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@article{Arshad:2019:10.1007/s00259-018-4139-4,
author = {Arshad, MA and Thornton, A and Lu, H and Tam, H and Wallitt, K and Rodgers, N and Scarsbrook, A and McDermott, G and Cook, GJ and Landau, D and Chua, S and O'Connor, R and Dickson, J and Power, DA and Barwick, TD and Rockall, A and Aboagye, EO},
doi = {10.1007/s00259-018-4139-4},
journal = {European Journal of Nuclear Medicine and Molecular Imaging},
pages = {455--466},
title = {Discovery of pre-therapy 2-deoxy-2-F-18-fluoro-D-glucose positron emission tomography-based radiomics classifiers of survival outcome in non-small-cell lung cancer patients},
url = {http://dx.doi.org/10.1007/s00259-018-4139-4},
volume = {46},
year = {2019}
}

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TY  - JOUR
AB  - PurposeThe aim of this multi-center study was to discover and validate radiomics classifiers as image-derived biomarkers for risk stratification of non-small-cell lung cancer (NSCLC).Patients and methodsPre-therapy PET scans from a total of 358 Stage I–III NSCLC patients scheduled for radiotherapy/chemo-radiotherapy acquired between October 2008 and December 2013 were included in this seven-institution study. A semi-automatic threshold method was used to segment the primary tumors. Radiomics predictive classifiers were derived from a training set of 133 scans using TexLAB v2. Least absolute shrinkage and selection operator (LASSO) regression analysis was used for data dimension reduction and radiomics feature vector (FV) discovery. Multivariable analysis was performed to establish the relationship between FV, stage and overall survival (OS). Performance of the optimal FV was tested in an independent validation set of 204 patients, and a further independent set of 21 (TESTI) patients.ResultsOf 358 patients, 249 died within the follow-up period [median 22 (range 0–85) months]. From each primary tumor, 665 three-dimensional radiomics features from each of seven gray levels were extracted. The most predictive feature vector discovered (FVX) was independent of known prognostic factors, such as stage and tumor volume, and of interest to multi-center studies, invariant to the type of PET/CT manufacturer. Using the median cut-off, FVX predicted a 14-month survival difference in the validation cohort (N = 204, p = 0.00465; HR = 1.61, 95% CI 1.16–2.24). In the TESTI cohort, a smaller cohort that presented with unusually poor survival of stage I cancers, FVX correctly indicated a lack of survival difference (N = 21, p = 0.501). In contrast to the radiomics classifier, clinically routine PET variables including SUVmax, SUVmean and SUVpeak lacked any prognostic information.ConclusionPET-based radiomics classifiers deriv
AU  - Arshad,MA
AU  - Thornton,A
AU  - Lu,H
AU  - Tam,H
AU  - Wallitt,K
AU  - Rodgers,N
AU  - Scarsbrook,A
AU  - McDermott,G
AU  - Cook,GJ
AU  - Landau,D
AU  - Chua,S
AU  - O'Connor,R
AU  - Dickson,J
AU  - Power,DA
AU  - Barwick,TD
AU  - Rockall,A
AU  - Aboagye,EO
DO  - 10.1007/s00259-018-4139-4
EP  - 466
PY  - 2019///
SN  - 0340-6997
SP  - 455
TI  - Discovery of pre-therapy 2-deoxy-2-F-18-fluoro-D-glucose positron emission tomography-based radiomics classifiers of survival outcome in non-small-cell lung cancer patients
T2  - European Journal of Nuclear Medicine and Molecular Imaging
UR  - http://dx.doi.org/10.1007/s00259-018-4139-4
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000455817600021&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://link.springer.com/article/10.1007%2Fs00259-018-4139-4
UR  - http://hdl.handle.net/10044/1/77698
VL  - 46
ER  -

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