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Author Ma, C. ♦ Yin, Y.
Source United States Department of Energy Office of Scientific and Technical Information
Content type Text
Language English
Subject Keyword APPLIED LIFE SCIENCES ♦ RADIATION PROTECTION AND DOSIMETRY ♦ BIOMEDICAL RADIOGRAPHY ♦ COMPUTER CODES ♦ CORRELATIONS ♦ FLUORINE 18 ♦ IMAGE PROCESSING ♦ IMAGES ♦ LUNGS ♦ NEOPLASMS ♦ PATIENTS ♦ POSITRON COMPUTED TOMOGRAPHY ♦ RADIOTHERAPY
Abstract Purpose: The purpose of this research is investigating which texture features extracted from FDG-PET images by gray-level co-occurrence matrix(GLCM) have a higher prognostic value than the other texture features. Methods: 21 non-small cell lung cancer(NSCLC) patients were approved in the study. Patients underwent 18F-FDG PET/CT scans with both pre-treatment and post-treatment. Firstly, the tumors were extracted by our house developed software. Secondly, the clinical features including the maximum SUV and tumor volume were extracted by MIM vista software, and texture features including angular second moment, contrast, inverse different moment, entropy and correlation were extracted using MATLAB.The differences can be calculated by using post-treatment features to subtract pre-treatment features. Finally, the SPSS software was used to get the Pearson correlation coefficients and Spearman rank correlation coefficients between the change ratios of texture features and change ratios of clinical features. Results: The Pearson and Spearman rank correlation coefficient between contrast and SUV maximum is 0.785 and 0.709. The P and S value between inverse difference moment and tumor volume is 0.953 and 0.942. Conclusion: This preliminary study showed that the relationships between different texture features and the same clinical feature are different. Finding the prognostic value of contrast and inverse difference moment were higher than the other three textures extracted by GLCM.
ISSN 00942405
Educational Use Research
Learning Resource Type Article
Publisher Date 2016-06-15
Publisher Place United States
Journal Medical Physics
Volume Number 43
Issue Number 6


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