Prognostic value of histogram analysis in advanced non-small cell lung cancer: a radiomic study
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Bluthgen Maria Virginia1, Faivre Laura2, Rosellini Silvia2, Ferrara Roberto1, Facchinetti Francesco1, Haspinger Eva1, Ferte Charles1, Ammari Samy3, Michiels Stefan2,4,5, Soria Jean-Charles1,5, Caramella Caroline3,5,* and Besse Benjamin1,5,*
1Department of Cancer Medicine, Gustave Roussy Cancer Center, 94805 Villejuif, France
2Department of Biostatistics and Epidemiology, Gustave Roussy Cancer Center, 94805 Villejuif, France
3Department of Radiology, Gustave Roussy Cancer Center, 94805 Villejuif, France
4INSERM U1018, CESP, Université Paris-Sud, Université Paris-Saclay, Villejuif, France
5Université Paris-Sud, 91400 Orsay, France
*These authors have contributed equally to this work
Besse Benjamin, email: firstname.lastname@example.org
Keywords: non-small cell lung cancer; advance; histogram analysis; texture; prognosis
Received: August 02, 2016 Accepted: June 02, 2017 Published: November 06, 2017
Introduction: Quantitative assessment of heterogeneity by histogram analysis (HA) of tumor images can potentially provide a non-invasive prognostic biomarker. We assessed the prognostic value of HA and evaluated a correlation with molecular signature.
Results: CT scans performed between July 2009 and January 2015 from 692 patients were reviewed. HA was performed on scans from 313 patients in the training dataset and 108 in the validation dataset. Median follow-up were 33.7 months [range: 1.7 - 65.5] and 29 months [range: 1.1 - 35.6] with a median overall survival (OS) of 11.7 months [95%CI: 10.7 - 13.1] and 9.5 months [95%CI: 7.9 - 12.7] respectively. Primary mass entropy in coarse texture with spatial filter 3.3 was prognostic for OS in a multivariate Cox analysis (HR: 1.3 [95%CI: 1.1 - 1.5], p=0.001). Results were not reproduced in our validation set and no correlation with molecular signature was identified.
Materials and Methods: HA using filtration-histogram method was applied to the region of interest on the primary tumor in enhanced-CT acquired as diagnostic/staging routine, from a cohort of patients with advanced non-small cell lung cancer (NSCLC) treated with platinum-based chemotherapy. The resultants parameters were prospectively applied to a validation dataset. CT scans, clinical and molecular data were retrospectively collected. Cox proportional hazard models were used for survival analysis and Wilcoxon test for correlations.
Conclusion: Primary mass entropy was significantly associated with survival in the training set but was not validated in the validation cohort, raising doubt over the reliability of published data from small cohorts.
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