TY - JOUR
T1 - F-18-fluorodeoxyglucose positron-emission tomography (FDG-PET)-Radiomics of metastatic lymph nodes and primary tumor in non-small cell lung cancer (NSCLC)
T2 - A prospective externally validated study
AU - Carvalho, Sara
AU - Leijenaar, Ralph T. H.
AU - Troost, Esther G. C.
AU - van Timmeren, Janna E.
AU - Oberije, Cary
AU - van Elmpt, Wouter
AU - de Geus-Oei, Lioe-Fee
AU - Bussink, Johan
AU - Lambin, Philippe
PY - 2018/3/1
Y1 - 2018/3/1
N2 - Background Lymph node stage prior to treatment is strongly related to disease progression and poor prognosis in non-small cell lung cancer (NSCLC). However, few studies have investigated metabolic imaging features derived from pre-radiotherapy F-18-fluorodeoxyglucose (FDG) positron-emission tomography (PET) of metastatic hilar/mediastinal lymph nodes (LNs). We hypothesized that these would provide complementary prognostic information to FDG-PET descriptors to only the primary tumor (tumor). Methods Two independent cohorts of 262 and 50 node-positive NSCLC patients were used for model development and validation. Image features (i.e. Radiomics) including shape and size, first order statistics, texture, and intensity-volume histograms (IVH) (http://www.radiomics.io/) were evaluated by univariable Cox regression on the development cohort. Prognostic modeling was conducted with a 10-fold cross-validated least absolute shrinkage and selection operator (LASSO), automatically selecting amongst FDG-PET-Radiomics descriptors from (1) tumor, (2) LNs or (3) both structures. Performance was assessed with the concordance-index. Development data are publicly available at www.cancerdata.org and Dryad (doi:10.5061/dryad.752153b). Results Common SUV descriptors (maximum, peak, and mean) were significantly related to overall survival when extracted from LNs, as were LN volume and tumor load (summed tumor and LNs' volumes), though this was not true for either SUV metrics or tumor's volume. Feature selection exclusively from imaging information based on FDG-PET-Radiomics, exhibited performances of (1) 0.53-external 0.54, when derived from the tumor, (2) 0.62-external 0.56 from LNs, and (3) 0.62-external 0.59 from both structures, including at least one feature from each sub-category, except IVH. Conclusion Combining imaging information based on FDG-PET-Radiomics features from tumors and LNs is desirable to achieve a higher prognostic discriminative power for NSCLC.
AB - Background Lymph node stage prior to treatment is strongly related to disease progression and poor prognosis in non-small cell lung cancer (NSCLC). However, few studies have investigated metabolic imaging features derived from pre-radiotherapy F-18-fluorodeoxyglucose (FDG) positron-emission tomography (PET) of metastatic hilar/mediastinal lymph nodes (LNs). We hypothesized that these would provide complementary prognostic information to FDG-PET descriptors to only the primary tumor (tumor). Methods Two independent cohorts of 262 and 50 node-positive NSCLC patients were used for model development and validation. Image features (i.e. Radiomics) including shape and size, first order statistics, texture, and intensity-volume histograms (IVH) (http://www.radiomics.io/) were evaluated by univariable Cox regression on the development cohort. Prognostic modeling was conducted with a 10-fold cross-validated least absolute shrinkage and selection operator (LASSO), automatically selecting amongst FDG-PET-Radiomics descriptors from (1) tumor, (2) LNs or (3) both structures. Performance was assessed with the concordance-index. Development data are publicly available at www.cancerdata.org and Dryad (doi:10.5061/dryad.752153b). Results Common SUV descriptors (maximum, peak, and mean) were significantly related to overall survival when extracted from LNs, as were LN volume and tumor load (summed tumor and LNs' volumes), though this was not true for either SUV metrics or tumor's volume. Feature selection exclusively from imaging information based on FDG-PET-Radiomics, exhibited performances of (1) 0.53-external 0.54, when derived from the tumor, (2) 0.62-external 0.56 from LNs, and (3) 0.62-external 0.59 from both structures, including at least one feature from each sub-category, except IVH. Conclusion Combining imaging information based on FDG-PET-Radiomics features from tumors and LNs is desirable to achieve a higher prognostic discriminative power for NSCLC.
KW - STANDARDIZED UPTAKE VALUE
KW - FDG-PET RADIOMICS
KW - TEXTURE ANALYSIS
KW - INTEROBSERVER VARIABILITY
KW - CT TEXTURE
KW - SURVIVAL
KW - FEATURES
KW - HETEROGENEITY
KW - INFORMATION
KW - COHORT
KW - F-18-FDG PET
KW - QUANTIFICATION
U2 - 10.1371/journal.pone.0192859
DO - 10.1371/journal.pone.0192859
M3 - Article
C2 - 29494598
SN - 1932-6203
VL - 13
JO - PLOS ONE
JF - PLOS ONE
IS - 3
M1 - e0192859
ER -