID: 33178967 Free PMC article. Review.
  • The application of radiomics in laryngeal cancer.
    Rajgor AD, Patel S, McCulloch D, Obara B, Bacardit J, McQueen A, Aboagye E, Ali T, O'Hara J, Hamilton DW. Rajgor AD, et al. Br J Radiol. 2021 Dec;94(1128):20210499. doi: 10.1259/bjr.20210499. Epub 2021 Sep 29. Br J Radiol. 2021. PMID: 34586899 Free PMC article.
  • Multiparametric detection and outcome prediction of pancreatic cancer involving dual-energy CT, diffusion-weighted MRI, and radiomics.
    Koch V, Weitzer N, Dos Santos DP, Gruenewald LD, Mahmoudi S, Martin SS, Eichler K, Bernatz S, Gruber-Rouh T, Booz C, Hammerstingl RM, Biciusca T, Rosbach N, Gökduman A, D'Angelo T, Finkelmeier F, Yel I, Alizadeh LS, Sommer CM, Cengiz D, Vogl TJ, Albrecht MH. Koch V, et al. Cancer Imaging. 2023 Apr 18;23(1):38. doi: 10.1186/s40644-023-00549-8. Cancer Imaging. 2023. PMID: 37072856 Free PMC article.
  • The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping.
    Zwanenburg A, Vallières M, Abdalah MA, Aerts HJWL, Andrearczyk V, Apte A, Ashrafinia S, Bakas S, Beukinga RJ, Boellaard R, Bogowicz M, Boldrini L, Buvat I, Cook GJR, Davatzikos C, Depeursinge A, Desseroit MC, Dinapoli N, Dinh CV, Echegaray S, El Naqa I, Fedorov AY, Gatta R, Gillies RJ, Goh V, Götz M, Guckenberger M, Ha SM, Hatt M, Isensee F, Lambin P, Leger S, Leijenaar RTH, Lenkowicz J, Lippert F, Losnegård A, Maier-Hein KH, Morin O, Müller H, Napel S, Nioche C, Orlhac F, Pati S, Pfaehler EAG, Rahmim A, Rao AUK, Scherer J, Siddique MM, Sijtsema NM, Socarras Fernandez J, Spezi E, Steenbakkers RJHM, Tanadini-Lang S, Thorwarth D, Troost EGC, Upadhaya T, Valentini V, van Dijk LV, van Griethuysen J, van Velden FHP, Whybra P, Richter C, Löck S. Zwanenburg A, et al. Radiology. 2020 May;295(2):328-338. doi: 10.1148/radiol.2020191145. Epub 2020 Mar 10. Radiology. 2020. PMID: 32154773 Free PMC article.

MeSH terms

Substances