PO-0959 Robust features selection in Apparent Diffusion Coefficient (ADC) maps of cervix cancer patients
Year: 2019
Type: conference-abstract
Abstract: ESTRO 38 histogram statistics, shape, texture and features by Wavelet and Laplacian of Gaussian filtering, were extracted from the GTV via an open-source radiomics package O-RAW that is an extension wrapper of PyRadiomics.Radiomic features were pre-selected to reduce the probability of over-fitting.If the Spearman correlation between pairs of radiomic features was bigger than 0.85, then the feature with the lower univariable association with OS was eliminated from further analysis.All the pre-selected potential radiomic features were analysed for their prognostic power using the median value in the training set as the threshold value in the univariable analysis.The logrank test was used to assessed whether the individual feature can stratify patients into high and low risk groups.The radiomic features were not normalized on any data sets.Multivariable Cox proportional hazards regression model was used to examine the association between survival and radiomic features.The concordance index (c-index) was determined to assess the models discrimination power.100 times bootstrapping was performed to compute cindex and the Wilcoxon test was used to assess radiomics signature power, compared with random (c-index = 0.5). ResultsAfter feature selection, 8 radiomic features were selected: (1) log-sigma-1-0-mm-3D_glszm_LowGrayLevelZoneEmphasis, (2) log-sigma-2-0mm-3D_gldm_DependenceVariance, (3) log-sigma-2-0mm-3D_glszm_SmallAreaLowGrayLevelEmphasis, (4) logsigma-3-0-mm-3D_gldm_DependenceEntropy, (5) wavelet-LHH_firstorder_Median, (6) wavelet-LLH_gldm_DependenceVariance, (7) original_firstorder_Maximum, and ( 8) original_glszm_SmallAreaLowGrayLevelEmphasis.The Cox regression model resulted in a c-index of 0.70 (95%CI: 0.63-0.74)on the training set and a c-index of 0.65 (95%CI: 0.56-0.68)on the validation set.The Kaplan-Meier curves of training and validation sets are shown in Figure-1.The prognostic score demonstrated significant differences in OS between risk groups in both training (X 2 17.0, p<0.001) and validation sets (X 2 5.4, p=0.02).
Source: Radiotherapy and Oncology
Institutions: Maastricht University, Maastro Clinic, University of Toronto
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $2,000
OpenAlex ID: W2945816023