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Tomography
Volume 5
Issue 1
10.18383/j.tom.2018.00026
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Tomography is published by MDPI from Volume 7 Issue 1 (2021). Previous articles were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence, and they are hosted by MDPI on mdpi.com as a courtesy and upon agreement with Grapho, LLC.
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Article

[18F] FDG Positron Emission Tomography (PET) Tumor and Penumbra Imaging Features Predict Recurrence in Non–Small Cell Lung Cancer

by
Sarah A. Mattonen
1,*,
Guido A. Davidzon
2,
Shaimaa Bakr
3,
Sebastian Echegaray
1,
Ann N.C. Leung
1,
Minal Vasanawala
4,
George Horng
5,
Sandy Napel
1 and
Viswam S. Nair
1,6,7
1
James H. Clark Center, 318 Campus Drive, Room S355, Department of Radiology, Stanford University, Stanford, CA 94305, USA
2
Department of Radiology, Division of Nuclear Medicine, Stanford University, Stanford, CA, USA
3
Department of Electrical Engineering, Stanford University, Stanford, CA, USA
4
Palo Alto VA Health Care System, Palo Alto, CA, USA
5
California Pacific Medical Center, San Francisco, CA, USA
6
Pulmonary & Critical Care Medicine, Moffitt Cancer Center & Research Institute, Tampa, FL, USA
7
Morsani College of Medicine, University of South Florida, Tampa, FL, USA
*
Author to whom correspondence should be addressed.
Tomography 2019, 5(1), 145-153; https://doi.org/10.18383/j.tom.2018.00026
Submission received: 6 December 2018 / Revised: 9 January 2019 / Accepted: 12 February 2019 / Published: 1 March 2019
Versions Notes

Abstract

We identified computational imaging features on 18F-fluorodeoxyglucose positron emission tomography (PET) that predict recurrence/progression in non–small cell lung cancer (NSCLC). We retrospectively identified 291 patients with NSCLC from 2 prospectively acquired cohorts (training, n = 145; validation, n = 146). We contoured the metabolic tumor volume (MTV) on all pretreatment PET images and added a 3-dimensional penumbra region that extended outward 1 cm from the tumor surface. We generated 512 radiomics features, selected 435 features based on robustness to contour variations, and then applied randomized sparse regression (LASSO) to identify features that predicted time to recurrence in the training cohort. We built Cox proportional hazards models in the training cohort and independently evaluated the models in the validation cohort. Two features including stage and a MTV plus penumbra texture feature were selected by LASSO. Both features were significant univariate predictors, with stage being the best predictor (hazard ratio [HR] = 2.15 [95% confidence interval (CI): 1.56–2.95], p < 0.001). However, adding the MTV plus penumbra texture feature to stage significantly improved prediction (p = 0.006). This multivariate model was a significant predictor of time to recurrence in the training cohort (concordance = 0.74 [95% CI: 0.66–0.81], p < 0.001) that was validated in a separate validation cohort (concordance = 0.74 [95% CI: 0.67–0.81], p < 0.001). A combined radiomics and clinical model improved NSCLC recurrence prediction. FDG PET radiomic features may be useful biomarkers for lung cancer prognosis and add clinical utility for risk stratification.
Keywords: radiomics; lung cancer; risk stratification; recurrence; PET radiomics; lung cancer; risk stratification; recurrence; PET

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MDPI and ACS Style

Mattonen, S.A.; Davidzon, G.A.; Bakr, S.; Echegaray, S.; Leung, A.N.C.; Vasanawala, M.; Horng, G.; Napel, S.; Nair, V.S. [18F] FDG Positron Emission Tomography (PET) Tumor and Penumbra Imaging Features Predict Recurrence in Non–Small Cell Lung Cancer. Tomography 2019, 5, 145-153. https://doi.org/10.18383/j.tom.2018.00026

AMA Style

Mattonen SA, Davidzon GA, Bakr S, Echegaray S, Leung ANC, Vasanawala M, Horng G, Napel S, Nair VS. [18F] FDG Positron Emission Tomography (PET) Tumor and Penumbra Imaging Features Predict Recurrence in Non–Small Cell Lung Cancer. Tomography. 2019; 5(1):145-153. https://doi.org/10.18383/j.tom.2018.00026

Chicago/Turabian Style

Mattonen, Sarah A., Guido A. Davidzon, Shaimaa Bakr, Sebastian Echegaray, Ann N.C. Leung, Minal Vasanawala, George Horng, Sandy Napel, and Viswam S. Nair. 2019. "[18F] FDG Positron Emission Tomography (PET) Tumor and Penumbra Imaging Features Predict Recurrence in Non–Small Cell Lung Cancer" Tomography 5, no. 1: 145-153. https://doi.org/10.18383/j.tom.2018.00026

APA Style

Mattonen, S. A., Davidzon, G. A., Bakr, S., Echegaray, S., Leung, A. N. C., Vasanawala, M., Horng, G., Napel, S., & Nair, V. S. (2019). [18F] FDG Positron Emission Tomography (PET) Tumor and Penumbra Imaging Features Predict Recurrence in Non–Small Cell Lung Cancer. Tomography, 5(1), 145-153. https://doi.org/10.18383/j.tom.2018.00026

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